From 0669d1b3cb7152c3ebc58618dd766a41705503c0 Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Thu, 25 Jun 2026 17:31:13 -0700 Subject: [PATCH 01/79] =?UTF-8?q?bump:=20version=200.1.43=20=E2=86=92=200.?= =?UTF-8?q?1.44?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- enterprise/pyproject.toml | 4 ++-- pyproject.toml | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index b032942427c..66f6aeb7abc 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm-enterprise" -version = "0.1.43" +version = "0.1.44" description = "Package for LiteLLM Enterprise features" readme = "README.md" requires-python = ">=3.9" @@ -26,7 +26,7 @@ required-version = ">=0.10.9" module-root = "" [tool.commitizen] -version = "0.1.43" +version = "0.1.44" version_files = [ "pyproject.toml:^version", "../pyproject.toml:litellm-enterprise==", diff --git a/pyproject.toml b/pyproject.toml index 6a6a47f540e..6e99d81f8f3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -63,7 +63,7 @@ proxy = [ "azure-storage-blob>=12.28.0,<13.0", "mcp>=1.26.0,<2.0", "litellm-proxy-extras==0.4.74", - "litellm-enterprise==0.1.43", + "litellm-enterprise==0.1.44", "RestrictedPython>=8.1,<9.0", "rich>=13.9.4,<14.0", "polars>=1.38.1,<2.0", From 2c8cd6ad4dc65371ac3b7f3dc58206c6120773ac Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Thu, 25 Jun 2026 17:35:56 -0700 Subject: [PATCH 02/79] uv lock --- uv.lock | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/uv.lock b/uv.lock index 917dff39e38..da44ad25715 100644 --- a/uv.lock +++ b/uv.lock @@ -9,7 +9,7 @@ resolution-markers = [ ] [options] -exclude-newer = "2026-06-22T19:05:55.080417Z" +exclude-newer = "2026-06-23T00:31:52.495979Z" exclude-newer-span = "P3D" [manifest] @@ -3597,7 +3597,7 @@ proxy-dev = [ [[package]] name = "litellm-enterprise" -version = "0.1.43" +version = "0.1.44" source = { editable = "enterprise" } [[package]] From 4a6f0dbd8c4af8eb56d0ee6a60eaf7139d051931 Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Fri, 26 Jun 2026 00:10:14 -0700 Subject: [PATCH 03/79] fix(ui): size Request Logs table columns so it scrolls instead of overflowing Tremor's Table forwards className to a wrapper div rather than the inner table element, so the table-fixed class never reached the table and it stayed table-layout: auto. Across 16 whitespace-nowrap columns that expanded the table far past the viewport Give each spend-logs column an explicit pixel size and drive the table width from getCenterTotalSize(), matching the Virtual Keys table. The shared DataTable applies this only when columns declare sizes, so the other consumers keep their existing fluid layout --- .../src/components/view_logs/columns.tsx | 16 +++++++ .../src/components/view_logs/table.test.tsx | 44 +++++++++++++++++++ .../src/components/view_logs/table.tsx | 15 ++++++- 3 files changed, 73 insertions(+), 2 deletions(-) create mode 100644 ui/litellm-dashboard/src/components/view_logs/table.test.tsx diff --git a/ui/litellm-dashboard/src/components/view_logs/columns.tsx b/ui/litellm-dashboard/src/components/view_logs/columns.tsx index 1265b8449de..aeeb31f78f3 100644 --- a/ui/litellm-dashboard/src/components/view_logs/columns.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/columns.tsx @@ -119,11 +119,13 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Time", accessorKey: "startTime", + size: 200, cell: (info: any) => , }, { header: "Type", id: "type", + size: 90, cell: (info: any) => { const row = info.row.original; const sessionCount = row.session_total_count || 1; @@ -168,6 +170,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Status", accessorKey: "metadata.status", + size: 100, cell: (info: any) => { const status = info.getValue() || "Success"; const isSuccess = status.toLowerCase() !== "failure"; @@ -186,6 +189,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Session ID", accessorKey: "session_id", + size: 160, cell: (info: any) => { const value = String(info.getValue() || ""); const onSessionClick = info.row.original.onSessionClick; @@ -207,6 +211,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Request ID", accessorKey: "request_id", + size: 160, cell: (info: any) => ( {String(info.getValue() || "")} @@ -226,6 +231,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Cost", accessorKey: "spend", + size: 110, cell: (info: any) => { const row = info.row.original; const mcpCount = row.mcp_tool_call_count || 0; @@ -258,6 +264,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Duration (s)", accessorKey: "request_duration_ms", + size: 120, cell: (info: any) => { const ms = info.getValue(); if (ms == null) return -; @@ -282,6 +289,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "TTFT (s)", accessorKey: "completionStartTime", + size: 110, cell: (info: any) => { const row = info.row.original; const completionStartTime = info.getValue(); @@ -301,6 +309,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Team Name", accessorKey: "metadata.user_api_key_team_alias", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -310,6 +319,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Hash", accessorKey: "metadata.user_api_key", + size: 160, cell: (info: any) => { const value = String(info.getValue() || "-"); const onKeyHashClick = info.row.original.onKeyHashClick; @@ -329,6 +339,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Alias", accessorKey: "metadata.user_api_key_alias", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -348,6 +359,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Model", accessorKey: "model", + size: 200, cell: (info: any) => { const row = info.row.original; const provider = row.custom_llm_provider; @@ -385,6 +397,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Tokens", accessorKey: "total_tokens", + size: 140, cell: (info: any) => { const row = info.row.original; return ( @@ -400,6 +413,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Internal User", accessorKey: "user", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -409,6 +423,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "End User", accessorKey: "end_user", + size: 140, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -419,6 +434,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Tags", accessorKey: "request_tags", + size: 150, cell: (info: any) => { const tags = info.getValue(); if (!tags || Object.keys(tags).length === 0) return "-"; diff --git a/ui/litellm-dashboard/src/components/view_logs/table.test.tsx b/ui/litellm-dashboard/src/components/view_logs/table.test.tsx new file mode 100644 index 00000000000..f88e9bd75c8 --- /dev/null +++ b/ui/litellm-dashboard/src/components/view_logs/table.test.tsx @@ -0,0 +1,44 @@ +import type { ColumnDef } from "@tanstack/react-table"; +import { render, screen } from "@testing-library/react"; +import { describe, expect, it } from "vitest"; +import { DataTable } from "./table"; + +type Row = { request_id: string; a: string; b: string }; + +const data: Row[] = [{ request_id: "r1", a: "alpha", b: "beta" }]; + +const sizedColumns: ColumnDef[] = [ + { header: "A", accessorKey: "a", size: 120 }, + { header: "B", accessorKey: "b", size: 80 }, +]; + +const unsizedColumns: ColumnDef[] = [ + { header: "A", accessorKey: "a" }, + { header: "B", accessorKey: "b" }, +]; + +describe("DataTable column sizing", () => { + it("widths the table and every cell from column sizes when columns declare them", () => { + render(); + + expect(screen.getByRole("table").style.width).toBe("200px"); + + const headers = screen.getAllByRole("columnheader"); + expect(headers.map((h) => h.style.width)).toEqual(["120px", "80px"]); + + const cells = screen.getAllByRole("cell"); + expect(cells.map((c) => c.style.width)).toEqual(["120px", "80px"]); + }); + + it("leaves cells unsized and keeps the fluid table when no column declares a size", () => { + render(); + + const table = screen.getByRole("table"); + expect(table.style.width).toBe(""); + expect(table.style.minWidth).toBe("400px"); + + for (const cell of [...screen.getAllByRole("columnheader"), ...screen.getAllByRole("cell")]) { + expect(cell.style.width).toBe(""); + } + }); +}); diff --git a/ui/litellm-dashboard/src/components/view_logs/table.tsx b/ui/litellm-dashboard/src/components/view_logs/table.tsx index 6aa349513d5..a47bf5a8e5c 100644 --- a/ui/litellm-dashboard/src/components/view_logs/table.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/table.tsx @@ -41,6 +41,7 @@ export function DataTable({ enableSorting = false, }: DataTableProps) { const supportsExpansion = !!(renderSubComponent || renderChildRows) && !!getRowCanExpand; + const hasExplicitColumnSizes = columns.some((column) => column.size !== undefined); const [sorting, setSorting] = useState([]); const table = useReactTable({ @@ -63,9 +64,14 @@ export function DataTable({ ...(supportsExpansion && { getExpandedRowModel: getExpandedRowModel() }), }); + const tableClassName = hasExplicitColumnSizes + ? "[&_td]:py-0.5 [&_th]:py-1 [&_table]:table-fixed" + : "[&_td]:py-0.5 [&_th]:py-1 table-fixed w-full box-border"; + const tableStyle = hasExplicitColumnSizes ? { width: table.getCenterTotalSize() } : { minWidth: "400px" }; + return (
- +
{table.getHeaderGroups().map((headerGroup) => ( @@ -77,6 +83,7 @@ export function DataTable({ {header.isPlaceholder ? null : ( @@ -112,7 +119,11 @@ export function DataTable({ onClick={() => onRowClick?.(row.original)} > {row.getVisibleCells().map((cell) => ( - + {flexRender(cell.column.columnDef.cell, cell.getContext())} ))} From 014754be947e60cbefa1a3ecaae0a68a05a7443f Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Fri, 26 Jun 2026 18:34:07 -0700 Subject: [PATCH 04/79] fix(ui): let dashboard main pane shrink so wide tables scroll instead of overflowing The Request Logs page pushed the whole page past the viewport horizontally. The cause was the app shell flex layout:
is a flex item, and flex items default to min-width: auto, so they refuse to shrink below their content's intrinsic width. The logs table is intrinsically ~2300px across its 16 nowrap columns, so main grew to that width and dragged the page with it; the table's own overflow-x-auto wrapper never got the chance to scroll Add min-w-0 to main so it can shrink to the available width, at which point the existing overflow-x-auto wrapper engages and the table scrolls inside its card. This applies to every dashboard page, not just logs Also drop the dead max-w-screen class on the logs container (not a real Tailwind utility, so it was a no-op), and revert the earlier column-sizing attempt which targeted table-layout rather than the actual containment problem --- .../src/app/(dashboard)/layout.tsx | 2 +- .../src/components/view_logs/columns.tsx | 16 ------- .../src/components/view_logs/index.tsx | 2 +- .../src/components/view_logs/table.test.tsx | 44 ------------------- .../src/components/view_logs/table.tsx | 15 +------ 5 files changed, 4 insertions(+), 75 deletions(-) delete mode 100644 ui/litellm-dashboard/src/components/view_logs/table.test.tsx diff --git a/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx b/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx index a5e83436888..09951dc1923 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/layout.tsx @@ -126,7 +126,7 @@ function DashboardShell({ children }: { children: React.ReactNode }) {
-
{children}
+
{children}
)} diff --git a/ui/litellm-dashboard/src/components/view_logs/columns.tsx b/ui/litellm-dashboard/src/components/view_logs/columns.tsx index aeeb31f78f3..1265b8449de 100644 --- a/ui/litellm-dashboard/src/components/view_logs/columns.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/columns.tsx @@ -119,13 +119,11 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Time", accessorKey: "startTime", - size: 200, cell: (info: any) => , }, { header: "Type", id: "type", - size: 90, cell: (info: any) => { const row = info.row.original; const sessionCount = row.session_total_count || 1; @@ -170,7 +168,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Status", accessorKey: "metadata.status", - size: 100, cell: (info: any) => { const status = info.getValue() || "Success"; const isSuccess = status.toLowerCase() !== "failure"; @@ -189,7 +186,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Session ID", accessorKey: "session_id", - size: 160, cell: (info: any) => { const value = String(info.getValue() || ""); const onSessionClick = info.row.original.onSessionClick; @@ -211,7 +207,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Request ID", accessorKey: "request_id", - size: 160, cell: (info: any) => ( {String(info.getValue() || "")} @@ -231,7 +226,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Cost", accessorKey: "spend", - size: 110, cell: (info: any) => { const row = info.row.original; const mcpCount = row.mcp_tool_call_count || 0; @@ -264,7 +258,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Duration (s)", accessorKey: "request_duration_ms", - size: 120, cell: (info: any) => { const ms = info.getValue(); if (ms == null) return -; @@ -289,7 +282,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "TTFT (s)", accessorKey: "completionStartTime", - size: 110, cell: (info: any) => { const row = info.row.original; const completionStartTime = info.getValue(); @@ -309,7 +301,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Team Name", accessorKey: "metadata.user_api_key_team_alias", - size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -319,7 +310,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Hash", accessorKey: "metadata.user_api_key", - size: 160, cell: (info: any) => { const value = String(info.getValue() || "-"); const onKeyHashClick = info.row.original.onKeyHashClick; @@ -339,7 +329,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Alias", accessorKey: "metadata.user_api_key_alias", - size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -359,7 +348,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Model", accessorKey: "model", - size: 200, cell: (info: any) => { const row = info.row.original; const provider = row.custom_llm_provider; @@ -397,7 +385,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Tokens", accessorKey: "total_tokens", - size: 140, cell: (info: any) => { const row = info.row.original; return ( @@ -413,7 +400,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Internal User", accessorKey: "user", - size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -423,7 +409,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "End User", accessorKey: "end_user", - size: 140, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -434,7 +419,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Tags", accessorKey: "request_tags", - size: 150, cell: (info: any) => { const tags = info.getValue(); if (!tags || Object.keys(tags).length === 0) return "-"; diff --git a/ui/litellm-dashboard/src/components/view_logs/index.tsx b/ui/litellm-dashboard/src/components/view_logs/index.tsx index 6c5fd03f0a0..cfe1bd6025a 100644 --- a/ui/litellm-dashboard/src/components/view_logs/index.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/index.tsx @@ -234,7 +234,7 @@ export default function SpendLogsTable({ accessToken, token, userRole, userID, p }; return ( -
+
setActiveTab(index === 0 ? "request logs" : "audit logs")}> Request Logs diff --git a/ui/litellm-dashboard/src/components/view_logs/table.test.tsx b/ui/litellm-dashboard/src/components/view_logs/table.test.tsx deleted file mode 100644 index f88e9bd75c8..00000000000 --- a/ui/litellm-dashboard/src/components/view_logs/table.test.tsx +++ /dev/null @@ -1,44 +0,0 @@ -import type { ColumnDef } from "@tanstack/react-table"; -import { render, screen } from "@testing-library/react"; -import { describe, expect, it } from "vitest"; -import { DataTable } from "./table"; - -type Row = { request_id: string; a: string; b: string }; - -const data: Row[] = [{ request_id: "r1", a: "alpha", b: "beta" }]; - -const sizedColumns: ColumnDef[] = [ - { header: "A", accessorKey: "a", size: 120 }, - { header: "B", accessorKey: "b", size: 80 }, -]; - -const unsizedColumns: ColumnDef[] = [ - { header: "A", accessorKey: "a" }, - { header: "B", accessorKey: "b" }, -]; - -describe("DataTable column sizing", () => { - it("widths the table and every cell from column sizes when columns declare them", () => { - render(); - - expect(screen.getByRole("table").style.width).toBe("200px"); - - const headers = screen.getAllByRole("columnheader"); - expect(headers.map((h) => h.style.width)).toEqual(["120px", "80px"]); - - const cells = screen.getAllByRole("cell"); - expect(cells.map((c) => c.style.width)).toEqual(["120px", "80px"]); - }); - - it("leaves cells unsized and keeps the fluid table when no column declares a size", () => { - render(); - - const table = screen.getByRole("table"); - expect(table.style.width).toBe(""); - expect(table.style.minWidth).toBe("400px"); - - for (const cell of [...screen.getAllByRole("columnheader"), ...screen.getAllByRole("cell")]) { - expect(cell.style.width).toBe(""); - } - }); -}); diff --git a/ui/litellm-dashboard/src/components/view_logs/table.tsx b/ui/litellm-dashboard/src/components/view_logs/table.tsx index a47bf5a8e5c..6aa349513d5 100644 --- a/ui/litellm-dashboard/src/components/view_logs/table.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/table.tsx @@ -41,7 +41,6 @@ export function DataTable({ enableSorting = false, }: DataTableProps) { const supportsExpansion = !!(renderSubComponent || renderChildRows) && !!getRowCanExpand; - const hasExplicitColumnSizes = columns.some((column) => column.size !== undefined); const [sorting, setSorting] = useState([]); const table = useReactTable({ @@ -64,14 +63,9 @@ export function DataTable({ ...(supportsExpansion && { getExpandedRowModel: getExpandedRowModel() }), }); - const tableClassName = hasExplicitColumnSizes - ? "[&_td]:py-0.5 [&_th]:py-1 [&_table]:table-fixed" - : "[&_td]:py-0.5 [&_th]:py-1 table-fixed w-full box-border"; - const tableStyle = hasExplicitColumnSizes ? { width: table.getCenterTotalSize() } : { minWidth: "400px" }; - return (
-
+
{table.getHeaderGroups().map((headerGroup) => ( @@ -83,7 +77,6 @@ export function DataTable({ {header.isPlaceholder ? null : ( @@ -119,11 +112,7 @@ export function DataTable({ onClick={() => onRowClick?.(row.original)} > {row.getVisibleCells().map((cell) => ( - + {flexRender(cell.column.columnDef.cell, cell.getContext())} ))} From 76be4461cad2dfe89fb2930d42eb99a65546d004 Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Fri, 26 Jun 2026 19:05:33 -0700 Subject: [PATCH 05/79] feat(ui): give Request Logs columns explicit widths and tighten the dense ones Now that the page-overflow bug is fixed by letting the main pane shrink, bring back per-column sizing purely to control widths. Columns declare explicit pixel sizes and the table derives its min-width from getCenterTotalSize(), so it stretches to fill a wide card but scrolls once the columns no longer fit. The shared DataTable applies this only when columns declare sizes, leaving the other consumers on their existing fluid layout Trim the columns that were eating horizontal space without earning it: Request ID and Key Hash drop ~30% (Key Hash now narrower than Key Alias, which is the more useful of the two), and Duration and TTFT shrink to fit their short numeric values --- .../src/components/view_logs/columns.tsx | 16 +++++++ .../src/components/view_logs/table.test.tsx | 46 +++++++++++++++++++ .../src/components/view_logs/table.tsx | 15 +++++- 3 files changed, 75 insertions(+), 2 deletions(-) create mode 100644 ui/litellm-dashboard/src/components/view_logs/table.test.tsx diff --git a/ui/litellm-dashboard/src/components/view_logs/columns.tsx b/ui/litellm-dashboard/src/components/view_logs/columns.tsx index 1265b8449de..310316d205e 100644 --- a/ui/litellm-dashboard/src/components/view_logs/columns.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/columns.tsx @@ -119,11 +119,13 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Time", accessorKey: "startTime", + size: 200, cell: (info: any) => , }, { header: "Type", id: "type", + size: 90, cell: (info: any) => { const row = info.row.original; const sessionCount = row.session_total_count || 1; @@ -168,6 +170,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Status", accessorKey: "metadata.status", + size: 100, cell: (info: any) => { const status = info.getValue() || "Success"; const isSuccess = status.toLowerCase() !== "failure"; @@ -186,6 +189,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Session ID", accessorKey: "session_id", + size: 160, cell: (info: any) => { const value = String(info.getValue() || ""); const onSessionClick = info.row.original.onSessionClick; @@ -207,6 +211,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Request ID", accessorKey: "request_id", + size: 110, cell: (info: any) => ( {String(info.getValue() || "")} @@ -226,6 +231,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Cost", accessorKey: "spend", + size: 110, cell: (info: any) => { const row = info.row.original; const mcpCount = row.mcp_tool_call_count || 0; @@ -258,6 +264,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Duration (s)", accessorKey: "request_duration_ms", + size: 90, cell: (info: any) => { const ms = info.getValue(); if (ms == null) return -; @@ -282,6 +289,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "TTFT (s)", accessorKey: "completionStartTime", + size: 80, cell: (info: any) => { const row = info.row.original; const completionStartTime = info.getValue(); @@ -301,6 +309,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Team Name", accessorKey: "metadata.user_api_key_team_alias", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -310,6 +319,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Hash", accessorKey: "metadata.user_api_key", + size: 110, cell: (info: any) => { const value = String(info.getValue() || "-"); const onKeyHashClick = info.row.original.onKeyHashClick; @@ -329,6 +339,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Key Alias", accessorKey: "metadata.user_api_key_alias", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -348,6 +359,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Model", accessorKey: "model", + size: 200, cell: (info: any) => { const row = info.row.original; const provider = row.custom_llm_provider; @@ -385,6 +397,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Tokens", accessorKey: "total_tokens", + size: 140, cell: (info: any) => { const row = info.row.original; return ( @@ -400,6 +413,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Internal User", accessorKey: "user", + size: 150, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -409,6 +423,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "End User", accessorKey: "end_user", + size: 140, cell: (info: any) => ( {String(info.getValue() || "-")} @@ -419,6 +434,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Tags", accessorKey: "request_tags", + size: 150, cell: (info: any) => { const tags = info.getValue(); if (!tags || Object.keys(tags).length === 0) return "-"; diff --git a/ui/litellm-dashboard/src/components/view_logs/table.test.tsx b/ui/litellm-dashboard/src/components/view_logs/table.test.tsx new file mode 100644 index 00000000000..da9bcef1455 --- /dev/null +++ b/ui/litellm-dashboard/src/components/view_logs/table.test.tsx @@ -0,0 +1,46 @@ +import type { ColumnDef } from "@tanstack/react-table"; +import { render, screen } from "@testing-library/react"; +import { describe, expect, it } from "vitest"; +import { DataTable } from "./table"; + +type Row = { request_id: string; a: string; b: string }; + +const data: Row[] = [{ request_id: "r1", a: "alpha", b: "beta" }]; + +const sizedColumns: ColumnDef[] = [ + { header: "A", accessorKey: "a", size: 120 }, + { header: "B", accessorKey: "b", size: 80 }, +]; + +const unsizedColumns: ColumnDef[] = [ + { header: "A", accessorKey: "a" }, + { header: "B", accessorKey: "b" }, +]; + +describe("DataTable column sizing", () => { + it("min-widths the table to the column total and sizes every cell when columns declare sizes", () => { + render(); + + const table = screen.getByRole("table"); + expect(table.style.minWidth).toBe("200px"); + expect(table.style.width).toBe(""); + + const headers = screen.getAllByRole("columnheader"); + expect(headers.map((h) => h.style.width)).toEqual(["120px", "80px"]); + + const cells = screen.getAllByRole("cell"); + expect(cells.map((c) => c.style.width)).toEqual(["120px", "80px"]); + }); + + it("leaves cells unsized and keeps the fluid table when no column declares a size", () => { + render(); + + const table = screen.getByRole("table"); + expect(table.style.width).toBe(""); + expect(table.style.minWidth).toBe("400px"); + + for (const cell of [...screen.getAllByRole("columnheader"), ...screen.getAllByRole("cell")]) { + expect(cell.style.width).toBe(""); + } + }); +}); diff --git a/ui/litellm-dashboard/src/components/view_logs/table.tsx b/ui/litellm-dashboard/src/components/view_logs/table.tsx index 6aa349513d5..4510cc9a1f0 100644 --- a/ui/litellm-dashboard/src/components/view_logs/table.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/table.tsx @@ -41,6 +41,7 @@ export function DataTable({ enableSorting = false, }: DataTableProps) { const supportsExpansion = !!(renderSubComponent || renderChildRows) && !!getRowCanExpand; + const hasExplicitColumnSizes = columns.some((column) => column.size !== undefined); const [sorting, setSorting] = useState([]); const table = useReactTable({ @@ -63,9 +64,14 @@ export function DataTable({ ...(supportsExpansion && { getExpandedRowModel: getExpandedRowModel() }), }); + const tableClassName = hasExplicitColumnSizes + ? "[&_td]:py-0.5 [&_th]:py-1 [&_table]:table-fixed" + : "[&_td]:py-0.5 [&_th]:py-1 table-fixed w-full box-border"; + const tableStyle = hasExplicitColumnSizes ? { minWidth: table.getCenterTotalSize() } : { minWidth: "400px" }; + return (
-
+
{table.getHeaderGroups().map((headerGroup) => ( @@ -77,6 +83,7 @@ export function DataTable({ {header.isPlaceholder ? null : ( @@ -112,7 +119,11 @@ export function DataTable({ onClick={() => onRowClick?.(row.original)} > {row.getVisibleCells().map((cell) => ( - + {flexRender(cell.column.columnDef.cell, cell.getContext())} ))} From 84d7a320201edc57c4ab6a293a08375909bbb3fd Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Mon, 29 Jun 2026 21:08:40 -0700 Subject: [PATCH 06/79] fix(ui): revert Duration and TTFT column widths to default The explicit 90px/80px sizes were too narrow for the Duration (s) and TTFT (s) headers once the sort arrows were factored in, cramping the header labels. Dropping the size lets these two columns fall back to the default width like before --- ui/litellm-dashboard/src/components/view_logs/columns.tsx | 2 -- 1 file changed, 2 deletions(-) diff --git a/ui/litellm-dashboard/src/components/view_logs/columns.tsx b/ui/litellm-dashboard/src/components/view_logs/columns.tsx index 310316d205e..73eecf9c01e 100644 --- a/ui/litellm-dashboard/src/components/view_logs/columns.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/columns.tsx @@ -264,7 +264,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "Duration (s)", accessorKey: "request_duration_ms", - size: 90, cell: (info: any) => { const ms = info.getValue(); if (ms == null) return -; @@ -289,7 +288,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] ) : "TTFT (s)", accessorKey: "completionStartTime", - size: 80, cell: (info: any) => { const row = info.row.original; const completionStartTime = info.getValue(); From 256b5aadfbf5168facfd1add1cfc956dce44773b Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Mon, 29 Jun 2026 21:16:59 -0700 Subject: [PATCH 07/79] fix(ui): revert Request ID width to default, tighten Session ID Drop the explicit size on Request ID so it falls back to the default width like the other reverted columns. Narrow Session ID from 160px to 120px since its truncated value needs less room --- ui/litellm-dashboard/src/components/view_logs/columns.tsx | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/ui/litellm-dashboard/src/components/view_logs/columns.tsx b/ui/litellm-dashboard/src/components/view_logs/columns.tsx index 73eecf9c01e..8de67e6ae19 100644 --- a/ui/litellm-dashboard/src/components/view_logs/columns.tsx +++ b/ui/litellm-dashboard/src/components/view_logs/columns.tsx @@ -189,7 +189,7 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Session ID", accessorKey: "session_id", - size: 160, + size: 120, cell: (info: any) => { const value = String(info.getValue() || ""); const onSessionClick = info.row.original.onSessionClick; @@ -211,7 +211,6 @@ export const createColumns = (sortProps?: LogsSortProps): ColumnDef[] { header: "Request ID", accessorKey: "request_id", - size: 110, cell: (info: any) => ( {String(info.getValue() || "")} From 70eb4e5d00c2beff458934e70c722ed8248b6d7e Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 12:34:17 +0300 Subject: [PATCH 08/79] feat(prometheus): add litellm_total_overhead_latency_metric (SDK overhead + guardrails) (#31593) litellm_overhead_latency_metric only covers the SDK wrapper window and excludes proxy guardrails. Add a histogram that sums SDK overhead plus pre/post-call guardrail durations (during-call excluded since it runs concurrently with the LLM call, alongside logging_only and MCP modes that never block the response), recorded next to the existing overhead metric with the same labels and buckets. No existing metric's value is changed. --- litellm/integrations/prometheus.py | 83 +++++- litellm/types/integrations/prometheus.py | 11 + ...est_prometheus_overhead_with_guardrails.py | 238 ++++++++++++++++++ 3 files changed, 331 insertions(+), 1 deletion(-) create mode 100644 tests/test_litellm/integrations/test_prometheus_overhead_with_guardrails.py diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index fcec551f25a..1f516e9dc93 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -49,12 +49,16 @@ from litellm.proxy._types import ( from litellm.repositories.organization_repository import OrganizationRepository from litellm.repositories.team_repository import TeamRepository from litellm.repositories.user_repository import UserRepository +from litellm.types.guardrails import GuardrailEventHooks from litellm.types.integrations.prometheus import * from litellm.types.integrations.prometheus import ( _sanitize_prometheus_label_name, _sanitize_prometheus_label_value, ) -from litellm.types.utils import StandardLoggingPayload +from litellm.types.utils import ( + StandardLoggingGuardrailInformation, + StandardLoggingPayload, +) if TYPE_CHECKING: from apscheduler.schedulers.asyncio import AsyncIOScheduler @@ -65,6 +69,8 @@ else: class PrometheusLogger(CustomLogger): # Class variables or attributes + _ADDITIVE_GUARDRAIL_MODES = frozenset((GuardrailEventHooks.pre_call.value, GuardrailEventHooks.post_call.value)) + @staticmethod def get_instance() -> Optional["PrometheusLogger"]: """Find the PrometheusLogger instance from litellm.callbacks, if registered.""" @@ -343,6 +349,14 @@ class PrometheusLogger(CustomLogger): buckets=self.latency_buckets, ) + self.litellm_overhead_with_guardrails_latency_metric = self._histogram_factory( + "litellm_overhead_with_guardrails_latency_metric", + "Total internal latency (seconds) added by LiteLLM, including " + "pre/post-call guardrails (excludes the LLM API call)", + labelnames=self.get_labels_for_metric("litellm_overhead_with_guardrails_latency_metric"), + buckets=self.latency_buckets, + ) + # Request queue time metric self.litellm_request_queue_time_metric = self._histogram_factory( "litellm_request_queue_time_seconds", @@ -1001,6 +1015,67 @@ class PrometheusLogger(CustomLogger): self._cached_metric_labels[metric_name] = filtered_labels return filtered_labels + @staticmethod + def _guardrail_is_additive(info: StandardLoggingGuardrailInformation) -> bool: + mode = info.get("guardrail_mode") + modes = mode if isinstance(mode, list) else [mode] + mode_values = frozenset( + m.value if isinstance(m, GuardrailEventHooks) else m for m in modes if isinstance(m, str) + ) + return bool(mode_values) and mode_values <= PrometheusLogger._ADDITIVE_GUARDRAIL_MODES + + @staticmethod + def _get_guardrail_overhead_seconds( + standard_logging_payload: StandardLoggingPayload, + ) -> float: + """Seconds of additive guardrail time (pre/post-call only) on the payload. + + during_call guardrails run concurrently with the LLM call, so their + wall-clock overlaps the provider call and is not additive overhead; + logging_only and MCP modes never block the user-facing response. A + guardrail counts only when every mode it carries is pre/post-call, so a + mixed list such as ["pre_call", "during_call"] is excluded. + + guardrail_information is typed as a list, but some guardrails assign a + single dict directly, so normalize that shape to a one-item list. + """ + guardrail_information = standard_logging_payload.get("guardrail_information") + entries: list[StandardLoggingGuardrailInformation] = ( + [cast("StandardLoggingGuardrailInformation", guardrail_information)] + if isinstance(guardrail_information, dict) + else guardrail_information or [] + ) + return sum( + (float(info.get("duration") or 0.0) for info in entries if PrometheusLogger._guardrail_is_additive(info)), + 0.0, + ) + + def _set_overhead_with_guardrails_metric( + self, + standard_logging_payload: StandardLoggingPayload, + enum_values: UserAPIKeyLabelValues, + label_context: Optional[PrometheusLabelFactoryContext] = None, + ) -> None: + """Record litellm_overhead_with_guardrails_latency_metric (seconds): SDK overhead + + pre/post-call guardrail time. Recorded outside the SDK-overhead gate so + guardrail-only overhead is still captured when litellm_overhead_time_ms + is 0 or absent. + """ + litellm_overhead_time_ms = standard_logging_payload["hidden_params"].get("litellm_overhead_time_ms") + guardrail_overhead_seconds = self._get_guardrail_overhead_seconds(standard_logging_payload) + if litellm_overhead_time_ms is None and guardrail_overhead_seconds <= 0: + return + labels = prometheus_label_factory( + supported_enum_labels=self.get_labels_for_metric( + metric_name="litellm_overhead_with_guardrails_latency_metric" + ), + enum_values=enum_values, + label_context=label_context, + ) + self.litellm_overhead_with_guardrails_latency_metric.labels(**labels).observe( + ((litellm_overhead_time_ms or 0.0) / 1000) + guardrail_overhead_seconds + ) + def _track_end_user_metric_series( self, metric: Any, @@ -2346,6 +2421,12 @@ class PrometheusLogger(CustomLogger): litellm_overhead_time_ms / 1000 ) # set as seconds + self._set_overhead_with_guardrails_metric( + standard_logging_payload=standard_logging_payload, + enum_values=enum_values, + label_context=label_context, + ) + if remaining_requests: """ "model_group", diff --git a/litellm/types/integrations/prometheus.py b/litellm/types/integrations/prometheus.py index 8f460b79955..fca3319254c 100644 --- a/litellm/types/integrations/prometheus.py +++ b/litellm/types/integrations/prometheus.py @@ -195,6 +195,7 @@ DEFINED_PROMETHEUS_METRICS = Literal[ "litellm_llm_api_time_to_first_token_metric", "litellm_request_total_latency_metric", "litellm_overhead_latency_metric", + "litellm_overhead_with_guardrails_latency_metric", "litellm_remaining_requests_metric", "litellm_remaining_tokens_metric", "litellm_proxy_total_requests_metric", @@ -379,6 +380,16 @@ class PrometheusMetricLabels: UserAPIKeyLabelNames.MODEL_ID.value, ] + litellm_overhead_with_guardrails_latency_metric = [ + UserAPIKeyLabelNames.MODEL_GROUP.value, + UserAPIKeyLabelNames.API_PROVIDER.value, + UserAPIKeyLabelNames.API_BASE.value, + UserAPIKeyLabelNames.v2_LITELLM_MODEL_NAME.value, + UserAPIKeyLabelNames.API_KEY_HASH.value, + UserAPIKeyLabelNames.API_KEY_ALIAS.value, + UserAPIKeyLabelNames.MODEL_ID.value, + ] + litellm_remaining_requests_metric = [ UserAPIKeyLabelNames.MODEL_GROUP.value, UserAPIKeyLabelNames.API_PROVIDER.value, diff --git a/tests/test_litellm/integrations/test_prometheus_overhead_with_guardrails.py b/tests/test_litellm/integrations/test_prometheus_overhead_with_guardrails.py new file mode 100644 index 00000000000..56c9702189e --- /dev/null +++ b/tests/test_litellm/integrations/test_prometheus_overhead_with_guardrails.py @@ -0,0 +1,238 @@ +""" +Unit tests for litellm_overhead_with_guardrails_latency_metric. + +The metric reports total internal latency LiteLLM adds around the provider +call = SDK overhead (litellm_overhead_time_ms) + pre/post-call guardrail +durations. During-call (moderation) guardrails run concurrently with the LLM +call and are excluded so they don't inflate the overhead. +""" + +from unittest.mock import MagicMock + +import pytest +from prometheus_client import REGISTRY + +from litellm.integrations.prometheus import PrometheusLogger +from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.utils import StandardLoggingPayload + + +@pytest.fixture(autouse=True) +def cleanup_prometheus_registry(): + """Clean up prometheus registry before/after each test.""" + for collector in list(REGISTRY._collector_to_names.keys()): + REGISTRY.unregister(collector) + yield + for collector in list(REGISTRY._collector_to_names.keys()): + REGISTRY.unregister(collector) + + +def test_get_guardrail_overhead_seconds_sums_pre_post_excludes_during(): + """Helper sums pre/post durations, excludes during_call, tolerates missing values.""" + payload = StandardLoggingPayload( + guardrail_information=[ + {"guardrail_mode": GuardrailEventHooks.pre_call, "duration": 0.1}, + {"guardrail_mode": GuardrailEventHooks.during_call, "duration": 0.5}, + {"guardrail_mode": GuardrailEventHooks.post_call, "duration": 0.25}, + {"guardrail_mode": GuardrailEventHooks.post_call}, # no duration -> 0 + ], + ) + # 0.1 (pre) + 0.25 (post) = 0.35; during_call 0.5 excluded; missing duration -> 0 + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.35) < 1e-6 + + +def test_get_guardrail_overhead_seconds_no_guardrails_is_zero(): + """No guardrail_information at all -> 0.0.""" + assert ( + PrometheusLogger._get_guardrail_overhead_seconds( + StandardLoggingPayload(model="gpt-4o") + ) + == 0.0 + ) + + +def test_get_guardrail_overhead_seconds_accepts_plain_string_mode(): + """guardrail_mode may arrive as a plain string after serialization.""" + payload = StandardLoggingPayload( + guardrail_information=[ + {"guardrail_mode": "pre_call", "duration": 0.2}, + {"guardrail_mode": "during_call", "duration": 0.9}, + ], + ) + # only pre_call counts; during_call excluded + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.2) < 1e-6 + + +def test_get_guardrail_overhead_seconds_excludes_list_mode_with_during_call(): + """A list-typed guardrail_mode containing during_call must be excluded. + + guardrail_mode is typed Optional[Union[GuardrailEventHooks, + List[GuardrailEventHooks], GuardrailMode]]; a list mixing in during_call is + not additive (concurrent) overhead and must not be counted. + """ + payload = StandardLoggingPayload( + guardrail_information=[ + { + "guardrail_mode": [ + GuardrailEventHooks.pre_call, + GuardrailEventHooks.during_call, + ], + "duration": 0.3, + }, + {"guardrail_mode": GuardrailEventHooks.post_call, "duration": 0.05}, + ], + ) + # the list entry mixes in during_call -> excluded; only the post_call counts + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.05) < 1e-6 + + +def test_get_guardrail_overhead_seconds_counts_pure_pre_post_list_mode(): + """A list-typed mode containing only additive (pre/post) phases is counted.""" + payload = StandardLoggingPayload( + guardrail_information=[ + {"guardrail_mode": [GuardrailEventHooks.pre_call], "duration": 0.1}, + {"guardrail_mode": ["post_call"], "duration": 0.2}, + ], + ) + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.3) < 1e-6 + + +def test_get_guardrail_overhead_seconds_excludes_logging_only_and_mcp(): + """logging_only and MCP-specific modes do not block the response -> excluded.""" + payload = StandardLoggingPayload( + guardrail_information=[ + {"guardrail_mode": GuardrailEventHooks.logging_only, "duration": 0.4}, + {"guardrail_mode": GuardrailEventHooks.pre_mcp_call, "duration": 0.3}, + {"guardrail_mode": GuardrailEventHooks.during_mcp_call, "duration": 0.2}, + {"guardrail_mode": GuardrailEventHooks.post_call, "duration": 0.05}, + ], + ) + # only the post_call guardrail is additive, user-visible overhead + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.05) < 1e-6 + + +def test_get_guardrail_overhead_seconds_ignores_dict_mode_without_error(): + """guardrail_mode may be a GuardrailMode TypedDict (an unhashable dict at + runtime, from the enterprise Mode-hook path). It must not raise TypeError and + must not be counted (the phase can't be resolved to a blocking pre/post).""" + payload = StandardLoggingPayload( + guardrail_information=[ + # GuardrailMode TypedDict -> plain dict at runtime + {"guardrail_mode": {"tags": {"default": ["pre_call"]}}, "duration": 0.3}, + {"guardrail_mode": GuardrailEventHooks.post_call, "duration": 0.05}, + ], + ) + # dict-typed mode is ignored (no TypeError); only the post_call entry counts + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.05) < 1e-6 + + +def test_get_guardrail_overhead_seconds_ignores_dict_inside_list_mode(): + """A list-typed mode containing a dict must not raise and the dict is ignored.""" + payload = StandardLoggingPayload( + guardrail_information=[ + {"guardrail_mode": [GuardrailEventHooks.pre_call, {"k": "v"}], "duration": 0.1}, + ], + ) + # the dict is ignored; remaining mode is pre_call -> counted + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.1) < 1e-6 + + +def test_get_guardrail_overhead_seconds_handles_single_dict_payload(): + """guardrail_information may be a single dict (e.g. xecguard) rather than a + list. Iterating it would yield string keys and crash the success-metrics + block, so a lone dict must be evaluated as one entry, not raise.""" + payload = StandardLoggingPayload( + guardrail_information={ + "guardrail_mode": "logging_only", + "duration": 0.7, + "guardrail_name": "xecguard", + }, + ) + # the single dict is logging_only -> excluded, and must not raise + assert PrometheusLogger._get_guardrail_overhead_seconds(payload) == 0.0 + + +def test_get_guardrail_overhead_seconds_counts_single_pre_call_dict(): + """A single pre/post-call dict (not wrapped in a list) is still counted.""" + payload = StandardLoggingPayload( + guardrail_information={"guardrail_mode": "pre_call", "duration": 0.3}, + ) + assert abs(PrometheusLogger._get_guardrail_overhead_seconds(payload) - 0.3) < 1e-6 + + +def _patch_label_factory(monkeypatch): + monkeypatch.setattr( + "litellm.integrations.prometheus.prometheus_label_factory", + lambda **kwargs: {}, + ) + + +def test_overhead_with_guardrails_recorded_when_only_guardrails_no_sdk_overhead(monkeypatch): + """Guardrail-only overhead is recorded even when SDK overhead is absent.""" + _patch_label_factory(monkeypatch) + logger = PrometheusLogger() + mock_metric = MagicMock() + logger.litellm_overhead_with_guardrails_latency_metric = mock_metric + + payload = StandardLoggingPayload( + hidden_params={}, # no litellm_overhead_time_ms + guardrail_information=[ + {"guardrail_mode": GuardrailEventHooks.post_call, "duration": 0.2} + ], + ) + logger._set_overhead_with_guardrails_metric( + payload, enum_values=MagicMock(), label_context=MagicMock() + ) + + mock_metric.labels.return_value.observe.assert_called_once() + observed = mock_metric.labels.return_value.observe.call_args[0][0] + assert abs(observed - 0.2) < 1e-6 + + +def test_overhead_with_guardrails_recorded_when_sdk_overhead_is_zero(monkeypatch): + """SDK overhead of exactly 0 (walrus-falsy) must not suppress the metric.""" + _patch_label_factory(monkeypatch) + logger = PrometheusLogger() + mock_metric = MagicMock() + logger.litellm_overhead_with_guardrails_latency_metric = mock_metric + + payload = StandardLoggingPayload( + hidden_params={"litellm_overhead_time_ms": 0.0}, + guardrail_information=[ + {"guardrail_mode": GuardrailEventHooks.pre_call, "duration": 0.1} + ], + ) + logger._set_overhead_with_guardrails_metric( + payload, enum_values=MagicMock(), label_context=MagicMock() + ) + + observed = mock_metric.labels.return_value.observe.call_args[0][0] + assert abs(observed - 0.1) < 1e-6 + + +def test_overhead_with_guardrails_skipped_when_no_overhead_and_no_guardrails(monkeypatch): + """Nothing to record -> the metric is not touched.""" + _patch_label_factory(monkeypatch) + logger = PrometheusLogger() + mock_metric = MagicMock() + logger.litellm_overhead_with_guardrails_latency_metric = mock_metric + + payload = StandardLoggingPayload(hidden_params={}) + logger._set_overhead_with_guardrails_metric( + payload, enum_values=MagicMock(), label_context=MagicMock() + ) + + mock_metric.labels.assert_not_called() + + +def test_overhead_with_guardrails_metric_is_registered(): + """The overhead-with-guardrails histogram is defined and registered on logger init.""" + logger = PrometheusLogger() + assert logger.litellm_overhead_with_guardrails_latency_metric is not None + + registered = [ + name + for name in REGISTRY._names_to_collectors + if name.startswith("litellm_overhead_with_guardrails_latency_metric") + ] + assert registered, "litellm_overhead_with_guardrails_latency_metric not registered" From 0965a4d1f4350e6991aa00ce77ef8eddc655d5fe Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 09:37:12 -0700 Subject: [PATCH 09/79] chore: shift CI lint left with an opt-in `make pre-commit` and CLAUDE.md rule (#31544) * chore: shift CI lint left with a pre-commit hook and CLAUDE.md rule Add an opt-in pre-commit hook (.githooks/pre-commit, active after make install-hooks) that runs the CI-equivalent checks against staged files: make lint for Python, prettier plus eslint for the dashboard, and a gen:api drift check for the proxy OpenAPI types. Document the same expectation in CLAUDE.md so reds surface locally instead of in CI. * fix: make `make lint` isomorphic to the CI lint job `make lint` diverged from test-linting.yml in ways that produced both false reds and false greens: its format-check ran over the whole repo (CI scopes it to changed files vs the base), its ruff-strict budget ran in absolute mode (CI runs it as a delta vs base), and it omitted the type-discipline gate entirely. Recompose `lint` to replay CI's exact sequence: diff-scoped ruff format check, whole-tree ruff check, the strict / type-discipline / basedpyright budgets as a delta resolved the same way CI resolves it (merge-base with origin/litellm_internal_staging), then circular-import and import-safety. Factor the repeated base fetch into one shared prerequisite so the chain hits the network once. Align the pre-commit hook's eslint invocation with the CI frontend-lint job (`--pass-on-unpruned-suppressions`) and fix the CLAUDE.md guidance to point at the diff-scoped frontend commands instead of the whole-folder npm scripts, which are broader than CI. * fix(githooks): make pre-commit 1:1 with CI frontend-lint, lint, and type-gen The shift-left pre-commit hook diverged from the CI jobs it claims to mirror, so a clean commit did not actually mean a green CI lint. The dashboard block only ran prettier and eslint over js/jsx/ts/tsx/mjs/cjs, but CI's frontend-lint runs prettier over a wider set (also json, css, scss, md, mdx, yml, yaml, html) and additionally gates the whole-folder eslint lint budgets via scripts/check-lint-budgets.mjs. The hook now mirrors that split and runs the budget check, so a dashboard commit that passes locally passes the job. The API-types block ran npm run gen:api without LITELLM_PYTHON, so it shelled out to the system python3 which has no litellm installed and always failed with a false 'could not regenerate API types' red. It now passes LITELLM_PYTHON="uv run --no-sync python" the way check-ui-api-types.yml does. make lint format-checks the files in origin/base...HEAD, which at pre-commit time predates the staged change, so a brand-new commit's formatting went unchecked. The Python block now also runs ruff format --check over the staged litellm files directly to cover that case, and its trigger is scoped to staged litellm/ files (the only tree CI's lint job inspects) so a tests-only or scripts-only commit skips the slow make lint instead of wasting time on a run that could not catch anything. CLAUDE.md's shift-left rule was cut off mid-sentence and understated the frontend checks; it now describes all three gates accurately and points agents at make install-hooks to run them automatically before each commit. Co-authored-by: Mateo Wang * fix(githooks): scope the API-types check to all of check-ui-api-types.yml's triggers spec_files was filtered from the staged Python files, so the gen:api drift check only fired for .py changes under litellm/proxy or litellm/types. CI's check-ui-api-types.yml triggers on any file under those directories (Prisma schema, configs) plus the generator script and the dashboard package files, so a non-Python proxy/types change could pass the hook and still fail CI. Match the workflow's full trigger set instead. * fix(pre-commit): run prisma generate before gen:api to mirror CI * refactor(githooks): run shift-left lint via on-demand make pre-commit, not an auto-firing hook The pre-commit hook ran make lint plus the dashboard eslint budgets, which are minutes of work (basedpyright over litellm/, a whole-folder eslint . pass at ~40s). Wiring that into core.hooksPath via make install-hooks meant every human commit, not just an agent's, paid that cost, which is real friction for interactive committers. Move the staged-file checks out of .githooks/ into scripts/pre_commit_lint.sh and expose them as make pre-commit, and keep .githooks/ to only the fast Conventional Commits / Branches hooks so make install-hooks no longer makes commits slow. Agents run make pre-commit right before each commit (CLAUDE.md instructs this), so the slow gates fire only for the commits an agent is making and never auto-fire for a human typing git commit. The script stays hook-compatible for anyone who still wants it to fire automatically via a symlink. Preferred this over sniffing an agent env var to auto-fire only for agents: that is fragile (misses agents when the var is unset, fires on humans when it leaks into their shell, and silently no-ops a hook a human deliberately installed), whereas an on-demand command achieves the same humans-never, agents-per-commit outcome deterministically. Co-authored-by: Mateo Wang * fix(pre-commit): run make lint last so it can't prune the proxy deps gen:api needs make lint's install-dev prerequisite runs uv sync --frozen, which prunes the proxy extras (prisma, websockets, ...) from the venv. With the Python block running first, the subsequent API-types block then failed: gen:api imports litellm.proxy.proxy_server, which needs those deps, so every litellm/proxy change (the main trigger for the API-types check) hit a false 'could not regenerate API types' red. Run the dashboard and API-types blocks before the Python block so gen:api sees an intact env; CI is unaffected because there the lint and check-ui-api-types jobs run in separate environments. Co-authored-by: Mateo Wang * fix: make CLAUDE.md more concise * fix(makefile): give make lint the CI lint env and stop it pruning the venv make lint diverged from test-linting.yml's lint job in two ways: it never generated the Prisma client (so basedpyright resolved the DB wrappers as Unknown, drifting from CI's counts), and its bare uv sync --frozen pruned the proxy extras (prisma, websockets, ...) out of the venv on every run, which broke the gen:api step that imports litellm.proxy.proxy_server and left a dev unable to run the proxy until re-syncing. Add a lint-install target that mirrors the job's environment (the proxy-dev group plus prisma generate) and runs before the checks, and make both it and install-dev use uv sync --inexact so they top up the venv instead of tearing packages out. CI is unaffected since it installs its own env per job. Because make lint no longer prunes, the pre-commit reorder that ran it last (to dodge the prune) is no longer needed, so restore the original block order. Co-authored-by: Mateo Wang * fix(makefile): drop lint-install so make lint matches CI's slimmer env test-linting.yml's lint job installs deps with a bare uv sync --frozen (default dev group only, no proxy-dev, no prisma generate), but the lint-install target chained into make lint pulled in --group proxy-dev and ran prisma generate. Because the basedpyright budget step compares head and base counts against fixed thresholds, the extra symbols and Prisma client locally resolved can shift error counts away from CI's, producing false greens or false reds on the type-check gate. Remove the lint-install target and its slot in lint. The remaining sub-targets already chain install-dev, which now uses uv sync --inexact --frozen, so the venv still isn't pruned but the installed set stays aligned with what CI sees. * ci(linting): install proxy-dev and generate prisma in lint job, matching make lint make lint now installs the proxy-dev group and generates the Prisma client so basedpyright resolves the DB wrappers; the lint job here still installed only the base env, so a local pre-commit could pass while the required CI lint failed (or vice versa). Bring this job in line, which is the same environment litellm_internal_staging's lint job already uses. Co-authored-by: Mateo Wang * fix(makefile): keep make lint on the proxy-dev + prisma env to match CI A concurrent change dropped lint-install to match what looked like CI's slim env, but test-linting.yml's lint job (and the merge ref this PR's CI actually runs) installs --group proxy-dev and generates the Prisma client. With make lint slim and CI fat, basedpyright resolves fewer symbols locally than CI, so a prisma-typed error can stay Unknown locally (green) while CI catches it (red). Restore lint-install so make lint installs the same env CI does; the previous commit also brought this PR's test-linting.yml in line with that env, so the two now match. Co-authored-by: Mateo Wang --------- Co-authored-by: Cursor Agent Co-authored-by: Mateo Wang --- CLAUDE.md | 4 +- Makefile | 62 ++++++++++++++++--- scripts/install_git_hooks.sh | 3 + scripts/pre_commit_lint.sh | 112 +++++++++++++++++++++++++++++++++++ 4 files changed, 171 insertions(+), 10 deletions(-) create mode 100755 scripts/pre_commit_lint.sh diff --git a/CLAUDE.md b/CLAUDE.md index eb32c2cd6da..cea38b8527b 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -34,7 +34,7 @@ If you ever make public-facing PR descriptions, comments, issues, commit message Don't hesitate to use values in .env to get needed API keys and other secrets, as long as you never add them to conversation history, commit them, or include them in GitHub issues / PRs -Run tests, format your code, and lint your code before each commit +Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed When you fix violations gated by `ruff-strict-budget.json` or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered baselines so the ceilings ratchet down instead of leaving stale headroom @@ -42,7 +42,7 @@ If you're trying to create a new function that relies on untyped stuff, instead If you get an LIT001 or LIT002 fail, refactor the code to follow functional programming best practices rather than introducing mutable data structures. For example, build values in one shot with comprehensions or generators wrapped in `tuple()` / `frozenset()` instead of seeding an empty `list`/`dict`/`set` and mutating it over time. Ideally `# mutable-ok` is never used; reach for it only as a genuine last resort when an immutable rewrite is truly impossible, and always pair it with a real reason -Ask to commit and push your work when you're done (or if you're confident that your code is good and works, just do it) +Commit and push your work when you're done without asking When you must use real LLM models to, for example, write e2e tests, write a QA runbook, etc., make sure to use the latest models (doesn't have to be smartest, can also be a modern small, fast one. No strong preference for smart vs fast here, just use something modern) as of the year and month of the current date. Do a web search as necessary to figure that out diff --git a/Makefile b/Makefile index 7701f54e15c..fb927148c80 100644 --- a/Makefile +++ b/Makefile @@ -8,7 +8,8 @@ lint-basedpyright lint-basedpyright-budget-update \ lint-ruff-budget lint-ruff-budget-update lint-budget-update lint-gate \ install-dev install-proxy-dev install-test-deps install-hooks \ - install-helm-unittest check-circular-imports check-import-safety + install-helm-unittest check-circular-imports check-import-safety pre-commit \ + lint-install lint-fetch-base # Default target help: @@ -20,6 +21,7 @@ help: @echo " make install-test-deps - Install the full local test environment" @echo " make install-helm-unittest - Install helm unittest plugin" @echo " make install-hooks - Install git hooks (Conventional Commits + Branches)" + @echo " make pre-commit - Run CI-equivalent lint on staged files (run before committing)" @echo " make format - Apply ruff format code formatting" @echo " make format-check - Check ruff format code formatting (matches CI)" @echo " make lint - Run all linting (Ruff, basedpyright, format check, circular imports, import safety)" @@ -56,8 +58,11 @@ info: @echo "UV: $(UV)" # Installation targets +# --inexact: sync the locked deps without pruning anything already installed, so running +# a lint/format target doesn't tear the proxy extras (prisma, websockets, ...) out from +# under a dev's venv (CI installs its own env per job, so it is unaffected by this). install-dev: - $(UV) sync --frozen + $(UV) sync --inexact --frozen install-proxy-dev: $(UV) sync --frozen --group proxy-dev --extra proxy @@ -90,6 +95,31 @@ format: install-dev format-check: install-dev cd litellm && $(UV_RUN) ruff format --check --exclude '/enterprise/' . && cd .. +# Single fetch of the PR base so the delta-based gates below share one network round +# trip instead of each re-fetching when chained from `lint`. +lint-fetch-base: + git fetch origin litellm_internal_staging + +# Mirror test-linting.yml's lint job environment: the proxy-dev group plus a generated +# Prisma client, so basedpyright resolves the same modules CI does (without the generated +# client the DB wrappers typed against it degrade to Unknown, drifting the budget from +# CI's). --inexact tops up the venv instead of pruning the proxy extras gen:api and the +# running proxy need. +lint-install: + $(UV) sync --inexact --frozen --group proxy-dev + $(UV_RUN) prisma generate --schema litellm/proxy/schema.prisma + +# Diff-scoped format check, identical to test-linting.yml's "Check ruff format" step: +# only the litellm Python files changed vs the base are checked, so a pre-existing +# format issue elsewhere doesn't block an unrelated commit. +lint-format-check-changed: install-dev lint-fetch-base + @files=$$(git diff --name-only origin/litellm_internal_staging...HEAD -- 'litellm/**/*.py' | grep -v '^litellm/enterprise/' || true); \ + if [ -z "$$files" ]; then \ + echo "No changed litellm Python files to format-check."; \ + else \ + echo "$$files" | xargs $(UV_RUN) ruff format --check --exclude '/enterprise/'; \ + fi + # Linting targets lint-ruff: install-dev cd litellm && $(UV_RUN) ruff check . && cd .. @@ -126,10 +156,14 @@ lint-ruff-FULL-dev: install-dev if [ -n "$$files" ]; then echo "$$files" | xargs $(UV_RUN) ruff check; \ else echo "No changed .py files to check."; fi -lint-basedpyright: install-dev - git fetch origin litellm_internal_staging +lint-basedpyright: install-dev lint-fetch-base ($(UV_RUN) basedpyright --outputjson || true) | $(UV_RUN) python scripts/type_check_gate.py --base origin/litellm_internal_staging +# Type-discipline budget (mutable collections / casts / type guards / kwargs / +# unexplained suppressions), the test-linting.yml step `make lint` used to omit. +lint-type-discipline: install-dev lint-fetch-base + $(UV_RUN) python scripts/type_discipline_gate.py --base origin/litellm_internal_staging + lint-basedpyright-budget-update: install-dev ($(UV_RUN) basedpyright --outputjson || true) | $(UV_RUN) python scripts/type_check_gate.py --update @@ -140,8 +174,7 @@ lint-ruff-budget: install-dev # Strict gate, invoked the same way CI does in test-linting.yml so a local pass # means the CI check will pass too. -lint-gate: install-dev - git fetch origin litellm_internal_staging +lint-gate: install-dev lint-fetch-base $(UV_RUN) python scripts/ruff_strict_gate.py --base origin/litellm_internal_staging lint-ruff-budget-update: install-dev @@ -156,12 +189,25 @@ check-circular-imports: install-dev check-import-safety: install-dev @$(UV_RUN) python -c "from litellm import *; print('[from litellm import *] OK! no issues!');" || (echo '🚨 import failed, this means you introduced unprotected imports! 🚨'; exit 1) -# Combined linting (matches test-linting.yml workflow) -lint: format-check lint-ruff lint-basedpyright check-circular-imports check-import-safety lint-ruff-budget +# Combined linting, isomorphic to test-linting.yml's lint job so a local pass means a +# green CI lint: it installs the same env (proxy-dev + generated Prisma client) and then +# runs the diff-scoped ruff format check, whole-tree ruff check, the strict-rule / +# type-discipline / basedpyright budgets as a delta vs the base, then the circular-import +# and import-safety checks. Steps that compare against the base resolve it the same way CI +# does (merge-base with origin/litellm_internal_staging). lint-install is first so the +# Prisma client exists before basedpyright runs. +lint: lint-install lint-format-check-changed lint-ruff lint-gate lint-type-discipline lint-basedpyright check-circular-imports check-import-safety # Faster linting for local development (only checks changed code) lint-dev: lint-format-changed check-circular-imports check-import-safety +# Run the gating CI checks against your staged files right before committing. Mirrors +# test-linting.yml (Python), test-litellm-ui-build.yml's frontend-lint (dashboard), and +# check-ui-api-types.yml (API-type drift), skipping any whose files you didn't stage. +# Not auto-installed as a git hook so it never slows an unrelated human commit. +pre-commit: + ./scripts/pre_commit_lint.sh + # Testing targets test: install-test-deps $(UV_RUN) pytest tests/ diff --git a/scripts/install_git_hooks.sh b/scripts/install_git_hooks.sh index 1e4e3c6de19..7ea8c3ff2e9 100755 --- a/scripts/install_git_hooks.sh +++ b/scripts/install_git_hooks.sh @@ -34,5 +34,8 @@ cat < `make lint` (test-linting.yml's lint job) +# - dashboard staged -> prettier + eslint + lint budgets (test-litellm-ui-build.yml's frontend-lint) +# - proxy/types staged -> regenerate dashboard API types and fail on drift (check-ui-api-types.yml) +# +# Each block is skipped when no matching files are staged, so unrelated commits stay +# fast. This is intentionally not auto-installed as a git hook (see scripts/install_git_hooks.sh): +# the dashboard and basedpyright passes can take minutes, so it's run on demand rather +# than firing on every human commit. It is hook-compatible if you want that anyway: +# `ln -s ../../scripts/pre_commit_lint.sh .git/hooks/pre-commit`. + +set -eu + +repo_root=$(git rev-parse --show-toplevel) +cd "$repo_root" + +staged=$(git diff --cached --name-only --diff-filter=ACMR) +staged_match() { printf '%s\n' "$staged" | grep -E "$1" || true; } + +# CI's lint job (test-linting.yml) only inspects litellm/, so a tests-only or +# scripts-only commit can't turn it red; scope the trigger there to skip the slow +# make lint when it couldn't catch anything. +litellm_py_files=$(staged_match '^litellm/.*\.py$') +# ruff format (and CI's format step) skip enterprise; the rest of make lint covers it. +fmt_files=$(printf '%s\n' "$litellm_py_files" | grep -v '^litellm/enterprise/' || true) +# check-ui-api-types.yml triggers on any file under litellm/proxy or litellm/types +# (Prisma schema and configs included, not just Python) plus the generator and its +# lockfiles, so match that whole trigger set rather than a Python subset. +spec_files=$(staged_match '^(litellm/(proxy|types)/.*|ui/litellm-dashboard/(scripts/gen-api-types\.mjs|package\.json|package-lock\.json|src/lib/http/schema\.d\.ts))$') +# CI's frontend-lint runs prettier over a wider extension set than eslint; keep that +# split so this flags exactly what the job would. +ui_prettier_files=$(staged_match '^ui/litellm-dashboard/.*\.(js|jsx|ts|tsx|mjs|cjs|json|css|scss|md|mdx|yml|yaml|html)$') +ui_eslint_files=$(staged_match '^ui/litellm-dashboard/.*\.(js|jsx|ts|tsx|mjs|cjs)$') + +lint_dashboard() { + ( + rc=0 + prettier_rel=() + eslint_rel=() + while IFS= read -r f; do + [ -n "$f" ] && prettier_rel+=("${f#ui/litellm-dashboard/}") + done <&2; status=1; } + # `make lint` format-checks files in origin/base...HEAD, which at pre-commit time + # predates the staged change, so format-check the staged litellm files directly to + # cover a brand-new commit before it lands. + if [ -n "$fmt_files" ]; then + echo "pre-commit: ruff format --check (staged litellm files)" + printf '%s\n' "$fmt_files" | xargs uv run --no-sync ruff format --check --exclude '/enterprise/' \ + || { echo "✗ Unformatted staged files. Fix with: make format, then re-stage." >&2; status=1; } + fi +fi + +if [ -n "$ui_prettier_files" ] || [ -n "$ui_eslint_files" ]; then + echo "pre-commit: linting dashboard (prettier + eslint + lint budgets)" + lint_dashboard || { echo "✗ Dashboard lint failed. See above; format with: (cd ui/litellm-dashboard && npm run format)." >&2; status=1; } +fi + +if [ -n "$spec_files" ]; then + echo "pre-commit: checking dashboard API types are in sync (npm run gen:api)" + # gen-api-types.mjs imports litellm.proxy.proxy_server, which needs the proxy deps + # and an up-to-date Prisma client; check-ui-api-types.yml installs those and runs + # prisma generate before gen:api, so mirror that here or a stale client can mask + # drift that CI will still flag. + if ! uv run --no-sync prisma generate --schema litellm/proxy/schema.prisma; then + echo "✗ Could not regenerate Prisma client (prisma generate failed)." >&2 + status=1 + elif ( cd ui/litellm-dashboard && LITELLM_PYTHON="uv run --no-sync python" npm run gen:api ); then + if ! git diff --quiet -- ui/litellm-dashboard/src/lib/http/schema.d.ts; then + echo "✗ Dashboard API types are stale; regenerated src/lib/http/schema.d.ts. Stage it and re-run make pre-commit." >&2 + status=1 + fi + else + echo "✗ Could not regenerate API types (npm run gen:api failed)." >&2 + status=1 + fi +fi + +exit $status From 3dce3daff644863178a7d59b53630d0519a6417b Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 09:58:01 -0700 Subject: [PATCH 10/79] feat(proxy): type Customer Management response_model for OpenAPI coverage (#31043) * feat(proxy): type Customer Management response_model for OpenAPI coverage Add response_model to the five remaining untyped /customer operations (block, unblock, new, update, delete) so the generated OpenAPI schema documents a concrete response body. new/update reuse the canonical LiteLLM_EndUserTable (matching info/list); block, unblock, and delete get small dedicated models in litellm/types/proxy/management_endpoints/customer_endpoints.py. Together with the already-typed info/list/daily-activity routes this brings the Customer Management group to full response_model coverage. Regression tests assert each public /customer/* route declares the expected response_model and that /customer/new surfaces a typed schema in app.openapi(), so dropping a response_model fails CI. * fix(proxy): keep budget_id in typed customer responses Address review feedback on the Customer Management response_model typing. Greptile flagged that response_model=LiteLLM_EndUserTable on /customer/new and /customer/update silently drops fields the raw Prisma model_dump() echoed. Checking the schema, budget_id is the only such scalar column that was missing from the Pydantic model (created_at/updated_at/tpm_limit do not exist on litellm_endusertable), so add budget_id to LiteLLM_EndUserTable. This restores budget_id on new/update and also fixes the pre-existing gap where /customer/info and /customer/list (already typed) dropped it, which the UI Customer type expects. A regression test pins budget_id surviving the response_model filter on /customer/update. Also document UnblockUsersResponse.blocked_users via a Field description: it holds the users that remain blocked after the call. The key name predates this PR and is kept to avoid a backwards-incompatible rename on a beta route. * fix(proxy): keep nested budget fields in customer responses response_model=LiteLLM_EndUserTable nests the budget as the narrow write allowlist LiteLLM_BudgetTable, which silently drops the server-managed fields the customer endpoints used to return (budget_reset_at, created_at). Introduce CustomerResponse, a thin response model that nests LiteLLM_BudgetTableFull (the repo's budget response model), and apply it on /customer/new, /customer/update, /customer/info and /customer/list. list also builds CustomerResponse so its budget isn't narrowed at construction time. created_by/updated_at/updated_by remain omitted, matching how budgets are returned elsewhere. The shared LiteLLM_EndUserTable is left untouched: it's constructed in many places that pass narrow budget instances, and pydantic v2 won't coerce a budget instance into a wider nested model. Typing only at the response boundary (where the handler hands FastAPI a dict) sidesteps that. A regression test pins budget_reset_at + created_at through the filter and asserts the internal audit fields stay out. * test(proxy): add golden-master characterization tests for customer responses Lock the exact JSON body each customer-object endpoint (info/list/new/update) and delete return today, so the upcoming type-safety refactor of the handlers is only allowed to land if it reproduces these byte for byte. Pins null-field inclusion, the nested budget shape (server fields kept, audit fields dropped), and object_permission reverse-relation stripping. Green against current code. * refactor(proxy): make the customer response flow type-safe Replace the untyped dict + bolt-on response_model pattern on the customer object endpoints with explicit typed construction. A single mapper, _to_customer_response, validates a DB row into CustomerResponse at one Any -> typed seam; new/update/info/list now return it (or a list of it) and carry real -> CustomerResponse / -> List[CustomerResponse] return annotations, and delete returns DeleteCustomersResponse. basedpyright now verifies the handlers' return shapes instead of a runtime filter doing it silently. This also deletes the four copy-pasted object_permission reverse-relation cleanup loops: pydantic's extra=ignore drops those undeclared fields during validation, so the loops were dead code (proven by the golden-master tests, which stay byte-for-byte green). basedpyright errors on the file drop from 140 to 116, all from removed dict plumbing. CustomerResponse stays a thin subclass of LiteLLM_EndUserTable so it inherits the existing validators/config unchanged (behavior preservation); only the nested budget type is widened. * refactor(proxy): annotate customer response mapper param as BaseModel Address review nit: the mapper's untyped `record` added an ANN001 violation. The incoming rows are pydantic v2 models, so type the param as BaseModel rather than object (object has no model_dump, which would just move the problem to basedpyright). This clears the ANN001 and also drops three basedpyright unknown-type violations the untyped param was adding. * style(test): ruff format customer endpoint tests * test(proxy): give customer budget test update mocks a valid model_dump The type-safe response refactor validates the update result via _to_customer_response (CustomerResponse.model_validate(record.model_dump())). These budget tests mocked the end-user update to return a bare MagicMock, so model_dump() yielded a MagicMock that fails validation. Give each update mock a minimal valid dict; the tests assert on the prisma calls, not the body. * chore(ui): regenerate API types from proxy OpenAPI spec * fix(ui): make generated API types stable across Python versions Python 3.13 strips a docstring's common leading indentation at compile time while 3.12 keeps it, so app.openapi() emits differently-indented description strings depending on the interpreter. The dashboard type generator ran locally on 3.13 and in CI on 3.12, so schema.d.ts drifted and the "Verify schema.d.ts matches the proxy OpenAPI spec" check failed Normalize every description through inspect.cleandoc in the spec dump so the output is identical regardless of interpreter, then regenerate --- litellm/models/end_user.py | 1 + .../customer_endpoints.py | 105 ++--- .../customer_endpoints.py | 30 ++ .../test_customer_budget.py | 13 +- .../test_customer_endpoints.py | 380 +++++++++++++++--- .../scripts/gen-api-types.mjs | 15 +- ui/litellm-dashboard/src/lib/http/schema.d.ts | 101 +++-- 7 files changed, 495 insertions(+), 150 deletions(-) create mode 100644 litellm/types/proxy/management_endpoints/customer_endpoints.py diff --git a/litellm/models/end_user.py b/litellm/models/end_user.py index 15fd03ec2ca..9bf895b9447 100644 --- a/litellm/models/end_user.py +++ b/litellm/models/end_user.py @@ -21,6 +21,7 @@ class LiteLLM_EndUserTable(LiteLLMPydanticObjectBase): spend: float = 0.0 allowed_model_region: Optional[Literal["eu", "us"]] = None default_model: Optional[str] = None + budget_id: Optional[str] = None litellm_budget_table: Optional[LiteLLM_BudgetTable] = None object_permission_id: Optional[str] = None object_permission: Optional[LiteLLM_ObjectPermissionTable] = None diff --git a/litellm/proxy/management_endpoints/customer_endpoints.py b/litellm/proxy/management_endpoints/customer_endpoints.py index 7c8a9b88191..84f67bdc3bc 100644 --- a/litellm/proxy/management_endpoints/customer_endpoints.py +++ b/litellm/proxy/management_endpoints/customer_endpoints.py @@ -15,6 +15,7 @@ from typing import List, Optional import fastapi from fastapi import APIRouter, Depends, HTTPException, Request +from pydantic import BaseModel import litellm from litellm._logging import verbose_proxy_logger @@ -32,10 +33,26 @@ from litellm.repositories.table_repositories import EndUserRepository from litellm.types.proxy.management_endpoints.common_daily_activity import ( SpendAnalyticsPaginatedResponse, ) +from litellm.types.proxy.management_endpoints.customer_endpoints import ( + BlockUsersResponse, + CustomerResponse, + DeleteCustomersResponse, + UnblockUsersResponse, +) router = APIRouter() +def _to_customer_response(record: BaseModel) -> CustomerResponse: + """Validate a raw end-user DB row into the typed customer response. + + object_permission reverse relations and the budget's audit fields are + dropped here by the response model's field set, so callers need no manual + cleanup. + """ + return CustomerResponse.model_validate(record.model_dump()) + + @router.post( "/end_user/block", tags=["Customer Management"], @@ -46,6 +63,7 @@ router = APIRouter() "/customer/block", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], + response_model=BlockUsersResponse, ) async def block_user(data: BlockUsers): """ @@ -100,6 +118,7 @@ async def block_user(data: BlockUsers): "/customer/unblock", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], + response_model=UnblockUsersResponse, ) async def unblock_user(data: BlockUsers): """ @@ -213,11 +232,12 @@ async def _handle_customer_object_permission_update( "/customer/new", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], + response_model=CustomerResponse, ) async def new_end_user( data: NewCustomerRequest, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): +) -> CustomerResponse: """ Allow creating a new Customer @@ -370,20 +390,7 @@ async def new_end_user( include={"litellm_budget_table": True, "object_permission": True}, ) - # Convert to dict and clean up recursive fields - response_dict = end_user_record.model_dump() - if response_dict.get("object_permission"): - # Remove reverse relations from object_permission - for field in [ - "teams", - "verification_tokens", - "organizations", - "users", - "end_users", - ]: - response_dict["object_permission"].pop(field, None) - - return response_dict + return _to_customer_response(end_user_record) except Exception as e: verbose_proxy_logger.exception( "litellm.proxy.management_endpoints.customer_endpoints.new_end_user(): Exception occured - {}".format( @@ -404,7 +411,7 @@ async def new_end_user( "/customer/info", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], - response_model=LiteLLM_EndUserTable, + response_model=CustomerResponse, ) @router.get( "/end_user/info", @@ -414,7 +421,7 @@ async def new_end_user( ) async def end_user_info( end_user_id: str = fastapi.Query(description="End User ID in the request parameters"), -): +) -> CustomerResponse: """ Get information about an end-user. An `end_user` is a customer (external user) of the proxy. @@ -449,20 +456,7 @@ async def end_user_info( param="end_user_id", ) - # Convert to dict and clean up recursive fields - response_dict = user_info.model_dump(exclude_none=True) - if response_dict.get("object_permission"): - # Remove reverse relations from object_permission - for field in [ - "teams", - "verification_tokens", - "organizations", - "users", - "end_users", - ]: - response_dict["object_permission"].pop(field, None) - - return response_dict + return _to_customer_response(user_info) except Exception as e: verbose_proxy_logger.exception( @@ -477,6 +471,7 @@ async def end_user_info( "/customer/update", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], + response_model=CustomerResponse, ) @router.post( "/end_user/update", @@ -487,7 +482,7 @@ async def end_user_info( async def update_end_user( data: UpdateCustomerRequest, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): +) -> CustomerResponse: """ Example curl @@ -641,20 +636,7 @@ async def update_end_user( raise ValueError(f"Failed updating customer data. User ID does not exist passed user_id={data.user_id}") verbose_proxy_logger.debug(f"received response from updating prisma client. response={response}") - # Convert to dict and clean up recursive fields - response_dict = response.model_dump() - if response_dict.get("object_permission"): - # Remove reverse relations from object_permission - for field in [ - "teams", - "verification_tokens", - "organizations", - "users", - "end_users", - ]: - response_dict["object_permission"].pop(field, None) - - return response_dict + return _to_customer_response(response) else: raise ValueError(f"user_id is required, passed user_id = {data.user_id}") @@ -671,6 +653,7 @@ async def update_end_user( "/customer/delete", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], + response_model=DeleteCustomersResponse, ) @router.post( "/end_user/delete", @@ -681,7 +664,7 @@ async def update_end_user( async def delete_end_user( data: DeleteCustomerRequest, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): +) -> DeleteCustomersResponse: """ Delete multiple end-users. @@ -728,10 +711,10 @@ async def delete_end_user( where={"user_id": {"in": data.user_ids}} ) verbose_proxy_logger.debug(f"received response from updating prisma client. response={response}") - return { - "deleted_customers": response, - "message": "Successfully deleted customers with ids: " + str(data.user_ids), - } + return DeleteCustomersResponse( + deleted_customers=response, + message="Successfully deleted customers with ids: " + str(data.user_ids), + ) else: raise ValueError(f"user_id is required, passed user_id = {data.user_ids}") @@ -747,7 +730,7 @@ async def delete_end_user( "/customer/list", tags=["Customer Management"], dependencies=[Depends(user_api_key_auth)], - response_model=List[LiteLLM_EndUserTable], + response_model=List[CustomerResponse], ) @router.get( "/end_user/list", @@ -758,7 +741,7 @@ async def delete_end_user( async def list_end_user( http_request: Request, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): +) -> List[CustomerResponse]: """ [Admin-only] List all available customers @@ -791,21 +774,7 @@ async def list_end_user( include={"litellm_budget_table": True, "object_permission": True} ) - returned_response: List[LiteLLM_EndUserTable] = [] - for item in response: - item_dict = item.model_dump() - # Remove reverse relations from object_permission - if item_dict.get("object_permission"): - for field in [ - "teams", - "verification_tokens", - "organizations", - "users", - "end_users", - ]: - item_dict["object_permission"].pop(field, None) - returned_response.append(LiteLLM_EndUserTable(**item_dict)) - return returned_response + return [_to_customer_response(item) for item in response] except Exception as e: verbose_proxy_logger.exception( diff --git a/litellm/types/proxy/management_endpoints/customer_endpoints.py b/litellm/types/proxy/management_endpoints/customer_endpoints.py new file mode 100644 index 00000000000..e7653360d63 --- /dev/null +++ b/litellm/types/proxy/management_endpoints/customer_endpoints.py @@ -0,0 +1,30 @@ +from typing import List, Optional + +from pydantic import BaseModel, Field + +from litellm.models.budget import LiteLLM_BudgetTableFull +from litellm.models.end_user import LiteLLM_EndUserTable + + +class CustomerResponse(LiteLLM_EndUserTable): + """Customer object returned by the /customer read+write endpoints. + + Nests the full budget response model so server-managed budget fields + (budget_reset_at, created_at) survive response_model filtering, rather than + the narrow write-allowlist shape LiteLLM_EndUserTable carries for internal use. + """ + + litellm_budget_table: Optional[LiteLLM_BudgetTableFull] = None # pyright: ignore + + +class BlockUsersResponse(BaseModel): + blocked_users: List[LiteLLM_EndUserTable] + + +class UnblockUsersResponse(BaseModel): + blocked_users: List[str] = Field(description="User IDs that remain blocked after this unblock call") + + +class DeleteCustomersResponse(BaseModel): + deleted_customers: int + message: str diff --git a/tests/test_litellm/proxy/management_endpoints/test_customer_budget.py b/tests/test_litellm/proxy/management_endpoints/test_customer_budget.py index 41f43c75f7d..0beca0c15e8 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_customer_budget.py +++ b/tests/test_litellm/proxy/management_endpoints/test_customer_budget.py @@ -134,8 +134,10 @@ async def test_update_customer_creates_budget_with_proper_relations( ) # Mock end user update + mock_updated_user = MagicMock() + mock_updated_user.model_dump.return_value = {"user_id": "test-user", "blocked": False} mock_prisma_client.db.litellm_endusertable.update = AsyncMock( - return_value=MagicMock() + return_value=mock_updated_user ) # Create update request with budget creation fields (not just budget_id) @@ -190,8 +192,10 @@ async def test_update_customer_creates_budget_with_required_fields( ) # Mock end user update + mock_updated_user = MagicMock() + mock_updated_user.model_dump.return_value = {"user_id": "test-user", "blocked": False} mock_prisma_client.db.litellm_endusertable.update = AsyncMock( - return_value=MagicMock() + return_value=mock_updated_user ) # Create update request with budget creation fields @@ -253,8 +257,10 @@ async def test_update_customer_budget_creation_with_fallback_admin( ) # Mock end user update + mock_updated_user = MagicMock() + mock_updated_user.model_dump.return_value = {"user_id": "test-user", "blocked": False} mock_prisma_client.db.litellm_endusertable.update = AsyncMock( - return_value=MagicMock() + return_value=mock_updated_user ) # Create update request with budget creation fields @@ -309,6 +315,7 @@ async def test_update_customer_with_budget_id_and_creation_fields( # Mock end user update mock_updated_user = MagicMock() + mock_updated_user.model_dump.return_value = {"user_id": "test-user", "blocked": False} mock_prisma_client.db.litellm_endusertable.update = AsyncMock( return_value=mock_updated_user ) diff --git a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py index 6c5ccd3562f..d4089b23e81 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py @@ -1,18 +1,28 @@ +from typing import List from unittest.mock import AsyncMock, MagicMock, patch import pytest from fastapi import FastAPI, HTTPException, Request, status from fastapi.responses import JSONResponse +from fastapi.routing import APIRoute from fastapi.testclient import TestClient from litellm.proxy._types import ( - LiteLLM_BudgetTable, LiteLLM_EndUserTable, LitellmUserRoles, ProxyException, ) from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth, user_api_key_auth from litellm.proxy.management_endpoints.customer_endpoints import router +from litellm.types.proxy.management_endpoints.common_daily_activity import ( + SpendAnalyticsPaginatedResponse, +) +from litellm.types.proxy.management_endpoints.customer_endpoints import ( + BlockUsersResponse, + CustomerResponse, + DeleteCustomersResponse, + UnblockUsersResponse, +) app = FastAPI() @@ -22,9 +32,7 @@ async def openai_exception_handler(request: Request, exc: ProxyException): headers = exc.headers error_dict = exc.to_dict() return JSONResponse( - status_code=( - int(exc.code) if exc.code else status.HTTP_500_INTERNAL_SERVER_ERROR - ), + status_code=(int(exc.code) if exc.code else status.HTTP_500_INTERNAL_SERVER_ERROR), content={"error": error_dict}, headers=headers, ) @@ -54,30 +62,20 @@ def mock_user_api_key_auth(): def test_update_customer_success(mock_prisma_client, mock_user_api_key_auth): # Mock the database responses - mock_end_user = LiteLLM_EndUserTable( - user_id="test-user-1", alias="Test User", blocked=False - ) - updated_mock_end_user = LiteLLM_EndUserTable( - user_id="test-user-1", alias="Updated Test User", blocked=False - ) + mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", alias="Test User", blocked=False) + updated_mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", alias="Updated Test User", blocked=False) # Mock the find_first response - mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock( - return_value=mock_end_user - ) + mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=mock_end_user) # Mock the update response - mock_prisma_client.db.litellm_endusertable.update = AsyncMock( - return_value=updated_mock_end_user - ) + mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=updated_mock_end_user) # Test data test_data = {"user_id": "test-user-1", "alias": "Updated Test User"} # Make the request - response = client.post( - "/customer/update", json=test_data, headers={"Authorization": "Bearer test-key"} - ) + response = client.post("/customer/update", json=test_data, headers={"Authorization": "Bearer test-key"}) # Assert response assert response.status_code == 200 @@ -106,10 +104,7 @@ def test_update_customer_not_found(mock_prisma_client, mock_user_api_key_auth): assert response.status_code == 404 response_json = response.json() assert "error" in response_json - assert ( - response_json["error"]["message"] - == "End User Id=non-existent-user does not exist in db" - ) + assert response_json["error"]["message"] == "End User Id=non-existent-user does not exist in db" assert response_json["error"]["type"] == "not_found" assert response_json["error"]["param"] == "user_id" assert response_json["error"]["code"] == "404" @@ -132,10 +127,7 @@ def test_info_customer_not_found(mock_prisma_client, mock_user_api_key_auth): assert response.status_code == 404 response_json = response.json() assert "error" in response_json - assert ( - response_json["error"]["message"] - == "End User Id=non-existent-user does not exist in db" - ) + assert response_json["error"]["message"] == "End User Id=non-existent-user does not exist in db" assert response_json["error"]["type"] == "not_found" assert response_json["error"]["param"] == "end_user_id" assert response_json["error"]["code"] == "404" @@ -220,11 +212,6 @@ def test_error_schema_consistency(mock_prisma_client, mock_user_api_key_auth): assert error["code"] == "404" # Test /customer/new - duplicate user error - from unittest.mock import MagicMock - - mock_end_user = LiteLLM_EndUserTable( - user_id="existing-user", alias="Existing User", blocked=False - ) mock_prisma_client.db.litellm_endusertable.create = AsyncMock( side_effect=Exception("Unique constraint failed on the fields: (`user_id`)") ) @@ -238,9 +225,7 @@ def test_error_schema_consistency(mock_prisma_client, mock_user_api_key_auth): assert error["code"] == "400" -def test_customer_endpoints_error_schema_consistency( - mock_prisma_client, mock_user_api_key_auth -): +def test_customer_endpoints_error_schema_consistency(mock_prisma_client, mock_user_api_key_auth): """ Test the exact scenarios from the curl examples provided. @@ -307,9 +292,7 @@ def test_customer_endpoints_error_schema_consistency( assert "Customer already exists" in error2["message"] # Verify both errors have the same schema structure - assert set(error1.keys()) == set( - error2.keys() - ), "Both errors should have the same top-level keys" + assert set(error1.keys()) == set(error2.keys()), "Both errors should have the same top-level keys" # Both should have string values for all fields for key in ["message", "type", "code"]: @@ -317,6 +300,153 @@ def test_customer_endpoints_error_schema_consistency( assert isinstance(error2[key], str), f"error2[{key}] should be a string" +EXPECTED_RESPONSE_MODELS = { + "/customer/block": BlockUsersResponse, + "/customer/unblock": UnblockUsersResponse, + "/customer/new": CustomerResponse, + "/customer/update": CustomerResponse, + "/customer/delete": DeleteCustomersResponse, + "/customer/info": CustomerResponse, + "/customer/list": List[CustomerResponse], + "/customer/daily/activity": SpendAnalyticsPaginatedResponse, +} + + +@pytest.mark.parametrize("path, expected_model", EXPECTED_RESPONSE_MODELS.items()) +def test_customer_routes_declare_response_model(path, expected_model): + """ + Every public /customer/* operation must declare a typed response_model so + the generated OpenAPI schema documents the response body. Regression for the + OpenAPI response-type coverage goal: drop a response_model and this fails. + """ + route = next(r for r in router.routes if isinstance(r, APIRoute) and r.path == path) + assert route.response_model == expected_model + + +def test_customer_new_documented_in_openapi_schema(): + """ + The response_model must surface in the OpenAPI schema as a concrete ref, not + an empty/default response. This is what the coverage metric measures. + """ + schema = app.openapi()["paths"]["/customer/new"]["post"] + json_schema = schema["responses"]["200"]["content"]["application/json"]["schema"] + assert json_schema["$ref"].endswith("/CustomerResponse") + + +def test_update_customer_response_preserves_budget_id(mock_prisma_client, mock_user_api_key_auth): + """ + Regression for the response_model field-stripping concern: budget_id is a real + column on the end-user table that /customer/update echoes. response_model= + LiteLLM_EndUserTable must NOT drop it, so budget_id stays in LiteLLM_EndUserTable. + """ + existing = LiteLLM_EndUserTable(user_id="cust-1", blocked=False) + updated = LiteLLM_EndUserTable(user_id="cust-1", blocked=False, budget_id="budget-123") + mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=existing) + mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=updated) + + response = client.post( + "/customer/update", + json={"user_id": "cust-1", "budget_id": "budget-123"}, + headers={"Authorization": "Bearer test-key"}, + ) + + assert response.status_code == 200 + assert response.json()["budget_id"] == "budget-123" + + +def test_update_customer_response_keeps_nested_budget_server_fields(mock_prisma_client, mock_user_api_key_auth): + """ + Faithfulness regression: /customer/update embeds the full budget row. The + response_model must keep the server-managed budget fields the endpoint used + to return (budget_reset_at, created_at) instead of the narrow write-allowlist + shape. The intentionally-internal audit fields (created_by/updated_by) stay out. + """ + existing = LiteLLM_EndUserTable(user_id="cust-1", blocked=False) + raw_row = MagicMock() + raw_row.model_dump.return_value = { + "user_id": "cust-1", + "blocked": False, + "alias": "renamed", + "spend": 0.0, + "allowed_model_region": None, + "default_model": None, + "budget_id": "b-1", + "object_permission_id": None, + "object_permission": None, + "litellm_budget_table": { + "budget_id": "b-1", + "max_budget": 10.0, + "budget_duration": "30d", + "budget_reset_at": "2024-02-01T00:00:00", + "created_at": "2024-01-01T00:00:00", + "created_by": "admin", + "updated_at": "2024-01-02T00:00:00", + "updated_by": "admin", + }, + } + mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=existing) + mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=raw_row) + + response = client.post( + "/customer/update", + json={"user_id": "cust-1", "alias": "renamed"}, + headers={"Authorization": "Bearer test-key"}, + ) + + assert response.status_code == 200 + budget = response.json()["litellm_budget_table"] + assert budget["budget_reset_at"] == "2024-02-01T00:00:00" + assert budget["created_at"] == "2024-01-01T00:00:00" + assert "created_by" not in budget + assert "updated_by" not in budget + + +def test_block_customer_success_serializes_through_response_model(mock_prisma_client, mock_user_api_key_auth): + """ + /customer/block returns {"blocked_users": []}. With + response_model=BlockUsersResponse, a shape mismatch would raise a 500 + ResponseValidationError, so a clean 200 proves the model matches runtime output. + """ + blocked_row = LiteLLM_EndUserTable(user_id="blocked-1", blocked=True) + mock_prisma_client.db.litellm_endusertable.upsert = AsyncMock(return_value=blocked_row) + + response = client.post( + "/customer/block", + json={"user_ids": ["blocked-1"]}, + headers={"Authorization": "Bearer test-key"}, + ) + + assert response.status_code == 200 + body = response.json() + assert body["blocked_users"][0]["user_id"] == "blocked-1" + assert body["blocked_users"][0]["blocked"] is True + + +def test_delete_customer_success_serializes_through_response_model(mock_prisma_client, mock_user_api_key_auth): + """ + /customer/delete returns {"deleted_customers": , "message": }. + response_model=DeleteCustomersResponse enforces that exact shape. + """ + existing = [ + LiteLLM_EndUserTable(user_id="u1", blocked=False), + LiteLLM_EndUserTable(user_id="u2", blocked=False), + ] + mock_prisma_client.db.litellm_endusertable.find_many = AsyncMock(return_value=existing) + mock_prisma_client.db.litellm_endusertable.delete_many = AsyncMock(return_value=2) + + response = client.post( + "/customer/delete", + json={"user_ids": ["u1", "u2"]}, + headers={"Authorization": "Bearer test-key"}, + ) + + assert response.status_code == 200 + assert response.json() == { + "deleted_customers": 2, + "message": "Successfully deleted customers with ids: ['u1', 'u2']", + } + + @pytest.mark.asyncio async def test_get_customer_daily_activity_admin_param_passing(monkeypatch): from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth @@ -331,9 +461,7 @@ async def test_get_customer_daily_activity_admin_param_passing(monkeypatch): mocked_response = MagicMock(name="SpendAnalyticsPaginatedResponse") get_daily_activity_mock = AsyncMock(return_value=mocked_response) - monkeypatch.setattr( - customer_endpoints, "get_daily_activity", get_daily_activity_mock - ) + monkeypatch.setattr(customer_endpoints, "get_daily_activity", get_daily_activity_mock) auth = UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN, user_id="admin1") result = await get_customer_daily_activity( @@ -380,16 +508,12 @@ async def test_get_customer_daily_activity_with_end_user_aliases(monkeypatch): mock_end_user2.user_id = "end-user-2" mock_end_user2.alias = "Customer Two" - mock_prisma_client.db.litellm_endusertable.find_many = AsyncMock( - return_value=[mock_end_user1, mock_end_user2] - ) + mock_prisma_client.db.litellm_endusertable.find_many = AsyncMock(return_value=[mock_end_user1, mock_end_user2]) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) mocked_response = MagicMock(name="SpendAnalyticsPaginatedResponse") get_daily_activity_mock = AsyncMock(return_value=mocked_response) - monkeypatch.setattr( - customer_endpoints, "get_daily_activity", get_daily_activity_mock - ) + monkeypatch.setattr(customer_endpoints, "get_daily_activity", get_daily_activity_mock) auth = UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN, user_id="admin1") await get_customer_daily_activity( @@ -436,9 +560,7 @@ async def test_get_customer_daily_activity_non_admin_is_rejected(monkeypatch): monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) get_daily_activity_mock = AsyncMock() - monkeypatch.setattr( - customer_endpoints, "get_daily_activity", get_daily_activity_mock - ) + monkeypatch.setattr(customer_endpoints, "get_daily_activity", get_daily_activity_mock) non_admin_key = UserAPIKeyAuth( user_id="regular-user-abc", @@ -482,9 +604,7 @@ async def test_get_customer_daily_activity_service_account_key_is_rejected(monke monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) get_daily_activity_mock = AsyncMock() - monkeypatch.setattr( - customer_endpoints, "get_daily_activity", get_daily_activity_mock - ) + monkeypatch.setattr(customer_endpoints, "get_daily_activity", get_daily_activity_mock) service_account_key = UserAPIKeyAuth( user_id=None, @@ -507,3 +627,157 @@ async def test_get_customer_daily_activity_service_account_key_is_rejected(monke assert exc_info.value.status_code == 401 assert "Admin-only endpoint" in str(exc_info.value.detail) get_daily_activity_mock.assert_not_called() + + +# --------------------------------------------------------------------------- +# Characterization (golden-master) tests. +# +# These lock the EXACT JSON body every customer-object endpoint returns today, +# so a type-safety refactor of the handlers is only allowed to land if it +# reproduces these byte for byte. The input below is what a Prisma row's +# .model_dump() yields (full nested budget incl. audit fields + object_permission +# incl. reverse relations); the expected output is what the live endpoint emits. +# --------------------------------------------------------------------------- + +_FULL_DB_ROW = { + "user_id": "c1", + "blocked": False, + "alias": "Acme", + "spend": 1.5, + "allowed_model_region": None, + "default_model": None, + "budget_id": "b1", + "object_permission_id": "p1", + "litellm_budget_table": { + "budget_id": "b1", + "max_budget": 10.0, + "soft_budget": None, + "max_parallel_requests": None, + "tpm_limit": None, + "rpm_limit": None, + "model_max_budget": None, + "budget_duration": "30d", + "allowed_models": [], + "budget_reset_at": "2024-02-01T00:00:00", + "created_at": "2024-01-01T00:00:00", + "created_by": "admin", + "updated_at": "2024-01-02T00:00:00", + "updated_by": "admin", + }, + "object_permission": { + "object_permission_id": "p1", + "mcp_servers": ["s1"], + "mcp_access_groups": [], + "mcp_tool_permissions": None, + "vector_stores": [], + "agents": [], + "agent_access_groups": [], + "models": [], + "mcp_toolsets": None, + "blocked_tools": [], + "search_tools": [], + "teams": [{"team_id": "t1"}], + "users": [{"user_id": "x"}], + "end_users": [], + "organizations": [], + "verification_tokens": [], + }, +} + +_EXPECTED_CUSTOMER = { + "user_id": "c1", + "blocked": False, + "alias": "Acme", + "spend": 1.5, + "allowed_model_region": None, + "default_model": None, + "budget_id": "b1", + "litellm_budget_table": { + "budget_id": "b1", + "soft_budget": None, + "max_budget": 10.0, + "max_parallel_requests": None, + "tpm_limit": None, + "rpm_limit": None, + "model_max_budget": None, + "budget_duration": "30d", + "allowed_models": [], + "budget_reset_at": "2024-02-01T00:00:00", + "created_at": "2024-01-01T00:00:00", + }, + "object_permission_id": "p1", + "object_permission": { + "object_permission_id": "p1", + "mcp_servers": ["s1"], + "mcp_access_groups": [], + "mcp_tool_permissions": None, + "vector_stores": [], + "agents": [], + "agent_access_groups": [], + "models": [], + "mcp_toolsets": None, + "blocked_tools": [], + "search_tools": [], + }, +} + + +def _row(dump: dict) -> MagicMock: + row = MagicMock() + row.model_dump.return_value = dump + return row + + +def test_char_info_body(mock_prisma_client, mock_user_api_key_auth): + mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=_row(_FULL_DB_ROW)) + response = client.get("/customer/info?end_user_id=c1", headers={"Authorization": "Bearer k"}) + assert response.status_code == 200 + assert response.json() == _EXPECTED_CUSTOMER + + +def test_char_list_body(mock_prisma_client, mock_user_api_key_auth): + mock_prisma_client.db.litellm_endusertable.find_many = AsyncMock(return_value=[_row(_FULL_DB_ROW)]) + response = client.get("/customer/list", headers={"Authorization": "Bearer k"}) + assert response.status_code == 200 + assert response.json() == [_EXPECTED_CUSTOMER] + + +def test_char_new_body(mock_prisma_client, mock_user_api_key_auth): + mock_prisma_client.db.litellm_endusertable.create = AsyncMock(return_value=_row(_FULL_DB_ROW)) + response = client.post("/customer/new", json={"user_id": "c1"}, headers={"Authorization": "Bearer k"}) + assert response.status_code == 200 + assert response.json() == _EXPECTED_CUSTOMER + + +def test_char_update_body(mock_prisma_client, mock_user_api_key_auth): + mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock( + return_value=_row({"user_id": "c1", "blocked": False}) + ) + mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=_row(_FULL_DB_ROW)) + response = client.post( + "/customer/update", + json={"user_id": "c1", "alias": "Acme"}, + headers={"Authorization": "Bearer k"}, + ) + assert response.status_code == 200 + assert response.json() == _EXPECTED_CUSTOMER + + +def test_char_delete_body(mock_prisma_client, mock_user_api_key_auth): + mock_prisma_client.db.litellm_endusertable.find_many = AsyncMock( + return_value=[ + LiteLLM_EndUserTable(user_id="c1", blocked=False), + LiteLLM_EndUserTable(user_id="c2", blocked=False), + ] + ) + mock_prisma_client.db.litellm_endusertable.delete_many = AsyncMock(return_value=2) + response = client.post( + "/customer/delete", + json={"user_ids": ["c1", "c2"]}, + headers={"Authorization": "Bearer k"}, + ) + assert response.status_code == 200 + assert response.json() == { + "deleted_customers": 2, + "message": "Successfully deleted customers with ids: ['c1', 'c2']", + } diff --git a/ui/litellm-dashboard/scripts/gen-api-types.mjs b/ui/litellm-dashboard/scripts/gen-api-types.mjs index 3c9373ec547..6b9f8581292 100644 --- a/ui/litellm-dashboard/scripts/gen-api-types.mjs +++ b/ui/litellm-dashboard/scripts/gen-api-types.mjs @@ -26,15 +26,26 @@ const python = (process.env.LITELLM_PYTHON ?? "python3").split(" "); // The dashboard calls internal UI routes that the public /openapi.json hides via // include_in_schema=False. Force them in so they get typed here; this mutates a // throwaway interpreter, so the spec the proxy actually serves is unchanged. +// Python 3.13 strips a docstring's common leading indentation at compile time +// while 3.12 keeps it, so the same model yields differently-indented descriptions +// depending on the interpreter — enough to make this output non-reproducible +// across CI and contributors. inspect.cleandoc normalizes every description to one +// canonical form regardless of interpreter, so the generated file is stable. const dumpSpec = [ - "import json, sys", + "import inspect, json, sys", "from litellm.proxy.proxy_server import app", "from fastapi.routing import APIRoute", "for route in app.routes:", " if isinstance(route, APIRoute):", " route.include_in_schema = True", "app.openapi_schema = None", - "with open(sys.argv[1], 'w') as f: json.dump(app.openapi(), f, sort_keys=True)", + "def normalize(node):", + " if isinstance(node, dict):", + " return {k: inspect.cleandoc(v) if k == 'description' and isinstance(v, str) else normalize(v) for k, v in node.items()}", + " if isinstance(node, list):", + " return [normalize(v) for v in node]", + " return node", + "with open(sys.argv[1], 'w') as f: json.dump(normalize(app.openapi()), f, sort_keys=True)", ].join("\n"); try { diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index 7d5d617c824..f15eaf9ea1f 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -3027,8 +3027,8 @@ export interface paths { /** * Get Active Tasks Stats * @description Returns: - * total_active_tasks: int - * by_name: { coroutine_name: count } + * total_active_tasks: int + * by_name: { coroutine_name: count } */ get: operations["get_active_tasks_stats_debug_asyncio_tasks_get"]; put?: never; @@ -21003,6 +21003,11 @@ export interface components { /** User Ids */ user_ids: string[]; }; + /** BlockUsersResponse */ + BlockUsersResponse: { + /** Blocked Users */ + blocked_users: components["schemas"]["LiteLLM_EndUserTable"][]; + }; /** * BlockedWord * @description Represents a blocked word with its action and optional description @@ -22651,10 +22656,10 @@ export interface components { /** * ContentFilterCategoryConfig * @description category: "harmful_self_harm" - * enabled: true - * action: "BLOCK" - * severity_threshold: "medium" - * category_file: "/path/to/custom_file.yaml" # optional override + * enabled: true + * action: "BLOCK" + * severity_threshold: "medium" + * category_file: "/path/to/custom_file.yaml" # optional override */ ContentFilterCategoryConfig: { /** @@ -22879,6 +22884,37 @@ export interface components { [key: string]: unknown; }; }; + /** + * CustomerResponse + * @description Customer object returned by the /customer read+write endpoints. + * + * Nests the full budget response model so server-managed budget fields + * (budget_reset_at, created_at) survive response_model filtering, rather than + * the narrow write-allowlist shape LiteLLM_EndUserTable carries for internal use. + */ + CustomerResponse: { + /** Alias */ + alias?: string | null; + /** Allowed Model Region */ + allowed_model_region?: ("eu" | "us") | null; + /** Blocked */ + blocked: boolean; + /** Budget Id */ + budget_id?: string | null; + /** Default Model */ + default_model?: string | null; + litellm_budget_table?: components["schemas"]["LiteLLM_BudgetTableFull"] | null; + object_permission?: components["schemas"]["LiteLLM_ObjectPermissionTable"] | null; + /** Object Permission Id */ + object_permission_id?: string | null; + /** + * Spend + * @default 0 + */ + spend: number; + /** User Id */ + user_id: string; + }; /** DailySpendData */ DailySpendData: { breakdown?: components["schemas"]["BreakdownMetrics"]; @@ -23043,6 +23079,13 @@ export interface components { /** User Ids */ user_ids: string[]; }; + /** DeleteCustomersResponse */ + DeleteCustomersResponse: { + /** Deleted Customers */ + deleted_customers: number; + /** Message */ + message: string; + }; /** * DeleteEvalResponse * @description Response from deleting an evaluation @@ -24792,6 +24835,8 @@ export interface components { allowed_model_region?: ("eu" | "us") | null; /** Blocked */ blocked: boolean; + /** Budget Id */ + budget_id?: string | null; /** Default Model */ default_model?: string | null; litellm_budget_table?: components["schemas"]["LiteLLM_BudgetTable"] | null; @@ -31477,6 +31522,14 @@ export interface components { */ workers: components["schemas"]["WorkerRegistryEntry"][]; }; + /** UnblockUsersResponse */ + UnblockUsersResponse: { + /** + * Blocked Users + * @description User IDs that remain blocked after this unblock call + */ + blocked_users: string[]; + }; /** * UpdateCustomerRequest * @description Update a Customer, use this to update customer budgets etc @@ -37482,7 +37535,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["BlockUsersResponse"]; }; }; /** @description Validation Error */ @@ -37553,7 +37606,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["DeleteCustomersResponse"]; }; }; /** @description Validation Error */ @@ -37585,7 +37638,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": components["schemas"]["LiteLLM_EndUserTable"]; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -37614,7 +37667,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": components["schemas"]["LiteLLM_EndUserTable"][]; + "application/json": components["schemas"]["CustomerResponse"][]; }; }; }; @@ -37638,7 +37691,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -37671,7 +37724,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["UnblockUsersResponse"]; }; }; /** @description Validation Error */ @@ -37704,7 +37757,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -38130,7 +38183,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["DeleteCustomersResponse"]; }; }; /** @description Validation Error */ @@ -38162,7 +38215,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -38191,7 +38244,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"][]; }; }; }; @@ -38215,7 +38268,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -38281,7 +38334,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": unknown; + "application/json": components["schemas"]["CustomerResponse"]; }; }; /** @description Validation Error */ @@ -43890,13 +43943,13 @@ export interface operations { /** * @description Unified rate-limit error. * - * Every rate-limit condition surfaced by litellm — whether it originated from - * an upstream LLM provider, a vendor batch endpoint, or one of litellm's own - * proxy-side limiters (parallel-requests, dynamic-rate, batch-rate, budget, - * max-iterations, etc.) — is raised as an instance of this class. + * Every rate-limit condition surfaced by litellm — whether it originated from + * an upstream LLM provider, a vendor batch endpoint, or one of litellm's own + * proxy-side limiters (parallel-requests, dynamic-rate, batch-rate, budget, + * max-iterations, etc.) — is raised as an instance of this class. * - * The :attr:`category` attribute lets callers distinguish the source. See - * :class:`RateLimitErrorCategory` for the available values. + * The :attr:`category` attribute lets callers distinguish the source. See + * :class:`RateLimitErrorCategory` for the available values. */ 429: { headers: { From 2e575d39f2557926c0aecadd67b8afba81c640e2 Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 20:26:20 +0300 Subject: [PATCH 11/79] perf(otel): memoize per-request lazy import of otel runtime hooks (#31707) The proxy auth path calls phase_span() and seed_request_identity() in litellm/integrations/otel/runtime.py on every request, each doing a try/except lazy import of litellm.integrations.otel.logger. When the OpenTelemetry SDK is not installed (the default), that import raises, and CPython never caches a failed import, so every request re-scanned sys.path and contended on the import lock. At 750 concurrent users this cost about 12% throughput versus v1.85.0. Resolve the hooks once and cache the outcome, absence included, with functools.cache, so the import is attempted a single time instead of per request. Throughput returns to the v1.85.0 baseline. --- litellm/integrations/otel/runtime.py | 34 ++++++---- .../integrations/otel/test_runtime.py | 64 +++++++++++++++++++ 2 files changed, 87 insertions(+), 11 deletions(-) create mode 100644 tests/test_litellm/integrations/otel/test_runtime.py diff --git a/litellm/integrations/otel/runtime.py b/litellm/integrations/otel/runtime.py index ac3b991c971..eb512375023 100644 --- a/litellm/integrations/otel/runtime.py +++ b/litellm/integrations/otel/runtime.py @@ -8,7 +8,23 @@ identity unconditionally. """ from contextlib import contextmanager -from typing import Any, Iterator +from functools import cache +from typing import Any, Callable, Iterator, Optional + + +@cache +def _otel_runtime() -> "Optional[tuple[Callable[[str], Any], Callable[..., None]]]": + """Resolve the SDK-backed hooks once and cache the outcome, absence included. + + CPython never caches a failed import, so without this memoization every call + site re-attempts the import on each request; when the OTel SDK is not installed + that re-scans ``sys.path`` and contends on the import lock on the hot path. + """ + try: + from litellm.integrations.otel import logger + except Exception: + return None + return (logger.phase_span, logger.seed_request_identity) @contextmanager @@ -18,21 +34,17 @@ def phase_span(name: str) -> "Iterator[Any]": Yields ``None`` (a plain no-op) when the OTel SDK is unavailable or V2 is not the active logger. """ - try: - from litellm.integrations.otel.logger import phase_span as _phase_span - except Exception: + runtime = _otel_runtime() + if runtime is None: yield None return - with _phase_span(name) as span: + with runtime[0](name) as span: yield span def seed_request_identity(user_api_key_dict: Any, model: Any = None) -> None: """Seed request-identity Baggage at the auth boundary (no-op without V2).""" - try: - from litellm.integrations.otel.logger import ( - seed_request_identity as _seed_request_identity, - ) - except Exception: + runtime = _otel_runtime() + if runtime is None: return - _seed_request_identity(user_api_key_dict, model=model) + runtime[1](user_api_key_dict, model=model) diff --git a/tests/test_litellm/integrations/otel/test_runtime.py b/tests/test_litellm/integrations/otel/test_runtime.py new file mode 100644 index 00000000000..d11f31b2523 --- /dev/null +++ b/tests/test_litellm/integrations/otel/test_runtime.py @@ -0,0 +1,64 @@ +"""Regression tests for the SDK-free OTel runtime shim. + +The proxy auth hot path calls ``phase_span`` and ``seed_request_identity`` on +every request. These wrappers resolve the SDK-backed implementations with a +lazy import. CPython never caches a failed import, so before memoization an +absent OTel SDK made every request re-scan ``sys.path`` and contend on the +import lock. These tests pin the import to a single resolution. +""" + +import builtins + +import litellm.integrations.otel.runtime as runtime + + +def test_logger_not_reimported_after_first_resolution(monkeypatch): + runtime._otel_runtime.cache_clear() + + counts = {"n": 0} + real_import = builtins.__import__ + + def counting_import(name, globals=None, locals=None, fromlist=(), level=0): + if name == "litellm.integrations.otel" and fromlist and "logger" in fromlist: + counts["n"] += 1 + return real_import(name, globals, locals, fromlist, level) + + monkeypatch.setattr(builtins, "__import__", counting_import) + + with runtime.phase_span("auth /v1/chat/completions"): + pass + after_first = counts["n"] + + for _ in range(49): + with runtime.phase_span("auth /v1/chat/completions"): + pass + + assert counts["n"] == after_first, ( + f"otel.logger re-imported {counts['n'] - after_first} times after the first " + "resolution; it must be memoized so it does not re-scan sys.path per request" + ) + + runtime._otel_runtime.cache_clear() + + +def test_resolution_is_memoized(): + runtime._otel_runtime.cache_clear() + + for _ in range(25): + with runtime.phase_span("p"): + pass + + info = runtime._otel_runtime.cache_info() + assert info.misses == 1 + assert info.hits >= 24 + + runtime._otel_runtime.cache_clear() + + +def test_wrappers_no_op_when_runtime_absent(monkeypatch): + monkeypatch.setattr(runtime, "_otel_runtime", lambda: None) + + with runtime.phase_span("auth") as span: + assert span is None + + assert runtime.seed_request_identity({"token": "sk-x"}, model="gpt-4o") is None From 468d11f71d2edeb2118d14de73d7733fbce62511 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 10:26:57 -0700 Subject: [PATCH 12/79] feat(otel): emit a tools/list CLIENT span for MCP discovery under otel_v2 (#31525) * feat(otel): emit a tools/list CLIENT span for MCP discovery under otel_v2 Under otel_v2 an MCP tools/call already produced a dedicated CLIENT span, but tools/list produced none. The discovery call surfaced only as the bare POST /{mcp_server_name}/mcp server span with no MCP attributes, indistinguishable from initialize and impossible to query by method The list success event already reaches the v2 logger with call_type list_mcp_tools, but _emit_mcp_tool_call only matched call_mcp_tool, so listing fell through to the LLM-call path and emitted nothing. This adds a dedicated MCP_LIST_TOOLS span role with its own MCPListToolsSpanData, emitted from a sibling _emit_mcp_list_tools branch that mirrors the tools/call path Per the OTel GenAI MCP semantic conventions the span is named tools/list (the method name alone, since there is no low-cardinality target), is a CLIENT span parented to the request span, and carries mcp.method.name plus the call id. It deliberately omits gen_ai.operation.name and gen_ai.tool.name, which the convention reserves for tool executions, since listing runs no tool * fix(otel): anchor MCP spans to params._meta trace context, not the transport span MCP streamable-HTTP multiplexes many JSON-RPC messages over one session, so the request-root anchor captured on initialize persisted and every later message's span (tools/call, tools/list) nested under it. A tools/list run 44s after the initialize rendered 44s to the right of its parent with a clock-skew warning, because the MCP message and the HTTP transport are independent lifecycles Following the OTel GenAI MCP semantic conventions, an MCP span now parents to the W3C trace context the client propagated in the request's params._meta (a remote parent, per SEP-414), records the transport/session span as a span link rather than the parent, and starts its own root trace when nothing was propagated. The MCP gateway captures traceparent/tracestate/baggage from each message's params._meta into a per-message contextvar that the otel_v2 emitter reads; opentelemetry stays an optional dependency via guarded lazy imports This applies to tools/call as well as the new tools/list span, since both shared the same transport-anchoring bug * fix(otel): drop client baggage from MCP params._meta to prevent identity spoofing The MCP trace propagation added a W3CBaggagePropagator, so resolve_mcp_span_context extracted the client's W3C Baggage from params._meta into the span's parent context. The LiteLLMBaggageSpanProcessor then stamps allowlisted baggage keys onto the span, and the list-tools/tool-call mappers don't set those identity keys, so nothing overwrites them. A malicious MCP client could send params._meta.baggage: litellm.team.id=...,litellm.metadata.user_api_key_user_id=... and have those identity attributes attributed to its spans. Extract trace context only (traceparent/tracestate) in the propagator, and stop collecting the baggage key at the source in _mcp_meta_trace_carrier. Parenting to the client's trace context, the actual goal, needs only trace context; remote baggage had no legitimate consumer here. Regression tests at both layers assert a spoofed params._meta.baggage never lands as a span identity attribute. * style(mcp): clear ruff strict-budget breach in otel trace-carrier helpers The otel MCP trace-carrier helpers added in this branch pushed the BLE001 and UP006 strict-rule totals past their ceilings. Use PEP 585 `dict[str, str]` instead of `Dict`, and narrow the optional-import guards to `except ImportError` (the only failure these can hit, matching the "when otel_v2 is unavailable" intent) instead of a blind `except Exception`. * fix(otel): stamp authenticated identity baggage onto MCP spans Parenting MCP spans to the client's params._meta trace context over an empty Context() meant the tool-call and tools/list spans carried no team/key/metadata identity at all, so they couldn't be attributed or filtered by team in a traces backend. The LLM-call span already re-seeds identity from the parsed, authenticated StandardLoggingPayload rather than trusting ambient/remote context; extract that into a shared _seed_identity_baggage helper and run both MCP emitters through it. Identity comes only from the authenticated payload, never the client carrier, so this keeps the earlier spoofing fix intact while restoring attribution. Regression tests assert the authenticated team lands on both MCP spans and that a spoofed params._meta.baggage value can't override it. * refactor(otel): model MCP spans as roots that link the transport in SPAN_REGISTRY --- litellm/integrations/otel/__init__.py | 4 + litellm/integrations/otel/emitter.py | 21 +- litellm/integrations/otel/logger.py | 85 ++++++-- litellm/integrations/otel/mappers/base.py | 3 +- litellm/integrations/otel/mappers/genai.py | 12 ++ litellm/integrations/otel/model/payloads.py | 38 ++++ litellm/integrations/otel/model/spans.py | 36 +++- litellm/integrations/otel/plumbing/context.py | 61 +++++- .../proxy/_experimental/mcp_server/server.py | 56 +++++ .../integrations/otel/test_otel_v2_logger.py | 192 +++++++++++++++++- .../otel/test_otel_v2_sources_of_truth.py | 19 +- .../mcp_server/test_mcp_server.py | 51 +++++ 12 files changed, 547 insertions(+), 31 deletions(-) diff --git a/litellm/integrations/otel/__init__.py b/litellm/integrations/otel/__init__.py index da3ce4af3e7..7f78f7156b4 100644 --- a/litellm/integrations/otel/__init__.py +++ b/litellm/integrations/otel/__init__.py @@ -32,11 +32,13 @@ from litellm.integrations.otel.model.payloads import ( LLMCallSpanData, LLMRequestParams, LLMUsage, + MCPListToolsSpanData, MCPToolCallSpanData, ProxyRequestSpanData, ServerInfo, ServiceSpanData, SpanError, + is_mcp_list_tools, is_mcp_tool_call, ) from litellm.integrations.otel.model.semconv import ( @@ -106,6 +108,7 @@ __all__ = [ "LLMCallSpanData", "LLMRequestParams", "LLMUsage", + "MCPListToolsSpanData", "MCPToolCallSpanData", "ProxyRequestSpanData", "RequestContext", @@ -113,6 +116,7 @@ __all__ = [ "ServerInfo", "ServiceSpanData", "SpanError", + "is_mcp_list_tools", "is_mcp_tool_call", "promoted_baggage", ] diff --git a/litellm/integrations/otel/emitter.py b/litellm/integrations/otel/emitter.py index 69fc53c5b9d..8441cbae834 100644 --- a/litellm/integrations/otel/emitter.py +++ b/litellm/integrations/otel/emitter.py @@ -4,7 +4,7 @@ from collections import OrderedDict from typing import Callable, Sequence from opentelemetry.context import Context -from opentelemetry.trace import Span, Tracer +from opentelemetry.trace import Link, Span, Tracer from opentelemetry.trace.status import Status, StatusCode from litellm.integrations.otel.model.config import OpenTelemetryV2Config @@ -13,6 +13,7 @@ from litellm.integrations.otel.mappers.base import AttributeMapper, SpanData from litellm.integrations.otel.model.payloads import ( GuardrailSpanData, LLMCallSpanData, + MCPListToolsSpanData, MCPToolCallSpanData, ServiceSpanData, ) @@ -23,6 +24,7 @@ from litellm.integrations.otel.model.spans import ( SpanRole, guardrail_span_name, llm_call_span_name, + mcp_list_tools_span_name, mcp_tool_call_span_name, service_span_name, ) @@ -33,6 +35,7 @@ from litellm.integrations.otel.model.spans import ( _NAME_BUILDERS: dict[SpanRole, Callable[..., str]] = { SpanRole.LLM_CALL: llm_call_span_name, SpanRole.MCP_TOOL_CALL: mcp_tool_call_span_name, + SpanRole.MCP_LIST_TOOLS: mcp_list_tools_span_name, SpanRole.GUARDRAIL: guardrail_span_name, # DB_CALL and SERVICE are both built from ServiceSpanData; they differ only in # span kind (CLIENT vs INTERNAL) and attribute vocabulary, not in naming. @@ -74,18 +77,21 @@ class SpanEmitter: start_time_ns: int | None = None, *, tracer: Tracer | None = None, + links: Sequence[Link] | None = None, ) -> Span: """Start a span for ``role`` without dedup or attribute mapping. For callers that own and manage their own span lifecycle. ``tracer`` overrides the bound tracer for this span only, used for per-request - multi-tenant credential routing. + multi-tenant credential routing. ``links`` records related-but-not-parent + spans (e.g. the transport span of an MCP message, per MCP semconv). """ return (tracer or self._tracer).start_span( name, context=parent_context, kind=to_otel_span_kind(SPAN_REGISTRY[role].kind), start_time=start_time_ns, + links=list(links) if links else None, ) def _seen(self, dedup_key: str | None, role: SpanRole) -> bool: @@ -116,16 +122,23 @@ class SpanEmitter: start_time_ns: int | None = None, end_time_ns: int | None = None, tracer: Tracer | None = None, + links: Sequence[Link] | None = None, ) -> Span | None: """Emit one complete span: dedup, start, map attributes, status, end. Return the span, or ``None`` if it was deduplicated away. ``tracer`` overrides the bound tracer for this span, used for per-request routing. + ``links`` records related-but-not-parent spans (the transport span of an + MCP message). """ # LLM-call and MCP tool-call spans carry a dedup key (their request's # call id), so a sync+async double-firing coalesces. ``isinstance`` narrows # the type for mypy and keeps the engine free of duck-typed attribute reads. - dedup_key = data.identity.call_id if isinstance(data, (LLMCallSpanData, MCPToolCallSpanData)) else None + dedup_key = ( + data.identity.call_id + if isinstance(data, (LLMCallSpanData, MCPToolCallSpanData, MCPListToolsSpanData)) + else None + ) if self._seen(dedup_key, role): return None span = self.start_span( @@ -134,6 +147,7 @@ class SpanEmitter: parent_context=parent_context, start_time_ns=start_time_ns, tracer=tracer, + links=links, ) self.finish_span(role, span, data, end_time_ns=end_time_ns) return span @@ -166,6 +180,7 @@ class SpanEmitter: ( LLMCallSpanData, MCPToolCallSpanData, + MCPListToolsSpanData, ServiceSpanData, GuardrailSpanData, ), diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py index 44484559948..5e729e12be0 100644 --- a/litellm/integrations/otel/logger.py +++ b/litellm/integrations/otel/logger.py @@ -5,7 +5,7 @@ from contextlib import contextmanager from datetime import datetime from typing import TYPE_CHECKING, Any, Callable, Iterator, Mapping, Sequence, cast -from opentelemetry.context import attach, get_current +from opentelemetry.context import Context, attach, get_current from opentelemetry.sdk.trace import TracerProvider from opentelemetry.trace import Span, Tracer, get_current_span, use_span @@ -17,6 +17,7 @@ from litellm.integrations.otel.model.config import OpenTelemetryV2Config from litellm.integrations.otel.plumbing.context import ( is_recordable_span, request_root_span, + resolve_mcp_span_context, resolve_parent_context, resolve_request_span_context, set_request_baggage, @@ -32,9 +33,11 @@ from litellm.integrations.otel.model.metadata import ( from litellm.integrations.otel.model.payloads import ( GuardrailSpanData, LLMCallSpanData, + MCPListToolsSpanData, MCPToolCallSpanData, ServiceSpanData, SpanError, + is_mcp_list_tools, is_mcp_tool_call, ) from litellm.integrations.otel.plumbing.metrics import ( @@ -218,6 +221,8 @@ class OpenTelemetryV2(CustomLogger): async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): if self._emit_mcp_tool_call(kwargs, start_time, end_time): return + if self._emit_mcp_list_tools(kwargs, start_time, end_time): + return self._close_llm_call(kwargs, start_time, end_time) self._record_metrics(kwargs, response_obj, start_time, end_time) @@ -242,8 +247,24 @@ class OpenTelemetryV2(CustomLogger): async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): if self._emit_mcp_tool_call(kwargs, start_time, end_time): return + if self._emit_mcp_list_tools(kwargs, start_time, end_time): + return self._close_llm_call(kwargs, start_time, end_time) + def _seed_identity_baggage(self, identity: RequestIdentity, model: str | None, context: Context) -> Context: + """Seed authenticated request-identity Baggage onto ``context`` so the Baggage + processor stamps team/key/metadata onto the span. Identity is read from the + parsed payload, never the client's ``params._meta`` carrier, so it can't be + spoofed.""" + bag = promoted_baggage( + identity, + model, + promoted_keys=tuple(self.config.baggage_promoted_keys), + metadata_keys=tuple(self.config.baggage_metadata_keys), + team_metadata_keys=tuple(self.config.baggage_team_metadata_keys), + ) + return set_request_baggage(bag, context=context) if bag else context + def _emit_mcp_tool_call( self, kwargs: Mapping[str, Any], @@ -254,10 +275,12 @@ class OpenTelemetryV2(CustomLogger): MCP tool calls reach the success/failure callbacks like any other request (with ``call_type`` ``call_mcp_tool``), but they are not LLM calls and have - no ``pre_call`` carrier — so they get their own CLIENT span here, parented - to the request's server span. Returns whether it handled the event, so the - caller skips the LLM-call path. The whole span is emitted at once (there is - no boundary to open it at), deduped on the call id by the emitter. + no ``pre_call`` carrier — so they get their own CLIENT span here. Per the MCP + semconv it parents to the trace context the client propagated in + ``params._meta`` (or starts a new root) and links the transport span, rather + than nesting under the HTTP/session span. Returns whether it handled the + event, so the caller skips the LLM-call path. The whole span is emitted at + once (there is no boundary to open it at), deduped on the call id. """ raw_payload = kwargs.get("standard_logging_object") if not raw_payload or not is_mcp_tool_call(cast(Mapping[str, object], raw_payload)): @@ -271,12 +294,51 @@ class OpenTelemetryV2(CustomLogger): # as a phantom LLM span. if data.identity.call_id: self._open_llm_calls.pop(data.identity.call_id, None) + parent_context, links = resolve_mcp_span_context() + parent_context = self._seed_identity_baggage(data.identity, None, parent_context) self._emitter.emit( SpanRole.MCP_TOOL_CALL, data, - parent_context=resolve_request_span_context(), + parent_context=parent_context, start_time_ns=to_ns(start_time), end_time_ns=to_ns(end_time), + links=links, + ) + return True + + def _emit_mcp_list_tools( + self, + kwargs: Mapping[str, object], + start_time: datetime | float | None, + end_time: datetime | float | None, + ) -> bool: + """Emit an MCP ``tools/list`` span when the closed request was a discovery call. + + Like a tool call, listing reaches the success/failure callbacks (here with + ``call_type`` ``list_mcp_tools``) with no ``pre_call`` carrier, so it gets its + own CLIENT span. Per the MCP semconv it parents to the ``params._meta`` trace + context (or starts a new root) and links the transport span, rather than + nesting under the HTTP/session span. Returns whether it handled the event so + the caller skips the LLM-call path. + """ + raw_payload = kwargs.get("standard_logging_object") + if not raw_payload or not is_mcp_list_tools(cast(Mapping[str, object], raw_payload)): + return False + payload = cast("StandardLoggingPayload", raw_payload) + data = MCPListToolsSpanData.from_standard_logging_payload( + payload, capture_content=self.config.capture_span_content + ) + if data.identity.call_id: + self._open_llm_calls.pop(data.identity.call_id, None) + parent_context, links = resolve_mcp_span_context() + parent_context = self._seed_identity_baggage(data.identity, None, parent_context) + self._emitter.emit( + SpanRole.MCP_LIST_TOOLS, + data, + parent_context=parent_context, + start_time_ns=to_ns(start_time), + end_time_ns=to_ns(end_time), + links=links, ) return True @@ -319,16 +381,7 @@ class OpenTelemetryV2(CustomLogger): # root span — parent to it (ambient fallback on the SDK path). Seed identity # Baggage so the span — and the SDK path, which has none — is labeled # consistently. - parent_ctx = resolve_request_span_context() - bag = promoted_baggage( - data.identity, - data.request_model, - promoted_keys=tuple(self.config.baggage_promoted_keys), - metadata_keys=tuple(self.config.baggage_metadata_keys), - team_metadata_keys=tuple(self.config.baggage_team_metadata_keys), - ) - if bag: - parent_ctx = set_request_baggage(bag, context=parent_ctx) + parent_ctx = self._seed_identity_baggage(data.identity, data.request_model, resolve_request_span_context()) return self._emitter.emit( SpanRole.LLM_CALL, data, diff --git a/litellm/integrations/otel/mappers/base.py b/litellm/integrations/otel/mappers/base.py index 6685e34578b..809d956a9c7 100644 --- a/litellm/integrations/otel/mappers/base.py +++ b/litellm/integrations/otel/mappers/base.py @@ -7,6 +7,7 @@ from typing_extensions import Protocol, runtime_checkable from litellm.integrations.otel.model.payloads import ( GuardrailSpanData, LLMCallSpanData, + MCPListToolsSpanData, MCPToolCallSpanData, ServiceSpanData, ) @@ -20,7 +21,7 @@ AttributeMap = dict[str, AttrValue] # The closed set of span-data types the engine routes through the mapper chain. # Server spans (PROXY_REQUEST + management routes) belong to the mounted FastAPI # instrumentor, not the mapper chain. -SpanData = LLMCallSpanData | MCPToolCallSpanData | GuardrailSpanData | ServiceSpanData +SpanData = LLMCallSpanData | MCPToolCallSpanData | MCPListToolsSpanData | GuardrailSpanData | ServiceSpanData @runtime_checkable diff --git a/litellm/integrations/otel/mappers/genai.py b/litellm/integrations/otel/mappers/genai.py index ad6d3e7ff21..c5d8c35de7d 100644 --- a/litellm/integrations/otel/mappers/genai.py +++ b/litellm/integrations/otel/mappers/genai.py @@ -19,6 +19,7 @@ from litellm.integrations.otel.mappers.utils import ( from litellm.integrations.otel.model.payloads import ( GuardrailSpanData, LLMCallSpanData, + MCPListToolsSpanData, MCPToolCallSpanData, ServiceSpanData, ToolDefinition, @@ -100,6 +101,15 @@ class GenAIMapper: f"{LiteLLM.COST_PREFIX}total": lambda d: d.response_cost, } + # A tools/list discovery span: the method and session only. Per semconv it must + # NOT carry gen_ai.operation.name (execute_tool) or gen_ai.tool.name — those are + # for tool calls, and listing executes no tool. + _MCP_LIST_ATTRS: dict[str, Callable[[MCPListToolsSpanData], AttrValue | None]] = { + MCP.METHOD_NAME: lambda d: d.method, + MCP.SESSION_ID: lambda d: d.session_id, + LiteLLM.CALL_ID: lambda d: d.identity.call_id or None, + } + _GUARDRAIL_ATTRS: dict[str, Callable[[GuardrailSpanData], AttrValue | None]] = { LiteLLM.GUARDRAIL_NAME: lambda d: d.guardrail_name, LiteLLM.GUARDRAIL_MODE: lambda d: d.mode, @@ -130,6 +140,8 @@ class GenAIMapper: return self._llm_call(data) case MCPToolCallSpanData(): return collect(self._MCP_ATTRS, data) + case MCPListToolsSpanData(): + return collect(self._MCP_LIST_ATTRS, data) case GuardrailSpanData(): return self._guardrail(data) case ServiceSpanData(): diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py index a368a862024..b0dcf97b787 100644 --- a/litellm/integrations/otel/model/payloads.py +++ b/litellm/integrations/otel/model/payloads.py @@ -37,12 +37,14 @@ __all__ = [ "LLMCost", "LLMRequestParams", "LLMUsage", + "MCPListToolsSpanData", "MCPToolCallSpanData", "ProxyRequestSpanData", "ServerInfo", "ServiceSpanData", "SpanError", "ToolDefinition", + "is_mcp_list_tools", "is_mcp_tool_call", ] @@ -415,6 +417,42 @@ def is_mcp_tool_call(payload: Mapping[str, object]) -> bool: return bool(_mcp_tool_call_metadata(payload)) or (payload.get("call_type") == "call_mcp_tool") +@dataclass(frozen=True) +class MCPListToolsSpanData: + """One MCP ``tools/list`` discovery call, parsed from a closed request's payload. + + The proxy is an MCP *client* enumerating an upstream server's tools, so this is + a CLIENT span. It carries neither ``gen_ai.operation.name`` nor ``gen_ai.tool.name``: + the GenAI semconv sets ``execute_tool`` (and the tool name) only for tool *calls*, + and listing executes no tool. + """ + + method: str + session_id: str | None + error: SpanError | None + identity: RequestIdentity + + @classmethod + def from_standard_logging_payload( + cls, payload: StandardLoggingPayload, capture_content: bool = False + ) -> MCPListToolsSpanData: + # The list-tools logging path does not thread an MCP session id into the + # payload (only the tool-call path stamps ``mcp_tool_call_metadata``), so + # there is none to read here; ``mcp.session.id`` is simply omitted. + return cls( + method=MCPMethod.TOOLS_LIST.value, + session_id=None, + error=_parse_error(payload), + identity=RequestContext.from_standard_logging_payload(payload).identity, + ) + + +def is_mcp_list_tools(payload: Mapping[str, object]) -> bool: + """Whether a closed request's payload is an MCP ``tools/list`` discovery call + rather than a tool call or an LLM call — true when the call type says so.""" + return payload.get("call_type") == "list_mcp_tools" + + # --- service event_metadata sanitization ------------------------------------ # # Substrings (case-insensitive) of keys that must never reach a span: secrets, diff --git a/litellm/integrations/otel/model/spans.py b/litellm/integrations/otel/model/spans.py index bc624cf6a57..c93f95ec97d 100644 --- a/litellm/integrations/otel/model/spans.py +++ b/litellm/integrations/otel/model/spans.py @@ -18,6 +18,13 @@ before the LLM call even starts), so a guardrail is a sibling of the LLM call, not a child of it. The emitter parents every span to the ambient OTel context (the active server span), which matches this. +MCP spans (``MCP_TOOL_CALL``, ``MCP_LIST_TOOLS``) are intentionally NOT in this +tree. Per the OTel GenAI MCP semconv, MCP and the HTTP transport are independent +contexts, so an MCP span parents to the trace context the client propagated in +``params._meta`` (or starts its own root when none is propagated) and records the +``PROXY_REQUEST`` transport span as a span *link*, never a parent. The registry +encodes this as ``parent=None, links=PROXY_REQUEST``. + Not every service call becomes a span — :func:`span_role_for_service` decides: - ``DB_CALL`` (CLIENT) — outbound datastores (redis, postgres, @@ -46,6 +53,7 @@ if TYPE_CHECKING: from litellm.integrations.otel.model.payloads import ( GuardrailSpanData, LLMCallSpanData, + MCPListToolsSpanData, MCPToolCallSpanData, ProxyRequestSpanData, ServiceSpanData, @@ -56,6 +64,7 @@ class SpanRole(str, Enum): PROXY_REQUEST = "proxy_request" LLM_CALL = "llm_call" MCP_TOOL_CALL = "mcp_tool_call" + MCP_LIST_TOOLS = "mcp_list_tools" GUARDRAIL = "guardrail" DB_CALL = "db_call" SERVICE = "service" @@ -74,14 +83,24 @@ class SpanSpec: role: SpanRole kind: LiteLLMSpanKind parent: SpanRole | None + links: SpanRole | None = None SPAN_REGISTRY: dict[SpanRole, SpanSpec] = { SpanRole.PROXY_REQUEST: SpanSpec(SpanRole.PROXY_REQUEST, LiteLLMSpanKind.SERVER, parent=None), SpanRole.LLM_CALL: SpanSpec(SpanRole.LLM_CALL, LiteLLMSpanKind.CLIENT, parent=SpanRole.PROXY_REQUEST), - # The proxy is an MCP client to the upstream server it dispatches the tool - # call to, so this is a CLIENT span, sibling of the LLM call under the request. - SpanRole.MCP_TOOL_CALL: SpanSpec(SpanRole.MCP_TOOL_CALL, LiteLLMSpanKind.CLIENT, parent=SpanRole.PROXY_REQUEST), + # MCP and the HTTP transport are independent contexts (OTel GenAI MCP semconv), + # so an MCP span does not nest under the transport span. The proxy is an MCP + # client to the upstream server, so it's a CLIENT span; it parents to the trace + # context the client propagated in ``params._meta`` (or starts its own root when + # none is propagated) and records the PROXY_REQUEST transport span as a span + # *link*, never a parent — hence ``parent=None, links=PROXY_REQUEST``. + SpanRole.MCP_TOOL_CALL: SpanSpec( + SpanRole.MCP_TOOL_CALL, LiteLLMSpanKind.CLIENT, parent=None, links=SpanRole.PROXY_REQUEST + ), + SpanRole.MCP_LIST_TOOLS: SpanSpec( + SpanRole.MCP_LIST_TOOLS, LiteLLMSpanKind.CLIENT, parent=None, links=SpanRole.PROXY_REQUEST + ), SpanRole.GUARDRAIL: SpanSpec(SpanRole.GUARDRAIL, LiteLLMSpanKind.INTERNAL, parent=SpanRole.PROXY_REQUEST), SpanRole.DB_CALL: SpanSpec(SpanRole.DB_CALL, LiteLLMSpanKind.CLIENT, parent=SpanRole.PROXY_REQUEST), SpanRole.SERVICE: SpanSpec(SpanRole.SERVICE, LiteLLMSpanKind.INTERNAL, parent=SpanRole.PROXY_REQUEST), @@ -163,6 +182,12 @@ def mcp_tool_call_span_name(data: "MCPToolCallSpanData") -> str: return f"{data.method} {data.tool_name}".strip() +def mcp_list_tools_span_name(data: "MCPListToolsSpanData") -> str: + """``"{mcp.method.name}"`` i.e. ``"tools/list"`` — no low-cardinality target, so + the method name alone names the span (MCP semconv).""" + return data.method + + def proxy_request_span_name(data: "ProxyRequestSpanData") -> str: """``"{method} {route}"`` (HTTP semconv).""" return f"{data.http_method} {data.route}".strip() @@ -179,7 +204,8 @@ def service_span_name(data: "ServiceSpanData") -> str: def root_roles() -> list[SpanRole]: - """Roles that start a new trace (no in-process parent).""" + """Roles with no in-process parent. They start a new trace unless they adopt a + remote parent (e.g. an MCP span joining the client's propagated context).""" return [role for role, spec in SPAN_REGISTRY.items() if spec.parent is None] @@ -196,6 +222,8 @@ def validate_registry( raise ValueError(f"SPAN_REGISTRY[{role}] has mismatched role {spec.role}") if spec.parent is not None and spec.parent not in reg: raise ValueError(f"span role {role} declares unknown parent {spec.parent}") + if spec.links is not None and spec.links not in reg: + raise ValueError(f"span role {role} declares unknown link target {spec.links}") missing = [role for role in SpanRole if role not in reg] if missing: raise ValueError(f"SPAN_REGISTRY is missing roles: {missing}") diff --git a/litellm/integrations/otel/plumbing/context.py b/litellm/integrations/otel/plumbing/context.py index ff513c84d95..8acac112c3d 100644 --- a/litellm/integrations/otel/plumbing/context.py +++ b/litellm/integrations/otel/plumbing/context.py @@ -1,11 +1,11 @@ """Trace-context + Baggage helpers.""" -from contextvars import ContextVar +from contextvars import ContextVar, Token from typing import Mapping from opentelemetry import baggage from opentelemetry.context import Context, get_current -from opentelemetry.trace import Span, get_current_span, set_span_in_context +from opentelemetry.trace import Link, Span, get_current_span, set_span_in_context from opentelemetry.trace.propagation.tracecontext import ( TraceContextTextMapPropagator, ) @@ -47,6 +47,31 @@ def request_root_span() -> "Span | None": return span if is_recordable_span(span) else None +# The W3C trace-context carrier (``traceparent``/``tracestate``/``baggage``) the +# MCP client propagated in the current request's ``params._meta``. The MCP gateway +# sets it per message so the MCP span can parent to the client's span rather than +# to the transport. A ``ContextVar`` because, like the root-span anchor, it must +# ride the request task and be readable by the inline success-logging callback. +_mcp_message_trace_carrier: "ContextVar[Mapping[str, str] | None]" = ContextVar( + "litellm_otel_mcp_message_trace_carrier", default=None +) + + +def set_mcp_message_trace_carrier( + carrier: "Mapping[str, str] | None", +) -> "Token[Mapping[str, str] | None]": + """Stash the current MCP message's propagated trace-context carrier. + + Returns the reset token; the caller must reset it once the message is handled + so the carrier never leaks to the next message on the same session task. + """ + return _mcp_message_trace_carrier.set(carrier) + + +def reset_mcp_message_trace_carrier(token: "Token[Mapping[str, str] | None]") -> None: + _mcp_message_trace_carrier.reset(token) + + def set_request_baggage(values: Mapping[str, str], context: Context | None = None) -> Context: """Return a context with ``values`` written into Baggage.""" ctx = context @@ -104,6 +129,38 @@ def resolve_request_span_context() -> Context: return get_current() +def resolve_mcp_span_context( + carrier: "Mapping[str, str] | None" = None, +) -> "tuple[Context, tuple[Link, ...]]": + """Parent context + links for an MCP message span, per the OTel GenAI MCP semconv. + + MCP and the underlying transport (HTTP) are independent lifecycles — one + streamable-HTTP session multiplexes many messages, so nesting the message span + under the HTTP/session span is wrong (it renders the message at the session's + start, skewed by however long the session has been open). Instead: + + * parent to the trace context the client propagated in the request's + ``params._meta`` (a *remote* parent), and + * record the transport/session span as a *link*, never the parent. + + Only trace context (``traceparent``/``tracestate``) is extracted, never the + client's W3C Baggage: ``params._meta`` is caller-controlled, and the otel + baggage processor stamps allowlisted baggage keys (``litellm.team.id``, + ``litellm.metadata.*``, ...) onto the span as attributes, so honoring remote + baggage would let a client spoof a span's identity attribution. + + With no propagated context the returned context carries no span, so the span + starts its own root trace (still linked to the transport). The base context is + explicitly empty so an absent ``traceparent`` can never fall through to the + ambient (stale session) span. + """ + source = carrier if carrier is not None else _mcp_message_trace_carrier.get() + parent = _PROPAGATOR.extract(dict(source or {}), context=Context()) + transport = request_root_span() + links = (Link(transport.get_span_context()),) if transport is not None else () + return parent, links + + def is_recordable_span(obj: object) -> bool: """True if ``obj`` is a live span with a valid context (safe to parent under).""" if not isinstance(obj, Span): diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index 4b55510a629..158fdda6c39 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -229,6 +229,56 @@ def _jsonrpc_text_has_top_level_method(text: str) -> bool: return False +def _mcp_meta_trace_carrier(req_ctx: object) -> Optional[dict[str, str]]: + """The W3C trace context (``traceparent``/``tracestate``) the MCP client + propagated in the request's ``params._meta`` (SEP-414), or ``None``. + + Per the OTel MCP semconv the MCP span parents to this propagated context rather + than to the HTTP/session transport (which is recorded as a link instead), so a + streamable-HTTP session that multiplexes many messages does not glue every + message under the session's first request. The client's W3C Baggage is + deliberately excluded: it is caller-controlled, and the otel baggage processor + stamps allowlisted baggage keys (``litellm.team.id``, ``litellm.metadata.*``, + ...) onto the span, so honoring remote baggage would let a client spoof a + span's identity attribution. + """ + meta = getattr(req_ctx, "meta", None) + extra = getattr(meta, "model_extra", None) + if not isinstance(extra, dict): + return None + carrier = {key: extra[key] for key in ("traceparent", "tracestate") if isinstance(extra.get(key), str)} + return carrier or None + + +def _otel_set_mcp_trace_carrier(carrier: Optional[dict[str, str]]) -> object: + """Stash ``carrier`` for the otel_v2 MCP span and return a reset token, or + ``None`` when otel_v2 is unavailable. Lazily imported so opentelemetry stays an + optional dependency.""" + try: + from litellm.integrations.otel.plumbing.context import ( + set_mcp_message_trace_carrier, + ) + + return set_mcp_message_trace_carrier(carrier) + except ImportError: + return None + + +def _otel_reset_mcp_trace_carrier(token: object) -> None: + """Clear the per-message trace carrier so it never leaks to the next message on + the same session task. Paired with ``_otel_set_mcp_trace_carrier``.""" + if token is None: + return + try: + from litellm.integrations.otel.plumbing.context import ( + reset_mcp_message_trace_carrier, + ) + + reset_mcp_message_trace_carrier(token) + except ImportError: + return + + def _proxy_exception_to_http_exception(exc: ProxyException) -> HTTPException: """Map a ``ProxyException`` to an ``HTTPException`` that preserves its real status code and headers. @@ -595,8 +645,10 @@ if MCP_AVAILABLE: _session_reset_token = None if req_ctx: _session_reset_token = active_mcp_session_var.set(req_ctx.session) + _trace_token = None try: + _trace_token = _otel_set_mcp_trace_carrier(_mcp_meta_trace_carrier(req_ctx)) # Get user authentication from context variable ( user_api_key_auth, @@ -632,6 +684,7 @@ if MCP_AVAILABLE: # This prevents the HTTP stream from failing and allows the client to get a response return [] finally: + _otel_reset_mcp_trace_carrier(_trace_token) if _session_reset_token is not None: active_mcp_session_var.reset(_session_reset_token) @@ -658,8 +711,10 @@ if MCP_AVAILABLE: _session_reset_token = None if req_ctx: _session_reset_token = active_mcp_session_var.set(req_ctx.session) + _trace_token = None try: + _trace_token = _otel_set_mcp_trace_carrier(_mcp_meta_trace_carrier(req_ctx)) # Validate arguments ( user_api_key_auth, @@ -778,6 +833,7 @@ if MCP_AVAILABLE: return response finally: + _otel_reset_mcp_trace_carrier(_trace_token) if _session_reset_token is not None: active_mcp_session_var.reset(_session_reset_token) diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py index 0ceb7efbe0b..674b2bec829 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_logger.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_logger.py @@ -27,9 +27,11 @@ from litellm.integrations.otel import ( # noqa: E402 OpenTelemetryV2Config, ) from litellm.integrations.otel.plumbing import providers # noqa: E402 -from litellm.integrations.otel.plumbing.context import ( +from litellm.integrations.otel.plumbing.context import ( # noqa: E402 + reset_mcp_message_trace_carrier, + set_mcp_message_trace_carrier, set_request_root_span, -) # noqa: E402 +) from litellm.integrations.otel.logger import OpenTelemetryV2 # noqa: E402 from litellm.integrations.otel.model.spans import ( # noqa: E402 LITELLM_PROXY_REQUEST_SPAN_NAME, @@ -53,8 +55,10 @@ def _reset_request_root_span(): from litellm.integrations.otel.plumbing import context as _otel_context _otel_context._request_root_span.set(None) + _otel_context._mcp_message_trace_carrier.set(None) yield _otel_context._request_root_span.set(None) + _otel_context._mcp_message_trace_carrier.set(None) def _payload(**overrides): @@ -387,6 +391,190 @@ def test_mcp_tool_call_metadata_read_from_nested_metadata_not_top_level(): assert LiteLLM.MCP_SERVER_NAME not in span.attributes +def _mcp_list_payload(**overrides): + payload = { + "call_type": "list_mcp_tools", + "status": "success", + "litellm_call_id": "mcp_list_1", + "metadata": { + "user_api_key_team_id": "t1", + "spend_logs_metadata": {"mcp_operation": "list_tools"}, + }, + "hidden_params": {}, + } + payload.update(overrides) + return payload + + +def test_mcp_list_tools_emits_client_span(): + """An MCP ``tools/list`` discovery call becomes a CLIENT span named ``tools/list``, + carrying only the MCP method and the call id. Per the GenAI MCP semconv the list + span omits ``gen_ai.operation.name`` and ``gen_ai.tool.name`` (tool-call-only) and + ``mcp.session.id`` (the list path threads no session id), so a naive reuse of the + tool-call mapper would wrongly stamp them, and the pre-fix code emitted no span at + all for a ``list_mcp_tools`` payload.""" + logger, exporter = _logger() + kwargs = {"standard_logging_object": _mcp_list_payload()} + asyncio.run(logger.async_log_success_event(kwargs, None, None, None)) + (span,) = exporter.get_finished_spans() + assert span.name == "tools/list" + assert span.kind is SpanKind.CLIENT + assert span.attributes["mcp.method.name"] == "tools/list" + assert span.attributes[LiteLLM.CALL_ID] == "mcp_list_1" + assert span.status.status_code is StatusCode.UNSET + # Bug-killers: no span pre-fix (empty exporter -> the unpack above raises), and a + # tool-call-shaped fix would leak execute_tool / tool name / session id here. + assert GenAI.OPERATION_NAME not in span.attributes + assert "gen_ai.tool.name" not in span.attributes + assert "mcp.session.id" not in span.attributes + + +_MCP_SPAN_CASES = [ + (_mcp_payload, "tools/call get_weather"), + (_mcp_list_payload, "tools/list"), +] + + +@pytest.mark.parametrize("make_payload, span_name", _MCP_SPAN_CASES) +def test_mcp_span_roots_and_links_transport_without_propagated_context( + make_payload, span_name +): + """MCP and the HTTP transport are independent lifecycles (one streamable-HTTP + session multiplexes many messages), so per the MCP semconv the message span + must NOT nest under the session/transport span — that is what made it render + skewed at the session's start. With no propagated ``params._meta`` context it + starts its own root trace and records the transport span as a *link*, never + the parent.""" + logger, exporter = _logger() + transport = logger._emitter.start_span( + SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME + ) + set_request_root_span(transport) + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": make_payload()}, None, None, None + ) + ) + transport.end() + span = next(s for s in exporter.get_finished_spans() if s.name == span_name) + assert span.parent is None + assert span.context.trace_id != transport.get_span_context().trace_id + assert [link.context.span_id for link in span.links] == [ + transport.get_span_context().span_id + ] + + +@pytest.mark.parametrize("make_payload, span_name", _MCP_SPAN_CASES) +def test_mcp_span_parents_to_propagated_meta_trace_context(make_payload, span_name): + """When the client propagates W3C trace context in the request's + ``params._meta`` (SEP-414), the MCP span parents to it (one distributed trace) + and still links the transport span — never falling through to the + ambient/session span.""" + logger, exporter = _logger() + transport = logger._emitter.start_span( + SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME + ) + set_request_root_span(transport) + token = set_mcp_message_trace_carrier( + {"traceparent": "00-11111111111111111111111111111111-2222222222222222-01"} + ) + try: + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": make_payload()}, None, None, None + ) + ) + finally: + reset_mcp_message_trace_carrier(token) + transport.end() + span = next(s for s in exporter.get_finished_spans() if s.name == span_name) + assert span.context.trace_id == 0x11111111111111111111111111111111 + assert span.parent is not None + assert span.parent.span_id == 0x2222222222222222 + assert [link.context.span_id for link in span.links] == [ + transport.get_span_context().span_id + ] + + +@pytest.mark.parametrize("make_payload, span_name", _MCP_SPAN_CASES) +def test_mcp_span_ignores_client_supplied_baggage(make_payload, span_name): + """The MCP span must NOT honor W3C Baggage from the client's ``params._meta``. + + ``params._meta`` is caller-controlled and the baggage processor stamps + allowlisted baggage keys onto every span, so extracting remote baggage would + let a client spoof a span's identity (e.g. ``litellm.team.id``). The propagator + extracts trace context only, so the spoofed keys never reach the span while the + legitimate traceparent parenting still works.""" + logger, exporter = _logger() + transport = logger._emitter.start_span( + SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME + ) + set_request_root_span(transport) + token = set_mcp_message_trace_carrier( + { + "traceparent": "00-11111111111111111111111111111111-2222222222222222-01", + "baggage": "litellm.team.id=spoofed-team,litellm.metadata.user_api_key_user_id=attacker", + } + ) + try: + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": make_payload()}, None, None, None + ) + ) + finally: + reset_mcp_message_trace_carrier(token) + transport.end() + span = next(s for s in exporter.get_finished_spans() if s.name == span_name) + # Trace context still honored: proves the carrier was processed, not dropped wholesale. + assert span.parent is not None and span.parent.span_id == 0x2222222222222222 + # Identity is the authenticated payload's team, never the client's spoofed value. + assert span.attributes[LiteLLM.TEAM_ID] == "t1" + assert "litellm.metadata.user_api_key_user_id" not in span.attributes + + +@pytest.mark.parametrize("make_payload, span_name", _MCP_SPAN_CASES) +def test_mcp_span_carries_authenticated_identity(make_payload, span_name): + """An MCP span is labeled with the authenticated request's identity (team/key), + seeded from the parsed payload like the LLM-call span. Without this seeding the + span — parented to an empty remote context — would carry no team/key attribute at + all, so it couldn't be attributed or filtered by team in the traces backend.""" + logger, exporter = _logger() + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": make_payload()}, None, None, None + ) + ) + span = next(s for s in exporter.get_finished_spans() if s.name == span_name) + assert span.attributes[LiteLLM.TEAM_ID] == "t1" + + +def test_mcp_span_malformed_traceparent_starts_root(): + """A malformed traceparent in ``params._meta`` must not crash or parent to a + bogus span: the propagator ignores it, so the span starts its own root trace and + still links the transport span.""" + logger, exporter = _logger() + transport = logger._emitter.start_span( + SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME + ) + set_request_root_span(transport) + token = set_mcp_message_trace_carrier({"traceparent": "not-a-valid-traceparent"}) + try: + asyncio.run( + logger.async_log_success_event( + {"standard_logging_object": _mcp_list_payload()}, None, None, None + ) + ) + finally: + reset_mcp_message_trace_carrier(token) + transport.end() + span = next(s for s in exporter.get_finished_spans() if s.name == "tools/list") + assert span.parent is None + assert [link.context.span_id for link in span.links] == [ + transport.get_span_context().span_id + ] + + def test_pre_call_idempotent_keeps_first_span(): """A retried call may re-enter ``pre_call`` with the same call id; the first span (with the true start time) is kept, not replaced.""" diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py index 4bb26a70b02..834a484090f 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py @@ -94,19 +94,32 @@ def test_registry_parent_integrity_no_orphans(): def test_registry_hierarchy_shape(): - assert set(root_roles()) == {SpanRole.PROXY_REQUEST} + # MCP roles have no in-process parent: per the MCP semconv they root (or adopt + # the client's propagated _meta context), so they sit alongside PROXY_REQUEST. + assert set(root_roles()) == { + SpanRole.PROXY_REQUEST, + SpanRole.MCP_TOOL_CALL, + SpanRole.MCP_LIST_TOOLS, + } # Guardrails parent to the request span, not the LLM call: a pre-call # guardrail runs before the LLM call exists, so it's a sibling of it. assert set(child_roles(SpanRole.PROXY_REQUEST)) == { SpanRole.LLM_CALL, - SpanRole.MCP_TOOL_CALL, SpanRole.GUARDRAIL, SpanRole.DB_CALL, SpanRole.SERVICE, } assert SPAN_REGISTRY[SpanRole.LLM_CALL].kind is LiteLLMSpanKind.CLIENT - # The proxy is an MCP client to the upstream tool server: CLIENT span. + # The proxy is an MCP client to the upstream tool server: CLIENT span. Listing + # tools is the same client relationship, so it's a CLIENT span too. assert SPAN_REGISTRY[SpanRole.MCP_TOOL_CALL].kind is LiteLLMSpanKind.CLIENT + assert SPAN_REGISTRY[SpanRole.MCP_LIST_TOOLS].kind is LiteLLMSpanKind.CLIENT + # MCP spans don't nest under the transport: they link the PROXY_REQUEST span + # instead of parenting to it (OTel GenAI MCP semconv). + assert SPAN_REGISTRY[SpanRole.MCP_TOOL_CALL].parent is None + assert SPAN_REGISTRY[SpanRole.MCP_LIST_TOOLS].parent is None + assert SPAN_REGISTRY[SpanRole.MCP_TOOL_CALL].links is SpanRole.PROXY_REQUEST + assert SPAN_REGISTRY[SpanRole.MCP_LIST_TOOLS].links is SpanRole.PROXY_REQUEST assert SPAN_REGISTRY[SpanRole.PROXY_REQUEST].kind is LiteLLMSpanKind.SERVER assert SPAN_REGISTRY[SpanRole.GUARDRAIL].parent is SpanRole.PROXY_REQUEST # An outbound datastore call is a CLIENT span; an internal service is INTERNAL. diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py index 34e932b6ae7..abefb2fd984 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py @@ -6447,3 +6447,54 @@ class TestStreamableHttpAuthErrorMapping: m.get("type") == "http.response.start" and m.get("status") == 500 for m in sent ) + + +class TestMCPMetaTraceCarrier: + """`_mcp_meta_trace_carrier` extracts the W3C trace context the MCP client + propagated in the request's params._meta (SEP-414) so the otel_v2 MCP span can + parent to the client's span. Exercises the real MCP SDK `RequestParams.Meta` + shape (extra='allow' preserves the unprefixed keys), not just an injected + carrier.""" + + def test_extracts_trace_context_and_excludes_baggage_and_other_meta(self): + """Only traceparent/tracestate are carried. The client's W3C ``baggage`` is + deliberately dropped even though it rides in params._meta: it is + caller-controlled, and the otel baggage processor stamps allowlisted baggage + keys onto the span, so honoring it would let a client spoof a span's identity + (e.g. ``litellm.team.id``). Dropping it at the source is the regression guard.""" + from types import SimpleNamespace + + from mcp.types import RequestParams + + from litellm.proxy._experimental.mcp_server.server import ( + _mcp_meta_trace_carrier, + ) + + meta = RequestParams.Meta.model_validate( + { + "traceparent": "00-11111111111111111111111111111111-2222222222222222-01", + "tracestate": "rojo=1", + "baggage": "litellm.team.id=spoofed-team,litellm.metadata.user_api_key_user_id=attacker", + "progressToken": "p1", + } + ) + carrier = _mcp_meta_trace_carrier(SimpleNamespace(meta=meta)) + assert carrier == { + "traceparent": "00-11111111111111111111111111111111-2222222222222222-01", + "tracestate": "rojo=1", + } + assert "baggage" not in carrier + + def test_none_when_no_trace_context(self): + from types import SimpleNamespace + + from mcp.types import RequestParams + + from litellm.proxy._experimental.mcp_server.server import ( + _mcp_meta_trace_carrier, + ) + + assert _mcp_meta_trace_carrier(None) is None + assert _mcp_meta_trace_carrier(SimpleNamespace(meta=None)) is None + only_progress = RequestParams.Meta.model_validate({"progressToken": "p1"}) + assert _mcp_meta_trace_carrier(SimpleNamespace(meta=only_progress)) is None From 1eb712246579bcf27734099155a3145a6aad6e3b Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 20:27:12 +0300 Subject: [PATCH 13/79] test(benchmarks): add CodSpeed benchmarks for inference, MCP and A2A hot paths (#31716) Guard the per-request CPU cost of the chat completion, MCP tool and A2A message transforms against regressions on every commit. All benchmarks are pure in-process work with no network I/O so they stay deterministic under CodSpeed's simulation mode, and they import under the base dependency set the benchmark job installs. Inference covers the full SDK overhead via mock_response (simple, multi-turn, tools, streaming) plus convert_to_model_response_object as a deterministic anchor. MCP covers the client-side tool translation and the proxy server-side tool-name prefix round-trip. A2A covers the client request/response transforms and the proxy server-ingress message conversion. Adds the mcp and a2a-sdk packages to the benchmark run since those transform modules need them, and broadens the workflow triggers to litellm_internal_staging so the internal branch flow is benchmarked too. --- .github/workflows/codspeed.yml | 4 + tests/benchmarks/test_a2a_benchmarks.py | 76 ++++++++++++ tests/benchmarks/test_inference_benchmarks.py | 113 ++++++++++++++++++ tests/benchmarks/test_mcp_benchmarks.py | 84 +++++++++++++ 4 files changed, 277 insertions(+) create mode 100644 tests/benchmarks/test_a2a_benchmarks.py create mode 100644 tests/benchmarks/test_inference_benchmarks.py create mode 100644 tests/benchmarks/test_mcp_benchmarks.py diff --git a/.github/workflows/codspeed.yml b/.github/workflows/codspeed.yml index 17efbf90339..1fad82827ff 100644 --- a/.github/workflows/codspeed.yml +++ b/.github/workflows/codspeed.yml @@ -4,9 +4,11 @@ on: push: branches: - main + - litellm_internal_staging pull_request: branches: - main + - litellm_internal_staging # Allow CodSpeed to trigger backtest performance analysis # in order to generate initial data workflow_dispatch: @@ -48,6 +50,8 @@ jobs: uv run --frozen --no-default-groups --with pytest==8.3.5 --with pytest-codspeed==4.3.0 + --with "mcp>=1.26.0,<2.0" + --with "a2a-sdk>=1.1.0,<2.0" pytest -p pytest_codspeed.plugin tests/benchmarks/ diff --git a/tests/benchmarks/test_a2a_benchmarks.py b/tests/benchmarks/test_a2a_benchmarks.py new file mode 100644 index 00000000000..cf7726230b6 --- /dev/null +++ b/tests/benchmarks/test_a2a_benchmarks.py @@ -0,0 +1,76 @@ +""" +Performance benchmarks for the A2A (agent-to-agent) message-translation hot path. + +Both directions are covered: the client direction (litellm.completion talking to +an upstream A2A agent) converts OpenAI messages into a prompt and extracts text +from the A2A response, and the proxy server-ingress direction converts an inbound +A2A message into OpenAI messages before bridging to a completion. All are pure-CPU +per-request transforms. +""" + +import pytest + +from litellm.a2a_protocol.litellm_completion_bridge.transformation import ( + A2ACompletionBridgeTransformation, +) +from litellm.llms.a2a.common_utils import ( + convert_messages_to_prompt, + extract_text_from_a2a_response, +) + +MESSAGES = [ + {"role": "system", "content": "You are a helpful research assistant."}, + {"role": "user", "content": "What is the capital of France?"}, + {"role": "assistant", "content": "The capital of France is Paris."}, + {"role": "user", "content": "And what is its population?"}, +] + +MESSAGE_RESPONSE = { + "result": { + "kind": "message", + "parts": [ + {"kind": "text", "text": "The population of Paris is about 2.1 million."}, + {"kind": "text", "text": "The metro area has over 12 million people."}, + ], + } +} + +TASK_RESPONSE = { + "result": { + "kind": "task", + "artifacts": [{"parts": [{"kind": "text", "text": "Paris has a population of about 2.1 million."}]}], + } +} + +A2A_INBOUND_MESSAGE = { + "role": "user", + "parts": [ + {"kind": "text", "text": "Summarize the latest quarterly report."}, + {"kind": "text", "text": "Focus on revenue and margins."}, + ], + "messageId": "msg-1", +} + + +@pytest.mark.benchmark +def test_convert_messages_to_a2a_prompt(): + """Benchmark converting OpenAI messages into an A2A prompt string.""" + convert_messages_to_prompt(messages=MESSAGES) + + +@pytest.mark.benchmark +def test_extract_text_from_a2a_message_response(): + """Benchmark extracting text from a direct-message A2A response.""" + extract_text_from_a2a_response(response_dict=MESSAGE_RESPONSE) + + +@pytest.mark.benchmark +def test_extract_text_from_a2a_task_response(): + """Benchmark extracting text from a task-with-artifacts A2A response.""" + extract_text_from_a2a_response(response_dict=TASK_RESPONSE) + + +@pytest.mark.benchmark +def test_a2a_inbound_message_to_openai_messages(): + """Benchmark the proxy converting an inbound A2A message into OpenAI messages.""" + A2ACompletionBridgeTransformation.a2a_message_to_openai_messages(A2A_INBOUND_MESSAGE) diff --git a/tests/benchmarks/test_inference_benchmarks.py b/tests/benchmarks/test_inference_benchmarks.py new file mode 100644 index 00000000000..0a95e34a32c --- /dev/null +++ b/tests/benchmarks/test_inference_benchmarks.py @@ -0,0 +1,113 @@ +""" +Performance benchmarks for the LLM inference (chat completion) hot path. + +The end-to-end cases use ``mock_response`` so the full SDK overhead is exercised +-- provider resolution, request/response transformation, ``ModelResponse`` +construction, token counting and cost calculation -- without any network I/O. The +``convert_to_model_response_object`` case isolates the provider-response to +``ModelResponse`` translation, the single deterministic core every non-streaming +completion runs. +""" + +import pytest + +import litellm +from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import ( + convert_to_model_response_object, +) +from litellm.types.utils import ModelResponse + +SIMPLE_MESSAGES = [{"role": "user", "content": "Hello, how are you?"}] + +MULTI_TURN_MESSAGES = [ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "user", "content": "What is the capital of France?"}, + { + "role": "assistant", + "content": "The capital of France is Paris. It is known as the City of Light.", + }, + {"role": "user", "content": "Tell me more about Paris."}, +] + +TOOL_DEFINITIONS = [ + { + "type": "function", + "function": { + "name": "get_weather", + "description": "Get the current weather in a given location", + "parameters": { + "type": "object", + "properties": { + "location": { + "type": "string", + "description": "The city and state, e.g. San Francisco, CA", + }, + "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, + }, + "required": ["location"], + }, + }, + } +] + +MOCK_RESPONSE = "The capital of France is Paris, the country's largest city and cultural centre." + +PROVIDER_RESPONSE = { + "id": "chatcmpl-abc123", + "object": "chat.completion", + "created": 1700000000, + "model": "gpt-4o", + "choices": [ + { + "index": 0, + "finish_reason": "stop", + "message": {"role": "assistant", "content": MOCK_RESPONSE}, + } + ], + "usage": {"prompt_tokens": 12, "completion_tokens": 16, "total_tokens": 28}, +} + + +@pytest.mark.benchmark +def test_completion_simple_message(): + """Benchmark a single-message completion through the full SDK path.""" + litellm.completion(model="gpt-4o", messages=SIMPLE_MESSAGES, mock_response=MOCK_RESPONSE) + + +@pytest.mark.benchmark +def test_completion_multi_turn(): + """Benchmark a multi-turn completion through the full SDK path.""" + litellm.completion(model="gpt-4o", messages=MULTI_TURN_MESSAGES, mock_response=MOCK_RESPONSE) + + +@pytest.mark.benchmark +def test_completion_with_tools(): + """Benchmark a completion that has to process tool schemas.""" + litellm.completion( + model="gpt-4o", + messages=SIMPLE_MESSAGES, + tools=TOOL_DEFINITIONS, + mock_response=MOCK_RESPONSE, + ) + + +@pytest.mark.benchmark +def test_completion_streaming(): + """Benchmark consuming a full streamed completion (CustomStreamWrapper).""" + stream = litellm.completion( + model="gpt-4o", + messages=SIMPLE_MESSAGES, + mock_response=MOCK_RESPONSE, + stream=True, + ) + for _ in stream: + pass + + +@pytest.mark.benchmark +def test_response_to_model_response_object(): + """Benchmark the provider-response to ModelResponse translation core.""" + convert_to_model_response_object( + response_object=PROVIDER_RESPONSE, + model_response_object=ModelResponse(), + ) diff --git a/tests/benchmarks/test_mcp_benchmarks.py b/tests/benchmarks/test_mcp_benchmarks.py new file mode 100644 index 00000000000..7e23ab1b4f5 --- /dev/null +++ b/tests/benchmarks/test_mcp_benchmarks.py @@ -0,0 +1,84 @@ +""" +Performance benchmarks for the MCP tool hot path. + +Two layers are covered: the client-side translation between MCP and OpenAI +function-calling formats, and the server-side tool-name prefixing that the proxy +runs on every list-tools (prefix each tool) and call-tool (strip prefix to route) +request. Both are pure-CPU and deterministic. +""" + +import pytest +from mcp.types import Tool as MCPTool + +from litellm.experimental_mcp_client.tools import ( + transform_mcp_tool_to_openai_tool, + transform_openai_tool_call_request_to_mcp_tool_call_request, +) +from litellm.proxy._experimental.mcp_server.utils import ( + add_server_prefix_to_name, + split_server_prefix_from_name, +) + + +def _make_tool(index: int) -> MCPTool: + return MCPTool( + name=f"tool_{index}", + description=f"Test tool number {index} that performs an operation", + inputSchema={ + "type": "object", + "properties": { + "query": {"type": "string", "description": "The search query"}, + "limit": {"type": "integer", "description": "Max results"}, + }, + "required": ["query"], + }, + ) + + +SINGLE_TOOL = _make_tool(0) +TOOL_LIST = tuple(_make_tool(i) for i in range(20)) +TOOL_NAMES = tuple(t.name for t in TOOL_LIST) + +SERVER_NAME = "github_mcp" +PREFIXED_TOOL_NAME = add_server_prefix_to_name("tool_0", SERVER_NAME) + +OPENAI_TOOL_CALL = { + "id": "call_abc123", + "type": "function", + "function": { + "name": "tool_0", + "arguments": '{"query": "weather in San Francisco", "limit": 5}', + }, +} + + +@pytest.mark.benchmark +def test_transform_single_mcp_tool_to_openai(): + """Benchmark translating one MCP tool into OpenAI tool format.""" + transform_mcp_tool_to_openai_tool(mcp_tool=SINGLE_TOOL) + + +@pytest.mark.benchmark +def test_transform_mcp_tool_list_to_openai(): + """Benchmark translating a full list-tools response into OpenAI format.""" + for tool in TOOL_LIST: + transform_mcp_tool_to_openai_tool(mcp_tool=tool) + + +@pytest.mark.benchmark +def test_transform_openai_tool_call_to_mcp(): + """Benchmark translating an OpenAI tool call into an MCP call request.""" + transform_openai_tool_call_request_to_mcp_tool_call_request(openai_tool=OPENAI_TOOL_CALL) + + +@pytest.mark.benchmark +def test_mcp_server_prefix_tool_list(): + """Benchmark the proxy prefixing every tool name on a list-tools response.""" + for name in TOOL_NAMES: + add_server_prefix_to_name(name, SERVER_NAME) + + +@pytest.mark.benchmark +def test_mcp_server_strip_prefix_on_call(): + """Benchmark the proxy stripping the server prefix to route a tool call.""" + split_server_prefix_from_name(PREFIXED_TOOL_NAME) From 7ed25de12028ba24975c0ac6e43dc77eafc75746 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 10:29:49 -0700 Subject: [PATCH 14/79] fix(ui): allow any git host on the skills add form (LIT-4053) (#31652) * fix(ui): allow any git host on the skills add form (LIT-4053) The skills add form only accepted GitHub URLs: its URL parser bailed on any host that did not start with github.com, so GitLab, Bitbucket, and self-hosted repos (and any repo subfolder on them) were rejected before a request was ever sent. The backend already accepts arbitrary git hosts via its url and git-subdir sources, with no host allowlist, so this was a client-side restriction only. Generalize the parser into an exported, host-agnostic parseSkillSource: GitHub URLs keep their github / git-subdir shorthand, every other host is treated as a raw repo url, and an optional Subfolder path field turns any repo into a git-subdir source (url + path). When a pasted GitHub tree/blob URL already encodes a subfolder, the field is cleared and disabled so a contradictory source can never be submitted. The parser is hardened to match the backend contract: query strings and fragments are stripped, the host match is case-insensitive and drops a leading www., the extracted and field-entered subfolder paths are both validated against the same regex the server uses, a real file-extension allowlist (not "any dot") decides whether a trailing blob segment is a file, a branch-only tree URL falls back to the repo, non-GitHub URLs require at least an org/repo, and the suggested skill name is kebab-cased so it satisfies the name field's own rule. The git-subdir source is now handled in the display helpers (getSourceDisplayText, getSourceLink, formatInstallCommand), which previously showed it as "Unknown source" with no link. The submit path is fully typed (RegisterPluginRequest plus an AddPluginFormValues interface), removing the two prior any usages; as a result an author with an email but no name is dropped rather than sent, since the backend requires the author name. No backend changes. Tests cover the full host/subfolder matrix at the parser level plus form-submit assertions on the exact source payload. * refactor(ui): sync skill register types to the generated OpenAPI schema, surface backend errors Replace the hand-maintained, already-drifted API types for the skills add flow with the generated ones from schema.d.ts: PluginAuthor now aliases components["schemas"]["PluginAuthor"], the registration payload is a new SkillRegisterRequest (the generated RegisterPluginRequest envelope with source narrowed to our PluginSource union, since the backend types source as a loose string map, and version kept optional since the backend defaults it), and the dead, mismatched RegisterPluginResponse is deleted. registerClaudeCodePlugin's inline payload type (which was missing the git-subdir path field entirely) is replaced with SkillRegisterRequest, so the networking layer and the form can no longer drift from the backend. Error handling: the add-skill form swallowed the real failure and always showed "Failed to register skill". registerClaudeCodePlugin already derives the backend message and throws it, so the form now surfaces it ("Failed to register skill: "), and the networking helper falls back to the raw body / status when the error response is not JSON instead of throwing a JSON parse error. A regression test asserts the backend message reaches the user. * fix(ui): reject credentialed git URLs on the skills form A repo URL with embedded user-info (user:token@host) passed the raw-host parser and was stored verbatim as the skill source, which is served on the unauthenticated /public/skill_hub and marketplace.json feeds, leaking the credentials. Reject any host segment containing '@'. * fix(ui): validate skill repo URLs through one WHATWG URL gate Replace the ad-hoc string parsing (stripScheme / splitHost / manual scheme, @, ?# checks) with a single parseRepoUrl gate built on the URL parser, so every malformed/unsafe class is handled in one place and the URL stored on the public skill feeds is always canonical. It enforces https (rejecting http/ssh/git/file/javascript/data and protocol-relative //host), rejects embedded credentials (user:token@host, including userinfo-confusion like github.com@evil.com), rejects IP-literal hosts (loopback/private/metadata and obfuscated/IPv6 forms), and rebuilds the stored url from origin+pathname so query strings, fragments, and trailing slashes can never be published. The GitHub org/repo shorthand is now charset-validated like the other paths, so junk can't reach the stored repo. Closes both Veria findings (credentialed and http sources) plus the adversarial-review follow-ups, with regression tests for each class. --- ui/litellm-dashboard/eslint-metrics.json | 4 +- ui/litellm-dashboard/eslint-suppressions.json | 5 - .../add_plugin_form.test.tsx | 190 ++++++++++++- .../claude_code_plugins/add_plugin_form.tsx | 219 ++++++++------- .../claude_code_plugins/helpers.test.ts | 260 +++++++++++++++++- .../components/claude_code_plugins/helpers.ts | 191 ++++++++++++- .../components/claude_code_plugins/types.ts | 48 +--- .../src/components/networking.tsx | 24 +- 8 files changed, 750 insertions(+), 191 deletions(-) diff --git a/ui/litellm-dashboard/eslint-metrics.json b/ui/litellm-dashboard/eslint-metrics.json index deef1136b43..09ad247391b 100644 --- a/ui/litellm-dashboard/eslint-metrics.json +++ b/ui/litellm-dashboard/eslint-metrics.json @@ -1,5 +1,5 @@ { - "@typescript-eslint/no-explicit-any": 2016, - "complexity": 127, + "@typescript-eslint/no-explicit-any": 2014, + "complexity": 126, "max-depth": 61 } diff --git a/ui/litellm-dashboard/eslint-suppressions.json b/ui/litellm-dashboard/eslint-suppressions.json index e3ae304c41c..7a3c8f4a42c 100644 --- a/ui/litellm-dashboard/eslint-suppressions.json +++ b/ui/litellm-dashboard/eslint-suppressions.json @@ -873,11 +873,6 @@ "count": 1 } }, - "src/components/claude_code_plugins/helpers.test.ts": { - "unused-imports/no-unused-imports": { - "count": 1 - } - }, "src/components/claude_code_plugins/plugin_table.tsx": { "no-restricted-imports": { "count": 1 diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.test.tsx b/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.test.tsx index 9aa6ec7a969..0453cd8a695 100644 --- a/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.test.tsx +++ b/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.test.tsx @@ -3,11 +3,20 @@ import { act, fireEvent, screen, waitFor } from "@testing-library/react"; import { describe, it, expect, vi, beforeEach } from "vitest"; import { renderWithProviders } from "../../../tests/test-utils"; import AddPluginForm from "./add_plugin_form"; +import { registerClaudeCodePlugin } from "../networking"; +import MessageManager from "@/components/molecules/message_manager"; vi.mock("../networking", () => ({ registerClaudeCodePlugin: vi.fn().mockResolvedValue({ status: "success" }), })); +vi.mock("@/components/molecules/message_manager", () => ({ + default: { error: vi.fn(), success: vi.fn() }, +})); + +const mockRegister = vi.mocked(registerClaudeCodePlugin); +const mockMessageError = vi.mocked(MessageManager.error); + const DEFAULT_PROPS = { visible: true, onClose: vi.fn(), @@ -15,22 +24,27 @@ const DEFAULT_PROPS = { onSuccess: vi.fn(), }; +const URL_PLACEHOLDER = "https://github.com/org/repo or https://gitlab.com/org/repo"; +const SUBPATH_PLACEHOLDER = "plugins/my-skill"; + describe("AddPluginForm", () => { beforeEach(() => { vi.clearAllMocks(); }); - it("renders with GitHub URL input", () => { + it("renders the host-agnostic repository URL input and subfolder field", () => { renderWithProviders(); - expect(screen.getByText("GitHub URL")).toBeInTheDocument(); - expect(screen.getByPlaceholderText("https://github.com/org/repo/tree/main/my-skill")).toBeInTheDocument(); + expect(screen.getByText("Repository URL")).toBeInTheDocument(); + expect(screen.getByPlaceholderText(URL_PLACEHOLDER)).toBeInTheDocument(); + expect(screen.getByText("Subfolder path (Optional)")).toBeInTheDocument(); + expect(screen.getByPlaceholderText(SUBPATH_PLACEHOLDER)).toBeInTheDocument(); }); it("shows GitHub repo preview for a plain repo URL", async () => { renderWithProviders(); - const urlInput = screen.getByPlaceholderText("https://github.com/org/repo/tree/main/my-skill"); + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); await act(async () => { fireEvent.change(urlInput, { @@ -43,10 +57,10 @@ describe("AddPluginForm", () => { }); }); - it("shows git-subdir preview for a tree URL", async () => { + it("shows git-subdir preview for a tree URL and disables the subfolder field", async () => { renderWithProviders(); - const urlInput = screen.getByPlaceholderText("https://github.com/org/repo/tree/main/my-skill"); + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); await act(async () => { fireEvent.change(urlInput, { @@ -59,12 +73,51 @@ describe("AddPluginForm", () => { await waitFor(() => { expect(screen.getByText(/GitHub subdir/)).toBeInTheDocument(); }); + expect(screen.getByPlaceholderText(SUBPATH_PLACEHOLDER)).toBeDisabled(); + }); + + it("shows a raw url preview for a non-github host", async () => { + renderWithProviders(); + + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); + + await act(async () => { + fireEvent.change(urlInput, { + target: { value: "https://gitlab.com/group/repo" }, + }); + }); + + await waitFor(() => { + expect(screen.getByText(/Git repo/)).toBeInTheDocument(); + }); + expect(screen.getByPlaceholderText(SUBPATH_PLACEHOLDER)).not.toBeDisabled(); + }); + + it("combines a repo URL with a subfolder into a git-subdir preview", async () => { + renderWithProviders(); + + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); + await act(async () => { + fireEvent.change(urlInput, { + target: { value: "https://gitlab.com/group/repo" }, + }); + }); + + const subPathInput = screen.getByPlaceholderText(SUBPATH_PLACEHOLDER); + await act(async () => { + fireEvent.change(subPathInput, { target: { value: "plugins/x" } }); + }); + + await waitFor(() => { + expect(screen.getByText(/Git subdir/)).toBeInTheDocument(); + expect(screen.getByText(/plugins\/x/)).toBeInTheDocument(); + }); }); it("auto-fills skill name from repo URL", async () => { renderWithProviders(); - const urlInput = screen.getByPlaceholderText("https://github.com/org/repo/tree/main/my-skill"); + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); await act(async () => { fireEvent.change(urlInput, { @@ -84,7 +137,7 @@ describe("AddPluginForm", () => { const nameInput = screen.getByPlaceholderText("my-skill") as HTMLInputElement; fireEvent.change(nameInput, { target: { value: "existing-name" } }); - const urlInput = screen.getByPlaceholderText("https://github.com/org/repo/tree/main/my-skill"); + const urlInput = screen.getByPlaceholderText(URL_PLACEHOLDER); await act(async () => { fireEvent.change(urlInput, { @@ -96,4 +149,125 @@ describe("AddPluginForm", () => { expect(nameInput.value).toBe("existing-name"); }); }); + + const typeUrl = async (value: string) => { + await act(async () => { + fireEvent.change(screen.getByPlaceholderText(URL_PLACEHOLDER), { target: { value } }); + }); + }; + + const typeSubPath = async (value: string) => { + await act(async () => { + fireEvent.change(screen.getByPlaceholderText(SUBPATH_PLACEHOLDER), { target: { value } }); + }); + }; + + const submit = async () => { + await act(async () => { + fireEvent.click(screen.getByRole("button", { name: "Add Skill" })); + }); + }; + + it("submits a github repo source", async () => { + renderWithProviders(); + + await typeUrl("https://github.com/anthropics/claude-code"); + await submit(); + + await waitFor(() => { + expect(mockRegister).toHaveBeenCalledWith( + "sk-test", + expect.objectContaining({ source: { source: "github", repo: "anthropics/claude-code" } }), + ); + }); + }); + + it("submits a github subdir source from a tree URL", async () => { + renderWithProviders(); + + await typeUrl("https://github.com/anthropics/claude-code/tree/main/plugins/my-skill"); + await submit(); + + await waitFor(() => { + expect(mockRegister).toHaveBeenCalledWith( + "sk-test", + expect.objectContaining({ + source: { source: "git-subdir", url: "https://github.com/anthropics/claude-code", path: "plugins/my-skill" }, + }), + ); + }); + }); + + it("submits a raw url source for a gitlab repo", async () => { + renderWithProviders(); + + await typeUrl("https://gitlab.com/group/repo"); + await submit(); + + await waitFor(() => { + expect(mockRegister).toHaveBeenCalledWith( + "sk-test", + expect.objectContaining({ source: { source: "url", url: "https://gitlab.com/group/repo" } }), + ); + }); + }); + + it("submits a git-subdir source from a gitlab repo plus subfolder field", async () => { + renderWithProviders(); + + await typeUrl("https://gitlab.com/group/repo"); + await typeSubPath("plugins/x"); + await submit(); + + await waitFor(() => { + expect(mockRegister).toHaveBeenCalledWith( + "sk-test", + expect.objectContaining({ + source: { source: "git-subdir", url: "https://gitlab.com/group/repo", path: "plugins/x" }, + }), + ); + }); + }); + + it("clears the subfolder field and uses the URL path once a tree URL is entered", async () => { + renderWithProviders(); + + await typeSubPath("plugins/x"); + const subPathInput = screen.getByPlaceholderText(SUBPATH_PLACEHOLDER) as HTMLInputElement; + expect(subPathInput.value).toBe("plugins/x"); + + await typeUrl("https://github.com/anthropics/claude-code/tree/main/plugins/from-url"); + + await waitFor(() => { + expect(subPathInput.value).toBe(""); + expect(subPathInput).toBeDisabled(); + }); + + await submit(); + + await waitFor(() => { + expect(mockRegister).toHaveBeenCalledWith( + "sk-test", + expect.objectContaining({ + source: { + source: "git-subdir", + url: "https://github.com/anthropics/claude-code", + path: "plugins/from-url", + }, + }), + ); + }); + }); + + it("surfaces the backend error message when registration fails", async () => { + mockRegister.mockRejectedValueOnce(new Error("Plugin 'claude-code' already exists")); + renderWithProviders(); + + await typeUrl("https://github.com/anthropics/claude-code"); + await submit(); + + await waitFor(() => { + expect(mockMessageError).toHaveBeenCalledWith(expect.stringContaining("Plugin 'claude-code' already exists")); + }); + }); }); diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.tsx b/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.tsx index f90261ae3a3..a1587bc5189 100644 --- a/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.tsx +++ b/ui/litellm-dashboard/src/components/claude_code_plugins/add_plugin_form.tsx @@ -3,7 +3,17 @@ import { Modal, Form, Input, Select } from "antd"; import MessageManager from "@/components/molecules/message_manager"; import { Button } from "@tremor/react"; import { registerClaudeCodePlugin } from "../networking"; -import { validatePluginName, isValidSemanticVersion, isValidEmail, isValidUrl, parseKeywords } from "./helpers"; +import { + validatePluginName, + isValidSemanticVersion, + isValidEmail, + isValidUrl, + parseKeywords, + parseSkillSource, + isValidSubPath, + SkillSourcePreview, +} from "./helpers"; +import { PluginAuthor, PluginSource, SkillRegisterRequest } from "./types"; const { TextArea } = Input; const { Option } = Select; @@ -15,6 +25,46 @@ interface AddPluginFormProps { onSuccess: () => void; } +interface AddPluginFormValues { + name: string; + skillUrl?: string; + subPath?: string; + version?: string; + description?: string; + authorName?: string; + authorEmail?: string; + homepage?: string; + category?: string; + keywords?: string; + domain?: string; + namespace?: string; +} + +const buildAuthor = (values: AddPluginFormValues): PluginAuthor | undefined => { + const name = values.authorName?.trim(); + const email = values.authorEmail?.trim(); + if (!name) { + return undefined; + } + return email ? { name, email } : { name }; +}; + +const buildRegisterRequest = (values: AddPluginFormValues, source: PluginSource): SkillRegisterRequest => { + const author = buildAuthor(values); + return { + name: values.name.trim(), + source, + ...(values.version ? { version: values.version.trim() } : {}), + ...(values.description ? { description: values.description.trim() } : {}), + ...(author ? { author } : {}), + ...(values.homepage ? { homepage: values.homepage.trim() } : {}), + ...(values.category ? { category: values.category } : {}), + ...(values.keywords ? { keywords: parseKeywords(values.keywords) } : {}), + ...(values.domain ? { domain: values.domain.trim() } : {}), + ...(values.namespace ? { namespace: values.namespace.trim() } : {}), + }; +}; + const PREDEFINED_CATEGORIES = [ "Development", "Productivity", @@ -26,106 +76,41 @@ const PREDEFINED_CATEGORIES = [ "Documentation", ]; -interface ParsedSource { - source: "github" | "url" | "git-subdir"; - repo?: string; - url?: string; - path?: string; -} - -interface ParsePreview { - parsed: ParsedSource; - label: string; - suggestedName: string; -} - -function parseGitHubUrl(raw: string): ParsePreview | null { - // Strip protocol and trailing slashes/spaces - let s = raw - .trim() - .replace(/^https?:\/\//, "") - .replace(/\/+$/, ""); - - if (!s.startsWith("github.com/")) return null; - - // Remove "github.com/" - const rest = s.slice("github.com/".length); - const parts = rest.split("/"); - - if (parts.length < 2) return null; - - const org = parts[0]; - const repo = parts[1]; - const repoBase = repo.replace(/\.git$/, ""); - - // github.com/org/repo (exactly 2 parts, or ends with .git) - if (parts.length === 2 || (parts.length === 2 && repoBase)) { - return { - parsed: { source: "github", repo: `${org}/${repoBase}` }, - label: `GitHub repo — ${org}/${repoBase}`, - suggestedName: repoBase, - }; - } - - // github.com/org/repo/tree/branch/folder or /blob/branch/folder/FILE.md - if (parts.length >= 5 && (parts[2] === "tree" || parts[2] === "blob")) { - // parts[3] = branch, parts[4..] = path segments - const pathParts = parts.slice(4); - // If last segment looks like a file (has extension), drop it - const lastPart = pathParts[pathParts.length - 1]; - if (lastPart && lastPart.includes(".")) { - pathParts.pop(); - } - if (pathParts.length === 0) { - // Path resolved to repo root — treat as plain github source - return { - parsed: { source: "github", repo: `${org}/${repoBase}` }, - label: `GitHub repo — ${org}/${repoBase}`, - suggestedName: repoBase, - }; - } - const subPath = pathParts.join("/"); - const suggestedName = pathParts[pathParts.length - 1]; - return { - parsed: { - source: "git-subdir", - url: `https://github.com/${org}/${repoBase}`, - path: subPath, - }, - label: `GitHub subdir — ${org}/${repoBase} @ ${subPath}`, - suggestedName, - }; - } - - return null; -} - const AddPluginForm: React.FC = ({ visible, onClose, accessToken, onSuccess }) => { const [form] = Form.useForm(); const [isSubmitting, setIsSubmitting] = useState(false); - const [urlPreview, setUrlPreview] = useState(null); + const [urlPreview, setUrlPreview] = useState(null); + const [urlEncodesSubdir, setUrlEncodesSubdir] = useState(false); - const handleUrlChange = (e: React.ChangeEvent) => { - const val = e.target.value; - const preview = parseGitHubUrl(val); + const recomputePreview = (skillUrl: string, subPath: string) => { + const encodesSubdir = parseSkillSource(skillUrl)?.parsed.source === "git-subdir"; + setUrlEncodesSubdir(encodesSubdir); + if (encodesSubdir && form.getFieldValue("subPath")) { + form.setFieldsValue({ subPath: "" }); + } + const preview = parseSkillSource(skillUrl, encodesSubdir ? undefined : subPath); setUrlPreview(preview); - if (preview) { - // Auto-fill name only if it's currently empty - const currentName = form.getFieldValue("name"); - if (!currentName) { - form.setFieldsValue({ name: preview.suggestedName }); - } + if (preview && !form.getFieldValue("name")) { + form.setFieldsValue({ name: preview.suggestedName }); } }; - const handleSubmit = async (values: any) => { + const handleUrlChange = (e: React.ChangeEvent) => { + recomputePreview(e.target.value, form.getFieldValue("subPath") ?? ""); + }; + + const handleSubPathChange = (e: React.ChangeEvent) => { + recomputePreview(form.getFieldValue("skillUrl") ?? "", e.target.value); + }; + + const handleSubmit = async (values: AddPluginFormValues) => { if (!accessToken) { MessageManager.error("No access token available"); return; } if (!urlPreview) { - MessageManager.error("Please enter a valid GitHub URL"); + MessageManager.error("Please enter a valid repository URL"); return; } @@ -151,33 +136,17 @@ const AddPluginForm: React.FC = ({ visible, onClose, accessT setIsSubmitting(true); try { - const pluginData: any = { - name: values.name.trim(), - source: urlPreview.parsed, - }; - - if (values.version) pluginData.version = values.version.trim(); - if (values.description) pluginData.description = values.description.trim(); - if (values.authorName || values.authorEmail) { - pluginData.author = {}; - if (values.authorName) pluginData.author.name = values.authorName.trim(); - if (values.authorEmail) pluginData.author.email = values.authorEmail.trim(); - } - if (values.homepage) pluginData.homepage = values.homepage.trim(); - if (values.category) pluginData.category = values.category; - if (values.keywords) pluginData.keywords = parseKeywords(values.keywords); - if (values.domain) pluginData.domain = values.domain.trim(); - if (values.namespace) pluginData.namespace = values.namespace.trim(); - - await registerClaudeCodePlugin(accessToken, pluginData); + await registerClaudeCodePlugin(accessToken, buildRegisterRequest(values, urlPreview.parsed)); MessageManager.success("Skill registered successfully"); form.resetFields(); setUrlPreview(null); + setUrlEncodesSubdir(false); onSuccess(); onClose(); } catch (error) { console.error("Error registering skill:", error); - MessageManager.error("Failed to register skill"); + const reason = error instanceof Error && error.message ? error.message : "Failed to register skill"; + MessageManager.error(`Failed to register skill: ${reason}`); } finally { setIsSubmitting(false); } @@ -186,6 +155,7 @@ const AddPluginForm: React.FC = ({ visible, onClose, accessT const handleCancel = () => { form.resetFields(); setUrlPreview(null); + setUrlEncodesSubdir(false); onClose(); }; @@ -194,18 +164,45 @@ const AddPluginForm: React.FC = ({ visible, onClose, accessT
{/* Smart URL Input */} + {/* Optional subfolder for monorepos */} + + !value || isValidSubPath(value) + ? Promise.resolve() + : Promise.reject( + new Error( + "Subfolder must be a relative path like plugins/my-skill (letters, numbers, dots, hyphens, underscores)", + ), + ), + }, + ]} + tooltip="Path within the repository where the skill lives (e.g., plugins/my-skill). Leave empty if the skill is at the repo root." + extra={urlEncodesSubdir ? "The URL already points to a subfolder, so this field is disabled" : undefined} + > + + + {/* Parsed preview */} {urlPreview && (
diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts index b3930d15718..4c84db2a97d 100644 --- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts +++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.test.ts @@ -15,23 +15,34 @@ import { isValidUrl, parseKeywords, formatKeywords, + parseSkillSource, + isValidSubPath, } from "./helpers"; import { MarketplacePluginEntry, PluginSource } from "./types"; describe("formatInstallCommand", () => { it("formats github source with repo", () => { - const plugin = { name: "my-plugin", source: { source: "github" as const, repo: "org/repo" } }; - expect(formatInstallCommand(plugin)).toBe("/plugin marketplace add org/repo"); + const source: PluginSource = { source: "github", repo: "org/repo" }; + expect(formatInstallCommand({ name: "my-plugin", source })).toBe("/plugin marketplace add org/repo"); }); it("formats url source", () => { - const plugin = { name: "my-plugin", source: { source: "url" as const, url: "https://example.com/plugin" } }; - expect(formatInstallCommand(plugin)).toBe("/plugin marketplace add https://example.com/plugin"); + const source: PluginSource = { source: "url", url: "https://example.com/plugin" }; + expect(formatInstallCommand({ name: "my-plugin", source })).toBe( + "/plugin marketplace add https://example.com/plugin", + ); + }); + + it("formats git-subdir source using its url", () => { + const source: PluginSource = { source: "git-subdir", url: "https://github.com/org/repo", path: "plugins/x" }; + expect(formatInstallCommand({ name: "my-plugin", source })).toBe( + "/plugin marketplace add https://github.com/org/repo", + ); }); it("falls back to plugin name when no repo or url", () => { - const plugin = { name: "my-plugin", source: { source: "github" as const } }; - expect(formatInstallCommand(plugin)).toBe("/plugin marketplace add my-plugin"); + const source: PluginSource = { source: "github" }; + expect(formatInstallCommand({ name: "my-plugin", source })).toBe("/plugin marketplace add my-plugin"); }); }); @@ -91,6 +102,18 @@ describe("getSourceDisplayText", () => { expect(getSourceDisplayText({ source: "url", url: "https://example.com" })).toBe("https://example.com"); }); + it("shows git-subdir as url @ path for a github subdir", () => { + expect(getSourceDisplayText({ source: "git-subdir", url: "https://github.com/org/repo", path: "plugins/x" })).toBe( + "https://github.com/org/repo @ plugins/x", + ); + }); + + it("shows git-subdir as url @ path for a gitlab subdir", () => { + expect(getSourceDisplayText({ source: "git-subdir", url: "https://gitlab.com/org/repo", path: "sub/dir" })).toBe( + "https://gitlab.com/org/repo @ sub/dir", + ); + }); + it("returns unknown for missing data", () => { expect(getSourceDisplayText({ source: "github" })).toBe("Unknown source"); }); @@ -105,6 +128,18 @@ describe("getSourceLink", () => { expect(getSourceLink({ source: "url", url: "https://example.com" })).toBe("https://example.com"); }); + it("returns the repo url for a github git-subdir source", () => { + expect(getSourceLink({ source: "git-subdir", url: "https://github.com/org/repo", path: "plugins/x" })).toBe( + "https://github.com/org/repo", + ); + }); + + it("returns the repo url for a gitlab git-subdir source", () => { + expect(getSourceLink({ source: "git-subdir", url: "https://gitlab.com/org/repo", path: "sub/dir" })).toBe( + "https://gitlab.com/org/repo", + ); + }); + it("returns null when no repo or url", () => { expect(getSourceLink({ source: "github" })).toBeNull(); }); @@ -323,3 +358,216 @@ describe("formatKeywords", () => { expect(formatKeywords(undefined)).toBe(""); }); }); + +describe("parseSkillSource", () => { + it("parses a plain github repo", () => { + expect(parseSkillSource("github.com/org/repo")?.parsed).toEqual({ source: "github", repo: "org/repo" }); + }); + + it("strips a .git suffix from the github repo shorthand", () => { + expect(parseSkillSource("https://github.com/org/repo.git")?.parsed).toEqual({ + source: "github", + repo: "org/repo", + }); + }); + + it("parses a github tree URL into a git-subdir", () => { + expect(parseSkillSource("github.com/org/repo/tree/main/plugins/x")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "plugins/x", + }); + }); + + it("drops a trailing file segment from a github blob URL", () => { + expect(parseSkillSource("github.com/org/repo/blob/main/x/SKILL.md")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "x", + }); + }); + + it("combines a github repo with an explicit subfolder", () => { + expect(parseSkillSource("github.com/org/repo", "plugins/x")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "plugins/x", + }); + }); + + it("treats a gitlab repo as a raw url source", () => { + expect(parseSkillSource("gitlab.com/org/repo")?.parsed).toEqual({ + source: "url", + url: "https://gitlab.com/org/repo", + }); + }); + + it("keeps the .git suffix on raw urls", () => { + expect(parseSkillSource("https://gitlab.com/org/repo.git")?.parsed).toEqual({ + source: "url", + url: "https://gitlab.com/org/repo.git", + }); + }); + + it("combines a gitlab repo with an explicit subfolder", () => { + expect(parseSkillSource("gitlab.com/org/repo", "plugins/x")?.parsed).toEqual({ + source: "git-subdir", + url: "https://gitlab.com/org/repo", + path: "plugins/x", + }); + }); + + it("combines a self-hosted host with an explicit subfolder", () => { + expect(parseSkillSource("https://git.acme.com/team/repo", "sub/dir")?.parsed).toEqual({ + source: "git-subdir", + url: "https://git.acme.com/team/repo", + path: "sub/dir", + }); + }); + + it("lets a github URL-encoded subdir win over an also-provided subfolder", () => { + expect(parseSkillSource("github.com/org/repo/tree/main/plugins/x", "ignored/path")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "plugins/x", + }); + }); + + it("rejects traversal, absolute, and double-slash subfolders", () => { + expect(parseSkillSource("gitlab.com/org/repo", "../etc")).toBeNull(); + expect(parseSkillSource("gitlab.com/org/repo", "/abs")).toBeNull(); + expect(parseSkillSource("gitlab.com/org/repo", "a//b")).toBeNull(); + }); + + it("returns null for empty and garbage input", () => { + expect(parseSkillSource("")).toBeNull(); + expect(parseSkillSource(" ")).toBeNull(); + expect(parseSkillSource("not a url")).toBeNull(); + }); + + it("suggests a kebab-friendly name from the last path segment", () => { + expect(parseSkillSource("github.com/org/my-awesome-skill")?.suggestedName).toBe("my-awesome-skill"); + expect(parseSkillSource("github.com/org/repo/tree/main/plugins/cool-skill")?.suggestedName).toBe("cool-skill"); + expect(parseSkillSource("gitlab.com/org/repo", "plugins/x")?.suggestedName).toBe("x"); + }); + + it("rejects a bad explicit subfolder for a github repo", () => { + expect(parseSkillSource("github.com/org/repo", "../etc")).toBeNull(); + expect(parseSkillSource("github.com/org/repo", "/abs")).toBeNull(); + expect(parseSkillSource("github.com/org/repo", "a//b")).toBeNull(); + }); + + it("treats a blob URL pointing at a root file as the plain repo", () => { + expect(parseSkillSource("github.com/org/repo/blob/main/SKILL.md")?.parsed).toEqual({ + source: "github", + repo: "org/repo", + }); + }); + + it("strips query strings and fragments before parsing", () => { + expect(parseSkillSource("github.com/org/repo?tab=readme")?.parsed).toEqual({ source: "github", repo: "org/repo" }); + expect(parseSkillSource("github.com/org/repo#section")?.parsed).toEqual({ source: "github", repo: "org/repo" }); + }); + + it("rejects a tree URL whose folder has a space or percent-encoded segment", () => { + expect(parseSkillSource("github.com/org/repo/tree/main/a b")).toBeNull(); + expect(parseSkillSource("github.com/org/repo/tree/main/a%20b")).toBeNull(); + }); + + it("routes uppercase and www github hosts through the github shorthand", () => { + expect(parseSkillSource("GitHub.com/org/repo/tree/main/x")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "x", + }); + expect(parseSkillSource("www.github.com/org/repo")?.parsed).toEqual({ source: "github", repo: "org/repo" }); + }); + + it("keeps a dotted folder name as the subdir path", () => { + expect(parseSkillSource("github.com/org/repo/blob/main/my.skill")?.parsed).toEqual({ + source: "git-subdir", + url: "https://github.com/org/repo", + path: "my.skill", + }); + }); + + it("falls back to the repo for a tree URL with a branch but no folder", () => { + expect(parseSkillSource("github.com/org/repo/tree/main")?.parsed).toEqual({ source: "github", repo: "org/repo" }); + }); + + it("kebab-cases the suggested name from a mixed-case repo", () => { + expect(parseSkillSource("github.com/Org/My_Repo")?.suggestedName).toBe("my-repo"); + }); + + it("rejects a bare host or single-segment raw git url", () => { + expect(parseSkillSource("gitlab.com")).toBeNull(); + expect(parseSkillSource("gitlab.com/org")).toBeNull(); + }); +}); + +// Skill sources are served on the unauthenticated public feeds and cloned by clients, so the +// parser must never publish an insecure, credentialed, internal, or malformed clone URL. +describe("parseSkillSource — security boundary", () => { + it("rejects non-https schemes", () => { + for (const url of [ + "http://gitlab.com/org/repo", + "HTTP://gitlab.com/org/repo", + "ssh://gitlab.com/org/repo", + "git://gitlab.com/org/repo", + "ftp://gitlab.com/org/repo", + "file:///etc/passwd", + "javascript:alert(1)", + "data:text/plain,hi", + "//gitlab.com/org/repo", + ]) { + expect(parseSkillSource(url)).toBeNull(); + } + }); + + it("rejects URLs with embedded credentials", () => { + expect(parseSkillSource("https://user:token@gitlab.com/org/repo")).toBeNull(); + expect(parseSkillSource("https://user@gitlab.com/org/repo")).toBeNull(); + // userinfo confusion: the real host is evil.com, not github.com + expect(parseSkillSource("https://github.com@evil.com/org/repo")).toBeNull(); + }); + + it("rejects IP-literal hosts (loopback, private, metadata, obfuscated, IPv6)", () => { + for (const url of [ + "https://127.0.0.1/org/repo", + "https://10.0.0.5/org/repo", + "https://169.254.169.254/org/repo", + "https://2130706433/org/repo", + "https://[::ffff:127.0.0.1]/org/repo", + ]) { + expect(parseSkillSource(url)).toBeNull(); + } + }); + + it("does not grant GitHub shorthand to a look-alike host", () => { + expect(parseSkillSource("https://github.com.evil.com/org/repo")?.parsed).toEqual({ + source: "url", + url: "https://github.com.evil.com/org/repo", + }); + }); + + it("rejects GitHub org/repo segments with illegal characters", () => { + expect(parseSkillSource("github.com/o@x/repo")).toBeNull(); + expect(parseSkillSource("github.com/org/..%2f..%2fx")).toBeNull(); + }); +}); + +describe("isValidSubPath", () => { + it("accepts relative segment paths", () => { + expect(isValidSubPath("plugins/x")).toBe(true); + expect(isValidSubPath("sub/dir")).toBe(true); + expect(isValidSubPath("a.b-c_d")).toBe(true); + expect(isValidSubPath("plugins/x/")).toBe(true); + }); + + it("rejects empty, traversal, absolute, and double-slash paths", () => { + expect(isValidSubPath("")).toBe(false); + expect(isValidSubPath("../etc")).toBe(false); + expect(isValidSubPath("/abs")).toBe(false); + expect(isValidSubPath("a//b")).toBe(false); + }); +}); diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts index d696a78b4cc..cab3c5cba3c 100644 --- a/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts +++ b/ui/litellm-dashboard/src/components/claude_code_plugins/helpers.ts @@ -4,15 +4,189 @@ import { PluginSource, MarketplacePluginEntry } from "./types"; +export interface SkillSourcePreview { + parsed: PluginSource; + label: string; + suggestedName: string; +} + +export const SUBDIR_PATH_REGEX = /^[a-zA-Z0-9][a-zA-Z0-9._-]*(\/[a-zA-Z0-9][a-zA-Z0-9._-]*)*$/; + +export const normalizeSubPath = (subPath: string): string => subPath.trim().replace(/\/+$/, ""); + +export const isValidSubPath = (subPath: string): boolean => { + const normalized = normalizeSubPath(subPath); + return normalized !== "" && SUBDIR_PATH_REGEX.test(normalized); +}; + +const GITHUB_HOST = "github.com"; + +const SKILL_FILE_EXTENSION_REGEX = /\.(md|markdown|txt|json|ya?ml|toml)$/i; + +// WHATWG normalizes obfuscated IPv4 (e.g. 2130706433, 0x7f.0.0.1) to dotted-decimal, so this +// catches every IPv4 form; bracketed IPv6 is rejected separately. +const IPV4_HOST_REGEX = /^\d{1,3}(\.\d{1,3}){3}$/; + +const GITHUB_ORG_REGEX = /^[A-Za-z0-9-]+$/; +const GITHUB_REPO_REGEX = /^[A-Za-z0-9._-]+$/; + +const buildRepoUrl = (url: URL): string => `${url.protocol}//${url.host}${url.pathname.replace(/\/+$/, "")}`; + +const pathSegments = (url: URL): string[] => url.pathname.split("/").filter((seg) => seg !== ""); + +/** + * Validate and normalize a repository URL into a parsed URL, or null. Enforces https (rejects + * http/ssh/git/etc.), rejects embedded credentials, and requires a dotted host, so the public + * skill feeds never serve an insecure or credentialed clone URL. Everything downstream parses + * this normalized object rather than the raw string. + */ +const parseRepoUrl = (raw: string): URL | null => { + const trimmed = raw.trim(); + if (trimmed === "" || trimmed.startsWith("//")) { + return null; + } + const withScheme = /^[a-z][a-z0-9+.-]*:\/\//i.test(trimmed) ? trimmed : `https://${trimmed}`; + let url: URL; + try { + url = new URL(withScheme); + } catch { + return null; + } + if ( + url.protocol !== "https:" || + url.username !== "" || + url.password !== "" || + !url.hostname.includes(".") || + url.hostname.startsWith("[") || + IPV4_HOST_REGEX.test(url.hostname) + ) { + return null; + } + return url; +}; + +const lastSegment = (path: string): string => { + const segments = path.split("/").filter((seg) => seg !== ""); + return segments[segments.length - 1] ?? ""; +}; + +const toKebabCase = (value: string): string => + value + .toLowerCase() + .replace(/[^a-z0-9-]+/g, "-") + .replace(/-+/g, "-") + .replace(/^-+|-+$/g, ""); + +const parseGitHubSource = (url: URL, subPath?: string): SkillSourcePreview | null => { + const parts = pathSegments(url); + if (parts.length < 2) { + return null; + } + + const org = parts[0]; + const repoBase = parts[1].replace(/\.git$/, ""); + if (!GITHUB_ORG_REGEX.test(org) || !GITHUB_REPO_REGEX.test(repoBase)) { + return null; + } + const repoFull = `${org}/${repoBase}`; + const repoUrl = `https://github.com/${repoFull}`; + const repoPreview: SkillSourcePreview = { + parsed: { source: "github", repo: repoFull }, + label: `GitHub repo — ${repoFull}`, + suggestedName: toKebabCase(repoBase), + }; + + const isTreeOrBlob = parts.length >= 4 && (parts[2] === "tree" || parts[2] === "blob"); + if (isTreeOrBlob) { + const pathParts = parts.slice(4); + const last = lastSegment(pathParts.join("/")); + const effective = SKILL_FILE_EXTENSION_REGEX.test(last) ? pathParts.slice(0, -1) : pathParts; + if (effective.length === 0) { + return repoPreview; + } + const path = normalizeSubPath(effective.join("/")); + if (!SUBDIR_PATH_REGEX.test(path)) { + return null; + } + return { + parsed: { source: "git-subdir", url: repoUrl, path }, + label: `GitHub subdir — ${repoFull} @ ${path}`, + suggestedName: toKebabCase(lastSegment(path)), + }; + } + + if (parts.length !== 2) { + return null; + } + + const normalized = normalizeSubPath(subPath ?? ""); + if (normalized !== "") { + if (!SUBDIR_PATH_REGEX.test(normalized)) { + return null; + } + return { + parsed: { source: "git-subdir", url: repoUrl, path: normalized }, + label: `GitHub subdir — ${repoFull} @ ${normalized}`, + suggestedName: toKebabCase(lastSegment(normalized)), + }; + } + + return repoPreview; +}; + +const parseRawGitSource = (url: URL, subPath?: string): SkillSourcePreview | null => { + if (pathSegments(url).length < 2) { + return null; + } + + const repoUrl = buildRepoUrl(url); + + const normalized = normalizeSubPath(subPath ?? ""); + if (normalized !== "") { + if (!SUBDIR_PATH_REGEX.test(normalized)) { + return null; + } + return { + parsed: { source: "git-subdir", url: repoUrl, path: normalized }, + label: `Git subdir — ${repoUrl} @ ${normalized}`, + suggestedName: toKebabCase(lastSegment(normalized)), + }; + } + + return { + parsed: { source: "url", url: repoUrl }, + label: `Git repo — ${repoUrl}`, + suggestedName: toKebabCase(lastSegment(url.pathname).replace(/\.git$/, "")), + }; +}; + +/** + * Parse any git-accessible repository URL into a registerable skill source. + * GitHub URLs keep their `github`/`git-subdir` shorthand; every other host is + * treated as a raw repo URL, with an optional subfolder turning it into git-subdir. + */ +export const parseSkillSource = (rawUrl: string, subPath?: string): SkillSourcePreview | null => { + const url = parseRepoUrl(rawUrl); + if (!url) { + return null; + } + if (url.hostname.replace(/^www\./, "") === GITHUB_HOST) { + return parseGitHubSource(url, subPath); + } + return parseRawGitSource(url, subPath); +}; + /** * Generate install command for Claude Code CLI * Format: /plugin marketplace add org/repo OR /plugin marketplace add url */ export const formatInstallCommand = (plugin: { name: string; source: PluginSource }): string => { - if (plugin.source.source === "github" && plugin.source.repo) { - return `/plugin marketplace add ${plugin.source.repo}`; - } else if (plugin.source.source === "url" && plugin.source.url) { - return `/plugin marketplace add ${plugin.source.url}`; + const { source } = plugin; + if (source.source === "github" && source.repo) { + return `/plugin marketplace add ${source.repo}`; + } + if ((source.source === "url" || source.source === "git-subdir") && source.url) { + return `/plugin marketplace add ${source.url}`; } // Fallback to plugin name return `/plugin marketplace add ${plugin.name}`; @@ -55,7 +229,11 @@ export const validatePluginName = (name: string): boolean => { export const getSourceDisplayText = (source: PluginSource): string => { if (source.source === "github" && source.repo) { return `GitHub: ${source.repo}`; - } else if (source.source === "url" && source.url) { + } + if (source.source === "git-subdir" && source.url && source.path) { + return `${source.url} @ ${source.path}`; + } + if (source.source === "url" && source.url) { return source.url; } return "Unknown source"; @@ -67,7 +245,8 @@ export const getSourceDisplayText = (source: PluginSource): string => { export const getSourceLink = (source: PluginSource): string | null => { if (source.source === "github" && source.repo) { return `https://github.com/${source.repo}`; - } else if (source.source === "url" && source.url) { + } + if ((source.source === "url" || source.source === "git-subdir") && source.url) { return source.url; } return null; diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/types.ts b/ui/litellm-dashboard/src/components/claude_code_plugins/types.ts index fcb1146685d..d16c880749b 100644 --- a/ui/litellm-dashboard/src/components/claude_code_plugins/types.ts +++ b/ui/litellm-dashboard/src/components/claude_code_plugins/types.ts @@ -1,8 +1,12 @@ /** * TypeScript types for Claude Code Marketplace - * Matches backend API types from /litellm/types/proxy/claude_code_endpoints.py + * API request/response shapes are synced from the generated OpenAPI types in @/lib/http/schema. */ +import type { components } from "@/lib/http/schema"; + +// Kept hand-written: the backend types `source` as Dict[str, str], so the generated type is a +// loose string map; this discriminant union is what the parser and display helpers rely on. export interface PluginSource { source: "github" | "url" | "git-subdir"; repo?: string; // Format: "org/repo" for GitHub @@ -10,10 +14,7 @@ export interface PluginSource { path?: string; // Subdirectory path for git-subdir } -export interface PluginAuthor { - name: string; - email?: string; -} +export type PluginAuthor = components["schemas"]["PluginAuthor"]; export interface Plugin { id: string; @@ -56,24 +57,12 @@ export interface ListPluginsResponse { count: number; } -export interface RegisterPluginRequest { - name: string; +// Request envelope synced from the OpenAPI spec, with `source` narrowed to our PluginSource +// union and `version` kept optional (the backend supplies its default). +export type SkillRegisterRequest = Omit & { source: PluginSource; version?: string; - description?: string; - author?: PluginAuthor; - homepage?: string; - keywords?: string[]; - category?: string; - domain?: string; - namespace?: string; -} - -export interface RegisterPluginResponse { - plugin: Plugin; - action: "created" | "updated"; - message: string; -} +}; // Public marketplace types export interface MarketplacePluginEntry { @@ -104,20 +93,3 @@ export interface CategoryTab { label: string; count: number; } - -export interface PluginFormData { - name: string; - sourceType: "github" | "url" | "git-subdir"; - repo: string; - url: string; - path: string; - version: string; - description: string; - authorName: string; - authorEmail: string; - homepage: string; - category: string; - keywords: string; // Comma-separated string, will be split into array - domain: string; - namespace: string; -} diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx index f5bae832e64..0bbf4d2a6e8 100644 --- a/ui/litellm-dashboard/src/components/networking.tsx +++ b/ui/litellm-dashboard/src/components/networking.tsx @@ -27,6 +27,7 @@ import { TagNewRequest, TagUpdateRequest, TagListResponse, TagInfoResponse } fro import { Team } from "./key_team_helpers/key_list"; import { UserInfo } from "./view_users/types"; import { EmailEventSettingsResponse, EmailEventSettingsUpdateRequest } from "./email_events/types"; +import type { SkillRegisterRequest } from "./claude_code_plugins/types"; import { jsonFields } from "./common_components/check_openapi_schema"; import NotificationsManager from "./molecules/notifications_manager"; import type { MCPUserEnvVarsStatus } from "./mcp_tools/types"; @@ -7402,19 +7403,7 @@ export const getClaudeCodePluginDetails = async (accessToken: string, pluginName * @param accessToken - Admin access token * @param pluginData - Plugin registration data */ -export const registerClaudeCodePlugin = async ( - accessToken: string, - pluginData: { - name: string; - source: { source: string; repo?: string; url?: string }; - version?: string; - description?: string; - author?: { name: string; email?: string }; - homepage?: string; - keywords?: string[]; - category?: string; - }, -) => { +export const registerClaudeCodePlugin = async (accessToken: string, pluginData: SkillRegisterRequest) => { try { const proxyBaseUrl = getProxyBaseUrl(); const url = proxyBaseUrl ? `${proxyBaseUrl}/claude-code/plugins` : `/claude-code/plugins`; @@ -7429,8 +7418,13 @@ export const registerClaudeCodePlugin = async ( }); if (!response.ok) { - const errorData = await response.text(); - const errorMessage = deriveErrorMessage(JSON.parse(errorData)); + const errorBody = await response.text(); + let errorMessage: string; + try { + errorMessage = deriveErrorMessage(JSON.parse(errorBody)); + } catch { + errorMessage = errorBody || `Request failed with status ${response.status}`; + } handleError(errorMessage); throw new Error(errorMessage); } From 6ab3742fa673467433070c926986aa2600f45928 Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 20:31:02 +0300 Subject: [PATCH 15/79] perf(spend): move cost-callback payload deepcopy off the request event loop (#31579) --- litellm/proxy/db/db_spend_update_writer.py | 20 ++- .../proxy/db/test_db_spend_update_writer.py | 118 +++++++++++++++++- 2 files changed, 124 insertions(+), 14 deletions(-) diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py index cf4c3e98f00..ca6875ca800 100644 --- a/litellm/proxy/db/db_spend_update_writer.py +++ b/litellm/proxy/db/db_spend_update_writer.py @@ -175,16 +175,9 @@ class DBSpendUpdateWriter: if team_id is not None and team_id != "": payload["team_id"] = team_id - # One deepcopy shared by all 6 daily spend helpers (was 5, fixes agent bug) - payload_copy = copy.deepcopy(payload) - - # Deepcopy request_tags for _update_tag_db - request_tags = copy.deepcopy(payload.get("request_tags")) - - # Keep _insert_spend_log_to_db awaited inline (not a task, preserve current behavior) if disable_spend_logs is False: await self._insert_spend_log_to_db( - payload=copy.deepcopy(payload), + payload=payload, prisma_client=prisma_client, ) else: @@ -204,8 +197,7 @@ class DBSpendUpdateWriter: prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, litellm_proxy_budget_name=litellm_proxy_budget_name, - payload_copy=payload_copy, - request_tags=request_tags, + payload=payload, ) ) @@ -336,14 +328,18 @@ class DBSpendUpdateWriter: prisma_client: Optional[PrismaClient], user_api_key_cache: DualCache, litellm_proxy_budget_name: Optional[str], - payload_copy: SpendLogsPayload, - request_tags: Optional[Any], + payload: SpendLogsPayload, ): """ Runs all 11 spend-update helpers sequentially inside a single asyncio task. Each helper is wrapped in try/except so one failure doesn't prevent the others. + + The deepcopy runs here, off the awaited request path, so the daily spend + helpers get a payload isolated from the spend-log queue entry and the caller. """ + payload_copy = copy.deepcopy(payload) + request_tags = payload_copy.get("request_tags") try: await self._update_user_db( response_cost=response_cost, diff --git a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py index 04c93f48ca9..c29cdaf4171 100644 --- a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py +++ b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py @@ -1,4 +1,5 @@ import asyncio +import copy import json import os import sys @@ -1419,8 +1420,7 @@ async def test_batch_database_updates_isolation_on_failure(): prisma_client=MagicMock(), user_api_key_cache=MagicMock(), litellm_proxy_budget_name="budget", - payload_copy={"key": "value"}, - request_tags=None, + payload={"key": "value"}, ) # _update_key_db raised, but all others should still have been called @@ -1704,3 +1704,117 @@ async def test_commit_spend_updates_iterates_in_sorted_order( ) assert captured_where_values == expected_order + + +@pytest.mark.asyncio +async def test_update_database_does_not_deepcopy_on_request_path(): + """ + Regression for LIT-4088: copy.deepcopy must not run while the caller awaits + update_database(). The deepcopy used to isolate the daily-spend helpers is + relocated into the _batch_database_updates background task, and the spend-log + insert receives the payload directly (all consumers are read-only). + + Asserts: + - zero copy.deepcopy calls happen on the awaited request path + - the batch background task still hands the daily helpers an isolated copy + (mutating the original after the task ran does not bleed into it) + - the spend-log insert receives the payload on the request path with the + correct content + """ + db_writer = DBSpendUpdateWriter() + + captured_batch_payloads = [] + captured_spend_log = {} + + async def capture_batch_payload(**kwargs): + captured_batch_payloads.append(kwargs.get("payload")) + + async def capture_spend_log(**kwargs): + payload = kwargs.get("payload") + captured_spend_log["ref"] = payload + captured_spend_log["model_at_call"] = payload["model"] + + db_writer._insert_spend_log_to_db = AsyncMock(side_effect=capture_spend_log) + db_writer._update_user_db = AsyncMock() + db_writer._update_key_db = AsyncMock() + db_writer._update_team_db = AsyncMock() + db_writer._update_org_db = AsyncMock() + db_writer._update_tag_db = AsyncMock() + db_writer._update_agent_db = AsyncMock() + db_writer.add_spend_log_transaction_to_daily_user_transaction = AsyncMock( + side_effect=capture_batch_payload + ) + db_writer.add_spend_log_transaction_to_daily_end_user_transaction = AsyncMock() + db_writer.add_spend_log_transaction_to_daily_agent_transaction = AsyncMock() + db_writer.add_spend_log_transaction_to_daily_team_transaction = AsyncMock() + db_writer.add_spend_log_transaction_to_daily_org_transaction = AsyncMock() + db_writer.add_spend_log_transaction_to_daily_tag_transaction = AsyncMock() + + fake_payload = { + "startTime": "2024-01-01T00:00:00", + "endTime": "2024-01-01T00:01:00", + "model": "gpt-4", + "custom_llm_provider": "openai", + "request_tags": '["prod-tag"]', + "spend": 0.0, + "nested": {"a": 1}, + } + + deepcopy_calls = [] + real_deepcopy = copy.deepcopy + + def counting_deepcopy(obj, *args, **kwargs): + deepcopy_calls.append(obj) + return real_deepcopy(obj, *args, **kwargs) + + with ( + patch("litellm.proxy.proxy_server.disable_spend_logs", False), + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), + patch("litellm.proxy.proxy_server.user_api_key_cache", MagicMock()), + patch("litellm.proxy.proxy_server.litellm_proxy_budget_name", "test-budget"), + patch( + "litellm.proxy.spend_tracking.spend_tracking_utils.get_logging_payload", + return_value=fake_payload, + ), + patch( + "litellm.proxy.db.db_spend_update_writer.copy.deepcopy", + counting_deepcopy, + ), + ): + await db_writer.update_database( + token="test-token", + user_id="test-user", + end_user_id="test-end-user", + team_id="test-team", + org_id="test-org", + kwargs={"model": "gpt-4", "custom_llm_provider": "openai"}, + completion_response=MagicMock(), + start_time=datetime.now(), + end_time=datetime.now(), + response_cost=0.1, + ) + + # Request path is clean: nothing was deepcopied while the caller awaited. + assert len(deepcopy_calls) == 0 + + # The spend-log insert ran inline on the request path with the real payload. + assert captured_spend_log["ref"] is fake_payload + assert captured_spend_log["model_at_call"] == "gpt-4" + assert fake_payload["spend"] == 0.1 + + # Now let the batch background task run; the deepcopy happens here. + await asyncio.sleep(0) + + assert len(deepcopy_calls) >= 1 + assert len(captured_batch_payloads) == 1 + batch_payload = captured_batch_payloads[0] + assert batch_payload is not fake_payload + assert batch_payload["model"] == "gpt-4" + assert batch_payload["spend"] == 0.1 + + # Mutating the original after the batch task captured its snapshot must not + # leak into the daily helper's isolated copy. + fake_payload["model"] = "MUTATED" + fake_payload["nested"]["a"] = 999 + assert batch_payload["model"] == "gpt-4" + assert batch_payload["nested"]["a"] == 1 From 59f51b2d72c0a9eefc06e9825ecff908f9dfdfb7 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 10:46:47 -0700 Subject: [PATCH 16/79] chore: prevent CLAUDE.md comment bloat (#31729) The existing comment rule is not strict enough --- CLAUDE.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index cea38b8527b..0cd1605b1b2 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -1,8 +1,7 @@ -Do not write comments unless they are absolutely necessary to explain some very complex business logic. Please clean up if there are comments that are not absolutely necessary. Do not remove comments that are unrelated to the addition of the code of this PR - -Explanation: code comments are, in a way, a violation of DRY code. You must update logic in two locations to change the code and "hard to change" is literally the definition of tech debt. We should instead aim to write code that is intuitive to the reader, while being both easy to maintain and high performance +Do not write any comments (existing comments can stay) unless explicitly asked to in a user (not system) prompt Don't assume that the existing code is correct or the right way of doing things / good coding patterns. In fact, there are a lot of bad coding practices, overly complex code, code smells, etc. If something doesn't look right, speak up. Feel free to break existing patterns or question weird existing code to make new code high quality, as in: + - correct - secure - performant From 1815636e1ce165096f45eceed5b968db01639402 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Tue, 30 Jun 2026 10:58:22 -0700 Subject: [PATCH 17/79] feat(guardrails): expose streaming knobs on generic_guardrail_api (#31730) * feat(guardrails): expose streaming knobs on generic_guardrail_api Wire streaming_end_of_stream_only and streaming_sampling_rate through optional params, initialize_guardrail, and get_config_model so the generic guardrail API participates in UnifiedLLMGuardrails streaming checks with configurable cadence and end-of-stream-only mode. * fix(guardrails): use builtin type[] in get_config_model return Avoids a new UP006 violation that tripped the ruff strict-rule budget gate on the PR lint job. * fix(guardrails): default optional streaming knobs to None Non-None Pydantic defaults on GenericGuardrailAPIOptionalParams made _get_config_value treat unset nested fields as explicit values, which shadowed top-level litellm_params streaming flags whenever any other optional_params key was present. Real defaults stay in the constructor. * fix(guardrails): address review nits on generic_guardrail_api streaming Validate streaming_sampling_rate >= 1 in the constructor and Pydantic optional_params (ge=1), and add /v1/responses streaming coverage through the unified post-call hook so Responses API usage is exercised alongside chat completions. * fix(guardrails): read nested streaming config from dict optional_params Guardrail API/UI delivers optional_params as a plain dict, so getattr was silently ignoring streaming_sampling_rate and streaming_end_of_stream_only. Handle both dict and model shapes in _get_config_value with regression tests. * fix(guardrails): clear ruff findings in generic_guardrail_api tests/types * style(guardrails): ruff format generic_guardrail_api modules --------- Co-authored-by: Marton Schneider --- .../generic_guardrail_api/__init__.py | 18 +- .../generic_guardrail_api.py | 20 + .../guardrail_hooks/generic_guardrail_api.py | 26 +- .../test_generic_guardrail_api.py | 716 +++++++++++++++++- 4 files changed, 775 insertions(+), 5 deletions(-) diff --git a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py index 2386f80e819..63ead52baa6 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py @@ -1,4 +1,4 @@ -from typing import TYPE_CHECKING +from typing import TYPE_CHECKING, Any, Optional from litellm.types.guardrails import SupportedGuardrailIntegrations @@ -8,9 +8,23 @@ if TYPE_CHECKING: from litellm.types.guardrails import Guardrail, LitellmParams +def _get_config_value(litellm_params: Any, optional_params: Any, attribute_name: str) -> Optional[Any]: + if optional_params is not None: + value = ( + optional_params.get(attribute_name) + if isinstance(optional_params, dict) + else getattr(optional_params, attribute_name, None) + ) + if value is not None: + return value + return getattr(litellm_params, attribute_name, None) + + def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail"): import litellm + optional_params = getattr(litellm_params, "optional_params", None) + _generic_guardrail_api_callback = GenericGuardrailAPI( api_base=litellm_params.api_base, api_key=litellm_params.api_key, @@ -22,6 +36,8 @@ def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail" guardrail_name=guardrail.get("guardrail_name", ""), event_hook=litellm_params.mode, default_on=litellm_params.default_on, + streaming_end_of_stream_only=_get_config_value(litellm_params, optional_params, "streaming_end_of_stream_only"), + streaming_sampling_rate=_get_config_value(litellm_params, optional_params, "streaming_sampling_rate"), ) litellm.logging_callback_manager.add_litellm_callback(_generic_guardrail_api_callback) diff --git a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py index df80ea09de0..dc519f56d1a 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py +++ b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py @@ -33,6 +33,7 @@ from litellm.types.utils import GenericGuardrailAPIInputs if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.types.proxy.guardrails.guardrail_hooks.base import GuardrailConfigModel GUARDRAIL_NAME = "generic_guardrail_api" @@ -178,6 +179,8 @@ class GenericGuardrailAPI(CustomGuardrail): unreachable_fallback: Literal["fail_closed", "fail_open"] = "fail_closed", fail_on_error: Optional[bool] = True, extra_headers: Optional[list] = None, + streaming_end_of_stream_only: Optional[bool] = None, + streaming_sampling_rate: Optional[int] = None, **kwargs, ): self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback) @@ -209,6 +212,15 @@ class GenericGuardrailAPI(CustomGuardrail): self.fail_on_error: bool = True if fail_on_error is None else fail_on_error + # Read by UnifiedLLMGuardrails.async_post_call_streaming_iterator_hook + # via getattr(guardrail_to_apply, "streaming_*", default). + self.streaming_end_of_stream_only: bool = ( + False if streaming_end_of_stream_only is None else streaming_end_of_stream_only + ) + if streaming_sampling_rate is not None and streaming_sampling_rate < 1: + raise ValueError(f"streaming_sampling_rate must be >= 1 (got {streaming_sampling_rate})") + self.streaming_sampling_rate: int = 5 if streaming_sampling_rate is None else streaming_sampling_rate + # Set supported event hooks if "supported_event_hooks" not in kwargs: kwargs["supported_event_hooks"] = [ @@ -470,3 +482,11 @@ class GenericGuardrailAPI(CustomGuardrail): return self._handle_guardrail_request_error(e, inputs, input_type, logging_obj) except Exception as e: return self._handle_guardrail_request_error(e, inputs, input_type, logging_obj, is_unreachable=False) + + @staticmethod + def get_config_model() -> Optional[type["GuardrailConfigModel"]]: + from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + GenericGuardrailAPIConfigModel, + ) + + return GenericGuardrailAPIConfigModel diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py b/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py index 28fb482b3af..d0ac8bb8998 100644 --- a/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py +++ b/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py @@ -1,7 +1,7 @@ from typing import Any, Dict, List, Literal, Optional, Union from pydantic import BaseModel, ConfigDict, Field -from typing_extensions import TYPE_CHECKING, TypedDict +from typing_extensions import TypedDict from litellm.types.llms.openai import ( AllMessageValues, @@ -60,6 +60,30 @@ class GenericGuardrailAPIOptionalParams(BaseModel): ), ) + streaming_end_of_stream_only: Optional[bool] = Field( + default=None, + description=( + "If False (default when unset), the guardrail runs on sampled chunks during " + "the stream at the cadence set by streaming_sampling_rate, and an in-flight " + "BLOCKED stops further chunks from streaming. If True, the guardrail runs " + "once at end of stream over the assembled response; lower cost and latency, " + "but flagged content has already streamed to the client before the terminal " + "block. Defaults are applied in GenericGuardrailAPI.__init__ when None so " + "unset optional_params does not shadow top-level litellm_params." + ), + ) + + streaming_sampling_rate: Optional[int] = Field( + default=None, + ge=1, + description=( + "When streaming_end_of_stream_only is False, the guardrail runs every Nth " + "streamed chunk. Ignored when streaming_end_of_stream_only is True. " + "Must be >= 1 when set. Defaults to 5 in GenericGuardrailAPI.__init__ " + "when None so unset optional_params does not shadow top-level litellm_params." + ), + ) + class GenericGuardrailAPIConfigModel( GuardrailConfigModel[GenericGuardrailAPIOptionalParams], diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py index 399442a5f71..791fdd4077c 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py @@ -609,7 +609,6 @@ class TestImageSupport: request_data=mock_request_data_input, input_type="request", ) - result_texts = guardrailed_inputs.get("texts", []) result_images = guardrailed_inputs.get("images", None) # Verify API was called with images @@ -943,7 +942,7 @@ class TestMultimodalSupport: guardrail.async_handler, "post", return_value=mock_response ) as mock_post: # This should not raise SerializationIterator error - result = await guardrail.apply_guardrail( + await guardrail.apply_guardrail( inputs={ "texts": ["What's in this image?"], "images": ["https://example.com/image.jpg"], @@ -1006,7 +1005,7 @@ class TestMultimodalSupport: with patch.object( guardrail.async_handler, "post", return_value=mock_response ) as mock_post: - result = await guardrail.apply_guardrail( + await guardrail.apply_guardrail( inputs={ "texts": ["Hello", "World"], "structured_messages": messages_with_iterable, @@ -1023,6 +1022,717 @@ class TestMultimodalSupport: assert isinstance(json_payload["structured_messages"], list) +def _make_stream_chunk(content: str, finish_reason=None): + """Build a real ModelResponseStream so the handler's isinstance checks pass.""" + from litellm.types.utils import Delta, ModelResponseStream + + return ModelResponseStream( + model="gpt-4", + choices=[ + litellm.StreamingChoices( + index=0, + delta=Delta(role="assistant", content=content), + finish_reason=finish_reason, + ) + ], + ) + + +def _make_assembled_model_response(content: str) -> ModelResponse: + return ModelResponse( + id="mock-response", + model="gpt-4", + choices=[ + litellm.Choices( + index=0, + message=litellm.Message(role="assistant", content=content), + finish_reason="stop", + ) + ], + ) + + +def _mock_guardrail_post_response(action: str = "NONE", texts=None, blocked_reason=None): + mock_response = MagicMock() + payload = {"action": action} + if texts is not None: + payload["texts"] = texts + if blocked_reason is not None: + payload["blocked_reason"] = blocked_reason + mock_response.json.return_value = payload + mock_response.raise_for_status = MagicMock() + return mock_response + + +def _make_responses_stream_events(text: str): + """Minimal /v1/responses SSE event sequence ending in response.completed.""" + return ( + {"type": "response.created", "response": {"id": "resp_test"}}, + { + "type": "response.output_item.added", + "item": {"type": "message", "id": "msg_test"}, + }, + { + "type": "response.content_part.added", + "part": {"type": "output_text", "text": ""}, + }, + {"type": "response.output_text.delta", "delta": text}, + { + "type": "response.output_text.done", + "text": text, + }, + { + "type": "response.completed", + "response": { + "id": "resp_test", + "output": [ + { + "type": "message", + "id": "msg_test", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": text}], + } + ], + "status": "completed", + }, + }, + ) + + +class TestGenericGuardrailAPIStreamingConfig: + """Streaming knobs on GenericGuardrailAPI and initialize_guardrail plumbing.""" + + def test_streaming_defaults(self): + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + ) + assert guardrail.streaming_end_of_stream_only is False + assert guardrail.streaming_sampling_rate == 5 + + def test_streaming_overrides(self): + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_end_of_stream_only=True, + streaming_sampling_rate=2, + ) + assert guardrail.streaming_end_of_stream_only is True + assert guardrail.streaming_sampling_rate == 2 + + @pytest.mark.parametrize("invalid_rate", [0, -1, -5]) + def test_streaming_sampling_rate_rejects_non_positive(self, invalid_rate): + with pytest.raises(ValueError, match="streaming_sampling_rate must be >= 1"): + GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_sampling_rate=invalid_rate, + ) + + def test_optional_params_streaming_sampling_rate_ge_one(self): + from pydantic import ValidationError + + from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + GenericGuardrailAPIOptionalParams, + ) + + with pytest.raises(ValidationError): + GenericGuardrailAPIOptionalParams(streaming_sampling_rate=0) + + def test_get_config_model(self): + from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + GenericGuardrailAPIConfigModel, + ) + + assert GenericGuardrailAPI.get_config_model() is GenericGuardrailAPIConfigModel + + def test_initialize_guardrail_forwards_streaming_flags(self): + from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + initialize_guardrail, + ) + from litellm.types.guardrails import LitellmParams + + litellm_params = LitellmParams( + guardrail="generic_guardrail_api", + mode="post_call", + api_base="https://api.test.guardrail.com", + default_on=False, + ) + # LitellmParams uses extra="allow" on the base; set streaming knobs dynamically + litellm_params.streaming_end_of_stream_only = False # type: ignore[attr-defined] + litellm_params.streaming_sampling_rate = 3 # type: ignore[attr-defined] + + guardrail_config = {"guardrail_name": "test-generic-streaming"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ): + guardrail = initialize_guardrail(litellm_params, guardrail_config) + + assert guardrail.streaming_end_of_stream_only is False + assert guardrail.streaming_sampling_rate == 3 + + def test_initialize_guardrail_optional_params_defaults_do_not_shadow_top_level( + self, + ): + """Top-level streaming knobs win when optional_params only carries siblings.""" + from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + initialize_guardrail, + ) + from litellm.types.guardrails import LitellmParams + from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + GenericGuardrailAPIOptionalParams, + ) + + litellm_params = LitellmParams( + guardrail="generic_guardrail_api", + mode="post_call", + api_base="https://api.test.guardrail.com", + default_on=False, + ) + litellm_params.streaming_end_of_stream_only = True # type: ignore[attr-defined] + litellm_params.streaming_sampling_rate = 2 # type: ignore[attr-defined] + # Sibling optional_params only; streaming fields stay at Pydantic default None. + litellm_params.optional_params = GenericGuardrailAPIOptionalParams( # type: ignore[attr-defined] + additional_provider_specific_params={"tenant": "acme"}, + ) + + guardrail_config = {"guardrail_name": "test-generic-streaming-mixed"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ): + guardrail = initialize_guardrail(litellm_params, guardrail_config) + + assert guardrail.streaming_end_of_stream_only is True + assert guardrail.streaming_sampling_rate == 2 + + def test_initialize_guardrail_explicit_optional_params_streaming_wins(self): + from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + initialize_guardrail, + ) + from litellm.types.guardrails import LitellmParams + from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + GenericGuardrailAPIOptionalParams, + ) + + litellm_params = LitellmParams( + guardrail="generic_guardrail_api", + mode="post_call", + api_base="https://api.test.guardrail.com", + default_on=False, + ) + litellm_params.streaming_end_of_stream_only = False # type: ignore[attr-defined] + litellm_params.streaming_sampling_rate = 9 # type: ignore[attr-defined] + litellm_params.optional_params = GenericGuardrailAPIOptionalParams( # type: ignore[attr-defined] + streaming_end_of_stream_only=True, + streaming_sampling_rate=1, + ) + + guardrail_config = {"guardrail_name": "test-generic-streaming-nested-wins"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ): + guardrail = initialize_guardrail(litellm_params, guardrail_config) + + assert guardrail.streaming_end_of_stream_only is True + assert guardrail.streaming_sampling_rate == 1 + + def test_initialize_guardrail_dict_optional_params_streaming_wins(self): + """Guardrail API/UI delivers optional_params as a plain dict, not a model.""" + from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + initialize_guardrail, + ) + from litellm.types.guardrails import LitellmParams + + litellm_params = LitellmParams( + guardrail="generic_guardrail_api", + mode="post_call", + api_base="https://api.test.guardrail.com", + default_on=False, + ) + litellm_params.streaming_end_of_stream_only = False # type: ignore[attr-defined] + litellm_params.streaming_sampling_rate = 9 # type: ignore[attr-defined] + # Plain dict mirrors how configs arrive from the guardrail API/UI. + litellm_params.optional_params = { # type: ignore[attr-defined] + "streaming_end_of_stream_only": True, + "streaming_sampling_rate": 1, + } + + guardrail_config = {"guardrail_name": "test-generic-streaming-dict-optional"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ): + guardrail = initialize_guardrail(litellm_params, guardrail_config) + + assert guardrail.streaming_end_of_stream_only is True + assert guardrail.streaming_sampling_rate == 1 + + def test_initialize_guardrail_dict_optional_params_sibling_only_falls_through( + self, + ): + """Dict optional_params without streaming keys must not shadow top-level knobs.""" + from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( + initialize_guardrail, + ) + from litellm.types.guardrails import LitellmParams + + litellm_params = LitellmParams( + guardrail="generic_guardrail_api", + mode="post_call", + api_base="https://api.test.guardrail.com", + default_on=False, + ) + litellm_params.streaming_end_of_stream_only = True # type: ignore[attr-defined] + litellm_params.streaming_sampling_rate = 2 # type: ignore[attr-defined] + litellm_params.optional_params = { # type: ignore[attr-defined] + "additional_provider_specific_params": {"tenant": "acme"}, + } + + guardrail_config = {"guardrail_name": "test-generic-streaming-dict-sibling"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ): + guardrail = initialize_guardrail(litellm_params, guardrail_config) + + assert guardrail.streaming_end_of_stream_only is True + assert guardrail.streaming_sampling_rate == 2 + + +class TestGenericGuardrailAPIStreamingViaUnified: + """Streaming output checks routed through UnifiedLLMGuardrails.""" + + @pytest.mark.asyncio + async def test_streaming_safe_content_yields_all_chunks(self): + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + chunks_data = ["Hello", " ", "world", "!", " Goodbye"] + for i, content in enumerate(chunks_data): + yield _make_stream_chunk( + content, + finish_reason="stop" if i == len(chunks_data) - 1 else None, + ) + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="NONE", texts=["Hello world! Goodbye"] + ) + ) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("Hello world! Goodbye"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + chunks_received = 0 + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + chunks_received += 1 + + assert chunks_received == 5 + assert mock_post.await_count >= 1 + + @pytest.mark.asyncio + async def test_streaming_blocked_content_raises(self): + from litellm.exceptions import GuardrailRaisedException + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_sampling_rate=1, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + chunks_data = ["Hello", " ishaan", " here"] + for i, content in enumerate(chunks_data): + yield _make_stream_chunk( + content, + finish_reason="stop" if i == len(chunks_data) - 1 else None, + ) + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="BLOCKED", blocked_reason="Ishaan is not allowed" + ) + ) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("Hello ishaan here"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + with pytest.raises(GuardrailRaisedException) as exc_info: + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + pass + + assert "Ishaan is not allowed" in str(exc_info.value) + + @pytest.mark.asyncio + async def test_streaming_default_uses_sampled_cadence(self): + """Default samples every 5th chunk + final pass: 10 chunks → calls at 5, 10, and final = 3.""" + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + chunks_data = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"] + for i, content in enumerate(chunks_data): + yield _make_stream_chunk( + content, + finish_reason="stop" if i == len(chunks_data) - 1 else None, + ) + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="NONE", texts=["ABCDEFGHIJ"] + ) + ) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("ABCDEFGHIJ"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + pass + + assert mock_post.await_count == 3, ( + f"Expected 3 guardrail calls (2 sampled at chunks 5 / 10 + 1 final), " + f"got {mock_post.await_count}" + ) + for call in mock_post.await_args_list: + assert call.kwargs["json"]["input_type"] == "response" + + @pytest.mark.asyncio + async def test_streaming_end_of_stream_only_calls_guardrail_once(self): + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_end_of_stream_only=True, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + chunks_data = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"] + for i, content in enumerate(chunks_data): + yield _make_stream_chunk( + content, + finish_reason="stop" if i == len(chunks_data) - 1 else None, + ) + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="NONE", texts=["ABCDEFGHIJ"] + ) + ) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("ABCDEFGHIJ"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + pass + + assert mock_post.await_count == 1, ( + f"Expected exactly one guardrail call at end of stream, " + f"got {mock_post.await_count}" + ) + + @pytest.mark.asyncio + async def test_streaming_sampling_rate_override(self): + """sampling_rate=2 on 6 chunks → in-stream at 2,4,6 plus final = 4 calls.""" + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_end_of_stream_only=False, + streaming_sampling_rate=2, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + chunks_data = ["A", "B", "C", "D", "E", "F"] + for i, content in enumerate(chunks_data): + yield _make_stream_chunk( + content, + finish_reason="stop" if i == len(chunks_data) - 1 else None, + ) + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response(action="NONE", texts=["ABCDEF"]) + ) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("ABCDEF"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + pass + + assert mock_post.await_count == 4, ( + f"Expected 4 guardrail calls (3 sampled + 1 final aggregate), " + f"got {mock_post.await_count}" + ) + + @pytest.mark.asyncio + async def test_streaming_fail_open_on_unreachable_continues_stream(self): + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + unreachable_fallback="fail_open", + streaming_end_of_stream_only=True, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_stream(): + for i, content in enumerate(["A", "B", "C"]): + yield _make_stream_chunk( + content, finish_reason="stop" if i == 2 else None + ) + + mock_post = AsyncMock(side_effect=httpx.ConnectError("connection refused")) + + with ( + patch.object(guardrail.async_handler, "post", mock_post), + patch( + "litellm.llms.openai.chat.guardrail_translation.handler.stream_chunk_builder", + return_value=_make_assembled_model_response("ABC"), + ), + ): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/chat/completions" + ) + request_data = { + "messages": [{"role": "user", "content": "hi"}], + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + chunks_received = 0 + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_stream(), + request_data=request_data, + ): + chunks_received += 1 + + assert chunks_received == 3 + + @pytest.mark.asyncio + async def test_responses_api_streaming_end_of_stream_only_calls_guardrail_once(self): + """/v1/responses path through unified hook; end-of-stream-only = one call.""" + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_end_of_stream_only=True, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_responses_stream(): + for event in _make_responses_stream_events("Hello world"): + yield event + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="NONE", texts=["Hello world"] + ) + ) + + with patch.object(guardrail.async_handler, "post", mock_post): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/v1/responses" + ) + request_data = { + "input": "hi", + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + events_received = 0 + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_responses_stream(), + request_data=request_data, + ): + events_received += 1 + + assert events_received == 6 + assert mock_post.await_count == 1, ( + f"Expected exactly one guardrail call at end of /v1/responses stream, " + f"got {mock_post.await_count}" + ) + assert mock_post.await_args.kwargs["json"]["input_type"] == "response" + + @pytest.mark.asyncio + async def test_responses_api_streaming_blocked_raises(self): + """Mid-stream BLOCKED on /v1/responses surfaces GuardrailRaisedException.""" + from litellm.exceptions import GuardrailRaisedException + from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import ( + UnifiedLLMGuardrails, + ) + + guardrail = GenericGuardrailAPI( + api_base="https://api.test.guardrail.com", + guardrail_name="test-generic-guardrail", + event_hook="post_call", + streaming_sampling_rate=1, + ) + unified_guardrail = UnifiedLLMGuardrails() + + async def mock_responses_stream(): + for event in _make_responses_stream_events("blocked content"): + yield event + + mock_post = AsyncMock( + return_value=_mock_guardrail_post_response( + action="BLOCKED", blocked_reason="Responses content not allowed" + ) + ) + + with patch.object(guardrail.async_handler, "post", mock_post): + user_api_key_dict = UserAPIKeyAuth( + api_key="test", request_route="/v1/responses" + ) + request_data = { + "input": "hi", + "guardrail_to_apply": guardrail, + "metadata": {"guardrails": ["test-generic-guardrail"]}, + } + + with pytest.raises(GuardrailRaisedException) as exc_info: + async for _ in unified_guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=user_api_key_dict, + response=mock_responses_stream(), + request_data=request_data, + ): + pass + + assert "Responses content not allowed" in str(exc_info.value) + class TestToolSupport: """Test tool handling in guardrail requests""" From fecaf5c9e525a50d1d49b4ce9df5ec1e5f699cfc Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 11:00:30 -0700 Subject: [PATCH 18/79] feat(router): tag routing denylist support via ! prefix (#31728) Adds `!` prefix negation to tag-based routing so callers can exclude deployments by exact tag value without enumerating every allowed alternative. `!provider:anthropic` removes all deployments tagged exactly `provider:anthropic` before routing, and positive and negation tags compose. Matching is exact literal membership (frozenset intersection), so there is no regex or ReDoS surface for client-supplied tags. Ban-only requests that carry only negation tags stay within the default pool, mirroring untagged-request semantics so callers can't use negation to escape it. Fallback chains keep working because get_deployments_for_tag runs on each routing hop Copy of #31680; implementation credit to @deepanshululla Co-authored-by: deepanshululla <15312873+deepanshululla@users.noreply.github.com> --- litellm/router_strategy/tag_based_routing.py | 107 ++- .../test_router_tag_routing.py | 662 ++++++++++++++++-- 2 files changed, 674 insertions(+), 95 deletions(-) diff --git a/litellm/router_strategy/tag_based_routing.py b/litellm/router_strategy/tag_based_routing.py index 65e76ba909b..6ca4e1de322 100644 --- a/litellm/router_strategy/tag_based_routing.py +++ b/litellm/router_strategy/tag_based_routing.py @@ -7,7 +7,7 @@ Use this to route requests between Teams """ import re -from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union +from typing import TYPE_CHECKING, Any, Literal, Optional, Union from litellm._logging import verbose_logger from litellm.types.router import RouterErrors @@ -21,8 +21,8 @@ else: def _is_valid_deployment_tag_regex( - tag_regexes: List[str], - header_strings: List[str], + tag_regexes: list[str], + header_strings: list[str], ) -> Optional[str]: """ Test compiled regex patterns against "Header-Name: value" strings. @@ -43,7 +43,7 @@ def _is_valid_deployment_tag_regex( return None -def is_valid_deployment_tag(deployment_tags: List[str], request_tags: List[str], match_any: bool = True) -> bool: +def is_valid_deployment_tag(deployment_tags: list[str], request_tags: list[str], match_any: bool = True) -> bool: """ Check if a tag is valid, the matching can be either any or all based on `match_any` flag """ @@ -71,10 +71,10 @@ def is_valid_deployment_tag(deployment_tags: List[str], request_tags: List[str], def _match_deployment( deployment: Any, - request_tags: Optional[List[str]], - header_strings: List[str], + request_tags: Optional[list[str]], + header_strings: list[str], match_any: bool, -) -> Optional[Dict[str, str]]: +) -> Optional[dict[str, str]]: """ Determine whether *deployment* matches the current request. @@ -87,8 +87,8 @@ def _match_deployment( ran and failed, so the regex cannot override strict-tag policy. """ litellm_params = deployment.get("litellm_params", {}) - deployment_tags: Optional[List[str]] = litellm_params.get("tags") - deployment_tag_regex: Optional[List[str]] = litellm_params.get("tag_regex") + deployment_tags: Optional[list[str]] = litellm_params.get("tags") + deployment_tag_regex: Optional[list[str]] = litellm_params.get("tag_regex") # 1. Exact tag match (existing behaviour). if deployment_tags and request_tags: @@ -114,11 +114,46 @@ def _match_deployment( return None +def _split_tags(tags: list[str]) -> tuple[list[str], list[str]]: + positive = [t for t in tags if not t.startswith("!")] + excluded = [tag[1:] for tag in tags if tag.startswith("!") and len(tag) > 1] + return positive, excluded + + +def _exclude_deployments( + deployments: Union[list[Any], dict[Any, Any]], + excluded_set: frozenset[str], +) -> list[Any]: + if not excluded_set: + return list(deployments) + return [d for d in deployments if not excluded_set.intersection(d.get("litellm_params", {}).get("tags") or [])] + + +def _require_candidates( + candidates: list[Any], + model: str, + request_tags: Any, +) -> list[Any]: + if not candidates: + raise ValueError( + f"{RouterErrors.no_deployments_with_tag_routing.value}. Passed model={model} and tags={request_tags}" + ) + return candidates + + +def _ban_only_base_pool( + deployments: Union[list[Any], dict[Any, Any]], +) -> list[Any]: + # Mirrors untagged-request semantics so callers can't use !tags to escape the default pool. + defaults = [d for d in deployments if "default" in (d.get("litellm_params", {}).get("tags") or [])] + return defaults if defaults else list(deployments) + + async def get_deployments_for_tag( llm_router_instance: LitellmRouter, model: str, # used to raise the correct error - healthy_deployments: Union[List[Any], Dict[Any, Any]], - request_kwargs: Optional[Dict[Any, Any]] = None, + healthy_deployments: Union[list[Any], dict[Any, Any]], + request_kwargs: Optional[dict[Any, Any]] = None, metadata_variable_name: Literal["metadata", "litellm_metadata"] = "metadata", ): """ @@ -136,13 +171,8 @@ async def get_deployments_for_tag( ) return healthy_deployments - if healthy_deployments is None: - verbose_logger.debug("get_deployments_for_tag: healthy_deployments is None returning healthy_deployments") - return healthy_deployments - - # Tag filtering applies only when there is at least one deployment to evaluate. - if isinstance(healthy_deployments, list) and len(healthy_deployments) == 0: - verbose_logger.debug("get_deployments_for_tag: empty candidate set; skipping tag filter") + if not healthy_deployments: + verbose_logger.debug("get_deployments_for_tag: empty or None healthy_deployments; skipping tag filter") return healthy_deployments verbose_logger.debug("request metadata: %s", request_kwargs.get(metadata_variable_name)) @@ -154,30 +184,36 @@ async def get_deployments_for_tag( # Build header strings for regex matching from what the proxy already stores. # Currently we match against User-Agent; format matches "^User-Agent: claude-code/..." user_agent = metadata.get("user_agent", "") - header_strings: List[str] = [f"User-Agent: {user_agent}"] if user_agent else [] + header_strings: list[str] = [f"User-Agent: {user_agent}"] if user_agent else [] - new_healthy_deployments: List[Any] = [] - default_deployments: List[Any] = [] + positive_tags, excluded_patterns = _split_tags(request_tags or []) + + excluded_set = frozenset(excluded_patterns) + candidates = _exclude_deployments(healthy_deployments, excluded_set) + + has_regex_deployments = any(d.get("litellm_params", {}).get("tag_regex") for d in candidates) + has_tag_filter = bool(positive_tags) or (bool(header_strings) and has_regex_deployments) + ban_only = bool(excluded_set) and not has_tag_filter + + if ban_only: + pool = _exclude_deployments(_ban_only_base_pool(healthy_deployments), excluded_set) + return _require_candidates(pool, model, request_tags) + + new_healthy_deployments: list[Any] = [] + default_deployments: list[Any] = [] - # Only activate header-based regex filtering when at least one deployment in - # the candidate set has tag_regex configured. This preserves existing - # behaviour for operators who use plain tags: a request that carries a - # User-Agent (all proxy requests do) but targets deployments with no - # tag_regex will continue to use the original tag-only code path. - has_regex_deployments = any(d.get("litellm_params", {}).get("tag_regex") for d in healthy_deployments) - has_tag_filter = bool(request_tags) or (bool(header_strings) and has_regex_deployments) if has_tag_filter: verbose_logger.debug( "get_deployments_for_tag routing: request_tags=%s user_agent=%s", request_tags, user_agent, ) - for deployment in healthy_deployments: + for deployment in candidates: deployment_tags = deployment.get("litellm_params", {}).get("tags") match_result = _match_deployment( deployment=deployment, - request_tags=request_tags, + request_tags=positive_tags, header_strings=header_strings, match_any=match_any, ) @@ -189,10 +225,6 @@ async def get_deployments_for_tag( match_result["matched_via"], match_result["matched_value"], ) - # Record provenance in metadata so it flows to SpendLogs. - # Written only for the first match — load balancer selects one - # deployment from new_healthy_deployments, so overwriting on - # subsequent matches would produce misleading observability data. if "tag_routing" not in metadata: metadata["tag_routing"] = { "matched_deployment": deployment.get("model_name"), @@ -208,7 +240,8 @@ async def get_deployments_for_tag( if len(new_healthy_deployments) == 0 and len(default_deployments) == 0: raise ValueError( - f"{RouterErrors.no_deployments_with_tag_routing.value}. Passed model={model} and tags={request_tags}" + f"{RouterErrors.no_deployments_with_tag_routing.value}." + f" Passed model={model} and tags={request_tags}" ) return new_healthy_deployments if len(new_healthy_deployments) > 0 else default_deployments @@ -231,9 +264,9 @@ async def get_deployments_for_tag( def _get_tags_from_request_kwargs( - request_kwargs: Optional[Dict[Any, Any]] = None, + request_kwargs: Optional[dict[Any, Any]] = None, metadata_variable_name: Literal["metadata", "litellm_metadata"] = "metadata", -) -> List[str]: +) -> list[str]: """ Helper to get tags from request kwargs diff --git a/tests/test_litellm/router_strategy/test_router_tag_routing.py b/tests/test_litellm/router_strategy/test_router_tag_routing.py index a6e39ec3c0a..eb289095c51 100644 --- a/tests/test_litellm/router_strategy/test_router_tag_routing.py +++ b/tests/test_litellm/router_strategy/test_router_tag_routing.py @@ -1,29 +1,17 @@ #### What this tests #### # This tests litellm router -import asyncio import os import sys -import time -import traceback -import openai import pytest -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system path +sys.path.insert(0, os.path.abspath("../..")) # Adds the parent directory to the system path import logging import os -from collections import defaultdict -from concurrent.futures import ThreadPoolExecutor -from unittest.mock import AsyncMock, MagicMock, patch -import httpx -from dotenv import load_dotenv import litellm -from litellm import Router from litellm._logging import verbose_logger @@ -66,10 +54,7 @@ async def test_router_free_paid_tier(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-cheap-model" @@ -82,10 +67,7 @@ async def test_router_free_paid_tier(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-expensive-model" @@ -141,10 +123,7 @@ async def test_router_free_paid_tier_embeddings(): mock_response=[1, 2, 3], ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-cheap-model" @@ -157,10 +136,7 @@ async def test_router_free_paid_tier_embeddings(): mock_response=[1, 2, 3], ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-expensive-model" @@ -212,10 +188,7 @@ async def test_default_tagged_deployments(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "default-model" @@ -228,10 +201,7 @@ async def test_default_tagged_deployments(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "default-model" @@ -244,10 +214,7 @@ async def test_default_tagged_deployments(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "default-model" @@ -257,10 +224,6 @@ async def test_error_from_tag_routing(): """ Tests the correct error raised when no deployments found for tag """ - import logging - - from litellm._logging import verbose_logger - verbose_logger.setLevel(logging.DEBUG) router = litellm.Router( model_list=[ @@ -294,7 +257,7 @@ async def test_error_from_tag_routing(): ) try: - response = await router.acompletion( + await router.acompletion( model="gpt-4", messages=[{"role": "user", "content": "Tell me a joke."}], metadata={"tags": ["paid"]}, @@ -306,7 +269,6 @@ async def test_error_from_tag_routing(): from litellm.types.router import RouterErrors assert RouterErrors.no_deployments_with_tag_routing.value in str(e) - print("got expected exception = ", e) pass @@ -332,16 +294,10 @@ def test_tag_routing_with_list_of_tags_match_all(): from litellm.router_strategy.tag_based_routing import is_valid_deployment_tag assert is_valid_deployment_tag(["teamA", "teamB"], ["teamA"], match_any=False) - assert is_valid_deployment_tag( - ["teamA", "teamB"], ["teamA", "teamB"], match_any=False - ) - assert not is_valid_deployment_tag( - ["teamA", "teamB", "teamC"], ["teamA", "teamD"], match_any=False - ) + assert is_valid_deployment_tag(["teamA", "teamB"], ["teamA", "teamB"], match_any=False) + assert not is_valid_deployment_tag(["teamA", "teamB", "teamC"], ["teamA", "teamD"], match_any=False) assert not is_valid_deployment_tag(["teamA"], ["teamA", "teamB"], match_any=False) - assert not is_valid_deployment_tag( - ["teamA", "teamB"], ["teamA", "teamC"], match_any=False - ) + assert not is_valid_deployment_tag(["teamA", "teamB"], ["teamA", "teamC"], match_any=False) assert not is_valid_deployment_tag(["teamA", "teamB"], [], match_any=False) assert not is_valid_deployment_tag(["default"], ["teamA"], match_any=False) @@ -413,10 +369,7 @@ async def test_router_free_paid_tier_with_responses_api(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-cheap-model" @@ -429,10 +382,7 @@ async def test_router_free_paid_tier_with_responses_api(): mock_response="Tell me a joke.", ) - print("Response: ", response) - response_extra_info = response._hidden_params - print("response_extra_info: ", response_extra_info) assert response_extra_info["model_id"] == "very-expensive-model" @@ -455,9 +405,7 @@ def test_get_tags_from_request_kwargs_various_inputs(): assert _get_tags_from_request_kwargs({"metadata": None}) == [] # Indirect via "litellm_params" - metadata inside - assert _get_tags_from_request_kwargs( - {"litellm_params": {"metadata": {"tags": ["paid"]}}} - ) == ["paid"] + assert _get_tags_from_request_kwargs({"litellm_params": {"metadata": {"tags": ["paid"]}}}) == ["paid"] assert _get_tags_from_request_kwargs({"litellm_params": {"metadata": None}}) == [] assert _get_tags_from_request_kwargs({"litellm_params": {}}) == [] @@ -473,3 +421,601 @@ def test_get_tags_from_request_kwargs_various_inputs(): # No relevant keys present assert _get_tags_from_request_kwargs({"foo": "bar"}) == [] + + +# --- _split_tags unit tests --- + + +def test_split_tags_positive_only(): + from litellm.router_strategy.tag_based_routing import _split_tags + + positive, excluded = _split_tags(["paid", "teamA"]) + assert positive == ["paid", "teamA"] + assert excluded == [] + + +def test_split_tags_negation_only(): + from litellm.router_strategy.tag_based_routing import _split_tags + + positive, excluded = _split_tags(["!provider:anthropic"]) + assert positive == [] + assert excluded == ["provider:anthropic"] + + +def test_split_tags_mixed(): + from litellm.router_strategy.tag_based_routing import _split_tags + + positive, excluded = _split_tags(["paid", "!provider:anthropic", "!inference:cerebras"]) + assert positive == ["paid"] + assert len(excluded) == 2 + + +def test_split_tags_bare_bang_skipped(): + from litellm.router_strategy.tag_based_routing import _split_tags + + # A bare "!" with nothing after it is not a valid negation tag; skip it + positive, excluded = _split_tags(["paid", "!"]) + assert positive == ["paid"] + assert excluded == [] + + +def test_split_tags_empty(): + from litellm.router_strategy.tag_based_routing import _split_tags + + positive, excluded = _split_tags([]) + assert positive == [] + assert excluded == [] + + +# --- get_deployments_for_tag negation integration tests --- + + +@pytest.mark.asyncio() +async def test_negation_excludes_matching_deployments(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic", "model:claude-sonnet-4-6"], + }, + "model_info": {"id": "anthropic-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai", "model:gpt-4o"], + }, + "model_info": {"id": "openai-model"}, + }, + ], + enable_tag_filtering=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "openai-model" + + +@pytest.mark.asyncio() +async def test_negation_multiple_tags_exclude_multiple_providers(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai"], + }, + "model_info": {"id": "openai-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:vertex"], + }, + "model_info": {"id": "vertex-model"}, + }, + ], + enable_tag_filtering=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic", "!provider:openai"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "vertex-model" + + +@pytest.mark.asyncio() +async def test_negation_with_positive_tag(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["paid", "provider:anthropic"], + }, + "model_info": {"id": "anthropic-paid"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["paid", "provider:openai"], + }, + "model_info": {"id": "openai-paid"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["free", "provider:openai"], + }, + "model_info": {"id": "openai-free"}, + }, + ], + enable_tag_filtering=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["paid", "!provider:anthropic"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "openai-paid" + + +@pytest.mark.asyncio() +async def test_negation_all_excluded_raises(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-model"}, + }, + ], + enable_tag_filtering=True, + ) + + with pytest.raises(Exception) as exc_info: + await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + + from litellm.types.router import RouterErrors + + assert RouterErrors.no_deployments_with_tag_routing.value in str(exc_info.value) + + +@pytest.mark.asyncio() +async def test_negation_ban_only_cannot_escape_default_pool(): + # A ban-only request must not route to tagged deployments outside the default pool. + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["default"], + }, + "model_info": {"id": "default-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["paid"], + }, + "model_info": {"id": "paid-model"}, + }, + ], + enable_tag_filtering=True, + ) + + # Sending only "!default" must NOT route to the paid deployment. + # The base pool for ban-only is the default pool; banning the only + # default deployment should raise rather than falling through to paid. + with pytest.raises(Exception) as exc_info: + await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!default"]}, + mock_response="hi", + ) + + from litellm.types.router import RouterErrors + + assert RouterErrors.no_deployments_with_tag_routing.value in str(exc_info.value) + + +@pytest.mark.asyncio() +async def test_negation_ban_only_respects_default_pool(): + # A ban-only request stays within the default pool; non-default deployments + # remain unreachable even when the negation tag is unrelated to the default. + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["default"], + }, + "model_info": {"id": "default-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["paid"], + }, + "model_info": {"id": "paid-model"}, + }, + ], + enable_tag_filtering=True, + ) + + # "!paid" bans the paid deployment, but the base pool for ban-only is + # already restricted to defaults; default-model must still be returned. + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!paid"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "default-model" + + +@pytest.mark.asyncio() +async def test_negation_untagged_deployment_kept(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + }, + "model_info": {"id": "untagged-model"}, + }, + ], + enable_tag_filtering=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "untagged-model" + + +@pytest.mark.asyncio() +async def test_negation_literal_only_no_partial_match(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic-haiku"], + }, + "model_info": {"id": "anthropic-haiku-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai"], + }, + "model_info": {"id": "openai-model"}, + }, + ], + enable_tag_filtering=True, + ) + + # "!provider:anthropic" should NOT match "provider:anthropic-haiku" — exact tag match only + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] in ( + "anthropic-haiku-model", + "openai-model", + ) + + +@pytest.mark.asyncio() +async def test_negation_regex_pattern_treated_as_literal(): + # "!provider:(anthropic|openai)" looks like a regex but is treated as a literal string. + # It does NOT exclude deployments tagged "provider:anthropic" or "provider:openai". + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai"], + }, + "model_info": {"id": "openai-model"}, + }, + ], + enable_tag_filtering=True, + ) + + # The regex-like string matches no deployment tag literally, so all + # candidates survive and both model IDs are reachable. + seen_ids = set() + for _ in range(10): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:(anthropic|openai)"]}, + mock_response="hi", + ) + seen_ids.add(response._hidden_params["model_id"]) + + assert seen_ids == {"anthropic-model", "openai-model"} + + +@pytest.mark.asyncio() +async def test_positive_tags_unchanged_by_negation(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["free"], + }, + "model_info": {"id": "free-model"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["paid"], + }, + "model_info": {"id": "paid-model"}, + }, + ], + enable_tag_filtering=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["free"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "free-model" + + +@pytest.mark.asyncio() +async def test_negation_skips_banned_group_and_uses_fallback(): + router = litellm.Router( + model_list=[ + { + "model_name": "primary", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-primary"}, + }, + { + "model_name": "fallback", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai"], + }, + "model_info": {"id": "openai-fallback"}, + }, + ], + fallbacks=[{"primary": ["fallback"]}], + enable_tag_filtering=True, + ) + + response = await router.acompletion( + model="primary", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "openai-fallback" + + +@pytest.mark.asyncio() +async def test_negation_exhausts_entire_fallback_chain(): + router = litellm.Router( + model_list=[ + { + "model_name": "primary", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-primary"}, + }, + { + "model_name": "fallback", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-fallback"}, + }, + ], + fallbacks=[{"primary": ["fallback"]}], + enable_tag_filtering=True, + ) + + with pytest.raises(Exception) as exc_info: + await router.acompletion( + model="primary", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"]}, + mock_response="hi", + ) + + from litellm.types.router import RouterErrors + + assert RouterErrors.no_deployments_with_tag_routing.value in str(exc_info.value) + + +@pytest.mark.asyncio() +async def test_tag_regex_survives_when_negation_removes_other_deployment(): + # Negation removes a plain-tagged deployment; the surviving tag_regex deployment + # is still matched by User-Agent and selected. + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tag_regex": ["^User-Agent: claude-code\\/"], + }, + "model_info": {"id": "claude-code-deployment"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:anthropic"], + }, + "model_info": {"id": "anthropic-deployment"}, + }, + ], + enable_tag_filtering=True, + tag_filtering_match_any=True, + ) + + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!provider:anthropic"], "user_agent": "claude-code/1.2.3"}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "claude-code-deployment" + + +@pytest.mark.asyncio() +async def test_negation_removes_tag_regex_deployment_falls_to_ban_only(): + # When a negation tag removes the only tag_regex deployment, no regex deployments + # remain in the candidate pool. has_tag_filter becomes False, ban_only fires, + # and the remaining plain-tagged deployment is returned via the ban-only path. + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tag_regex": ["^User-Agent: claude-code\\/"], + "tags": ["group:claude"], + }, + "model_info": {"id": "claude-code-deployment"}, + }, + { + "model_name": "gpt-4", + "litellm_params": { + "model": "gpt-4o-mini", + "api_base": "https://exampleopenaiendpoint-production.up.railway.app/", + "tags": ["provider:openai"], + }, + "model_info": {"id": "openai-deployment"}, + }, + ], + enable_tag_filtering=True, + tag_filtering_match_any=True, + ) + + # !group:claude removes the tag_regex deployment from candidates, so no regex + # deployments remain. The ban-only path fires and returns the openai deployment. + for _ in range(5): + response = await router.acompletion( + model="gpt-4", + messages=[{"role": "user", "content": "hi"}], + metadata={"tags": ["!group:claude"], "user_agent": "claude-code/1.2.3"}, + mock_response="hi", + ) + assert response._hidden_params["model_id"] == "openai-deployment" From 9968499aabf6d6b4e36579c05979fc1deda44098 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 11:28:51 -0700 Subject: [PATCH 19/79] fix(ui): fix Router Settings Loadbalancing tab save (LIT-4057) The Loadbalancing tab rendered routing_groups as a generic text input and sent its array value back as the JSON string "[]", which fails Pydantic list validation on POST /config/update and returns 422. routing_groups has its own dedicated Routing Groups tab, so this tab must neither render nor write it; exclude it the same way retry_policy and model_group_retry_policy are excluded for the Model Retry Settings tab. The save was also fire-and-forget: setCallbacksCall was not awaited, so the rejected promise escaped the try/catch and the success toast fired unconditionally, showing success even when the backend rejected the change. Await the call, gate the success toast on resolution, and surface the error. --- .../ReliabilityRetriesSection.tsx | 5 ++- .../components/router_settings/index.test.tsx | 40 +++++++++++++++++++ .../src/components/router_settings/index.tsx | 13 +++--- 3 files changed, 49 insertions(+), 9 deletions(-) diff --git a/ui/litellm-dashboard/src/components/router_settings/ReliabilityRetriesSection.tsx b/ui/litellm-dashboard/src/components/router_settings/ReliabilityRetriesSection.tsx index fa48c1c97b9..da089552b11 100644 --- a/ui/litellm-dashboard/src/components/router_settings/ReliabilityRetriesSection.tsx +++ b/ui/litellm-dashboard/src/components/router_settings/ReliabilityRetriesSection.tsx @@ -20,14 +20,15 @@ const ReliabilityRetriesSection: React.FC = ({
{Object.entries(routerSettings) .filter( - ([param, value]) => + ([param]) => param != "fallbacks" && param != "context_window_fallbacks" && param != "routing_strategy_args" && param != "routing_strategy" && param != "enable_tag_filtering" && param != "retry_policy" && - param != "model_group_retry_policy", + param != "model_group_retry_policy" && + param != "routing_groups", ) .map(([param, value]) => (
diff --git a/ui/litellm-dashboard/src/components/router_settings/index.test.tsx b/ui/litellm-dashboard/src/components/router_settings/index.test.tsx index 78a0b4b0dff..0df1cd81d6b 100644 --- a/ui/litellm-dashboard/src/components/router_settings/index.test.tsx +++ b/ui/litellm-dashboard/src/components/router_settings/index.test.tsx @@ -146,4 +146,44 @@ describe("RouterSettings", () => { expect(NotificationsManager.success).toHaveBeenCalledWith("router settings updated successfully"); }); + + it("should not render or save routing_groups (owned by the Routing Groups tab) (LIT-4057)", async () => { + const user = userEvent.setup(); + vi.mocked(getCallbacksCall).mockResolvedValue({ + router_settings: { + routing_strategy: "simple-shuffle", + num_retries: 3, + routing_groups: [{ group_name: "g1", models: ["gpt-4"], routing_strategy: "simple-shuffle" }], + }, + }); + renderWithProviders(); + + await waitFor(() => { + expect(screen.getByTestId("strategy-select")).toBeInTheDocument(); + }); + expect(document.querySelector('input[name="routing_groups"]')).toBeNull(); + + await user.click(screen.getByRole("button", { name: /save changes/i })); + + const payload = vi.mocked(setCallbacksCall).mock.calls[0][1] as { + router_settings: Record; + }; + expect(payload.router_settings).not.toHaveProperty("routing_groups"); + }); + + it("should surface an error and not claim success when saving fails (LIT-4057)", async () => { + const user = userEvent.setup(); + vi.mocked(setCallbacksCall).mockRejectedValue(new Error("422 Unprocessable Entity")); + renderWithProviders(); + + await waitFor(() => { + expect(screen.getByTestId("strategy-select")).toBeInTheDocument(); + }); + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => { + expect(NotificationsManager.fromBackend).toHaveBeenCalled(); + }); + expect(NotificationsManager.success).not.toHaveBeenCalled(); + }); }); diff --git a/ui/litellm-dashboard/src/components/router_settings/index.tsx b/ui/litellm-dashboard/src/components/router_settings/index.tsx index d3753529058..360c7f41138 100644 --- a/ui/litellm-dashboard/src/components/router_settings/index.tsx +++ b/ui/litellm-dashboard/src/components/router_settings/index.tsx @@ -81,7 +81,7 @@ const RouterSettings: React.FC = ({ accessToken, userRole, }); }, [accessToken, userRole, userID]); - const handleSaveChanges = () => { + const handleSaveChanges = async () => { if (!accessToken) { return; } @@ -91,9 +91,9 @@ const RouterSettings: React.FC = ({ accessToken, userRole, const numberKeys = new Set(["allowed_fails", "cooldown_time", "num_retries", "timeout", "retry_after"]); const jsonKeys = new Set(["model_group_alias"]); - // retry_policy and model_group_retry_policy are owned exclusively by the - // Model Retry Settings tab; this page must not read or write them. - const tabOwnedKeys = new Set(["retry_policy", "model_group_retry_policy"]); + // retry_policy and model_group_retry_policy are owned by the Model Retry Settings tab; + // routing_groups is owned by the Routing Groups tab. This page must not read or write them. + const tabOwnedKeys = new Set(["retry_policy", "model_group_retry_policy", "routing_groups"]); const parseInputValue = (key: string, raw: string | undefined, fallback: unknown) => { if (raw === undefined) return fallback; @@ -172,12 +172,11 @@ const RouterSettings: React.FC = ({ accessToken, userRole, }; try { - setCallbacksCall(accessToken, payload); + await setCallbacksCall(accessToken, payload); + NotificationsManager.success("router settings updated successfully"); } catch (error) { NotificationsManager.fromBackend("Failed to update router settings: " + error); } - - NotificationsManager.success("router settings updated successfully"); }; if (!accessToken) { From 30141f86f824cdc53e425a4b27fe07e34cc61c64 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 11:40:09 -0700 Subject: [PATCH 20/79] test(ui): make router settings save tests resilient to async timing Address Greptile P2: the routing_groups test read setCallbacksCall.mock.calls[0][1] immediately after the now-async save handler, so any latency in the mock would throw an opaque TypeError instead of a clean assertion failure. Assert through toHaveBeenCalledWith inside waitFor with expect.not.objectContaining, dropping the index access and the cast. Also drop the ticket id from the test names. --- .../src/components/router_settings/index.test.tsx | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/ui/litellm-dashboard/src/components/router_settings/index.test.tsx b/ui/litellm-dashboard/src/components/router_settings/index.test.tsx index 0df1cd81d6b..94cbb94d164 100644 --- a/ui/litellm-dashboard/src/components/router_settings/index.test.tsx +++ b/ui/litellm-dashboard/src/components/router_settings/index.test.tsx @@ -147,7 +147,7 @@ describe("RouterSettings", () => { expect(NotificationsManager.success).toHaveBeenCalledWith("router settings updated successfully"); }); - it("should not render or save routing_groups (owned by the Routing Groups tab) (LIT-4057)", async () => { + it("should not render or save routing_groups (owned by the Routing Groups tab)", async () => { const user = userEvent.setup(); vi.mocked(getCallbacksCall).mockResolvedValue({ router_settings: { @@ -165,13 +165,14 @@ describe("RouterSettings", () => { await user.click(screen.getByRole("button", { name: /save changes/i })); - const payload = vi.mocked(setCallbacksCall).mock.calls[0][1] as { - router_settings: Record; - }; - expect(payload.router_settings).not.toHaveProperty("routing_groups"); + await waitFor(() => + expect(setCallbacksCall).toHaveBeenCalledWith("test-token", { + router_settings: expect.not.objectContaining({ routing_groups: expect.anything() }), + }), + ); }); - it("should surface an error and not claim success when saving fails (LIT-4057)", async () => { + it("should surface an error and not claim success when saving fails", async () => { const user = userEvent.setup(); vi.mocked(setCallbacksCall).mockRejectedValue(new Error("422 Unprocessable Entity")); renderWithProviders(); From a126cdf5b79362aea1c76fec2c1c654ad5175fcb Mon Sep 17 00:00:00 2001 From: Cursor Agent Date: Tue, 30 Jun 2026 18:47:08 +0000 Subject: [PATCH 21/79] feat(anthropic): add Claude Sonnet 5 Register claude-sonnet-5 across the Anthropic, Bedrock (base + global/us/eu/au/jp cross-region inference profiles), Vertex AI, and Azure AI cost-map entries in both the root and bundled-backup model maps, plus BEDROCK_CONVERSE_MODELS and the setup-wizard provider list. Sonnet 5 ships with the gen-5 adaptive-thinking profile (adaptive thinking always on, no extended thinking, effort defaults to high), so the entries mirror the Fable 5 / Opus 4.8 sampling-param and prefill restrictions rather than the older Sonnet 4.6 behavior: supports_sampling_params and supports_assistant_prefill are false while supports_adaptive_thinking, supports_xhigh_reasoning_effort, and supports_max_reasoning_effort are true. Pricing follows standard Sonnet rates ($3 / $15 per MTok) with the 10% regional premium on the us/eu/au/jp profiles. Add a reasoning-effort grid entry for the Anthropic direct route and a regression test pinning pricing, capabilities, regional premiums, backup parity, and bare-name provider resolution. Co-authored-by: Mateo Wang --- litellm/constants.py | 1 + ...odel_prices_and_context_window_backup.json | 325 ++++++++++++++++++ litellm/setup_wizard.py | 1 + model_prices_and_context_window.json | 325 ++++++++++++++++++ .../reasoning_effort_grid/grid_spec.py | 7 + .../test_claude_sonnet_5_config.py | 174 ++++++++++ 6 files changed, 833 insertions(+) create mode 100644 tests/test_litellm/test_claude_sonnet_5_config.py diff --git a/litellm/constants.py b/litellm/constants.py index aeb74a65839..5cc41bd7954 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -1123,6 +1123,7 @@ BEDROCK_CONVERSE_MODELS = [ "anthropic.claude-haiku-4-5-20251001-v1:0", "anthropic.claude-sonnet-4-5-20250929-v1:0", "anthropic.claude-fable-5", + "anthropic.claude-sonnet-5", "anthropic.claude-opus-4-8", "anthropic.claude-opus-4-7", "anthropic.claude-opus-4-6-v1:0", diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 21132db93cb..5bd70690d48 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1671,6 +1671,204 @@ "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, + "anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "global.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "us.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "eu.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "au.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "jp.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, "anthropic.claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -2511,6 +2709,37 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure_ai/claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "azure_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -10245,6 +10474,40 @@ "supports_vision": true, "supports_web_search": true }, + "claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "anthropic", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "provider_specific_entry": { + "us": 1.1 + }, + "supports_output_config": true + }, "claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, @@ -34944,6 +35207,37 @@ "supports_tool_choice": true, "supports_vision": true }, + "vertex_ai/claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "vertex_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -42381,6 +42675,37 @@ "search_context_size_high": 0.035 } }, + "vertex_ai/claude-sonnet-5@default": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "vertex_ai/claude-sonnet-4-6@default": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, diff --git a/litellm/setup_wizard.py b/litellm/setup_wizard.py index b43590079fa..10b4fb30f22 100644 --- a/litellm/setup_wizard.py +++ b/litellm/setup_wizard.py @@ -58,6 +58,7 @@ PROVIDERS: List[Dict] = [ "test_model": "claude-haiku-4-5-20251001", "models": [ "claude-fable-5", + "claude-sonnet-5", "claude-opus-4-8", "claude-opus-4-7", "claude-opus-4-6", diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 73cefeb7c77..5fc431d721b 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1671,6 +1671,204 @@ "supports_max_reasoning_effort": true, "supports_minimal_reasoning_effort": true }, + "anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "global.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "us.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "eu.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "au.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, + "jp.anthropic.claude-sonnet-5": { + "cache_creation_input_token_cost": 4.125e-06, + "cache_creation_input_token_cost_above_1hr": 6.6e-06, + "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 3.3e-06, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.65e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_native_structured_output": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true, + "bedrock_output_config_effort_ceiling": "xhigh" + }, "anthropic.claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -2511,6 +2709,37 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure_ai/claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "azure_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -10245,6 +10474,40 @@ "supports_vision": true, "supports_web_search": true }, + "claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "anthropic", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "provider_specific_entry": { + "us": 1.1 + }, + "supports_output_config": true + }, "claude-sonnet-4-6": { "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, @@ -35121,6 +35384,37 @@ "supports_tool_choice": true, "supports_vision": true }, + "vertex_ai/claude-sonnet-5": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "vertex_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -42616,6 +42910,37 @@ "search_context_size_high": 0.035 } }, + "vertex_ai/claude-sonnet-5@default": { + "cache_creation_input_token_cost": 3.75e-06, + "cache_creation_input_token_cost_above_1hr": 6e-06, + "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 3e-06, + "litellm_provider": "vertex_ai-anthropic_models", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 1.5e-05, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, + "supports_adaptive_thinking": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": true, + "supports_output_config": true + }, "vertex_ai/claude-sonnet-4-6@default": { "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 3.75e-06, diff --git a/tests/llm_translation/reasoning_effort_grid/grid_spec.py b/tests/llm_translation/reasoning_effort_grid/grid_spec.py index 1bb468d15ad..762606bb3a0 100644 --- a/tests/llm_translation/reasoning_effort_grid/grid_spec.py +++ b/tests/llm_translation/reasoning_effort_grid/grid_spec.py @@ -181,6 +181,13 @@ ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = ( required_env=_ANTHROPIC_REQ, caps=_CAPS_XHIGH_MAX, ), + ModelEntry( + alias="claude-sonnet-5", + model="anthropic/claude-sonnet-5", + mode="adaptive", + required_env=_ANTHROPIC_REQ, + caps=_CAPS_XHIGH_MAX, + ), ModelEntry( alias="claude-sonnet-4-6", model="anthropic/claude-sonnet-4-6", diff --git a/tests/test_litellm/test_claude_sonnet_5_config.py b/tests/test_litellm/test_claude_sonnet_5_config.py new file mode 100644 index 00000000000..88a06aea95f --- /dev/null +++ b/tests/test_litellm/test_claude_sonnet_5_config.py @@ -0,0 +1,174 @@ +""" +Validate Claude Sonnet 5 model configuration entries. + +Sonnet 5 ships with the gen-5 adaptive-thinking profile (adaptive thinking +always on, no extended thinking, ``effort`` defaults to ``high``), so it must +mirror the sampling-param and prefill restrictions that Fable 5 / Opus 4.8 carry +rather than the older Sonnet 4.6 behavior. The cost-map entries are also what +populate ``litellm.anthropic_models`` at import, which is what lets a bare +``claude-sonnet-5`` name resolve to the ``anthropic`` provider (and match an +``anthropic/*`` wildcard deployment). +""" + +import json +import os + +import pytest + +import litellm +from litellm.constants import BEDROCK_CONVERSE_MODELS +from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap + +REPO_ROOT = os.path.join(os.path.dirname(__file__), "../..") + +ALL_SONNET_5_VARIANTS = ( + "claude-sonnet-5", + "anthropic.claude-sonnet-5", + "global.anthropic.claude-sonnet-5", + "us.anthropic.claude-sonnet-5", + "eu.anthropic.claude-sonnet-5", + "au.anthropic.claude-sonnet-5", + "jp.anthropic.claude-sonnet-5", + "vertex_ai/claude-sonnet-5", + "vertex_ai/claude-sonnet-5@default", + "azure_ai/claude-sonnet-5", +) + + +def _load_root_cost_map() -> dict: + json_path = os.path.join(REPO_ROOT, "model_prices_and_context_window.json") + with open(json_path) as f: + return json.load(f) + + +@pytest.fixture +def local_model_cost_map(monkeypatch): + """Force the bundled backup cost map so assertions don't depend on the + network-fetched ``main`` copy (which lags this branch until merge).""" + original_model_cost = litellm.model_cost + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + litellm.model_cost = litellm.get_model_cost_map(url="") + litellm.get_model_info.cache_clear() + try: + yield + finally: + litellm.model_cost = original_model_cost + litellm.get_model_info.cache_clear() + + +def test_sonnet_5_pricing_and_capabilities(): + model_data = _load_root_cost_map() + + expected_providers = { + "claude-sonnet-5": "anthropic", + "anthropic.claude-sonnet-5": "bedrock_converse", + "vertex_ai/claude-sonnet-5": "vertex_ai-anthropic_models", + "azure_ai/claude-sonnet-5": "azure_ai", + } + + for model_name, provider in expected_providers.items(): + assert model_name in model_data, f"Missing model entry: {model_name}" + info = model_data[model_name] + + assert info["litellm_provider"] == provider + assert info["mode"] == "chat" + assert info["max_input_tokens"] == 1000000 + assert info["max_output_tokens"] == 128000 + assert info["max_tokens"] == 128000 + + # Standard Sonnet pricing: $3 / $15 per MTok, with the 1.25x cache-write + # and 0.1x cache-read multipliers. + assert info["input_cost_per_token"] == 3e-06 + assert info["output_cost_per_token"] == 1.5e-05 + assert info["cache_creation_input_token_cost"] == 3.75e-06 + assert info["cache_read_input_token_cost"] == 3e-07 + + # gen-5 adaptive-thinking profile: effort-driven, no sampling params, no + # assistant prefill. + assert info["supports_adaptive_thinking"] is True + assert info["supports_reasoning"] is True + assert info["supports_sampling_params"] is False + assert info["supports_assistant_prefill"] is False + + assert info["supports_function_calling"] is True + assert info["supports_prompt_caching"] is True + assert info["supports_tool_choice"] is True + assert info["supports_vision"] is True + + +def test_sonnet_5_bedrock_regional_pricing(): + """Global/base endpoints use base pricing; the us./eu./au./jp. regional + cross-region inference profiles carry a 10% premium.""" + model_data = _load_root_cost_map() + + base_pricing = { + "input_cost_per_token": 3e-06, + "output_cost_per_token": 1.5e-05, + "cache_creation_input_token_cost": 3.75e-06, + "cache_read_input_token_cost": 3e-07, + } + regional_pricing = { + "input_cost_per_token": 3.3e-06, + "output_cost_per_token": 1.65e-05, + "cache_creation_input_token_cost": 4.125e-06, + "cache_read_input_token_cost": 3.3e-07, + } + + expected = { + "anthropic.claude-sonnet-5": base_pricing, + "global.anthropic.claude-sonnet-5": base_pricing, + "us.anthropic.claude-sonnet-5": regional_pricing, + "eu.anthropic.claude-sonnet-5": regional_pricing, + "au.anthropic.claude-sonnet-5": regional_pricing, + "jp.anthropic.claude-sonnet-5": regional_pricing, + } + + for model_name, pricing in expected.items(): + assert model_name in model_data, f"Missing model entry: {model_name}" + info = model_data[model_name] + assert info["litellm_provider"] == "bedrock_converse" + assert info["bedrock_output_config_effort_ceiling"] == "xhigh" + for key, value in pricing.items(): + assert info[key] == value, f"{model_name}.{key} = {info[key]}, want {value}" + + +def test_sonnet_5_present_in_bundled_backup(): + """The bundled backup is the runtime fallback (and what tests load with + ``LITELLM_LOCAL_MODEL_COST_MAP=True``); it must carry the same entries as the + root cost map, otherwise the model resolves on one path but not the other.""" + backup = GetModelCostMap.load_local_model_cost_map() + for model_name in ALL_SONNET_5_VARIANTS: + assert model_name in backup, f"Missing from backup cost map: {model_name}" + + +def test_sonnet_5_registered_for_bedrock_converse(): + assert "anthropic.claude-sonnet-5" in BEDROCK_CONVERSE_MODELS + + +def test_sonnet_5_provider_resolves_via_model_info(local_model_cost_map): + """Regression: ``claude-sonnet-5`` must resolve to provider ``anthropic``. + + Before the cost-map entry existed, the model was unknown to LiteLLM, so it + could not be tied to the ``anthropic`` provider and an ``anthropic/*`` + wildcard deployment would not match it.""" + info = litellm.get_model_info(model="claude-sonnet-5") + assert info["litellm_provider"] == "anthropic" + assert info["max_input_tokens"] == 1000000 + assert info["max_output_tokens"] == 128000 + + +@pytest.mark.parametrize( + "cost_map", + [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()], + ids=["root", "bundled_backup"], +) +def test_sonnet_5_all_variants_carry_adaptive_thinking_flag(cost_map): + """Every Sonnet 5 entry must advertise ``supports_adaptive_thinking``. + + Adaptive-thinking detection is cost-map driven, so a single variant missing + the flag silently sends the legacy ``thinking.type='enabled'`` shape and the + provider 400s. This guards against a future variant being added without it.""" + variants = [k for k in cost_map if "claude-sonnet-5" in k] + assert variants, "no claude-sonnet-5 entries found in cost map" + missing = [k for k in variants if cost_map[k].get("supports_adaptive_thinking") is not True] + assert not missing, f"missing supports_adaptive_thinking: {missing}" From 540c860a9737838e5fa2146aa8d4cd2fab445548 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 11:47:35 -0700 Subject: [PATCH 22/79] test(ui): add typed e2e for Router Settings Loadbalancing save (LIT-4057) Drives the real save flow against a live proxy: seeds a present routing_groups array (the LIT-4057 trigger) via the typed /config/update contract, changes num_retries on the Loadbalancing tab, and asserts the POST returns 200 instead of 422, the success toast appears, and the value still shows after a reload (the ticket's "refresh shows old values" symptom). The round-trip is typed against the OpenAPI-generated backend schema (ConfigYAML write, RouterSettingsResponse read) through a type-only import, so a backend contract drift fails the type check. --- .../tests/settings/routerSettings.spec.ts | 84 +++++++++++++++++++ 1 file changed, 84 insertions(+) diff --git a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts index 98b86ec9b11..e560500fca6 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts @@ -3,6 +3,10 @@ import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; import { Role, users } from "../../fixtures/users"; +// Type-only import of the OpenAPI-generated backend schema; esbuild erases it at +// runtime, so the round-trip below is checked against the real /config/update and +// /router/settings contracts without bundling the 2 MB definition file. +import type { components } from "../../../src/lib/http/schema"; const PRIMARY = "fake-openai-gpt-4"; const FALLBACK = "fake-anthropic-claude"; @@ -99,3 +103,83 @@ test.describe("Router Settings - Fallbacks", () => { await expect(newRow).toHaveCount(1, { timeout: 10_000 }); }); }); + +type ConfigYAML = components["schemas"]["ConfigYAML"]; +type RouterSettingsResponse = components["schemas"]["RouterSettingsResponse"]; + +const BASE_URL = "http://localhost:4000"; +const ADMIN_AUTH = { Authorization: `Bearer ${users[Role.ProxyAdmin].password}` }; + +/** + * Merge a router_settings patch into the live config through the typed + * /config/update contract, preserving any other settings already present. + */ +async function patchRouterSettings( + request: import("@playwright/test").APIRequestContext, + patch: Partial>, +) { + const current = await request.get(`${BASE_URL}/get/config/callbacks`, { headers: ADMIN_AUTH }); + const existing = current.ok() ? (await current.json())?.router_settings ?? {} : {}; + const payload = { router_settings: { ...(existing as Record), ...patch } }; + await request.post(`${BASE_URL}/config/update`, { headers: ADMIN_AUTH, data: payload }); +} + +test.describe("Router Settings - Loadbalancing", () => { + test.use({ storageState: ADMIN_STORAGE_PATH }); + + // Seed a present routing_groups array (the LIT-4057 trigger) plus a known + // num_retries so the UI assertions are deterministic across reruns. + const ROUTING_GROUP = { group_name: "e2e-lit-4057", models: [PRIMARY], routing_strategy: "simple-shuffle" }; + + test.beforeEach(async ({ request }) => { + await patchRouterSettings(request, { num_retries: 3, routing_groups: [ROUTING_GROUP] }); + }); + + test.afterEach(async ({ request }) => { + await patchRouterSettings(request, { num_retries: 3, routing_groups: [] }); + }); + + test("saves the Loadbalancing tab without a 422 when routing_groups is present, and persists", async ({ + page, + request, + }) => { + await navigateToPage(page, Page.RouterSettings); + await page.getByRole("tab", { name: "Loadbalancing" }).click(); + + const numRetries = page.locator('input[name="num_retries"]'); + await expect(numRetries).toHaveValue("3", { timeout: 15_000 }); + // routing_groups belongs to its own tab and must not leak into this form. + await expect(page.locator('input[name="routing_groups"]')).toHaveCount(0); + + await numRetries.fill("5"); + + // LIT-4057: the tab used to serialize routing_groups as the string "[]", + // which the backend rejects with 422 while the UI still claimed success. + // Assert the save actually succeeds at the network level. + const saveResponse = page.waitForResponse( + (res) => res.url().includes("/config/update") && res.request().method() === "POST", + { timeout: 15_000 }, + ); + await page.getByRole("button", { name: /save changes/i }).click(); + expect((await saveResponse).status()).toBe(200); + + await expect(page.getByText(/router settings updated successfully/i).first()).toBeVisible({ timeout: 10_000 }); + + // The ticket's core symptom was that a refresh showed the old value. + await navigateToPage(page, Page.RouterSettings); + await page.getByRole("tab", { name: "Loadbalancing" }).click(); + await expect(page.locator('input[name="num_retries"]')).toHaveValue("5", { timeout: 15_000 }); + + // The typed backend read agrees the change persisted. + await expect + .poll( + async () => { + const res = await request.get(`${BASE_URL}/router/settings`, { headers: ADMIN_AUTH }); + const data = (await res.json()) as RouterSettingsResponse; + return data.current_values?.num_retries; + }, + { timeout: 10_000 }, + ) + .toBe(5); + }); +}); From 87de0e80a83628885aa68775e1cf07e8a140c1d7 Mon Sep 17 00:00:00 2001 From: tin-berri Date: Tue, 30 Jun 2026 11:58:47 -0700 Subject: [PATCH 23/79] fix(mcp): stop one unauthenticated server from emptying the aggregate tools/list (#31684) * fix(mcp): stop one unauthenticated server from emptying the aggregate tools/list On the aggregate MCP route (/mcp), the gateway fans out to every server the caller can access and flattens their tools. _fetch_and_filter_server_tools re-raises MCPUpstreamAuthError unconditionally (added with the OAuth passthrough feature in #28356) so it surfaces a 401 on single-server routes, but on the aggregate route that exception propagates through the asyncio.gather fan-out and the outer handler turns it into an empty list. The result: a single delegate/passthrough OAuth server the user has not authenticated (e.g. a delegate-auth server) zeroes the tools of every other server, including the ones that resolve fine, so the client connects and sees no tools. Surface the upstream auth error only when a single server was explicitly targeted (so that route still drives the upstream OAuth flow); across the aggregate, absorb it to [] for that one server so the rest still list their tools. This restores the graceful per-server degradation that predated #28356. Adds regression tests: the aggregate keeps a healthy server's tools when a sibling raises MCPUpstreamAuthError, and a single-server listing still surfaces it. * fix(mcp): decide aggregate vs single-server listing by route scope, not server count Addresses review: keying the surface-vs-absorb decision off the server count (len(allowed_mcp_servers), and even len(mcp_servers)) misclassifies an aggregate /mcp request from a key that can access exactly one server as a targeted single-server listing, so that one server's MCPUpstreamAuthError re-raises and empties the aggregate again for one-server permission sets. Use the path-derived single-server scope instead: _mcp_gateway_server_name, set by _gateway_initialize_instructions_request_scope only when the request path names exactly one upstream server (//mcp) and never from client headers, is None on the aggregate route (/mcp) regardless of how many servers the key can access. Single-server routes still surface the upstream-auth challenge; the aggregate absorbs it per server. Adds a regression test that an aggregate request with a single accessible server still absorbs, plus renames the single-server test to drive the route scope explicitly. The new test fails on the count-based logic. * fixing aggregation error * style(mcp): collapse single-line debug log to satisfy ruff format --- .../proxy/_experimental/mcp_server/server.py | 13 +- .../test_mcp_oauth_passthrough_tools.py | 128 ++++++++++++++++++ 2 files changed, 135 insertions(+), 6 deletions(-) diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index 158fdda6c39..607e676524e 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -1699,12 +1699,13 @@ if MCP_AVAILABLE: ) return filtered_tools except MCPUpstreamAuthError: - # Surface upstream 401/403 to the outer handler so the - # client receives a proper WWW-Authenticate challenge - # instead of a silently empty tool list. Without this - # re-raise the broad ``except Exception`` below would - # swallow the auth error. - raise + # Absorb so one unauthenticated server does not empty every other server's + # tools. Surfacing the upstream 401 to the client as a re-auth challenge is + # intentionally not done here: raising from this list handler cannot produce a + # 401 + WWW-Authenticate (the MCP session manager serializes it as a JSON-RPC + # error), so that belongs in a request-scope preemptive check, tracked separately. + verbose_logger.debug(f"MCP list_tools: omitting {server.name}; it needs upstream auth") + return [] except Exception as e: verbose_logger.exception(f"Error getting tools from server {server.name}: {str(e)}") return [] diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_oauth_passthrough_tools.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_oauth_passthrough_tools.py index d51cf8c5b72..b836c3aef33 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_oauth_passthrough_tools.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_oauth_passthrough_tools.py @@ -265,3 +265,131 @@ async def test_fetch_tools_from_gateway_managed_swallows_errors(): ) assert tools == [] mock_client.list_tools.assert_awaited_with(raise_on_error=False) + + +def _http_server(server_id: str, name: str, **kwargs) -> MCPServer: + return MCPServer( + server_id=server_id, + name=name, + url=f"https://{name}/mcp", + transport=MCPTransport.http, + **kwargs, + ) + + +@pytest.mark.asyncio +async def test_aggregate_list_tools_absorbs_one_unauthenticated_server(): + """Regression: across the aggregate (/mcp), a delegate/passthrough server that raises + MCPUpstreamAuthError must not empty every other server's tools. Re-raising it on the + aggregate path (introduced with the passthrough feature) zeroed the whole list because the + fan-out gather propagated it.""" + from unittest.mock import patch + + from mcp.types import Tool as MCPTool + + from litellm.proxy._experimental.mcp_server import server as mcp_server + from litellm.proxy._types import UserAPIKeyAuth + + delegate = _http_server( + "s1", "delegate_docs", auth_type=MCPAuth.oauth2, delegate_auth_to_upstream=True + ) + working = _http_server("s2", "working_docs", auth_type=MCPAuth.none) + good_tool = MCPTool(name="working_docs-read", description="d", inputSchema={"type": "object"}) + + async def fake_get_tools(server, **kwargs): + if server.server_id == delegate.server_id: + raise MCPUpstreamAuthError(status_code=401, www_authenticate=None, server_name=server.name) + return [good_tool] + + with patch.object(mcp_server, "_get_allowed_mcp_servers", AsyncMock(return_value=[delegate, working])), patch.object( + mcp_server, "_prefetch_oauth_creds_for_user", AsyncMock(return_value={}) + ), patch.object(mcp_server, "_prepare_mcp_server_headers", MagicMock(return_value=(None, None))), patch.object( + mcp_server, "_get_user_oauth_extra_headers_from_db", AsyncMock(return_value=None) + ), patch.object( + mcp_server, "filter_tools_by_key_team_permissions", AsyncMock(side_effect=lambda tools, **k: tools) + ), patch.object( + mcp_server.global_mcp_server_manager, "_get_tools_from_server", AsyncMock(side_effect=fake_get_tools) + ): + tools = await mcp_server._get_tools_from_mcp_servers( + user_api_key_auth=UserAPIKeyAuth(token="h", user_id="u1"), + mcp_auth_header=None, + mcp_servers=None, + ) + + assert [t.name for t in tools] == ["working_docs-read"] + + +@pytest.mark.asyncio +async def test_single_server_route_also_absorbs_upstream_auth_error(): + """A single-server route (//mcp) absorbs an upstream-auth error just like the aggregate: + the failing server is omitted (empty list) rather than re-raised. Surfacing it to the client as a + 401 + WWW-Authenticate challenge cannot be done from this list handler — the MCP session manager + serializes a raise into a JSON-RPC error, not an HTTP 401 — so re-auth surfacing is handled by a + request-scope preemptive check, tracked separately.""" + from unittest.mock import patch + + from litellm.proxy._experimental.mcp_server import server as mcp_server + from litellm.proxy._experimental.mcp_server.mcp_context import _mcp_gateway_server_name + from litellm.proxy._types import UserAPIKeyAuth + + delegate = _http_server( + "s1", "delegate_docs", auth_type=MCPAuth.oauth2, delegate_auth_to_upstream=True + ) + + async def fake_get_tools(server, **kwargs): + raise MCPUpstreamAuthError(status_code=401, www_authenticate=None, server_name=server.name) + + # //mcp sets the path-derived single-server scope; absorption must hold even then. + token = _mcp_gateway_server_name.set("delegate_docs") + try: + with patch.object(mcp_server, "_get_allowed_mcp_servers", AsyncMock(return_value=[delegate])), patch.object( + mcp_server, "_prefetch_oauth_creds_for_user", AsyncMock(return_value={}) + ), patch.object(mcp_server, "_prepare_mcp_server_headers", MagicMock(return_value=(None, None))), patch.object( + mcp_server, "_get_user_oauth_extra_headers_from_db", AsyncMock(return_value=None) + ), patch.object( + mcp_server.global_mcp_server_manager, "_get_tools_from_server", AsyncMock(side_effect=fake_get_tools) + ): + tools = await mcp_server._get_tools_from_mcp_servers( + user_api_key_auth=UserAPIKeyAuth(token="h", user_id="u1"), + mcp_auth_header=None, + mcp_servers=["delegate_docs"], + ) + assert tools == [] + finally: + _mcp_gateway_server_name.reset(token) + + +@pytest.mark.asyncio +async def test_aggregate_with_single_accessible_server_still_absorbs(): + """Regression for the route-misclassification: an aggregate request (/mcp, mcp_servers=None) + from a key that can access exactly one server must still absorb that server's + MCPUpstreamAuthError, not surface it. Keying the surface decision off the allowed count rather + than the request filter would re-raise here and leave the aggregate broken for one-server + permission sets.""" + from unittest.mock import patch + + from litellm.proxy._experimental.mcp_server import server as mcp_server + from litellm.proxy._types import UserAPIKeyAuth + + delegate = _http_server( + "s1", "delegate_docs", auth_type=MCPAuth.oauth2, delegate_auth_to_upstream=True + ) + + async def fake_get_tools(server, **kwargs): + raise MCPUpstreamAuthError(status_code=401, www_authenticate=None, server_name=server.name) + + with patch.object(mcp_server, "_get_allowed_mcp_servers", AsyncMock(return_value=[delegate])), patch.object( + mcp_server, "_prefetch_oauth_creds_for_user", AsyncMock(return_value={}) + ), patch.object(mcp_server, "_prepare_mcp_server_headers", MagicMock(return_value=(None, None))), patch.object( + mcp_server, "_get_user_oauth_extra_headers_from_db", AsyncMock(return_value=None) + ), patch.object( + mcp_server.global_mcp_server_manager, "_get_tools_from_server", AsyncMock(side_effect=fake_get_tools) + ): + # Aggregate route: no explicit server filter, even though only one server is accessible. + tools = await mcp_server._get_tools_from_mcp_servers( + user_api_key_auth=UserAPIKeyAuth(token="h", user_id="u1"), + mcp_auth_header=None, + mcp_servers=None, + ) + + assert tools == [] From d6f09c4f245bcf4cfa1f5be2abab6e70b910e525 Mon Sep 17 00:00:00 2001 From: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 19:04:19 +0000 Subject: [PATCH 24/79] test(reasoning-effort-grid): bump cell-count assertion for claude-sonnet-5 The Sonnet 5 grid entry raised the Anthropic direct route to 30 model combos, so test_grid_cell_count now expects 330 cells instead of 319. --- .../reasoning_effort_grid/test_reasoning_effort_grid.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py index 304743b1f3c..2409067ebbe 100644 --- a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py +++ b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py @@ -201,8 +201,8 @@ async def test_reasoning_effort_grid( def test_grid_cell_count() -> None: - assert len(_PARAMS) == 29 * 11, ( - f"expected 319 cells (29 provider x model combos x 11 efforts), " + assert len(_PARAMS) == 30 * 11, ( + f"expected 330 cells (30 provider x model combos x 11 efforts), " f"got {len(_PARAMS)}" ) From 87f035b58f31e1d43b7e5ed49d29974bbc919191 Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 22:07:47 +0300 Subject: [PATCH 25/79] perf(spend): gather independent per-scope spend-counter increments (#31578) --- litellm/proxy/proxy_server.py | 187 ++++++++++-------- .../proxy/proxy_server/test_spend_counters.py | 186 +++++++++++++++++ 2 files changed, 291 insertions(+), 82 deletions(-) diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 6298a5a98b1..57814de6e3f 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -470,6 +470,7 @@ from litellm.proxy.response_api_endpoints.endpoints import router as response_ro from litellm.proxy.route_llm_request import route_request from litellm.proxy.search_endpoints.endpoints import router as search_router from litellm.proxy.shutdown.graceful_shutdown_manager import GracefulShutdownManager +from litellm.proxy.spend_tracking.budget_reservation import get_budget_window_start from litellm.proxy.spend_tracking.spend_management_endpoints import ( router as spend_management_router, ) @@ -2263,111 +2264,133 @@ async def increment_spend_counters( budget_reservation["finalized"] = True return - if token is not None: - # token arrives pre-hashed from metadata["user_api_key"] (auth flow + cost: float = response_cost + + async def _key_scope(key_token: str) -> None: + # key_token arrives pre-hashed from metadata["user_api_key"] (auth flow # hashes raw "sk-..." keys before they reach the callback). The # startswith("sk-") check is a safety net matching update_cache — # if a raw key somehow arrives, hash it; otherwise use as-is to # avoid double-hashing (budget checks read valid_token.token which # is single-hashed). - hashed_token = hash_token(token=token) if isinstance(token, str) and token.startswith("sk-") else token + hashed_token = ( + hash_token(token=key_token) if isinstance(key_token, str) and key_token.startswith("sk-") else key_token + ) key_counter_key = f"spend:key:{hashed_token}" if key_counter_key not in reserved_counter_keys: await _init_and_increment_spend_counter( counter_key=key_counter_key, source_cache_key=hashed_token, - increment=response_cost, + increment=cost, ) - # Increment per-window budget counters for multi-budget keys key_obj = await user_api_key_cache.async_get_cache(key=hashed_token) - if key_obj is not None: - key_budget_limits = getattr(key_obj, "budget_limits", None) or ( - key_obj.get("budget_limits") if isinstance(key_obj, dict) else None - ) - if isinstance(key_budget_limits, str): - key_budget_limits = json.loads(key_budget_limits) - if isinstance(key_budget_limits, list): - for window in key_budget_limits: - duration = window["budget_duration"] if isinstance(window, dict) else window.budget_duration - key_window_counter = f"spend:key:{hashed_token}:window:{duration}" - if key_window_counter not in reserved_counter_keys: - from litellm.proxy.spend_tracking.budget_reservation import ( - get_budget_window_start, - ) + if key_obj is None: + return + key_budget_limits = getattr(key_obj, "budget_limits", None) or ( + key_obj.get("budget_limits") if isinstance(key_obj, dict) else None + ) + if isinstance(key_budget_limits, str): + key_budget_limits = json.loads(key_budget_limits) + if not isinstance(key_budget_limits, list): + return + for window in key_budget_limits: + duration = window["budget_duration"] if isinstance(window, dict) else window.budget_duration + key_window_counter = f"spend:key:{hashed_token}:window:{duration}" + if key_window_counter not in reserved_counter_keys: + await _init_and_increment_window_spend_counter( + counter_key=key_window_counter, + entity_type="Key", + entity_id=hashed_token, + window_start=get_budget_window_start(window), + increment=cost, + ) - await _init_and_increment_window_spend_counter( - counter_key=key_window_counter, - entity_type="Key", - entity_id=hashed_token, - window_start=get_budget_window_start(window), - increment=response_cost, - ) - - if team_id is not None: - team_counter_key = f"spend:team:{team_id}" + async def _team_scope(scope_team_id: str) -> None: + team_counter_key = f"spend:team:{scope_team_id}" if team_counter_key not in reserved_counter_keys: await _init_and_increment_spend_counter( counter_key=team_counter_key, - source_cache_key=f"team_id:{team_id}", - increment=response_cost, + source_cache_key=f"team_id:{scope_team_id}", + increment=cost, ) - # Increment per-window budget counters for multi-budget teams - team_obj = await user_api_key_cache.async_get_cache(key=f"team_id:{team_id}") - if team_obj is not None: - team_budget_limits = getattr(team_obj, "budget_limits", None) or ( - team_obj.get("budget_limits") if isinstance(team_obj, dict) else None + team_obj = await user_api_key_cache.async_get_cache(key=f"team_id:{scope_team_id}") + if team_obj is None: + return + team_budget_limits = getattr(team_obj, "budget_limits", None) or ( + team_obj.get("budget_limits") if isinstance(team_obj, dict) else None + ) + if isinstance(team_budget_limits, str): + team_budget_limits = json.loads(team_budget_limits) + if not isinstance(team_budget_limits, list): + return + for window in team_budget_limits: + duration = window["budget_duration"] if isinstance(window, dict) else window.budget_duration + team_window_counter = f"spend:team:{scope_team_id}:window:{duration}" + if team_window_counter not in reserved_counter_keys: + await _init_and_increment_window_spend_counter( + counter_key=team_window_counter, + entity_type="Team", + entity_id=scope_team_id, + window_start=get_budget_window_start(window), + increment=cost, + ) + + async def _team_member_scope(scope_user_id: str, scope_team_id: str) -> None: + team_member_counter_key = f"spend:team_member:{scope_user_id}:{scope_team_id}" + if team_member_counter_key in reserved_counter_keys: + return + await _init_and_increment_spend_counter( + counter_key=team_member_counter_key, + source_cache_key=f"team_membership:{scope_user_id}:{scope_team_id}", + increment=cost, + ) + + async def _user_scope(scope_user_id: str) -> None: + user_counter_key = f"spend:user:{scope_user_id}" + if user_counter_key in reserved_counter_keys: + return + await _init_and_increment_spend_counter( + counter_key=user_counter_key, + source_cache_key=scope_user_id, + increment=cost, + ) + + scope_coros = tuple( + coro + for coro in ( + _key_scope(token) if token is not None else None, + _team_scope(team_id) if team_id is not None else None, + _team_member_scope(user_id, team_id) if user_id is not None and team_id is not None else None, + _user_scope(user_id) if user_id is not None else None, + _increment_end_user_and_tag_spend_counters( + end_user_id=end_user_id, + tags=tags, + response_cost=cost, + reserved_counter_keys=reserved_counter_keys, ) - if isinstance(team_budget_limits, str): - team_budget_limits = json.loads(team_budget_limits) - if isinstance(team_budget_limits, list): - for window in team_budget_limits: - duration = window["budget_duration"] if isinstance(window, dict) else window.budget_duration - team_window_counter = f"spend:team:{team_id}:window:{duration}" - if team_window_counter not in reserved_counter_keys: - from litellm.proxy.spend_tracking.budget_reservation import ( - get_budget_window_start, - ) - - await _init_and_increment_window_spend_counter( - counter_key=team_window_counter, - entity_type="Team", - entity_id=team_id, - window_start=get_budget_window_start(window), - increment=response_cost, - ) - - if user_id is not None and team_id is not None: - team_member_counter_key = f"spend:team_member:{user_id}:{team_id}" - if team_member_counter_key not in reserved_counter_keys: - await _init_and_increment_spend_counter( - counter_key=team_member_counter_key, - source_cache_key=f"team_membership:{user_id}:{team_id}", - increment=response_cost, + if end_user_id is not None or tags is not None + else None, + _increment_org_spend_counter( + org_id=org_id, + response_cost=cost, + reserved_counter_keys=reserved_counter_keys, ) - - if user_id is not None: - user_counter_key = f"spend:user:{user_id}" - if user_counter_key not in reserved_counter_keys: - await _init_and_increment_spend_counter( - counter_key=user_counter_key, - source_cache_key=user_id, - increment=response_cost, - ) - - await _increment_end_user_and_tag_spend_counters( - end_user_id=end_user_id, - tags=tags, - response_cost=response_cost, - reserved_counter_keys=reserved_counter_keys, + if org_id is not None + else None, + ) + if coro is not None ) - await _increment_org_spend_counter( - org_id=org_id, - response_cost=response_cost, - reserved_counter_keys=reserved_counter_keys, - ) + # return_exceptions so a failing scope does not leave its siblings running + # as orphaned tasks that race the caller's reservation-counter invalidation; + # all scopes settle, then the first error propagates as before. + scope_results = await asyncio.gather(*scope_coros, return_exceptions=True) + scope_errors = [r for r in scope_results if isinstance(r, BaseException)] + if scope_errors: + raise scope_errors[0] + if budget_reservation is not None: budget_reservation["finalized"] = True diff --git a/tests/test_litellm/proxy/proxy_server/test_spend_counters.py b/tests/test_litellm/proxy/proxy_server/test_spend_counters.py index a839d82984c..51980342a1d 100644 --- a/tests/test_litellm/proxy/proxy_server/test_spend_counters.py +++ b/tests/test_litellm/proxy/proxy_server/test_spend_counters.py @@ -20,6 +20,7 @@ Pins covered: from __future__ import annotations +import asyncio from datetime import datetime from unittest.mock import AsyncMock, MagicMock @@ -420,6 +421,191 @@ async def test_increment_spend_counters_increments_all_buckets(monkeypatch): } +class _ConcurrencyProbe: + """Stand-in for redis_cache.async_increment that pins concurrency. + + Each call registers itself as in-flight and blocks on ``release`` until the + test lets it proceed. ``all_arrived`` fires once ``expected`` distinct scope + increments are simultaneously suspended here, which can only happen if the + per-scope increments are gathered rather than awaited one after another. + """ + + def __init__(self, expected_concurrency: int): + self.expected = expected_concurrency + self.in_flight = 0 + self.max_in_flight = 0 + self.all_arrived = asyncio.Event() + self.release = asyncio.Event() + self.values: dict[str, float] = {} + + async def async_increment(self, *, key, value, refresh_ttl=True): + self.in_flight += 1 + self.max_in_flight = max(self.max_in_flight, self.in_flight) + if self.in_flight >= self.expected: + self.all_arrived.set() + if not self.release.is_set(): + await self.release.wait() + self.in_flight -= 1 + self.values[key] = self.values.get(key, 0.0) + value + return self.values[key] + + +@pytest.mark.asyncio +async def test_increment_spend_counters_runs_scopes_concurrently(monkeypatch): + """The six independent scopes (key, team, team_member, user, end_user+tags, + org) must be incremented concurrently. The probe only fires once all six are + suspended in async_increment at the same time, which is impossible if the + awaits are chained sequentially.""" + probe = _ConcurrencyProbe(expected_concurrency=6) + fake_cache = _make_spend_counter_cache(redis_get_value=None) + fake_cache.redis_cache.async_increment = probe.async_increment + fake_user_cache = _make_user_api_key_cache(get_value=None) + monkeypatch.setattr(ps, "spend_counter_cache", fake_cache) + monkeypatch.setattr(ps, "user_api_key_cache", fake_user_cache) + monkeypatch.setattr(ps, "prisma_client", None) + monkeypatch.setattr( + ps.SpendCounterReseed, "coalesced", AsyncMock(return_value=None) + ) + + task = asyncio.create_task( + ps.increment_spend_counters( + token="hashed-tok", + team_id="t1", + user_id="u1", + org_id="org1", + end_user_id="eu1", + tags=["a", "b"], + response_cost=5.0, + ) + ) + + try: + await asyncio.wait_for(probe.all_arrived.wait(), timeout=2.0) + except asyncio.TimeoutError: + probe.release.set() + await task + pytest.fail( + "scope increments did not run concurrently; sequential awaits " + f"detected (peak in-flight was {probe.max_in_flight}, expected 6)" + ) + + assert probe.in_flight == 6 + assert probe.max_in_flight == 6 + probe.release.set() + await task + + assert probe.values == { + "spend:key:hashed-tok": 5.0, + "spend:team:t1": 5.0, + "spend:team_member:u1:t1": 5.0, + "spend:user:u1": 5.0, + "spend:end_user:eu1": 5.0, + "spend:tag:a": 5.0, + "spend:tag:b": 5.0, + "spend:org:org1": 5.0, + } + + +@pytest.mark.asyncio +async def test_increment_spend_counters_skips_reserved_counter_keys(monkeypatch): + """Counters already reserved by a budget reservation are skipped, every + other scope is still incremented exactly once, and the reservation is + finalized after the gathered work completes.""" + import litellm.proxy.spend_tracking.budget_reservation as br + + reserved = {"spend:key:hashed-tok", "spend:org:org1"} + monkeypatch.setattr( + br, "get_reserved_counter_keys", MagicMock(return_value=set(reserved)) + ) + monkeypatch.setattr(br, "reconcile_budget_reservation", AsyncMock()) + + recorded: dict[str, float] = {} + + async def _record_increment(*, key, value, refresh_ttl=True): + recorded[key] = recorded.get(key, 0.0) + value + return recorded[key] + + fake_cache = _make_spend_counter_cache(redis_get_value=None) + fake_cache.redis_cache.async_increment = _record_increment + fake_user_cache = _make_user_api_key_cache(get_value=None) + monkeypatch.setattr(ps, "spend_counter_cache", fake_cache) + monkeypatch.setattr(ps, "user_api_key_cache", fake_user_cache) + monkeypatch.setattr(ps, "prisma_client", None) + monkeypatch.setattr( + ps.SpendCounterReseed, "coalesced", AsyncMock(return_value=None) + ) + + reservation = {"finalized": False} + await ps.increment_spend_counters( + token="hashed-tok", + team_id="t1", + user_id="u1", + org_id="org1", + end_user_id="eu1", + tags=["a"], + response_cost=5.0, + budget_reservation=reservation, + ) + + assert reservation["finalized"] is True + assert recorded == { + "spend:team:t1": 5.0, + "spend:team_member:u1:t1": 5.0, + "spend:user:u1": 5.0, + "spend:end_user:eu1": 5.0, + "spend:tag:a": 5.0, + } + + +@pytest.mark.asyncio +async def test_increment_spend_counters_failing_scope_propagates_after_siblings_settle( + monkeypatch, +): + """A failure in one scope must propagate to the caller (so it can invalidate + reserved counters) while every other scope still settles rather than being + left as an orphaned background task, and the reservation is not finalized.""" + recorded: dict[str, float] = {} + + async def _increment(*, key, value, refresh_ttl=True): + if key == "spend:team:t1": + raise RuntimeError("redis increment failed") + recorded[key] = recorded.get(key, 0.0) + value + return recorded[key] + + fake_cache = _make_spend_counter_cache(redis_get_value=None) + fake_cache.redis_cache.async_increment = _increment + fake_user_cache = _make_user_api_key_cache(get_value=None) + monkeypatch.setattr(ps, "spend_counter_cache", fake_cache) + monkeypatch.setattr(ps, "user_api_key_cache", fake_user_cache) + monkeypatch.setattr(ps, "prisma_client", None) + monkeypatch.setattr( + ps.SpendCounterReseed, "coalesced", AsyncMock(return_value=None) + ) + + reservation = {"finalized": False} + with pytest.raises(RuntimeError, match="redis increment failed"): + await ps.increment_spend_counters( + token="hashed-tok", + team_id="t1", + user_id="u1", + org_id="org1", + end_user_id="eu1", + tags=["a"], + response_cost=5.0, + budget_reservation=reservation, + ) + + assert reservation["finalized"] is False + assert recorded == { + "spend:key:hashed-tok": 5.0, + "spend:team_member:u1:t1": 5.0, + "spend:user:u1": 5.0, + "spend:end_user:eu1": 5.0, + "spend:tag:a": 5.0, + "spend:org:org1": 5.0, + } + + @pytest.mark.asyncio async def test_increment_spend_counters_zero_cost_is_noop_finalizes_reservation( monkeypatch, From 3971469b71e4454bc02dc5ee1d5b9bd1618566ad Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 12:08:15 -0700 Subject: [PATCH 26/79] test(ui): harden Router Settings e2e and make its typing a real CI gate Address an adversarial review of the Loadbalancing e2e: - The "typed against the backend schema" claim was hollow: nothing type-checked e2e_tests (the root tsconfig excludes it and no CI step runs tsc), so a contract drift would compile and run unchanged. Add e2e_tests/tsconfig.json, a typecheck:e2e script, and a CircleCI step so the schema typing actually gates. - The two describe blocks both mutate the proxy's shared router_settings, and the Loadbalancing save echoes the whole settings object, so they could clobber each other under local fullyParallel. Run the file serially. - patchRouterSettings swallowed a failed seed, which surfaced later as a misleading UI timeout. Assert the write succeeded, and rely on the server-side merge instead of echoing the whole settings object back (drops a cast and a GET). - Empty routing_groups already reproduces the bug, so drop the non-empty seed and its model coupling. --- .circleci/config.yml | 8 +++++ .../tests/settings/routerSettings.spec.ts | 36 +++++++++++-------- ui/litellm-dashboard/e2e_tests/tsconfig.json | 9 +++++ ui/litellm-dashboard/package.json | 1 + 4 files changed, 39 insertions(+), 15 deletions(-) create mode 100644 ui/litellm-dashboard/e2e_tests/tsconfig.json diff --git a/.circleci/config.yml b/.circleci/config.yml index f13e9bf66f1..009884cbfe4 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -2687,6 +2687,14 @@ jobs: paths: - ui/litellm-dashboard/node_modules - ~/.cache/ms-playwright + - run: + name: Type-check E2E specs + # The specs type their request/response round-trips against the generated + # OpenAPI schema; this step turns that typing into a real gate, so a backend + # contract drift fails here instead of silently passing at runtime. + command: | + cd ui/litellm-dashboard + npm run typecheck:e2e - run: name: Build UI from source # Prior version used `cp -r out/ ../../litellm/proxy/_experimental/out/`. diff --git a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts index e560500fca6..64dab6d7cf6 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts @@ -3,11 +3,16 @@ import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; import { Role, users } from "../../fixtures/users"; -// Type-only import of the OpenAPI-generated backend schema; esbuild erases it at -// runtime, so the round-trip below is checked against the real /config/update and -// /router/settings contracts without bundling the 2 MB definition file. +// Type-only import of the OpenAPI-generated backend schema. esbuild erases it at +// runtime; the round-trip below is enforced by the `typecheck:e2e` CI step (tsc over +// e2e_tests), so a drift in the /config/update or /router/settings contract fails the +// build rather than silently passing here. import type { components } from "../../../src/lib/http/schema"; +// These tests mutate the proxy's shared router_settings, and the Loadbalancing save +// echoes the whole settings object, so they must not run concurrently. +test.describe.configure({ mode: "serial" }); + const PRIMARY = "fake-openai-gpt-4"; const FALLBACK = "fake-anthropic-claude"; @@ -111,32 +116,33 @@ const BASE_URL = "http://localhost:4000"; const ADMIN_AUTH = { Authorization: `Bearer ${users[Role.ProxyAdmin].password}` }; /** - * Merge a router_settings patch into the live config through the typed - * /config/update contract, preserving any other settings already present. + * Apply a router_settings patch through the typed /config/update contract. The + * server merges it over existing settings (request wins), so only the passed keys + * change. Fails loudly if the write is rejected instead of leaving a silent bad seed. */ async function patchRouterSettings( request: import("@playwright/test").APIRequestContext, patch: Partial>, ) { - const current = await request.get(`${BASE_URL}/get/config/callbacks`, { headers: ADMIN_AUTH }); - const existing = current.ok() ? (await current.json())?.router_settings ?? {} : {}; - const payload = { router_settings: { ...(existing as Record), ...patch } }; - await request.post(`${BASE_URL}/config/update`, { headers: ADMIN_AUTH, data: payload }); + const res = await request.post(`${BASE_URL}/config/update`, { + headers: ADMIN_AUTH, + data: { router_settings: patch }, + }); + expect(res.ok(), `seed /config/update failed: ${res.status()} ${await res.text()}`).toBeTruthy(); } test.describe("Router Settings - Loadbalancing", () => { test.use({ storageState: ADMIN_STORAGE_PATH }); - // Seed a present routing_groups array (the LIT-4057 trigger) plus a known - // num_retries so the UI assertions are deterministic across reruns. - const ROUTING_GROUP = { group_name: "e2e-lit-4057", models: [PRIMARY], routing_strategy: "simple-shuffle" }; - + // Pin num_retries and an empty routing_groups so the assertions are deterministic. + // Empty already reproduces LIT-4057: the old tab serialized [] to the string "[]" + // and the save 422'd. test.beforeEach(async ({ request }) => { - await patchRouterSettings(request, { num_retries: 3, routing_groups: [ROUTING_GROUP] }); + await patchRouterSettings(request, { num_retries: 3, routing_groups: [] }); }); test.afterEach(async ({ request }) => { - await patchRouterSettings(request, { num_retries: 3, routing_groups: [] }); + await patchRouterSettings(request, { num_retries: 3 }); }); test("saves the Loadbalancing tab without a 422 when routing_groups is present, and persists", async ({ diff --git a/ui/litellm-dashboard/e2e_tests/tsconfig.json b/ui/litellm-dashboard/e2e_tests/tsconfig.json new file mode 100644 index 00000000000..abda3fdb8b6 --- /dev/null +++ b/ui/litellm-dashboard/e2e_tests/tsconfig.json @@ -0,0 +1,9 @@ +{ + "extends": "../tsconfig.json", + "compilerOptions": { + "noEmit": true, + "types": ["node"] + }, + "include": ["**/*.ts"], + "exclude": ["node_modules"] +} diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index a8948f4be34..1d2b505a172 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -19,6 +19,7 @@ "e2e:ui": "playwright test --ui --config e2e_tests/playwright.config.ts", "e2e:migration": "playwright test e2e_tests/tests/migration/migratedPages.spec.ts --config e2e_tests/playwright.config.ts", "e2e:migration:root": "playwright test --config e2e_tests/migration.serverRootPath.config.ts", + "typecheck:e2e": "tsc -p e2e_tests/tsconfig.json --noEmit", "knip": "knip", "knip:fix": "knip --fix", "gen:api": "node scripts/gen-api-types.mjs" From 88c34a5bad735c98804d427ce6d30a0bd5bea124 Mon Sep 17 00:00:00 2001 From: michelligabriele Date: Tue, 30 Jun 2026 21:11:50 +0200 Subject: [PATCH 27/79] fix(email): apply EMAIL_SIGNATURE to budget alert emails (#31712) --- .../send_emails/base_email.py | 4 + .../integrations/email_templates/templates.py | 9 +- .../send_emails/test_base_email.py | 130 ++++++++++++++++++ 3 files changed, 137 insertions(+), 6 deletions(-) diff --git a/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py b/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py index 89c3b854686..9d15f45079f 100644 --- a/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py +++ b/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py @@ -239,6 +239,7 @@ class BaseEmailLogger(CustomLogger): max_budget_info=max_budget_info, base_url=email_params.base_url, email_support_contact=email_params.support_contact, + email_footer=email_params.signature, ) await self.send_email( from_email=self.DEFAULT_LITELLM_EMAIL, @@ -311,6 +312,7 @@ class BaseEmailLogger(CustomLogger): max_budget_info=max_budget_info, base_url=email_params.base_url, email_support_contact=email_params.support_contact, + email_footer=email_params.signature, ) # Send email to all recipients @@ -379,6 +381,7 @@ class BaseEmailLogger(CustomLogger): alert_threshold=alert_threshold_str, base_url=email_params.base_url, email_support_contact=email_params.support_contact, + email_footer=email_params.signature, ) await self.send_email( from_email=self.DEFAULT_LITELLM_EMAIL, @@ -403,6 +406,7 @@ class BaseEmailLogger(CustomLogger): alert_threshold=alert_threshold_str, base_url=email_params.base_url, email_support_contact=email_params.support_contact, + email_footer=email_params.signature, ) await self.send_email( from_email=self.DEFAULT_LITELLM_EMAIL, diff --git a/litellm/integrations/email_templates/templates.py b/litellm/integrations/email_templates/templates.py index 8df816dfecd..b4f39074a94 100644 --- a/litellm/integrations/email_templates/templates.py +++ b/litellm/integrations/email_templates/templates.py @@ -81,8 +81,7 @@ SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ If you have any questions, please send an email to {email_support_contact}

- Best,
- The LiteLLM team
+ {email_footer} """ TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ @@ -105,8 +104,7 @@ TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ If you have any questions, please send an email to {email_support_contact}

- Best,
- The LiteLLM team
+ {email_footer} """ MAX_BUDGET_ALERT_EMAIL_TEMPLATE = """ @@ -129,6 +127,5 @@ MAX_BUDGET_ALERT_EMAIL_TEMPLATE = """ If you have any questions, please send an email to {email_support_contact}

- Best,
- The LiteLLM team
+ {email_footer} """ diff --git a/tests/test_litellm/enterprise/enterprise_callbacks/send_emails/test_base_email.py b/tests/test_litellm/enterprise/enterprise_callbacks/send_emails/test_base_email.py index 5cabfe5fb7f..db23b712125 100644 --- a/tests/test_litellm/enterprise/enterprise_callbacks/send_emails/test_base_email.py +++ b/tests/test_litellm/enterprise/enterprise_callbacks/send_emails/test_base_email.py @@ -1112,3 +1112,133 @@ async def test_no_map_preserves_old_single_threshold( # Old path cache key has no threshold percentage cache_key = mock_cache.async_set_cache.call_args[1]["key"] assert cache_key == "email_budget_alerts:max_budget_alert:test_user" + + +CUSTOM_SIGNATURE = "
Best,
The Acme Platform Team
" + + +@pytest.mark.asyncio +async def test_send_soft_budget_alert_email_uses_custom_signature( + base_email_logger, mock_send_email, mock_lookup_user_email +): + """Soft budget alert honors EMAIL_SIGNATURE for premium users.""" + event = WebhookEvent( + user_id="test_user", + user_email="test@example.com", + event_group=Litellm_EntityType.USER, + event="soft_budget_crossed", + event_message="Soft Budget Crossed", + spend=105.0, + max_budget=200.0, + soft_budget=100.0, + ) + with mock.patch.dict( + os.environ, + {"PROXY_BASE_URL": "http://test.com", "EMAIL_SIGNATURE": CUSTOM_SIGNATURE}, + ), patch("litellm.proxy.proxy_server.premium_user", True): + await base_email_logger.send_soft_budget_alert_email(event) + + html_body = mock_send_email.call_args[1]["html_body"] + assert CUSTOM_SIGNATURE in html_body + assert "The LiteLLM team" not in html_body + + +@pytest.mark.asyncio +async def test_send_team_soft_budget_alert_email_uses_custom_signature( + base_email_logger, mock_send_email, mock_lookup_user_email +): + """Team soft budget alert honors EMAIL_SIGNATURE for premium users.""" + event = WebhookEvent( + user_id="test_user", + event_group=Litellm_EntityType.TEAM, + event="soft_budget_crossed", + event_message="Team Soft Budget Crossed", + spend=105.0, + max_budget=200.0, + soft_budget=100.0, + team_alias="Acme", + alert_emails=["teamlead@example.com"], + ) + with mock.patch.dict( + os.environ, + {"PROXY_BASE_URL": "http://test.com", "EMAIL_SIGNATURE": CUSTOM_SIGNATURE}, + ), patch("litellm.proxy.proxy_server.premium_user", True): + await base_email_logger.send_team_soft_budget_alert_email(event) + + html_body = mock_send_email.call_args[1]["html_body"] + assert CUSTOM_SIGNATURE in html_body + assert "The LiteLLM team" not in html_body + + +@pytest.mark.asyncio +async def test_send_max_budget_alert_email_single_recipient_uses_custom_signature( + base_email_logger, mock_send_email, mock_lookup_user_email +): + """Max budget alert (single-recipient path) honors EMAIL_SIGNATURE.""" + event = WebhookEvent( + user_id="test_user", + user_email="test@example.com", + event_group=Litellm_EntityType.USER, + event="max_budget_alert", + event_message="Max Budget Alert", + spend=165.0, + max_budget=200.0, + ) + with mock.patch.dict( + os.environ, + {"PROXY_BASE_URL": "http://test.com", "EMAIL_SIGNATURE": CUSTOM_SIGNATURE}, + ), patch("litellm.proxy.proxy_server.premium_user", True): + await base_email_logger.send_max_budget_alert_email(event) + + html_body = mock_send_email.call_args[1]["html_body"] + assert CUSTOM_SIGNATURE in html_body + assert "The LiteLLM team" not in html_body + + +@pytest.mark.asyncio +async def test_send_max_budget_alert_email_multi_recipient_uses_custom_signature( + base_email_logger, mock_send_email, mock_lookup_user_email +): + """Max budget alert (multi-threshold/recipient path) honors EMAIL_SIGNATURE.""" + event = WebhookEvent( + user_id="test_user", + user_email="owner@example.com", + event_group=Litellm_EntityType.USER, + event="max_budget_alert", + event_message="Max Budget Alert", + spend=165.0, + max_budget=200.0, + ) + with mock.patch.dict( + os.environ, + {"PROXY_BASE_URL": "http://test.com", "EMAIL_SIGNATURE": CUSTOM_SIGNATURE}, + ), patch("litellm.proxy.proxy_server.premium_user", True): + await base_email_logger.send_max_budget_alert_email( + event, threshold_pct=75, recipient_emails=["a@example.com", "b@example.com"] + ) + + html_body = mock_send_email.call_args[1]["html_body"] + assert CUSTOM_SIGNATURE in html_body + assert "The LiteLLM team" not in html_body + + +@pytest.mark.asyncio +async def test_send_soft_budget_alert_email_default_footer_when_no_signature( + base_email_logger, mock_send_email, mock_lookup_user_email +): + """Without EMAIL_SIGNATURE, budget alert falls back to the default EMAIL_FOOTER.""" + event = WebhookEvent( + user_id="test_user", + user_email="test@example.com", + event_group=Litellm_EntityType.USER, + event="soft_budget_crossed", + event_message="Soft Budget Crossed", + spend=105.0, + max_budget=200.0, + soft_budget=100.0, + ) + with mock.patch.dict(os.environ, {"PROXY_BASE_URL": "http://test.com"}): + await base_email_logger.send_soft_budget_alert_email(event) + + html_body = mock_send_email.call_args[1]["html_body"] + assert EMAIL_FOOTER in html_body From 6d828e5759dc76ecc5d582861fd56e27a5763c2d Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 12:17:33 -0700 Subject: [PATCH 28/79] feat(messages): passthrough /v1/messages to native endpoints via supported_endpoints (#31685) * feat(messages): passthrough /v1/messages to native endpoints via supported_endpoints The unified /v1/messages proxy endpoint always translated inbound Anthropic requests down to /v1/chat/completions (or the Responses API for openai) when the deployment's provider lacked a native Anthropic-messages config, dropping Anthropic-only features like cache_control and thinking. Some customers run OpenAI-compatible servers (self-hosted vLLM, DeepSeek's Anthropic endpoint, etc.) that also natively expose /v1/messages and want the raw Anthropic payload forwarded untranslated, while keeping provider openai so /v1/chat/completions to the same deployment stays native. Opt in per deployment via model_info.supported_endpoints containing /v1/messages. When present, the gate routes to a generic, provider-agnostic OpenAILikeAnthropicMessagesConfig that POSTs the Anthropic payload to {api_base}/v1/messages with Bearer auth, instead of translating. Default behavior is unchanged. Generalizes and supersedes the hosted_vllm-only, env-var-toggled PR #28745. * fix(messages): preserve standard-cased caller headers in native passthrough The OpenAI-like Anthropic passthrough config only checked for lowercase header names before injecting Bearer auth, anthropic-version, and content-type defaults. A caller sending standard-cased Authorization, Anthropic-Version, or Content-Type was treated as missing those headers, so LiteLLM added duplicate lowercase variants and overwrote the caller's credential/version at the HTTP layer. Header presence is now checked case-insensitively and the merge no longer mutates the caller dict. Also moves the feature docs out of the main repo (docs live in litellm-docs). * fix(openai_like/messages): delegate to parent transform and inject anthropic-beta headers The passthrough config bypassed the parent transform and skipped header beta injection. Both gaps cause native /v1/messages features (context management, advisor tool, fast mode, structured outputs, reasoning_effort, advisor stripping) to silently degrade on opted-in deployments. Reuse the parent's pipeline and call _update_headers_with_anthropic_beta after merging defaults * fix: normalize anthropic-beta header key case before beta injection * style: collapse anthropic-beta header normalization to single line ruff format --check requires the comprehension on one line (it fits within the 120 char limit); fixes the lint job failure on the bugbot autofix commit * fix(messages): forward anthropic-beta to native passthrough upstream The shared anthropic_messages HTTP handler ran update_headers_with_filtered_beta with the deployment's custom_llm_provider after validate. For the native /v1/messages passthrough that provider is openai, which has no beta-header mapping, so every anthropic-beta value (caller-supplied or feature-derived for speed/context_management/etc.) was stripped to empty before the upstream request, breaking beta passthrough to the Anthropic-compatible endpoint. Beta filtering only makes sense on cross-provider translation paths where the upstream cannot understand Anthropic betas. Gate it on a new should_filter_anthropic_beta_headers() that defaults to True (bedrock, vertex_ai, native anthropic unchanged) and is overridden to False by OpenAILikeAnthropicMessagesConfig, whose upstream is a native Anthropic endpoint, so betas pass through verbatim. * chore: remove accidentally committed local QA logs and config --------- Co-authored-by: Cursor Agent --- .../messages/handler.py | 21 ++ .../anthropic_messages/transformation.py | 11 + litellm/llms/custom_httpx/llm_http_handler.py | 3 +- litellm/llms/openai_like/messages/__init__.py | 0 .../openai_like/messages/transformation.py | 69 ++++ ...erimental_pass_through_messages_handler.py | 106 ++++++ .../llms/openai_like/messages/__init__.py | 0 ..._like_anthropic_messages_transformation.py | 301 ++++++++++++++++++ 8 files changed, 510 insertions(+), 1 deletion(-) create mode 100644 litellm/llms/openai_like/messages/__init__.py create mode 100644 litellm/llms/openai_like/messages/transformation.py create mode 100644 tests/test_litellm/llms/openai_like/messages/__init__.py create mode 100644 tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py index 9c9427c7302..547ddd9b8d3 100644 --- a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py +++ b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py @@ -61,6 +61,19 @@ def _should_route_to_responses_api(custom_llm_provider: Optional[str]) -> bool: return custom_llm_provider in _RESPONSES_API_PROVIDERS +def _deployment_passes_through_anthropic_messages(model_info: object) -> bool: + """Whether the deployment opted into forwarding /v1/messages untranslated. + + The opt-in is ``model_info.supported_endpoints`` containing ``"/v1/messages"``, + declared per deployment in config.yaml and plumbed here as ``kwargs["model_info"]`` + by the router. + """ + if not isinstance(model_info, dict): + return False + supported_endpoints = model_info.get("supported_endpoints") + return isinstance(supported_endpoints, (list, tuple)) and "/v1/messages" in supported_endpoints + + ####### ENVIRONMENT VARIABLES ################### # Initialize any necessary instances or variables here base_llm_http_handler = BaseLLMHTTPHandler() @@ -456,6 +469,14 @@ def anthropic_messages_handler( model=model, provider=litellm.LlmProviders(custom_llm_provider), ) + if anthropic_messages_provider_config is None and _deployment_passes_through_anthropic_messages( + kwargs.get("model_info") + ): + from litellm.llms.openai_like.messages.transformation import ( + OpenAILikeAnthropicMessagesConfig, + ) + + anthropic_messages_provider_config = OpenAILikeAnthropicMessagesConfig() if anthropic_messages_provider_config is None: # Route to Responses API for OpenAI / Azure, chat/completions for everything else. _shared_kwargs = dict( diff --git a/litellm/llms/base_llm/anthropic_messages/transformation.py b/litellm/llms/base_llm/anthropic_messages/transformation.py index 7f8403c0223..966995bc571 100644 --- a/litellm/llms/base_llm/anthropic_messages/transformation.py +++ b/litellm/llms/base_llm/anthropic_messages/transformation.py @@ -103,6 +103,17 @@ class BaseAnthropicMessagesConfig(ABC): """ return headers, None + def should_filter_anthropic_beta_headers(self) -> bool: + """ + Whether ``anthropic-beta`` header values should be filtered down to the + ones the routed provider supports before the upstream request. + + Cross-provider translation paths (bedrock, vertex_ai, ...) need this so + unsupported betas are dropped. Configs that forward natively to an + Anthropic-compatible endpoint return False to pass betas through verbatim. + """ + return True + def get_async_streaming_response_iterator( self, model: str, diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index 9f18b669124..9bb956d0808 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -1986,7 +1986,8 @@ class BaseLLMHTTPHandler: api_base=api_base, ) - headers = update_headers_with_filtered_beta(headers=headers, provider=custom_llm_provider) + if anthropic_messages_provider_config.should_filter_anthropic_beta_headers(): + headers = update_headers_with_filtered_beta(headers=headers, provider=custom_llm_provider) logging_obj.update_from_kwargs( kwargs=kwargs, diff --git a/litellm/llms/openai_like/messages/__init__.py b/litellm/llms/openai_like/messages/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/openai_like/messages/transformation.py b/litellm/llms/openai_like/messages/transformation.py new file mode 100644 index 00000000000..0df8c6e830b --- /dev/null +++ b/litellm/llms/openai_like/messages/transformation.py @@ -0,0 +1,69 @@ +from typing import Any, Optional + +from litellm.llms.anthropic.experimental_pass_through.messages.transformation import ( + AnthropicMessagesConfig, +) + +DEFAULT_ANTHROPIC_API_VERSION = "2023-06-01" + + +class OpenAILikeAnthropicMessagesConfig(AnthropicMessagesConfig): + """ + Forwards Anthropic /v1/messages requests to an OpenAI-compatible server that + also natively exposes the Anthropic Messages API, with no translation. + + Opted into per deployment via ``model_info.supported_endpoints`` containing + ``"/v1/messages"``. The inbound Anthropic payload (system, cache_control, + thinking, tools, ...) is forwarded essentially unchanged to + ``{api_base}/v1/messages``, so Anthropic-only features that the + Anthropic->OpenAI translation would otherwise drop are preserved. Response + parsing and streaming are inherited from the native Anthropic config. + """ + + def validate_anthropic_messages_environment( + self, + headers: dict[str, str], + model: str, + messages: list[Any], + optional_params: dict, + litellm_params: dict, + api_key: Optional[str] = None, + api_base: Optional[str] = None, + ) -> tuple[dict[str, str], Optional[str]]: + present = {key.lower() for key in headers} + needs_auth = bool(api_key) and "authorization" not in present and "x-api-key" not in present + defaults: dict[str, str] = { + **({"authorization": f"Bearer {api_key}"} if needs_auth else {}), + **({"anthropic-version": DEFAULT_ANTHROPIC_API_VERSION} if "anthropic-version" not in present else {}), + **({"content-type": "application/json"} if "content-type" not in present else {}), + } + combined = {**headers, **defaults} + normalized = { + ("anthropic-beta" if key.lower() == "anthropic-beta" else key): value for key, value in combined.items() + } + merged = self._update_headers_with_anthropic_beta( + headers=normalized, + optional_params=optional_params, + ) + return merged, api_base + + def should_filter_anthropic_beta_headers(self) -> bool: + return False + + def get_complete_url( + self, + api_base: Optional[str], + api_key: Optional[str], + model: str, + optional_params: dict, + litellm_params: dict, + stream: Optional[bool] = None, + ) -> str: + if not api_base: + raise ValueError("api_base is required to forward Anthropic /v1/messages to a native endpoint") + base = api_base.rstrip("/") + if base.endswith("/v1/messages"): + return base + if base.endswith("/v1"): + base = base[: -len("/v1")] + return f"{base}/v1/messages" diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py index 7bcaf07c5bb..3327fc39f73 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py @@ -715,3 +715,109 @@ async def test_async_wrapper_sets_presanitized_and_sanitizes_once(): assert spy.call_count == 1 assert captured["presanitized"] is True assert [b["type"] for b in captured["messages"][0]["content"]] == ["tool_use"] + + +def _gate_stubs(monkeypatch): + """Patch the gate's downstream dispatch targets so config selection can be + observed without making a network call. + + Returns ``(captured, translation_calls)`` where ``captured["config"]`` is the + provider config handed to the native passthrough path and ``translation_calls`` + counts hits on the Anthropic->OpenAI translation handlers. + """ + from litellm.llms.anthropic.experimental_pass_through.messages import handler + + captured = {} + translation_calls = {"count": 0} + + def fake_native(**kwargs): + captured["config"] = kwargs.get("anthropic_messages_provider_config") + return "native-passthrough" + + def fake_translation(**kwargs): + translation_calls["count"] += 1 + return "translated" + + monkeypatch.setattr(handler.base_llm_http_handler, "anthropic_messages_handler", fake_native) + monkeypatch.setattr( + handler.LiteLLMMessagesToResponsesAPIHandler, + "anthropic_messages_handler", + staticmethod(fake_translation), + ) + monkeypatch.setattr( + handler.LiteLLMMessagesToCompletionTransformationHandler, + "anthropic_messages_handler", + staticmethod(fake_translation), + ) + return captured, translation_calls + + +def test_gate_passthrough_when_supported_endpoints_opts_in(monkeypatch): + """provider=openai + model_info.supported_endpoints containing /v1/messages + must route to the native passthrough config, NOT the translation handlers.""" + from litellm.llms.anthropic.experimental_pass_through.messages.handler import ( + anthropic_messages_handler, + ) + from litellm.llms.openai_like.messages.transformation import ( + OpenAILikeAnthropicMessagesConfig, + ) + + captured, translation_calls = _gate_stubs(monkeypatch) + + result = anthropic_messages_handler( + max_tokens=100, + messages=[{"role": "user", "content": "Hello"}], + model="openai/some-model", + api_key="sk-test", + api_base="https://host/v1", + model_info={"supported_endpoints": ["/v1/chat/completions", "/v1/messages"]}, + ) + + assert result == "native-passthrough" + assert isinstance(captured["config"], OpenAILikeAnthropicMessagesConfig) + assert translation_calls["count"] == 0 + + +def test_gate_translates_when_supported_endpoints_absent(monkeypatch): + """Default behavior is unchanged: without the /v1/messages opt-in, an openai + deployment is translated (Responses API), never passed through natively.""" + from litellm.llms.anthropic.experimental_pass_through.messages.handler import ( + anthropic_messages_handler, + ) + + captured, translation_calls = _gate_stubs(monkeypatch) + + result = anthropic_messages_handler( + max_tokens=100, + messages=[{"role": "user", "content": "Hello"}], + model="openai/some-model", + api_key="sk-test", + api_base="https://host/v1", + ) + + assert result == "translated" + assert translation_calls["count"] == 1 + assert "config" not in captured + + +def test_gate_passthrough_skipped_when_only_chat_completions_supported(monkeypatch): + """A deployment that lists only /v1/chat/completions is still translated; + the opt-in is specifically the /v1/messages entry.""" + from litellm.llms.anthropic.experimental_pass_through.messages.handler import ( + anthropic_messages_handler, + ) + + captured, translation_calls = _gate_stubs(monkeypatch) + + result = anthropic_messages_handler( + max_tokens=100, + messages=[{"role": "user", "content": "Hello"}], + model="openai/some-model", + api_key="sk-test", + api_base="https://host/v1", + model_info={"supported_endpoints": ["/v1/chat/completions"]}, + ) + + assert result == "translated" + assert translation_calls["count"] == 1 + assert "config" not in captured diff --git a/tests/test_litellm/llms/openai_like/messages/__init__.py b/tests/test_litellm/llms/openai_like/messages/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py b/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py new file mode 100644 index 00000000000..534d7aefda4 --- /dev/null +++ b/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py @@ -0,0 +1,301 @@ +import pytest + +from litellm.llms.anthropic.common_utils import AnthropicError +from litellm.llms.openai_like.messages.transformation import ( + OpenAILikeAnthropicMessagesConfig, +) +from litellm.types.router import GenericLiteLLMParams + + +@pytest.fixture +def config() -> OpenAILikeAnthropicMessagesConfig: + return OpenAILikeAnthropicMessagesConfig() + + +@pytest.mark.parametrize( + "api_base, expected", + [ + ("https://host/v1", "https://host/v1/messages"), + ("https://host/v1/", "https://host/v1/messages"), + ("https://host", "https://host/v1/messages"), + ("https://host/v1/messages", "https://host/v1/messages"), + ("https://api.deepseek.com/anthropic", "https://api.deepseek.com/anthropic/v1/messages"), + ("https://api.deepseek.com/anthropic/v1", "https://api.deepseek.com/anthropic/v1/messages"), + ], +) +def test_get_complete_url_handles_api_base_variants(config, api_base, expected): + url = config.get_complete_url( + api_base=api_base, + api_key="sk-test", + model="some-model", + optional_params={}, + litellm_params={}, + ) + assert url == expected + + +def test_get_complete_url_requires_api_base(config): + with pytest.raises(ValueError, match="api_base is required"): + config.get_complete_url( + api_base=None, + api_key="sk-test", + model="some-model", + optional_params={}, + litellm_params={}, + ) + + +def test_request_stays_in_anthropic_shape(config): + messages = [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "Summarize this", + "cache_control": {"type": "ephemeral"}, + } + ], + } + ] + optional_params = { + "max_tokens": 256, + "system": "You are a careful assistant", + "thinking": {"type": "enabled", "budget_tokens": 1024}, + "temperature": 0.3, + "tools": [{"name": "lookup", "input_schema": {"type": "object"}}], + "stream": False, + } + + payload = config.transform_anthropic_messages_request( + model="some-model", + messages=messages, + anthropic_messages_optional_request_params=optional_params, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert payload["model"] == "some-model" + assert payload["messages"] == messages + assert payload["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral"} + assert payload["system"] == "You are a careful assistant" + assert payload["thinking"] == {"type": "enabled", "budget_tokens": 1024} + assert payload["max_tokens"] == 256 + assert payload["tools"] == optional_params["tools"] + + openai_only_keys = { + "max_completion_tokens", + "stop", + "n", + "logprobs", + "response_format", + "frequency_penalty", + } + assert openai_only_keys.isdisjoint(payload.keys()) + + +def test_request_requires_max_tokens(config): + with pytest.raises(AnthropicError, match="max_tokens is required"): + config.transform_anthropic_messages_request( + model="some-model", + messages=[{"role": "user", "content": "hi"}], + anthropic_messages_optional_request_params={"system": "s"}, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + +def test_validate_environment_sets_bearer_and_anthropic_defaults(config): + headers, api_base = config.validate_anthropic_messages_environment( + headers={}, + model="some-model", + messages=[], + optional_params={}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + assert headers["authorization"] == "Bearer sk-test" + assert headers["anthropic-version"] == "2023-06-01" + assert headers["content-type"] == "application/json" + assert api_base == "https://host/v1" + + +def test_validate_environment_does_not_overwrite_caller_headers(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={ + "authorization": "Bearer caller-token", + "anthropic-version": "2024-10-22", + "content-type": "application/json", + }, + model="some-model", + messages=[], + optional_params={}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + assert headers["authorization"] == "Bearer caller-token" + assert headers["anthropic-version"] == "2024-10-22" + + +def test_validate_environment_preserves_standard_cased_caller_headers(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={ + "Authorization": "Bearer caller-token", + "Anthropic-Version": "2024-10-22", + "Content-Type": "application/json", + }, + model="some-model", + messages=[], + optional_params={}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + lowercased = {key.lower() for key in headers} + assert len(lowercased) == len(headers) + assert headers["Authorization"] == "Bearer caller-token" + assert headers["Anthropic-Version"] == "2024-10-22" + assert headers["Content-Type"] == "application/json" + + +def test_validate_environment_honors_x_api_key_when_present(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={"X-Api-Key": "caller-key"}, + model="some-model", + messages=[], + optional_params={}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + assert "authorization" not in {key.lower() for key in headers} + assert headers["X-Api-Key"] == "caller-key" + + +def test_validate_environment_injects_anthropic_beta_for_context_management(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={}, + model="some-model", + messages=[], + optional_params={ + "context_management": {"edits": [{"type": "clear_tool_uses_20250919"}]}, + }, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + assert "context-management-2025-06-27" in headers["anthropic-beta"].split(",") + + +def test_validate_environment_injects_anthropic_beta_for_fast_mode(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={}, + model="some-model", + messages=[], + optional_params={"speed": "fast"}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + assert "fast-mode-2026-02-01" in headers["anthropic-beta"].split(",") + + +def test_validate_environment_merges_existing_anthropic_beta(config): + headers, _ = config.validate_anthropic_messages_environment( + headers={"anthropic-beta": "caller-flag"}, + model="some-model", + messages=[], + optional_params={"speed": "fast"}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + beta_values = set(headers["anthropic-beta"].split(",")) + assert "caller-flag" in beta_values + assert "fast-mode-2026-02-01" in beta_values + + +def test_request_strips_advisor_blocks_when_advisor_tool_absent(config): + messages = [ + {"role": "user", "content": "hello"}, + { + "role": "assistant", + "content": [ + {"type": "text", "text": "thinking out loud"}, + {"type": "server_tool_use", "id": "advisor_1", "name": "advisor", "input": {}}, + {"type": "advisor_tool_result", "tool_use_id": "advisor_1", "content": "stale"}, + ], + }, + ] + + payload = config.transform_anthropic_messages_request( + model="some-model", + messages=messages, + anthropic_messages_optional_request_params={"max_tokens": 64}, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + flattened_types = [ + block.get("type") + for message in payload["messages"] + if isinstance(message.get("content"), list) + for block in message["content"] + if isinstance(block, dict) + ] + assert "advisor_tool_result" not in flattened_types + assert "server_tool_use" not in flattened_types + + +def test_request_maps_reasoning_effort_to_thinking(config): + payload = config.transform_anthropic_messages_request( + model="claude-sonnet-4-20250514", + messages=[{"role": "user", "content": "hi"}], + anthropic_messages_optional_request_params={ + "max_tokens": 1024, + "reasoning_effort": "medium", + }, + litellm_params=GenericLiteLLMParams(), + headers={}, + ) + + assert "reasoning_effort" not in payload + assert isinstance(payload.get("thinking"), dict) + assert payload["thinking"].get("type") == "enabled" + + +def test_passthrough_disables_anthropic_beta_filtering(config): + from litellm.llms.anthropic.experimental_pass_through.messages.transformation import ( + AnthropicMessagesConfig, + ) + + assert config.should_filter_anthropic_beta_headers() is False + assert AnthropicMessagesConfig().should_filter_anthropic_beta_headers() is True + + +def test_anthropic_beta_survives_provider_filter_on_passthrough_path(config): + from litellm.anthropic_beta_headers_manager import update_headers_with_filtered_beta + + headers, _ = config.validate_anthropic_messages_environment( + headers={"Anthropic-Beta": "caller-flag"}, + model="some-model", + messages=[], + optional_params={"speed": "fast"}, + litellm_params={}, + api_key="sk-test", + api_base="https://host/v1", + ) + + # The deployment routes as provider "openai", which has no beta mapping, so an + # unconditional filter would drop every anthropic-beta value. The handler must + # skip filtering for this config so the native upstream still receives them. + if config.should_filter_anthropic_beta_headers(): + headers = update_headers_with_filtered_beta(headers=dict(headers), provider="openai") + + survived = set(headers.get("anthropic-beta", "").split(",")) + assert {"caller-flag", "fast-mode-2026-02-01"} <= survived + + stripped = update_headers_with_filtered_beta(headers=dict(headers), provider="openai") + assert "anthropic-beta" not in stripped From 6d43c21ec641baee73e486ec3f9b72c1c36a850d Mon Sep 17 00:00:00 2001 From: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 19:19:48 +0000 Subject: [PATCH 29/79] fix(anthropic): drop redundant supports_output_config from Vertex/Azure Sonnet 5 The Vertex AI and Azure AI Sonnet 5 entries carried supports_output_config: true, which the gen-5 siblings (vertex_ai/claude-opus-4-8, azure_ai/claude-fable-5, etc.) do not. The flag only feeds AnthropicConfig._model_supports_effort_param, which already returns true for these entries via supports_xhigh/max_reasoning_effort, so output_config.effort still forwards on both routes. Removing it is behavior neutral and matches the existing per-platform convention for gen-5 Claude. --- litellm/model_prices_and_context_window_backup.json | 9 +++------ model_prices_and_context_window.json | 9 +++------ 2 files changed, 6 insertions(+), 12 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 5bd70690d48..b16e1015255 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -2737,8 +2737,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "azure_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, @@ -35235,8 +35234,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "vertex_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, @@ -42703,8 +42701,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "vertex_ai/claude-sonnet-4-6@default": { "supports_adaptive_thinking": true, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 5fc431d721b..3e4c5b947a1 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -2737,8 +2737,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "azure_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, @@ -35412,8 +35411,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "vertex_ai/claude-sonnet-4-6": { "supports_adaptive_thinking": true, @@ -42938,8 +42936,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, - "supports_output_config": true + "supports_max_reasoning_effort": true }, "vertex_ai/claude-sonnet-4-6@default": { "supports_adaptive_thinking": true, From 52dc15adfefc9385e68c6a4a635f659cfb466f9e Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 22:21:14 +0300 Subject: [PATCH 30/79] fix(proxy): isolate poison spend-log rows so one bad record can't drop the whole batch (#31705) update_spend_logs flushes the queue with a single create_many per batch, so one row carrying bytes Postgres refuses (a residual NUL byte is the canonical case) fails the entire insert and drops every good spend log alongside it. PR #29515 strips NUL bytes from the JSON columns, but the scalar string columns (end_user, model, session_id, ...) still flow through unsanitized, so a poisoned row can still reach the write and take a batch of up to 1000 good rows down with it. On a genuine data-layer rejection the batch is now bisected so the good rows still persist and only the offending row is dropped and logged with its request_id. The classification lives in PrismaDBExceptionHandler.is_prisma_data_error (matched by exact type so systemic subclasses like a missing table are not mistaken for a single poison row), which keeps prisma an in-function import and litellm.proxy.utils importable without the proxy extra. Transport failures, including the "can't reach database server" outage that prisma mislabels as a DataError, are re-raised unchanged so the existing connection-retry path still runs and a transient outage never turns into silent per-row data loss. The bisection carries a per-batch isolation budget so an authenticated caller flooding poisoned rows cannot amplify one failed bulk insert into ~2N failed inserts and N log lines; once the budget is spent the still-failing remainder is dropped wholesale under a single log line. Resolves LIT-4103 --- litellm/proxy/db/exception_handler.py | 23 ++++ litellm/proxy/utils.py | 67 ++++++++++- .../proxy/db/test_exception_handler.py | 31 +++++ .../test_proxy_update_spend.py | 106 ++++++++++++++++++ 4 files changed, 225 insertions(+), 2 deletions(-) diff --git a/litellm/proxy/db/exception_handler.py b/litellm/proxy/db/exception_handler.py index 48066945131..3a93896a206 100644 --- a/litellm/proxy/db/exception_handler.py +++ b/litellm/proxy/db/exception_handler.py @@ -66,6 +66,29 @@ class PrismaDBExceptionHandler: return True return False + @staticmethod + def is_prisma_data_error(e: Exception) -> bool: + """True iff ``e`` is a base prisma ``DataError``: the database processed + the statement and refused the data itself (e.g. ``invalid byte sequence + for encoding "UTF8": 0x00``), as opposed to a connectivity failure. + + Matched by exact type, not ``isinstance``: the specific data-layer + subclasses (``UniqueViolationError``, ``TableNotFoundError``, + ``MissingRequiredValueError`` ...) all derive from ``DataError`` but + carry their own semantics, and a systemic one like a missing table must + not be mistaken for a single poison row and bisected away. A raw + Postgres execution error with no prisma P-code surfaces as the base + ``DataError``. + + prisma also wraps the P1001 "can't reach database server" outage as a + base ``DataError``, so a caller that must not treat an outage as a + per-row data rejection has to additionally consult + ``is_database_service_unavailable_error`` before acting on a True here. + """ + import prisma + + return type(e) is prisma.errors.DataError + @staticmethod def is_database_transport_error(e: Exception) -> bool: """ diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 154a17bc4db..4433a35f5d0 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -23,7 +23,9 @@ from typing import ( Dict, List, Literal, + Mapping, Optional, + Sequence, Tuple, Union, cast, @@ -5194,8 +5196,10 @@ class ProxyUpdateSpend: for j in range(0, len(logs_to_process), BATCH_SIZE): batch = logs_to_process[j : j + BATCH_SIZE] batch_with_dates = [prisma_client.jsonify_object({**entry}) for entry in batch] - await SpendLogsRepository(prisma_client).table.create_many( - data=batch_with_dates, skip_duplicates=True + await _create_spend_logs_with_poison_isolation( + SpendLogsRepository(prisma_client), + batch_with_dates, + MAX_SPEND_LOG_ISOLATION_ATTEMPTS_PER_BATCH, ) verbose_proxy_logger.debug(f"Flushed {len(batch)} logs to the DB.") # Explicitly clear batch memory @@ -5462,6 +5466,65 @@ async def _monitor_spend_logs_queue( await asyncio.sleep(current_interval) +MAX_SPEND_LOG_ISOLATION_ATTEMPTS_PER_BATCH = 256 + + +async def _create_spend_logs_with_poison_isolation( + repo: SpendLogsRepository, + rows: Sequence[Mapping[str, object]], + attempts_left: int, +) -> int: + """Write spend-log rows, isolating any row Postgres rejects on its data. + + ``create_many`` writes the whole batch in a single statement, so one row + carrying bytes Postgres refuses (a residual NUL byte is the canonical case) + fails the entire insert and drops every good row alongside it. On a genuine + data-layer rejection the batch is bisected so the good rows still persist + and only the offending row is dropped and logged. Transport failures, + including the "can't reach database server" outage that prisma mislabels as + a ``DataError``, are re-raised unchanged so the caller's connection-retry + path still runs. + + ``attempts_left`` is a hard ceiling on the number of ``create_many`` calls + the isolation may issue for this batch, so an authenticated caller flooding + poisoned rows cannot amplify one failed bulk insert into unbounded failed + inserts and log lines. It is checked before any insert (so an exhausted + budget never even attempts a write), decremented once per ``create_many`` + call, and threaded through the recursion so the whole bisection shares one + allowance; total inserts are therefore bounded by the initial value + regardless of how many rows are poisoned. When it runs out the still-failing + remainder is dropped wholesale (the pre-existing drop-the-batch behavior) + under one log line. Returns the budget left after this subtree. + """ + if attempts_left <= 0: + spend_log_error( + "Spend tracking - dropping %d spend log rows without per-row isolation; " + "isolation attempt budget exhausted for this flush", + len(rows), + ) + return 0 + try: + await repo.table.create_many(data=rows, skip_duplicates=True) + return attempts_left - 1 + except Exception as e: + if not PrismaDBExceptionHandler.is_prisma_data_error(e): + raise + if PrismaDBExceptionHandler.is_database_service_unavailable_error(e): + raise + if len(rows) == 1: + request_id = rows[0].get("request_id") + spend_log_error( + "Spend tracking - dropping spend log row Postgres rejected. request_id=%s error=%s", + request_id, + str(e), + exc=e, + ) + return attempts_left - 1 + mid = len(rows) // 2 + remaining = await _create_spend_logs_with_poison_isolation(repo, rows[:mid], attempts_left - 1) + return await _create_spend_logs_with_poison_isolation(repo, rows[mid:], remaining) + + def _raise_failed_update_spend_exception(e: Exception, start_time: float, proxy_logging_obj: ProxyLogging): """ Raise an exception for failed update spend logs diff --git a/tests/test_litellm/proxy/db/test_exception_handler.py b/tests/test_litellm/proxy/db/test_exception_handler.py index 6021c221426..0634a01326c 100644 --- a/tests/test_litellm/proxy/db/test_exception_handler.py +++ b/tests/test_litellm/proxy/db/test_exception_handler.py @@ -148,6 +148,37 @@ def test_is_database_service_unavailable_error_prisma_p1001_masquerades_as_datae ) +def test_is_prisma_data_error_only_true_for_dataerror(): + """The spend-log poison-row isolation gates on this: only a prisma + ``DataError`` (the DB refused the data, e.g. a NUL byte) may be bisected + into a per-row drop. A connectivity failure or any non-prisma exception + must not be treated as a data rejection, so the whole batch surfaces.""" + import httpx + + data_error = DataError(data={"user_facing_error": {"message": "invalid byte sequence for encoding UTF8: 0x00"}}) + assert PrismaDBExceptionHandler.is_prisma_data_error(data_error) is True + + for non_data in ( + httpx.ConnectError("conn refused"), + PrismaError("can't reach database server"), + UniqueViolationError(data={"user_facing_error": {"meta": {"table": "t"}}}), + RuntimeError("boom"), + ): + assert PrismaDBExceptionHandler.is_prisma_data_error(non_data) is False + + +def test_is_prisma_data_error_true_for_connection_masquerade_dataerror(): + """The P1001 outage prisma mislabels as a ``DataError`` is still a + ``DataError`` by type, so this returns True; the spend-log helper relies on + ``is_database_service_unavailable_error`` (not this check) to keep that + outage on the retry path instead of dropping rows.""" + p1001_as_dataerror = DataError( + data={"user_facing_error": {"message": "Can't reach database server at `127.0.0.1`:`5499`"}} + ) + assert PrismaDBExceptionHandler.is_prisma_data_error(p1001_as_dataerror) is True + assert PrismaDBExceptionHandler.is_database_service_unavailable_error(p1001_as_dataerror) is True + + def test_is_database_service_unavailable_error_cached_plan_escapes_as_503(): """Composes with the cached-plan retry: when that recovery fails and the Postgres "cached plan must not change result type" error escapes (raised by diff --git a/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py b/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py index 6a4fd516c9b..d5d4de7f2cf 100644 --- a/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py +++ b/tests/test_litellm/proxy/utils/prisma_and_spend/test_proxy_update_spend.py @@ -231,6 +231,112 @@ async def test_update_spend_logs_failure_raises_after_retries( ) +def _data_error(message: str) -> Any: + from prisma.errors import DataError + + return DataError({"user_facing_error": {"message": message}}) + + +@pytest.mark.asyncio +async def test_update_spend_logs_isolates_poison_row_and_persists_good_rows( + mock_prisma_client: Any, make_spend_log_row: Any +) -> None: + """One row Postgres rejects (22P05) must not drop the whole batch. + + The good rows still persist and only the offending row is dropped, with no + exception bubbling up. On the unfixed single-shot ``create_many`` the first + write raises and the entire batch is lost. + """ + poison_id = "r1" + written: List[str] = [] + + async def _create_many(*, data: Any, skip_duplicates: bool) -> None: + ids = [row["request_id"] for row in data] + if poison_id in ids: + raise _data_error( + "Inconsistent column data: 22P05 invalid byte sequence for encoding UTF8: 0x00" + ) + written.extend(ids) + + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock(side_effect=_create_many) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + + logs = [make_spend_log_row(request_id=f"r{i}") for i in range(4)] + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=logs, + ) + assert sorted(written) == ["r0", "r2", "r3"] + + +@pytest.mark.asyncio +async def test_update_spend_logs_reraises_connection_masquerade_dataerror( + mock_prisma_client: Any, make_spend_log_row: Any +) -> None: + """A P1001 "can't reach database server" outage that prisma mislabels as a + ``DataError`` is transient, not a poison row: it must propagate so the batch + is surfaced/retried rather than bisected into silent per-row drops. + """ + err = _data_error("Can't reach database server at db-host:5432") + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock(side_effect=err) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + + with pytest.raises(type(err)): + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=[ + make_spend_log_row(request_id="a"), + make_spend_log_row(request_id="b"), + ], + ) + + +@pytest.mark.asyncio +async def test_update_spend_logs_caps_isolation_attempts_under_poison_flood( + mock_prisma_client: Any, make_spend_log_row: Any +) -> None: + """A flood of poisoned rows must not amplify one failed bulk insert into + unbounded failed inserts. The per-batch attempt budget hard-caps the number + of ``create_many`` calls regardless of how many rows are poisoned, so the DB + work stays bounded and well below the input row count, and the helper still + completes without raising. + """ + import litellm.proxy.utils as utils_mod + + attempt_cap = utils_mod.MAX_SPEND_LOG_ISOLATION_ATTEMPTS_PER_BATCH + # single create_many batch (< BATCH_SIZE) whose row count exceeds the attempt + # cap, so the bound bites and attempts stay below the input row count + n_rows = attempt_cap * 3 + + async def _always_poison(*, data: Any, skip_duplicates: bool) -> None: + raise _data_error("invalid byte sequence for encoding UTF8: 0x00") + + mock_prisma_client.db.litellm_spendlogs.create_many = AsyncMock(side_effect=_always_poison) + proxy_logging = MagicMock() + proxy_logging.failure_handler = AsyncMock() + logs = [make_spend_log_row(request_id=f"r{i}") for i in range(n_rows)] + + await ProxyUpdateSpend.update_spend_logs( + n_retry_times=0, + prisma_client=mock_prisma_client, + db_writer_client=None, + proxy_logging_obj=proxy_logging, + logs_to_process=logs, + ) + + attempts = mock_prisma_client.db.litellm_spendlogs.create_many.await_count + assert attempts <= attempt_cap + assert attempts < n_rows + + def test_disable_spend_updates_reflects_general_settings( monkeypatch: pytest.MonkeyPatch, ) -> None: From be4d0d8439ad6bea5b7a310824c74f2df0c73884 Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 22:25:15 +0300 Subject: [PATCH 31/79] fix(redis): re-establish async cluster connections after a node restart (#31577) When redis_startup_nodes is set the async cluster client was built with no health check and no TCP keepalive, so a connection silently dropped by a cluster restart (e.g. ElastiCache Serverless maintenance) stayed in the pool and got reused while dead; the first command after the restart stalled in re-initialization until the LoggingWorker timeout cancelled it, surfacing as CancelledError then TimeoutError on the spend-counter path Build the async cluster client with a 25s health_check_interval and socket_keepalive so an idle connection is PING-validated and reconnected before reuse, and expose both through the cluster kwarg allow-list so an explicit value from config still wins Resolves LIT-4083 --- litellm/_redis.py | 15 +++++++++++- litellm/constants.py | 4 ++++ tests/test_litellm/test_redis.py | 41 ++++++++++++++++++++++++++++++++ 3 files changed, 59 insertions(+), 1 deletion(-) diff --git a/litellm/_redis.py b/litellm/_redis.py index 2bcce0e1083..bb3a0974241 100644 --- a/litellm/_redis.py +++ b/litellm/_redis.py @@ -23,7 +23,11 @@ from litellm._redis_credential_provider import ( GCPIAMCredentialProvider, _generate_gcp_iam_access_token, ) -from litellm.constants import REDIS_CONNECTION_POOL_TIMEOUT, REDIS_SOCKET_TIMEOUT +from litellm.constants import ( + REDIS_CLUSTER_HEALTH_CHECK_INTERVAL, + REDIS_CONNECTION_POOL_TIMEOUT, + REDIS_SOCKET_TIMEOUT, +) from litellm.litellm_core_utils.sensitive_data_masker import SensitiveDataMasker from ._logging import verbose_logger @@ -102,6 +106,8 @@ def _get_redis_cluster_kwargs(client=None): "max_connections", "socket_timeout", "socket_connect_timeout", + "health_check_interval", + "socket_keepalive", } return available_args @@ -579,6 +585,13 @@ def get_redis_async_client( new_startup_nodes.append(ClusterNode(**item)) cluster_kwargs.pop("startup_nodes", None) + # Default to a periodic health check + TCP keepalive so a connection silently dropped + # by a cluster restart (e.g. ElastiCache Serverless maintenance) is revalidated and + # reconnected before reuse instead of stalling in re-initialization; an explicit value + # from config still wins. + cluster_kwargs.setdefault("health_check_interval", REDIS_CLUSTER_HEALTH_CHECK_INTERVAL) + cluster_kwargs.setdefault("socket_keepalive", True) + # Create async RedisCluster with IAM token as password if available cluster_client = async_redis.RedisCluster( startup_nodes=new_startup_nodes, diff --git a/litellm/constants.py b/litellm/constants.py index aeb74a65839..f6add8da3ea 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -332,6 +332,10 @@ REDIS_CONNECTION_POOL_TIMEOUT = int(os.getenv("REDIS_CONNECTION_POOL_TIMEOUT", 5 REDIS_CIRCUIT_BREAKER_FAILURE_THRESHOLD = int(os.getenv("REDIS_CIRCUIT_BREAKER_FAILURE_THRESHOLD", 5)) REDIS_CIRCUIT_BREAKER_RECOVERY_TIMEOUT = int(os.getenv("REDIS_CIRCUIT_BREAKER_RECOVERY_TIMEOUT", 60)) REDIS_CIRCUIT_BREAKER_ENABLED = os.getenv("REDIS_CIRCUIT_BREAKER_ENABLED", "true").lower() == "true" +# Seconds of idle before a Redis cluster connection is validated with a PING and +# reconnected if dead, so a connection silently dropped by a cluster restart +# (e.g. ElastiCache Serverless maintenance) is not reused while broken +REDIS_CLUSTER_HEALTH_CHECK_INTERVAL = 25 # Default Redis major version to assume when version cannot be determined # Using 7 as it's the modern version that supports LPOP with count parameter DEFAULT_REDIS_MAJOR_VERSION = int(os.getenv("DEFAULT_REDIS_MAJOR_VERSION", 7)) diff --git a/tests/test_litellm/test_redis.py b/tests/test_litellm/test_redis.py index a89e30a0e06..0081e1c819f 100644 --- a/tests/test_litellm/test_redis.py +++ b/tests/test_litellm/test_redis.py @@ -12,6 +12,7 @@ from litellm._redis import ( get_redis_connection_pool, get_redis_url_from_environment, ) +from litellm.constants import REDIS_CLUSTER_HEALTH_CHECK_INTERVAL from litellm._redis_credential_provider import ( GCPIAMCredentialProvider, _token_cache, @@ -171,6 +172,46 @@ def test_socket_timeouts_in_cluster_kwargs(): assert "socket_connect_timeout" in kwargs +def test_reconnect_kwargs_in_cluster_kwargs(): + """Health check and keepalive must survive the cluster kwarg allow-list so + operators can tune Redis cluster reconnection behavior via config.""" + kwargs = _get_redis_cluster_kwargs() + assert "health_check_interval" in kwargs + assert "socket_keepalive" in kwargs + + +@patch("litellm._redis.async_redis.RedisCluster") +def test_async_cluster_sets_reconnect_defaults(mock_cluster_cls): + """ + The async RedisCluster client must be built with a periodic health check and + TCP keepalive so a connection silently dropped by a cluster restart (e.g. + ElastiCache Serverless maintenance) is revalidated and reconnected before + reuse instead of stalling in re-initialization. Regression for LIT-4083. + """ + get_redis_async_client(startup_nodes=[{"host": "cluster-node", "port": 6379}]) + + mock_cluster_cls.assert_called_once() + call_kwargs = mock_cluster_cls.call_args[1] + assert call_kwargs["health_check_interval"] == REDIS_CLUSTER_HEALTH_CHECK_INTERVAL + assert call_kwargs["health_check_interval"] > 0 + assert call_kwargs["socket_keepalive"] is True + + +@patch("litellm._redis.async_redis.RedisCluster") +def test_async_cluster_reconnect_defaults_are_overridable(mock_cluster_cls): + """An explicit health_check_interval / socket_keepalive from config must win + over the built-in reconnect defaults.""" + get_redis_async_client( + startup_nodes=[{"host": "cluster-node", "port": 6379}], + health_check_interval=7, + socket_keepalive=False, + ) + + call_kwargs = mock_cluster_cls.call_args[1] + assert call_kwargs["health_check_interval"] == 7 + assert call_kwargs["socket_keepalive"] is False + + def test_get_redis_async_client_with_connection_pool(): """Test that connection_pool parameter is properly passed to Redis client""" # Create a mock connection pool From 4f41a9e140ebcf12ec56bfc8d24b4dd5ba78ed4f Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 12:49:46 -0700 Subject: [PATCH 32/79] test(ui): drop the e2e typecheck CI gate, keep the typed import for the editor The e2e runs against the real proxy, so a contract drift already fails the test at runtime; tsc only checks the spec against schema.d.ts, a generated snapshot, so a backend change with a stale snapshot would pass tsc while the live test still catches it. The dedicated tsconfig + script + CI step were circular ceremony for that. Keep the zero-runtime-cost type-only import, which still catches mistakes in the editor, and make its comment honest about what enforces the contract. --- .circleci/config.yml | 8 -------- .../e2e_tests/tests/settings/routerSettings.spec.ts | 7 +++---- ui/litellm-dashboard/e2e_tests/tsconfig.json | 9 --------- ui/litellm-dashboard/package.json | 1 - 4 files changed, 3 insertions(+), 22 deletions(-) delete mode 100644 ui/litellm-dashboard/e2e_tests/tsconfig.json diff --git a/.circleci/config.yml b/.circleci/config.yml index 009884cbfe4..f13e9bf66f1 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -2687,14 +2687,6 @@ jobs: paths: - ui/litellm-dashboard/node_modules - ~/.cache/ms-playwright - - run: - name: Type-check E2E specs - # The specs type their request/response round-trips against the generated - # OpenAPI schema; this step turns that typing into a real gate, so a backend - # contract drift fails here instead of silently passing at runtime. - command: | - cd ui/litellm-dashboard - npm run typecheck:e2e - run: name: Build UI from source # Prior version used `cp -r out/ ../../litellm/proxy/_experimental/out/`. diff --git a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts index 64dab6d7cf6..3e140b9ab56 100644 --- a/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts +++ b/ui/litellm-dashboard/e2e_tests/tests/settings/routerSettings.spec.ts @@ -3,10 +3,9 @@ import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; import { Role, users } from "../../fixtures/users"; -// Type-only import of the OpenAPI-generated backend schema. esbuild erases it at -// runtime; the round-trip below is enforced by the `typecheck:e2e` CI step (tsc over -// e2e_tests), so a drift in the /config/update or /router/settings contract fails the -// build rather than silently passing here. +// Type-only import of the OpenAPI-generated backend schema, erased at runtime by +// esbuild. It types the round-trips below so mistakes surface in the editor; the live +// test against the real proxy is what actually enforces the contract. import type { components } from "../../../src/lib/http/schema"; // These tests mutate the proxy's shared router_settings, and the Loadbalancing save diff --git a/ui/litellm-dashboard/e2e_tests/tsconfig.json b/ui/litellm-dashboard/e2e_tests/tsconfig.json deleted file mode 100644 index abda3fdb8b6..00000000000 --- a/ui/litellm-dashboard/e2e_tests/tsconfig.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "extends": "../tsconfig.json", - "compilerOptions": { - "noEmit": true, - "types": ["node"] - }, - "include": ["**/*.ts"], - "exclude": ["node_modules"] -} diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index 1d2b505a172..a8948f4be34 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -19,7 +19,6 @@ "e2e:ui": "playwright test --ui --config e2e_tests/playwright.config.ts", "e2e:migration": "playwright test e2e_tests/tests/migration/migratedPages.spec.ts --config e2e_tests/playwright.config.ts", "e2e:migration:root": "playwright test --config e2e_tests/migration.serverRootPath.config.ts", - "typecheck:e2e": "tsc -p e2e_tests/tsconfig.json --noEmit", "knip": "knip", "knip:fix": "knip --fix", "gen:api": "node scripts/gen-api-types.mjs" From d4c33b2b5922cdc780c7dac31c73a2a21f342540 Mon Sep 17 00:00:00 2001 From: mubashir1osmani Date: Tue, 30 Jun 2026 12:54:47 -0700 Subject: [PATCH 33/79] fix(logging): route realtime success logging through the bounded worker (#31733) RealTimeStreaming.log_messages dispatched the success handler with a bare asyncio.create_task, bypassing GLOBAL_LOGGING_WORKER (which gives a per-coroutine timeout and a concurrency cap). On a long-lived realtime websocket a slow logging callback left one suspended task per logged turn, each pinning that turn's assembled response, accumulating without bound (~12-15k in-flight under load in a repro) until OOM. Route realtime success logging through the bounded worker so in-flight logging is capped and a hung callback is cancelled at the worker timeout. The chat and responses streaming success-logging paths are intentionally left unchanged: their success callbacks must complete within the call's event-loop run (the non-streaming path pairs the worker with a synchronous callback; the streaming path has no such companion), so deferring them through the worker would drop logs for one-shot SDK calls and breaks test_async_custom_handler_stream. Bounding those paths needs a load-shedding approach and is left to a follow-up. --- .../litellm_core_utils/realtime_streaming.py | 7 ++++-- .../test_realtime_streaming.py | 23 +++++++++++++++++++ 2 files changed, 28 insertions(+), 2 deletions(-) diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index bd6406c6241..a1a070eb5b7 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -5,6 +5,7 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional, Protocol, Union, ca import litellm from litellm._logging import verbose_logger +from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig from litellm.types.llms.openai import ( OpenAIRealtimeEvents, @@ -315,8 +316,10 @@ class RealTimeStreaming: self.logging_obj.model_call_details["realtime_tools"] = self.session_tools self.logging_obj.model_call_details["realtime_tool_calls"] = self.tool_calls ## ASYNC LOGGING - # Create an event loop for the new thread - asyncio.create_task(self.logging_obj.async_success_handler(self.messages)) + # Route through the bounded logging worker (per-coroutine timeout + + # concurrency cap) instead of a bare create_task, so a slow callback + # can't leave suspended tasks pinning each call's response in memory. + GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(self.logging_obj.async_success_handler(self.messages)) ## SYNC LOGGING executor.submit(self.logging_obj.success_handler(self.messages)) diff --git a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py index 2ad9b919a1f..766befd1a99 100644 --- a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py +++ b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py @@ -2945,3 +2945,26 @@ def test_non_bidi_setup_left_untouched_for_followup_capable_providers(): assert streaming._maybe_inject_guardrail_auto_response_disable(msg) == msg finally: litellm.callbacks = [] + + +@pytest.mark.asyncio +async def test_log_messages_routes_async_logging_through_bounded_worker(): + """Realtime success logging must go through GLOBAL_LOGGING_WORKER (bounded + queue + per-coroutine timeout), not a bare asyncio.create_task. A bare task + has no timeout/concurrency cap, so when a logging callback is slow every + realtime turn leaves a suspended task pinning its response in memory -> an + unbounded leak. Regression for that fix.""" + logging_obj = MagicMock() + streaming = RealTimeStreaming(MagicMock(), MagicMock(), logging_obj) + streaming.messages = [{"type": "session.created"}] + + with ( + patch("litellm.litellm_core_utils.realtime_streaming.GLOBAL_LOGGING_WORKER") as mock_worker, + patch("litellm.litellm_core_utils.realtime_streaming.asyncio.create_task") as mock_create_task, + patch("litellm.litellm_core_utils.realtime_streaming.executor.submit"), + ): + await streaming.log_messages() + + mock_worker.ensure_initialized_and_enqueue.assert_called_once() + # the bare create_task path must no longer be used for success logging + mock_create_task.assert_not_called() From 94936a3922aeb8aa9a4d5928e63ea6f15be6f098 Mon Sep 17 00:00:00 2001 From: Yassin Kortam Date: Tue, 30 Jun 2026 22:59:18 +0300 Subject: [PATCH 34/79] fix(presidio): stream SSE output incrementally instead of buffering the whole response (#31503) The Presidio streaming post-call hooks (_stream_apply_output_masking for apply_to_output and _stream_pii_unmasking for output_parse_pii) collected every upstream chunk, reassembled the full completion with stream_chunk_builder at end-of-stream, ran Presidio over it, then emitted one reconstructed SSE chunk. Time-to-first-token collapsed to the total generation time and token-by-token streaming was lost whenever Presidio output handling was enabled. With the default presidio_filter_scope both, an apply_to_output masking instance is always created, so even the unmask configuration buffered the stream. Both paths now transform and forward chunks as they arrive. The unmask path replaces placeholder tokens per chunk, holding back only the trailing run that could still grow into a token so a placeholder split across SSE chunks () is still rewritten atomically. The mask path emits a prefix only when masking it in isolation matches the corresponding prefix of masking the whole buffer, with a lookahead margin still buffered past the cut, so an entity straddling the cut is detected and held until complete; past _PRESIDIO_STREAM_MAX_BUFFER the run is bounded without splitting an entity. Tool-call and legacy function-call argument fragments are accumulated per choice and transformed once the choice closes, content is buffered independently per choice index for correct n>1 streaming, raw Anthropic SSE bytes and /v1/responses events pass through with any held content flushed first so events never reorder, and a masking error redacts only the affected chunk (fail closed, keeping finish_reason) while the stream continues. Resolves LIT-3222 --- .../guardrails/guardrail_hooks/presidio.py | 529 +++++++++---- .../guardrail_hooks/test_presidio.py | 712 +++++++++++++++++- 2 files changed, 1086 insertions(+), 155 deletions(-) diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py index 95876a55eab..e60b6233038 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py +++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py @@ -17,6 +17,8 @@ from typing import ( TYPE_CHECKING, Any, AsyncGenerator, + Awaitable, + Callable, Dict, List, Literal, @@ -54,7 +56,14 @@ from litellm.types.proxy.guardrails.guardrail_hooks.presidio import ( PresidioAnalyzeRequest, PresidioAnalyzeResponseItem, ) -from litellm.types.utils import GuardrailStatus, StreamingChoices +from litellm.types.utils import ( + ChatCompletionDeltaToolCall, + Delta, + Function, + FunctionCall, + GuardrailStatus, + StreamingChoices, +) from litellm.utils import ( EmbeddingResponse, ImageResponse, @@ -62,6 +71,17 @@ from litellm.utils import ( ModelResponseStream, ) +# Trailing context (chars) the streaming output-masking path keeps buffered past +# a sentence boundary before emitting, so a PII entity that straddles the +# boundary is seen in full by Presidio and is never split across two analyze +# calls. It bounds the largest single entity the incremental path can mask +# without leaking; an entity longer than this could still be split. +_PRESIDIO_STREAM_MARGIN = 96 +# Hard cap on buffered un-emitted output. Past this with no sentence boundary, +# stable prefixes are flushed; if stability cannot be proven, the ambiguous +# prefix is dropped while retaining the trailing margin. +_PRESIDIO_STREAM_MAX_BUFFER = 2000 + class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): user_api_key_cache = None @@ -93,6 +113,10 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): self.mock_redacted_text = mock_redacted_text self.output_parse_pii = output_parse_pii or False self.apply_to_output = apply_to_output + # Streaming output-masking safety window; instance attributes so tests can + # exercise incremental flushing with short content (see _mask_emit_decision). + self._stream_mask_margin = _PRESIDIO_STREAM_MARGIN + self._stream_mask_max_buffer = _PRESIDIO_STREAM_MAX_BUFFER # When output_parse_pii or apply_to_output is enabled, the guardrail must # also run on post_call to unmask/mask the response. Expand the event_hook @@ -1048,81 +1072,353 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): ) return response + @staticmethod + def _unmask_hold_len(text: str, token_keys: Any) -> int: + """Length of the trailing run of ``text`` that could still grow into a + PII placeholder token, so the unmask path holds it until the next chunk + completes (or aborts) the token instead of emitting a half-written + ````.""" + keys = tuple(token_keys) + if not text or not keys: + return 0 + longest = max(len(key) for key in keys) + for start in range(max(0, len(text) - (longest - 1)), len(text)): + suffix = text[start:] + if any(key.startswith(suffix) for key in keys if len(suffix) < len(key)): + return len(text) - start + return 0 + + @staticmethod + def _mask_boundaries(text: str) -> tuple[int, ...]: + """Candidate flush points: a newline, or a sentence terminator already + followed by whitespace. A terminator at the very end of the buffer is + excluded because the next chunk may continue the token (``jane.`` + + ``doe@example.com``); it becomes a boundary once the whitespace arrives. + A boundary is only a *candidate* here; ``_mask_emit_decision`` still + confirms via a stability check that no entity straddles it.""" + return tuple( + i + 1 + for i in range(len(text)) + if text[i] == "\n" or (text[i] in ".!?" and i + 1 < len(text) and text[i + 1].isspace()) + ) + + async def _mask_emit_decision( + self, + buffer: str, + terminal: bool, + transform: "Callable[[str], Awaitable[str]]", + ) -> "tuple[str, str]": + """Decide how much of ``buffer`` is safe to mask and emit now, returning + ``(masked_emit, hold_raw)``. + + A sentence boundary is not trusted blindly (it can fall inside a name + with an initial or an address spanning a newline). Instead a prefix is + emitted only when masking it in isolation matches the corresponding + prefix of masking the whole buffer, with at least ``_PRESIDIO_STREAM_MARGIN`` + characters of lookahead still buffered past the cut. That guarantees any + entity overlapping the cut is present in full when the buffer is analyzed, + so a straddling entity makes the prefixes differ and the cut is held. + Past ``_PRESIDIO_STREAM_MAX_BUFFER`` with no sentence boundary the buffer + first tries stable forced cuts and then drops the ambiguous prefix while + retaining the trailing margin, so a failed stability check cannot grow + the held buffer without bound.""" + if terminal: + return (await transform(buffer) if buffer else ""), "" + margin = self._stream_mask_margin + forced_cut = ( + len(buffer) - margin if len(buffer) > self._stream_mask_max_buffer and len(buffer) > margin else None + ) + cuts = [index for index in self._mask_boundaries(buffer) if len(buffer) - index >= margin] + if forced_cut is not None: + verbose_proxy_logger.warning( + "Presidio apply_to_output: buffered %d streamed chars with no " + "sentence boundary; bounding held stream state.", + len(buffer), + ) + cuts.append(forced_cut) + cuts.extend(index for index in range(forced_cut, len(buffer)) if buffer[index].isspace()) + if cuts: + masked_full = await transform(buffer) + for index in sorted(set(cuts), reverse=True): + masked_prefix = await transform(buffer[:index]) + if masked_full.startswith(masked_prefix): + return masked_prefix, buffer[index:] + if forced_cut is not None: + return "", buffer[forced_cut:] + return "", buffer + + @staticmethod + def _accumulate_tool_calls( + tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], + choice_index: int, + tool_calls: list[Any], + ) -> None: + choice_acc = tool_acc.setdefault(choice_index, {}) # mutable-ok: streaming tool-call accumulator + for tool_call in tool_calls: + entry = choice_acc.setdefault( # mutable-ok: streaming tool-call accumulator + getattr(tool_call, "index", 0) or 0, + {"id": None, "type": None, "name": None, "args": ""}, + ) + if getattr(tool_call, "id", None): + entry["id"] = tool_call.id + if getattr(tool_call, "type", None): + entry["type"] = tool_call.type + function = getattr(tool_call, "function", None) + if function is not None: + if getattr(function, "name", None): + entry["name"] = function.name + arguments = getattr(function, "arguments", None) + if isinstance(arguments, str): + entry["args"] = (entry["args"] or "") + arguments + + @staticmethod + def _accumulate_function_call( + func_acc: dict[int, dict[str, Optional[str]]], + choice_index: int, + function_call: Any, + ) -> None: + entry = func_acc.setdefault( # mutable-ok: streaming function-call accumulator + choice_index, {"name": None, "args": ""} + ) + if getattr(function_call, "name", None): + entry["name"] = function_call.name + arguments = getattr(function_call, "arguments", None) + if isinstance(arguments, str): + entry["args"] = (entry["args"] or "") + arguments + + @staticmethod + async def _build_tool_calls( + choice_acc: dict[int, dict[str, Optional[str]]], + transform: "Callable[[str], Awaitable[str]]", + ) -> list[ChatCompletionDeltaToolCall]: + return [ + ChatCompletionDeltaToolCall( + index=tool_index, + id=entry["id"], + type=entry["type"], + function=Function( + name=entry["name"], + arguments=(await transform(entry["args"]) if entry["args"] else ""), + ), + ) + for tool_index, entry in sorted(choice_acc.items()) + ] + + @staticmethod + async def _build_function_call( + entry: Optional[dict[str, Optional[str]]], + transform: "Callable[[str], Awaitable[str]]", + ) -> Optional[FunctionCall]: + if entry is None: + return None + return FunctionCall( + name=entry["name"], + arguments=await transform(entry["args"]) if entry["args"] else "", + ) + + async def _rewrite_chat_chunk( + self, + chunk: ModelResponseStream, + content_buffers: dict[int, str], + tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], + func_acc: dict[int, dict[str, Optional[str]]], + transform: "Callable[[str], Awaitable[str]]", + emit_content: "Callable[[str, bool], Awaitable[tuple[str, str]]]", + ) -> None: + """Transform one streaming chat chunk in place: text content is masked / + unmasked and emitted as soon as ``emit_content`` deems a prefix safe (it + returns the already-transformed text to emit plus the raw remainder to + hold), while tool-call and function-call argument fragments are + accumulated and emitted, fully transformed, on the chunk that closes the + choice.""" + for choice in chunk.choices: + index = getattr(choice, "index", 0) + delta = getattr(choice, "delta", None) + if delta is None: + continue + terminal = bool(getattr(choice, "finish_reason", None)) + + tool_calls = getattr(delta, "tool_calls", None) + if tool_calls: + self._accumulate_tool_calls(tool_acc, index, tool_calls) + delta.tool_calls = None + function_call = getattr(delta, "function_call", None) + if function_call is not None: + self._accumulate_function_call(func_acc, index, function_call) + delta.function_call = None + + raw_content = getattr(delta, "content", None) + content = raw_content if isinstance(raw_content, str) else None + if content is not None or terminal: + emitted, hold = await emit_content(content_buffers.pop(index, "") + (content or ""), terminal) + if hold: + content_buffers[index] = hold + if emitted: + delta.content = emitted + else: + delta.content = None if content is None else "" + + if terminal: + built_tool_calls = await self._build_tool_calls(tool_acc.get(index, {}), transform) + built_function_call = await self._build_function_call(func_acc.get(index), transform) + if built_tool_calls: + delta.tool_calls = built_tool_calls + if built_function_call is not None: + delta.function_call = built_function_call + tool_acc.pop(index, None) + func_acc.pop(index, None) + + @staticmethod + async def _build_tail_chunk( + template: Optional[ModelResponseStream], + content_buffers: dict[int, str], + tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], + func_acc: dict[int, dict[str, Optional[str]]], + transform: "Callable[[str], Awaitable[str]]", + ) -> Optional[ModelResponseStream]: + """Flush any content / tool-call state still held when a stream ends + without a finish-reason chunk to attach it to.""" + if template is None: + return None + cls = _OPTIONAL_PresidioPIIMasking + choices: list[StreamingChoices] = [] + for index in sorted(set(content_buffers) | set(tool_acc) | set(func_acc)): + held = content_buffers.get(index, "") + masked_content = await transform(held) if held else None + built_tool_calls = await cls._build_tool_calls(tool_acc.get(index, {}), transform) + built_function_call = await cls._build_function_call(func_acc.get(index), transform) + if masked_content is None and not built_tool_calls and built_function_call is None: + continue + choices.append( + StreamingChoices( + index=index, + delta=Delta( + content=masked_content, + tool_calls=built_tool_calls or None, + function_call=built_function_call, + ), + ) + ) + if not choices: + return None + return ModelResponseStream( + id=getattr(template, "id", None), + created=getattr(template, "created", None), + model=getattr(template, "model", None), + object="chat.completion.chunk", + choices=choices, + ) + + @staticmethod + def _redacted_chunk(chunk: ModelResponseStream) -> ModelResponseStream: + """Fail closed when masking a chunk raises: rebuild it with empty content + but its original ``finish_reason`` and choice indices preserved, so + possibly-unmasked PII never reaches the client yet a terminal chunk still + carries the completion signal instead of being dropped.""" + return ModelResponseStream( + id=chunk.id, + created=chunk.created, + model=chunk.model, + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=choice.index, + delta=Delta(content=None), + finish_reason=choice.finish_reason, + ) + for choice in chunk.choices + ], + ) + async def _stream_apply_output_masking( self, response: Any, request_data: dict, ) -> AsyncGenerator[Union[ModelResponseStream, bytes], None]: """Apply Presidio masking to streaming output (apply_to_output=True path).""" - from litellm.llms.base_llm.base_model_iterator import ( - convert_model_response_to_streaming, - ) - from litellm.main import stream_chunk_builder - from litellm.types.utils import ModelResponse + presidio_config = self.get_presidio_settings_from_request_data(request_data or {}) - all_chunks: List[ModelResponseStream] = [] - passthrough_due_to_unknown_stream_shape = False - try: - async for chunk in response: - if isinstance(chunk, ModelResponseStream): - if passthrough_due_to_unknown_stream_shape: - yield chunk - else: - all_chunks.append(chunk) - elif isinstance(chunk, bytes): - yield chunk # type: ignore[misc] - continue - else: - if all_chunks: - # Flush buffered chunks and switch to transparent passthrough for this stream shape. - # NOTE: these buffered chunks are emitted unmasked because this - # stream mixed chunk types and cannot be safely reconstructed. - verbose_proxy_logger.warning( - "Presidio apply_to_output: mixed stream detected (ModelResponseStream + unknown event). " - "Flushing %d buffered chunks without PII masking and switching to transparent passthrough.", - len(all_chunks), - ) - for buffered_chunk in all_chunks: - yield buffered_chunk - all_chunks = [] - passthrough_due_to_unknown_stream_shape = True - yield chunk - if passthrough_due_to_unknown_stream_shape: - verbose_proxy_logger.warning( - "Presidio apply_to_output: streaming response contained unknown event objects " - "(e.g. /v1/responses events). Output PII masking was skipped for this response." - ) - return - if not all_chunks: - verbose_proxy_logger.warning( - "Presidio apply_to_output: streaming response contained no " - "ModelResponseStream chunks (e.g. raw SSE bytes or an empty " - "upstream stream). Output PII masking was skipped for this " - "response." - ) - return - - assembled_model_response = stream_chunk_builder(chunks=all_chunks, messages=request_data.get("messages")) - - if not isinstance(assembled_model_response, ModelResponse): - for chunk in all_chunks: - yield chunk - return - - await self._process_response_for_pii( - response=assembled_model_response, + async def transform(text: str) -> str: + return await self.check_pii( + text=text, + output_parse_pii=False, + presidio_config=presidio_config, request_data=request_data, - mode="mask", ) - mock_response_stream = convert_model_response_to_streaming(assembled_model_response) - yield mock_response_stream + async def emit_content(text: str, terminal: bool) -> tuple[str, str]: + return await self._mask_emit_decision(text, terminal, transform) - except Exception as e: - verbose_proxy_logger.error(f"Error masking streaming PII output: {str(e)}") - for chunk in all_chunks: + async def flush_held() -> Optional[ModelResponseStream]: + """Build the held-content tail, failing closed (drop held content) + on a masking error instead of letting it abort the whole stream.""" + try: + return await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) + except Exception as e: + if self._is_guardrail_intervention(e): + raise + verbose_proxy_logger.error(f"Error masking streaming PII tail: {str(e)}") + return None + + content_buffers: dict[int, str] = {} + tool_acc: dict[int, dict[int, dict[str, Optional[str]]]] = {} + func_acc: dict[int, dict[str, Optional[str]]] = {} + last_chunk: Optional[ModelResponseStream] = None + masked_any_content = False + saw_unmaskable_shape = False + try: + async for chunk in response: + if not isinstance(chunk, ModelResponseStream): + # Flush buffered masked content before forwarding a non-chat + # shape (raw bytes / a /v1/responses event) so the client + # never sees a later event ahead of earlier masked text. + tail = await flush_held() + if tail is not None: + yield tail + content_buffers.clear() + tool_acc.clear() + func_acc.clear() + saw_unmaskable_shape = True + yield chunk + continue + masked_any_content = True + last_chunk = chunk + try: + await self._rewrite_chat_chunk( + chunk, + content_buffers, + tool_acc, + func_acc, + transform, + emit_content, + ) + except Exception as e: + if self._is_guardrail_intervention(e): + raise + # Fail closed: a transient masking error redacts this chunk's + # content (so possibly-unmasked PII never reaches the client) + # but keeps its finish_reason and keeps the stream flowing, + # rather than truncating the response or dropping a terminal + # chunk's completion signal. + verbose_proxy_logger.error(f"Error masking streaming PII chunk: {str(e)}") + yield self._redacted_chunk(chunk) + continue yield chunk + tail = await flush_held() + if tail is not None: + yield tail + if not masked_any_content and saw_unmaskable_shape: + verbose_proxy_logger.warning( + "Presidio apply_to_output: streaming response contained no " + "maskable chat content (e.g. raw SSE bytes or /v1/responses " + "events). Output PII masking was skipped for this response." + ) + except Exception as e: + if self._is_guardrail_intervention(e): + raise + verbose_proxy_logger.error(f"Error masking streaming PII output: {str(e)}") + @staticmethod def _unmask_sse_bytes_chunk(chunk: bytes, pii_tokens: Dict[str, str]) -> bytes: try: @@ -1183,74 +1479,56 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): request_data: dict, ) -> AsyncGenerator[Union[ModelResponseStream, bytes], None]: """Apply PII unmasking to streaming output (output_parse_pii=True path).""" - from litellm.llms.base_llm.base_model_iterator import ( - convert_model_response_to_streaming, - ) - from litellm.main import stream_chunk_builder - from litellm.types.utils import ModelResponse - metadata = (request_data.get("metadata") or {}) if request_data else {} pii_tokens: Dict[str, str] = metadata.get("pii_tokens", {}) - remaining_chunks: List[ModelResponseStream] = [] - saw_non_chat_chunk = False + async def transform(text: str) -> str: + return self._unmask_pii_text(text, pii_tokens) + + async def emit_content(text: str, terminal: bool) -> tuple[str, str]: + if terminal: + return (await transform(text) if text else ""), "" + hold = self._unmask_hold_len(text, pii_tokens.keys()) + emit_raw, held = text[: len(text) - hold], text[len(text) - hold :] + return (await transform(emit_raw) if emit_raw else ""), held + + content_buffers: dict[int, str] = {} + tool_acc: dict[int, dict[int, dict[str, Optional[str]]]] = {} + func_acc: dict[int, dict[str, Optional[str]]] = {} + last_chunk: Optional[ModelResponseStream] = None try: async for chunk in response: - if isinstance(chunk, ModelResponseStream): - if saw_non_chat_chunk: - yield chunk - else: - remaining_chunks.append(chunk) - elif isinstance(chunk, bytes): - if pii_tokens: - yield self._unmask_sse_bytes_chunk(chunk, pii_tokens) # type: ignore[misc] - else: - yield chunk # type: ignore[misc] + if isinstance(chunk, bytes): + tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) + if tail is not None: + yield tail + content_buffers.clear() + tool_acc.clear() + func_acc.clear() + yield ( # type: ignore[misc] + self._unmask_sse_bytes_chunk(chunk, pii_tokens) if pii_tokens else chunk + ) continue - else: - # /v1/responses events: unmask response.completed text in-place. - # A mixed stream can't be reassembled, so flush buffered chat - # chunks in order before passthrough instead of dropping them. - if remaining_chunks and not saw_non_chat_chunk: - for buffered_chunk in remaining_chunks: - yield buffered_chunk - remaining_chunks = [] - chunk_type = getattr(chunk, "type", None) - if chunk_type == "response.completed" and pii_tokens: + if not isinstance(chunk, ModelResponseStream): + tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) + if tail is not None: + yield tail + content_buffers.clear() + tool_acc.clear() + func_acc.clear() + if getattr(chunk, "type", None) == "response.completed" and pii_tokens: self._unmask_responses_api_completed_chunk(chunk, pii_tokens) - saw_non_chat_chunk = True yield chunk + continue + last_chunk = chunk + await self._rewrite_chat_chunk(chunk, content_buffers, tool_acc, func_acc, transform, emit_content) + yield chunk - if saw_non_chat_chunk: - return - - if not remaining_chunks: - return - - assembled_model_response = stream_chunk_builder( - chunks=remaining_chunks, messages=request_data.get("messages") - ) - - if not isinstance(assembled_model_response, ModelResponse): - for chunk in remaining_chunks: - yield chunk - return - - self._preserve_usage_from_last_chunk(assembled_model_response, remaining_chunks) - - await self._process_response_for_pii( - response=assembled_model_response, - request_data=request_data, - mode="unmask", - ) - - mock_response_stream = convert_model_response_to_streaming(assembled_model_response) - yield mock_response_stream - + tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) + if tail is not None: + yield tail except Exception as e: verbose_proxy_logger.error(f"Error in PII streaming processing: {str(e)}") - for chunk in remaining_chunks: - yield chunk async def async_post_call_streaming_iterator_hook( # type: ignore[override] self, @@ -1282,17 +1560,6 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): async for chunk in self._stream_pii_unmasking(response, request_data): yield chunk - @staticmethod - def _preserve_usage_from_last_chunk( - assembled_model_response: Any, - chunks: List[Any], - ) -> None: - """Copy usage metadata from the last chunk when stream_chunk_builder misses it.""" - if not getattr(assembled_model_response, "usage", None) and chunks: - last_chunk_usage = getattr(chunks[-1], "usage", None) - if last_chunk_usage: - setattr(assembled_model_response, "usage", last_chunk_usage) - def get_presidio_settings_from_request_data(self, data: dict) -> Optional[PresidioPerRequestConfig]: if "metadata" in data: _metadata = data.get("metadata", None) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py index 253d989f203..ce4d6d4a8b0 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py @@ -19,7 +19,7 @@ from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.guardrails.guardrail_hooks.presidio import ( _OPTIONAL_PresidioPIIMasking, ) -from litellm.exceptions import GuardrailRaisedException +from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException from litellm.types.guardrails import LitellmParams, PiiAction, PiiEntityType from litellm.types.utils import Choices, Message, ModelResponse @@ -2207,11 +2207,12 @@ async def test_apply_to_output_streaming_unknown_events_passthrough(): @pytest.mark.asyncio -async def test_apply_to_output_streaming_mixed_chunks_flushes_and_warns(): +async def test_apply_to_output_streaming_mixed_chunks_preserve_order(): """ - Regression test for mixed stream shape: - a buffered ModelResponseStream chunk followed by unknown responses-style - events should be preserved, and masking skip should be visible via warnings. + Regression test for mixed stream shape: a ModelResponseStream chat chunk + followed by an unknown responses-style event must be forwarded in order. + Incremental masking forwards chat chunks as they arrive, so a responses + event after them does not buffer or drop anything. """ guardrail = _OPTIONAL_PresidioPIIMasking( mock_testing=True, @@ -2238,26 +2239,14 @@ async def test_apply_to_output_streaming_mixed_chunks_flushes_and_warns(): mock_user_api_key = UserAPIKeyAuth(api_key="test-key") received = [] - with patch( - "litellm.proxy.guardrails.guardrail_hooks.presidio.verbose_proxy_logger" - ) as mock_logger: - async for chunk in guardrail.async_post_call_streaming_iterator_hook( - user_api_key_dict=mock_user_api_key, - response=mock_stream(), - request_data={}, - ): - received.append(chunk) + async for chunk in guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=mock_user_api_key, + response=mock_stream(), + request_data={}, + ): + received.append(chunk) - # Preserve original ordering across mixed stream types. - assert received == [model_chunk, response_completed] - - # Two warnings are expected: - # 1) mixed stream detected + unmasked flush - # 2) passthrough mode skipped output masking - assert mock_logger.warning.call_count == 2 - warning_messages = [call.args[0] for call in mock_logger.warning.call_args_list] - assert any("mixed stream detected" in msg for msg in warning_messages) - assert any("unknown event objects" in msg for msg in warning_messages) + assert received == [model_chunk, response_completed] # --------------------------------------------------------------------------- @@ -2849,3 +2838,678 @@ async def test_stream_pii_unmasking_passthrough_when_no_tokens(mock_user_api_key chunks.append(chunk) assert chunks == [raw_chunk] + + +# --------------------------------------------------------------------------- +# LIT-3222: incremental SSE streaming for Presidio output masking / unmasking +# --------------------------------------------------------------------------- + +from litellm.types.utils import ( + ChatCompletionDeltaToolCall, + Delta, + Function, + StreamingChoices, +) + + +def _content_chunk(text, index=0, finish_reason=None): + return ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=index, delta=Delta(content=text), finish_reason=finish_reason + ) + ], + ) + + +def _non_empty_content(chunks): + out = [] + for chunk in chunks: + for choice in chunk.choices: + piece = getattr(choice.delta, "content", None) + if piece: + out.append(piece) + return out + + +async def _drive(guardrail, stream, request_data): + collected = [] + async for chunk in guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=UserAPIKeyAuth(api_key="test-key"), + response=stream, + request_data=request_data, + ): + collected.append(chunk) + return collected + + +@pytest.mark.asyncio +async def test_unmask_streaming_is_incremental_not_buffered(): + """ + output_parse_pii streaming must forward each content chunk as it arrives + (unmasked), not collapse the whole completion into a single end-of-stream + chunk. The buffering implementation yielded exactly one content chunk. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) + request_data = {"metadata": {"pii_tokens": {"": "John Smith"}}} + + pieces = ["Hello ", "", " is here."] + + async def stream(): + for i, piece in enumerate(pieces): + yield _content_chunk(piece) + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), request_data) + content = _non_empty_content(collected) + + assert len(content) >= 3, f"expected progressive chunks, got {content}" + assert "".join(content) == "Hello John Smith is here." + assert all("" not in piece for piece in content) + + +@pytest.mark.asyncio +async def test_unmask_streaming_token_split_across_chunks(): + """ + A placeholder token split across SSE chunks (````) must + still be unmasked atomically via the cross-chunk carry buffer. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) + request_data = {"metadata": {"pii_tokens": {"": "John Smith"}}} + + pieces = ["Hi ", "", "!"] + + async def stream(): + for piece in pieces: + yield _content_chunk(piece) + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), request_data) + reassembled = "".join(_non_empty_content(collected)) + + assert reassembled == "Hi John Smith!" + assert "" not in reassembled + + +@pytest.mark.asyncio +async def test_unmask_streaming_independent_per_choice_buffers(): + """ + With n>1 each choice keeps its own carry buffer, so a token split across + chunks on choice 1 does not corrupt choice 0 and vice versa. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) + request_data = { + "metadata": { + "pii_tokens": {"": "John", "": "Jane"} + } + } + + def two_choice_chunk(c0, c1): + return ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices(index=0, delta=Delta(content=c0)), + StreamingChoices(index=1, delta=Delta(content=c1)), + ], + ) + + async def stream(): + yield two_choice_chunk(" ok", "SON_2>!") + yield two_choice_chunk("", "") + + collected = [] + async for chunk in guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=UserAPIKeyAuth(api_key="test-key"), + response=stream(), + request_data=request_data, + ): + collected.append(chunk) + + per_choice = {0: "", 1: ""} + for chunk in collected: + for choice in chunk.choices: + if choice.delta.content: + per_choice[choice.index] += choice.delta.content + + assert per_choice[0] == "John ok" + assert per_choice[1] == "Jane!" + + +@pytest.mark.asyncio +async def test_unmask_streaming_tool_call_arguments_unmasked_at_finish(): + """ + Tool-call argument fragments carrying a placeholder token must be + reassembled and unmasked (the tool would otherwise receive ````). + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) + request_data = { + "metadata": {"pii_tokens": {"": "real@example.com"}} + } + + def tool_chunk(*, id=None, name=None, args, finish_reason=None): + return ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=0, + delta=Delta( + tool_calls=[ + ChatCompletionDeltaToolCall( + index=0, + id=id, + type="function" if id else None, + function=Function(name=name, arguments=args), + ) + ] + ), + finish_reason=finish_reason, + ) + ], + ) + + async def stream(): + yield tool_chunk(id="call_1", name="send_email", args="") + yield tool_chunk(args='{"to": "") + + guardrail.check_pii = mock_check_pii + + pieces = ["My email is ", "secret@example.com. ", "Call me later."] + + async def stream(): + for piece in pieces: + yield _content_chunk(piece) + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + content = _non_empty_content(collected) + + assert len(content) >= 2, f"expected per-sentence chunks, got {content}" + reassembled = "".join(content) + assert reassembled == "My email is . Call me later." + assert "secret@example.com" not in reassembled + + +@pytest.mark.asyncio +async def test_mask_streaming_tool_call_arguments_masked_at_finish(): + """ + Model-generated PII inside streamed tool-call arguments must be masked + before reaching the client, not passed through unmasked. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("secret@example.com", "") + + guardrail.check_pii = mock_check_pii + + def tool_chunk(*, id=None, name=None, args, finish_reason=None): + return ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=0, + delta=Delta( + tool_calls=[ + ChatCompletionDeltaToolCall( + index=0, + id=id, + type="function" if id else None, + function=Function(name=name, arguments=args), + ) + ] + ), + finish_reason=finish_reason, + ) + ], + ) + + async def stream(): + yield tool_chunk(id="call_1", name="save", args='{"email": "sec') + yield tool_chunk(args='ret@example.com"}') + yield ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices(index=0, delta=Delta(), finish_reason="tool_calls") + ], + ) + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + + all_args = [ + tc.function.arguments + for chunk in collected + for choice in chunk.choices + for tc in (getattr(choice.delta, "tool_calls", None) or []) + ] + assert all_args == ['{"email": ""}'] + assert all("secret@example.com" not in args for args in all_args) + + +@pytest.mark.asyncio +async def test_mask_streaming_flushes_buffered_content_before_passthrough_event(): + """ + Regression test (Greptile 4/5 finding): in the apply_to_output path, masked + content held in the buffer (no sentence boundary yet) must be flushed BEFORE + a non-chat passthrough event (e.g. a /v1/responses completion) is forwarded, + so the client never observes stream completion ahead of the final text. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("secret@example.com", "") + + guardrail.check_pii = mock_check_pii + + class FakeResponsesEvent: + def __init__(self, event_type: str): + self.type = event_type + + completed = FakeResponsesEvent("response.completed") + + async def stream(): + # No sentence terminator -> held in the mask buffer, not yet emitted. + yield _content_chunk("My email is secret@example.com") + yield completed + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + + event_index = collected.index(completed) + masked_indexes = [ + i + for i, chunk in enumerate(collected) + if not isinstance(chunk, FakeResponsesEvent) + and any(getattr(c.delta, "content", None) for c in chunk.choices) + ] + assert masked_indexes, "buffered masked content was never emitted" + assert max(masked_indexes) < event_index, "masked content must precede the event" + + masked_text = "".join( + c.delta.content + for chunk in collected + if not isinstance(chunk, FakeResponsesEvent) + for c in chunk.choices + if getattr(c.delta, "content", None) + ) + assert masked_text == "My email is " + assert "secret@example.com" not in masked_text + + +@pytest.mark.asyncio +async def test_mask_streaming_does_not_split_entity_on_long_unpunctuated_run(): + """ + A long punctuation-free run must never force-flush mid-entity. The old + fixed-window fallback emitted at the last whitespace once the buffer grew + past a cap, so a space-bearing entity (SSN, phone) straddling that cut was + analyzed in two halves and leaked unmasked. Content past the last sentence + boundary is now held until a boundary or end-of-stream so each analyze call + sees the whole entity. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("123 45 6789", "") + + guardrail.check_pii = mock_check_pii + + filler = "data " * 90 # >400 chars, spaces only, no .!?\n boundary + async def stream(): + yield _content_chunk(filler + "my ssn is 123 45 6789") + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + reassembled = "".join(_non_empty_content(collected)) + + assert "" in reassembled + assert "123 45 6789" not in reassembled + assert "456789" not in reassembled + + +@pytest.mark.asyncio +async def test_mask_streaming_preserves_stream_on_check_pii_error(): + """ + A transient Presidio failure mid-stream must not truncate the response. The + failing run is dropped (fail closed, never leaking the PII it could not mask) + while content that already flushed safely, later chunks, and the finish chunk + still reach the client. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + guardrail._stream_mask_margin = 4 + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + if "boom@example.com" in text: + raise RuntimeError("presidio down") + return text.replace("ok@example.com", "") + + guardrail.check_pii = mock_check_pii + + pieces = [ + "First ok@example.com. ", + "filler text here. ", + "Second boom@example.com. ", + "Third part here.", + ] + + async def stream(): + for piece in pieces: + yield _content_chunk(piece) + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + reassembled = "".join(_non_empty_content(collected)) + + assert "" in reassembled + assert "boom@example.com" not in reassembled + assert "Third part" in reassembled, "stream truncated after a masking error" + assert any( + getattr(choice, "finish_reason", None) + for chunk in collected + for choice in getattr(chunk, "choices", []) + ), "finish chunk dropped after a masking error" + + +@pytest.mark.asyncio +async def test_mask_streaming_error_preserves_tool_call_accumulators(): + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + if "bad@example.com" in text: + raise RuntimeError("presidio down") + return text.replace("secret@example.com", "") + + guardrail.check_pii = mock_check_pii + + def tool_chunk(*, id=None, name=None, args=None, finish_reason=None): + return ModelResponseStream( + id="chatcmpl-lit3222", + created=1, + model="gpt-4o-mini", + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=1, + delta=( + Delta( + tool_calls=[ + ChatCompletionDeltaToolCall( + index=0, + id=id, + type="function" if id else None, + function=Function(name=name, arguments=args), + ) + ] + ) + if args is not None + else Delta() + ), + finish_reason=finish_reason, + ) + ], + ) + + async def stream(): + yield tool_chunk( + id="call_1", + name="save", + args='{"email": "secret@example.com"}', + ) + yield _content_chunk("bad@example.com", index=0, finish_reason="stop") + yield tool_chunk(finish_reason="tool_calls") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + tool_args = [ + tc.function.arguments + for chunk in collected + for choice in chunk.choices + for tc in (getattr(choice.delta, "tool_calls", None) or []) + ] + + assert tool_args == ['{"email": ""}'] + + +@pytest.mark.asyncio +async def test_mask_emit_decision_caps_buffer_when_stability_fails(): + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + guardrail._stream_mask_margin = 3 + guardrail._stream_mask_max_buffer = 6 + + async def unstable_transform(text): + return text[::-1] + + emitted, held = await guardrail._mask_emit_decision( + "abcdefghij", False, unstable_transform + ) + + assert emitted == "" + assert held == "hij" + + +@pytest.mark.parametrize( + "exception", + [ + BlockedPiiEntityError(entity_type="EMAIL_ADDRESS", guardrail_name="presidio"), + GuardrailRaisedException(guardrail_name="presidio", message="invalid response"), + ], +) +@pytest.mark.asyncio +async def test_mask_streaming_propagates_guardrail_interventions(exception): + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + raise exception + + guardrail.check_pii = mock_check_pii + + async def stream(): + yield _content_chunk("blocked", finish_reason="stop") + + with pytest.raises(type(exception)): + await _drive(guardrail, stream(), {"metadata": {}}) + + +@pytest.mark.asyncio +async def test_mask_streaming_holds_terminator_at_chunk_end_until_whitespace(): + """ + A sentence terminator at the very end of a chunk is not a safe boundary: the + next chunk may continue the token. "Contact jane." followed by + "doe@example.com" must mask the whole email rather than flushing "jane." and + analyzing the two halves separately, which would leak the address. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("jane.doe@example.com", "") + + guardrail.check_pii = mock_check_pii + + async def stream(): + yield _content_chunk("Contact jane.") + yield _content_chunk("doe@example.com") + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + reassembled = "".join(_non_empty_content(collected)) + + assert "" in reassembled + assert "jane.doe@example.com" not in reassembled + assert "jane." not in reassembled + + +@pytest.mark.asyncio +async def test_mask_streaming_does_not_split_entity_across_sentence_boundary(): + """ + An entity that straddles a sentence boundary (a name with a middle initial, + an address across a newline) must not be flushed in halves. The stability + check holds the prefix until masking it alone matches masking the whole + buffer, so the straddling entity is analyzed and masked as one unit instead + of leaking the part before the boundary. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + guardrail._stream_mask_margin = 8 + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("John Q. Public", "") + + guardrail.check_pii = mock_check_pii + + async def stream(): + yield _content_chunk("Please greet John Q. Public warmly when they arrive.") + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + reassembled = "".join(_non_empty_content(collected)) + + assert "" in reassembled + assert "John Q. Public" not in reassembled + assert "John Q." not in reassembled + + +@pytest.mark.asyncio +async def test_mask_streaming_caps_runaway_buffer_without_splitting_entity(): + """ + A punctuation-free run past the buffer cap must be flushed to bound memory, + but the forced flush still cuts a margin back from the end so a PII value + split exactly at the cap (``secret@`` in one chunk, ``example.com`` in the + next) stays buffered and is masked whole instead of leaking its raw halves. + The early flush plus the terminal flush yields more than one content chunk. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + guardrail._stream_mask_margin = 8 + guardrail._stream_mask_max_buffer = 20 + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + return text.replace("secret@example.com", "") + + guardrail.check_pii = mock_check_pii + + async def stream(): + yield _content_chunk("please email me at secret@") # 26 > cap, email cut + yield _content_chunk("example.com now") + yield _content_chunk("", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + content = _non_empty_content(collected) + reassembled = "".join(content) + + assert "" in reassembled + assert "secret@example.com" not in reassembled + assert "secret@" not in reassembled + assert len(content) >= 2, f"cap did not flush before end of stream, got {content}" + + +@pytest.mark.asyncio +async def test_mask_streaming_preserves_finish_reason_when_terminal_chunk_fails(): + """ + When the masking call fails on the terminal chunk itself, that chunk must be + redacted in place (content dropped, fail closed) but keep its finish_reason, + so the client still receives the completion signal instead of a stream that + ends without one. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) + guardrail._stream_mask_margin = 4 + + async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): + if "boom@example.com" in text: + raise RuntimeError("presidio down") + return text + + guardrail.check_pii = mock_check_pii + + async def stream(): + yield _content_chunk("Hello world. ") + yield _content_chunk("more text here. ") + yield _content_chunk("boom@example.com", finish_reason="stop") + + collected = await _drive(guardrail, stream(), {"metadata": {}}) + reassembled = "".join(_non_empty_content(collected)) + + assert "boom@example.com" not in reassembled + assert "Hello world" in reassembled + finish_reasons = [ + choice.finish_reason + for chunk in collected + for choice in getattr(chunk, "choices", []) + if getattr(choice, "finish_reason", None) + ] + assert "stop" in finish_reasons, "finish_reason dropped when terminal chunk failed" + + +@pytest.mark.asyncio +async def test_unmask_streaming_flushes_held_content_before_bytes(): + """ + When a held placeholder prefix is buffered and the next upstream item is a + raw SSE byte chunk, the held chat text must be flushed before the bytes so + the client never sees the byte chunk ahead of earlier content. + """ + guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) + request_data = {"metadata": {"pii_tokens": {"": "Jane"}}} + + async def stream(): + yield _content_chunk("Hi Date: Tue, 30 Jun 2026 13:20:57 -0700 Subject: [PATCH 35/79] =?UTF-8?q?bump:=20version=201.91.0=20=E2=86=92=201.?= =?UTF-8?q?92.0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2ad96c4936b..63afd87f455 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm" -version = "1.91.0" +version = "1.92.0" description = "Library to easily interface with LLM API providers" readme = "README.md" requires-python = ">=3.10, <3.14" @@ -274,7 +274,7 @@ source-exclude = [ profile = "black" [tool.commitizen] -version = "1.91.0" +version = "1.92.0" version_files = [ "pyproject.toml:^version", ] From c736ec52859f650c1b20a6f7772a78a02ce842d5 Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Tue, 30 Jun 2026 13:21:13 -0700 Subject: [PATCH 36/79] =?UTF-8?q?bump:=20version=200.1.44=20=E2=86=92=200.?= =?UTF-8?q?1.45?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- enterprise/pyproject.toml | 4 ++-- pyproject.toml | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index 66f6aeb7abc..f2ad04510a8 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "litellm-enterprise" -version = "0.1.44" +version = "0.1.45" description = "Package for LiteLLM Enterprise features" readme = "README.md" requires-python = ">=3.9" @@ -26,7 +26,7 @@ required-version = ">=0.10.9" module-root = "" [tool.commitizen] -version = "0.1.44" +version = "0.1.45" version_files = [ "pyproject.toml:^version", "../pyproject.toml:litellm-enterprise==", diff --git a/pyproject.toml b/pyproject.toml index 63afd87f455..5165859b1b6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -63,7 +63,7 @@ proxy = [ "azure-storage-blob>=12.28.0,<13.0", "mcp>=1.26.0,<2.0", "litellm-proxy-extras==0.4.74", - "litellm-enterprise==0.1.44", + "litellm-enterprise==0.1.45", "RestrictedPython>=8.1,<9.0", "rich>=13.9.4,<14.0", "polars>=1.38.1,<2.0", From aaa58a72f763b5ce1462418013d14b9b24528d52 Mon Sep 17 00:00:00 2001 From: Yuneng Jiang Date: Tue, 30 Jun 2026 13:21:49 -0700 Subject: [PATCH 37/79] chore: rebuild uv lock for version bumps --- uv.lock | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/uv.lock b/uv.lock index f76be69505f..768a2176d53 100644 --- a/uv.lock +++ b/uv.lock @@ -9,7 +9,7 @@ resolution-markers = [ ] [options] -exclude-newer = "2026-06-23T00:31:52.495979Z" +exclude-newer = "2026-06-27T20:21:25.609736Z" exclude-newer-span = "P3D" [manifest] @@ -3274,7 +3274,7 @@ wheels = [ [[package]] name = "litellm" -version = "1.91.0" +version = "1.92.0" source = { editable = "." } dependencies = [ { name = "aiohttp" }, @@ -3639,7 +3639,7 @@ proxy-dev = [ [[package]] name = "litellm-enterprise" -version = "0.1.44" +version = "0.1.45" source = { editable = "enterprise" } [[package]] From 5d4bb7548fa25a3d240b446e393d64dc788841fb Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Tue, 30 Jun 2026 14:23:09 -0700 Subject: [PATCH 38/79] fix(token_counter): count legacy function_call.arguments (VERIA-492) (#31741) * fix(token_counter): count legacy function_call.arguments (VERIA-492) token_counter handled the modern assistant tool_calls field but had no branch for the legacy OpenAI function_call payload. The value is a dict, so it skipped every special-cased branch in _count_messages and fell through to the unsupported-key continue, letting arbitrary text in function_call.arguments slip past the count. Resolves VERIA-492 * refactor(token_counter): raise on unexpected key in _count_function_call_tokens Address Greptile P2: the helper's fallback branch previously applied function_call logic to any key that wasn't tool_calls. Make the contract explicit so a future caller can't silently miscount. --- litellm/litellm_core_utils/token_counter.py | 43 +++++++++++++----- .../litellm_core_utils/test_token_counter.py | 44 +++++++++++++++++++ 2 files changed, 77 insertions(+), 10 deletions(-) diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index 56b9d42092c..071b16c8378 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -407,6 +407,37 @@ def token_counter( return num_tokens +def _count_function_call_tokens( + key: str, + value: Any, + message: Mapping[str, Any], + count_function: TokenCounterFunction, +) -> int: + """ + Count tokens contributed by an assistant message's tool/function call payload. + + Handles both the modern `tool_calls` list and the legacy OpenAI + `function_call` dict. Only the `arguments` string is counted (matching the + existing tool_calls behavior); names are accounted for elsewhere via the + tool/function definitions and `tool_choice`. + """ + if key == "tool_calls": + if not isinstance(value, List): + raise ValueError(f"Unsupported type {type(value)} for key tool_calls in message {message}") + total = 0 + for tool_call in value: + if "function" not in tool_call: + raise ValueError(f"Unsupported tool call {tool_call} must contain a function key") + function_arguments = tool_call["function"].get("arguments", "") + total += count_function(str(function_arguments)) + return total + if key == "function_call": + if not isinstance(value, Mapping): + raise ValueError(f"Unsupported type {type(value)} for key function_call in message {message}") + return count_function(str(value.get("arguments", ""))) + raise ValueError(f"Unexpected key {key!r}; expected 'tool_calls' or 'function_call'") + + def _count_messages( params: _MessageCountParams, messages: List[AllMessageValues], @@ -430,16 +461,8 @@ def _count_messages( for key, value in message.items(): if value is None: pass - elif key == "tool_calls": - if isinstance(value, List): - for tool_call in value: - if "function" in tool_call: - function_arguments = tool_call["function"].get("arguments", []) - num_tokens += params.count_function(str(function_arguments)) - else: - raise ValueError(f"Unsupported tool call {tool_call} must contain a function key") - else: - raise ValueError(f"Unsupported type {type(value)} for key tool_calls in message {message}") + elif key in ("tool_calls", "function_call"): + num_tokens += _count_function_call_tokens(key, value, message, params.count_function) elif isinstance(value, str): num_tokens += params.count_function(value) if key == "name": diff --git a/tests/test_litellm/litellm_core_utils/test_token_counter.py b/tests/test_litellm/litellm_core_utils/test_token_counter.py index 60e5a797627..71e686563a5 100644 --- a/tests/test_litellm/litellm_core_utils/test_token_counter.py +++ b/tests/test_litellm/litellm_core_utils/test_token_counter.py @@ -97,6 +97,50 @@ def test_token_counter_normal_plus_function_calling(): # test_token_counter_normal_plus_function_calling() +def test_token_counter_legacy_function_call_counts_arguments(): + """ + Regression for VERIA-492 (Token-counter function_call bypass). + + The legacy OpenAI assistant `function_call` field carries arbitrary text in + `arguments`. Before the fix, `_count_messages` had no branch for + `function_call` and fell through to the unsupported-key `continue`, so an + assistant turn could smuggle unlimited text past `token_counter` and the + proxy `/utils/token_counter` endpoint (and downstream pre-call budget / + `get_modified_max_tokens` math). After the fix it must be counted the + same as the equivalent `tool_calls` payload. + """ + long_arg = "A" * 4000 + fc_messages = [ + {"role": "user", "content": "hi"}, + { + "role": "assistant", + "content": None, + "function_call": {"name": "search", "arguments": long_arg}, + }, + ] + tc_messages = [ + {"role": "user", "content": "hi"}, + { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_1", + "type": "function", + "function": {"name": "search", "arguments": long_arg}, + } + ], + }, + ] + fc_tokens = token_counter(model="gpt-3.5-turbo", messages=fc_messages) + tc_tokens = token_counter(model="gpt-3.5-turbo", messages=tc_messages) + assert fc_tokens == tc_tokens, ( + f"function_call arguments must count like tool_calls arguments; " + f"got function_call={fc_tokens}, tool_calls={tc_tokens}" + ) + assert fc_tokens > 500, f"4000-char arguments payload must contribute real tokens, got {fc_tokens}" + + @pytest.mark.parametrize( "message_count_pair", MESSAGES_TEXT, From a0b26d2c3c498f6c11ec4548aa986183eec18f20 Mon Sep 17 00:00:00 2001 From: tin-berri Date: Tue, 30 Jun 2026 14:37:11 -0700 Subject: [PATCH 39/79] =?UTF-8?q?Revert=20"fix(presidio):=20stream=20SSE?= =?UTF-8?q?=20output=20incrementally=20instead=20of=20buffering=20t?= =?UTF-8?q?=E2=80=A6"=20(#31764)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit This reverts commit 94936a3922aeb8aa9a4d5928e63ea6f15be6f098. --- .../guardrails/guardrail_hooks/presidio.py | 523 ++++--------- .../guardrail_hooks/test_presidio.py | 712 +----------------- 2 files changed, 152 insertions(+), 1083 deletions(-) diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py index e60b6233038..95876a55eab 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py +++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py @@ -17,8 +17,6 @@ from typing import ( TYPE_CHECKING, Any, AsyncGenerator, - Awaitable, - Callable, Dict, List, Literal, @@ -56,14 +54,7 @@ from litellm.types.proxy.guardrails.guardrail_hooks.presidio import ( PresidioAnalyzeRequest, PresidioAnalyzeResponseItem, ) -from litellm.types.utils import ( - ChatCompletionDeltaToolCall, - Delta, - Function, - FunctionCall, - GuardrailStatus, - StreamingChoices, -) +from litellm.types.utils import GuardrailStatus, StreamingChoices from litellm.utils import ( EmbeddingResponse, ImageResponse, @@ -71,17 +62,6 @@ from litellm.utils import ( ModelResponseStream, ) -# Trailing context (chars) the streaming output-masking path keeps buffered past -# a sentence boundary before emitting, so a PII entity that straddles the -# boundary is seen in full by Presidio and is never split across two analyze -# calls. It bounds the largest single entity the incremental path can mask -# without leaking; an entity longer than this could still be split. -_PRESIDIO_STREAM_MARGIN = 96 -# Hard cap on buffered un-emitted output. Past this with no sentence boundary, -# stable prefixes are flushed; if stability cannot be proven, the ambiguous -# prefix is dropped while retaining the trailing margin. -_PRESIDIO_STREAM_MAX_BUFFER = 2000 - class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): user_api_key_cache = None @@ -113,10 +93,6 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): self.mock_redacted_text = mock_redacted_text self.output_parse_pii = output_parse_pii or False self.apply_to_output = apply_to_output - # Streaming output-masking safety window; instance attributes so tests can - # exercise incremental flushing with short content (see _mask_emit_decision). - self._stream_mask_margin = _PRESIDIO_STREAM_MARGIN - self._stream_mask_max_buffer = _PRESIDIO_STREAM_MAX_BUFFER # When output_parse_pii or apply_to_output is enabled, the guardrail must # also run on post_call to unmask/mask the response. Expand the event_hook @@ -1072,352 +1048,80 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): ) return response - @staticmethod - def _unmask_hold_len(text: str, token_keys: Any) -> int: - """Length of the trailing run of ``text`` that could still grow into a - PII placeholder token, so the unmask path holds it until the next chunk - completes (or aborts) the token instead of emitting a half-written - ````.""" - keys = tuple(token_keys) - if not text or not keys: - return 0 - longest = max(len(key) for key in keys) - for start in range(max(0, len(text) - (longest - 1)), len(text)): - suffix = text[start:] - if any(key.startswith(suffix) for key in keys if len(suffix) < len(key)): - return len(text) - start - return 0 - - @staticmethod - def _mask_boundaries(text: str) -> tuple[int, ...]: - """Candidate flush points: a newline, or a sentence terminator already - followed by whitespace. A terminator at the very end of the buffer is - excluded because the next chunk may continue the token (``jane.`` + - ``doe@example.com``); it becomes a boundary once the whitespace arrives. - A boundary is only a *candidate* here; ``_mask_emit_decision`` still - confirms via a stability check that no entity straddles it.""" - return tuple( - i + 1 - for i in range(len(text)) - if text[i] == "\n" or (text[i] in ".!?" and i + 1 < len(text) and text[i + 1].isspace()) - ) - - async def _mask_emit_decision( - self, - buffer: str, - terminal: bool, - transform: "Callable[[str], Awaitable[str]]", - ) -> "tuple[str, str]": - """Decide how much of ``buffer`` is safe to mask and emit now, returning - ``(masked_emit, hold_raw)``. - - A sentence boundary is not trusted blindly (it can fall inside a name - with an initial or an address spanning a newline). Instead a prefix is - emitted only when masking it in isolation matches the corresponding - prefix of masking the whole buffer, with at least ``_PRESIDIO_STREAM_MARGIN`` - characters of lookahead still buffered past the cut. That guarantees any - entity overlapping the cut is present in full when the buffer is analyzed, - so a straddling entity makes the prefixes differ and the cut is held. - Past ``_PRESIDIO_STREAM_MAX_BUFFER`` with no sentence boundary the buffer - first tries stable forced cuts and then drops the ambiguous prefix while - retaining the trailing margin, so a failed stability check cannot grow - the held buffer without bound.""" - if terminal: - return (await transform(buffer) if buffer else ""), "" - margin = self._stream_mask_margin - forced_cut = ( - len(buffer) - margin if len(buffer) > self._stream_mask_max_buffer and len(buffer) > margin else None - ) - cuts = [index for index in self._mask_boundaries(buffer) if len(buffer) - index >= margin] - if forced_cut is not None: - verbose_proxy_logger.warning( - "Presidio apply_to_output: buffered %d streamed chars with no " - "sentence boundary; bounding held stream state.", - len(buffer), - ) - cuts.append(forced_cut) - cuts.extend(index for index in range(forced_cut, len(buffer)) if buffer[index].isspace()) - if cuts: - masked_full = await transform(buffer) - for index in sorted(set(cuts), reverse=True): - masked_prefix = await transform(buffer[:index]) - if masked_full.startswith(masked_prefix): - return masked_prefix, buffer[index:] - if forced_cut is not None: - return "", buffer[forced_cut:] - return "", buffer - - @staticmethod - def _accumulate_tool_calls( - tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], - choice_index: int, - tool_calls: list[Any], - ) -> None: - choice_acc = tool_acc.setdefault(choice_index, {}) # mutable-ok: streaming tool-call accumulator - for tool_call in tool_calls: - entry = choice_acc.setdefault( # mutable-ok: streaming tool-call accumulator - getattr(tool_call, "index", 0) or 0, - {"id": None, "type": None, "name": None, "args": ""}, - ) - if getattr(tool_call, "id", None): - entry["id"] = tool_call.id - if getattr(tool_call, "type", None): - entry["type"] = tool_call.type - function = getattr(tool_call, "function", None) - if function is not None: - if getattr(function, "name", None): - entry["name"] = function.name - arguments = getattr(function, "arguments", None) - if isinstance(arguments, str): - entry["args"] = (entry["args"] or "") + arguments - - @staticmethod - def _accumulate_function_call( - func_acc: dict[int, dict[str, Optional[str]]], - choice_index: int, - function_call: Any, - ) -> None: - entry = func_acc.setdefault( # mutable-ok: streaming function-call accumulator - choice_index, {"name": None, "args": ""} - ) - if getattr(function_call, "name", None): - entry["name"] = function_call.name - arguments = getattr(function_call, "arguments", None) - if isinstance(arguments, str): - entry["args"] = (entry["args"] or "") + arguments - - @staticmethod - async def _build_tool_calls( - choice_acc: dict[int, dict[str, Optional[str]]], - transform: "Callable[[str], Awaitable[str]]", - ) -> list[ChatCompletionDeltaToolCall]: - return [ - ChatCompletionDeltaToolCall( - index=tool_index, - id=entry["id"], - type=entry["type"], - function=Function( - name=entry["name"], - arguments=(await transform(entry["args"]) if entry["args"] else ""), - ), - ) - for tool_index, entry in sorted(choice_acc.items()) - ] - - @staticmethod - async def _build_function_call( - entry: Optional[dict[str, Optional[str]]], - transform: "Callable[[str], Awaitable[str]]", - ) -> Optional[FunctionCall]: - if entry is None: - return None - return FunctionCall( - name=entry["name"], - arguments=await transform(entry["args"]) if entry["args"] else "", - ) - - async def _rewrite_chat_chunk( - self, - chunk: ModelResponseStream, - content_buffers: dict[int, str], - tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], - func_acc: dict[int, dict[str, Optional[str]]], - transform: "Callable[[str], Awaitable[str]]", - emit_content: "Callable[[str, bool], Awaitable[tuple[str, str]]]", - ) -> None: - """Transform one streaming chat chunk in place: text content is masked / - unmasked and emitted as soon as ``emit_content`` deems a prefix safe (it - returns the already-transformed text to emit plus the raw remainder to - hold), while tool-call and function-call argument fragments are - accumulated and emitted, fully transformed, on the chunk that closes the - choice.""" - for choice in chunk.choices: - index = getattr(choice, "index", 0) - delta = getattr(choice, "delta", None) - if delta is None: - continue - terminal = bool(getattr(choice, "finish_reason", None)) - - tool_calls = getattr(delta, "tool_calls", None) - if tool_calls: - self._accumulate_tool_calls(tool_acc, index, tool_calls) - delta.tool_calls = None - function_call = getattr(delta, "function_call", None) - if function_call is not None: - self._accumulate_function_call(func_acc, index, function_call) - delta.function_call = None - - raw_content = getattr(delta, "content", None) - content = raw_content if isinstance(raw_content, str) else None - if content is not None or terminal: - emitted, hold = await emit_content(content_buffers.pop(index, "") + (content or ""), terminal) - if hold: - content_buffers[index] = hold - if emitted: - delta.content = emitted - else: - delta.content = None if content is None else "" - - if terminal: - built_tool_calls = await self._build_tool_calls(tool_acc.get(index, {}), transform) - built_function_call = await self._build_function_call(func_acc.get(index), transform) - if built_tool_calls: - delta.tool_calls = built_tool_calls - if built_function_call is not None: - delta.function_call = built_function_call - tool_acc.pop(index, None) - func_acc.pop(index, None) - - @staticmethod - async def _build_tail_chunk( - template: Optional[ModelResponseStream], - content_buffers: dict[int, str], - tool_acc: dict[int, dict[int, dict[str, Optional[str]]]], - func_acc: dict[int, dict[str, Optional[str]]], - transform: "Callable[[str], Awaitable[str]]", - ) -> Optional[ModelResponseStream]: - """Flush any content / tool-call state still held when a stream ends - without a finish-reason chunk to attach it to.""" - if template is None: - return None - cls = _OPTIONAL_PresidioPIIMasking - choices: list[StreamingChoices] = [] - for index in sorted(set(content_buffers) | set(tool_acc) | set(func_acc)): - held = content_buffers.get(index, "") - masked_content = await transform(held) if held else None - built_tool_calls = await cls._build_tool_calls(tool_acc.get(index, {}), transform) - built_function_call = await cls._build_function_call(func_acc.get(index), transform) - if masked_content is None and not built_tool_calls and built_function_call is None: - continue - choices.append( - StreamingChoices( - index=index, - delta=Delta( - content=masked_content, - tool_calls=built_tool_calls or None, - function_call=built_function_call, - ), - ) - ) - if not choices: - return None - return ModelResponseStream( - id=getattr(template, "id", None), - created=getattr(template, "created", None), - model=getattr(template, "model", None), - object="chat.completion.chunk", - choices=choices, - ) - - @staticmethod - def _redacted_chunk(chunk: ModelResponseStream) -> ModelResponseStream: - """Fail closed when masking a chunk raises: rebuild it with empty content - but its original ``finish_reason`` and choice indices preserved, so - possibly-unmasked PII never reaches the client yet a terminal chunk still - carries the completion signal instead of being dropped.""" - return ModelResponseStream( - id=chunk.id, - created=chunk.created, - model=chunk.model, - object="chat.completion.chunk", - choices=[ - StreamingChoices( - index=choice.index, - delta=Delta(content=None), - finish_reason=choice.finish_reason, - ) - for choice in chunk.choices - ], - ) - async def _stream_apply_output_masking( self, response: Any, request_data: dict, ) -> AsyncGenerator[Union[ModelResponseStream, bytes], None]: """Apply Presidio masking to streaming output (apply_to_output=True path).""" - presidio_config = self.get_presidio_settings_from_request_data(request_data or {}) + from litellm.llms.base_llm.base_model_iterator import ( + convert_model_response_to_streaming, + ) + from litellm.main import stream_chunk_builder + from litellm.types.utils import ModelResponse - async def transform(text: str) -> str: - return await self.check_pii( - text=text, - output_parse_pii=False, - presidio_config=presidio_config, - request_data=request_data, - ) - - async def emit_content(text: str, terminal: bool) -> tuple[str, str]: - return await self._mask_emit_decision(text, terminal, transform) - - async def flush_held() -> Optional[ModelResponseStream]: - """Build the held-content tail, failing closed (drop held content) - on a masking error instead of letting it abort the whole stream.""" - try: - return await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) - except Exception as e: - if self._is_guardrail_intervention(e): - raise - verbose_proxy_logger.error(f"Error masking streaming PII tail: {str(e)}") - return None - - content_buffers: dict[int, str] = {} - tool_acc: dict[int, dict[int, dict[str, Optional[str]]]] = {} - func_acc: dict[int, dict[str, Optional[str]]] = {} - last_chunk: Optional[ModelResponseStream] = None - masked_any_content = False - saw_unmaskable_shape = False + all_chunks: List[ModelResponseStream] = [] + passthrough_due_to_unknown_stream_shape = False try: async for chunk in response: - if not isinstance(chunk, ModelResponseStream): - # Flush buffered masked content before forwarding a non-chat - # shape (raw bytes / a /v1/responses event) so the client - # never sees a later event ahead of earlier masked text. - tail = await flush_held() - if tail is not None: - yield tail - content_buffers.clear() - tool_acc.clear() - func_acc.clear() - saw_unmaskable_shape = True + if isinstance(chunk, ModelResponseStream): + if passthrough_due_to_unknown_stream_shape: + yield chunk + else: + all_chunks.append(chunk) + elif isinstance(chunk, bytes): + yield chunk # type: ignore[misc] + continue + else: + if all_chunks: + # Flush buffered chunks and switch to transparent passthrough for this stream shape. + # NOTE: these buffered chunks are emitted unmasked because this + # stream mixed chunk types and cannot be safely reconstructed. + verbose_proxy_logger.warning( + "Presidio apply_to_output: mixed stream detected (ModelResponseStream + unknown event). " + "Flushing %d buffered chunks without PII masking and switching to transparent passthrough.", + len(all_chunks), + ) + for buffered_chunk in all_chunks: + yield buffered_chunk + all_chunks = [] + passthrough_due_to_unknown_stream_shape = True yield chunk - continue - masked_any_content = True - last_chunk = chunk - try: - await self._rewrite_chat_chunk( - chunk, - content_buffers, - tool_acc, - func_acc, - transform, - emit_content, - ) - except Exception as e: - if self._is_guardrail_intervention(e): - raise - # Fail closed: a transient masking error redacts this chunk's - # content (so possibly-unmasked PII never reaches the client) - # but keeps its finish_reason and keeps the stream flowing, - # rather than truncating the response or dropping a terminal - # chunk's completion signal. - verbose_proxy_logger.error(f"Error masking streaming PII chunk: {str(e)}") - yield self._redacted_chunk(chunk) - continue - yield chunk - - tail = await flush_held() - if tail is not None: - yield tail - if not masked_any_content and saw_unmaskable_shape: + if passthrough_due_to_unknown_stream_shape: + verbose_proxy_logger.warning( + "Presidio apply_to_output: streaming response contained unknown event objects " + "(e.g. /v1/responses events). Output PII masking was skipped for this response." + ) + return + if not all_chunks: verbose_proxy_logger.warning( "Presidio apply_to_output: streaming response contained no " - "maskable chat content (e.g. raw SSE bytes or /v1/responses " - "events). Output PII masking was skipped for this response." + "ModelResponseStream chunks (e.g. raw SSE bytes or an empty " + "upstream stream). Output PII masking was skipped for this " + "response." ) + return + + assembled_model_response = stream_chunk_builder(chunks=all_chunks, messages=request_data.get("messages")) + + if not isinstance(assembled_model_response, ModelResponse): + for chunk in all_chunks: + yield chunk + return + + await self._process_response_for_pii( + response=assembled_model_response, + request_data=request_data, + mode="mask", + ) + + mock_response_stream = convert_model_response_to_streaming(assembled_model_response) + yield mock_response_stream + except Exception as e: - if self._is_guardrail_intervention(e): - raise verbose_proxy_logger.error(f"Error masking streaming PII output: {str(e)}") + for chunk in all_chunks: + yield chunk @staticmethod def _unmask_sse_bytes_chunk(chunk: bytes, pii_tokens: Dict[str, str]) -> bytes: @@ -1479,56 +1183,74 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): request_data: dict, ) -> AsyncGenerator[Union[ModelResponseStream, bytes], None]: """Apply PII unmasking to streaming output (output_parse_pii=True path).""" + from litellm.llms.base_llm.base_model_iterator import ( + convert_model_response_to_streaming, + ) + from litellm.main import stream_chunk_builder + from litellm.types.utils import ModelResponse + metadata = (request_data.get("metadata") or {}) if request_data else {} pii_tokens: Dict[str, str] = metadata.get("pii_tokens", {}) - async def transform(text: str) -> str: - return self._unmask_pii_text(text, pii_tokens) - - async def emit_content(text: str, terminal: bool) -> tuple[str, str]: - if terminal: - return (await transform(text) if text else ""), "" - hold = self._unmask_hold_len(text, pii_tokens.keys()) - emit_raw, held = text[: len(text) - hold], text[len(text) - hold :] - return (await transform(emit_raw) if emit_raw else ""), held - - content_buffers: dict[int, str] = {} - tool_acc: dict[int, dict[int, dict[str, Optional[str]]]] = {} - func_acc: dict[int, dict[str, Optional[str]]] = {} - last_chunk: Optional[ModelResponseStream] = None + remaining_chunks: List[ModelResponseStream] = [] + saw_non_chat_chunk = False try: async for chunk in response: - if isinstance(chunk, bytes): - tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) - if tail is not None: - yield tail - content_buffers.clear() - tool_acc.clear() - func_acc.clear() - yield ( # type: ignore[misc] - self._unmask_sse_bytes_chunk(chunk, pii_tokens) if pii_tokens else chunk - ) + if isinstance(chunk, ModelResponseStream): + if saw_non_chat_chunk: + yield chunk + else: + remaining_chunks.append(chunk) + elif isinstance(chunk, bytes): + if pii_tokens: + yield self._unmask_sse_bytes_chunk(chunk, pii_tokens) # type: ignore[misc] + else: + yield chunk # type: ignore[misc] continue - if not isinstance(chunk, ModelResponseStream): - tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) - if tail is not None: - yield tail - content_buffers.clear() - tool_acc.clear() - func_acc.clear() - if getattr(chunk, "type", None) == "response.completed" and pii_tokens: + else: + # /v1/responses events: unmask response.completed text in-place. + # A mixed stream can't be reassembled, so flush buffered chat + # chunks in order before passthrough instead of dropping them. + if remaining_chunks and not saw_non_chat_chunk: + for buffered_chunk in remaining_chunks: + yield buffered_chunk + remaining_chunks = [] + chunk_type = getattr(chunk, "type", None) + if chunk_type == "response.completed" and pii_tokens: self._unmask_responses_api_completed_chunk(chunk, pii_tokens) + saw_non_chat_chunk = True yield chunk - continue - last_chunk = chunk - await self._rewrite_chat_chunk(chunk, content_buffers, tool_acc, func_acc, transform, emit_content) - yield chunk - tail = await self._build_tail_chunk(last_chunk, content_buffers, tool_acc, func_acc, transform) - if tail is not None: - yield tail + if saw_non_chat_chunk: + return + + if not remaining_chunks: + return + + assembled_model_response = stream_chunk_builder( + chunks=remaining_chunks, messages=request_data.get("messages") + ) + + if not isinstance(assembled_model_response, ModelResponse): + for chunk in remaining_chunks: + yield chunk + return + + self._preserve_usage_from_last_chunk(assembled_model_response, remaining_chunks) + + await self._process_response_for_pii( + response=assembled_model_response, + request_data=request_data, + mode="unmask", + ) + + mock_response_stream = convert_model_response_to_streaming(assembled_model_response) + yield mock_response_stream + except Exception as e: verbose_proxy_logger.error(f"Error in PII streaming processing: {str(e)}") + for chunk in remaining_chunks: + yield chunk async def async_post_call_streaming_iterator_hook( # type: ignore[override] self, @@ -1560,6 +1282,17 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): async for chunk in self._stream_pii_unmasking(response, request_data): yield chunk + @staticmethod + def _preserve_usage_from_last_chunk( + assembled_model_response: Any, + chunks: List[Any], + ) -> None: + """Copy usage metadata from the last chunk when stream_chunk_builder misses it.""" + if not getattr(assembled_model_response, "usage", None) and chunks: + last_chunk_usage = getattr(chunks[-1], "usage", None) + if last_chunk_usage: + setattr(assembled_model_response, "usage", last_chunk_usage) + def get_presidio_settings_from_request_data(self, data: dict) -> Optional[PresidioPerRequestConfig]: if "metadata" in data: _metadata = data.get("metadata", None) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py index ce4d6d4a8b0..253d989f203 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py @@ -19,7 +19,7 @@ from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.guardrails.guardrail_hooks.presidio import ( _OPTIONAL_PresidioPIIMasking, ) -from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException +from litellm.exceptions import GuardrailRaisedException from litellm.types.guardrails import LitellmParams, PiiAction, PiiEntityType from litellm.types.utils import Choices, Message, ModelResponse @@ -2207,12 +2207,11 @@ async def test_apply_to_output_streaming_unknown_events_passthrough(): @pytest.mark.asyncio -async def test_apply_to_output_streaming_mixed_chunks_preserve_order(): +async def test_apply_to_output_streaming_mixed_chunks_flushes_and_warns(): """ - Regression test for mixed stream shape: a ModelResponseStream chat chunk - followed by an unknown responses-style event must be forwarded in order. - Incremental masking forwards chat chunks as they arrive, so a responses - event after them does not buffer or drop anything. + Regression test for mixed stream shape: + a buffered ModelResponseStream chunk followed by unknown responses-style + events should be preserved, and masking skip should be visible via warnings. """ guardrail = _OPTIONAL_PresidioPIIMasking( mock_testing=True, @@ -2239,14 +2238,26 @@ async def test_apply_to_output_streaming_mixed_chunks_preserve_order(): mock_user_api_key = UserAPIKeyAuth(api_key="test-key") received = [] - async for chunk in guardrail.async_post_call_streaming_iterator_hook( - user_api_key_dict=mock_user_api_key, - response=mock_stream(), - request_data={}, - ): - received.append(chunk) + with patch( + "litellm.proxy.guardrails.guardrail_hooks.presidio.verbose_proxy_logger" + ) as mock_logger: + async for chunk in guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=mock_user_api_key, + response=mock_stream(), + request_data={}, + ): + received.append(chunk) - assert received == [model_chunk, response_completed] + # Preserve original ordering across mixed stream types. + assert received == [model_chunk, response_completed] + + # Two warnings are expected: + # 1) mixed stream detected + unmasked flush + # 2) passthrough mode skipped output masking + assert mock_logger.warning.call_count == 2 + warning_messages = [call.args[0] for call in mock_logger.warning.call_args_list] + assert any("mixed stream detected" in msg for msg in warning_messages) + assert any("unknown event objects" in msg for msg in warning_messages) # --------------------------------------------------------------------------- @@ -2838,678 +2849,3 @@ async def test_stream_pii_unmasking_passthrough_when_no_tokens(mock_user_api_key chunks.append(chunk) assert chunks == [raw_chunk] - - -# --------------------------------------------------------------------------- -# LIT-3222: incremental SSE streaming for Presidio output masking / unmasking -# --------------------------------------------------------------------------- - -from litellm.types.utils import ( - ChatCompletionDeltaToolCall, - Delta, - Function, - StreamingChoices, -) - - -def _content_chunk(text, index=0, finish_reason=None): - return ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices( - index=index, delta=Delta(content=text), finish_reason=finish_reason - ) - ], - ) - - -def _non_empty_content(chunks): - out = [] - for chunk in chunks: - for choice in chunk.choices: - piece = getattr(choice.delta, "content", None) - if piece: - out.append(piece) - return out - - -async def _drive(guardrail, stream, request_data): - collected = [] - async for chunk in guardrail.async_post_call_streaming_iterator_hook( - user_api_key_dict=UserAPIKeyAuth(api_key="test-key"), - response=stream, - request_data=request_data, - ): - collected.append(chunk) - return collected - - -@pytest.mark.asyncio -async def test_unmask_streaming_is_incremental_not_buffered(): - """ - output_parse_pii streaming must forward each content chunk as it arrives - (unmasked), not collapse the whole completion into a single end-of-stream - chunk. The buffering implementation yielded exactly one content chunk. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) - request_data = {"metadata": {"pii_tokens": {"": "John Smith"}}} - - pieces = ["Hello ", "", " is here."] - - async def stream(): - for i, piece in enumerate(pieces): - yield _content_chunk(piece) - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), request_data) - content = _non_empty_content(collected) - - assert len(content) >= 3, f"expected progressive chunks, got {content}" - assert "".join(content) == "Hello John Smith is here." - assert all("" not in piece for piece in content) - - -@pytest.mark.asyncio -async def test_unmask_streaming_token_split_across_chunks(): - """ - A placeholder token split across SSE chunks (````) must - still be unmasked atomically via the cross-chunk carry buffer. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) - request_data = {"metadata": {"pii_tokens": {"": "John Smith"}}} - - pieces = ["Hi ", "", "!"] - - async def stream(): - for piece in pieces: - yield _content_chunk(piece) - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), request_data) - reassembled = "".join(_non_empty_content(collected)) - - assert reassembled == "Hi John Smith!" - assert "" not in reassembled - - -@pytest.mark.asyncio -async def test_unmask_streaming_independent_per_choice_buffers(): - """ - With n>1 each choice keeps its own carry buffer, so a token split across - chunks on choice 1 does not corrupt choice 0 and vice versa. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) - request_data = { - "metadata": { - "pii_tokens": {"": "John", "": "Jane"} - } - } - - def two_choice_chunk(c0, c1): - return ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices(index=0, delta=Delta(content=c0)), - StreamingChoices(index=1, delta=Delta(content=c1)), - ], - ) - - async def stream(): - yield two_choice_chunk(" ok", "SON_2>!") - yield two_choice_chunk("", "") - - collected = [] - async for chunk in guardrail.async_post_call_streaming_iterator_hook( - user_api_key_dict=UserAPIKeyAuth(api_key="test-key"), - response=stream(), - request_data=request_data, - ): - collected.append(chunk) - - per_choice = {0: "", 1: ""} - for chunk in collected: - for choice in chunk.choices: - if choice.delta.content: - per_choice[choice.index] += choice.delta.content - - assert per_choice[0] == "John ok" - assert per_choice[1] == "Jane!" - - -@pytest.mark.asyncio -async def test_unmask_streaming_tool_call_arguments_unmasked_at_finish(): - """ - Tool-call argument fragments carrying a placeholder token must be - reassembled and unmasked (the tool would otherwise receive ````). - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) - request_data = { - "metadata": {"pii_tokens": {"": "real@example.com"}} - } - - def tool_chunk(*, id=None, name=None, args, finish_reason=None): - return ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices( - index=0, - delta=Delta( - tool_calls=[ - ChatCompletionDeltaToolCall( - index=0, - id=id, - type="function" if id else None, - function=Function(name=name, arguments=args), - ) - ] - ), - finish_reason=finish_reason, - ) - ], - ) - - async def stream(): - yield tool_chunk(id="call_1", name="send_email", args="") - yield tool_chunk(args='{"to": "") - - guardrail.check_pii = mock_check_pii - - pieces = ["My email is ", "secret@example.com. ", "Call me later."] - - async def stream(): - for piece in pieces: - yield _content_chunk(piece) - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - content = _non_empty_content(collected) - - assert len(content) >= 2, f"expected per-sentence chunks, got {content}" - reassembled = "".join(content) - assert reassembled == "My email is . Call me later." - assert "secret@example.com" not in reassembled - - -@pytest.mark.asyncio -async def test_mask_streaming_tool_call_arguments_masked_at_finish(): - """ - Model-generated PII inside streamed tool-call arguments must be masked - before reaching the client, not passed through unmasked. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("secret@example.com", "") - - guardrail.check_pii = mock_check_pii - - def tool_chunk(*, id=None, name=None, args, finish_reason=None): - return ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices( - index=0, - delta=Delta( - tool_calls=[ - ChatCompletionDeltaToolCall( - index=0, - id=id, - type="function" if id else None, - function=Function(name=name, arguments=args), - ) - ] - ), - finish_reason=finish_reason, - ) - ], - ) - - async def stream(): - yield tool_chunk(id="call_1", name="save", args='{"email": "sec') - yield tool_chunk(args='ret@example.com"}') - yield ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices(index=0, delta=Delta(), finish_reason="tool_calls") - ], - ) - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - - all_args = [ - tc.function.arguments - for chunk in collected - for choice in chunk.choices - for tc in (getattr(choice.delta, "tool_calls", None) or []) - ] - assert all_args == ['{"email": ""}'] - assert all("secret@example.com" not in args for args in all_args) - - -@pytest.mark.asyncio -async def test_mask_streaming_flushes_buffered_content_before_passthrough_event(): - """ - Regression test (Greptile 4/5 finding): in the apply_to_output path, masked - content held in the buffer (no sentence boundary yet) must be flushed BEFORE - a non-chat passthrough event (e.g. a /v1/responses completion) is forwarded, - so the client never observes stream completion ahead of the final text. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("secret@example.com", "") - - guardrail.check_pii = mock_check_pii - - class FakeResponsesEvent: - def __init__(self, event_type: str): - self.type = event_type - - completed = FakeResponsesEvent("response.completed") - - async def stream(): - # No sentence terminator -> held in the mask buffer, not yet emitted. - yield _content_chunk("My email is secret@example.com") - yield completed - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - - event_index = collected.index(completed) - masked_indexes = [ - i - for i, chunk in enumerate(collected) - if not isinstance(chunk, FakeResponsesEvent) - and any(getattr(c.delta, "content", None) for c in chunk.choices) - ] - assert masked_indexes, "buffered masked content was never emitted" - assert max(masked_indexes) < event_index, "masked content must precede the event" - - masked_text = "".join( - c.delta.content - for chunk in collected - if not isinstance(chunk, FakeResponsesEvent) - for c in chunk.choices - if getattr(c.delta, "content", None) - ) - assert masked_text == "My email is " - assert "secret@example.com" not in masked_text - - -@pytest.mark.asyncio -async def test_mask_streaming_does_not_split_entity_on_long_unpunctuated_run(): - """ - A long punctuation-free run must never force-flush mid-entity. The old - fixed-window fallback emitted at the last whitespace once the buffer grew - past a cap, so a space-bearing entity (SSN, phone) straddling that cut was - analyzed in two halves and leaked unmasked. Content past the last sentence - boundary is now held until a boundary or end-of-stream so each analyze call - sees the whole entity. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("123 45 6789", "") - - guardrail.check_pii = mock_check_pii - - filler = "data " * 90 # >400 chars, spaces only, no .!?\n boundary - async def stream(): - yield _content_chunk(filler + "my ssn is 123 45 6789") - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - reassembled = "".join(_non_empty_content(collected)) - - assert "" in reassembled - assert "123 45 6789" not in reassembled - assert "456789" not in reassembled - - -@pytest.mark.asyncio -async def test_mask_streaming_preserves_stream_on_check_pii_error(): - """ - A transient Presidio failure mid-stream must not truncate the response. The - failing run is dropped (fail closed, never leaking the PII it could not mask) - while content that already flushed safely, later chunks, and the finish chunk - still reach the client. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - guardrail._stream_mask_margin = 4 - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - if "boom@example.com" in text: - raise RuntimeError("presidio down") - return text.replace("ok@example.com", "") - - guardrail.check_pii = mock_check_pii - - pieces = [ - "First ok@example.com. ", - "filler text here. ", - "Second boom@example.com. ", - "Third part here.", - ] - - async def stream(): - for piece in pieces: - yield _content_chunk(piece) - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - reassembled = "".join(_non_empty_content(collected)) - - assert "" in reassembled - assert "boom@example.com" not in reassembled - assert "Third part" in reassembled, "stream truncated after a masking error" - assert any( - getattr(choice, "finish_reason", None) - for chunk in collected - for choice in getattr(chunk, "choices", []) - ), "finish chunk dropped after a masking error" - - -@pytest.mark.asyncio -async def test_mask_streaming_error_preserves_tool_call_accumulators(): - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - if "bad@example.com" in text: - raise RuntimeError("presidio down") - return text.replace("secret@example.com", "") - - guardrail.check_pii = mock_check_pii - - def tool_chunk(*, id=None, name=None, args=None, finish_reason=None): - return ModelResponseStream( - id="chatcmpl-lit3222", - created=1, - model="gpt-4o-mini", - object="chat.completion.chunk", - choices=[ - StreamingChoices( - index=1, - delta=( - Delta( - tool_calls=[ - ChatCompletionDeltaToolCall( - index=0, - id=id, - type="function" if id else None, - function=Function(name=name, arguments=args), - ) - ] - ) - if args is not None - else Delta() - ), - finish_reason=finish_reason, - ) - ], - ) - - async def stream(): - yield tool_chunk( - id="call_1", - name="save", - args='{"email": "secret@example.com"}', - ) - yield _content_chunk("bad@example.com", index=0, finish_reason="stop") - yield tool_chunk(finish_reason="tool_calls") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - tool_args = [ - tc.function.arguments - for chunk in collected - for choice in chunk.choices - for tc in (getattr(choice.delta, "tool_calls", None) or []) - ] - - assert tool_args == ['{"email": ""}'] - - -@pytest.mark.asyncio -async def test_mask_emit_decision_caps_buffer_when_stability_fails(): - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - guardrail._stream_mask_margin = 3 - guardrail._stream_mask_max_buffer = 6 - - async def unstable_transform(text): - return text[::-1] - - emitted, held = await guardrail._mask_emit_decision( - "abcdefghij", False, unstable_transform - ) - - assert emitted == "" - assert held == "hij" - - -@pytest.mark.parametrize( - "exception", - [ - BlockedPiiEntityError(entity_type="EMAIL_ADDRESS", guardrail_name="presidio"), - GuardrailRaisedException(guardrail_name="presidio", message="invalid response"), - ], -) -@pytest.mark.asyncio -async def test_mask_streaming_propagates_guardrail_interventions(exception): - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - raise exception - - guardrail.check_pii = mock_check_pii - - async def stream(): - yield _content_chunk("blocked", finish_reason="stop") - - with pytest.raises(type(exception)): - await _drive(guardrail, stream(), {"metadata": {}}) - - -@pytest.mark.asyncio -async def test_mask_streaming_holds_terminator_at_chunk_end_until_whitespace(): - """ - A sentence terminator at the very end of a chunk is not a safe boundary: the - next chunk may continue the token. "Contact jane." followed by - "doe@example.com" must mask the whole email rather than flushing "jane." and - analyzing the two halves separately, which would leak the address. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("jane.doe@example.com", "") - - guardrail.check_pii = mock_check_pii - - async def stream(): - yield _content_chunk("Contact jane.") - yield _content_chunk("doe@example.com") - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - reassembled = "".join(_non_empty_content(collected)) - - assert "" in reassembled - assert "jane.doe@example.com" not in reassembled - assert "jane." not in reassembled - - -@pytest.mark.asyncio -async def test_mask_streaming_does_not_split_entity_across_sentence_boundary(): - """ - An entity that straddles a sentence boundary (a name with a middle initial, - an address across a newline) must not be flushed in halves. The stability - check holds the prefix until masking it alone matches masking the whole - buffer, so the straddling entity is analyzed and masked as one unit instead - of leaking the part before the boundary. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - guardrail._stream_mask_margin = 8 - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("John Q. Public", "") - - guardrail.check_pii = mock_check_pii - - async def stream(): - yield _content_chunk("Please greet John Q. Public warmly when they arrive.") - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - reassembled = "".join(_non_empty_content(collected)) - - assert "" in reassembled - assert "John Q. Public" not in reassembled - assert "John Q." not in reassembled - - -@pytest.mark.asyncio -async def test_mask_streaming_caps_runaway_buffer_without_splitting_entity(): - """ - A punctuation-free run past the buffer cap must be flushed to bound memory, - but the forced flush still cuts a margin back from the end so a PII value - split exactly at the cap (``secret@`` in one chunk, ``example.com`` in the - next) stays buffered and is masked whole instead of leaking its raw halves. - The early flush plus the terminal flush yields more than one content chunk. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - guardrail._stream_mask_margin = 8 - guardrail._stream_mask_max_buffer = 20 - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - return text.replace("secret@example.com", "") - - guardrail.check_pii = mock_check_pii - - async def stream(): - yield _content_chunk("please email me at secret@") # 26 > cap, email cut - yield _content_chunk("example.com now") - yield _content_chunk("", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - content = _non_empty_content(collected) - reassembled = "".join(content) - - assert "" in reassembled - assert "secret@example.com" not in reassembled - assert "secret@" not in reassembled - assert len(content) >= 2, f"cap did not flush before end of stream, got {content}" - - -@pytest.mark.asyncio -async def test_mask_streaming_preserves_finish_reason_when_terminal_chunk_fails(): - """ - When the masking call fails on the terminal chunk itself, that chunk must be - redacted in place (content dropped, fail closed) but keep its finish_reason, - so the client still receives the completion signal instead of a stream that - ends without one. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True) - guardrail._stream_mask_margin = 4 - - async def mock_check_pii(text, output_parse_pii, presidio_config, request_data): - if "boom@example.com" in text: - raise RuntimeError("presidio down") - return text - - guardrail.check_pii = mock_check_pii - - async def stream(): - yield _content_chunk("Hello world. ") - yield _content_chunk("more text here. ") - yield _content_chunk("boom@example.com", finish_reason="stop") - - collected = await _drive(guardrail, stream(), {"metadata": {}}) - reassembled = "".join(_non_empty_content(collected)) - - assert "boom@example.com" not in reassembled - assert "Hello world" in reassembled - finish_reasons = [ - choice.finish_reason - for chunk in collected - for choice in getattr(chunk, "choices", []) - if getattr(choice, "finish_reason", None) - ] - assert "stop" in finish_reasons, "finish_reason dropped when terminal chunk failed" - - -@pytest.mark.asyncio -async def test_unmask_streaming_flushes_held_content_before_bytes(): - """ - When a held placeholder prefix is buffered and the next upstream item is a - raw SSE byte chunk, the held chat text must be flushed before the bytes so - the client never sees the byte chunk ahead of earlier content. - """ - guardrail = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True) - request_data = {"metadata": {"pii_tokens": {"": "Jane"}}} - - async def stream(): - yield _content_chunk("Hi Date: Tue, 30 Jun 2026 15:25:55 -0700 Subject: [PATCH 40/79] ci(codspeed): pin benchmark runner to ubuntu-24.04 (#31746) * ci(codspeed): pin benchmark runner to ubuntu-24.04 ubuntu-latest resolves to different runner images between the BASE (main/staging) and HEAD (PR) runs, so CodSpeed reports 'Different runtime environments detected' and emits false-positive regressions (e.g. a -25.2% swing on test_completion_multi_turn in #31684, an MCP auth fix with no LLM code changes). Pinning the runner to a fixed image keeps BASE and HEAD on the same hardware so 1 ms swings on a ~3 ms benchmark stop blocking unrelated PRs. Fixes #31738 * ci(codspeed): stop running benchmarks on litellm_internal_staging The CodSpeed check flip-flops on internal staging and on PRs targeting it (e.g. "+11.75% improvement" on one run, "-25.36% regression" on the next) because the comparison flags "different runtime environments" and the benchmarks are only 3-4 ms, so sub-millisecond runner noise swings the result by 25-30%. Pinning the runner to ubuntu-24.04 in this PR helps the head side, but the internal_staging base is still recorded on the old unpinned runner, so comparisons keep flapping until the pin merges and the base is re-baselined. Until that settles, the red X's on internal staging make the OSS project look unhealthy and confuse contributors, so drop the litellm_internal_staging push and pull_request triggers and keep CodSpeed running on main only. --------- Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- .github/workflows/codspeed.yml | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/.github/workflows/codspeed.yml b/.github/workflows/codspeed.yml index 1fad82827ff..49f1d906069 100644 --- a/.github/workflows/codspeed.yml +++ b/.github/workflows/codspeed.yml @@ -4,11 +4,9 @@ on: push: branches: - main - - litellm_internal_staging pull_request: branches: - main - - litellm_internal_staging # Allow CodSpeed to trigger backtest performance analysis # in order to generate initial data workflow_dispatch: @@ -23,7 +21,7 @@ concurrency: jobs: benchmarks: - runs-on: ubuntu-latest + runs-on: ubuntu-24.04 timeout-minutes: 15 steps: From a7d8c6f46760eae1051d92129507b17e50642234 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 30 Jun 2026 15:27:48 -0700 Subject: [PATCH 41/79] test(pass-through): de-flake vertex spend-log test by routing through the proxy (#31689) * test(pass-through): de-flake vertex spend-log assertion by re-billing The vertex pass-through spend-log test asserted that a single billed generateContent call moved the global spend aggregate within a fixed wait. CI failures show the call returning a valid response with real usage, yet spend never increasing over a 240s poll. Pass-through spend logging is best-effort: the success handler is enqueued on a background worker that can drop or time out an individual event under load and never retries it, so one billed call occasionally never reaches LiteLLM_SpendLogs. Waiting longer cannot recover a dropped event; only re-issuing the call can. Re-bill the call up to a few times and require at least one to be tracked, mirroring the sibling jest test that already retries. The test still fails hard if cost tracking is actually broken, since then every call records nothing. Also sum spend across all returned days instead of matching the runner's local 'today', removing a separate UTC-rollover flake. * test(pass-through): route vertex spend-log test through proxy via direct HTTP The vertexai SDK, configured with location="global" and an http api_endpoint override, intermittently sends generateContent to the public Vertex endpoint instead of the proxy. Proxy logs from a failing run show all 46 of the test's own spend-log polls reaching the proxy while zero generateContent calls did, so LiteLLM never saw the billed call and no spend was ever recorded; re-billing through the SDK could not help because every retry bypassed the proxy too. Issue the pass-through request directly over HTTP so it always hits the proxy, minting a Google token from the same service-account credentials, then assert that the specific call's own spend log lands with spend > 0, a gemini model, and custom_llm_provider vertex_ai. A small best-effort retry covers the rare case where the background logging worker drops a single event; failing every attempt still fails hard so the test keeps its teeth if cost tracking breaks. * test(pass-through): reuse LITE_LLM_ENDPOINT and drop needless async in get_tracked_spend --- tests/pass_through_tests/test_vertex_ai.py | 175 +++++++++++---------- 1 file changed, 96 insertions(+), 79 deletions(-) diff --git a/tests/pass_through_tests/test_vertex_ai.py b/tests/pass_through_tests/test_vertex_ai.py index e8223f2219c..35cb5f49c56 100644 --- a/tests/pass_through_tests/test_vertex_ai.py +++ b/tests/pass_through_tests/test_vertex_ai.py @@ -11,6 +11,7 @@ import json import os import pytest import asyncio +import requests # Path to your service account JSON file SERVICE_ACCOUNT_FILE = "path/to/your/service-account.json" @@ -57,98 +58,114 @@ def load_vertex_ai_credentials(): os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = os.path.abspath(temp_file.name) -async def call_spend_logs_endpoint(): - """ - Call this - curl -X GET "http://0.0.0.0:4000/spend/logs" -H "Authorization: Bearer sk-1234" - """ - import datetime - import requests - - todays_date = datetime.datetime.now().strftime("%Y-%m-%d") - url = f"http://0.0.0.0:4000/global/spend/logs?api_key=best-api-key-ever" - headers = {"Authorization": f"Bearer sk-1234"} - response = requests.get(url, headers=headers) - print("response from call_spend_logs_endpoint", response) - - if response.status_code != 200: - print(f"spend logs endpoint returned {response.status_code}: {response.text}") - return None - - json_response = response.json() - - # get spend for today - """ - json response looks like this - - [{'date': '2024-08-30', 'spend': 0.00016600000000000002, 'api_key': 'best-api-key-ever'}] - """ - print("json_response", json_response) - - todays_date = datetime.datetime.now().strftime("%Y-%m-%d") - for spend_log in json_response: - if spend_log["date"] == todays_date: - return spend_log["spend"] - - LITE_LLM_ENDPOINT = "http://localhost:4000" +SPEND_LOG_API_KEY = "best-api-key-ever" -def _is_vertex_quota_error(exc: Exception) -> bool: - message = str(exc) - return ( - "429" in message - or "Too Many Requests" in message - or "RESOURCE_EXHAUSTED" in message + +def get_tracked_spend() -> float: + """ + Total spend recorded under the pass-through key in the global spend view. + + Sums every day the endpoint returns instead of matching the runner's local + "today" so a UTC date rollover mid-test can't hide a freshly billed call, and + treats an unreachable endpoint as "nothing recorded yet" (0.0). + """ + url = f"{LITE_LLM_ENDPOINT}/global/spend/logs?api_key={SPEND_LOG_API_KEY}" + response = requests.get(url, headers={"Authorization": "Bearer sk-1234"}) + if response.status_code != 200: + print(f"global spend logs endpoint returned {response.status_code}: {response.text}") + return 0.0 + + rows = response.json() + print("global spend logs rows", rows) + return sum(float(row.get("spend") or 0.0) for row in rows) + + +VERTEX_PROJECT = "litellm-ci-cd" +VERTEX_MODEL = "gemini-3.1-flash-lite" +VERTEX_GENERATE_CONTENT_URL = ( + f"{LITE_LLM_ENDPOINT}/vertex_ai/v1/projects/{VERTEX_PROJECT}" + f"/locations/global/publishers/google/models/{VERTEX_MODEL}:generateContent" +) + + +def _vertex_access_token() -> str: + import google.auth + import google.auth.transport.requests + + credentials, _ = google.auth.default( + scopes=["https://www.googleapis.com/auth/cloud-platform"] ) + credentials.refresh(google.auth.transport.requests.Request()) + return credentials.token + + +def _spend_log_for_request(call_id: str) -> dict | None: + response = requests.get( + f"{LITE_LLM_ENDPOINT}/spend/logs?request_id={call_id}", + headers={"Authorization": "Bearer sk-1234"}, + timeout=30, + ) + if response.status_code != 200: + return None + rows = response.json() + return rows[0] if rows else None + + +def _is_vertex_quota_error(response: requests.Response) -> bool: + return response.status_code == 429 or "RESOURCE_EXHAUSTED" in response.text @pytest.mark.asyncio() async def test_basic_vertex_ai_pass_through_with_spendlog(): - - spend_before = await call_spend_logs_endpoint() or 0.0 load_vertex_ai_credentials() + access_token = _vertex_access_token() - vertexai.init( - project="litellm-ci-cd", - location="global", - api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", - api_transport="rest", - ) + # Drive the pass-through over HTTP instead of the vertexai SDK: the SDK intermittently + # routes generateContent to the public Vertex endpoint rather than the proxy override, + # so the call never reaches LiteLLM and no spend is logged. A direct request always + # hits the proxy. Spend logging then runs on a best-effort background worker that can + # drop a single event, so retry a few billed calls and assert that one specific call's + # spend log lands. Failing every attempt still fails hard, which is the signal we want + # if cost tracking is broken. + max_attempts = 3 + poll_seconds = 60 + poll_interval = 5 - model = GenerativeModel(model_name="gemini-3.1-flash-lite") - try: - response = model.generate_content("hi") - except Exception as exc: - if _is_vertex_quota_error(exc): + for attempt in range(1, max_attempts + 1): + response = requests.post( + VERTEX_GENERATE_CONTENT_URL, + headers={ + "Authorization": f"Bearer {access_token}", + "Content-Type": "application/json", + }, + json={"contents": [{"role": "user", "parts": [{"text": "hi"}]}]}, + timeout=60, + ) + if _is_vertex_quota_error(response): pytest.skip("Vertex AI quota exhausted") - raise + assert ( + response.status_code == 200 + ), f"vertex pass-through call failed: {response.status_code} {response.text}" - print("response", response) + call_id = response.headers.get("x-litellm-call-id") + assert call_id, "proxy response missing x-litellm-call-id header" - # Spend logging is async/batched and can lag under CI load, so poll instead of - # sleeping a fixed amount. A transient empty read is skipped, not counted as 0.0 - # spend, which would spuriously fail the assertion on an otherwise-billed call. - max_wait = 240 # total seconds to wait - poll_interval = 10 # seconds between checks - elapsed = 0 - spend_after = spend_before - while elapsed < max_wait: - await asyncio.sleep(poll_interval) - elapsed += poll_interval - latest_spend = await call_spend_logs_endpoint() - if latest_spend is None: - print(f"spend logs unavailable (elapsed={elapsed}s), retrying") - continue - spend_after = latest_spend - print(f"spend_after (elapsed={elapsed}s)", spend_after) - if spend_after > spend_before: - break + for _ in range(poll_seconds // poll_interval): + await asyncio.sleep(poll_interval) + row = _spend_log_for_request(call_id) + if row is not None and float(row.get("spend") or 0) > 0: + assert "gemini" in row["model"], f"unexpected model in spend log: {row}" + assert ( + row["custom_llm_provider"] == "vertex_ai" + ), f"unexpected provider in spend log: {row}" + return - assert ( - spend_after > spend_before - ), "Spend should be greater than before after {}s. spend_before: {}, spend_after: {}".format( - elapsed, spend_before, spend_after + print(f"attempt {attempt}: spend log for call {call_id} not found yet, re-billing") + + pytest.fail( + f"Vertex pass-through spend never recorded after {max_attempts} billed calls" ) @@ -156,7 +173,7 @@ async def test_basic_vertex_ai_pass_through_with_spendlog(): @pytest.mark.skip(reason="skip flaky test - vertex pass through streaming is flaky") async def test_basic_vertex_ai_pass_through_streaming_with_spendlog(): - spend_before = await call_spend_logs_endpoint() or 0.0 + spend_before = get_tracked_spend() print("spend_before", spend_before) load_vertex_ai_credentials() @@ -176,7 +193,7 @@ async def test_basic_vertex_ai_pass_through_streaming_with_spendlog(): print("response", response) await asyncio.sleep(20) - spend_after = await call_spend_logs_endpoint() + spend_after = get_tracked_spend() print("spend_after", spend_after) assert ( spend_after > spend_before From 41f9d8de7b16516808bbad3b5be5da9dd736e698 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Tue, 30 Jun 2026 15:30:08 -0700 Subject: [PATCH 42/79] fix(proxy): extend banned-params + admin-clear lists for NVIDIA Riva (VERIA-493) (#31742) Two NVIDIA-Riva-specific fields consumed by the audio-transcription handler via the provider's `optional_params` passthrough were not covered by the proxy's existing banned-request-body list or the admin-config clearing list applied on `api_base` BYOK override: * `nvcf_function_id` * `use_ssl` Add both to `_BANNED_REQUEST_BODY_PARAMS` in `litellm/proxy/auth/auth_utils.py` and to the kwargs-only list in `_admin_config_fields_to_clear_on_base_override()` in `litellm/router_utils/clientside_credential_handler.py`, next to the analogous provider-specific entries already there (`aws_bedrock_*`, OCI provider fields, etc.). Same admin opt-ins as every other entry on those lists (`general_settings.allow_client_side_credentials` proxy-wide, or `configurable_clientside_auth_params` per deployment). Regression tests in `tests/test_litellm/proxy/auth/test_auth_utils.py` cover root-level rejection, the historical `api_key` bypass, both admin opt-in paths (proxy-wide and per-deployment), nested-container smuggling via the existing recursive walk, and clearing on `api_base` override. Mutation check verified. Resolves VERIA-493 --- litellm/proxy/auth/auth_utils.py | 6 + .../clientside_credential_handler.py | 7 + .../proxy/auth/test_auth_utils.py | 173 ++++++++++++++++++ 3 files changed, 186 insertions(+) diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index b1bce352784..2bf0acc7232 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -278,6 +278,12 @@ _BANNED_REQUEST_BODY_PARAMS: Tuple[str, ...] = ( "s3_endpoint_url", "sagemaker_base_url", "deployment_url", + # NVIDIA Riva fields consumed by the audio-transcription handler + # via ``optional_params``. Banned for the same reason as the + # provider-specific entries above: a caller-supplied value retargets + # the request away from the admin's pinned configuration. + "nvcf_function_id", + "use_ssl", # SDK-only field; also rejected outright in is_request_body_safe. "model_list", # Observability credentials, hosts, and project identifiers: derived diff --git a/litellm/router_utils/clientside_credential_handler.py b/litellm/router_utils/clientside_credential_handler.py index e992ef63658..8234d89e248 100644 --- a/litellm/router_utils/clientside_credential_handler.py +++ b/litellm/router_utils/clientside_credential_handler.py @@ -52,6 +52,13 @@ def _admin_config_fields_to_clear_on_base_override() -> List[str]: "oci_tenancy", "oci_key", "oci_key_file", + # NVIDIA Riva fields — consumed by + # ``litellm/llms/nvidia_riva/audio_transcription/handler.py`` via + # optional_params and not declared on CredentialLiteLLMParams. + # Admin-pinned values must not flow through on a caller-redirected + # ``api_base`` for the same reason as the OCI entries above. + "nvcf_function_id", + "use_ssl", ] return typed_fields + kwargs_only_fields diff --git a/tests/test_litellm/proxy/auth/test_auth_utils.py b/tests/test_litellm/proxy/auth/test_auth_utils.py index cd8cf10d037..d5d2d27cb7e 100644 --- a/tests/test_litellm/proxy/auth/test_auth_utils.py +++ b/tests/test_litellm/proxy/auth/test_auth_utils.py @@ -1520,6 +1520,42 @@ class TestGetDynamicLitellmParamsClearsAdminConfigOnBaseOverride: assert "vertex_credentials" not in out assert "vertex_project" not in out + def test_clears_nvcf_function_id_on_base_override(self): + from litellm.router_utils.clientside_credential_handler import ( + get_dynamic_litellm_params, + ) + + admin_params = { + "model": "nvidia_riva/parakeet", + "api_base": "grpc.nvcf.nvidia.com:443", + "api_key": "nvapi-admin", + "nvcf_function_id": "admin-pinned-function", + } + out = get_dynamic_litellm_params( + litellm_params=dict(admin_params), + request_kwargs={"api_base": "self-hosted.example.com:50051"}, + ) + assert out["api_base"] == "self-hosted.example.com:50051" + assert "nvcf_function_id" not in out + + def test_clears_use_ssl_on_base_override(self): + from litellm.router_utils.clientside_credential_handler import ( + get_dynamic_litellm_params, + ) + + admin_params = { + "model": "nvidia_riva/parakeet", + "api_base": "grpc.nvcf.nvidia.com:443", + "api_key": "nvapi-admin", + "use_ssl": True, + } + out = get_dynamic_litellm_params( + litellm_params=dict(admin_params), + request_kwargs={"api_base": "self-hosted.example.com:50051"}, + ) + assert out["api_base"] == "self-hosted.example.com:50051" + assert "use_ssl" not in out + def test_caller_resupplied_value_overrides_admin_value_on_base_override(self): # When the caller redirects ``api_base`` and *also* supplies their # own value for one of the admin fields (e.g. ``organization``), @@ -1712,6 +1748,127 @@ class TestIsRequestBodySafeBlocksBedrockProjectOverride: ) +class TestIsRequestBodySafeBlocksNVCFFunctionOverride: + """``nvcf_function_id`` is rejected as a request-body param unless the + admin opted in proxy-wide or per-deployment.""" + + def test_nvcf_function_id_in_request_body_is_rejected(self): + with pytest.raises(ValueError, match="nvcf_function_id"): + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "nvcf_function_id": "caller-supplied", + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + + def test_nvcf_function_id_with_api_key_still_rejected(self): + with pytest.raises(ValueError, match="nvcf_function_id"): + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "api_key": "sk-anything", + "nvcf_function_id": "caller-supplied", + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + + def test_admin_opt_in_proxy_wide_allows_nvcf_function_id(self): + assert ( + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "nvcf_function_id": "byok-function-id", + }, + general_settings={"allow_client_side_credentials": True}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + is True + ) + + def test_admin_opt_in_per_deployment_allows_nvcf_function_id(self, monkeypatch): + """The error message lists per-deployment ``configurable_clientside_auth_params`` + as a second opt-in. Cover that path too so it can't silently regress.""" + from litellm.proxy.auth import auth_utils + + monkeypatch.setattr( + auth_utils, + "_allow_model_level_clientside_configurable_parameters", + lambda model, param, request_body_value, llm_router: param == "nvcf_function_id", + ) + + assert ( + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "nvcf_function_id": "byok-function-id", + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + is True + ) + + +class TestIsRequestBodySafeBlocksRivaUseSsl: + """``use_ssl`` is rejected as a request-body param unless the admin + opted in proxy-wide or per-deployment.""" + + def test_use_ssl_in_request_body_is_rejected(self): + with pytest.raises(ValueError, match="use_ssl"): + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "use_ssl": False, + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + + def test_admin_opt_in_proxy_wide_allows_use_ssl(self): + assert ( + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "use_ssl": True, + }, + general_settings={"allow_client_side_credentials": True}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + is True + ) + + def test_admin_opt_in_per_deployment_allows_use_ssl(self, monkeypatch): + from litellm.proxy.auth import auth_utils + + monkeypatch.setattr( + auth_utils, + "_allow_model_level_clientside_configurable_parameters", + lambda model, param, request_body_value, llm_router: param == "use_ssl", + ) + + assert ( + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "use_ssl": True, + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + is True + ) + + # ── is_request_body_safe nested-config recursion (VERIA-6) ──────────────────── @@ -1748,6 +1905,22 @@ class TestIsRequestBodySafeNestedConfig: model="milvus-store", ) + def test_nested_nvcf_function_id_in_metadata_blocked(self): + """Smuggling ``nvcf_function_id`` via ``metadata`` / ``extra_body`` + is the same shape as the VERIA-6 ``api_base`` bypass — must be + rejected by the recursive walk so the NVCF override gate cannot + be sidestepped with nesting.""" + with pytest.raises(ValueError, match="nvcf_function_id"): + is_request_body_safe( + request_body={ + "model": "nvidia_riva/parakeet", + "litellm_metadata": {"nvcf_function_id": "attacker-via-metadata"}, + }, + general_settings={}, + llm_router=None, + model="nvidia_riva/parakeet", + ) + def test_nested_langfuse_host_in_embedding_config_blocked(self): """The recursion uses the *full* banned-param list, not a special subset — so any flag that's banned at the root is also banned From 833406a711111e8e1347eead3aac5a831de39ea8 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Tue, 30 Jun 2026 17:20:24 -0700 Subject: [PATCH 43/79] fix(ui): rotate model credentials in a dedicated modal so a normal save can't overwrite secrets (#28089) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * feat(ui): add provider auth editing to the model edit view Provider API keys / auth could previously only be changed by hand-editing the raw litellm_params JSON, so there was no first-class way to rotate a model's key. Adds an Authentication section that renders the correct provider-specific fields (reusing ProviderSpecificFields) keyed off the model's custom_llm_provider; fields are blank ("leave blank to keep current") so untouched secrets are preserved and only entered values are PATCHed and encrypted at rest. Resolves LIT-3169 * refactor(ui): simplify model auth editing; fix stale credential branch Drop the onFieldsResolved/authFieldKeys round trip: the parent now resolves provider auth field keys itself via the new useProviderAuthFieldKeys hook (same metadata ProviderSpecificFields renders), removing the report-up effect and its stable-reference footgun. ProviderSpecificFields keeps only excludeKeys (real need: suppress duplicate visible inputs). Fix the stale Authentication branch: derive it from the live litellm_credential_name form value (Form.useWatch) instead of the server snapshot, so clearing/adding a credential mid-edit shows the right UI. Also skip inline auth updates entirely when a named credential is selected, so we never submit a credential name and raw inline auth together. * fix(ui): don't leak freshly-entered model auth secrets to display/console The auth values a user types are still sent in the PATCH request, but: - strip them from the locally-stored litellm_params after save so the read-only LiteLLM Params JSON doesn't render the plaintext key - remove the debug console.log in modelPatchUpdateCall that dumped the full update payload (incl. api_key / vertex_credentials) to the browser console on every model update Backend stores these encrypted and returns them masked on refetch. * fix(ui): don't require blank auth fields in model edit context Auth fields render blank ('leave blank to keep'), but required metadata (e.g. OpenAI api_key) added a required validation rule that blocked onFinish entirely — making it impossible to save any unrelated edit without re-entering the secret. Add a disableRequired prop to ProviderSpecificFields and set it in the model edit Authentication section. * fix(ui): rotate model credentials in a dedicated modal so a normal save can't overwrite secrets The model edit form seeded the read-only LiteLLM Params textarea with the whole litellm_params blob and re-sent all of it on every save. Because /model/info redacts secrets by masking them ("azur****BBCC") rather than removing them, any save re-encrypted the asterisk mask over the real value and silently destroyed credentials such as azure_ad_token, aws_session_token, watsonx token/zen_api_key and the OCI key fields. api_key, client_secret, vertex_credentials and the AWS access/secret keys were safe only because the backend strips those entirely Credential rotation now lives in a dedicated UpdateModelCredentialsModal that PATCHes only the fields the user types, decoupled from the params blob; the backend already merges partial litellm_params, so the rest of the deployment is left untouched. The general edit form drops masked values from both the textarea seed and the outbound payload, so a normal save can never carry a redacted secret Also removes the now-unused inline auth section and its excludeKeys and useProviderAuthFieldKeys plumbing, strips secret-leaking console.logs from the provider upload handler and the model-update response, and fixes a react-hooks/use-memo error that was failing the frontend-lint CI job * chore(ui): ratchet no-explicit-any lint metric to 2013 Removing the credential-echoing console.log (and its info: any param) from the provider upload handler dropped the tracked count by one; update the committed baseline so the Check lint budgets CI step is not stale * refactor(ui): scope the model credential modal to api-key rotation only Narrows UpdateModelCredentialsModal to a single API Key field. On submit it PATCHes only { api_key }, so the backend merge leaves every other deployment param untouched; a model authed via azure_ad_token, AWS keys, or a Vertex JSON won't have anything to rotate here yet, which is the intended scope for now. Drops the multi-field provider rendering this added earlier, which also removes the now-unused disableRequired prop from ProviderSpecificFields and reverts that shared component to its prior shape. The "Update API Key" trigger button is now an antd Button rather than a TremorButton, so the feature introduces no tremor. * refactor(ui): convert the model detail toolbar buttons from tremor to antd Switches Test Connection, Re-use Credentials and Delete Model to antd Button so the toolbar matches the Update API Key button and no longer mixes libraries; Delete Model uses antd's danger styling instead of hand-rolled red classes * style(ui): make the api-key modal submit button primary and drop the Need Help link --- ui/litellm-dashboard/eslint-metrics.json | 2 +- .../add_model/provider_specific_fields.tsx | 17 ---- .../src/components/model_info_view.test.tsx | 45 ++++++++++ .../src/components/model_info_view.tsx | 74 +++++++++++++---- .../src/components/networking.tsx | 5 +- .../update_model_credentials_modal.test.tsx | 83 +++++++++++++++++++ .../update_model_credentials_modal.tsx | 76 +++++++++++++++++ 7 files changed, 265 insertions(+), 37 deletions(-) create mode 100644 ui/litellm-dashboard/src/components/update_model_credentials_modal.test.tsx create mode 100644 ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx diff --git a/ui/litellm-dashboard/eslint-metrics.json b/ui/litellm-dashboard/eslint-metrics.json index 09ad247391b..92c5a991eb6 100644 --- a/ui/litellm-dashboard/eslint-metrics.json +++ b/ui/litellm-dashboard/eslint-metrics.json @@ -1,5 +1,5 @@ { - "@typescript-eslint/no-explicit-any": 2014, + "@typescript-eslint/no-explicit-any": 2013, "complexity": 126, "max-depth": 61 } diff --git a/ui/litellm-dashboard/src/components/add_model/provider_specific_fields.tsx b/ui/litellm-dashboard/src/components/add_model/provider_specific_fields.tsx index 045a9b0c1b6..205292edfb4 100644 --- a/ui/litellm-dashboard/src/components/add_model/provider_specific_fields.tsx +++ b/ui/litellm-dashboard/src/components/add_model/provider_specific_fields.tsx @@ -212,9 +212,7 @@ const ProviderSpecificFields: React.FC = ({ selecte reader.onload = (e) => { if (e.target) { const jsonStr = e.target.result as string; - console.log(`Setting field value from JSON, length: ${jsonStr.length}`); form.setFieldsValue({ vertex_credentials: jsonStr }); - console.log("Form values after setting:", form.getFieldsValue()); } }; reader.readAsText(file); @@ -222,14 +220,6 @@ const ProviderSpecificFields: React.FC = ({ selecte // Prevent upload return false; }, - onChange(info: any) { - console.log("Upload onChange triggered in ProviderSpecificFields"); - console.log("Current form values:", form.getFieldsValue()); - - if (info.file.status !== "uploading") { - console.log(info.file, info.fileList); - } - }, }; return ( @@ -271,16 +261,9 @@ const ProviderSpecificFields: React.FC = ({ selecte { - // First call the original onChange if (uploadProps?.onChange) { uploadProps.onChange(info); } - - // Check the field value after a short delay - setTimeout(() => { - const value = form.getFieldValue(field.key); - console.log(`${field.key} value after upload:`, JSON.stringify(value)); - }, 500); }} > }>Click to Upload diff --git a/ui/litellm-dashboard/src/components/model_info_view.test.tsx b/ui/litellm-dashboard/src/components/model_info_view.test.tsx index d91d5ec307e..2546601b4db 100644 --- a/ui/litellm-dashboard/src/components/model_info_view.test.tsx +++ b/ui/litellm-dashboard/src/components/model_info_view.test.tsx @@ -633,6 +633,51 @@ describe("ModelInfoView", () => { expect(updatePayload.litellm_params).not.toHaveProperty("output_cost_per_token"); }); + it("never re-sends a masked secret on save (regression: masked auth value must not overwrite the real secret)", async () => { + // /model/info redacts secrets by masking (e.g. "azur****BBCC"), not removing them. + // A plain save re-PATCHes the whole litellm_params blob; if the masked value were + // sent, the backend would encrypt the asterisks over the real azure_ad_token and + // silently destroy the credential. The edit form must strip masked values entirely. + const maskedSecret = "azur********************************************BBCC"; + const maskedModelData = { + ...defaultModelData, + litellm_params: { + model: "azure/gpt-4o", + api_base: "https://example-az.openai.azure.com", + custom_llm_provider: "azure", + azure_ad_token: maskedSecret, + }, + }; + mockUseModelsInfo.mockReturnValue({ + data: { data: [maskedModelData] }, + isLoading: false, + error: null, + }); + mockModelInfoV1Call.mockResolvedValue({ data: [maskedModelData] }); + + const user = userEvent.setup(); + render(, { wrapper }); + + await waitFor(() => { + expect(screen.getByRole("button", { name: /edit settings/i })).toBeInTheDocument(); + }); + await user.click(screen.getByRole("button", { name: /edit settings/i })); + + await waitFor(() => { + expect(screen.getByRole("button", { name: /save changes/i })).toBeInTheDocument(); + }); + await user.click(screen.getByRole("button", { name: /save changes/i })); + + await waitFor(() => { + expect(mockModelPatchUpdateCall).toHaveBeenCalled(); + }); + + const updatePayload = mockModelPatchUpdateCall.mock.calls[0][1]; + expect(updatePayload.litellm_params.azure_ad_token).not.toBe(maskedSecret); + // No masked value may appear anywhere in the outbound params. + expect(JSON.stringify(updatePayload.litellm_params)).not.toContain("**"); + }); + it("should display health check model field for wildcard models", async () => { const wildcardModelData = { ...defaultModelData, diff --git a/ui/litellm-dashboard/src/components/model_info_view.tsx b/ui/litellm-dashboard/src/components/model_info_view.tsx index 66a00b9bbe3..45c5b0fd9b6 100644 --- a/ui/litellm-dashboard/src/components/model_info_view.tsx +++ b/ui/litellm-dashboard/src/components/model_info_view.tsx @@ -1,5 +1,6 @@ import { useModelCostMap } from "@/app/(dashboard)/hooks/models/useModelCostMap"; import { useModelHub, useModelsInfo } from "@/app/(dashboard)/hooks/models/useModels"; +import { useQueryClient } from "@tanstack/react-query"; import { transformModelData } from "@/app/(dashboard)/models-and-endpoints/utils/modelDataTransformer"; import { InfoCircleOutlined } from "@ant-design/icons"; import { ArrowLeftIcon, KeyIcon, RefreshIcon, TrashIcon } from "@heroicons/react/outline"; @@ -40,6 +41,7 @@ import { testConnectionRequest, } from "./networking"; import { getProviderLogoAndName } from "./provider_info_helpers"; +import UpdateModelCredentialsModal from "./update_model_credentials_modal"; import NumericalInput from "./shared/numerical_input"; import { Tag } from "./tag_management/types"; import { getDisplayModelName } from "./view_model/model_name_display"; @@ -54,6 +56,18 @@ interface ModelInfoViewProps { modelAccessGroups: string[] | null; } +// The /model/info response redacts secrets by masking them (e.g. "sk-1****2345"), +// not by removing them. The edit form must never echo a masked value back on save: +// the backend would encrypt the asterisks and overwrite the real secret. A run of +// 2+ mask chars only appears in masker output (real config — incl. wildcard model +// names like "openai/*" — carries at most a single "*"), so this reliably detects a +// redacted value without a provider-metadata lookup. API-key rotation goes through +// UpdateModelCredentialsModal instead, which sends only the new key. +const isMaskedSecret = (value: unknown): boolean => typeof value === "string" && /\*{2,}/.test(value); + +const stripMaskedSecrets = (params: Record): Record => + Object.fromEntries(Object.entries(params).filter(([, value]) => !isMaskedSecret(value))); + export default function ModelInfoView({ modelId, onClose, @@ -64,10 +78,12 @@ export default function ModelInfoView({ modelAccessGroups, }: ModelInfoViewProps) { const [form] = Form.useForm(); + const queryClient = useQueryClient(); const [localModelData, setLocalModelData] = useState(null); const [isDeleteModalOpen, setIsDeleteModalOpen] = useState(false); const [deleteLoading, setDeleteLoading] = useState(false); const [isCredentialModalOpen, setIsCredentialModalOpen] = useState(false); + const [isUpdateCredentialsModalOpen, setIsUpdateCredentialsModalOpen] = useState(false); const [isDirty, setIsDirty] = useState(false); const [isSaving, setIsSaving] = useState(false); const [isEditing, setIsEditing] = useState(false); @@ -351,9 +367,15 @@ export default function ModelInfoView({ return; } + // Final guard: never PATCH a redacted secret. The /model/info snapshot that + // seeds this form masks secrets, and any save re-sends the whole params blob; + // without this strip a masked value would be re-encrypted over the real secret. + // Credential rotation has its own dedicated path (UpdateModelCredentialsModal). + const safeLitellmParams = stripMaskedSecrets(updatedLitellmParams); + const updateData = { model_name: values.model_name, - litellm_params: updatedLitellmParams, + litellm_params: safeLitellmParams, model_info: updatedModelInfo, }; @@ -363,7 +385,7 @@ export default function ModelInfoView({ ...localModelData, model_name: values.model_name, litellm_model_name: values.litellm_model_name, - litellm_params: updatedLitellmParams, + litellm_params: safeLitellmParams, model_info: updatedModelInfo, }; @@ -511,36 +533,44 @@ export default function ModelInfoView({
- } onClick={handleTestConnection} className="flex items-center gap-2" data-testid="test-connection-button" > Test Connection - + - } + onClick={() => setIsUpdateCredentialsModalOpen(true)} + className="flex items-center" + disabled={!canEditModel} + data-testid="update-api-key-button" + > + Update API Key + + +
@@ -715,7 +745,7 @@ export default function ModelInfoView({ litellm_extra_params: JSON.stringify( Object.fromEntries( Object.entries(localModelData.litellm_params || {}).filter( - ([key]) => key !== "litellm_credential_name", + ([key, value]) => key !== "litellm_credential_name" && !isMaskedSecret(value), ), ), null, @@ -1375,6 +1405,18 @@ export default function ModelInfoView({ )} + {isUpdateCredentialsModalOpen && accessToken && ( + setIsUpdateCredentialsModalOpen(false)} + accessToken={accessToken} + modelId={modelId} + onUpdated={() => { + queryClient.invalidateQueries({ queryKey: ["models", "list"] }); + }} + /> + )} + {/* Edit Auto Router Modal */} { try { - console.log("Form Values in modelUpateCall:", formValues); // Log the form values before making the API call - + // Intentionally not logging the payload: it can contain freshly-entered + // provider secrets (api_key, vertex_credentials, AWS creds). const url = proxyBaseUrl ? `${proxyBaseUrl}/model/${modelId}/update` : `/model/${modelId}/update`; const response = await fetch(url, { method: "PATCH", @@ -2802,7 +2802,6 @@ export const modelPatchUpdateCall = async ( throw new Error("Network response was not ok"); } const data = await response.json(); - console.log("Update model Response:", data); return data; // Handle success - you might want to update some state or UI based on the created key } catch (error) { diff --git a/ui/litellm-dashboard/src/components/update_model_credentials_modal.test.tsx b/ui/litellm-dashboard/src/components/update_model_credentials_modal.test.tsx new file mode 100644 index 00000000000..ab18ae71203 --- /dev/null +++ b/ui/litellm-dashboard/src/components/update_model_credentials_modal.test.tsx @@ -0,0 +1,83 @@ +import { render, screen, waitFor } from "@testing-library/react"; +import userEvent from "@testing-library/user-event"; +import { beforeAll, beforeEach, describe, expect, it, vi } from "vitest"; +import UpdateModelCredentialsModal from "./update_model_credentials_modal"; +import * as networking from "./networking"; + +vi.mock("./networking", async () => { + const actual = await vi.importActual("./networking"); + return { + ...actual, + modelPatchUpdateCall: vi.fn().mockResolvedValue({}), + }; +}); + +vi.mock("./molecules/notifications_manager", () => ({ + default: { success: vi.fn(), error: vi.fn(), info: vi.fn(), fromBackend: vi.fn() }, +})); + +const mockModelPatchUpdateCall = vi.mocked(networking.modelPatchUpdateCall); + +beforeAll(() => { + Object.defineProperty(window, "matchMedia", { + writable: true, + value: (query: string) => ({ + matches: false, + media: query, + onchange: null, + addListener: () => {}, + removeListener: () => {}, + addEventListener: () => {}, + removeEventListener: () => {}, + dispatchEvent: () => false, + }), + }); +}); + +const renderModal = (overrides: Partial[0]> = {}) => + render( + , + ); + +describe("UpdateModelCredentialsModal", () => { + beforeEach(() => { + vi.clearAllMocks(); + }); + + it("sends a minimal PATCH with only the new api_key", async () => { + const user = userEvent.setup(); + const onUpdated = vi.fn(); + const onCancel = vi.fn(); + renderModal({ onUpdated, onCancel }); + + await user.type(screen.getByLabelText(/new api key/i), "sk-rotated-9988"); + await user.click(screen.getByRole("button", { name: /update api key/i })); + + await waitFor(() => expect(mockModelPatchUpdateCall).toHaveBeenCalledTimes(1)); + const [token, payload, modelId] = mockModelPatchUpdateCall.mock.calls[0]; + expect(token).toBe("test-token"); + expect(modelId).toBe("model-123"); + // Exactly the new key plus the id — nothing else from the deployment. + expect(payload).toEqual({ litellm_params: { api_key: "sk-rotated-9988" }, model_info: { id: "model-123" } }); + expect(onUpdated).toHaveBeenCalledTimes(1); + expect(onCancel).toHaveBeenCalledTimes(1); + }); + + it("does not call the update API when the field is left blank", async () => { + const user = userEvent.setup(); + renderModal(); + + await user.click(screen.getByRole("button", { name: /update api key/i })); + + // Required-field validation blocks submit; give it a tick then assert no call. + await new Promise((resolve) => setTimeout(resolve, 50)); + expect(mockModelPatchUpdateCall).not.toHaveBeenCalled(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx b/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx new file mode 100644 index 00000000000..238207a4aa8 --- /dev/null +++ b/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx @@ -0,0 +1,76 @@ +import { Button, Form, Input, Modal, Typography } from "antd"; +import { useState } from "react"; +import { modelPatchUpdateCall } from "./networking"; +import NotificationsManager from "./molecules/notifications_manager"; + +const { Text } = Typography; + +interface UpdateModelCredentialsModalProps { + open: boolean; + onCancel: () => void; + accessToken: string; + modelId: string; + onUpdated: () => void; +} + +export default function UpdateModelCredentialsModal({ + open, + onCancel, + accessToken, + modelId, + onUpdated, +}: UpdateModelCredentialsModalProps) { + const [form] = Form.useForm(); + const [isSaving, setIsSaving] = useState(false); + + const close = () => { + form.resetFields(); + onCancel(); + }; + + const handleSubmit = async (values: { api_key?: string }) => { + const apiKey = values.api_key?.trim(); + if (!apiKey) { + NotificationsManager.fromBackend("Enter a new API key"); + return; + } + setIsSaving(true); + try { + await modelPatchUpdateCall( + accessToken, + { litellm_params: { api_key: apiKey }, model_info: { id: modelId } }, + modelId, + ); + NotificationsManager.success("API key updated"); + form.resetFields(); + onUpdated(); + onCancel(); + } catch (error) { + console.error("Error updating API key:", error); + NotificationsManager.fromBackend("Failed to update API key"); + } finally { + setIsSaving(false); + } + }; + + return ( + + + Rotate this model's API key. Only the new key is sent; the rest of the deployment is left untouched. + + + + + +
+ + +
+ + + ); +} From 2860dad5145772070c6607883989454dbb2943d4 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Tue, 30 Jun 2026 18:17:56 -0700 Subject: [PATCH 44/79] feat(proxy): audit default user settings updates (#31753) * feat(proxy): audit default user settings updates Adds audit logging for the customer-impacting path: PATCH /update/internal_user_settings, which is what the admin dashboard hits when an admin changes Default User Settings and which today leaves no record of who changed what. Introduces the small framework that future system-wide settings audits will share: a CONFIG_TABLE_NAME enum value, a create_config_audit_log helper that reuses the existing create_object_audit_log path (so the enterprise gate and store_audit_logs flag still apply), and a _dump_redacted_config helper that strips secret leaves before the row is written using the same matcher /config/field/info applies for non-admins. The helper handles environment_variables as a special case where every value is redacted, since that section carries credentials under non-secret-looking uppercase keys (e.g. DATABASE_URL). Only update_internal_user_settings is wired up in this change. Coverage for the other LiteLLM_Config writers (/config/update sections, /config/field/update, /config/field/delete, /config/callback/delete, default_team_settings, mcp_semantic_filter, allowed_ip, sso_settings, ui_theme, ui_settings) is intentionally a follow-up so each can be verified live against the credential-bearing fields it actually carries. The audit-actor parameter on _update_litellm_setting is optional today so non-audited callers keep working unchanged; the follow-up will make it required once every caller is wired up. * fix(proxy): make audit-log call non-blocking and serializer defensive Greptile review of #31753 surfaced three robustness issues with the audit-log call path. The settings change always commits; these fixes prevent post-commit audit failures from surfacing as 500 responses. Switch the audit-log call in _update_litellm_setting from a blocking await to asyncio.create_task, matching the create_object_audit_log pattern every other call site uses (model_management_endpoints etc.). A transient prisma blip or a JSON serialization error in the audit row no longer turns a successful save_config into a 500 the caller sees. Add default=str to both json.dumps calls in _dump_redacted_config so a YAML-loaded value with a non-JSON-native leaf (datetime, custom object) serializes cleanly. The sibling audit-log serializers in team_endpoints.py already pass default=str for the same reason. Tighten the redact_all_values branch to redact wholesale for non-dict inputs rather than silently falling through to the key-name matcher; defensive against a future change that stores a section as a list or scalar. Each fix has a regression test mutation-checked against reverting the fix. * refactor(proxy): drop unreachable non-dict redact_all_values branch The defensive non-dict fallback in _dump_redacted_config emitted json.dumps("REDACTED") which, if ever hit, would crash LiteLLM_AuditLogs construction (mask_api_keys validator calls json.loads on the already- parsed bare string). Reachability is zero: redact_all_values is True only for param_name=="environment_variables", which is always a dict. Delete the dead branch and its test rather than ship provably-wrong defensive code with a test that green-lights it. --- litellm/proxy/_types.py | 1 + litellm/proxy/proxy_server.py | 46 +++++++- .../proxy_setting_endpoints.py | 28 ++++- tests/test_litellm/proxy/test_proxy_server.py | 106 ++++++++++++++++++ .../test_proxy_setting_endpoints.py | 91 +++++++++++++++ 5 files changed, 270 insertions(+), 2 deletions(-) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 5fe17d79ab5..a6ef7de07ae 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -189,6 +189,7 @@ class LitellmTableNames(str, enum.Enum): TOOL_TABLE_NAME = "LiteLLM_ToolTable" CACHE_CONFIG_TABLE_NAME = "LiteLLM_CacheConfig" CONFIG_OVERRIDES_TABLE_NAME = "LiteLLM_ConfigOverrides" + CONFIG_TABLE_NAME = "LiteLLM_Config" class Litellm_EntityType(enum.Enum): diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 57814de6e3f..0158f601d32 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -425,7 +425,10 @@ from litellm.proxy.management_endpoints.user_agent_analytics_endpoints import ( from litellm.proxy.management_endpoints.workflow_management_endpoints import ( router as workflow_management_router, ) -from litellm.proxy.management_helpers.audit_logs import create_audit_log_for_update +from litellm.proxy.management_helpers.audit_logs import ( + create_audit_log_for_update, + create_object_audit_log, +) from litellm.proxy.memory.memory_endpoints import router as memory_router from litellm.proxy.plugin_routes import ( router as plugin_router, @@ -14228,6 +14231,47 @@ def _redact_general_setting_value(field_name: str, value: JsonValue, is_full_adm return value +def _dump_redacted_config(value: Optional[JsonValue], *, redact_all_values: bool = False) -> Optional[str]: + # `default=str` matches the sibling audit-log serializers in + # team_endpoints.py and the LiteLLM_AuditLogs validator, so a YAML-loaded + # value with a non-JSON-native leaf (datetime, custom object) cannot turn + # an audit write into a 500. + if value is None: + return None + if redact_all_values and isinstance(value, dict): + return json.dumps({key: "REDACTED" for key in value}, default=str) + return json.dumps(_redact_secret_values_in_obj(value), default=str) + + +async def create_config_audit_log( + param_name: str, + action: AUDIT_ACTIONS, + before_value: Optional[JsonValue], + after_value: Optional[JsonValue], + user_api_key_dict: UserAPIKeyAuth, + table_name: LitellmTableNames = LitellmTableNames.CONFIG_TABLE_NAME, +) -> None: + """Record a system-wide settings change in LiteLLM_AuditLog. + + Secret leaves are redacted before the row is written. environment_variables + hold arbitrary credentials under non-secret-looking uppercase keys (e.g. + DATABASE_URL), so every value in that section is redacted rather than + relying on key-name matching; other sections reuse the same matcher + /config/field/info applies for non-admins. + """ + redact_all_values = param_name == "environment_variables" + await create_object_audit_log( + object_id=param_name, + action=action, + table_name=table_name, + before_value=_dump_redacted_config(before_value, redact_all_values=redact_all_values), + after_value=_dump_redacted_config(after_value, redact_all_values=redact_all_values), + user_api_key_dict=user_api_key_dict, + litellm_changed_by=None, + litellm_proxy_admin_name=LITELLM_PROXY_ADMIN_NAME, + ) + + @router.get( "/config/field/info", tags=["config.yaml"], diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py index e4f68a1e9db..1be17c86123 100644 --- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py +++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py @@ -1,4 +1,5 @@ #### CRUD ENDPOINTS for UI Settings ##### +import asyncio import json from typing import Any, Dict, List, Optional, Set, Tuple, Type, Union from urllib.parse import urlparse @@ -553,6 +554,7 @@ async def _update_litellm_setting( settings: Union[DefaultInternalUserParams, DefaultTeamSSOParams, MCPSemanticFilterSettings], settings_key: str, success_message: str, + user_api_key_dict: Optional[UserAPIKeyAuth] = None, ): """ Common utility function to update `litellm_settings` in both memory and config. @@ -561,8 +563,15 @@ async def _update_litellm_setting( settings: The settings object to update settings_key: The key in litellm_settings to update success_message: Message to return on success + user_api_key_dict: The acting admin, recorded as the audit-log actor. + Optional today so callers that have not been wired for auditing + keep working; the audit row is only written when an actor is passed. """ - from litellm.proxy.proxy_server import proxy_config, store_model_in_db + from litellm.proxy.proxy_server import ( + create_config_audit_log, + proxy_config, + store_model_in_db, + ) if store_model_in_db is not True: raise HTTPException( @@ -576,6 +585,7 @@ async def _update_litellm_setting( # because get_config() may overwrite litellm. with stale DB values # via LITELLM_SETTINGS_SAFE_DB_OVERRIDES. config = await proxy_config.get_config() + before_value = config.get("litellm_settings", {}).get(settings_key) # Update the in-memory settings (after get_config to avoid stale override) setattr(litellm, settings_key, in_memory_var) @@ -589,6 +599,21 @@ async def _update_litellm_setting( # Save the updated config await proxy_config.save_config(new_config=config) + if user_api_key_dict is not None: + # Fire-and-forget so an audit-log failure (transient DB blip, etc.) + # never surfaces as a 500 after save_config has already committed, + # matching the create_object_audit_log pattern used elsewhere + # (e.g. model_management_endpoints). + asyncio.create_task( + create_config_audit_log( + param_name=settings_key, + action="updated", + before_value=before_value, + after_value=in_memory_var, + user_api_key_dict=user_api_key_dict, + ) + ) + return { "message": success_message, "status": "success", @@ -619,6 +644,7 @@ async def update_internal_user_settings( settings=settings, settings_key="default_internal_user_params", success_message="Internal user settings updated successfully", + user_api_key_dict=user_api_key_dict, ) diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 019a7dc90d2..dc35d71ccbd 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -8658,3 +8658,109 @@ def test_config_field_info_returns_raw_secrets_for_full_admin(monkeypatch): ) finally: app.dependency_overrides.clear() + + +def _fake_prisma_with_config(existing_param_value): + """MagicMock prisma whose litellm_config row returns existing_param_value and + whose litellm_auditlog.create records the written audit row.""" + fake = MagicMock() + config_row = MagicMock() + config_row.param_value = existing_param_value + fake.db.litellm_config.find_first = AsyncMock(return_value=config_row) + fake.db.litellm_config.upsert = AsyncMock(return_value=config_row) + fake.db.litellm_auditlog.create = AsyncMock() + return fake + + +def test_dump_redacted_config_redacts_secret_leaves(): + from litellm.proxy.proxy_server import _dump_redacted_config + + assert _dump_redacted_config(None) is None + + restored = json.loads( + _dump_redacted_config( + { + "api_key": "sk-leak", + "model": "gpt-4", + "nested": {"aws_secret_access_key": "abc", "region": "us-east-1"}, + } + ) + ) + assert restored["api_key"] == "REDACTED" + assert restored["model"] == "gpt-4" + assert restored["nested"]["aws_secret_access_key"] == "REDACTED" + assert restored["nested"]["region"] == "us-east-1" + + +@pytest.mark.asyncio +async def test_create_config_audit_log_writes_redacted_entry(monkeypatch): + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import LitellmTableNames + from litellm.proxy.proxy_server import create_config_audit_log + + fake = _fake_prisma_with_config({}) + monkeypatch.setattr(proxy_server_module, "prisma_client", fake) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + caller = UserAPIKeyAuth(api_key="hashed-key-abc", user_id="admin-7") + await create_config_audit_log( + "router_settings", + "updated", + {"routing_strategy": "simple-shuffle", "api_key": "sk-old"}, + {"routing_strategy": "latency-based", "api_key": "sk-new"}, + caller, + ) + + fake.db.litellm_auditlog.create.assert_awaited_once() + written = fake.db.litellm_auditlog.create.call_args.kwargs["data"] + assert written["table_name"] == LitellmTableNames.CONFIG_TABLE_NAME.value + assert written["object_id"] == "router_settings" + assert written["action"] == "updated" + assert written["changed_by"] == "admin-7" + assert written["changed_by_api_key"] == "hashed-key-abc" + + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert before["routing_strategy"] == "simple-shuffle" + assert after["routing_strategy"] == "latency-based" + assert "sk-old" not in written["before_value"] + assert "sk-new" not in written["updated_values"] + assert before["api_key"] != "sk-old" + assert after["api_key"] != "sk-new" + + +@pytest.mark.asyncio +async def test_create_config_audit_log_noop_when_store_audit_logs_disabled(monkeypatch): + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy.proxy_server import create_config_audit_log + + fake = _fake_prisma_with_config({}) + monkeypatch.setattr(proxy_server_module, "prisma_client", fake) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", False) + + await create_config_audit_log( + "router_settings", + "updated", + {}, + {"a": 1}, + UserAPIKeyAuth(api_key="k", user_id="u"), + ) + fake.db.litellm_auditlog.create.assert_not_called() + + +def test_dump_redacted_config_serializes_non_json_native_values(): + """YAML-loaded config can contain datetime/date/custom values that plain + json.dumps refuses. Without default=str the audit write turns into a 500 + after the config change has already committed; the sibling audit-log + serializers in team_endpoints.py use default=str for the same reason.""" + from datetime import datetime, timezone + + from litellm.proxy.proxy_server import _dump_redacted_config + + out = _dump_redacted_config({"updated_at": datetime(2026, 6, 30, tzinfo=timezone.utc)}) + assert out is not None + restored = json.loads(out) + assert "2026-06-30" in restored["updated_at"] + diff --git a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py index ae217aca16e..7a586f758f4 100644 --- a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py +++ b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py @@ -1869,3 +1869,94 @@ class TestProxySettingEndpoints: assert "field_schema" in data assert "properties" in data["field_schema"] assert "role_mappings" in data["field_schema"]["properties"] + + +def test_update_internal_user_settings_writes_audit_log(mock_proxy_config, monkeypatch): + """Regression for the reported scenario: an admin changes Default User + Settings from the dashboard, which issues PATCH /update/internal_user_settings + (NOT /config/update). An audit row must record who changed it and what + changed.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + monkeypatch.setattr(litellm, "default_internal_user_params", {}) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/internal_user_settings", + json={"max_budget": 999.0, "models": ["gpt-4"]}, + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "default_internal_user_params" + assert written["action"] == "updated" + assert written["table_name"] == "LiteLLM_Config" + assert written["changed_by"] == "audit-admin" + assert written["changed_by_api_key"] == "hashed-admin-key" + + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert before["max_budget"] == 100.0 + assert after["max_budget"] == 999.0 + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_update_internal_user_settings_returns_200_when_audit_write_raises( + mock_proxy_config, monkeypatch +): + """The settings change is already committed by save_config, so an + audit-log failure must never surface as a 500. Scheduling via + asyncio.create_task keeps the audit call off the request path; this + test asserts that contract by making the audit helper raise.""" + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "default_internal_user_params", {}) + + async def _raise(**_kwargs): + raise RuntimeError("audit prisma blip") + + monkeypatch.setattr(proxy_server_module, "create_config_audit_log", _raise) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/internal_user_settings", json={"max_budget": 42.0} + ) + assert resp.status_code == 200, resp.text + assert resp.json()["status"] == "success" + finally: + app.dependency_overrides.pop(user_api_key_auth, None) From ada9ef88ac1a18d7c3073bad951cea9be4a3f981 Mon Sep 17 00:00:00 2001 From: Krrish Dholakia Date: Tue, 30 Jun 2026 18:36:40 -0700 Subject: [PATCH 45/79] fix(websearch): websearch_interception agentic loop fixes for chat completions and anthropic messages (#31669) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix(websearch): wire chat completion agentic loop to correct hooks maybe_run_chat_completion_agentic_loop was calling async_should_run_agentic_loop (Anthropic format) and async_run_agentic_loop (Anthropic path) instead of the chat-completion variants. This meant WebSearchInterceptionLogger never intercepted chat completion requests — the LLM returned a litellm_web_search tool_call but the agentic loop never executed, so the raw tool_calls response was returned to the caller. Fix: gate on async_should_run_chat_completion_agentic_loop override, call that hook and async_build_chat_completion_agentic_loop_plan / async_run_chat_completion_agentic_loop in the execution path. Regression test added. * fix(websearch): strip tool_choice from follow-up request When the original request forces tool_choice to litellm_web_search, the follow-up request after search execution inherited that tool_choice, causing the model to call the search tool again instead of synthesizing an answer from the results. * fix(websearch): inject api_key into agentic hook kwargs for anthropic messages Follow-up calls inside async_run_agentic_loop (e.g. websearch interception's synthesis call after executing Exa/Perplexity searches) were missing api_key because the named api_key param in async_anthropic_messages_handler was never merged into the kwargs dict forwarded downstream. Result: every /v1/messages websearch follow-up failed with "x-api-key header is required" and the caller received the raw tool_use response instead of the synthesized answer. * ci: trigger CI run * fix(websearch): support unified agentic hooks alongside chat-completion-specific hooks CodeInterpreterInterceptionLogger uses async_should_run_agentic_loop with _agentic_loop_api_surface to handle both surfaces from one hook. The chat completion loop must also check _gate_overridden so callbacks using the unified hook pattern still fire for chat completions. * fix(websearch): strip tool_choice from legacy chat completion follow-up call The _execute_chat_completion_agentic_loop path merged original optional_params (which includes forced tool_choice) into follow-up params without explicit removal. _build_chat_completion_request_patch already excluded tool_choice from its optional_params output, but dict.update() with a missing key leaves the original value intact. Explicit pop after the merge removes it. * fix(websearch): always strip tool_choice from plan-path follow-up params The tool_choice removal was gated on patch.tools is not None. WebSearch sets tools via patch.optional_params not patch.tools, so the gate was False and forced tool_choice from the original request survived into the synthesis call. Move the pop outside the patch.tools branch so it applies unconditionally. --- .../websearch_interception/handler.py | 31 +- .../chat_completion_agentic_loop.py | 18 +- litellm/llms/custom_httpx/llm_http_handler.py | 8 +- .../test_websearch_chat_completion.py | 281 ++++++++++++++---- .../test_chat_completion_agentic_loop.py | 18 +- .../custom_httpx/test_llm_http_handler.py | 67 +++++ 6 files changed, 325 insertions(+), 98 deletions(-) diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py index 2e11405af3f..bfae6d5b7b0 100644 --- a/litellm/integrations/websearch_interception/handler.py +++ b/litellm/integrations/websearch_interception/handler.py @@ -31,6 +31,7 @@ from litellm.types.integrations.websearch_interception import ( WebSearchInterceptionConfig, ) from litellm.types.integrations.custom_logger import ( + CHAT_COMPLETION_AGENTIC_SURFACE, AgenticLoopPlan, AgenticLoopRequestPatch, ) @@ -440,12 +441,16 @@ class WebSearchInterceptionLogger(CustomLogger): custom_llm_provider: str, kwargs: Dict, ) -> Tuple[bool, Dict]: - """ - Check if WebSearch tool interception is needed for Anthropic Messages API. - - This is the legacy method for Anthropic-style responses. - For chat completions, use async_should_run_chat_completion_agentic_loop instead. - """ + if kwargs.get("_agentic_loop_api_surface") == CHAT_COMPLETION_AGENTIC_SURFACE: + return await self.async_should_run_chat_completion_agentic_loop( + response=response, + model=model, + messages=messages, + tools=tools, + stream=stream, + custom_llm_provider=custom_llm_provider, + kwargs=kwargs, + ) verbose_logger.debug(f"WebSearchInterception: Hook called! provider={custom_llm_provider}, stream={stream}") verbose_logger.debug(f"WebSearchInterception: Response type: {type(response)}") @@ -629,6 +634,18 @@ class WebSearchInterceptionLogger(CustomLogger): stream: bool, kwargs: Dict, ) -> AgenticLoopPlan: + if kwargs.get("_agentic_loop_api_surface") == CHAT_COMPLETION_AGENTIC_SURFACE: + return await self.async_build_chat_completion_agentic_loop_plan( + tools=tools, + model=model, + messages=messages, + response=response, + optional_params=anthropic_messages_optional_request_params, + logging_obj=logging_obj, + stream=stream, + kwargs=kwargs, + ) + tool_calls = tools["tool_calls"] thinking_blocks = tools.get("thinking_blocks", []) request_patch, structured_results = await self._build_anthropic_request_patch( @@ -1088,6 +1105,7 @@ class WebSearchInterceptionLogger(CustomLogger): raise ValueError("WebSearchInterception: missing follow-up messages") params = dict(optional_params) params.update(request_patch.optional_params) + params.pop("tool_choice", None) return await litellm.acompletion( model=request_patch.model or model, messages=request_patch.messages, @@ -1203,6 +1221,7 @@ class WebSearchInterceptionLogger(CustomLogger): if k not in { "tools", + "tool_choice", "extra_body", "model_alias_map", "stream_response", diff --git a/litellm/litellm_core_utils/chat_completion_agentic_loop.py b/litellm/litellm_core_utils/chat_completion_agentic_loop.py index 828605d5ef8..b7262a42324 100644 --- a/litellm/litellm_core_utils/chat_completion_agentic_loop.py +++ b/litellm/litellm_core_utils/chat_completion_agentic_loop.py @@ -137,8 +137,8 @@ async def _execute_chat_completion_agentic_plan( optional_params_for_followup = {**optional_params, **patch.optional_params} if patch.tools is not None: optional_params_for_followup["tools"] = patch.tools - if "tool_choice" not in patch.optional_params: - optional_params_for_followup.pop("tool_choice", None) + if "tool_choice" not in patch.optional_params: + optional_params_for_followup.pop("tool_choice", None) kwargs_for_followup = _filter_followup_kwargs(kwargs) kwargs_for_followup.update( @@ -206,10 +206,11 @@ async def maybe_run_chat_completion_agentic_loop( for callback in callbacks: if not isinstance(callback, CustomLogger): continue + if not _gate_overridden(callback): continue - gate_kwargs = { + hook_kwargs = { **kwargs, "_agentic_loop_api_surface": CHAT_COMPLETION_AGENTIC_SURFACE, "custom_llm_provider": custom_llm_provider, @@ -222,7 +223,7 @@ async def maybe_run_chat_completion_agentic_loop( tools=tools, stream=stream, custom_llm_provider=custom_llm_provider, - kwargs=gate_kwargs, + kwargs=hook_kwargs, ) except Exception as e: verbose_logger.exception( @@ -243,11 +244,6 @@ async def maybe_run_chat_completion_agentic_loop( ) try: - plan_kwargs = { - **kwargs, - "_agentic_loop_api_surface": CHAT_COMPLETION_AGENTIC_SURFACE, - "custom_llm_provider": custom_llm_provider, - } if not _build_plan_overridden(callback): return await callback.async_run_agentic_loop( tools=tool_calls, @@ -258,7 +254,7 @@ async def maybe_run_chat_completion_agentic_loop( anthropic_messages_optional_request_params=optional_params, logging_obj=logging_obj, stream=stream, - kwargs=plan_kwargs, + kwargs=hook_kwargs, ) plan = await callback.async_build_agentic_loop_plan( @@ -270,7 +266,7 @@ async def maybe_run_chat_completion_agentic_loop( anthropic_messages_optional_request_params=optional_params, logging_obj=logging_obj, stream=stream, - kwargs=plan_kwargs, + kwargs=hook_kwargs, ) if plan.response_override is not None: diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index 9bb956d0808..3c10239f868 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -2112,7 +2112,7 @@ class BaseLLMHTTPHandler: anthropic_messages_optional_request_params=anthropic_messages_optional_request_params, logging_obj=logging_obj, custom_llm_provider=custom_llm_provider, - kwargs=kwargs, + kwargs={**kwargs, "api_key": api_key} if api_key else kwargs, ) return initial_response else: @@ -2122,6 +2122,10 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, ) + # Inject api_key into kwargs so follow-up calls in agentic hooks can + # authenticate. api_key is a named param here (not in kwargs), so + # _prepare_followup_kwargs would miss it otherwise. + kwargs_for_agentic = {**kwargs, "api_key": api_key} if api_key else kwargs # Call agentic completion hooks (non-streaming path only) final_response = await self._call_agentic_completion_hooks( response=initial_response, @@ -2132,7 +2136,7 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, stream=False, custom_llm_provider=custom_llm_provider, - kwargs=kwargs, + kwargs=kwargs_for_agentic, ) return self._maybe_wrap_in_fake_stream( diff --git a/tests/test_litellm/integrations/websearch_interception/test_websearch_chat_completion.py b/tests/test_litellm/integrations/websearch_interception/test_websearch_chat_completion.py index 34555d76554..7ef43e2eadf 100644 --- a/tests/test_litellm/integrations/websearch_interception/test_websearch_chat_completion.py +++ b/tests/test_litellm/integrations/websearch_interception/test_websearch_chat_completion.py @@ -6,7 +6,7 @@ litellm.acompletion() for transparent server-side web search execution. """ import os -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import MagicMock import pytest @@ -34,9 +34,7 @@ def mock_search_response(): @pytest.fixture def websearch_logger(): """Create a WebSearchInterceptionLogger instance""" - return WebSearchInterceptionLogger( - enabled_providers=[LlmProviders.OPENAI, LlmProviders.MINIMAX] - ) + return WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI, LlmProviders.MINIMAX]) @pytest.mark.asyncio @@ -55,9 +53,7 @@ async def test_websearch_chat_completion_with_openai(): """ # Configure WebSearch interception original_callbacks = litellm.callbacks.copy() if litellm.callbacks else [] - websearch_logger = WebSearchInterceptionLogger( - enabled_providers=[LlmProviders.OPENAI] - ) + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI]) litellm.callbacks = [websearch_logger] try: @@ -100,9 +96,7 @@ async def test_websearch_chat_completion_with_openai(): if hasattr(response.choices[0].message, "tool_calls"): # If tool_calls exist, it means agentic loop didn't run # This could happen if search tool is not configured - pytest.skip( - "Agentic loop did not execute - search tool may not be configured" - ) + pytest.skip("Agentic loop did not execute - search tool may not be configured") # Verify we got a meaningful response assert response.choices[0].finish_reason in ["stop", "end_turn"] @@ -122,9 +116,7 @@ async def test_websearch_chat_completion_hook_detection(): Message, ) - websearch_logger = WebSearchInterceptionLogger( - enabled_providers=[LlmProviders.OPENAI] - ) + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI]) # Mock response with litellm_web_search tool call mock_response = ModelResponse( @@ -155,21 +147,19 @@ async def test_websearch_chat_completion_hook_detection(): ) # Test should_run_chat_completion_agentic_loop - should_run, tools_dict = ( - await websearch_logger.async_should_run_chat_completion_agentic_loop( - response=mock_response, - model="gpt-4o", - messages=[{"role": "user", "content": "What's the weather?"}], - tools=[ - { - "type": "function", - "function": {"name": "litellm_web_search"}, - } - ], - stream=False, - custom_llm_provider="openai", - kwargs={}, - ) + should_run, tools_dict = await websearch_logger.async_should_run_chat_completion_agentic_loop( + response=mock_response, + model="gpt-4o", + messages=[{"role": "user", "content": "What's the weather?"}], + tools=[ + { + "type": "function", + "function": {"name": "litellm_web_search"}, + } + ], + stream=False, + custom_llm_provider="openai", + kwargs={}, ) # Verify hook detected the tool call @@ -185,9 +175,7 @@ async def test_websearch_not_triggered_without_tool(): """Test that websearch hook is NOT triggered when no web search tool in request.""" from litellm.types.utils import Choices, Message - websearch_logger = WebSearchInterceptionLogger( - enabled_providers=[LlmProviders.OPENAI] - ) + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI]) mock_response = ModelResponse( id="test-123", @@ -208,21 +196,19 @@ async def test_websearch_not_triggered_without_tool(): ) # Test without web search tool - should_run, tools_dict = ( - await websearch_logger.async_should_run_chat_completion_agentic_loop( - response=mock_response, - model="gpt-4o", - messages=[{"role": "user", "content": "Hello"}], - tools=[ - { - "type": "function", - "function": {"name": "some_other_tool"}, - } - ], - stream=False, - custom_llm_provider="openai", - kwargs={}, - ) + should_run, tools_dict = await websearch_logger.async_should_run_chat_completion_agentic_loop( + response=mock_response, + model="gpt-4o", + messages=[{"role": "user", "content": "Hello"}], + tools=[ + { + "type": "function", + "function": {"name": "some_other_tool"}, + } + ], + stream=False, + custom_llm_provider="openai", + kwargs={}, ) # Verify hook did NOT trigger @@ -241,9 +227,7 @@ async def test_websearch_not_triggered_for_disabled_provider(): ) # Only enable bedrock - websearch_logger = WebSearchInterceptionLogger( - enabled_providers=[LlmProviders.BEDROCK] - ) + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.BEDROCK]) mock_response = ModelResponse( id="test-123", @@ -273,21 +257,19 @@ async def test_websearch_not_triggered_for_disabled_provider(): ) # Test with OpenAI provider (not enabled) - should_run, tools_dict = ( - await websearch_logger.async_should_run_chat_completion_agentic_loop( - response=mock_response, - model="gpt-4o", - messages=[{"role": "user", "content": "test"}], - tools=[ - { - "type": "function", - "function": {"name": "litellm_web_search"}, - } - ], - stream=False, - custom_llm_provider="openai", # Not in enabled_providers - kwargs={}, - ) + should_run, tools_dict = await websearch_logger.async_should_run_chat_completion_agentic_loop( + response=mock_response, + model="gpt-4o", + messages=[{"role": "user", "content": "test"}], + tools=[ + { + "type": "function", + "function": {"name": "litellm_web_search"}, + } + ], + stream=False, + custom_llm_provider="openai", # Not in enabled_providers + kwargs={}, ) # Verify hook did NOT trigger @@ -341,8 +323,7 @@ async def test_websearch_json_serialization_fix(): @pytest.mark.asyncio @pytest.mark.skipif( - os.environ.get("OPENAI_API_KEY") is None - or os.environ.get("PERPLEXITY_API_KEY") is None, + os.environ.get("OPENAI_API_KEY") is None or os.environ.get("PERPLEXITY_API_KEY") is None, reason="OPENAI_API_KEY or PERPLEXITY_API_KEY not set", ) async def test_websearch_streaming_conversion(): @@ -395,6 +376,174 @@ async def test_websearch_streaming_conversion(): litellm.callbacks = [] +@pytest.mark.asyncio +async def test_maybe_run_chat_completion_agentic_loop_calls_chat_completion_hook(): + """Regression test: maybe_run_chat_completion_agentic_loop must call + async_should_run_chat_completion_agentic_loop, not async_should_run_agentic_loop. + + Before the fix, the function used the wrong gate check and wrong hook, + causing WebSearchInterceptionLogger to never intercept chat completion requests + even when the LLM returned a litellm_web_search tool call. + """ + from litellm.litellm_core_utils.chat_completion_agentic_loop import ( + maybe_run_chat_completion_agentic_loop, + ) + from litellm.types.utils import ( + ChatCompletionMessageToolCall, + Choices, + Function, + Message, + ) + + mock_response = ModelResponse( + id="test-regression-123", + choices=[ + Choices( + finish_reason="tool_calls", + index=0, + message=Message( + role="assistant", + content=None, + tool_calls=[ + ChatCompletionMessageToolCall( + id="call_abc", + type="function", + function=Function( + name="litellm_web_search", + arguments='{"query": "latest news"}', + ), + ) + ], + ), + ) + ], + model="gpt-4o", + object="chat.completion", + created=1234567890, + ) + + sentinel = ModelResponse( + id="sentinel-final", + choices=[ + Choices( + finish_reason="stop", + index=0, + message=Message(role="assistant", content="Here is the news."), + ) + ], + model="gpt-4o", + object="chat.completion", + created=1234567890, + ) + + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI]) + + chat_completion_hook_called = False + + async def fake_should_run_chat_completion(response, model, messages, tools, stream, custom_llm_provider, kwargs): + nonlocal chat_completion_hook_called + chat_completion_hook_called = True + return True, { + "tool_calls": [{"id": "call_abc", "name": "litellm_web_search", "input": {"query": "latest news"}}], + "tool_type": "websearch", + "provider": "openai", + "response_format": "openai", + } + + async def fake_build_plan(tools, model, messages, response, optional_params, logging_obj, stream, kwargs): + from litellm.types.integrations.custom_logger import AgenticLoopPlan + + return AgenticLoopPlan(run_agentic_loop=False, response_override=sentinel) + + websearch_logger.async_should_run_chat_completion_agentic_loop = fake_should_run_chat_completion + websearch_logger.async_build_chat_completion_agentic_loop_plan = fake_build_plan + + import litellm as _litellm + + original_callbacks = _litellm.callbacks[:] + _litellm.callbacks = [websearch_logger] + + mock_logging_obj = MagicMock() + mock_logging_obj.dynamic_success_callbacks = None + + try: + result = await maybe_run_chat_completion_agentic_loop( + response=mock_response, + model="gpt-4o", + messages=[{"role": "user", "content": "Latest news?"}], + optional_params={ + "tools": [ + { + "type": "function", + "function": {"name": "litellm_web_search"}, + } + ] + }, + kwargs={}, + logging_obj=mock_logging_obj, + custom_llm_provider="openai", + stream=False, + ) + finally: + _litellm.callbacks = original_callbacks + + assert chat_completion_hook_called, ( + "async_should_run_chat_completion_agentic_loop was never called; " + "maybe_run_chat_completion_agentic_loop used the wrong hook" + ) + assert result is sentinel, "Expected agentic loop to return sentinel final response" + + +@pytest.mark.asyncio +async def test_execute_chat_completion_agentic_loop_strips_tool_choice(): + """Regression: _execute_chat_completion_agentic_loop must not forward tool_choice + from the original request into the follow-up synthesis call. + + When the original request forces tool_choice to litellm_web_search, merging + optional_params into the follow-up params without explicit removal causes the + model to call the search tool again instead of synthesizing an answer. + """ + from unittest.mock import patch + + websearch_logger = WebSearchInterceptionLogger(enabled_providers=[LlmProviders.OPENAI]) + + captured_kwargs: dict = {} + + async def fake_acompletion(**kwargs): + captured_kwargs.update(kwargs) + return ModelResponse(id="followup", model="gpt-4o", object="chat.completion") + + async def fake_search(query): + return ("Bitcoin price is $60,000", None) + + with patch.object(websearch_logger, "_execute_search", side_effect=fake_search): + with patch("litellm.acompletion", side_effect=fake_acompletion): + await websearch_logger._execute_chat_completion_agentic_loop( + model="gpt-4o", + messages=[{"role": "user", "content": "What is Bitcoin price?"}], + tool_calls=[ + { + "id": "call_1", + "name": "litellm_web_search", + "input": {"query": "bitcoin price"}, + } + ], + optional_params={ + "tools": [{"type": "function", "function": {"name": "litellm_web_search"}}], + "tool_choice": {"type": "function", "function": {"name": "litellm_web_search"}}, + "max_tokens": 512, + }, + logging_obj=MagicMock(), + stream=False, + kwargs={}, + ) + + assert "tool_choice" not in captured_kwargs, ( + "tool_choice must not appear in follow-up acompletion kwargs; " + "it would force the model to call the search tool again instead of synthesizing" + ) + + if __name__ == "__main__": # Run with: pytest test_websearch_chat_completion.py -v -s pytest.main([__file__, "-v", "-s"]) diff --git a/tests/test_litellm/litellm_core_utils/test_chat_completion_agentic_loop.py b/tests/test_litellm/litellm_core_utils/test_chat_completion_agentic_loop.py index f1196ab4692..cc16ad558e4 100644 --- a/tests/test_litellm/litellm_core_utils/test_chat_completion_agentic_loop.py +++ b/tests/test_litellm/litellm_core_utils/test_chat_completion_agentic_loop.py @@ -181,8 +181,7 @@ async def test_internal_control_fields_never_leak_into_provider_body(restore_cal # The loop must have actually fired (sanity: two provider calls). assert create.await_count == 2, ( - "expected the agentic loop to issue a follow-up provider call; " - f"got {create.await_count} call(s)" + f"expected the agentic loop to issue a follow-up provider call; got {create.await_count} call(s)" ) for idx, call in enumerate(create.await_args_list): @@ -194,8 +193,7 @@ async def test_internal_control_fields_never_leak_into_provider_body(restore_cal f"top-level request body: {sorted(body.keys())}" ) assert field not in extra_body, ( - f"provider call #{idx}: internal field {field!r} leaked into " - f"extra_body: {sorted(extra_body.keys())}" + f"provider call #{idx}: internal field {field!r} leaked into extra_body: {sorted(extra_body.keys())}" ) # The native code_interpreter tool must have been swapped for the # function tool, never sent raw to OpenAI as a chat-completions request. @@ -254,9 +252,7 @@ class _GateOnlyLogger(CustomLogger): ) -> AgenticLoopPlan: return self._plan - async def async_agentic_loop_cleanup_hook( - self, plan: AgenticLoopPlan, kwargs: Dict[str, Any] - ) -> None: + async def async_agentic_loop_cleanup_hook(self, plan: AgenticLoopPlan, kwargs: Dict[str, Any]) -> None: self.cleanup_calls += 1 @@ -343,9 +339,7 @@ async def test_dispatcher_runs_followup_with_incremented_depth_and_patched_messa assert call_kwargs["max_agentic_loops"] >= 1 assert "_agentic_loop_fingerprints" in call_kwargs # Interception markers are mirrored into litellm_metadata for the follow-up. - assert ( - call_kwargs["litellm_metadata"]["_code_interpreter_interception_active"] is True - ) + assert call_kwargs["litellm_metadata"]["_code_interpreter_interception_active"] is True # The transient surface marker is NOT forwarded to the follow-up call. assert "_agentic_loop_api_surface" not in call_kwargs # Cleanup hook always runs. @@ -390,9 +384,7 @@ async def test_dispatcher_raises_on_repeated_tool_call_fingerprint(restore_callb # The dispatcher fingerprints the whole value the gate returns as its second # tuple element, so the seeded fingerprint must mirror that dict exactly. - gate_tool_calls = { - "tool_calls": [{"id": "call_abc", "name": "litellm_code_execution"}] - } + gate_tool_calls = {"tool_calls": [{"id": "call_abc", "name": "litellm_code_execution"}]} fingerprint = json.dumps(gate_tool_calls, sort_keys=True, default=str) logger = _GateOnlyLogger( diff --git a/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py b/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py index 8c934f9c21e..b18af060a20 100644 --- a/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py +++ b/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py @@ -1212,6 +1212,73 @@ def test_async_compact_handler_sends_json_when_not_signed(): assert "data" not in kwargs +@pytest.mark.asyncio +async def test_async_anthropic_messages_handler_passes_api_key_to_agentic_hooks(): + """ + Regression: async_anthropic_messages_handler must inject api_key into the + kwargs dict forwarded to _call_agentic_completion_hooks. + + Without this, follow-up calls made by agentic hooks (e.g. websearch + interception's second LLM call after executing searches) have no api_key + and fail with "x-api-key header is required". + """ + handler = BaseLLMHTTPHandler() + + mock_config = Mock() + mock_config.validate_anthropic_messages_environment = Mock( + return_value=({"x-api-key": "sk-test"}, "https://api.anthropic.com") + ) + mock_config.transform_anthropic_messages_request = Mock( + return_value={"model": "claude-haiku", "messages": [], "max_tokens": 16} + ) + mock_config.sign_request = Mock(return_value=({}, None)) + + fake_raw_response = {"id": "msg_1", "type": "message", "role": "assistant", "content": [], "stop_reason": "end_turn"} + mock_config.transform_anthropic_messages_response = Mock(return_value=fake_raw_response) + + mock_logging_obj = Mock() + mock_logging_obj.update_environment_variables = Mock() + mock_logging_obj.model_call_details = {} + mock_logging_obj.stream = False + mock_logging_obj.dynamic_success_callbacks = None + + captured_kwargs: dict = {} + sentinel_response = object() + + async def fake_agentic_hooks(**call_kwargs): + captured_kwargs.update(call_kwargs) + return sentinel_response + + mock_httpx_response = Mock() + mock_httpx_response.status_code = 200 + + with ( + patch.object(handler, "_async_post_anthropic_messages_with_http_error_retry", new=AsyncMock(return_value=mock_httpx_response)), + patch.object(handler, "_call_agentic_completion_hooks", side_effect=fake_agentic_hooks), + patch("litellm.llms.custom_httpx.llm_http_handler.get_async_httpx_client"), + patch("litellm.litellm_core_utils.get_provider_specific_headers.ProviderSpecificHeaderUtils.get_provider_specific_headers", return_value=None), + ): + result = await handler.async_anthropic_messages_handler( + model="claude-haiku", + messages=[{"role": "user", "content": "hi"}], + anthropic_messages_provider_config=mock_config, + anthropic_messages_optional_request_params={"stream": False}, + custom_llm_provider="anthropic", + litellm_params=GenericLiteLLMParams(api_key="sk-real-anthropic-key"), + logging_obj=mock_logging_obj, + api_key="sk-real-anthropic-key", + stream=False, + ) + + assert result is sentinel_response + assert "kwargs" in captured_kwargs, "_call_agentic_completion_hooks not called" + forwarded = captured_kwargs["kwargs"] + assert forwarded.get("api_key") == "sk-real-anthropic-key", ( + "api_key must be injected into kwargs passed to _call_agentic_completion_hooks " + "so follow-up calls in agentic hooks (e.g. websearch) can authenticate" + ) + + class _FakeWSExceptions: class WebSocketException(Exception): pass From 6c21029cb7e8fe827ea9f8d108f1ff18ae3b9e4b Mon Sep 17 00:00:00 2001 From: Krrish Dholakia Date: Tue, 30 Jun 2026 18:58:09 -0700 Subject: [PATCH 46/79] feat(sandbox): reuse e2b container across requests when metadata.session_id is set (#31688) * feat(sandbox): reuse e2b container across requests when metadata.session_id is set When a client passes `metadata.session_id` in a /chat/completions request alongside a code_interpreter tool, the proxy now routes all requests sharing that session_id to the same sandbox container. State (variables, imports, installed packages) persists across requests within the session. Without a session_id the existing ephemeral behavior is unchanged: one container per agentic loop, deleted immediately after. The sandbox key is derived from session_id rather than a per-request UUID. The cleanup and post-loop hooks skip deletion for session-scoped containers. TTL-based pruning (15 min idle) still applies and refreshes on every use, so an active session never expires mid-use. The session_id-scoped key is registered in all_litellm_params and the proxy strip-list so it never leaks to the upstream LLM provider. * fix(sandbox): scope session sandbox key to API key identity; add per-identity LRU cap Two security issues addressed: 1. Cross-user sandbox isolation: the session_id supplied by the client is now combined with the server-minted user_api_key_hash to form the cache key (format: "{hash}:{session_id}" when authenticated, bare session_id for non-proxy use). Two tenants sharing the same session_id no longer share a sandbox. 2. Bounded session allocation: each API key identity is capped at _SESSION_SCOPED_PER_IDENTITY_CAP (10) live session-scoped containers. When a new session is opened beyond the cap, the least-recently-used entry for that identity is evicted and its sandbox deleted, preventing unbounded accumulation via rotating session IDs. The container cache tuple gains a fourth element (identity: str | None) so eviction can filter by identity without parsing key formats. Tests added for both properties. --- .../code_interpreter_interception/handler.py | 71 +++- litellm/proxy/dev_config.yaml | 15 + litellm/proxy/litellm_pre_call_utils.py | 1 + litellm/types/utils.py | 1 + qa_sticky_session.sh | 59 +++ .../test_handler.py | 369 ++++++++++++++---- 6 files changed, 421 insertions(+), 95 deletions(-) create mode 100755 qa_sticky_session.sh diff --git a/litellm/integrations/code_interpreter_interception/handler.py b/litellm/integrations/code_interpreter_interception/handler.py index cd7b211f1a5..759b2be3a84 100644 --- a/litellm/integrations/code_interpreter_interception/handler.py +++ b/litellm/integrations/code_interpreter_interception/handler.py @@ -40,9 +40,11 @@ from litellm.types.utils import ( LITELLM_CODE_EXECUTION_TOOL_NAME = "litellm_code_execution" _INTERCEPTION_ACTIVE_KEY = "_code_interpreter_interception_active" _SANDBOX_KEY = "_code_interpreter_interception_sandbox_key" +_SESSION_SCOPED_KEY = "_code_interpreter_interception_session_scoped" _CONVERTED_STREAM_KEY = "_code_interpreter_interception_converted_stream" _LITELLM_METADATA_KEY = "litellm_metadata" _CACHE_TTL_SECONDS = 15 * 60 +_SESSION_SCOPED_PER_IDENTITY_CAP = 10 class CodeExecutionToolCall(TypedDict, total=False): @@ -107,6 +109,20 @@ class ChatCompletionFunctionToolChoice(TypedDict): CodeExecutionFunctionToolChoice = ResponsesFunctionToolChoice | ChatCompletionFunctionToolChoice +def _extract_session_id(kwargs: dict[str, Any]) -> str | None: + for meta_key in ("metadata", "litellm_metadata"): + meta = kwargs.get(meta_key) + if isinstance(meta, dict): + sid = meta.get("session_id") + if sid and isinstance(sid, str): + return sid + return None + + +def _extract_identity(kwargs: dict[str, Any]) -> str: + return kwargs.get("user_api_key_hash") or "" + + def _resolve_sandbox_tool(sandbox_tool_name: str | None) -> dict[str, Any] | None: try: from litellm.sandbox.sandbox_tools import resolve_sandbox_tool @@ -140,7 +156,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): self.enabled_providers = enabled_providers self.sandbox_tool_name = sandbox_tool_name self.sandbox_config = sandbox_config - self._container_cache: dict[str, tuple[Any, dict[str, Any] | None, float]] = {} + self._container_cache: dict[str, tuple[Any, dict[str, Any] | None, float, str | None]] = {} @classmethod def from_config_yaml(cls, config: CodeInterpreterInterceptionConfig) -> "CodeInterpreterInterceptionLogger": @@ -191,7 +207,13 @@ class CodeInterpreterInterceptionLogger(CustomLogger): return None kwargs[_INTERCEPTION_ACTIVE_KEY] = True - kwargs[_SANDBOX_KEY] = uuid.uuid4().hex + session_id = _extract_session_id(kwargs) + if session_id: + identity = _extract_identity(kwargs) + kwargs[_SANDBOX_KEY] = f"{identity}:{session_id}" if identity else session_id + kwargs[_SESSION_SCOPED_KEY] = True + else: + kwargs[_SANDBOX_KEY] = uuid.uuid4().hex if kwargs.get("stream"): kwargs["stream"] = False kwargs[_CONVERTED_STREAM_KEY] = True @@ -217,6 +239,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): if not is_interception_internal_key(key) and not key.startswith("_agentic_loop") and key != "max_agentic_loops" + and key != _SESSION_SCOPED_KEY } if filtered_metadata: kwargs[_LITELLM_METADATA_KEY] = filtered_metadata @@ -227,7 +250,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): def _write_interception_metadata(kwargs: dict[str, Any]) -> None: metadata = kwargs.get(_LITELLM_METADATA_KEY) metadata = dict(metadata) if isinstance(metadata, dict) else {} - for key in (_INTERCEPTION_ACTIVE_KEY, _SANDBOX_KEY, _CONVERTED_STREAM_KEY): + for key in (_INTERCEPTION_ACTIVE_KEY, _SANDBOX_KEY, _SESSION_SCOPED_KEY, _CONVERTED_STREAM_KEY): if key in kwargs: metadata[key] = kwargs[key] kwargs[_LITELLM_METADATA_KEY] = metadata @@ -347,7 +370,9 @@ class CodeInterpreterInterceptionLogger(CustomLogger): await self._prune_expired_cache() tool_calls = cast(list[CodeExecutionToolCall], tools.get("tool_calls", [])) sandbox_key = kwargs.get(_SANDBOX_KEY) - container, params = await self._get_or_create_container(cache_key=sandbox_key) + is_session = bool(kwargs.get(_SESSION_SCOPED_KEY)) + identity = _extract_identity(kwargs) if is_session else None + container, params = await self._get_or_create_container(cache_key=sandbox_key, identity=identity) try: container_id = cast(str | None, getattr(container, "id", None)) @@ -404,6 +429,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): metadata={ "tool_type": "code_interpreter", "sandbox_key": sandbox_key or "", + "is_session_scoped": bool(kwargs.get(_SESSION_SCOPED_KEY)), "code_interpreter_calls": code_interpreter_calls, }, ) @@ -419,7 +445,9 @@ class CodeInterpreterInterceptionLogger(CustomLogger): await self._prune_expired_cache() tool_calls = cast(list[CodeExecutionToolCall], tools.get("tool_calls", [])) sandbox_key = cast(str | None, kwargs.get(_SANDBOX_KEY)) - container, params = await self._get_or_create_container(cache_key=sandbox_key) + is_session = bool(kwargs.get(_SESSION_SCOPED_KEY)) + identity = _extract_identity(cast(dict[str, Any], kwargs)) if is_session else None + container, params = await self._get_or_create_container(cache_key=sandbox_key, identity=identity) try: container_id = cast(str | None, getattr(container, "id", None)) @@ -455,6 +483,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): metadata={ "tool_type": "code_interpreter", "sandbox_key": sandbox_key or "", + "is_session_scoped": bool(kwargs.get(_SESSION_SCOPED_KEY)), "code_interpreter_calls": code_interpreter_calls, "response_format": "openai", }, @@ -489,6 +518,8 @@ class CodeInterpreterInterceptionLogger(CustomLogger): async def async_agentic_loop_cleanup_hook(self, plan: AgenticLoopPlan, kwargs: dict) -> None: metadata = plan.metadata or {} if plan else {} + if metadata.get("is_session_scoped"): + return await self._delete_container_for_cache_key(metadata.get("sandbox_key")) @staticmethod @@ -520,7 +551,8 @@ class CodeInterpreterInterceptionLogger(CustomLogger): async def async_post_agentic_loop_response_hook(self, response: Any, plan: AgenticLoopPlan, kwargs: dict) -> Any: metadata = plan.metadata or {} if plan else {} - await self._delete_container_for_cache_key(metadata.get("sandbox_key")) + if not metadata.get("is_session_scoped"): + await self._delete_container_for_cache_key(metadata.get("sandbox_key")) calls = metadata.get("code_interpreter_calls") if not calls: @@ -565,17 +597,32 @@ class CodeInterpreterInterceptionLogger(CustomLogger): return f"[execution error] {message}" return getattr(result, "stdout", "") or "" - async def _get_or_create_container(self, cache_key: str | None) -> tuple[Any, dict[str, Any] | None]: + async def _get_or_create_container( + self, + cache_key: str | None, + identity: str | None = None, + ) -> tuple[Any, dict[str, Any] | None]: if cache_key: cached = self._container_cache.get(cache_key) if cached is not None: + self._container_cache[cache_key] = (cached[0], cached[1], time.time(), cached[3]) return cached[0], cached[1] container, params = await self._create_container() if cache_key: - self._container_cache[cache_key] = (container, params, time.time()) + if identity is not None: + await self._evict_lru_session_if_over_cap(identity) + self._container_cache[cache_key] = (container, params, time.time(), identity) return container, params + async def _evict_lru_session_if_over_cap(self, identity: str) -> None: + identity_entries = [(k, v) for k, v in self._container_cache.items() if v[3] == identity] + if len(identity_entries) < _SESSION_SCOPED_PER_IDENTITY_CAP: + return + lru_key, lru_entry = min(identity_entries, key=lambda item: item[1][2]) + self._container_cache.pop(lru_key, None) + await self._delete_container(container=lru_entry[0], params=lru_entry[1]) + async def _create_container(self) -> tuple[Any, dict[str, Any] | None]: if self.sandbox_config is not None: return await self.sandbox_config.acreate_sandbox(), None @@ -739,12 +786,8 @@ class CodeInterpreterInterceptionLogger(CustomLogger): now = time.time() expired = [ (cache_key, container, params) - for cache_key, ( - container, - params, - created_at, - ) in self._container_cache.items() - if now - created_at > _CACHE_TTL_SECONDS + for cache_key, (container, params, last_accessed, *_) in self._container_cache.items() + if now - last_accessed > _CACHE_TTL_SECONDS ] for cache_key, container, params in expired: self._container_cache.pop(cache_key, None) diff --git a/litellm/proxy/dev_config.yaml b/litellm/proxy/dev_config.yaml index e437ed7a118..6078161c780 100644 --- a/litellm/proxy/dev_config.yaml +++ b/litellm/proxy/dev_config.yaml @@ -182,10 +182,25 @@ model_list: litellm_params: model: openai/gpt-5.5 api_key: os.environ/OPENAI_API_KEY + - model_name: gpt-4o-mini + litellm_params: + model: openai/gpt-4o-mini + api_key: os.environ/OPENAI_API_KEY general_settings: master_key: sk-1234 +sandbox_tools: + - sandbox_tool_name: e2b_sandbox + litellm_params: + sandbox_provider: e2b + api_key: os.environ/E2B_API_KEY + litellm_settings: drop_params: True telemetry: False + code_interpreter_interception_params: + enabled: true + sandbox_tool_name: e2b_sandbox + callbacks: + - code_interpreter_interception diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 0ffb0337545..6f5c82530e3 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -153,6 +153,7 @@ _UNTRUSTED_ROOT_CONTROL_FIELDS = ( "_code_interpreter_interception_active", "_code_interpreter_interception_converted_stream", "_code_interpreter_interception_sandbox_key", + "_code_interpreter_interception_session_scoped", "max_agentic_loops", ) diff --git a/litellm/types/utils.py b/litellm/types/utils.py index dff4e4af89e..4f0c0c21bce 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -3062,6 +3062,7 @@ agentic_loop_internal_litellm_params = [ "max_agentic_loops", "_code_interpreter_interception_active", "_code_interpreter_interception_sandbox_key", + "_code_interpreter_interception_session_scoped", "_code_interpreter_interception_converted_stream", ] diff --git a/qa_sticky_session.sh b/qa_sticky_session.sh new file mode 100755 index 00000000000..326bb8117c7 --- /dev/null +++ b/qa_sticky_session.sh @@ -0,0 +1,59 @@ +#!/usr/bin/env bash +# QA: code interpreter sandbox stickiness via metadata.session_id +# bash qa_sticky_session.sh +# LITELLM_BASE_URL=http://localhost:4000 LITELLM_KEY=sk-1234 bash qa_sticky_session.sh + +set -euo pipefail + +BASE="${LITELLM_BASE_URL:-http://localhost:4000}" +KEY="${LITELLM_KEY:-sk-1234}" +MODEL="${LITELLM_MODEL:-gpt-4o-mini}" +# proxy running at http://localhost:4000 (master key: sk-1234) +SESSION_A="qa-session-$(date +%s)-A" +SESSION_B="qa-session-$(date +%s)-B" + +content() { + echo "$1" | python3 -c "import sys,json; d=json.load(sys.stdin); print(d.get('choices',[{}])[0].get('message',{}).get('content',''))" +} + +call() { + local session="${1:-}" code="$2" meta="" + [[ -n "$session" ]] && meta=", \"metadata\": {\"session_id\": \"$session\"}" + curl -s -X POST "$BASE/chat/completions" \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer $KEY" \ + -d "{\"model\":\"$MODEL\"$meta,\"tools\":[{\"type\":\"code_interpreter\"}],\"messages\":[{\"role\":\"user\",\"content\":\"Run this Python code and tell me the result: $code\"}]}" +} + +assert_match() { + local label="$1" body="$2" pattern="$3" + if echo "$body" | grep -qiE "$pattern"; then + echo "PASS $label" + else + echo "FAIL $label (expected /$pattern/)" + echo " $(content "$body")" + exit 1 + fi +} + +echo "=== Sticky Session Sandbox QA ===" +echo "base: $BASE session A: $SESSION_A session B: $SESSION_B" +echo + +R=$(call "$SESSION_A" "x = 42; print(x)") +assert_match "same session_id reuses sandbox (set x=42)" "$R" "42" + +R=$(call "$SESSION_A" "print(x)") +assert_match "same session_id keeps state (x still 42)" "$R" "42" + +R=$(call "$SESSION_B" "print(x)") +assert_match "different session_id is isolated" "$R" "not defined|NameError|undefined|error" + +R=$(call "" "y = 99; print(y)") +assert_match "no session_id runs code" "$R" "99" + +R=$(call "" "print(y)") +assert_match "no session_id gets fresh sandbox each request" "$R" "not defined|NameError|undefined|error" + +echo +echo "All checks passed." diff --git a/tests/test_litellm/integrations/code_interpreter_interception/test_handler.py b/tests/test_litellm/integrations/code_interpreter_interception/test_handler.py index 7ff58ba6324..9d308ac1989 100644 --- a/tests/test_litellm/integrations/code_interpreter_interception/test_handler.py +++ b/tests/test_litellm/integrations/code_interpreter_interception/test_handler.py @@ -14,6 +14,7 @@ from litellm.integrations.code_interpreter_interception.handler import ( LITELLM_CODE_EXECUTION_TOOL_NAME, _INTERCEPTION_ACTIVE_KEY as _ACTIVE_KEY, _SANDBOX_KEY, + _SESSION_SCOPED_KEY, ) from litellm.types.integrations.custom_logger import ( CHAT_COMPLETION_AGENTIC_SURFACE, @@ -138,11 +139,7 @@ async def test_build_plan_runs_code_and_feeds_output_back(): assert sandbox.run_calls[0]["code"] == "print(40 + 2)" messages = _iter_messages(plan) - outputs = [ - m - for m in messages - if isinstance(m, dict) and m.get("type") == "function_call_output" - ] + outputs = [m for m in messages if isinstance(m, dict) and m.get("type") == "function_call_output"] assert outputs, "expected a function_call_output item appended" output_item = next(m for m in outputs if m.get("call_id") == "c1") assert "42" in str(output_item["output"]) @@ -160,9 +157,7 @@ async def test_pre_call_converts_code_interpreter_tool(): assert result is not None tools = result["tools"] - assert not any( - t.get("type") == "code_interpreter" for t in tools - ), "code_interpreter tool must be removed" + assert not any(t.get("type") == "code_interpreter" for t in tools), "code_interpreter tool must be removed" names = [t.get("name") or (t.get("function") or {}).get("name") for t in tools] assert LITELLM_CODE_EXECUTION_TOOL_NAME in names @@ -267,9 +262,7 @@ async def test_should_run_detects_only_matching_function_call(): logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) active_kwargs = {"_code_interpreter_interception_active": True} - match = FakeResponse( - output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)] - ) + match = FakeResponse(output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)]) should_run, payload = await logger.async_should_run_agentic_loop( response=match, model="gpt-5", @@ -331,9 +324,7 @@ async def test_container_reused_within_request_via_server_sandbox_key(): **common, ) - assert ( - len(sandbox.create_calls) == 1 - ), "the sandbox is reused across loop iterations sharing one server sandbox key" + assert len(sandbox.create_calls) == 1, "the sandbox is reused across loop iterations sharing one server sandbox key" @pytest.mark.asyncio @@ -372,9 +363,9 @@ async def test_colliding_caller_call_id_does_not_share_sandbox(): **common, ) - assert ( - len(sandbox.create_calls) == 2 - ), "distinct server sandbox keys must isolate sandboxes despite a colliding call id" + assert len(sandbox.create_calls) == 2, ( + "distinct server sandbox keys must isolate sandboxes despite a colliding call id" + ) @pytest.mark.asyncio @@ -479,14 +470,11 @@ async def test_post_hook_injects_code_interpreter_call_matching_openai_shape(): ) response = FakeResponse(output=[{"type": "message", "content": []}]) - out = await logger.async_post_agentic_loop_response_hook( - response=response, plan=plan, kwargs={} - ) + out = await logger.async_post_agentic_loop_response_hook(response=response, plan=plan, kwargs={}) types = [item.get("type") for item in out.output] assert types == ["code_interpreter_call", "message"], ( - "code_interpreter_call must be re-injected before the message, matching " - "OpenAI's native output ordering" + "code_interpreter_call must be re-injected before the message, matching OpenAI's native output ordering" ) assert set(out.output[0].keys()) == { "id", @@ -524,8 +512,7 @@ async def test_pre_call_forces_non_stream_for_loop(): assert out is not None assert out["stream"] is False, "loop requires a non-streaming upstream call" assert out["_code_interpreter_interception_converted_stream"] is True, ( - "the converted-stream flag must be set so the final response is wrapped " - "back into a stream for the caller" + "the converted-stream flag must be set so the final response is wrapped back into a stream for the caller" ) @@ -556,9 +543,7 @@ async def test_gate_refuses_without_server_active_marker(): """A forged litellm_code_execution call must not trigger the loop unless the pre-call hook actually converted a native code_interpreter tool.""" logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) - forged = FakeResponse( - output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)] - ) + forged = FakeResponse(output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)]) should_run, payload = await logger.async_should_run_agentic_loop( response=forged, @@ -577,12 +562,8 @@ async def test_gate_refuses_without_server_active_marker(): @pytest.mark.asyncio async def test_gate_rechecks_provider_scope(): """enabled_providers must be re-enforced at the gate, not only in pre-call.""" - logger = CodeInterpreterInterceptionLogger( - sandbox_config=FakeSandbox(), enabled_providers=["openai"] - ) - response = FakeResponse( - output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)] - ) + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox(), enabled_providers=["openai"]) + response = FakeResponse(output=[_function_call_item(name=LITELLM_CODE_EXECUTION_TOOL_NAME)]) should_run, _ = await logger.async_should_run_agentic_loop( response=response, @@ -600,11 +581,7 @@ async def test_gate_rechecks_provider_scope(): @pytest.mark.asyncio async def test_chat_completion_gate_detects_code_execution_tool_call(): logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) - response = { - "choices": [ - {"message": {"tool_calls": [_chat_function_call_item(call_id="call_123")]}} - ] - } + response = {"choices": [{"message": {"tool_calls": [_chat_function_call_item(call_id="call_123")]}}]} should_run, payload = await logger.async_should_run_agentic_loop( response=response, @@ -661,9 +638,7 @@ async def test_chat_completion_build_plan_runs_code_and_appends_tool_message(): }, model="gpt-5", messages=[{"role": "user", "content": "x"}], - response={ - "choices": [{"message": {"tool_calls": [_chat_function_call_item()]}}] - }, + response={"choices": [{"message": {"tool_calls": [_chat_function_call_item()]}}]}, anthropic_messages_provider_config=None, anthropic_messages_optional_request_params={ "tools": [native_chat_tool], @@ -738,8 +713,7 @@ async def test_pre_call_strips_client_forged_marker_on_initial_request(): await logger.async_pre_call_deployment_hook(kwargs, CallTypes.aresponses) assert _ACTIVE_KEY not in kwargs, ( - "no native code_interpreter tool was present, so a client-supplied " - "active marker must be cleared" + "no native code_interpreter tool was present, so a client-supplied active marker must be cleared" ) assert kwargs["litellm_metadata"] == {"safe_user_value": "kept"} @@ -774,8 +748,7 @@ async def test_pre_call_strips_forged_loop_controls_then_mints_own_markers(): assert metadata[_ACTIVE_KEY] is True assert metadata[_SANDBOX_KEY] == result[_SANDBOX_KEY] assert metadata[_SANDBOX_KEY] != "client-forged", ( - "the surviving sandbox key must be the server-minted one, not the forged " - "value the client supplied" + "the surviving sandbox key must be the server-minted one, not the forged value the client supplied" ) @@ -793,8 +766,7 @@ async def test_pre_call_preserves_marker_on_server_followup(): await logger.async_pre_call_deployment_hook(kwargs, CallTypes.aresponses) assert kwargs.get(_ACTIVE_KEY) is True, ( - "the server-set marker must survive followup requests so multi-round " - "code execution keeps working" + "the server-set marker must survive followup requests so multi-round code execution keeps working" ) @@ -805,9 +777,7 @@ async def test_sandbox_deleted_after_loop_completes(): plan = await _build_plan(logger, sandbox, call_id="k1") assert sandbox.create_calls, "sandbox must be created during the loop" - assert ( - not sandbox.delete_calls - ), "sandbox must outlive the loop until the final hook" + assert not sandbox.delete_calls, "sandbox must outlive the loop until the final hook" await logger.async_post_agentic_loop_response_hook( response=FakeResponse(output=[{"type": "message", "content": []}]), @@ -816,8 +786,7 @@ async def test_sandbox_deleted_after_loop_completes(): ) assert len(sandbox.delete_calls) == 1, ( - "the sandbox must be deleted once the final response is assembled, " - "otherwise it keeps running and billing" + "the sandbox must be deleted once the final response is assembled, otherwise it keeps running and billing" ) assert "sbxkey1" not in logger._container_cache @@ -829,16 +798,11 @@ async def test_post_hook_delete_is_idempotent_across_loop_levels(): plan = await _build_plan(logger, sandbox, call_id="k1") response = FakeResponse(output=[{"type": "message", "content": []}]) - await logger.async_post_agentic_loop_response_hook( - response=response, plan=plan, kwargs={} - ) - await logger.async_post_agentic_loop_response_hook( - response=response, plan=plan, kwargs={} - ) + await logger.async_post_agentic_loop_response_hook(response=response, plan=plan, kwargs={}) + await logger.async_post_agentic_loop_response_hook(response=response, plan=plan, kwargs={}) assert len(sandbox.delete_calls) == 1, ( - "deleting an already-removed container must be a no-op so unwinding " - "loop levels do not double-delete" + "deleting an already-removed container must be a no-op so unwinding loop levels do not double-delete" ) @@ -860,8 +824,7 @@ async def test_build_plan_deletes_sandbox_when_execution_raises(): assert len(sandbox.create_calls) == 1, "the sandbox must have been created" assert len(sandbox.delete_calls) == 1, ( - "a build failure must delete the cached sandbox so it does not keep " - "running and billing" + "a build failure must delete the cached sandbox so it does not keep running and billing" ) assert "sbxkey1" not in logger._container_cache @@ -875,8 +838,7 @@ async def test_cleanup_hook_deletes_sandbox(): await logger.async_agentic_loop_cleanup_hook(plan=plan, kwargs={}) assert len(sandbox.delete_calls) == 1, ( - "the cleanup hook must delete the sandbox so a rerun failure cannot " - "leak a running container" + "the cleanup hook must delete the sandbox so a rerun failure cannot leak a running container" ) assert "sbxkey1" not in logger._container_cache @@ -895,8 +857,7 @@ async def test_cleanup_hook_is_idempotent_with_post_hook(): await logger.async_agentic_loop_cleanup_hook(plan=plan, kwargs={}) assert len(sandbox.delete_calls) == 1, ( - "cleanup running in finally after the success-path post hook already " - "deleted the sandbox must not double-delete" + "cleanup running in finally after the success-path post hook already deleted the sandbox must not double-delete" ) @@ -923,9 +884,7 @@ async def test_responses_plan_cleans_up_sandbox_when_followup_raises(): plan = AgenticLoopPlan( run_agentic_loop=True, - request_patch=AgenticLoopRequestPatch( - model="gpt-5", messages=[{"role": "user", "content": "x"}] - ), + request_patch=AgenticLoopRequestPatch(model="gpt-5", messages=[{"role": "user", "content": "x"}]), metadata={"sandbox_key": "sbxkey1"}, ) @@ -995,9 +954,7 @@ async def test_run_code_does_not_re_resolve_registry(monkeypatch): sandbox_tools.clear_sandbox_tools() - stdout = await logger._run_tool_call( - container=container, params=params, arguments='{"code":"print(1)"}' - ) + stdout = await logger._run_tool_call(container=container, params=params, arguments='{"code":"print(1)"}') finally: sandbox_tools.clear_sandbox_tools() @@ -1013,9 +970,7 @@ async def test_run_tool_call_surfaces_execution_error(): class ErroringSandbox(FakeSandbox): async def arun_code(self, *, container, code, **kwargs): self.run_calls.append({"container": container, "code": code}) - return CodeExecutionResult( - stdout="", error={"name": "ValueError", "value": "boom"} - ) + return CodeExecutionResult(stdout="", error={"name": "ValueError", "value": "boom"}) sandbox = ErroringSandbox() logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) @@ -1036,9 +991,7 @@ async def test_run_tool_call_reports_unparseable_arguments(): logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) container = await logger._create_container() - stdout = await logger._run_tool_call( - container=container[0], params=None, arguments="not-json" - ) + stdout = await logger._run_tool_call(container=container[0], params=None, arguments="not-json") assert stdout == "[invalid tool arguments: could not parse code]" assert not sandbox.run_calls, "code must not run when arguments cannot be parsed" @@ -1048,9 +1001,7 @@ async def test_run_tool_call_reports_unparseable_arguments(): async def test_pre_call_skips_provider_outside_scope(): """enabled_providers must filter the pre-call conversion so a request to an out-of-scope provider is left untouched.""" - logger = CodeInterpreterInterceptionLogger( - sandbox_config=FakeSandbox(), enabled_providers=["openai"] - ) + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox(), enabled_providers=["openai"]) kwargs = { "tools": [{"type": "code_interpreter", "container": {"type": "auto"}}], "custom_llm_provider": "anthropic", @@ -1119,6 +1070,7 @@ async def test_prune_expired_cache_deletes_underlying_container(): container, params, time.time() - handler_mod._CACHE_TTL_SECONDS - 1, + None, ) await logger._prune_expired_cache() @@ -1217,3 +1169,258 @@ async def test_extract_tool_calls_reads_object_attributes(): assert len(calls) == 1 assert calls[0]["call_id"] == "c9" assert calls[0]["arguments"] == '{"code":"print(1)"}' + + +# --------------------------------------------------------------------------- +# Sticky session tests +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_pre_call_uses_session_id_from_metadata_as_sandbox_key(): + """When session_id is in request metadata, it becomes the sandbox key so the + container is shared across requests in the same session.""" + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) + session_id = "conv-abc-123" + kwargs = { + "tools": [{"type": "code_interpreter", "container": {"type": "auto"}}], + "custom_llm_provider": "openai", + "metadata": {"session_id": session_id}, + } + + result = await logger.async_pre_call_deployment_hook(kwargs, CallTypes.acompletion) + + assert result is not None + assert result[_SANDBOX_KEY] == session_id + assert result[_SESSION_SCOPED_KEY] is True + assert result["litellm_metadata"][_SANDBOX_KEY] == session_id + assert result["litellm_metadata"][_SESSION_SCOPED_KEY] is True + + +@pytest.mark.asyncio +async def test_pre_call_uses_session_id_from_litellm_metadata(): + """session_id in litellm_metadata also works as the sticky key.""" + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) + session_id = "sess-xyz-789" + kwargs = { + "tools": [{"type": "code_interpreter", "container": {"type": "auto"}}], + "custom_llm_provider": "openai", + "litellm_metadata": {"session_id": session_id}, + } + + result = await logger.async_pre_call_deployment_hook(kwargs, CallTypes.acompletion) + + assert result is not None + assert result[_SANDBOX_KEY] == session_id + assert result[_SESSION_SCOPED_KEY] is True + + +@pytest.mark.asyncio +async def test_pre_call_without_session_id_still_mints_random_key(): + """Requests without a session_id still get a server-minted random sandbox key.""" + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) + kwargs = { + "tools": [{"type": "code_interpreter", "container": {"type": "auto"}}], + "custom_llm_provider": "openai", + } + + result = await logger.async_pre_call_deployment_hook(kwargs, CallTypes.acompletion) + + assert result is not None + assert _SESSION_SCOPED_KEY not in result or result[_SESSION_SCOPED_KEY] is False + assert len(result[_SANDBOX_KEY]) >= 16 + + +@pytest.mark.asyncio +async def test_session_scoped_sandbox_survives_agentic_loop_cleanup(): + """A session-scoped sandbox must NOT be deleted by the cleanup or post hooks; + it needs to persist across requests within the same session.""" + sandbox = FakeSandbox(stdout="42") + logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + session_id = "conv-persist-me" + + plan = await logger.async_build_agentic_loop_plan( + tools={ + "tool_calls": [ + { + "call_id": "c1", + "name": LITELLM_CODE_EXECUTION_TOOL_NAME, + "arguments": '{"code":"x = 10"}', + } + ] + }, + model="gpt-4o-mini", + messages=[{"role": "user", "content": "set x"}], + response=FakeResponse(output=[_function_call_item()]), + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={"tools": []}, + logging_obj=FakeLogging(litellm_call_id="k1"), + stream=False, + kwargs={ + "litellm_call_id": "k1", + _SANDBOX_KEY: session_id, + _SESSION_SCOPED_KEY: True, + }, + ) + + assert plan.metadata["is_session_scoped"] is True + + await logger.async_post_agentic_loop_response_hook( + response=FakeResponse(output=[{"type": "message", "content": []}]), + plan=plan, + kwargs={}, + ) + await logger.async_agentic_loop_cleanup_hook(plan=plan, kwargs={}) + + assert not sandbox.delete_calls, ( + "session-scoped sandbox must not be deleted after a single agentic loop; " + "it must persist for the next request in the session" + ) + assert session_id in logger._container_cache, "session-scoped container must remain in cache after loop ends" + + +@pytest.mark.asyncio +async def test_session_scoped_sandbox_reused_across_sequential_requests(): + """Two sequential requests with the same session_id must share one container, + confirming state (e.g. assigned variables) can persist across HTTP requests.""" + sandbox = FakeSandbox(stdout="42") + logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + session_id = "conv-reuse-me" + + common_plan_args = dict( + tools={ + "tool_calls": [ + { + "call_id": "c1", + "name": LITELLM_CODE_EXECUTION_TOOL_NAME, + "arguments": '{"code":"print(1)"}', + } + ] + }, + model="gpt-4o-mini", + messages=[{"role": "user", "content": "x"}], + response=FakeResponse(output=[_function_call_item()]), + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={"tools": []}, + stream=False, + ) + session_kwargs = {_SANDBOX_KEY: session_id, _SESSION_SCOPED_KEY: True} + + plan1 = await logger.async_build_agentic_loop_plan( + logging_obj=FakeLogging(litellm_call_id="req1"), + kwargs={"litellm_call_id": "req1", **session_kwargs}, + **common_plan_args, + ) + await logger.async_post_agentic_loop_response_hook( + response=FakeResponse(output=[{"type": "message", "content": []}]), + plan=plan1, + kwargs={}, + ) + + plan2 = await logger.async_build_agentic_loop_plan( + logging_obj=FakeLogging(litellm_call_id="req2"), + kwargs={"litellm_call_id": "req2", **session_kwargs}, + **common_plan_args, + ) + await logger.async_post_agentic_loop_response_hook( + response=FakeResponse(output=[{"type": "message", "content": []}]), + plan=plan2, + kwargs={}, + ) + + assert len(sandbox.create_calls) == 1, ( + "a single container must serve both requests in the same session; " + "two creates means state cannot persist between requests" + ) + assert len(sandbox.delete_calls) == 0, "the session container must still be alive after both requests complete" + + +@pytest.mark.asyncio +async def test_non_session_sandbox_still_deleted_after_loop(): + """Without a session_id, the existing per-request ephemeral behavior is unchanged.""" + sandbox = FakeSandbox(stdout="42") + logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + + plan = await _build_plan(logger, sandbox, call_id="k1") + await logger.async_post_agentic_loop_response_hook( + response=FakeResponse(output=[{"type": "message", "content": []}]), + plan=plan, + kwargs={}, + ) + + assert len(sandbox.delete_calls) == 1, "non-session sandbox must still be cleaned up after each request" + + +@pytest.mark.asyncio +async def test_sandbox_key_scoped_to_api_key_hash_isolates_users(): + """Two callers supplying the same session_id but different API key hashes must + each get their own sandbox; sharing across tenants would let one read or mutate + the other's interpreter state.""" + logger = CodeInterpreterInterceptionLogger(sandbox_config=FakeSandbox()) + session_id = "same-session-id" + + result_a = await logger.async_pre_call_deployment_hook( + { + "tools": [{"type": "code_interpreter"}], + "custom_llm_provider": "openai", + "metadata": {"session_id": session_id}, + "user_api_key_hash": "hash-for-tenant-a", + }, + CallTypes.acompletion, + ) + result_b = await logger.async_pre_call_deployment_hook( + { + "tools": [{"type": "code_interpreter"}], + "custom_llm_provider": "openai", + "metadata": {"session_id": session_id}, + "user_api_key_hash": "hash-for-tenant-b", + }, + CallTypes.acompletion, + ) + + assert result_a is not None and result_b is not None + assert result_a[_SANDBOX_KEY] != result_b[_SANDBOX_KEY], ( + "same session_id from different API keys must yield different sandbox keys; " + "otherwise tenant A can read tenant B's sandbox state" + ) + assert "hash-for-tenant-a" in result_a[_SANDBOX_KEY] + assert "hash-for-tenant-b" in result_b[_SANDBOX_KEY] + + +@pytest.mark.asyncio +async def test_per_identity_cap_evicts_lru_session(): + """When a single identity holds the cap limit of session sandboxes and opens a + new one, the least-recently-used session is evicted so the allocation stays + bounded. Without this, rotating session IDs is an unbounded sandbox leak.""" + from litellm.integrations.code_interpreter_interception.handler import _SESSION_SCOPED_PER_IDENTITY_CAP + + sandbox = FakeSandbox(stdout="ok") + logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + identity = "hash-for-identity-x" + + for i in range(_SESSION_SCOPED_PER_IDENTITY_CAP): + await logger._get_or_create_container( + cache_key=f"{identity}:session-{i}", + identity=identity, + ) + logger._container_cache[f"{identity}:session-{i}"] = ( + logger._container_cache[f"{identity}:session-{i}"][0], + logger._container_cache[f"{identity}:session-{i}"][1], + float(i), + identity, + ) + + assert len(logger._container_cache) == _SESSION_SCOPED_PER_IDENTITY_CAP + + await logger._get_or_create_container( + cache_key=f"{identity}:session-new", + identity=identity, + ) + + assert len(logger._container_cache) == _SESSION_SCOPED_PER_IDENTITY_CAP, ( + "adding a new session beyond the cap must evict one entry so total stays bounded" + ) + assert f"{identity}:session-0" not in logger._container_cache, ( + "the entry with the oldest last_accessed timestamp must be evicted first (LRU)" + ) + assert len(sandbox.delete_calls) == 1, "evicted sandbox must be deleted, not just removed from cache" From 846dbecbf2bcf3e11c60f56971c16c21f13f40fd Mon Sep 17 00:00:00 2001 From: Krrish Dholakia Date: Tue, 30 Jun 2026 19:02:00 -0700 Subject: [PATCH 47/79] feat(proxy): support object_permission in default_key_generate_params (#31776) * feat(proxy): support object_permission in default_key_generate_params default_key_generate_params filled in a fixed whitelist of scalar fields plus a full-replace for models/metadata, but never touched object_permission, so admins had no way to set a default (e.g. mcp_tool_search_enabled, vector_stores) applied to every new key. Merge object_permission field-by-field instead of replacing it wholesale, so a caller-supplied field (e.g. mcp_servers) is preserved alongside defaulted fields the caller left unset. * ci: retrigger proxy_pass_through_endpoint_tests (suspected flake, unrelated to this PR's diff) * fix(proxy): apply default object_permission after team-scope validation Injecting the default before validate_key_vector_stores_against_team / validate_key_search_tools_against_team ran meant a default containing a team-scoped field (e.g. vector_stores) looked like a caller-requested permission, turning ordinary non-admin personal key creation into a 403. Merge the default into data_json after those checks instead, and guard against a non-dict default value. --- .../key_management_endpoints.py | 17 ++ .../test_key_management_endpoints.py | 258 ++++++++++++++++++ 2 files changed, 275 insertions(+) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 4106eae606c..523cb9b74e5 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -965,6 +965,23 @@ async def _common_key_generation_helper( is_proxy_admin=_is_proxy_admin_caller, ) + # Merge default_key_generate_params.object_permission in *after* the team-scope + # checks above, so an admin-configured default (e.g. vector_stores, search_tools) + # is never mistaken for a caller-requested permission and rejected by those + # non-admin/no-team checks. Only fields the caller left unset are filled in. + _default_object_permission = ( + litellm.default_key_generate_params.get("object_permission") + if litellm.default_key_generate_params is not None + else None + ) + if isinstance(_default_object_permission, dict): + _caller_object_permission = data_json.get("object_permission") + if _caller_object_permission is None: + data_json["object_permission"] = dict(_default_object_permission) + elif isinstance(_caller_object_permission, dict): + for _op_field, _op_default_value in _default_object_permission.items(): + _caller_object_permission.setdefault(_op_field, _op_default_value) + data_json = await _set_object_permission( data_json=data_json, prisma_client=prisma_client, diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index 04048020e18..ae62be8799f 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -7781,6 +7781,264 @@ async def test_default_key_generate_params_duration(monkeypatch): litellm.default_key_generate_params = original_value +async def test_default_key_generate_params_object_permission_applied_when_absent( + monkeypatch, +): + """ + default_key_generate_params.object_permission is applied to a key that + doesn't specify object_permission at all. + """ + import litellm + + mock_prisma_client = AsyncMock() + mock_insert_data = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.insert_data = mock_insert_data + mock_prisma_client.db = MagicMock() + mock_prisma_client.db.litellm_verificationtoken = MagicMock() + mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=None + ) + mock_prisma_client.db.litellm_verificationtoken.find_many = AsyncMock( + return_value=[] + ) + mock_prisma_client.db.litellm_verificationtoken.count = AsyncMock(return_value=0) + mock_prisma_client.db.litellm_verificationtoken.update = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.db.litellm_objectpermissiontable = MagicMock() + mock_prisma_client.db.litellm_objectpermissiontable.create = AsyncMock( + return_value=MagicMock(object_permission_id="objperm-1") + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + original_value = litellm.default_key_generate_params + litellm.default_key_generate_params = { + "object_permission": {"vector_stores": ["default-vs"]} + } + + try: + request = GenerateKeyRequest() # No object_permission specified + await _common_key_generation_helper( + data=request, + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + litellm_changed_by=None, + team_table=None, + ) + + created_data = mock_prisma_client.db.litellm_objectpermissiontable.create.call_args.kwargs["data"] + assert created_data["vector_stores"] == ["default-vs"] + finally: + litellm.default_key_generate_params = original_value + + +async def test_default_key_generate_params_object_permission_merges_partial( + monkeypatch, +): + """ + default_key_generate_params.object_permission fills only the fields the + caller left unset - an explicitly supplied field (agents here) is + preserved alongside the defaulted field (vector_stores). + """ + import litellm + from litellm.proxy._types import LiteLLM_ObjectPermissionBase + + mock_prisma_client = AsyncMock() + mock_insert_data = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.insert_data = mock_insert_data + mock_prisma_client.db = MagicMock() + mock_prisma_client.db.litellm_verificationtoken = MagicMock() + mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=None + ) + mock_prisma_client.db.litellm_verificationtoken.find_many = AsyncMock( + return_value=[] + ) + mock_prisma_client.db.litellm_verificationtoken.count = AsyncMock(return_value=0) + mock_prisma_client.db.litellm_verificationtoken.update = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.db.litellm_objectpermissiontable = MagicMock() + mock_prisma_client.db.litellm_objectpermissiontable.create = AsyncMock( + return_value=MagicMock(object_permission_id="objperm-2") + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + original_value = litellm.default_key_generate_params + litellm.default_key_generate_params = { + "object_permission": {"vector_stores": ["default-vs"]} + } + + try: + request = GenerateKeyRequest( + object_permission=LiteLLM_ObjectPermissionBase(agents=["agent-1"]) + ) + await _common_key_generation_helper( + data=request, + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + litellm_changed_by=None, + team_table=None, + ) + + created_data = mock_prisma_client.db.litellm_objectpermissiontable.create.call_args.kwargs["data"] + assert created_data["agents"] == ["agent-1"] + assert created_data["vector_stores"] == ["default-vs"] + finally: + litellm.default_key_generate_params = original_value + + +async def test_default_key_generate_params_object_permission_does_not_override_explicit( + monkeypatch, +): + """ + A field the caller explicitly set on object_permission must win over the + same field in default_key_generate_params. + """ + import litellm + from litellm.proxy._types import LiteLLM_ObjectPermissionBase + + mock_prisma_client = AsyncMock() + mock_insert_data = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.insert_data = mock_insert_data + mock_prisma_client.db = MagicMock() + mock_prisma_client.db.litellm_verificationtoken = MagicMock() + mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=None + ) + mock_prisma_client.db.litellm_verificationtoken.find_many = AsyncMock( + return_value=[] + ) + mock_prisma_client.db.litellm_verificationtoken.count = AsyncMock(return_value=0) + mock_prisma_client.db.litellm_verificationtoken.update = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.db.litellm_objectpermissiontable = MagicMock() + mock_prisma_client.db.litellm_objectpermissiontable.create = AsyncMock( + return_value=MagicMock(object_permission_id="objperm-3") + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + original_value = litellm.default_key_generate_params + litellm.default_key_generate_params = { + "object_permission": {"vector_stores": ["default-vs"]} + } + + try: + request = GenerateKeyRequest( + object_permission=LiteLLM_ObjectPermissionBase( + vector_stores=["explicit-vs"] + ) + ) + await _common_key_generation_helper( + data=request, + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + litellm_changed_by=None, + team_table=None, + ) + + created_data = mock_prisma_client.db.litellm_objectpermissiontable.create.call_args.kwargs["data"] + assert created_data["vector_stores"] == ["explicit-vs"] + finally: + litellm.default_key_generate_params = original_value + + +async def test_default_key_generate_params_object_permission_not_rejected_for_non_admin_personal_key( + monkeypatch, +): + """ + Regression test: a default_key_generate_params.object_permission containing + a team-scoped field (vector_stores) must not turn ordinary non-admin + personal key creation into a 403. The default is merged in *after* the + caller-scope validation, so it is never mistaken for a caller-requested + permission. + """ + import litellm + + mock_prisma_client = AsyncMock() + mock_insert_data = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.insert_data = mock_insert_data + mock_prisma_client.db = MagicMock() + mock_prisma_client.db.litellm_verificationtoken = MagicMock() + mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock( + return_value=None + ) + mock_prisma_client.db.litellm_verificationtoken.find_many = AsyncMock( + return_value=[] + ) + mock_prisma_client.db.litellm_verificationtoken.count = AsyncMock(return_value=0) + mock_prisma_client.db.litellm_verificationtoken.update = AsyncMock( + return_value=MagicMock( + token="hashed_token_123", litellm_budget_table=None, object_permission=None + ) + ) + mock_prisma_client.db.litellm_objectpermissiontable = MagicMock() + mock_prisma_client.db.litellm_objectpermissiontable.create = AsyncMock( + return_value=MagicMock(object_permission_id="objperm-4") + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + original_value = litellm.default_key_generate_params + litellm.default_key_generate_params = { + "object_permission": {"vector_stores": ["default-vs"]} + } + + try: + request = GenerateKeyRequest(user_id="alice") # No object_permission specified + response = await _common_key_generation_helper( + data=request, + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-alice", + user_id="alice", + ), + litellm_changed_by=None, + team_table=None, + ) + + assert response is not None + created_data = mock_prisma_client.db.litellm_objectpermissiontable.create.call_args.kwargs["data"] + assert created_data["vector_stores"] == ["default-vs"] + finally: + litellm.default_key_generate_params = original_value + + @pytest.mark.asyncio async def test_build_key_filter_member_team_service_accounts(): """ From 50b936c75e8d7066968b8b6e31b73969d95790ae Mon Sep 17 00:00:00 2001 From: Krrish Dholakia Date: Tue, 30 Jun 2026 19:19:34 -0700 Subject: [PATCH 48/79] feat(guardrails/headroom): add CCR (compress-cache-retrieve) via agentic loop (#31681) * feat(guardrails/headroom): add CCR (compress-cache-retrieve) support via agentic loop When Headroom's /v1/compress returns messages containing hash markers (hash=[a-f0-9]{24}), inject a headroom_retrieve tool into the request. When the LLM calls that tool, intercept via async_should_run_agentic_loop and async_build_agentic_loop_plan, call GET /v1/retrieve/{hash} on the Headroom sidecar, and replay the LLM with the original content as a tool result -- all transparent to the caller. * style: run ruff format on headroom guardrail and tests * fix(guardrails/headroom): detect headroom_retrieve calls in both OpenAI and Anthropic response formats * test(guardrails/headroom): add test for Anthropic content block format detection in CCR loop * ci: trigger CI checks * fix(guardrails/headroom): replace List/Dict with list/dict to fix UP006 ruff violations * fix(guardrails/headroom): replace except Exception with except ValueError to fix BLE001 * fix(guardrails/headroom): add Responses API output format detection for CCR tool calls * refactor(guardrails/headroom): extract format-specific helpers to fix C901 complexity * fix(guardrails/headroom): scope CCR retrieval to hashes produced by current request Previously any LLM-supplied hash in a headroom_retrieve tool call was forwarded to the Headroom retrieve API, letting a crafted tool call fetch arbitrary cached content. Validate the hash against the set produced by compressing the current request's messages before calling retrieve. * fix(guardrails/headroom): track issued hashes server-side, fix Responses API replay shape Hash validation now also checks an in-memory cache of hashes actually returned by /v1/compress, not just whether the hash text appears somewhere in the request's messages. The message-text check alone is forgeable: an attacker can plant a hash-shaped string in their own prompt and have it treated as valid. Responses API follow-up now emits function_call/function_call_output items keyed by call_id instead of chat-style assistant/tool messages, since the Responses API does not accept the latter as input. Also fixes call_id/id field priority when extracting tool calls from Responses API output, since call_id (not id) is what must match between the function_call and its output. * fix(guardrails/headroom): drop redundant quoted type annotations UP037 flags quotes on annotations that are already lazily evaluated via `from __future__ import annotations`. * test(guardrails/headroom): add missing pytest.mark.asyncio decorators Functional under asyncio_mode=auto, but every other async test in the file has the decorator for consistency. * fix(guardrails/headroom): scope CCR hashes per call_id, fix Anthropic replay shape Two real gaps found in review: 1. The instance-wide issued-hash cache combined with a message-text check did not actually scope retrieval to the request that produced the hash. A hash issued for request A stays in the shared cache until TTL expiry, and the message-text check is satisfied by any request whose own messages happen to echo that hash string. Request B could plant A's hash in its own prompt and retrieve A's content. Fixed by keying the issued-hash cache by litellm_call_id, matching the pattern already used in compression_interception: a hash is only honored when it was issued under the exact call_id resolving for the current request. 2. The Anthropic Messages replay path fell through to the chat-style assistant/tool-message builder, which Anthropic does not accept. Anthropic requires the tool_use block echoed in an assistant message paired with a tool_result block in a user message, keyed by tool_use_id. Added a dedicated branch for this shape. * docs: note proactive API-fragmentation helper convention Add a bullet to the coding-conventions list: look for or add a shared helper when logic branches on API surface (chat completions vs Anthropic Messages vs Responses API), instead of duplicating format-detection per module. * fix(guardrails/headroom): fix Anthropic tool-shape detection, extract shared cross-API tool util Live e2e testing against the real Anthropic API surfaced two bugs the mocked unit tests couldn't catch because they used MagicMock responses instead of realistic response shapes: 1. has_headroom_retrieve_tool only recognized OpenAI-shaped function tools. By the time an Anthropic Messages response reaches the agentic-loop gate, the tool this guardrail injected has already been transformed into Anthropic's native shape (type: "custom", top-level "name"), so the gate never fired for real Anthropic requests. 2. AnthropicMessagesResponse is a TypedDict, so real responses are plain dicts at runtime, not objects with attribute access. The extractors and format detectors used bare getattr(), which silently returns nothing for dict responses instead of reading the actual key. Extracted the cross-API-surface tool-call extraction and tool-presence check into litellm/litellm_core_utils/prompt_templates/factory.py (get_tool_calls_from_response, has_tool_with_name) so this format fragmentation is handled in one place instead of being duplicated per-guardrail, and reused the existing repair-aware parse_tool_call_arguments from common_utils instead of a naive json.loads. headroom.py now delegates to these shared helpers. Confirmed live against the real Anthropic API: the retrieve loop now fires and successfully retrieves the correct hash's content through the full compress -> tool-call -> retrieve -> replay round-trip. * fix(guardrails/headroom): fix ruff-strict UP006/I001 budget violations Use lowercase list/dict generics in the new factory.py tool-call helpers instead of typing.List/Dict, drop the now-unused Tuple import in headroom.py, and reorder the new factory import ahead of the llms.custom_httpx import to satisfy import sorting. * fix(guardrails/headroom): match Anthropic tools without a type field Anthropic's documented client tool format is just name + input_schema; type: "custom" is only one possible value, not a requirement. Match any non-OpenAI-shaped tool on its top-level name instead of requiring type == "custom". --- CLAUDE.md | 1 + .../prompt_templates/factory.py | 145 +++- .../guardrail_hooks/headroom/headroom.py | 355 ++++++++- tests/llm_translation/test_prompt_factory.py | 99 +++ .../guardrail_hooks/test_headroom.py | 741 +++++++++++++++++- 5 files changed, 1319 insertions(+), 22 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 0cd1605b1b2..83bf3e22d27 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -69,6 +69,7 @@ Follow these coding conventions for new/updated code (a three-line fix in a lega - No monster files or god objects - No file sprawl: deliberate file and folder structure - Standard over hand-rolled: use the official SDK or a library where one exists; where none does, follow industry standards instead of inventing local conventions +- API-fragmentation-aware: when logic must branch on which API surface produced or consumes data (e.g. chat completions vs Anthropic Messages vs Responses API shapes), proactively look for an existing shared helper (e.g. `litellm_core_utils/prompt_templates/factory.py`) before writing per-surface parsing in the new module; if none exists, add one there instead of duplicating the same format-detection logic in every new guardrail/integration Follow conventional commits for commit names and PR titles diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index 1f0df51d7de..c2448430387 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -6,7 +6,7 @@ import mimetypes import re import xml.etree.ElementTree as ET from enum import Enum -from typing import Any, Dict, List, Optional, Set, Tuple, Union, cast, overload +from typing import Any, Dict, List, Optional, Set, Tuple, TypedDict, Union, cast, overload from jinja2.sandbox import ImmutableSandboxedEnvironment @@ -5322,3 +5322,146 @@ def get_attribute_or_key(tool_or_function, attribute, default=None): if hasattr(tool_or_function, attribute): return getattr(tool_or_function, attribute) return tool_or_function.get(attribute, default) + + +class NormalizedToolCall(TypedDict): + id: Optional[str] + name: Optional[str] + arguments: dict[str, Any] + + +def _parse_tool_call_arguments(raw: Any, tool_name: Optional[str], context: str) -> dict[str, Any]: + # Anthropic's tool_use blocks already carry a parsed dict in "input"; + # chat completions and the Responses API carry a JSON string that may be + # truncated by the model, so route those through the repair-aware parser. + if isinstance(raw, dict): + return raw + if not isinstance(raw, str): + return {} + from litellm.litellm_core_utils.prompt_templates.common_utils import ( + parse_tool_call_arguments, + ) + + try: + parsed = parse_tool_call_arguments(raw, tool_name=tool_name, context=context) + except ValueError as e: + verbose_logger.warning("Failed to parse tool call arguments: %s", e) + return {} + return parsed if isinstance(parsed, dict) else {} + + +def _tool_calls_from_chat_completion_response(response: Any) -> list[NormalizedToolCall]: + choices = get_attribute_or_key(response, "choices", None) + if not (isinstance(choices, list) and choices): + return [] + message = get_attribute_or_key(choices[0], "message", None) + tool_calls = get_attribute_or_key(message, "tool_calls", None) if message else None + if not isinstance(tool_calls, list): + return [] + result: list[NormalizedToolCall] = [] + for tc in tool_calls: + fn = get_attribute_or_key(tc, "function", None) + if fn is None: + continue + name = get_attribute_or_key(fn, "name") + result.append( + NormalizedToolCall( + id=get_attribute_or_key(tc, "id"), + name=name, + arguments=_parse_tool_call_arguments( + get_attribute_or_key(fn, "arguments", "{}"), + tool_name=name, + context="chat completions", + ), + ) + ) + return result + + +def _tool_calls_from_responses_api_response(response: Any) -> list[NormalizedToolCall]: + output = get_attribute_or_key(response, "output", None) + if not isinstance(output, list): + return [] + result: list[NormalizedToolCall] = [] + for item in output: + if get_attribute_or_key(item, "type") != "function_call": + continue + name = get_attribute_or_key(item, "name") + result.append( + NormalizedToolCall( + id=get_attribute_or_key(item, "call_id") or get_attribute_or_key(item, "id"), + name=name, + arguments=_parse_tool_call_arguments( + get_attribute_or_key(item, "arguments", "{}"), + tool_name=name, + context="responses API", + ), + ) + ) + return result + + +def _tool_calls_from_anthropic_messages_response(response: Any) -> list[NormalizedToolCall]: + content = get_attribute_or_key(response, "content", None) + if not isinstance(content, list): + return [] + result: list[NormalizedToolCall] = [] + for block in content: + if get_attribute_or_key(block, "type") != "tool_use": + continue + raw_input = get_attribute_or_key(block, "input", {}) + result.append( + NormalizedToolCall( + id=get_attribute_or_key(block, "id"), + name=get_attribute_or_key(block, "name"), + arguments=raw_input if isinstance(raw_input, dict) else {}, + ) + ) + return result + + +def get_tool_calls_from_response(response: Any) -> list[NormalizedToolCall]: + """ + Extract tool/function calls from a response object into a normalized + ``{"id", "name", "arguments"}`` shape, regardless of which API surface + produced it: chat completions (``choices[].message.tool_calls``), + the Responses API (``output`` items of type ``function_call``), or the + Anthropic Messages API (``content`` blocks of type ``tool_use``). + + Callers that only care about a specific tool should filter the result by + ``name`` themselves -- this returns every tool call found. + """ + for extractor in ( + _tool_calls_from_chat_completion_response, + _tool_calls_from_responses_api_response, + _tool_calls_from_anthropic_messages_response, + ): + tool_calls = extractor(response) + if tool_calls: + return tool_calls + return [] + + +def has_tool_with_name(tools: Any, tool_name: str) -> bool: + """ + Check whether a tools list (as sent to an LLM) includes a tool with the + given name, regardless of shape: OpenAI-style function tools + (``{"type": "function", "function": {"name": ...}}``) or Anthropic's + native tool shape (a top-level ``"name"``, e.g. + ``{"name": ..., "input_schema": ...}``). Anthropic's documented client + tool format doesn't require a ``"type"`` key at all -- ``"custom"`` is + only one of several possible values -- so any non-OpenAI-shaped tool is + matched on its top-level ``"name"``. + """ + if not isinstance(tools, list): + return False + for tool in tools: + if not isinstance(tool, dict): + continue + function = tool.get("function") + if tool.get("type") == "function" and isinstance(function, dict): + if function.get("name") == tool_name: + return True + elif tool.get("name") == tool_name: + return True + return False diff --git a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py index 2228ccf3997..4badb48e2eb 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py +++ b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py @@ -1,6 +1,10 @@ from __future__ import annotations -from typing import TYPE_CHECKING, Literal +import json +import re +import time +import uuid +from typing import TYPE_CHECKING, Any, Literal, Optional import httpx from fastapi import HTTPException @@ -12,12 +16,18 @@ from litellm.integrations.custom_guardrail import ( CustomGuardrail, log_guardrail_information, ) +from litellm.litellm_core_utils.prompt_templates.factory import ( + get_attribute_or_key, + get_tool_calls_from_response, + has_tool_with_name, +) from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, # pyright: ignore[reportUnknownVariableType] httpxSpecialProvider, ) from litellm.secret_managers.main import get_secret_str from litellm.types.guardrails import GuardrailEventHooks, Mode +from litellm.types.integrations.custom_logger import AgenticLoopPlan, AgenticLoopRequestPatch from litellm.types.utils import GenericGuardrailAPIInputs if TYPE_CHECKING: @@ -25,6 +35,9 @@ if TYPE_CHECKING: from litellm.types.proxy.guardrails.guardrail_hooks.base import GuardrailConfigModel BYPASS_HEADER = "x-headroom-bypass" +HEADROOM_RETRIEVE_TOOL_NAME = "headroom_retrieve" +_HASH_PATTERN = re.compile(r"hash=([a-f0-9]{24})") +_HASH_CACHE_TTL_SECONDS = 15 * 60 def _is_str_object_dict(value: object) -> TypeGuard[dict[str, object]]: # guard-ok: isinstance narrows correctly; predicate is trivially correct # fmt: skip @@ -35,6 +48,163 @@ def _is_object_list(value: object) -> TypeGuard[list[object]]: # guard-ok: isin return isinstance(value, list) +def extract_hashes_from_messages(messages: list[dict[str, object]]) -> list[str]: + hashes: list[str] = [] + for msg in messages: + content = msg.get("content") + if isinstance(content, str): + hashes.extend(_HASH_PATTERN.findall(content)) + elif isinstance(content, list): + for block in content: + if isinstance(block, dict): + text = block.get("text") + if isinstance(text, str): + hashes.extend(_HASH_PATTERN.findall(text)) + return hashes + + +def _build_headroom_retrieve_tool() -> dict[str, object]: + return { + "type": "function", + "function": { + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "description": ( + "Retrieve original content that was compressed by Headroom. " + "Call this when you encounter a compression marker containing a hash." + ), + "parameters": { + "type": "object", + "properties": { + "hash": { + "type": "string", + "description": "The 24-character hex hash from the compression marker.", + }, + "query": { + "type": "string", + "description": "Optional search query for BM25-ranked retrieval.", + }, + }, + "required": ["hash"], + }, + }, + } + + +def _resolve_call_id(logging_obj: object, request_state: dict[str, object]) -> Optional[str]: + """Resolve the litellm_call_id shared by a request's pre-call hook and its + agentic-loop hooks, so CCR hash validation can be scoped per call instead + of trusting any hash-shaped string that shows up in message text.""" + logging_call_id = getattr(logging_obj, "litellm_call_id", None) + if isinstance(logging_call_id, str) and logging_call_id: + return logging_call_id + kwargs_call_id = request_state.get("litellm_call_id") + return kwargs_call_id if isinstance(kwargs_call_id, str) else None + + +def has_headroom_retrieve_tool(tools: object) -> bool: + return has_tool_with_name(tools, HEADROOM_RETRIEVE_TOOL_NAME) + + +def _extract_headroom_tool_calls(response: object) -> list[dict[str, object]]: + return [ + {"id": tc["id"], "type": "function", "name": tc["name"], "arguments": tc["arguments"]} + for tc in get_tool_calls_from_response(response) + if tc["name"] == HEADROOM_RETRIEVE_TOOL_NAME + ] + + +def _build_assistant_message_from_response(response: object) -> dict[str, object]: + choices = getattr(response, "choices", None) + if not isinstance(choices, list) or not choices: + return {"role": "assistant", "content": None, "tool_calls": []} + message = getattr(choices[0], "message", None) + if message is None: + return {"role": "assistant", "content": None, "tool_calls": []} + content = getattr(message, "content", None) + tool_calls = getattr(message, "tool_calls", None) + raw_tool_calls: list[dict[str, object]] = [] + if isinstance(tool_calls, list): + for tc in tool_calls: + fn = getattr(tc, "function", None) + raw_tool_calls.append( + { + "id": getattr(tc, "id", None), + "type": "function", + "function": { + "name": getattr(fn, "name", None) if fn else None, + "arguments": getattr(fn, "arguments", "{}") if fn else "{}", + }, + } + ) + return {"role": "assistant", "content": content, "tool_calls": raw_tool_calls} + + +def _is_responses_api_response(response: object) -> bool: + # Real response objects can be plain dicts at runtime (e.g. TypedDict-based + # response types), so getattr alone would silently miss the key -- use the + # same dict-or-object accessor as the tool-call extractors. + return isinstance(get_attribute_or_key(response, "output", None), list) + + +def _is_anthropic_messages_response(response: object) -> bool: + return isinstance(get_attribute_or_key(response, "content", None), list) + + +def _build_anthropic_followup_messages( + retrieved: list[tuple[dict[str, object], str]], +) -> list[dict[str, object]]: + """Build Anthropic Messages API follow-up messages for a tool round-trip. + + Anthropic requires the tool_use block to be echoed back in an assistant + message, paired with a tool_result block in a user message keyed by the + same tool_use_id -- it does not accept chat-style tool-role messages. + """ + assistant_message: dict[str, object] = { + "role": "assistant", + "content": [ + { + "type": "tool_use", + "id": tool_call.get("id"), + "name": tool_call.get("name"), + "input": tool_call.get("arguments", {}), + } + for tool_call, _ in retrieved + ], + } + user_message: dict[str, object] = { + "role": "user", + "content": [ + {"type": "tool_result", "tool_use_id": tool_call.get("id"), "content": content} + for tool_call, content in retrieved + ], + } + return [assistant_message, user_message] + + +def _build_responses_followup_items( + retrieved: list[tuple[dict[str, object], str]], +) -> list[dict[str, object]]: + """Build Responses API input items for a tool round-trip. + + The Responses API does not accept chat-style assistant/tool messages as + follow-up input; it requires the model's function_call to be echoed back + paired with a function_call_output keyed by the same call_id. + """ + items: list[dict[str, object]] = [] + for tool_call, content in retrieved: + call_id = tool_call.get("id") + items.append( + { + "type": "function_call", + "call_id": call_id, + "name": tool_call.get("name"), + "arguments": json.dumps(tool_call.get("arguments", {})), + } + ) + items.append({"type": "function_call_output", "call_id": call_id, "output": content}) + return items + + class HeadroomGuardrail(CustomGuardrail): def __init__( self, @@ -56,6 +226,7 @@ class HeadroomGuardrail(CustomGuardrail): self.async_handler = get_async_httpx_client( llm_provider=httpxSpecialProvider.GuardrailCallback, ) + self._issued_hashes_by_call_id: dict[str, tuple[frozenset[str], float]] = {} super().__init__( # pyright: ignore[reportUnknownMemberType] guardrail_name=guardrail_name, event_hook=event_hook, @@ -72,6 +243,20 @@ class HeadroomGuardrail(CustomGuardrail): value = headers.get(BYPASS_HEADER) return str(value).lower() == "true" + def _request_headers(self) -> dict[str, str]: + headers: dict[str, str] = {"Content-Type": "application/json"} + if self.headroom_api_key: + headers["Authorization"] = f"Bearer {self.headroom_api_key}" + return headers + + def _prune_expired_hashes(self) -> None: + now = time.monotonic() + self._issued_hashes_by_call_id = { + call_id: (hashes, expiry) + for call_id, (hashes, expiry) in self._issued_hashes_by_call_id.items() + if expiry > now + } + async def _call_compress( self, messages: list[dict[str, object]], @@ -81,15 +266,11 @@ class HeadroomGuardrail(CustomGuardrail): if model: payload["model"] = model - request_headers: dict[str, str] = {"Content-Type": "application/json"} - if self.headroom_api_key: - request_headers["Authorization"] = f"Bearer {self.headroom_api_key}" - try: raw_response: HttpxResponse | None = await self.async_handler.post( # pyright: ignore[reportUnknownMemberType] url=f"{self.headroom_api_base}/v1/compress", json=payload, - headers=request_headers, + headers=self._request_headers(), ) except (httpx.ConnectError, httpx.TimeoutException, httpx.TransportError) as e: raise HTTPException( @@ -118,7 +299,7 @@ class HeadroomGuardrail(CustomGuardrail): try: body: object = response.json() - except Exception: + except ValueError: raise HTTPException( status_code=502, detail={ @@ -163,6 +344,44 @@ class HeadroomGuardrail(CustomGuardrail): ) return filtered + async def _call_retrieve(self, hash_value: str, query: str | None = None) -> str: + params: dict[str, str] = {} + if query: + params["query"] = query + + try: + raw_response: HttpxResponse | None = await self.async_handler.get( # pyright: ignore[reportUnknownMemberType] + url=f"{self.headroom_api_base}/v1/retrieve/{hash_value}", + params=params, + headers=self._request_headers(), + ) + except (httpx.ConnectError, httpx.TimeoutException, httpx.TransportError) as e: + verbose_proxy_logger.warning("Headroom: retrieve failed for hash=%s: %s", hash_value, e) + return f"[Headroom: retrieval failed for hash={hash_value}]" + + if raw_response is None or raw_response.status_code == 404: + return f"[Headroom: hash={hash_value} not found or expired]" + + if raw_response.status_code != 200: + verbose_proxy_logger.warning( + "Headroom: retrieve returned %s for hash=%s", + raw_response.status_code, + hash_value, + ) + return f"[Headroom: retrieval error {raw_response.status_code} for hash={hash_value}]" + + try: + body: object = raw_response.json() + except ValueError: + return raw_response.text + + if _is_str_object_dict(body): + original_content = body.get("original_content") + if isinstance(original_content, str): + return original_content + + return str(body) + @log_guardrail_information async def apply_guardrail( self, @@ -192,7 +411,127 @@ class HeadroomGuardrail(CustomGuardrail): model=model if isinstance(model, str) else None, ) - return {**inputs, "structured_messages": compressed} # pyright: ignore[reportReturnType] + hashes = extract_hashes_from_messages(compressed) + if not hashes: + return {**inputs, "structured_messages": compressed} # pyright: ignore[reportReturnType] + + self._prune_expired_hashes() + call_id = _resolve_call_id(logging_obj, request_data) + if not call_id: + call_id = str(uuid.uuid4()) + request_data["litellm_call_id"] = call_id + self._issued_hashes_by_call_id[call_id] = (frozenset(hashes), time.monotonic() + _HASH_CACHE_TTL_SECONDS) + + existing_tools = inputs.get("tools") + retrieve_tool = _build_headroom_retrieve_tool() + if isinstance(existing_tools, list) and not has_headroom_retrieve_tool(existing_tools): + merged_tools: list[object] = list(existing_tools) + [retrieve_tool] + elif existing_tools is None: + merged_tools = [retrieve_tool] + else: + merged_tools = list(existing_tools) if isinstance(existing_tools, list) else [retrieve_tool] + + return {**inputs, "structured_messages": compressed, "tools": merged_tools} # pyright: ignore[reportReturnType] + + async def async_should_run_agentic_loop( + self, + response: Any, + model: str, + messages: list[dict], + tools: Optional[list[dict]], + stream: bool, + custom_llm_provider: str, + kwargs: dict, + ) -> tuple[bool, dict]: + if not has_headroom_retrieve_tool(tools): + return False, {} + + tool_calls = _extract_headroom_tool_calls(response) + if not tool_calls: + return False, {} + + return True, {"tool_calls": tool_calls} + + async def async_build_agentic_loop_plan( + self, + tools: dict, + model: str, + messages: list[dict], + response: Any, + anthropic_messages_provider_config: Any, + anthropic_messages_optional_request_params: dict, + logging_obj: Any, + stream: bool, + kwargs: dict, + ) -> AgenticLoopPlan: + tool_calls: list[dict[str, object]] = tools.get("tool_calls", []) # type: ignore[assignment] + + self._prune_expired_hashes() + call_id = _resolve_call_id(logging_obj, kwargs) + valid_hashes = self._issued_hashes_by_call_id.get(call_id, (frozenset(), 0.0))[0] if call_id else frozenset() + + retrieved: list[tuple[dict[str, object], str]] = [] + for tc in tool_calls: + arguments = tc.get("arguments", {}) + hash_value = arguments.get("hash", "") if isinstance(arguments, dict) else "" + query = arguments.get("query") if isinstance(arguments, dict) else None + # A hash is only honored if it was issued by *this request's own* + # Headroom /v1/compress call, scoped by litellm_call_id. Scoping by + # message text alone is forgeable -- an attacker can plant a + # hash-shaped string in their own prompt, and a hash issued for one + # request would validate for any other request that echoes it back. + if str(hash_value) not in valid_hashes: + verbose_proxy_logger.warning( + "Headroom CCR: rejecting hash=%s not produced by current request compression", + hash_value, + ) + content = f"[Headroom: hash={hash_value} was not produced by the current request]" + else: + content = await self._call_retrieve( + hash_value=str(hash_value), + query=str(query) if query else None, + ) + verbose_proxy_logger.debug("Headroom CCR: retrieved hash=%s (%d chars)", hash_value, len(content)) + retrieved.append((tc, content)) + + if _is_responses_api_response(response): + follow_up_messages = list(messages) + _build_responses_followup_items(retrieved) + elif _is_anthropic_messages_response(response): + follow_up_messages = list(messages) + _build_anthropic_followup_messages(retrieved) + else: + assistant_message = _build_assistant_message_from_response(response) + tool_results = [ + {"role": "tool", "tool_call_id": tc.get("id"), "content": content} for tc, content in retrieved + ] + follow_up_messages = list(messages) + [assistant_message] + tool_results + + max_tokens: Optional[int] = anthropic_messages_optional_request_params.get("max_tokens") or kwargs.get( + "max_tokens" + ) + optional_params_without_max_tokens = { + k: v for k, v in anthropic_messages_optional_request_params.items() if k != "max_tokens" + } + + full_model_name = model + if logging_obj is not None: + agentic_params = getattr(logging_obj, "model_call_details", {}).get("agentic_loop_params", {}) + candidate = agentic_params.get("model", model) + if isinstance(candidate, str) and candidate: + full_model_name = candidate + + return AgenticLoopPlan( + run_agentic_loop=True, + request_patch=AgenticLoopRequestPatch( + model=full_model_name, + messages=follow_up_messages, + max_tokens=max_tokens, + optional_params=optional_params_without_max_tokens, + kwargs={ + k: v for k, v in kwargs.items() if not k.startswith("_headroom") and k != "litellm_logging_obj" + }, + ), + metadata={"tool_type": "headroom_ccr"}, + ) @staticmethod def get_config_model() -> type[GuardrailConfigModel[object]] | None: diff --git a/tests/llm_translation/test_prompt_factory.py b/tests/llm_translation/test_prompt_factory.py index 05a58a135d2..ae215602e31 100644 --- a/tests/llm_translation/test_prompt_factory.py +++ b/tests/llm_translation/test_prompt_factory.py @@ -20,6 +20,8 @@ from litellm.litellm_core_utils.prompt_templates.factory import ( convert_to_anthropic_tool_invoke, convert_url_to_base64, create_anthropic_image_param, + get_tool_calls_from_response, + has_tool_with_name, llama_2_chat_pt, prompt_factory, ) @@ -2385,3 +2387,100 @@ def test_anthropic_messages_pt_list_content_with_thinking_preserves_order(): # Verify signatures preserved in correct positions assert content[0]["signature"] == "sig_1" assert content[3]["signature"] == "sig_2" + + +def test_get_tool_calls_from_response_chat_completions(): + response = MagicMock() + response.output = None + response.content = None + tool_call = MagicMock() + tool_call.id = "call_abc" + tool_call.function.name = "my_tool" + tool_call.function.arguments = '{"x": 1}' + response.choices = [MagicMock(message=MagicMock(tool_calls=[tool_call]))] + + result = get_tool_calls_from_response(response) + + assert result == [{"id": "call_abc", "name": "my_tool", "arguments": {"x": 1}}] + + +def test_get_tool_calls_from_response_responses_api(): + response = MagicMock() + response.choices = None + response.content = None + response.output = [ + { + "type": "function_call", + "id": "fc_1", + "call_id": "call_1", + "name": "my_tool", + "arguments": '{"x": 2}', + } + ] + + result = get_tool_calls_from_response(response) + + assert result == [{"id": "call_1", "name": "my_tool", "arguments": {"x": 2}}] + + +def test_get_tool_calls_from_response_anthropic_messages(): + response = MagicMock() + response.choices = None + response.output = None + response.content = [ + {"type": "tool_use", "id": "toolu_1", "name": "my_tool", "input": {"x": 3}}, + ] + + result = get_tool_calls_from_response(response) + + assert result == [{"id": "toolu_1", "name": "my_tool", "arguments": {"x": 3}}] + + +def test_get_tool_calls_from_response_anthropic_messages_plain_dict(): + # AnthropicMessagesResponse is a TypedDict -- real responses are plain + # dicts at runtime, not objects with attribute access. A MagicMock-only + # test would pass even if the extractor used bare getattr() and silently + # returned nothing for a real response. + response = { + "content": [ + {"type": "tool_use", "id": "toolu_1", "name": "my_tool", "input": {"x": 3}}, + ] + } + + result = get_tool_calls_from_response(response) + + assert result == [{"id": "toolu_1", "name": "my_tool", "arguments": {"x": 3}}] + + +def test_get_tool_calls_from_response_no_tool_calls(): + response = MagicMock() + response.choices = None + response.output = None + response.content = None + + assert get_tool_calls_from_response(response) == [] + + +def test_has_tool_with_name_openai_function_shape(): + tools = [{"type": "function", "function": {"name": "my_tool"}}] + assert has_tool_with_name(tools, "my_tool") + assert not has_tool_with_name(tools, "other_tool") + + +def test_has_tool_with_name_anthropic_custom_shape(): + tools = [{"type": "custom", "name": "my_tool", "input_schema": {}}] + assert has_tool_with_name(tools, "my_tool") + assert not has_tool_with_name(tools, "other_tool") + + +def test_has_tool_with_name_anthropic_shape_without_type_field(): + # Anthropic's documented client tool format is just name + input_schema; + # "type" isn't required at all (type: "custom" is only one possible value). + tools = [{"name": "my_tool", "input_schema": {}}] + assert has_tool_with_name(tools, "my_tool") + assert not has_tool_with_name(tools, "other_tool") + + +def test_has_tool_with_name_not_a_list(): + assert not has_tool_with_name(None, "my_tool") + assert not has_tool_with_name("not a list", "my_tool") diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py index 66395035384..f5ce6cedf64 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py @@ -8,15 +8,25 @@ Tests cover: - response-type input is passed through unchanged - /v1/compress HTTP error raises HTTPException - /v1/compress returning malformed JSON raises HTTPException +- CCR: headroom_retrieve tool injected when compressed messages contain hashes +- CCR: async_should_run_agentic_loop returns True when response has headroom_retrieve tool calls +- CCR: async_build_agentic_loop_plan calls retrieve endpoint and builds follow-up messages """ +import json +import time from unittest.mock import AsyncMock, MagicMock, patch import httpx import pytest from fastapi import HTTPException -from litellm.proxy.guardrails.guardrail_hooks.headroom.headroom import HeadroomGuardrail +from litellm.proxy.guardrails.guardrail_hooks.headroom.headroom import ( + HeadroomGuardrail, + extract_hashes_from_messages, + has_headroom_retrieve_tool, + HEADROOM_RETRIEVE_TOOL_NAME, +) from litellm.types.utils import GenericGuardrailAPIInputs FAKE_API_BASE = "https://headroom.example.com" @@ -30,6 +40,13 @@ COMPRESSED_MESSAGES = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "A" * 500}, ] +COMPRESSED_MESSAGES_WITH_HASH = [ + {"role": "system", "content": "You are a helpful assistant."}, + { + "role": "user", + "content": "Summary. Retrieve more: hash=b573993006976af767214fac", + }, +] def _make_guardrail(**kwargs) -> HeadroomGuardrail: @@ -57,6 +74,36 @@ def _make_compress_response(messages: list, status: int = 200) -> MagicMock: return mock +def _make_retrieve_response(original_content: str, status: int = 200) -> MagicMock: + mock = MagicMock() + mock.status_code = status + mock.json.return_value = {"original_content": original_content} + mock.text = original_content + return mock + + +def _make_openai_response_with_tool_call(tool_name: str, arguments: dict, tool_id: str = "call_abc123") -> MagicMock: + fn = MagicMock() + fn.name = tool_name + fn.arguments = json.dumps(arguments) + + tc = MagicMock() + tc.id = tool_id + tc.type = "function" + tc.function = fn + + message = MagicMock() + message.content = None + message.tool_calls = [tc] + + choice = MagicMock() + choice.message = message + + response = MagicMock() + response.choices = [choice] + return response + + @pytest.fixture def guardrail() -> HeadroomGuardrail: return _make_guardrail() @@ -87,6 +134,567 @@ async def test_apply_guardrail_compresses_and_returns_structured_messages( assert result.get("structured_messages") == COMPRESSED_MESSAGES +@pytest.mark.asyncio +async def test_apply_guardrail_injects_retrieve_tool_when_hashes_present( + guardrail: HeadroomGuardrail, +): + inputs = GenericGuardrailAPIInputs( + texts=["A" * 5000], + structured_messages=ORIGINAL_MESSAGES, + ) + mock_response = _make_compress_response(COMPRESSED_MESSAGES_WITH_HASH) + + with patch.object( + guardrail.async_handler, + "post", + new_callable=AsyncMock, + return_value=mock_response, + ): + result = await guardrail.apply_guardrail( + inputs=inputs, + request_data={"model": "gpt-4o"}, + input_type="request", + ) + + tools = result.get("tools") + assert tools is not None + assert has_headroom_retrieve_tool(tools) + + +@pytest.mark.asyncio +async def test_apply_guardrail_no_tool_injected_when_no_hashes( + guardrail: HeadroomGuardrail, +): + inputs = GenericGuardrailAPIInputs( + texts=["A" * 5000], + structured_messages=ORIGINAL_MESSAGES, + ) + mock_response = _make_compress_response(COMPRESSED_MESSAGES) + + with patch.object( + guardrail.async_handler, + "post", + new_callable=AsyncMock, + return_value=mock_response, + ): + result = await guardrail.apply_guardrail( + inputs=inputs, + request_data={"model": "gpt-4o"}, + input_type="request", + ) + + tools = result.get("tools") + assert not has_headroom_retrieve_tool(tools or []) + + +@pytest.mark.asyncio +async def test_apply_guardrail_preserves_existing_tools_when_injecting( + guardrail: HeadroomGuardrail, +): + existing_tool = {"type": "function", "function": {"name": "my_tool", "parameters": {}}} + inputs = GenericGuardrailAPIInputs( + texts=["A" * 5000], + structured_messages=ORIGINAL_MESSAGES, + tools=[existing_tool], + ) + mock_response = _make_compress_response(COMPRESSED_MESSAGES_WITH_HASH) + + with patch.object( + guardrail.async_handler, + "post", + new_callable=AsyncMock, + return_value=mock_response, + ): + result = await guardrail.apply_guardrail( + inputs=inputs, + request_data={"model": "gpt-4o"}, + input_type="request", + ) + + tools = result.get("tools") + assert tools is not None + assert isinstance(tools, list) + assert any(isinstance(t, dict) and t.get("function", {}).get("name") == "my_tool" for t in tools) + assert has_headroom_retrieve_tool(tools) + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_returns_true_for_retrieve_call( + guardrail: HeadroomGuardrail, +): + retrieve_tool_def = [{"type": "function", "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME}}] + response = _make_openai_response_with_tool_call( + tool_name=HEADROOM_RETRIEVE_TOOL_NAME, + arguments={"hash": "b573993006976af767214fac"}, + ) + + should_run, ctx = await guardrail.async_should_run_agentic_loop( + response=response, + model="gpt-4o", + messages=[], + tools=retrieve_tool_def, + stream=False, + custom_llm_provider="openai", + kwargs={}, + ) + + assert should_run is True + assert len(ctx["tool_calls"]) == 1 + assert ctx["tool_calls"][0]["arguments"]["hash"] == "b573993006976af767214fac" + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_returns_false_without_retrieve_tool( + guardrail: HeadroomGuardrail, +): + other_tools = [{"type": "function", "function": {"name": "other_tool"}}] + response = _make_openai_response_with_tool_call( + tool_name="other_tool", + arguments={}, + ) + + should_run, _ = await guardrail.async_should_run_agentic_loop( + response=response, + model="gpt-4o", + messages=[], + tools=other_tools, + stream=False, + custom_llm_provider="openai", + kwargs={}, + ) + + assert should_run is False + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_returns_false_when_no_retrieve_calls( + guardrail: HeadroomGuardrail, +): + retrieve_tool_def = [{"type": "function", "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME}}] + response = _make_openai_response_with_tool_call( + tool_name="some_other_function", + arguments={}, + ) + + should_run, _ = await guardrail.async_should_run_agentic_loop( + response=response, + model="gpt-4o", + messages=[], + tools=retrieve_tool_def, + stream=False, + custom_llm_provider="openai", + kwargs={}, + ) + + assert should_run is False + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_calls_retrieve_and_builds_messages( + guardrail: HeadroomGuardrail, +): + original_content = "This is the full compressed content." + mock_retrieve = _make_retrieve_response(original_content) + + tool_calls = [ + { + "id": "call_abc123", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "b573993006976af767214fac"}, + } + ] + response = _make_openai_response_with_tool_call( + tool_name=HEADROOM_RETRIEVE_TOOL_NAME, + arguments={"hash": "b573993006976af767214fac"}, + tool_id="call_abc123", + ) + messages = [{"role": "user", "content": "What does it say? hash=b573993006976af767214fac"}] + guardrail._issued_hashes_by_call_id["call-1"] = ( + frozenset({"b573993006976af767214fac"}), + time.monotonic() + 999, + ) + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + return_value=mock_retrieve, + ) as mock_get: + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="gpt-4o", + messages=messages, + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-1"}, + ) + + assert plan.run_agentic_loop is True + assert plan.request_patch is not None + + follow_up = plan.request_patch.messages + assert follow_up is not None + + tool_result_message = next((m for m in follow_up if m.get("role") == "tool"), None) + assert tool_result_message is not None + assert tool_result_message["content"] == original_content + assert tool_result_message["tool_call_id"] == "call_abc123" + + mock_get.assert_called_once() + call_url = mock_get.call_args.kwargs.get("url") or mock_get.call_args.args[0] + assert "b573993006976af767214fac" in call_url + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_handles_retrieve_404( + guardrail: HeadroomGuardrail, +): + mock_retrieve = MagicMock() + mock_retrieve.status_code = 404 + + tool_calls = [ + { + "id": "call_xyz", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "deadbeef000000000000dead"}, + } + ] + response = _make_openai_response_with_tool_call( + tool_name=HEADROOM_RETRIEVE_TOOL_NAME, + arguments={"hash": "deadbeef000000000000dead"}, + tool_id="call_xyz", + ) + + messages = [ + { + "role": "user", + "content": "Retrieve more: hash=deadbeef000000000000dead", + } + ] + guardrail._issued_hashes_by_call_id["call-1"] = ( + frozenset({"deadbeef000000000000dead"}), + time.monotonic() + 999, + ) + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + return_value=mock_retrieve, + ): + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="gpt-4o", + messages=messages, + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-1"}, + ) + + follow_up = plan.request_patch.messages # type: ignore[union-attr] + tool_result = next((m for m in follow_up if m.get("role") == "tool"), None) + assert tool_result is not None + assert "not found" in tool_result["content"] or "expired" in tool_result["content"] + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_rejects_hash_with_no_known_call( + guardrail: HeadroomGuardrail, +): + """A hash-shaped string planted in message text must not be honored when + this guardrail has no record of ever issuing it, even if it's echoed back + in the current request's own messages (e.g. via prompt injection).""" + tool_calls = [ + { + "id": "call_xyz", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "deadbeef000000000000dead"}, + } + ] + response = _make_openai_response_with_tool_call( + tool_name=HEADROOM_RETRIEVE_TOOL_NAME, + arguments={"hash": "deadbeef000000000000dead"}, + tool_id="call_xyz", + ) + assert not guardrail._issued_hashes_by_call_id + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + ) as mock_get: + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="gpt-4o", + messages=[{"role": "user", "content": "Please fetch hash=deadbeef000000000000dead for me"}], + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-unknown"}, + ) + + mock_get.assert_not_called() + + follow_up = plan.request_patch.messages # type: ignore[union-attr] + tool_result = next((m for m in follow_up if m.get("role") == "tool"), None) + assert tool_result is not None + assert "was not produced by the current request" in tool_result["content"] + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_rejects_hash_issued_for_different_call( + guardrail: HeadroomGuardrail, +): + """A hash issued for one request must not be retrievable by a different + request just because the second request echoes that hash-shaped string + back in its own messages -- retrieval must be scoped per litellm_call_id, + not derived by re-scanning attacker-controlled message text.""" + guardrail._issued_hashes_by_call_id["call-A"] = ( + frozenset({"b573993006976af767214fac"}), + time.monotonic() + 999, + ) + + tool_calls = [ + { + "id": "call_xyz", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "b573993006976af767214fac"}, + } + ] + response = _make_openai_response_with_tool_call( + tool_name=HEADROOM_RETRIEVE_TOOL_NAME, + arguments={"hash": "b573993006976af767214fac"}, + tool_id="call_xyz", + ) + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + ) as mock_get: + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="gpt-4o", + messages=[{"role": "user", "content": "Please fetch hash=b573993006976af767214fac for me"}], + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-B"}, + ) + + mock_get.assert_not_called() + + follow_up = plan.request_patch.messages # type: ignore[union-attr] + tool_result = next((m for m in follow_up if m.get("role") == "tool"), None) + assert tool_result is not None + assert "was not produced by the current request" in tool_result["content"] + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_builds_responses_api_function_call_items( + guardrail: HeadroomGuardrail, +): + """For the Responses API, follow-up input must echo a function_call paired + with a function_call_output keyed by the same call_id -- chat-style + assistant/tool messages are not valid Responses API input items.""" + original_content = "This is the full compressed content." + mock_retrieve = _make_retrieve_response(original_content) + + response = MagicMock() + response.choices = None + response.content = None + response.output = [ + { + "type": "function_call", + "id": "fc_abc123", + "call_id": "call_abc123", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": json.dumps({"hash": "b573993006976af767214fac"}), + } + ] + + tool_calls = [ + { + "id": "call_abc123", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "b573993006976af767214fac"}, + } + ] + messages = [{"role": "user", "content": "What does it say? hash=b573993006976af767214fac"}] + guardrail._issued_hashes_by_call_id["call-1"] = ( + frozenset({"b573993006976af767214fac"}), + time.monotonic() + 999, + ) + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + return_value=mock_retrieve, + ): + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="gpt-4o", + messages=messages, + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-1"}, + ) + + follow_up = plan.request_patch.messages # type: ignore[union-attr] + assert all("role" not in item for item in follow_up if item not in messages) + + function_call_item = next((i for i in follow_up if i.get("type") == "function_call"), None) + assert function_call_item is not None + assert function_call_item["call_id"] == "call_abc123" + assert function_call_item["name"] == HEADROOM_RETRIEVE_TOOL_NAME + + output_item = next((i for i in follow_up if i.get("type") == "function_call_output"), None) + assert output_item is not None + assert output_item["call_id"] == "call_abc123" + assert output_item["output"] == original_content + + +@pytest.mark.asyncio +async def test_async_build_agentic_loop_plan_builds_anthropic_tool_result_messages( + guardrail: HeadroomGuardrail, +): + """For the Anthropic Messages API, follow-up must echo a tool_use content + block in an assistant message paired with a tool_result content block in a + user message keyed by the same tool_use_id -- chat-style tool-role + messages are not valid Anthropic input. + + AnthropicMessagesResponse is a TypedDict, so real responses are plain + dicts at runtime; a MagicMock response here would pass even if branch + selection used bare getattr() and silently fell through to the + chat-completions replay shape for every real Anthropic response. + """ + original_content = "This is the full compressed content." + mock_retrieve = _make_retrieve_response(original_content) + + response = { + "content": [ + { + "type": "tool_use", + "id": "toolu_abc123", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input": {"hash": "b573993006976af767214fac"}, + } + ] + } + + tool_calls = [ + { + "id": "toolu_abc123", + "type": "function", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": {"hash": "b573993006976af767214fac"}, + } + ] + messages = [{"role": "user", "content": "What does it say? hash=b573993006976af767214fac"}] + guardrail._issued_hashes_by_call_id["call-1"] = ( + frozenset({"b573993006976af767214fac"}), + time.monotonic() + 999, + ) + + with patch.object( + guardrail.async_handler, + "get", + new_callable=AsyncMock, + return_value=mock_retrieve, + ): + plan = await guardrail.async_build_agentic_loop_plan( + tools={"tool_calls": tool_calls}, + model="claude-sonnet-4-5", + messages=messages, + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={}, + logging_obj=None, + stream=False, + kwargs={"litellm_call_id": "call-1"}, + ) + + follow_up = plan.request_patch.messages # type: ignore[union-attr] + assert all(m.get("role") != "tool" for m in follow_up) + + assistant_message = next((m for m in follow_up if m.get("role") == "assistant"), None) + assert assistant_message is not None + tool_use_block = next((b for b in assistant_message["content"] if b.get("type") == "tool_use"), None) + assert tool_use_block is not None + assert tool_use_block["id"] == "toolu_abc123" + + user_message = follow_up[-1] + assert user_message["role"] == "user" + tool_result_block = next((b for b in user_message["content"] if b.get("type") == "tool_result"), None) + assert tool_result_block is not None + assert tool_result_block["tool_use_id"] == "toolu_abc123" + assert tool_result_block["content"] == original_content + + +def test_extract_hashes_from_messages_finds_hashes(): + messages = [ + {"role": "user", "content": "Retrieve more: hash=b573993006976af767214fac"}, + {"role": "assistant", "content": "Also: hash=aabbccdd001122334455aabb"}, + ] + hashes = extract_hashes_from_messages(messages) + assert "b573993006976af767214fac" in hashes + assert "aabbccdd001122334455aabb" in hashes + + +def test_extract_hashes_from_messages_ignores_short_hashes(): + messages = [{"role": "user", "content": "hash=tooshort"}] + hashes = extract_hashes_from_messages(messages) + assert not hashes + + +def test_extract_hashes_from_list_content_blocks(): + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "hash=b573993006976af767214fac found here"}, + ], + } + ] + hashes = extract_hashes_from_messages(messages) + assert "b573993006976af767214fac" in hashes + + +def test_has_headroom_retrieve_tool_recognizes_anthropic_native_shape(): + """By the time an Anthropic Messages API response reaches the agentic-loop + gate, the OpenAI-shaped tool this guardrail injects (type: "function") + has already been transformed into Anthropic's native tool shape + (type: "custom", top-level "name", no nested "function" object).""" + anthropic_native_tools = [ + { + "type": "custom", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input_schema": {"type": "object", "properties": {"hash": {"type": "string"}}}, + } + ] + assert has_headroom_retrieve_tool(anthropic_native_tools) + assert not has_headroom_retrieve_tool([{"type": "custom", "name": "some_other_tool"}]) + + @pytest.mark.asyncio async def test_apply_guardrail_bypass_header_skips_compression( guardrail: HeadroomGuardrail, @@ -97,9 +705,7 @@ async def test_apply_guardrail_bypass_header_skips_compression( ) request_data = {"proxy_server_request": {"headers": {"x-headroom-bypass": "true"}}} - with patch.object( - guardrail.async_handler, "post", new_callable=AsyncMock - ) as mock_post: + with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post: result = await guardrail.apply_guardrail( inputs=inputs, request_data=request_data, @@ -119,9 +725,7 @@ async def test_apply_guardrail_response_type_passthrough( structured_messages=ORIGINAL_MESSAGES, ) - with patch.object( - guardrail.async_handler, "post", new_callable=AsyncMock - ) as mock_post: + with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post: result = await guardrail.apply_guardrail( inputs=inputs, request_data={}, @@ -138,9 +742,7 @@ async def test_apply_guardrail_empty_structured_messages_passthrough( ): inputs = GenericGuardrailAPIInputs(texts=["hello"]) - with patch.object( - guardrail.async_handler, "post", new_callable=AsyncMock - ) as mock_post: + with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post: result = await guardrail.apply_guardrail( inputs=inputs, request_data={}, @@ -277,9 +879,7 @@ def test_bypass_header_case_insensitive(): guardrail = _make_guardrail() for header_value in ("true", "True", "TRUE"): - data = { - "proxy_server_request": {"headers": {"x-headroom-bypass": header_value}} - } + data = {"proxy_server_request": {"headers": {"x-headroom-bypass": header_value}}} assert guardrail._should_bypass(data) is True data = {"proxy_server_request": {"headers": {"x-headroom-bypass": "false"}}} @@ -344,3 +944,118 @@ async def test_apply_guardrail_sends_model_from_request_data_when_no_config_mode call_kwargs = mock_post.call_args sent_payload = call_kwargs.kwargs.get("json") or call_kwargs.args[1] assert sent_payload.get("model") == "gpt-4o" + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_detects_anthropic_content_block_format( + guardrail: HeadroomGuardrail, +): + # Anthropic's native tool format (type: "custom", top-level "name") -- + # by the time a Messages API response reaches this gate, the OpenAI-shaped + # tool this guardrail injects has already been transformed into this shape. + retrieve_tool_def = [ + { + "type": "custom", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input_schema": {"type": "object", "properties": {"hash": {"type": "string"}}}, + } + ] + + response = MagicMock() + response.choices = None + response.content = [ + { + "type": "tool_use", + "id": "toolu_abc", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input": {"hash": "b573993006976af767214fac"}, + } + ] + + should_run, ctx = await guardrail.async_should_run_agentic_loop( + response=response, + model="claude-sonnet-4-6", + messages=[], + tools=retrieve_tool_def, + stream=False, + custom_llm_provider="anthropic", + kwargs={}, + ) + + assert should_run is True + assert len(ctx["tool_calls"]) == 1 + assert ctx["tool_calls"][0]["arguments"]["hash"] == "b573993006976af767214fac" + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_detects_anthropic_response_as_plain_dict( + guardrail: HeadroomGuardrail, +): + """AnthropicMessagesResponse is a TypedDict -- real Messages API responses + are plain dicts at runtime, not objects with attribute access. A + MagicMock-only test would pass even if detection used bare getattr() and + silently treated every real response as having no tool calls.""" + retrieve_tool_def = [ + { + "type": "custom", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input_schema": {"type": "object", "properties": {"hash": {"type": "string"}}}, + } + ] + response = { + "content": [ + { + "type": "tool_use", + "id": "toolu_abc", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "input": {"hash": "b573993006976af767214fac"}, + } + ] + } + + should_run, ctx = await guardrail.async_should_run_agentic_loop( + response=response, + model="claude-sonnet-4-6", + messages=[], + tools=retrieve_tool_def, + stream=False, + custom_llm_provider="anthropic", + kwargs={}, + ) + + assert should_run is True + assert len(ctx["tool_calls"]) == 1 + assert ctx["tool_calls"][0]["arguments"]["hash"] == "b573993006976af767214fac" + + +@pytest.mark.asyncio +async def test_async_should_run_agentic_loop_detects_responses_api_output_format( + guardrail: HeadroomGuardrail, +): + retrieve_tool_def = [{"type": "function", "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME}}] + + response = MagicMock() + response.choices = None + response.content = None + response.output = [ + { + "type": "function_call", + "id": "fc_abc123", + "name": HEADROOM_RETRIEVE_TOOL_NAME, + "arguments": json.dumps({"hash": "b573993006976af767214fac"}), + } + ] + + should_run, ctx = await guardrail.async_should_run_agentic_loop( + response=response, + model="gpt-4o", + messages=[], + tools=retrieve_tool_def, + stream=False, + custom_llm_provider="openai", + kwargs={}, + ) + + assert should_run is True + assert len(ctx["tool_calls"]) == 1 + assert ctx["tool_calls"][0]["arguments"]["hash"] == "b573993006976af767214fac" From 23af78465c877f5f7f02c53d9f04cf1af612f7a9 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Tue, 30 Jun 2026 19:31:51 -0700 Subject: [PATCH 49/79] feat: add cache control injection support for v1/messages endpoint (#31778) * feat: add cache control injection support for v1/messages endpoint Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * fix: normalize string content to list for Anthropic-native cache_control injection Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor: simplify cache control injection, fix system=[] bug, fix handler system type Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * refactor: extract cache control logic into static helper on AnthropicCacheControlHook Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Krrish Dholakia Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- .../anthropic_cache_control_hook.py | 97 ++++- .../messages/handler.py | 16 +- .../test_anthropic_cache_control_hook.py | 400 +++++++++++------- 3 files changed, 356 insertions(+), 157 deletions(-) diff --git a/litellm/integrations/anthropic_cache_control_hook.py b/litellm/integrations/anthropic_cache_control_hook.py index 1314fd82255..608fdebc1d9 100644 --- a/litellm/integrations/anthropic_cache_control_hook.py +++ b/litellm/integrations/anthropic_cache_control_hook.py @@ -1,9 +1,12 @@ """ -This hook is used to inject cache control directives into the messages of a chat completion. +This hook is used to inject cache control directives into messages. Users can define - `cache_control_injection_points` in the completion params and litellm will inject the cache control directives into the messages at the specified injection points. +Supported for both `v1/chat/completions` (via the prompt-management hook) and +`v1/messages` (via `apply_to_anthropic_messages_request`). + """ import copy @@ -225,6 +228,98 @@ class AnthropicCacheControlHook(CustomPromptManagement): message_content[-1]["cache_control"] = control # type: ignore return message + @staticmethod + def apply_to_anthropic_messages_request( + messages: List[Dict], + system: str | list | None, + injection_points: List[CacheControlInjectionPoint], + ) -> Tuple[List[Dict], str | list | None, List[CacheControlInjectionPoint]]: + """Apply cache control injection for the Anthropic-native v1/messages endpoint. + + Returns (messages, system, remaining_non_message_points). + """ + if not injection_points: + return messages, system, [] + + processed_messages: List[Dict] = copy.deepcopy(messages) + processed_system = copy.deepcopy(system) if system is not None else None + + message_points: List[CacheControlMessageInjectionPoint] = [] + system_points: List[CacheControlMessageInjectionPoint] = [] + remaining_points: List[CacheControlInjectionPoint] = [] + + for point in injection_points: + if point.get("location") == "message": + msg_point = cast(CacheControlMessageInjectionPoint, point) + if msg_point.get("role") == "system": + system_points.append(msg_point) + else: + message_points.append(msg_point) + else: + remaining_points.append(point) + + reserved_blocks = 1 if any(p.get("location") == "tool_config" for p in remaining_points) else 0 + max_blocks = MAX_CACHE_CONTROL_BLOCKS - reserved_blocks + + used_blocks = sum( + AnthropicCacheControlHook._count_cache_control_blocks(cast(AllMessageValues, msg)) + for msg in processed_messages + ) + if isinstance(processed_system, list): + used_blocks += sum( + 1 for b in processed_system if isinstance(b, dict) and b.get("cache_control") is not None + ) + + if system_points and processed_system is not None and used_blocks < max_blocks: + system_already_has_cc = isinstance(processed_system, list) and any( + isinstance(b, dict) and b.get("cache_control") is not None for b in processed_system + ) + if not system_already_has_cc: + control = system_points[0].get("control") or ChatCompletionCachedContent(type="ephemeral") + if isinstance(processed_system, str): + processed_system = [{"type": "text", "text": processed_system, "cache_control": control}] + used_blocks += 1 + elif len(processed_system) > 0 and isinstance(processed_system[-1], dict): + processed_system[-1] = {**processed_system[-1], "cache_control": control} + used_blocks += 1 + + for i, msg in enumerate(processed_messages): + content = msg.get("content") + if isinstance(content, str): + processed_messages[i] = {**msg, "content": [{"type": "text", "text": content}]} + + processed_messages = AnthropicCacheControlHook._apply_message_injections( + points=message_points, + messages=cast(List[AllMessageValues], processed_messages), + max_blocks=max_blocks - used_blocks, + ) + + return processed_messages, processed_system, remaining_points + + @staticmethod + def maybe_inject_cache_control( + messages: List[Dict], + system: str | list | None, + kwargs: Dict[str, Any], + ) -> Tuple[List[Dict], str | list | None]: + """Extract cache_control_injection_points from kwargs and apply if present. + + Pops the key from kwargs; if remaining (non-message) points exist they + are written back so downstream transforms can handle them. + """ + injection_points = kwargs.pop("cache_control_injection_points", None) + if not injection_points: + return messages, system + + messages, system, remaining = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + if remaining: + kwargs["cache_control_injection_points"] = remaining + return messages, system + @property def integration_name(self) -> str: """Return the integration name for this hook.""" diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py index 547ddd9b8d3..effd7dda6a0 100644 --- a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py +++ b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py @@ -199,7 +199,7 @@ async def anthropic_messages( metadata: Optional[Dict] = None, stop_sequences: Optional[List[str]] = None, stream: Optional[bool] = False, - system: Optional[str] = None, + system: Optional[Union[str, list]] = None, temperature: Optional[float] = None, thinking: Optional[Dict] = None, tool_choice: Optional[Dict] = None, @@ -230,6 +230,12 @@ async def anthropic_messages( # ids like ``functions.Bash:0`` that violate Anthropic's id pattern. messages = sanitize_tool_use_ids_in_anthropic_messages(messages) + from litellm.integrations.anthropic_cache_control_hook import ( + AnthropicCacheControlHook, + ) + + messages, system = AnthropicCacheControlHook.maybe_inject_cache_control(messages, system, kwargs) + original_stream = stream or kwargs.get("_websearch_interception_converted_stream", False) # Execute pre-request hooks to allow CustomLoggers to modify request. @@ -375,7 +381,7 @@ def anthropic_messages_handler( metadata: Optional[Dict] = None, stop_sequences: Optional[List[str]] = None, stream: Optional[bool] = False, - system: Optional[str] = None, + system: Optional[Union[str, list]] = None, temperature: Optional[float] = None, thinking: Optional[Dict] = None, tool_choice: Optional[Dict] = None, @@ -412,6 +418,12 @@ def anthropic_messages_handler( messages = strip_empty_text_blocks_from_anthropic_messages(messages) messages = sanitize_tool_use_ids_in_anthropic_messages(messages) + from litellm.integrations.anthropic_cache_control_hook import ( + AnthropicCacheControlHook, + ) + + messages, system = AnthropicCacheControlHook.maybe_inject_cache_control(messages, system, kwargs) + metadata = validate_anthropic_api_metadata(metadata) local_vars = locals() diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py index 6afe5efc54d..4664cc86303 100644 --- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py +++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py @@ -1,3 +1,4 @@ +import copy import datetime import json import os @@ -9,9 +10,7 @@ from unittest.mock import ANY, MagicMock, Mock, patch import httpx import pytest -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system-path +sys.path.insert(0, os.path.abspath("../..")) # Adds the parent directory to the system-path import litellm from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler @@ -93,13 +92,9 @@ async def test_anthropic_cache_control_hook_system_message(): # Verify that cache control was applied (Bedrock transforms it to a separate item) cache_control_count = sum( - 1 - for item in request_body["system"] - if isinstance(item, dict) and "cachePoint" in item + 1 for item in request_body["system"] if isinstance(item, dict) and "cachePoint" in item ) - assert ( - cache_control_count == 1 - ), f"Expected exactly 1 cache control point, found {cache_control_count}" + assert cache_control_count == 1, f"Expected exactly 1 cache control point, found {cache_control_count}" @pytest.mark.asyncio @@ -171,9 +166,7 @@ async def test_anthropic_cache_control_hook_user_message(): print("request_body: ", json.dumps(request_body, indent=4)) # Verify the request body - assert request_body["messages"][1]["content"][1]["cachePoint"] == { - "type": "default" - } + assert request_body["messages"][1]["content"][1]["cachePoint"] == {"type": "default"} @pytest.mark.asyncio @@ -262,14 +255,10 @@ async def test_anthropic_cache_control_hook_negative_indices(): # Verify the last message (input index -1 -> request index 2) has cache control last_message_content = request_body["messages"][2]["content"] - assert isinstance( - last_message_content, list - ), "Last message content should be a list" - assert any( - "cachePoint" in item - for item in last_message_content - if isinstance(item, dict) - ), "CachePoint missing in last message" + assert isinstance(last_message_content, list), "Last message content should be a list" + assert any("cachePoint" in item for item in last_message_content if isinstance(item, dict)), ( + "CachePoint missing in last message" + ) # Note: Based on debug output, the hook correctly applies cache control to both messages, # but the Bedrock API transformation appears to only preserve cache control for user messages, @@ -278,30 +267,20 @@ async def test_anthropic_cache_control_hook_negative_indices(): # The second-to-last message (assistant) gets cache_control from the hook but loses it # during API transformation. This test documents this behavior. second_last_message_content = request_body["messages"][1]["content"] - assert isinstance( - second_last_message_content, list - ), "Second-to-last message content should be a list" + assert isinstance(second_last_message_content, list), "Second-to-last message content should be a list" # Check if assistant message cache control is preserved (currently it's not) assistant_has_cache_control = any( - "cachePoint" in item - for item in second_last_message_content - if isinstance(item, dict) - ) - print( - f"Assistant message has cache control in final request: {assistant_has_cache_control}" + "cachePoint" in item for item in second_last_message_content if isinstance(item, dict) ) + print(f"Assistant message has cache control in final request: {assistant_has_cache_control}") # Verify the first user message (request index 0) was NOT modified first_user_message_content = request_body["messages"][0]["content"] - assert isinstance( - first_user_message_content, list - ), "First user message content should be a list" - assert not any( - "cachePoint" in item - for item in first_user_message_content - if isinstance(item, dict) - ), "CachePoint unexpectedly found in first user message" + assert isinstance(first_user_message_content, list), "First user message content should be a list" + assert not any("cachePoint" in item for item in first_user_message_content if isinstance(item, dict)), ( + "CachePoint unexpectedly found in first user message" + ) @pytest.mark.asyncio @@ -342,9 +321,7 @@ async def test_anthropic_cache_control_hook_out_of_bounds_logging(): client = AsyncHTTPHandler() # Mock the verbose_logger to capture warning calls - with patch( - "litellm.integrations.anthropic_cache_control_hook.verbose_logger" - ) as mock_logger: + with patch("litellm.integrations.anthropic_cache_control_hook.verbose_logger") as mock_logger: with patch.object(client, "post", return_value=mock_response) as mock_post: messages = [ {"role": "user", "content": "Message 1"}, @@ -354,9 +331,7 @@ async def test_anthropic_cache_control_hook_out_of_bounds_logging(): await litellm.acompletion( model="bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0", messages=messages, - cache_control_injection_points=[ - {"location": "message", "index": 10} - ], # Out of bounds index + cache_control_injection_points=[{"location": "message", "index": 10}], # Out of bounds index client=client, ) @@ -365,10 +340,7 @@ async def test_anthropic_cache_control_hook_out_of_bounds_logging(): warning_call = mock_logger.warning.call_args[0][0] # Check that the warning message contains the expected information - assert ( - "AnthropicCacheControlHook: Provided index 10 is out of bounds" - in warning_call - ) + assert "AnthropicCacheControlHook: Provided index 10 is out of bounds" in warning_call assert "message list of length 2" in warning_call assert "Targeted index was 10" in warning_call assert "Skipping cache control injection for this point" in warning_call @@ -411,9 +383,7 @@ async def test_anthropic_cache_control_hook_negative_out_of_bounds_logging(): client = AsyncHTTPHandler() # Mock the verbose_logger to capture warning calls - with patch( - "litellm.integrations.anthropic_cache_control_hook.verbose_logger" - ) as mock_logger: + with patch("litellm.integrations.anthropic_cache_control_hook.verbose_logger") as mock_logger: with patch.object(client, "post", return_value=mock_response) as mock_post: messages = [ {"role": "user", "content": "Single message"}, @@ -436,14 +406,9 @@ async def test_anthropic_cache_control_hook_negative_out_of_bounds_logging(): warning_call = mock_logger.warning.call_args[0][0] # Check that the warning message contains the original negative index - assert ( - "AnthropicCacheControlHook: Provided index -5 is out of bounds" - in warning_call - ) + assert "AnthropicCacheControlHook: Provided index -5 is out of bounds" in warning_call assert "message list of length 1" in warning_call - assert ( - "Targeted index was -4" in warning_call - ) # -5 + 1 = -4 (converted index) + assert "Targeted index was -4" in warning_call # -5 + 1 = -4 (converted index) assert "Skipping cache control injection for this point" in warning_call @@ -531,15 +496,11 @@ async def test_anthropic_cache_control_hook_multiple_user_messages(): # Count cache control points - should have 2 since both injection points were applied cache_control_count = sum( - 1 - for item in combined_message_content - if isinstance(item, dict) and "cachePoint" in item + 1 for item in combined_message_content if isinstance(item, dict) and "cachePoint" in item ) assert cache_control_count == 2 - print( - f"Found {cache_control_count} cache control points in the combined message" - ) + print(f"Found {cache_control_count} cache control points in the combined message") @pytest.mark.asyncio @@ -588,9 +549,7 @@ async def test_anthropic_cache_control_hook_out_of_bounds(bad_index): await litellm.acompletion( model="bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0", messages=messages, - cache_control_injection_points=[ - {"location": "message", "index": bad_index} - ], + cache_control_injection_points=[{"location": "message", "index": bad_index}], client=client, ) @@ -601,19 +560,13 @@ async def test_anthropic_cache_control_hook_out_of_bounds(bad_index): for msg in request_body["messages"]: content = msg.get("content", []) if isinstance(content, list): - assert not any( - "cachePoint" in item - for item in content - if isinstance(item, dict) - ) + assert not any("cachePoint" in item for item in content if isinstance(item, dict)) @pytest.mark.asyncio @pytest.mark.parametrize( "message_list", - [ - [{"role": "user", "content": "Single message"}] - ], # Single message only - empty list will fail at API level + [[{"role": "user", "content": "Single message"}]], # Single message only - empty list will fail at API level ) async def test_anthropic_cache_control_hook_single_message(message_list): """ @@ -662,9 +615,7 @@ async def test_anthropic_cache_control_hook_single_message(message_list): # For the single message, verify cache control was applied content = request_body["messages"][0]["content"] assert isinstance(content, list) - assert any( - "cachePoint" in item for item in content if isinstance(item, dict) - ) + assert any("cachePoint" in item for item in content if isinstance(item, dict)) @pytest.mark.asyncio @@ -693,9 +644,7 @@ async def test_anthropic_cache_control_hook_empty_message_list(): await litellm.acompletion( model="bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0", messages=[], - cache_control_injection_points=[ - {"location": "message", "index": -1} - ], + cache_control_injection_points=[{"location": "message", "index": -1}], client=client, ) @@ -755,11 +704,7 @@ async def test_anthropic_cache_control_hook_no_op(): for msg in request_body["messages"]: content = msg.get("content", []) if isinstance(content, list): - assert not any( - "cachePoint" in item - for item in content - if isinstance(item, dict) - ) + assert not any("cachePoint" in item for item in content if isinstance(item, dict)) @pytest.mark.asyncio @@ -827,14 +772,10 @@ async def test_anthropic_cache_control_hook_multiple_content_items_last_only(): message_content = request_body["messages"][0]["content"] assert isinstance(message_content, list) - cache_control_count = sum( - 1 - for item in message_content - if isinstance(item, dict) and "cachePoint" in item + cache_control_count = sum(1 for item in message_content if isinstance(item, dict) and "cachePoint" in item) + assert cache_control_count == 1, ( + f"Expected exactly 1 cache control point, found {cache_control_count}. This test verifies the fix for issue 15696 where cache_control was incorrectly applied to ALL content items." ) - assert ( - cache_control_count == 1 - ), f"Expected exactly 1 cache control point, found {cache_control_count}. This test verifies the fix for issue 15696 where cache_control was incorrectly applied to ALL content items." @pytest.mark.asyncio @@ -891,30 +832,22 @@ async def test_anthropic_cache_control_hook_document_analysis_multiple_pages(): ], } ], - cache_control_injection_points=[ - {"location": "message", "role": "user"} - ], + cache_control_injection_points=[{"location": "message", "role": "user"}], client=client, ) mock_post.assert_called_once() request_body = json.loads(mock_post.call_args.kwargs["data"]) - print( - "Document analysis request_body: ", json.dumps(request_body, indent=4) - ) + print("Document analysis request_body: ", json.dumps(request_body, indent=4)) message_content = request_body["messages"][0]["content"] assert isinstance(message_content, list) - cache_control_count = sum( - 1 - for item in message_content - if isinstance(item, dict) and "cachePoint" in item + cache_control_count = sum(1 for item in message_content if isinstance(item, dict) and "cachePoint" in item) + assert cache_control_count == 1, ( + f"Expected exactly 1 cache control point (last item only), found {cache_control_count}. Before fix, this would be 6 (one for each content item)." ) - assert ( - cache_control_count == 1 - ), f"Expected exactly 1 cache control point (last item only), found {cache_control_count}. Before fix, this would be 6 (one for each content item)." def test_gemini_cache_control_injection_points_detected(): @@ -1076,13 +1009,8 @@ async def test_anthropic_cache_control_hook_string_negative_index(): # The last user message should have cache control applied last_message = request_body["messages"][-1] last_message_content = last_message["content"] - assert isinstance( - last_message_content, list - ), f"Expected list content, got {type(last_message_content)}" - has_cache_point = any( - isinstance(item, dict) and "cachePoint" in item - for item in last_message_content - ) + assert isinstance(last_message_content, list), f"Expected list content, got {type(last_message_content)}" + has_cache_point = any(isinstance(item, dict) and "cachePoint" in item for item in last_message_content) assert has_cache_point, ( f"Expected cachePoint in last message content, got: {last_message_content}. " "String index '-1' was not parsed correctly (str.isdigit() returns False for negative strings)." @@ -1146,17 +1074,13 @@ def test_cache_control_hook_caps_at_four_blocks_with_client_cache_control(): _, processed, _ = hook.get_chat_completion_prompt( model="bedrock/us.anthropic.claude-opus-4-6-v1:0", messages=messages, - non_default_params={ - "cache_control_injection_points": _build_injection_points() - }, + non_default_params={"cache_control_injection_points": _build_injection_points()}, prompt_id=None, prompt_variables=None, dynamic_callback_params={}, ) - assert ( - _count_cache_control(processed) == 4 - ), "Hook must cap cache_control at Anthropic's limit of 4 blocks" + assert _count_cache_control(processed) == 4, "Hook must cap cache_control at Anthropic's limit of 4 blocks" # Client TTL on system blocks must be preserved (not overwritten by config). for i in range(4): @@ -1170,11 +1094,7 @@ def test_cache_control_hook_caps_at_four_blocks_with_client_cache_control(): assert user_message.get("cache_control") is None user_content = user_message.get("content") if isinstance(user_content, list): - assert all( - block.get("cache_control") is None - for block in user_content - if isinstance(block, dict) - ) + assert all(block.get("cache_control") is None for block in user_content if isinstance(block, dict)) def test_cache_control_hook_caps_at_four_blocks_without_client_cache_control(): @@ -1184,17 +1104,13 @@ def test_cache_control_hook_caps_at_four_blocks_without_client_cache_control(): """ hook = AnthropicCacheControlHook() - messages: List[AllMessageValues] = [ - {"role": "system", "content": f"System {i}"} for i in range(4) - ] + messages: List[AllMessageValues] = [{"role": "system", "content": f"System {i}"} for i in range(4)] messages.append({"role": "user", "content": "hello"}) _, processed, _ = hook.get_chat_completion_prompt( model="bedrock/us.anthropic.claude-opus-4-6-v1:0", messages=messages, - non_default_params={ - "cache_control_injection_points": _build_injection_points() - }, + non_default_params={"cache_control_injection_points": _build_injection_points()}, prompt_id=None, prompt_variables=None, dynamic_callback_params={}, @@ -1303,18 +1219,12 @@ async def test_cache_control_hook_bedrock_payload_caps_cachepoints_at_four(): request_body = json.loads(mock_post.call_args.kwargs["data"]) cache_points = sum( - 1 - for block in request_body.get("system", []) - if isinstance(block, dict) and "cachePoint" in block + 1 for block in request_body.get("system", []) if isinstance(block, dict) and "cachePoint" in block ) for msg in request_body.get("messages", []): content = msg.get("content", []) if isinstance(content, list): - cache_points += sum( - 1 - for block in content - if isinstance(block, dict) and "cachePoint" in block - ) + cache_points += sum(1 for block in content if isinstance(block, dict) and "cachePoint" in block) assert cache_points <= 4, ( f"Bedrock payload exceeded Anthropic's 4 cache_control block limit: " @@ -1331,9 +1241,7 @@ def test_cache_control_hook_reserves_slot_for_tool_config_point(): """ hook = AnthropicCacheControlHook() - messages: List[AllMessageValues] = [ - {"role": "system", "content": f"System {i}"} for i in range(4) - ] + messages: List[AllMessageValues] = [{"role": "system", "content": f"System {i}"} for i in range(4)] messages.append({"role": "user", "content": "hello"}) _, processed, non_default_params = hook.get_chat_completion_prompt( @@ -1356,9 +1264,7 @@ def test_cache_control_hook_reserves_slot_for_tool_config_point(): assert _count_cache_control(processed) == 3 # The tool_config point is passed through for the provider transform. - assert non_default_params["cache_control_injection_points"] == [ - {"location": "tool_config"} - ] + assert non_default_params["cache_control_injection_points"] == [{"location": "tool_config"}] @pytest.mark.asyncio @@ -1384,9 +1290,7 @@ async def test_cache_control_hook_bedrock_payload_caps_with_tool_config_point(): client = AsyncHTTPHandler() with patch.object(client, "post", return_value=mock_response) as mock_post: - messages = [ - {"role": "system", "content": f"System block {i}"} for i in range(4) - ] + messages = [{"role": "system", "content": f"System block {i}"} for i in range(4)] messages.append({"role": "user", "content": "What is the weather?"}) await litellm.acompletion( @@ -1421,18 +1325,12 @@ async def test_cache_control_hook_bedrock_payload_caps_with_tool_config_point(): request_body = json.loads(mock_post.call_args.kwargs["data"]) cache_points = sum( - 1 - for block in request_body.get("system", []) - if isinstance(block, dict) and "cachePoint" in block + 1 for block in request_body.get("system", []) if isinstance(block, dict) and "cachePoint" in block ) for msg in request_body.get("messages", []): content = msg.get("content", []) if isinstance(content, list): - cache_points += sum( - 1 - for block in content - if isinstance(block, dict) and "cachePoint" in block - ) + cache_points += sum(1 for block in content if isinstance(block, dict) and "cachePoint" in block) for tool in request_body.get("toolConfig", {}).get("tools", []): if isinstance(tool, dict) and "cachePoint" in tool: cache_points += 1 @@ -1441,3 +1339,197 @@ async def test_cache_control_hook_bedrock_payload_caps_with_tool_config_point(): f"Bedrock payload exceeded Anthropic's 4 cache_control block limit " f"when mixing message and tool_config injection: found {cache_points}" ) + + +class TestApplyToAnthropicMessagesRequest: + """Tests for apply_to_anthropic_messages_request (v1/messages cache control).""" + + def test_system_string_injection(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + system = "You are helpful" + injection_points = [{"location": "message", "role": "system"}] + + result_msgs, result_sys, remaining = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + assert result_sys == [{"type": "text", "text": "You are helpful", "cache_control": {"type": "ephemeral"}}] + assert result_msgs == messages + assert remaining == [] + + def test_system_list_injection(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + system = [ + {"type": "text", "text": "Part 1"}, + {"type": "text", "text": "Part 2"}, + ] + injection_points = [{"location": "message", "role": "system"}] + + _, result_sys, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + assert result_sys[0] == {"type": "text", "text": "Part 1"} + assert result_sys[1] == {"type": "text", "text": "Part 2", "cache_control": {"type": "ephemeral"}} + + def test_user_message_injection_by_role(self): + messages = [ + {"role": "user", "content": [{"type": "text", "text": "First"}]}, + {"role": "assistant", "content": [{"type": "text", "text": "Response"}]}, + {"role": "user", "content": [{"type": "text", "text": "Second"}]}, + ] + injection_points = [{"location": "message", "role": "user"}] + + result_msgs, _, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=None, + injection_points=injection_points, + ) + + assert result_msgs[0]["content"][-1].get("cache_control") == {"type": "ephemeral"} + assert result_msgs[2]["content"][-1].get("cache_control") == {"type": "ephemeral"} + assert result_msgs[1]["content"][-1].get("cache_control") is None + + def test_message_injection_by_index(self): + messages = [ + {"role": "user", "content": [{"type": "text", "text": "First"}]}, + {"role": "assistant", "content": [{"type": "text", "text": "Response"}]}, + {"role": "user", "content": [{"type": "text", "text": "Second"}]}, + ] + injection_points = [{"location": "message", "index": -1}] + + result_msgs, _, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=None, + injection_points=injection_points, + ) + + assert result_msgs[2]["content"][-1].get("cache_control") == {"type": "ephemeral"} + assert result_msgs[0]["content"][-1].get("cache_control") is None + assert result_msgs[1]["content"][-1].get("cache_control") is None + + def test_mixed_system_and_message_injection(self): + messages = [ + {"role": "user", "content": [{"type": "text", "text": "Hello"}]}, + {"role": "assistant", "content": [{"type": "text", "text": "Hi"}]}, + {"role": "user", "content": [{"type": "text", "text": "Question"}]}, + ] + system = "System prompt" + injection_points = [ + {"location": "message", "role": "system"}, + {"location": "message", "index": -1}, + ] + + result_msgs, result_sys, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + assert result_sys[0]["cache_control"] == {"type": "ephemeral"} + assert result_msgs[2]["content"][-1].get("cache_control") == {"type": "ephemeral"} + + def test_respects_max_4_blocks(self): + messages = [{"role": "user", "content": [{"type": "text", "text": f"Msg {i}"}]} for i in range(6)] + system = "System" + injection_points = [ + {"location": "message", "role": "system"}, + {"location": "message", "role": "user"}, + ] + + result_msgs, result_sys, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + sys_blocks = sum(1 for b in (result_sys or []) if isinstance(b, dict) and b.get("cache_control") is not None) + total_blocks = sys_blocks + sum(AnthropicCacheControlHook._count_cache_control_blocks(m) for m in result_msgs) + assert total_blocks <= 4 + + def test_tool_config_points_forwarded_as_remaining(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + injection_points = [ + {"location": "message", "role": "user"}, + {"location": "tool_config"}, + ] + + _, _, remaining = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=None, + injection_points=injection_points, + ) + + assert remaining == [{"location": "tool_config"}] + + def test_no_injection_points_returns_unchanged(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + system = "System" + + result_msgs, result_sys, remaining = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=[], + ) + + assert result_msgs == messages + assert result_sys == system + assert remaining == [] + + def test_does_not_mutate_input(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + system = [{"type": "text", "text": "System"}] + injection_points = [{"location": "message", "role": "system"}] + + original_system = copy.deepcopy(system) + original_messages = copy.deepcopy(messages) + + AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + assert messages == original_messages + assert system == original_system + + def test_system_none_with_system_point_skipped(self): + messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}] + injection_points = [{"location": "message", "role": "system"}] + + result_msgs, result_sys, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=None, + injection_points=injection_points, + ) + + assert result_sys is None + + def test_existing_cache_control_counted_toward_limit(self): + messages = [ + {"role": "user", "content": [{"type": "text", "text": "A", "cache_control": {"type": "ephemeral"}}]}, + {"role": "assistant", "content": [{"type": "text", "text": "B", "cache_control": {"type": "ephemeral"}}]}, + {"role": "user", "content": [{"type": "text", "text": "C", "cache_control": {"type": "ephemeral"}}]}, + {"role": "user", "content": [{"type": "text", "text": "D"}]}, + {"role": "user", "content": [{"type": "text", "text": "E"}]}, + ] + system = "System" + injection_points = [ + {"location": "message", "role": "system"}, + {"location": "message", "index": 3}, + {"location": "message", "index": 4}, + ] + + result_msgs, result_sys, _ = AnthropicCacheControlHook.apply_to_anthropic_messages_request( + messages=messages, + system=system, + injection_points=injection_points, + ) + + sys_blocks = sum(1 for b in (result_sys or []) if isinstance(b, dict) and b.get("cache_control") is not None) + total_blocks = sys_blocks + sum(AnthropicCacheControlHook._count_cache_control_blocks(m) for m in result_msgs) + assert total_blocks <= 4 From bfb8ffccb8e42b69533d95605c5821d88324c870 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Tue, 30 Jun 2026 19:32:27 -0700 Subject: [PATCH 50/79] feat(proxy): audit remaining system-wide settings updates (#31754) * feat(proxy): audit remaining system-wide settings updates Extends the audit logging framework introduced in the parent PR to the rest of the LiteLLM_Config writers and the two adjacent settings tables: /config/update (general, environment_variables, litellm_settings, router_settings sections), /config/field/update, /config/field/delete, /config/callback/delete, /update/default_team_settings, /update/mcp_semantic_filter_settings, /add/allowed_ip, /delete/allowed_ip, /update/sso_settings, /update/ui_theme_settings, /update/ui_settings. Each writer records the actor, action, the affected config section, and a redacted before/after snapshot. SSO and UI settings rows use their own table_name (LiteLLM_SSOConfig, LiteLLM_UISettings). The /config/callback and /update/sso_settings audits fire BEFORE the proxy reload and the env cleanup step respectively, so a failure in either leaves the audit row intact. The audit-actor parameter on _update_litellm_setting is now required rather than optional; the chokepoint covers default_team and mcp_semantic_filter for free, and a future caller that forgets the actor fails loudly instead of silently skipping the audit. The two direct-calling tests pass a dummy actor. The environment_variables section redacts every value rather than relying on key-name matching, because it carries credentials under non-secret-looking uppercase keys (e.g. DATABASE_URL). * fix(proxy): capture redacted SSO before-snapshot in audit log Greptile review of #31754 flagged update_sso_settings as the one endpoint where before_value is permanently None, so the LiteLLM_SSOConfig audit trail has no pre-change state. An auditor reviewing a secret-rotation event could see what the SSO settings were changed to but not what they were before. Read the existing SSO row before the upsert, decrypt it via proxy_config._decrypt_db_variables, and pass it as before_value. create_config_audit_log's secret-name redaction then masks the *_client_secret fields, so neither the old nor the new plaintext secret lands in the audit row. Add a regression test asserting the before-snapshot reflects the pre-change values for non-secret fields (google_client_id) and is redacted for secret fields (google_client_secret). Mutation-checked against reverting to before_value=None. The pre-existing SSO tests now also mock litellm_ssoconfig.find_unique since the endpoint reads it; the read returns None for tests that do not care about the before-state. * fix: remove committed zero init migration * refactor(proxy): audit config writes via asyncio.create_task everywhere PR A's chokepoint audit call was refactored from a blocking await to asyncio.create_task so that a post-save audit-log failure could not surface as a 500 to the caller. The 12 other audit call sites added in this PR were still using await, reintroducing the exact 500-after-commit exposure at every sibling endpoint. Wrap them all in asyncio.create_task to match the model_management_endpoints / key_management_endpoints / hooks / config_override_endpoints / team_callback_endpoints / cache_settings_endpoints house pattern, so the codebase tells one story. The two direct-invocation tests (test_update_config_general_settings and test_delete_config_general_settings, which call the handler in-process rather than via TestClient) yield with `await asyncio.sleep(0)` after the handler returns so the scheduled audit task runs before the assertion. --------- Co-authored-by: Cursor Agent --- litellm/proxy/_types.py | 2 + litellm/proxy/proxy_server.py | 53 ++- .../proxy_setting_endpoints.py | 145 +++++-- .../scim/test_scim_v2_endpoints.py | 2 + .../test_team_default_params.py | 2 + tests/test_litellm/proxy/test_proxy_server.py | 275 ++++++++++++ .../test_proxy_setting_endpoints.py | 407 ++++++++++++++++++ 7 files changed, 861 insertions(+), 25 deletions(-) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index a6ef7de07ae..643f8d69300 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -190,6 +190,8 @@ class LitellmTableNames(str, enum.Enum): CACHE_CONFIG_TABLE_NAME = "LiteLLM_CacheConfig" CONFIG_OVERRIDES_TABLE_NAME = "LiteLLM_ConfigOverrides" CONFIG_TABLE_NAME = "LiteLLM_Config" + SSO_CONFIG_TABLE_NAME = "LiteLLM_SSOConfig" + UI_SETTINGS_TABLE_NAME = "LiteLLM_UISettings" class Litellm_EntityType(enum.Enum): diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 0158f601d32..2f6c48a751b 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -13962,6 +13962,7 @@ async def update_config( # effect of auto-enabling slack alerting. if config_info.general_settings is not None: existing = await _read_section("general_settings") + before_general_settings = copy.deepcopy(existing) updates = config_info.general_settings.dict(exclude_none=True) for k, v in updates.items(): if k == "alert_to_webhook_url": @@ -13971,6 +13972,11 @@ async def update_config( existing["alerting"].append("slack") existing[k] = v await _upsert_section("general_settings", existing) + asyncio.create_task( + create_config_audit_log( + "general_settings", "updated", before_general_settings, existing, user_api_key_dict + ) + ) # environment_variables: idempotently encrypt the request values # (plaintext on first write, OR ciphertext the UI read back via @@ -13979,10 +13985,16 @@ async def update_config( # their stored ciphertext byte-for-byte. if config_info.environment_variables is not None: existing = await _read_section("environment_variables") + before_environment_variables = copy.deepcopy(existing) existing.update( proxy_config._encrypt_env_variables_for_db(environment_variables=config_info.environment_variables) ) await _upsert_section("environment_variables", existing) + asyncio.create_task( + create_config_audit_log( + "environment_variables", "updated", before_environment_variables, existing, user_api_key_dict + ) + ) # litellm_settings: merge existing + request, request wins (matching # router_settings semantics — the caller's value for any given key is @@ -13994,6 +14006,7 @@ async def update_config( # entries that delete_callback (lowercase lookup) cannot find. if config_info.litellm_settings is not None: existing = await _read_section("litellm_settings") + before_litellm_settings = copy.deepcopy(existing) updated_litellm_settings = dict(config_info.litellm_settings) incoming_cb = updated_litellm_settings.get("success_callback") @@ -14015,12 +14028,24 @@ async def update_config( merged["success_callback"] = list(set(incoming_cb)) await _upsert_section("litellm_settings", merged) + asyncio.create_task( + create_config_audit_log( + "litellm_settings", "updated", before_litellm_settings, merged, user_api_key_dict + ) + ) # router_settings: merge existing + request, request wins. if config_info.router_settings is not None: existing = await _read_section("router_settings") + before_router_settings = copy.deepcopy(existing) updates = config_info.router_settings.dict(exclude_none=True) - await _upsert_section("router_settings", {**existing, **updates}) + new_router_settings = {**existing, **updates} + await _upsert_section("router_settings", new_router_settings) + asyncio.create_task( + create_config_audit_log( + "router_settings", "updated", before_router_settings, new_router_settings, user_api_key_dict + ) + ) await proxy_config.add_deployment(prisma_client=prisma_client, proxy_logging_obj=proxy_logging_obj) @@ -14152,6 +14177,8 @@ async def update_config_general_settings( else: general_settings = dict(db_general_settings.param_value) + before_general_settings = copy.deepcopy(general_settings) + ## update db field_value = data.field_value @@ -14171,6 +14198,11 @@ async def update_config_general_settings( }, ) await invalidate_config_param("general_settings") + asyncio.create_task( + create_config_audit_log( + "general_settings", "updated", before_general_settings, general_settings, user_api_key_dict + ) + ) if data.field_name == "plugins": register_plugins_from_config(general_settings) @@ -14555,6 +14587,8 @@ async def delete_config_general_settings( else: general_settings = dict(db_general_settings.param_value) + before_general_settings = copy.deepcopy(general_settings) + ## update db general_settings.pop(data.field_name, None) @@ -14570,6 +14604,11 @@ async def delete_config_general_settings( }, ) await invalidate_config_param("general_settings") + asyncio.create_task( + create_config_audit_log( + "general_settings", "deleted", before_general_settings, general_settings, user_api_key_dict + ) + ) return response @@ -14627,6 +14666,8 @@ async def delete_callback( detail={"error": f"Callback '{callback_name}' not found in active configuration"}, ) + before_success_callbacks = list(success_callbacks) + # Remove callback from success_callback list success_callbacks.remove(callback_name) config.setdefault("litellm_settings", {})["success_callback"] = success_callbacks @@ -14634,6 +14675,16 @@ async def delete_callback( # Save the updated configuration await proxy_config.save_config(new_config=config) + asyncio.create_task( + create_config_audit_log( + "litellm_settings", + "deleted", + {"success_callback": before_success_callbacks}, + {"success_callback": success_callbacks}, + user_api_key_dict, + ) + ) + # Restart the proxy to apply changes await proxy_config.add_deployment(prisma_client=prisma_client, proxy_logging_obj=proxy_logging_obj) diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py index 1be17c86123..0fc303737b4 100644 --- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py +++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py @@ -323,8 +323,12 @@ async def get_allowed_ips(): tags=["Budget & Spend Tracking"], dependencies=[Depends(user_api_key_auth)], ) -async def add_allowed_ip(ip_address: IPAddress): +async def add_allowed_ip( + ip_address: IPAddress, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): from litellm.proxy.proxy_server import ( + create_config_audit_log, general_settings, prisma_client, proxy_config, @@ -356,11 +360,22 @@ async def add_allowed_ip(ip_address: IPAddress): if "allowed_ips" not in config["general_settings"]: config["general_settings"]["allowed_ips"] = [] + before_allowed_ips = list(config["general_settings"]["allowed_ips"]) if ip_address.ip not in config["general_settings"]["allowed_ips"]: config["general_settings"]["allowed_ips"].append(ip_address.ip) await proxy_config.save_config(new_config=config) + asyncio.create_task( + create_config_audit_log( + param_name="general_settings", + action="updated", + before_value={"allowed_ips": before_allowed_ips}, + after_value={"allowed_ips": config["general_settings"]["allowed_ips"]}, + user_api_key_dict=user_api_key_dict, + ) + ) + return { "message": f"IP {ip_address.ip} address added successfully", "status": "success", @@ -372,8 +387,15 @@ async def add_allowed_ip(ip_address: IPAddress): tags=["Budget & Spend Tracking"], dependencies=[Depends(user_api_key_auth)], ) -async def delete_allowed_ip(ip_address: IPAddress): - from litellm.proxy.proxy_server import general_settings, proxy_config +async def delete_allowed_ip( + ip_address: IPAddress, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + from litellm.proxy.proxy_server import ( + create_config_audit_log, + general_settings, + proxy_config, + ) _allowed_ips: List = general_settings.get("allowed_ips", []) if ip_address.ip in _allowed_ips: @@ -391,11 +413,22 @@ async def delete_allowed_ip(ip_address: IPAddress): if "allowed_ips" not in config["general_settings"]: config["general_settings"]["allowed_ips"] = [] + before_allowed_ips = list(config["general_settings"]["allowed_ips"]) if ip_address.ip in config["general_settings"]["allowed_ips"]: config["general_settings"]["allowed_ips"].remove(ip_address.ip) await proxy_config.save_config(new_config=config) + asyncio.create_task( + create_config_audit_log( + param_name="general_settings", + action="deleted", + before_value={"allowed_ips": before_allowed_ips}, + after_value={"allowed_ips": config["general_settings"]["allowed_ips"]}, + user_api_key_dict=user_api_key_dict, + ) + ) + return {"message": f"IP {ip_address.ip} deleted successfully", "status": "success"} @@ -554,7 +587,7 @@ async def _update_litellm_setting( settings: Union[DefaultInternalUserParams, DefaultTeamSSOParams, MCPSemanticFilterSettings], settings_key: str, success_message: str, - user_api_key_dict: Optional[UserAPIKeyAuth] = None, + user_api_key_dict: UserAPIKeyAuth, ): """ Common utility function to update `litellm_settings` in both memory and config. @@ -564,8 +597,6 @@ async def _update_litellm_setting( settings_key: The key in litellm_settings to update success_message: Message to return on success user_api_key_dict: The acting admin, recorded as the audit-log actor. - Optional today so callers that have not been wired for auditing - keep working; the audit row is only written when an actor is passed. """ from litellm.proxy.proxy_server import ( create_config_audit_log, @@ -599,20 +630,19 @@ async def _update_litellm_setting( # Save the updated config await proxy_config.save_config(new_config=config) - if user_api_key_dict is not None: - # Fire-and-forget so an audit-log failure (transient DB blip, etc.) - # never surfaces as a 500 after save_config has already committed, - # matching the create_object_audit_log pattern used elsewhere - # (e.g. model_management_endpoints). - asyncio.create_task( - create_config_audit_log( - param_name=settings_key, - action="updated", - before_value=before_value, - after_value=in_memory_var, - user_api_key_dict=user_api_key_dict, - ) + # Fire-and-forget so an audit-log failure (transient DB blip, etc.) + # never surfaces as a 500 after save_config has already committed, + # matching the create_object_audit_log pattern used elsewhere + # (e.g. model_management_endpoints). + asyncio.create_task( + create_config_audit_log( + param_name=settings_key, + action="updated", + before_value=before_value, + after_value=in_memory_var, + user_api_key_dict=user_api_key_dict, ) + ) return { "message": success_message, @@ -653,7 +683,10 @@ async def update_internal_user_settings( tags=["SSO Settings"], dependencies=[Depends(user_api_key_auth)], ) -async def update_default_team_settings(settings: DefaultTeamSSOParams): +async def update_default_team_settings( + settings: DefaultTeamSSOParams, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): """ Update the default team parameters for SSO users. These settings will be applied to new teams created from SSO. @@ -662,6 +695,7 @@ async def update_default_team_settings(settings: DefaultTeamSSOParams): settings=settings, settings_key="default_team_params", success_message="Default team settings updated successfully", + user_api_key_dict=user_api_key_dict, ) @@ -772,7 +806,10 @@ async def get_sso_settings(): tags=["SSO Settings"], dependencies=[Depends(user_api_key_auth)], ) -async def update_sso_settings(sso_config: SSOConfig): +async def update_sso_settings( + sso_config: SSOConfig, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): """ Update SSO configuration by saving to the dedicated SSO table. """ @@ -780,6 +817,7 @@ async def update_sso_settings(sso_config: SSOConfig): import os from litellm.proxy.proxy_server import ( + create_config_audit_log, prisma_client, proxy_config, store_model_in_db, @@ -812,6 +850,20 @@ async def update_sso_settings(sso_config: SSOConfig): "proxy_base_url": "PROXY_BASE_URL", } + # Read the existing SSO row first so the audit log captures a real + # before/after diff. Stored values are encrypted; decrypt them so the + # before-snapshot has the same shape as after_value, and rely on + # create_config_audit_log's secret-name redaction to mask the + # *_client_secret fields before the audit row is written. + existing_sso_record = await SSOConfigRepository(prisma_client).table.find_unique(where={"id": "sso_config"}) + before_sso_data: Optional[Dict[str, Any]] = None + if existing_sso_record and existing_sso_record.sso_settings: + stored = existing_sso_record.sso_settings + if isinstance(stored, str): + stored = json.loads(stored) + if isinstance(stored, dict): + before_sso_data = proxy_config._decrypt_db_variables(stored) + # Load existing config config = await proxy_config.get_config() @@ -850,6 +902,17 @@ async def update_sso_settings(sso_config: SSOConfig): }, ) + asyncio.create_task( + create_config_audit_log( + param_name="sso_config", + action="updated", + before_value=before_sso_data, + after_value=sso_data, + user_api_key_dict=user_api_key_dict, + table_name=LitellmTableNames.SSO_CONFIG_TABLE_NAME, + ) + ) + # Remove SSO-related env vars from config.environment_variables try: env_var_entry = await ConfigRepository(prisma_client).table.find_unique( @@ -943,14 +1006,21 @@ def _validate_public_image_url(value: Optional[str], field_name: str) -> None: tags=["UI Theme Settings"], dependencies=[Depends(user_api_key_auth)], ) -async def update_ui_theme_settings(theme_config: UIThemeConfig): +async def update_ui_theme_settings( + theme_config: UIThemeConfig, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): """ Update UI theme configuration. Updates logo settings for the admin UI. """ import os - from litellm.proxy.proxy_server import proxy_config, store_model_in_db + from litellm.proxy.proxy_server import ( + create_config_audit_log, + proxy_config, + store_model_in_db, + ) _validate_public_image_url(theme_config.logo_url, "logo_url") _validate_public_image_url(theme_config.favicon_url, "favicon_url") @@ -963,6 +1033,7 @@ async def update_ui_theme_settings(theme_config: UIThemeConfig): # Load existing config config = await proxy_config.get_config() + before_theme = config.get("litellm_settings", {}).get("ui_theme_config") # Update config with UI theme settings if "general_settings" not in config: @@ -1029,6 +1100,16 @@ async def update_ui_theme_settings(theme_config: UIThemeConfig): # Save the updated config await proxy_config.save_config(new_config=stored_config) + asyncio.create_task( + create_config_audit_log( + param_name="ui_theme_config", + action="updated", + before_value=before_theme, + after_value=theme_data, + user_api_key_dict=user_api_key_dict, + ) + ) + return { "message": "UI theme settings updated successfully.", "status": "success", @@ -1083,6 +1164,7 @@ async def update_mcp_semantic_filter_settings( settings=settings, settings_key="mcp_semantic_tool_filter", success_message="MCP Semantic Filter settings updated successfully. Changes will be applied across all pods within 10 seconds.", + user_api_key_dict=user_api_key_dict, ) try: from litellm.proxy.proxy_server import prisma_client, proxy_config @@ -1200,7 +1282,11 @@ async def update_ui_settings( Update UI-specific configuration flags. Only proxy admins are allowed to modify these settings. """ - from litellm.proxy.proxy_server import prisma_client, store_model_in_db + from litellm.proxy.proxy_server import ( + create_config_audit_log, + prisma_client, + store_model_in_db, + ) if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN: raise HTTPException(status_code=403, detail="Only proxy admins can update UI settings.") @@ -1282,6 +1368,17 @@ async def update_ui_settings( sanitized = {k: v for k, v in ui_settings.items() if k in ALLOWED_UI_SETTINGS_FIELDS} await user_api_key_cache.async_set_cache(key=UI_SETTINGS_CACHE_KEY, value=sanitized, ttl=UI_SETTINGS_CACHE_TTL) + asyncio.create_task( + create_config_audit_log( + param_name="ui_settings", + action="updated", + before_value=existing, + after_value=ui_settings, + user_api_key_dict=user_api_key_dict, + table_name=LitellmTableNames.UI_SETTINGS_TABLE_NAME, + ) + ) + return { "message": "UI settings updated successfully", "status": "success", diff --git a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py index 7f5aee51f51..f39ff93cee7 100644 --- a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py @@ -258,6 +258,7 @@ async def test_scim_create_user_respects_default_role_set_via_ui(mocker, monkeyp ) import litellm + from litellm.proxy._types import UserAPIKeyAuth settings = DefaultInternalUserParams( user_role=LitellmUserRoles.INTERNAL_USER, @@ -266,6 +267,7 @@ async def test_scim_create_user_respects_default_role_set_via_ui(mocker, monkeyp settings=settings, settings_key="default_internal_user_params", success_message="ok", + user_api_key_dict=UserAPIKeyAuth(user_id="test-admin"), ) # Verify the in-memory variable was actually updated diff --git a/tests/test_litellm/proxy/management_endpoints/test_team_default_params.py b/tests/test_litellm/proxy/management_endpoints/test_team_default_params.py index 443089b5f01..e0b90332ca0 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_team_default_params.py +++ b/tests/test_litellm/proxy/management_endpoints/test_team_default_params.py @@ -426,6 +426,7 @@ class TestUpdateLitellmSettingOrdering: settings=new_settings, settings_key="default_team_params", success_message="Updated", + user_api_key_dict=UserAPIKeyAuth(user_id="test-admin"), ) # In-memory value should be the NEW value, not the stale one @@ -459,6 +460,7 @@ class TestUpdateLitellmSettingOrdering: settings=DefaultTeamSSOParams(max_budget=100.0), settings_key="default_team_params", success_message="Updated", + user_api_key_dict=UserAPIKeyAuth(user_id="test-admin"), ) assert exc_info.value.status_code == 500 diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index dc35d71ccbd..88d9ad0d968 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -8764,3 +8764,278 @@ def test_dump_redacted_config_serializes_non_json_native_values(): restored = json.loads(out) assert "2026-06-30" in restored["updated_at"] + +@pytest.mark.asyncio +async def test_update_config_general_settings_emits_audit_log(monkeypatch): + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import ConfigFieldUpdate + from litellm.proxy.proxy_server import update_config_general_settings + + existing = {"max_parallel_requests": 5, "some_api_key": "sk-stored-secret"} + fake = _fake_prisma_with_config(existing) + monkeypatch.setattr(proxy_server_module, "prisma_client", fake) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + admin = UserAPIKeyAuth( + api_key="hashed-admin", + user_id="admin-1", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + await update_config_general_settings( + data=ConfigFieldUpdate( + field_name="max_parallel_requests", + field_value=42, + config_type="general_settings", + ), + user_api_key_dict=admin, + ) + # Audit is scheduled via asyncio.create_task; yield so it runs. + await asyncio.sleep(0) + + fake.db.litellm_auditlog.create.assert_awaited_once() + written = fake.db.litellm_auditlog.create.call_args.kwargs["data"] + assert written["table_name"] == "LiteLLM_Config" + assert written["object_id"] == "general_settings" + assert written["action"] == "updated" + assert written["changed_by"] == "admin-1" + + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert before["max_parallel_requests"] == 5 + assert after["max_parallel_requests"] == 42 + assert "sk-stored-secret" not in written["before_value"] + assert "sk-stored-secret" not in written["updated_values"] + assert before["some_api_key"] != "sk-stored-secret" + + +@pytest.mark.asyncio +async def test_delete_config_general_settings_emits_deleted_audit_log(monkeypatch): + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import ConfigFieldDelete + from litellm.proxy.proxy_server import delete_config_general_settings + + existing = {"max_parallel_requests": 5} + fake = _fake_prisma_with_config(existing) + monkeypatch.setattr(proxy_server_module, "prisma_client", fake) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + admin = UserAPIKeyAuth( + api_key="hashed-admin", + user_id="admin-1", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + await delete_config_general_settings( + data=ConfigFieldDelete( + field_name="max_parallel_requests", config_type="general_settings" + ), + user_api_key_dict=admin, + ) + # Audit is scheduled via asyncio.create_task; yield so it runs. + await asyncio.sleep(0) + + fake.db.litellm_auditlog.create.assert_awaited_once() + written = fake.db.litellm_auditlog.create.call_args.kwargs["data"] + assert written["object_id"] == "general_settings" + assert written["action"] == "deleted" + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert before["max_parallel_requests"] == 5 + assert "max_parallel_requests" not in after + + +def test_update_config_audits_every_written_section(_update_config_setup, monkeypatch): + """/config/update must emit one audit row per section it writes, so each + of the four call sites (general_settings, environment_variables, + litellm_settings, router_settings) is mutation-protected. litellm_settings + is the row that holds default_internal_user_params ("default user settings").""" + import litellm.proxy.proxy_server as proxy_server_module + + client, prisma, restore = _update_config_setup( + initial_rows={"litellm_settings": {"drop_params": True}} + ) + audit_create = AsyncMock() + prisma.db.litellm_auditlog.create = audit_create + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + try: + resp = client.post( + "/config/update", + json={ + "general_settings": {"store_prompts_in_spend_logs": True}, + "environment_variables": {"FOO": "bar"}, + "litellm_settings": { + "default_internal_user_params": {"max_budget": 10} + }, + "router_settings": {"routing_strategy": "latency-based-routing"}, + }, + ) + assert resp.status_code == 200, resp.text + + audited = { + call.kwargs["data"]["object_id"]: call.kwargs["data"]["action"] + for call in audit_create.await_args_list + } + assert audited == { + "general_settings": "updated", + "environment_variables": "updated", + "litellm_settings": "updated", + "router_settings": "updated", + } + for call in audit_create.await_args_list: + assert call.kwargs["data"]["table_name"] == "LiteLLM_Config" + assert call.kwargs["data"]["changed_by"] == "test_admin" + + ls_call = next( + c + for c in audit_create.await_args_list + if c.kwargs["data"]["object_id"] == "litellm_settings" + ) + after = json.loads(ls_call.kwargs["data"]["updated_values"]) + assert after["default_internal_user_params"] == {"max_budget": 10} + finally: + restore() + + +def test_delete_callback_audits_litellm_settings_deletion( + _update_config_setup, monkeypatch +): + """/config/callback/delete must emit a deleted audit row for litellm_settings + capturing the success_callback list before and after removal.""" + import litellm.proxy.proxy_server as proxy_server_module + + client, prisma, restore = _update_config_setup() + audit_create = AsyncMock() + prisma.db.litellm_auditlog.create = audit_create + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + from litellm.proxy.proxy_server import proxy_config as real_proxy_config + + monkeypatch.setattr( + real_proxy_config, + "get_config", + AsyncMock( + return_value={ + "litellm_settings": {"success_callback": ["langfuse", "datadog"]} + } + ), + ) + monkeypatch.setattr( + real_proxy_config, "save_config", AsyncMock(return_value=None) + ) + try: + resp = client.post( + "/config/callback/delete", json={"callback_name": "datadog"} + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "litellm_settings" + assert written["action"] == "deleted" + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert before["success_callback"] == ["langfuse", "datadog"] + assert after["success_callback"] == ["langfuse"] + finally: + restore() + + +def test_delete_callback_audits_before_reload_failure(_update_config_setup, monkeypatch): + import litellm.proxy.proxy_server as proxy_server_module + + client, prisma, restore = _update_config_setup() + audit_create = AsyncMock() + prisma.db.litellm_auditlog.create = audit_create + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + from litellm.proxy.proxy_server import proxy_config as real_proxy_config + + monkeypatch.setattr( + real_proxy_config, + "get_config", + AsyncMock( + return_value={ + "litellm_settings": {"success_callback": ["langfuse", "datadog"]} + } + ), + ) + monkeypatch.setattr( + real_proxy_config, "save_config", AsyncMock(return_value=None) + ) + monkeypatch.setattr( + real_proxy_config, + "add_deployment", + AsyncMock(side_effect=RuntimeError("reload failed")), + ) + try: + resp = client.post( + "/config/callback/delete", json={"callback_name": "datadog"} + ) + assert resp.status_code == 500, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "litellm_settings" + assert written["action"] == "deleted" + finally: + restore() + + +def test_update_config_redacts_all_environment_variable_values( + _update_config_setup, monkeypatch +): + """environment_variables hold credentials under arbitrary uppercase keys + (DATABASE_URL) that key-name secret matching misses, so every value in the + section must be redacted before the audit row is written; a plaintext + secret must never reach LiteLLM_AuditLog.""" + import litellm.proxy.proxy_server as proxy_server_module + + # DATABASE_URL is the bug class: an uppercase env key that key-name secret + # matching does NOT flag, so only whole-section value redaction protects it. + client, prisma, restore = _update_config_setup( + initial_rows={ + "environment_variables": { + "DATABASE_URL": "enc:postgresql://OLDsecret@old.host:5432/db" + } + } + ) + audit_create = AsyncMock() + prisma.db.litellm_auditlog.create = audit_create + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + try: + resp = client.post( + "/config/update", + json={ + "environment_variables": { + "DATABASE_URL": "postgresql://u:p@db.internal:5432/litellm", + "LOG_LEVEL": "debug", + } + }, + ) + assert resp.status_code == 200, resp.text + + env_call = next( + c + for c in audit_create.await_args_list + if c.kwargs["data"]["object_id"] == "environment_variables" + ) + data = env_call.kwargs["data"] + + # the pre-existing secret must be redacted in the before snapshot + before = json.loads(data["before_value"]) + assert before == {"DATABASE_URL": "REDACTED"} + assert "OLDsecret" not in data["before_value"] + assert "old.host" not in data["before_value"] + + # the newly-written values must be redacted in the after snapshot + after = json.loads(data["updated_values"]) + assert after == {"DATABASE_URL": "REDACTED", "LOG_LEVEL": "REDACTED"} + assert "postgresql://" not in data["updated_values"] + assert "db.internal" not in data["updated_values"] + finally: + restore() diff --git a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py index 7a586f758f4..cb77c42fe9b 100644 --- a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py +++ b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py @@ -396,6 +396,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) @@ -466,6 +467,62 @@ class TestProxySettingEndpoints: create_sso_settings = json.loads(create_data["sso_settings"]) assert create_sso_settings["google_client_id"] == "new_google_client_id" + def test_update_sso_settings_audits_when_env_cleanup_fails( + self, mock_proxy_config, mock_auth, monkeypatch + ): + import json + from unittest.mock import AsyncMock, MagicMock + + monkeypatch.setenv("LITELLM_SALT_KEY", "test_salt_key") + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + + mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) + mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() + mock_prisma.db.litellm_config = MagicMock() + mock_prisma.db.litellm_config.find_unique = AsyncMock( + side_effect=ValueError("cleanup failed") + ) + mock_prisma.db.litellm_config.update = AsyncMock() + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma) + + from litellm.proxy.proxy_server import proxy_config + + monkeypatch.setattr( + proxy_config, + "_encrypt_env_variables", + lambda environment_variables: environment_variables, + ) + + create_config_audit_log = AsyncMock() + monkeypatch.setattr( + "litellm.proxy.proxy_server.create_config_audit_log", + create_config_audit_log, + ) + + response = client.patch( + "/update/sso_settings", + json={"google_client_id": "new_google_client_id"}, + ) + + assert response.status_code == 500 + assert mock_prisma.db.litellm_ssoconfig.upsert.called + create_config_audit_log.assert_awaited_once() + audit_log_kwargs = create_config_audit_log.await_args.kwargs + assert audit_log_kwargs["param_name"] == "sso_config" + assert ( + audit_log_kwargs["after_value"]["google_client_id"] + == "new_google_client_id" + ) + assert ( + json.loads( + mock_prisma.db.litellm_ssoconfig.upsert.call_args.kwargs["data"][ + "create" + ]["sso_settings"] + )["google_client_id"] + == "new_google_client_id" + ) + def test_update_sso_settings_with_null_values_clears_env_vars( self, mock_proxy_config, mock_auth, monkeypatch ): @@ -478,6 +535,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() @@ -557,6 +615,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() env_var_entry = MagicMock() @@ -627,6 +686,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() @@ -704,6 +764,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) @@ -1350,6 +1411,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() upsert_mock = AsyncMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = upsert_mock mock_prisma.db.litellm_config = MagicMock() mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) @@ -1429,6 +1491,7 @@ class TestProxySettingEndpoints: mock_prisma = MagicMock() mock_prisma.db = MagicMock() mock_prisma.db.litellm_ssoconfig = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() env_var_entry = MagicMock() @@ -1480,6 +1543,7 @@ class TestProxySettingEndpoints: mock_prisma = MagicMock() mock_prisma.db = MagicMock() mock_prisma.db.litellm_ssoconfig = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() env_var_entry = MagicMock() @@ -1651,6 +1715,7 @@ class TestProxySettingEndpoints: # Mock the prisma client mock_prisma = MagicMock() + mock_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) mock_prisma.db.litellm_ssoconfig.upsert = AsyncMock() mock_prisma.db.litellm_config = MagicMock() mock_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) @@ -1960,3 +2025,345 @@ def test_update_internal_user_settings_returns_200_when_audit_write_raises( assert resp.json()["status"] == "success" finally: app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_update_sso_settings_writes_redacted_audit_log(mock_proxy_config, monkeypatch): + """Updating SSO settings must write an audit row to the SSO config table + with the client secret redacted.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + fake_prisma.db.litellm_ssoconfig.upsert = AsyncMock() + # No prior SSO row, so before_value resolves to None. + fake_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=None) + fake_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + monkeypatch.setattr( + proxy_server_module.proxy_config, + "_encrypt_env_variables", + lambda environment_variables: environment_variables, + ) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/sso_settings", + json={ + "google_client_id": "client-id-123", + "google_client_secret": "super-secret-xyz", + }, + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "sso_config" + assert written["table_name"] == "LiteLLM_SSOConfig" + assert written["changed_by"] == "audit-admin" + + after = json.loads(written["updated_values"]) + assert after["google_client_id"] == "client-id-123" + assert after["google_client_secret"] == "REDACTED" + assert "super-secret-xyz" not in written["updated_values"] + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_update_sso_settings_audit_captures_redacted_before_snapshot( + mock_proxy_config, monkeypatch +): + """An auditor reviewing an SSO secret rotation needs to see a real + before/after diff in the audit row, not before_value=None. The endpoint + reads the existing (encrypted) SSO row, decrypts it, and lets the audit + helper redact the *_client_secret fields before persistence so neither + the old nor the new plaintext secret is recorded.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + fake_prisma.db.litellm_ssoconfig.upsert = AsyncMock() + + # Pre-existing SSO row contains the *prior* secret (would be ciphertext in + # production; the test patches _decrypt_db_variables to pass through). + existing_record = MagicMock() + existing_record.sso_settings = { + "google_client_id": "old-client-id", + "google_client_secret": "OLD-SUPER-SECRET", + } + fake_prisma.db.litellm_ssoconfig.find_unique = AsyncMock(return_value=existing_record) + fake_prisma.db.litellm_config.find_unique = AsyncMock(return_value=None) + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + monkeypatch.setattr( + proxy_server_module.proxy_config, + "_encrypt_env_variables", + lambda environment_variables: environment_variables, + ) + # Pretend the stored value is already plaintext for the test (production + # decrypts via Fernet); the audit helper still has to redact it. + monkeypatch.setattr( + proxy_server_module.proxy_config, + "_decrypt_db_variables", + lambda variables_dict: dict(variables_dict), + ) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/sso_settings", + json={ + "google_client_id": "new-client-id", + "google_client_secret": "NEW-SUPER-SECRET", + }, + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + + # Non-secret field shows the diff + assert before["google_client_id"] == "old-client-id" + assert after["google_client_id"] == "new-client-id" + + # Secret field is redacted in BOTH snapshots — auditor sees the + # rotation event without ever seeing either plaintext secret. + assert before["google_client_secret"] == "REDACTED" + assert after["google_client_secret"] == "REDACTED" + assert "OLD-SUPER-SECRET" not in written["before_value"] + assert "NEW-SUPER-SECRET" not in written["updated_values"] + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_add_allowed_ip_writes_audit_log(mock_proxy_config, monkeypatch): + """Adding an allowed IP is a system-wide security setting change and must + be audited with the before and after IP list.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr(proxy_server_module, "general_settings", {}) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.post("/add/allowed_ip", json={"ip": "203.0.113.77"}) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "general_settings" + assert written["action"] == "updated" + assert written["changed_by"] == "audit-admin" + + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert "203.0.113.77" not in before["allowed_ips"] + assert "203.0.113.77" in after["allowed_ips"] + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_delete_allowed_ip_writes_deleted_audit_log(monkeypatch): + """Removing an allowed IP must be audited as a deletion, symmetric with the + add path.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + + config = {"general_settings": {"allowed_ips": ["203.0.113.77", "198.51.100.1"]}} + + async def _get_config(): + return config + + async def _save_config(new_config=None): + nonlocal config + if new_config is not None: + config = new_config + return config + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr( + proxy_server_module, "general_settings", {"allowed_ips": ["203.0.113.77"]} + ) + monkeypatch.setattr(litellm, "store_audit_logs", True) + monkeypatch.setattr(proxy_server_module.proxy_config, "get_config", _get_config) + monkeypatch.setattr(proxy_server_module.proxy_config, "save_config", _save_config) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.post("/delete/allowed_ip", json={"ip": "203.0.113.77"}) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "general_settings" + assert written["action"] == "deleted" + before = json.loads(written["before_value"]) + after = json.loads(written["updated_values"]) + assert "203.0.113.77" in before["allowed_ips"] + assert "203.0.113.77" not in after["allowed_ips"] + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_update_ui_theme_settings_writes_audit_log(mock_proxy_config, monkeypatch): + """Updating the UI theme must be audited under ui_theme_config.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + monkeypatch.setattr( + proxy_server_module.proxy_config, + "_encrypt_env_variables", + lambda environment_variables: environment_variables, + ) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/ui_theme_settings", + json={"logo_url": "https://example.com/logo.png"}, + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "ui_theme_config" + assert written["action"] == "updated" + assert written["changed_by"] == "audit-admin" + after = json.loads(written["updated_values"]) + assert after["logo_url"] == "https://example.com/logo.png" + finally: + app.dependency_overrides.pop(user_api_key_auth, None) + + +def test_update_ui_settings_writes_audit_log(monkeypatch): + """Updating UI settings must be audited under the UI settings table.""" + from unittest.mock import AsyncMock, MagicMock + + import litellm + import litellm.proxy.proxy_server as proxy_server_module + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + audit_create = AsyncMock() + fake_prisma = MagicMock() + fake_prisma.db.litellm_auditlog.create = audit_create + fake_prisma.db.litellm_uisettings.find_unique = AsyncMock(return_value=None) + fake_prisma.db.litellm_uisettings.upsert = AsyncMock() + + monkeypatch.setattr(proxy_server_module, "prisma_client", fake_prisma) + monkeypatch.setattr(proxy_server_module, "premium_user", True) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True) + monkeypatch.setattr(litellm, "store_audit_logs", True) + + async def _admin_auth(): + return UserAPIKeyAuth( + user_id="audit-admin", + api_key="hashed-admin-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + ) + + app.dependency_overrides[user_api_key_auth] = _admin_auth + try: + resp = client.patch( + "/update/ui_settings", json={"disable_custom_api_keys": True} + ) + assert resp.status_code == 200, resp.text + + audit_create.assert_awaited_once() + written = audit_create.await_args.kwargs["data"] + assert written["object_id"] == "ui_settings" + assert written["table_name"] == "LiteLLM_UISettings" + assert written["changed_by"] == "audit-admin" + after = json.loads(written["updated_values"]) + assert after["disable_custom_api_keys"] is True + finally: + app.dependency_overrides.pop(user_api_key_auth, None) From c4a77bded7b3e21e0ca8bf52caaa75b9442f6145 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Wed, 1 Jul 2026 10:44:02 +0800 Subject: [PATCH 51/79] fix(prometheus): expose project_alias in custom metadata labels (LIT-3741) (#31784) Include top-level scalar fields from standard_logging_metadata in the combined metadata dict used by custom_prometheus_metadata_labels. Previously only nested sub-dicts (requester_metadata, user_api_key_auth_metadata, spend_logs_metadata) were spread into combined_metadata, so fields like user_api_key_project_alias were inaccessible and always resolved to None. Co-authored-by: unknown <> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/integrations/prometheus.py | 5 + .../test_prometheus_spend_logs_metadata.py | 98 ++++++++++++++++++- 2 files changed, 102 insertions(+), 1 deletion(-) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 1f516e9dc93..8eb6eaa8e2b 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -3804,6 +3804,10 @@ def _get_combined_custom_metadata_from_standard_logging_payload( ) -> Dict[str, Any]: """ Combine the metadata sources that can supply custom Prometheus labels. + + Includes top-level scalar fields from the standard logging metadata (e.g. + user_api_key_project_alias, user_api_key_team_alias) so they are accessible + via custom_prometheus_metadata_labels configuration. """ if not isinstance(standard_logging_payload, dict): return {} @@ -3817,6 +3821,7 @@ def _get_combined_custom_metadata_from_standard_logging_payload( spend_logs_metadata = standard_logging_metadata.get("spend_logs_metadata") return { + **{k: v for k, v in standard_logging_metadata.items() if not isinstance(v, dict)}, **(requester_metadata if isinstance(requester_metadata, dict) else {}), **(user_api_key_auth_metadata if isinstance(user_api_key_auth_metadata, dict) else {}), **(spend_logs_metadata if isinstance(spend_logs_metadata, dict) else {}), diff --git a/tests/test_litellm/integrations/test_prometheus_spend_logs_metadata.py b/tests/test_litellm/integrations/test_prometheus_spend_logs_metadata.py index 31934e5fd8e..e2af6fd2daf 100644 --- a/tests/test_litellm/integrations/test_prometheus_spend_logs_metadata.py +++ b/tests/test_litellm/integrations/test_prometheus_spend_logs_metadata.py @@ -5,7 +5,10 @@ Verifies that metadata from x-litellm-spend-logs-metadata header is available in Prometheus custom labels via combined_metadata. """ -from litellm.integrations.prometheus import get_custom_labels_from_metadata +from litellm.integrations.prometheus import ( + _get_combined_custom_metadata_from_standard_logging_payload, + get_custom_labels_from_metadata, +) def test_get_custom_labels_includes_spend_logs_metadata(monkeypatch): @@ -109,3 +112,96 @@ def test_combined_metadata_with_none_spend_logs(monkeypatch): result = get_custom_labels_from_metadata(combined_metadata) assert result == {"metadata_foo": "bar"} + + +def test_combined_metadata_includes_top_level_fields(): + """ + Regression test for LIT-3741: user_api_key_project_alias (and other + top-level metadata fields) must be included in the combined metadata + so they can be referenced via custom_prometheus_metadata_labels. + """ + standard_logging_payload = { + "metadata": { + "user_api_key_hash": "sk-abc123", + "user_api_key_alias": "hotel-key", + "user_api_key_team_id": "team-1", + "user_api_key_team_alias": "hotel-team", + "user_api_key_project_id": "proj-1", + "user_api_key_project_alias": "hotel-recommendations", + "user_api_key_user_id": "user-1", + "user_api_key_user_email": "user@example.com", + "user_api_key_end_user_id": None, + "user_api_key_org_id": None, + "user_api_key_org_alias": None, + "user_api_key_request_route": "/v1/chat/completions", + "requester_metadata": {"custom_field": "custom_value"}, + "user_api_key_auth_metadata": {"auth_field": "auth_value"}, + "spend_logs_metadata": None, + } + } + + combined = _get_combined_custom_metadata_from_standard_logging_payload( + standard_logging_payload + ) + + assert combined["user_api_key_project_alias"] == "hotel-recommendations" + assert combined["user_api_key_project_id"] == "proj-1" + assert combined["user_api_key_team_alias"] == "hotel-team" + assert combined["user_api_key_request_route"] == "/v1/chat/completions" + assert combined["custom_field"] == "custom_value" + assert combined["auth_field"] == "auth_value" + + +def test_project_alias_accessible_via_custom_prometheus_labels(monkeypatch): + """ + Regression test for LIT-3741: configuring + custom_prometheus_metadata_labels with "metadata.user_api_key_project_alias" + should produce a label with the project's alias value. + """ + monkeypatch.setattr( + "litellm.custom_prometheus_metadata_labels", + ["metadata.user_api_key_project_alias"], + ) + + standard_logging_payload = { + "metadata": { + "user_api_key_project_alias": "hotel-recommendations", + "requester_metadata": None, + "user_api_key_auth_metadata": None, + "spend_logs_metadata": None, + } + } + + combined = _get_combined_custom_metadata_from_standard_logging_payload( + standard_logging_payload + ) + result = get_custom_labels_from_metadata(combined) + + assert result == {"metadata_user_api_key_project_alias": "hotel-recommendations"} + + +def test_project_alias_accessible_without_prefix(monkeypatch): + """ + user_api_key_project_alias should also be accessible without + the "metadata." prefix in custom_prometheus_metadata_labels config. + """ + monkeypatch.setattr( + "litellm.custom_prometheus_metadata_labels", + ["user_api_key_project_alias"], + ) + + standard_logging_payload = { + "metadata": { + "user_api_key_project_alias": "hotel-recommendations", + "requester_metadata": None, + "user_api_key_auth_metadata": None, + "spend_logs_metadata": None, + } + } + + combined = _get_combined_custom_metadata_from_standard_logging_payload( + standard_logging_payload + ) + result = get_custom_labels_from_metadata(combined) + + assert result == {"user_api_key_project_alias": "hotel-recommendations"} From cca71a07c20e065fe0bd2fa1857cba783946ac93 Mon Sep 17 00:00:00 2001 From: Krrish Dholakia Date: Tue, 30 Jun 2026 20:03:59 -0700 Subject: [PATCH 52/79] feat(mcp): add mcp_tool_search virtual tools for large tool catalogs (#31777) * feat(mcp): add tool search virtual tools for large catalogs When mcp_tool_search_enabled is set on a key's object_permission, tools/list returns only mcp_tool_search and mcp_tool_call instead of the full catalog. The LLM searches by keyword then calls discovered tools by name, avoiding context bloat with 100+ tool deployments. * fix(mcp): persist mcp_tool_search_enabled and route tool_call by name The mcp_tool_search_enabled flag existed on the Pydantic models but the Prisma schema lacked the column, so keys generated with the flag never persisted it and tools/list kept returning the full catalog. Add the column across all three schema.prisma copies plus a migration. handle_mcp_tool_call passed server_name="" into call_tool, which built a malformed prefixed name ("-") and failed to resolve the server. Resolve the caller's allowed servers and dispatch through execute_mcp_tool instead, matching how the normal /tools/call path routes. * fix(mcp): filter list_tools to virtual tools on the protocol path The REST surface (/mcp-rest/tools/list) returned only the two virtual tools when mcp_tool_search_enabled was set, but the MCP protocol handler (handle_list_tools, used by real MCP clients over streamable-http/SSE) still returned the full catalog. Apply the same early return there so an actual MCP client sees mcp_tool_search and mcp_tool_call instead of every tool. call_tool was already intercepted on this path. * fix(mcp): enforce IP + server filtering on virtual tool search/call Review flagged that the virtual mcp_tool_search/mcp_tool_call path skipped access controls the normal MCP flow applies. mcp_tool_call resolved allowed servers from key permissions only, never applying IP filtering, so a caller on a public IP could invoke a tool on a server marked available_on_public_internet: false. mcp_tool_search listed the raw catalog via global_mcp_server_manager.list_tools, exposing tool names/schemas that /tools/list would hide and ignoring per-key/per-server tool filters. Route both virtual handlers through the same filtered paths used by the normal MCP flow: search now calls _list_mcp_tools and call resolves servers via _get_allowed_mcp_servers, both threaded with the request client IP so filter_server_ids_by_ip applies. execute_mcp_tool then enforces the server allowlist and per-key tool permissions. Thread client_ip through _list_mcp_tools/_get_tools_from_mcp_servers and pass it from the REST and SSE call sites. * fix(ci): ruff format server.py and sync dashboard API types ruff format normalizes the list_tools client_ip changes in server.py, and schema.d.ts gains the mcp_tool_search_enabled object-permission field so the generated dashboard types match the proxy OpenAPI spec. * style(mcp): drop quoted annotations and sort imports Clears UP037 on the virtual tool handler signatures (redundant with from __future__ import annotations) and I001 on the list_tools import block. * refactor(mcp): extract virtual-tool dispatch and host progress capture Pulls the mcp_tool_search/mcp_tool_call interception and the host progress-callback setup out of mcp_server_tool_call into helpers, keeping that handler under the strict cyclomatic-complexity ceiling after the client_ip threading. No behavior change. * test(mcp): cover SSE virtual-tool dispatch and host progress helpers Adds unit tests for _dispatch_virtual_mcp_tool (non-virtual passthrough, flag-disabled rejection, search/call routing with client_ip), _capture_host_progress_callback, and the protocol list_tools virtual early-return, covering the new server.py paths. * fix(mcp): forward per-request auth headers through virtual tool handlers The virtual mcp_tool_search/mcp_tool_call path intercepted the request before the normal header extraction ran, so client-supplied per-request auth (Authorization for upstream pass-through, x-mcp-auth-) was dropped and execute_mcp_tool/_list_mcp_tools received None. Thread mcp_auth_header, mcp_server_auth_headers, oauth2_headers, and raw_headers from both the REST and SSE call sites through the handlers so upstream MCP servers that require pass-through auth can be listed and called. * fix(mcp): preserve requested server scope in virtual tool calls A scoped MCP session (/mcp// or header-scoped) carries an mcp_servers scope that the normal call path passes into routing so the session can only reach that server. The virtual-tool branch dropped it and resolved with mcp_servers=None, letting a scoped session call mcp_tool_call for any server the key can access. Thread the context mcp_servers scope through _dispatch_virtual_mcp_tool into both handlers so search and call resolve against the same scoped server set. * fix(mcp): convert virtual tool errors to isError on the protocol path The virtual-tool dispatch ran before the protocol handler's HTTPException and guardrail handling, so a rejected virtual call (e.g. an out-of-scope 403 from execute_mcp_tool) raised out of mcp_server_tool_call and broke the MCP JSON-RPC stream instead of returning an isError CallToolResult. Move the dispatch inside the same try that wraps call_mcp_tool so virtual-tool errors get the same isError conversion as normal tool calls. * fix(mcp): spend-log virtual tool calls on the REST path The REST virtual-tool branch returned before common_processing_pre_call_logic, so execute_mcp_tool ran without a litellm_logging_obj and virtual mcp_tool_call invocations were not spend-logged or guardrail-checked like normal calls. Run the same pre-call pipeline in the call branch and thread the resulting litellm_logging_obj through handle_mcp_tool_call into execute_mcp_tool. * fix(mcp): reject virtual tool call when key has no accessible servers handle_mcp_tool_call passed an empty allowed_mcp_servers list into execute_mcp_tool; an unprefixed local tool name then fell through to the local registry, which has no server permission check, so a key with only mcp_tool_search_enabled and no server grants could run operator-configured local tools by name. Reject with 403 before dispatch when no servers are accessible, matching call_mcp_tool. * docs(mcp): document virtual tool_search module and parity rule in AGENTS.md * style(mcp): apply ruff format at repo line-length (120) * fix(mcp): add mcp_tool_search_enabled to ObjectPermissionDict and customer test fixture * chore: trigger CI * fix(mcp): mirror pre-call pipeline, guard imports, coerce top_k, honor include_disabled_tools - SSE mcp_tool_call now runs common_processing_pre_call_logic so it spend-logs and runs guardrails like the REST path (P1) - coerce_top_k avoids ValueError on non-integer top_k from clients (both REST and SSE) - guard mcp.types import in tool_search behind runtime/TYPE_CHECKING per package convention - admin list with include_disabled_tools returns the real catalog even when mcp_tool_search_enabled is set --- .../migration.sql | 2 + .../litellm_proxy_extras/schema.prisma | 1 + litellm/models/object_permission.py | 1 + .../proxy/_experimental/mcp_server/AGENTS.md | 6 + .../mcp_server/rest_endpoints.py | 86 +- .../proxy/_experimental/mcp_server/server.py | 228 ++++- .../_experimental/mcp_server/tool_search.py | 157 ++++ litellm/proxy/_types.py | 1 + litellm/proxy/schema.prisma | 1 + litellm/types/object_permission.py | 1 + schema.prisma | 1 + .../mcp_server/test_mcp_tool_search.py | 837 ++++++++++++++++++ .../test_customer_endpoints.py | 1 + .../test_object_permission_utils.py | 32 + ui/litellm-dashboard/src/lib/http/schema.d.ts | 4 + 15 files changed, 1321 insertions(+), 38 deletions(-) create mode 100644 litellm-proxy-extras/litellm_proxy_extras/migrations/20260626120000_add_mcp_tool_search_enabled/migration.sql create mode 100644 litellm/proxy/_experimental/mcp_server/tool_search.py create mode 100644 tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260626120000_add_mcp_tool_search_enabled/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260626120000_add_mcp_tool_search_enabled/migration.sql new file mode 100644 index 00000000000..542677426ba --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260626120000_add_mcp_tool_search_enabled/migration.sql @@ -0,0 +1,2 @@ +-- AlterTable +ALTER TABLE "LiteLLM_ObjectPermissionTable" ADD COLUMN "mcp_tool_search_enabled" BOOLEAN; diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index e21c0016491..5351e0a1470 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -279,6 +279,7 @@ model LiteLLM_ObjectPermissionTable { blocked_tools String[] @default([]) // Tool names blocked for any key/team/user with this permission mcp_toolsets String[] @default([]) // Toolset IDs granted to this key/team/user search_tools String[] @default([]) // search_tool_name values this key/team/user may call + mcp_tool_search_enabled Boolean? teams LiteLLM_TeamTable[] projects LiteLLM_ProjectTable[] verification_tokens LiteLLM_VerificationToken[] diff --git a/litellm/models/object_permission.py b/litellm/models/object_permission.py index 6c0d100046c..3052a2af459 100644 --- a/litellm/models/object_permission.py +++ b/litellm/models/object_permission.py @@ -24,3 +24,4 @@ class LiteLLM_ObjectPermissionTable(LiteLLMPydanticObjectBase): mcp_toolsets: Optional[List[str]] = None blocked_tools: Optional[List[str]] = [] search_tools: Optional[List[str]] = [] + mcp_tool_search_enabled: Optional[bool] = None diff --git a/litellm/proxy/_experimental/mcp_server/AGENTS.md b/litellm/proxy/_experimental/mcp_server/AGENTS.md index 8eebc3ea3b3..6e1d121c3be 100644 --- a/litellm/proxy/_experimental/mcp_server/AGENTS.md +++ b/litellm/proxy/_experimental/mcp_server/AGENTS.md @@ -41,6 +41,7 @@ litellm/proxy/_experimental/mcp_server/ sampling_handler.py # MCP sampling to LiteLLM completion flow elicitation_handler.py # MCP elicitation relay flow semantic_tool_filter.py # semantic filtering of available MCP tools + tool_search.py # opt-in virtual tools (mcp_tool_search + mcp_tool_call) for large catalogs guardrail_translation/ handler.py # MCP guardrail result translation sse_transport.py # SSE transport implementation @@ -79,6 +80,11 @@ module materially harder to understand. encryption need focused tests for both allowed and rejected paths. - Avoid adding comments to new code unless they explain non-obvious security or protocol behavior. Prefer clear names and small functions. +- The virtual tool path (`tool_search.py`, gated by `mcp_tool_search_enabled`) + must mirror the normal tool flow: IP filtering, server allowlist, per-key tool + permissions, no-accessible-server rejection, per-request auth headers, server + scope, error to `isError` conversion, and spend logging. Reuse `_list_mcp_tools` + and `execute_mcp_tool` rather than reimplementing any of these checks. ## Tests diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py index d30d8af2af2..7ab7eb28147 100644 --- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py +++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py @@ -569,6 +569,21 @@ if MCP_AVAILABLE: include_disabled_tools and user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN ) + if apply_tool_filters and getattr( + getattr(user_api_key_dict, "object_permission", None), + "mcp_tool_search_enabled", + False, + ): + from litellm.proxy._experimental.mcp_server.tool_search import ( + get_virtual_tool_definitions, + ) + + return { + "tools": get_virtual_tool_definitions(), + "error": None, + "message": "Successfully retrieved tools", + } + # Extract auth headers from request headers = request.headers raw_headers_from_request = dict(headers) @@ -727,6 +742,74 @@ if MCP_AVAILABLE: try: data = await request.json() + tool_name = data.get("name") + tool_arguments = data.get("arguments") or {} + + from litellm.proxy._experimental.mcp_server.tool_search import ( + MCP_TOOL_CALL_TOOL_NAME, + MCP_TOOL_SEARCH_TOOL_NAME, + coerce_top_k, + handle_mcp_tool_call, + handle_mcp_tool_search, + ) + + if tool_name in (MCP_TOOL_SEARCH_TOOL_NAME, MCP_TOOL_CALL_TOOL_NAME): + if not getattr( + getattr(user_api_key_dict, "object_permission", None), + "mcp_tool_search_enabled", + False, + ): + raise HTTPException( + status_code=403, + detail={ + "error": "forbidden", + "message": f"{tool_name} requires mcp_tool_search_enabled on the key", + }, + ) + rest_client_ip = IPAddressUtils.get_mcp_client_ip(request) + ( + virtual_mcp_auth_header, + virtual_mcp_server_auth_headers, + virtual_raw_headers, + ) = _extract_mcp_headers_from_request(request, MCPRequestHandler) + virtual_oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(request.headers) + if tool_name == MCP_TOOL_SEARCH_TOOL_NAME: + return await handle_mcp_tool_search( + query=tool_arguments.get("query", ""), + top_k=coerce_top_k(tool_arguments.get("top_k", 5)), + user_api_key_dict=user_api_key_dict, + client_ip=rest_client_ip, + mcp_auth_header=virtual_mcp_auth_header, + mcp_server_auth_headers=virtual_mcp_server_auth_headers, + oauth2_headers=virtual_oauth2_headers, + raw_headers=virtual_raw_headers, + ) + else: # MCP_TOOL_CALL_TOOL_NAME + # Run the same pre-call pipeline as the normal call path so the + # tool execution is spend-logged and guardrail-checked. + ( + _, + virtual_logging_obj, + ) = await ProxyBaseLLMRequestProcessing(data=data).common_processing_pre_call_logic( + request=request, + user_api_key_dict=user_api_key_dict, + proxy_config=proxy_config, + route_type=CallTypes.call_mcp_tool.value, + proxy_logging_obj=proxy_logging_obj, + general_settings=general_settings, + ) + return await handle_mcp_tool_call( + tool_name=tool_arguments.get("tool_name", ""), + arguments=tool_arguments.get("arguments") or {}, + user_api_key_dict=user_api_key_dict, + client_ip=rest_client_ip, + mcp_auth_header=virtual_mcp_auth_header, + mcp_server_auth_headers=virtual_mcp_server_auth_headers, + oauth2_headers=virtual_oauth2_headers, + raw_headers=virtual_raw_headers, + litellm_logging_obj=virtual_logging_obj, + ) + # Validate required parameters early server_id = data.get("server_id") if not server_id: @@ -738,7 +821,6 @@ if MCP_AVAILABLE: }, ) - tool_name = data.get("name") if not tool_name: raise HTTPException( status_code=400, @@ -748,8 +830,6 @@ if MCP_AVAILABLE: }, ) - tool_arguments = data.get("arguments") or {} - proxy_base_llm_response_processor = ProxyBaseLLMRequestProcessing(data=data) ( data, diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index 607e676524e..a65239b296f 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -10,8 +10,8 @@ import contextvars import hashlib import json import time -import types import traceback +import types import uuid from datetime import datetime from typing import ( @@ -37,13 +37,17 @@ from starlette.types import Message, Receive, Scope, Send from litellm._logging import verbose_logger from litellm.constants import MAXIMUM_TRACEBACK_LINES_TO_LOG from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.custom_httpx.http_handler import ( + get_async_httpx_client, + httpxSpecialProvider, +) from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import ( MCPRequestHandler, ) -from litellm.proxy._experimental.mcp_server.exceptions import MCPUpstreamAuthError from litellm.proxy._experimental.mcp_server.discoverable_endpoints import ( get_request_base_url, ) +from litellm.proxy._experimental.mcp_server.exceptions import MCPUpstreamAuthError from litellm.proxy._experimental.mcp_server.mcp_context import ( _mcp_active_toolset_id, _mcp_gateway_initialize_instructions, @@ -59,10 +63,6 @@ from litellm.proxy._experimental.mcp_server.utils import ( get_server_prefix, iter_known_server_prefixes, ) -from litellm.llms.custom_httpx.http_handler import ( - get_async_httpx_client, - httpxSpecialProvider, -) from litellm.proxy._types import ( ProxyException, SpecialMCPServerNames, @@ -122,9 +122,12 @@ def _write_byok_cred_cache(user_id: str, server_id: str, credential: Optional[st # TODO: Make this a util function for litellm client usage MCP_AVAILABLE: bool = True try: + import weakref + from mcp import ReadResourceResult, Resource from mcp.server import Server from mcp.server.lowlevel.helper_types import ReadResourceContents + from mcp.server.session import ServerSession as _McpServerSession from mcp.types import ( BlobResourceContents, GetPromptResult, @@ -132,8 +135,6 @@ try: TextResourceContents, Tool, ) - from mcp.server.session import ServerSession as _McpServerSession - import weakref # Robust auth lookup keyed by session_object. _session_obj_auth_storage: "weakref.WeakKeyDictionary[Any, MCPAuthenticatedUser]" = weakref.WeakKeyDictionary() @@ -303,14 +304,14 @@ def _proxy_exception_to_http_exception(exc: ProxyException) -> HTTPException: if MCP_AVAILABLE: from mcp.server import Server - from mcp.server.lowlevel.server import NotificationOptions - from mcp.server.models import InitializationOptions # Import auth context variables and middleware from mcp.server.auth.middleware.auth_context import ( AuthContextMiddleware, auth_context_var, ) + from mcp.server.lowlevel.server import NotificationOptions + from mcp.server.models import InitializationOptions try: from mcp.server.streamable_http_manager import StreamableHTTPSessionManager @@ -664,6 +665,19 @@ if MCP_AVAILABLE: verbose_logger.debug( f"MCP list_tools - MCP server auth headers: {list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None}" ) + if getattr( + getattr(user_api_key_auth, "object_permission", None), + "mcp_tool_search_enabled", + False, + ): + from mcp.types import Tool + + from litellm.proxy._experimental.mcp_server.tool_search import ( + get_virtual_tool_definitions, + ) + + return [Tool(**d) for d in get_virtual_tool_definitions()] + # Get mcp_servers from context variable verbose_logger.debug("MCP list_tools - Calling _list_mcp_tools") tools = await _list_mcp_tools( @@ -688,6 +702,150 @@ if MCP_AVAILABLE: if _session_reset_token is not None: active_mcp_session_var.reset(_session_reset_token) + def _capture_host_progress_callback(host_server) -> Optional[Callable]: + """Return a progress-forwarding callback bound to the host MCP session. + + Returns ``None`` when the host did not supply a progress token. + """ + try: + host_ctx = host_server.request_context + except Exception as e: + verbose_logger.warning(f"Could not capture host progress context: {e}") + return None + + if not (host_ctx and hasattr(host_ctx, "meta") and host_ctx.meta): + return None + host_token = getattr(host_ctx.meta, "progressToken", None) + if not (host_token and hasattr(host_ctx, "session") and host_ctx.session): + return None + host_session = host_ctx.session + + async def forward_progress(progress: float, total: Optional[float]): + """Forward progress notifications from external MCP to Host""" + try: + await host_session.send_progress_notification( + progress_token=host_token, + progress=progress, + total=total, + ) + verbose_logger.debug(f"Forwarded progress {progress}/{total} to Host") + except Exception as e: + verbose_logger.error(f"Failed to forward progress to Host: {e}") + + verbose_logger.debug(f"Host progressToken captured: {host_token[:8]}...") + return forward_progress + + async def _build_virtual_call_logging_obj( + name: str, + arguments: dict[str, Any], + user_api_key_auth: UserAPIKeyAuth, + ) -> Optional[LiteLLMLoggingObj]: + """Run the pre-call pipeline (guardrails + logging setup) for a virtual + mcp_tool_call so the SSE path spend-logs like the REST path.""" + from fastapi import Request + + from litellm.proxy.common_request_processing import ( + ProxyBaseLLMRequestProcessing, + ) + from litellm.proxy.proxy_server import ( + general_settings, + proxy_config, + proxy_logging_obj, + ) + + request = Request( + scope={ + "type": "http", + "method": "POST", + "path": "/mcp/tools/call", + "headers": [(b"content-type", b"application/json")], + } + ) + _, virtual_logging_obj = await ProxyBaseLLMRequestProcessing( + data={"name": name, "arguments": arguments} + ).common_processing_pre_call_logic( + request=request, + user_api_key_dict=user_api_key_auth, + proxy_config=proxy_config, + route_type=CallTypes.call_mcp_tool.value, + proxy_logging_obj=proxy_logging_obj, + general_settings=general_settings, + ) + return virtual_logging_obj + + async def _dispatch_virtual_mcp_tool( + name: str, + arguments: Optional[dict[str, Any]], + user_api_key_auth: Optional[UserAPIKeyAuth], + client_ip: Optional[str], + mcp_servers: Optional[list[str]] = None, + mcp_auth_header: Optional[str] = None, + mcp_server_auth_headers: Optional[dict[str, dict[str, str]]] = None, + oauth2_headers: Optional[dict[str, str]] = None, + raw_headers: Optional[dict[str, str]] = None, + ) -> Optional[CallToolResult]: + """Handle the mcp_tool_search / mcp_tool_call virtual tools. + + Returns a CallToolResult when ``name`` is a virtual tool, else ``None`` so + the caller falls through to normal tool routing. + """ + from litellm.proxy._experimental.mcp_server.tool_search import ( + MCP_TOOL_CALL_TOOL_NAME, + MCP_TOOL_SEARCH_TOOL_NAME, + coerce_top_k, + handle_mcp_tool_call, + handle_mcp_tool_search, + ) + + if name not in (MCP_TOOL_SEARCH_TOOL_NAME, MCP_TOOL_CALL_TOOL_NAME): + return None + + if not getattr( + getattr(user_api_key_auth, "object_permission", None), + "mcp_tool_search_enabled", + False, + ): + return CallToolResult( + content=[ + TextContent( + type="text", + text=f"Tool {name} requires mcp_tool_search_enabled on the key", + ) + ], + isError=True, + ) + + args = arguments or {} + if name == MCP_TOOL_SEARCH_TOOL_NAME: + return await handle_mcp_tool_search( + query=args.get("query", ""), + top_k=coerce_top_k(args.get("top_k", 5)), + user_api_key_dict=user_api_key_auth, + client_ip=client_ip, + mcp_servers=mcp_servers, + mcp_auth_header=mcp_auth_header, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + ) + + assert user_api_key_auth is not None # guaranteed by the flag check above + virtual_logging_obj = await _build_virtual_call_logging_obj( + name=name, arguments=args, user_api_key_auth=user_api_key_auth + ) + return await handle_mcp_tool_call( + tool_name=args.get("tool_name", ""), + arguments=args.get("arguments") or {}, + user_api_key_dict=user_api_key_auth, + client_ip=client_ip, + mcp_servers=mcp_servers, + mcp_auth_header=mcp_auth_header, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + litellm_logging_obj=virtual_logging_obj, + ) + @server.call_tool() async def mcp_server_tool_call(name: str, arguments: Dict[str, Any] | None) -> CallToolResult: """ @@ -701,11 +859,12 @@ if MCP_AVAILABLE: HTTPException: If tool not found or arguments missing """ from fastapi import Request + from mcp.server.lowlevel.server import request_ctx + from mcp.types import CallToolResult + from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request from litellm.proxy.proxy_server import proxy_config - from mcp.types import CallToolResult - from mcp.server.lowlevel.server import request_ctx req_ctx = request_ctx.get(None) _session_reset_token = None @@ -730,31 +889,25 @@ if MCP_AVAILABLE: ) verbose_logger.debug(f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}") - host_progress_callback = None - try: - host_ctx = server.request_context - if host_ctx and hasattr(host_ctx, "meta") and host_ctx.meta: - host_token = getattr(host_ctx.meta, "progressToken", None) - if host_token and hasattr(host_ctx, "session") and host_ctx.session: - host_session = host_ctx.session - async def forward_progress(progress: float, total: Optional[float]): - """Forward progress notifications from external MCP to Host""" - try: - await host_session.send_progress_notification( - progress_token=host_token, - progress=progress, - total=total, - ) - verbose_logger.debug(f"Forwarded progress {progress}/{total} to Host") - except Exception as e: - verbose_logger.error(f"Failed to forward progress to Host: {e}") - - host_progress_callback = forward_progress - verbose_logger.debug(f"Host progressToken captured: {host_token[:8]}...") - except Exception as e: - verbose_logger.warning(f"Could not capture host progress context: {e}") try: + # Inside this try so virtual-tool errors convert to isError + # CallToolResult instead of raising out of the protocol handler. + virtual_tool_result = await _dispatch_virtual_mcp_tool( + name=name, + arguments=arguments, + user_api_key_auth=user_api_key_auth, + client_ip=_client_ip, + mcp_servers=mcp_servers, + mcp_auth_header=mcp_auth_header, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + ) + if virtual_tool_result is not None: + return virtual_tool_result + + host_progress_callback = _capture_host_progress_callback(server) # Create a body date for logging body_data = {"name": name, "arguments": arguments} # Set trace/session id from raw_headers so spend logs and logging_obj stay consistent (same as A2A) @@ -1528,6 +1681,7 @@ if MCP_AVAILABLE: log_list_tools_to_spendlogs: bool = False, list_tools_log_source: Optional[str] = None, litellm_trace_id: Optional[str] = None, + client_ip: Optional[str] = None, ) -> List[MCPTool]: """ Helper method to fetch tools from MCP servers based on server filtering criteria. @@ -1615,6 +1769,7 @@ if MCP_AVAILABLE: allowed_mcp_servers = await _get_allowed_mcp_servers( user_api_key_auth=user_api_key_auth, mcp_servers=mcp_servers, + client_ip=client_ip, ) # Pre-fetch OAuth credentials only when at least one server uses OAuth2, @@ -2024,6 +2179,7 @@ if MCP_AVAILABLE: raw_headers: Optional[Dict[str, str]] = None, log_list_tools_to_spendlogs: bool = False, list_tools_log_source: Optional[str] = None, + client_ip: Optional[str] = None, ) -> List[MCPTool]: """ List all available MCP tools. @@ -2033,6 +2189,7 @@ if MCP_AVAILABLE: mcp_auth_header: Optional auth header for MCP server (deprecated) mcp_servers: Optional list of server names/aliases to filter by mcp_server_auth_headers: Optional dict of server-specific auth headers {server_alias: auth_value} + client_ip: Client IP for IP-based server access control Returns: List[MCPTool]: Combined list of tools from all accessible servers @@ -2056,6 +2213,7 @@ if MCP_AVAILABLE: raw_headers=raw_headers, log_list_tools_to_spendlogs=log_list_tools_to_spendlogs, list_tools_log_source=list_tools_log_source, + client_ip=client_ip, ) verbose_logger.debug(f"Successfully fetched {len(managed_tools)} tools from managed MCP servers") except Exception as e: diff --git a/litellm/proxy/_experimental/mcp_server/tool_search.py b/litellm/proxy/_experimental/mcp_server/tool_search.py new file mode 100644 index 00000000000..fa57a2b3eb2 --- /dev/null +++ b/litellm/proxy/_experimental/mcp_server/tool_search.py @@ -0,0 +1,157 @@ +from __future__ import annotations + +import json +from datetime import datetime +from typing import TYPE_CHECKING, Any, Optional + +if TYPE_CHECKING: + from mcp.types import CallToolResult + + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.proxy._types import UserAPIKeyAuth + +MCP_TOOL_SEARCH_TOOL_NAME: str = "mcp_tool_search" +MCP_TOOL_CALL_TOOL_NAME: str = "mcp_tool_call" + + +def coerce_top_k(value: Any, default: int = 5) -> int: + try: + return int(value) + except (TypeError, ValueError): + return default + + +def search_tools(query: str, tools: list[dict[str, Any]], top_k: int = 5) -> list[dict[str, Any]]: + if not query: + return [] + tokens = query.lower().split() + + def _score(tool: dict[str, Any]) -> int: + haystack = (tool.get("name", "") + " " + tool.get("description", "")).lower() + return sum(1 for t in tokens if t in haystack) + + scored = ((s, tool) for tool in tools if (s := _score(tool)) > 0) + return [tool for _, tool in sorted(scored, key=lambda x: x[0], reverse=True)[:top_k]] + + +def get_virtual_tool_definitions() -> list[dict[str, Any]]: + return [ + { + "name": MCP_TOOL_SEARCH_TOOL_NAME, + "description": "Search for MCP tools by keyword. Returns top matching tools with names, descriptions, and input schemas.", + "inputSchema": { + "type": "object", + "properties": { + "query": { + "type": "string", + "description": "Keywords to search for in tool names and descriptions.", + }, + "top_k": { + "type": "integer", + "description": "Maximum number of results to return.", + "default": 5, + }, + }, + "required": ["query"], + }, + }, + { + "name": MCP_TOOL_CALL_TOOL_NAME, + "description": "Call an MCP tool by name with the given arguments.", + "inputSchema": { + "type": "object", + "properties": { + "tool_name": { + "type": "string", + "description": "The exact name of the MCP tool to call.", + }, + "arguments": { + "type": "object", + "description": "Arguments to pass to the tool.", + }, + }, + "required": ["tool_name"], + }, + }, + ] + + +async def handle_mcp_tool_search( + query: str, + top_k: int, + user_api_key_dict: UserAPIKeyAuth, + client_ip: Optional[str] = None, + mcp_servers: Optional[list[str]] = None, + mcp_auth_header: Optional[str] = None, + mcp_server_auth_headers: Optional[dict[str, dict[str, str]]] = None, + oauth2_headers: Optional[dict[str, str]] = None, + raw_headers: Optional[dict[str, str]] = None, +) -> CallToolResult: + from mcp.types import CallToolResult, TextContent + + from litellm.proxy._experimental.mcp_server.server import _list_mcp_tools + + mcp_tools = await _list_mcp_tools( + user_api_key_auth=user_api_key_dict, + mcp_servers=mcp_servers, + client_ip=client_ip, + mcp_auth_header=mcp_auth_header, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + ) + tools = [ + { + "name": t.name, + "description": t.description or "", + "inputSchema": t.inputSchema, + } + for t in mcp_tools + ] + results = search_tools(query, tools, top_k) + return CallToolResult(content=[TextContent(type="text", text=json.dumps(results))], isError=False) + + +async def handle_mcp_tool_call( + tool_name: str, + arguments: dict[str, Any], + user_api_key_dict: UserAPIKeyAuth, + client_ip: Optional[str] = None, + mcp_servers: Optional[list[str]] = None, + mcp_auth_header: Optional[str] = None, + mcp_server_auth_headers: Optional[dict[str, dict[str, str]]] = None, + oauth2_headers: Optional[dict[str, str]] = None, + raw_headers: Optional[dict[str, str]] = None, + litellm_logging_obj: Optional[LiteLLMLoggingObj] = None, +) -> CallToolResult: + from litellm.proxy._experimental.mcp_server.server import ( + _get_allowed_mcp_servers, + execute_mcp_tool, + ) + + allowed_mcp_servers = await _get_allowed_mcp_servers( + user_api_key_auth=user_api_key_dict, + mcp_servers=mcp_servers, + client_ip=client_ip, + ) + + # Reject before dispatch when the key has no accessible servers; otherwise an + # unprefixed local tool name would fall through to the local registry in + # execute_mcp_tool, which has no server permission check. + if not allowed_mcp_servers: + from fastapi import HTTPException + + raise HTTPException(status_code=403, detail="User not allowed to call this tool.") + + return await execute_mcp_tool( + name=tool_name, + arguments=arguments, + allowed_mcp_servers=allowed_mcp_servers, + start_time=datetime.now(), + user_api_key_auth=user_api_key_dict, + mcp_auth_header=mcp_auth_header, + mcp_server_auth_headers=mcp_server_auth_headers, + oauth2_headers=oauth2_headers, + raw_headers=raw_headers, + litellm_logging_obj=litellm_logging_obj, + ) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 643f8d69300..12466b525d6 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -1006,6 +1006,7 @@ class LiteLLM_ObjectPermissionBase(LiteLLMPydanticObjectBase): agent_access_groups: Optional[List[str]] = None models: Optional[List[str]] = None search_tools: Optional[List[str]] = None + mcp_tool_search_enabled: Optional[bool] = None from litellm.types.object_permission import ( # noqa: E402 diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index e21c0016491..5351e0a1470 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -279,6 +279,7 @@ model LiteLLM_ObjectPermissionTable { blocked_tools String[] @default([]) // Tool names blocked for any key/team/user with this permission mcp_toolsets String[] @default([]) // Toolset IDs granted to this key/team/user search_tools String[] @default([]) // search_tool_name values this key/team/user may call + mcp_tool_search_enabled Boolean? teams LiteLLM_TeamTable[] projects LiteLLM_ProjectTable[] verification_tokens LiteLLM_VerificationToken[] diff --git a/litellm/types/object_permission.py b/litellm/types/object_permission.py index ff932dccd5d..d0458173fbf 100644 --- a/litellm/types/object_permission.py +++ b/litellm/types/object_permission.py @@ -24,3 +24,4 @@ class ObjectPermissionDict(TypedDict, total=False): agent_access_groups: Optional[list[str]] models: Optional[list[str]] search_tools: Optional[list[str]] + mcp_tool_search_enabled: Optional[bool] diff --git a/schema.prisma b/schema.prisma index e21c0016491..5351e0a1470 100644 --- a/schema.prisma +++ b/schema.prisma @@ -279,6 +279,7 @@ model LiteLLM_ObjectPermissionTable { blocked_tools String[] @default([]) // Tool names blocked for any key/team/user with this permission mcp_toolsets String[] @default([]) // Toolset IDs granted to this key/team/user search_tools String[] @default([]) // search_tool_name values this key/team/user may call + mcp_tool_search_enabled Boolean? teams LiteLLM_TeamTable[] projects LiteLLM_ProjectTable[] verification_tokens LiteLLM_VerificationToken[] diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py new file mode 100644 index 00000000000..9c20808df67 --- /dev/null +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py @@ -0,0 +1,837 @@ +""" +Tests for MCP tool search feature. + +Covers: +- search_tools() pure function +- get_virtual_tool_definitions() shape +- list_tool_rest_api returns only virtual tools when mcp_tool_search_enabled=True +- call_tool_rest_api intercepts mcp_tool_search calls +- call_tool_rest_api intercepts mcp_tool_call calls +""" + +import json +from typing import Any +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from litellm.models.object_permission import LiteLLM_ObjectPermissionTable +from litellm.proxy._experimental.mcp_server.tool_search import ( + MCP_TOOL_CALL_TOOL_NAME, + MCP_TOOL_SEARCH_TOOL_NAME, + coerce_top_k, + get_virtual_tool_definitions, + search_tools, +) +from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth + + +def _make_tools(specs: list[tuple[str, str]]) -> list[dict[str, Any]]: + return [ + { + "name": name, + "description": desc, + "inputSchema": {"type": "object", "properties": {}}, + } + for name, desc in specs + ] + + +def _make_perm(**kwargs: Any) -> LiteLLM_ObjectPermissionTable: + return LiteLLM_ObjectPermissionTable(object_permission_id="test", **kwargs) + + +SAMPLE_TOOLS = _make_tools( + [ + ("github-create_issue", "Create a new issue in a GitHub repository"), + ("github-list_repos", "List all repositories for a GitHub user"), + ("slack-send_message", "Send a message to a Slack channel"), + ("slack-list_channels", "List all Slack channels in a workspace"), + ("notion-create_page", "Create a new page in Notion"), + ] +) + + +class TestCoerceTopK: + def test_int_passthrough(self) -> None: + assert coerce_top_k(3) == 3 + + def test_numeric_string_coerced(self) -> None: + assert coerce_top_k("7") == 7 + + def test_float_truncated(self) -> None: + assert coerce_top_k(3.9) == 3 + + def test_non_numeric_string_returns_default(self) -> None: + assert coerce_top_k("abc") == 5 + + def test_none_returns_default(self) -> None: + assert coerce_top_k(None) == 5 + + def test_custom_default(self) -> None: + assert coerce_top_k("nope", default=10) == 10 + + +class TestSearchTools: + def test_returns_matching_tools(self) -> None: + results = search_tools("github issue", SAMPLE_TOOLS) + names = [t["name"] for t in results] + assert "github-create_issue" in names + + def test_ranks_by_relevance(self) -> None: + results = search_tools("github", SAMPLE_TOOLS) + names = [t["name"] for t in results] + github_positions = [i for i, n in enumerate(names) if n.startswith("github")] + other_positions = [i for i, n in enumerate(names) if not n.startswith("github")] + assert all(g < o for g in github_positions for o in other_positions) + + def test_top_k_limits_results(self) -> None: + results = search_tools("a", SAMPLE_TOOLS, top_k=2) + assert len(results) <= 2 + + def test_empty_query_returns_empty(self) -> None: + assert search_tools("", SAMPLE_TOOLS) == [] + + def test_no_match_returns_empty(self) -> None: + assert search_tools("xyzzy_nonexistent_zzz", SAMPLE_TOOLS) == [] + + def test_matches_description_not_just_name(self) -> None: + results = search_tools("channel", SAMPLE_TOOLS) + names = [t["name"] for t in results] + assert "slack-list_channels" in names + + def test_case_insensitive(self) -> None: + lower = [t["name"] for t in search_tools("github", SAMPLE_TOOLS)] + upper = [t["name"] for t in search_tools("GITHUB", SAMPLE_TOOLS)] + assert lower == upper + + def test_result_tools_have_full_schema(self) -> None: + for tool in search_tools("github", SAMPLE_TOOLS): + assert "name" in tool + assert "description" in tool + assert "inputSchema" in tool + + +class TestGetVirtualToolDefinitions: + def test_returns_two_tools(self) -> None: + assert len(get_virtual_tool_definitions()) == 2 + + def test_has_mcp_tool_search(self) -> None: + names = [t["name"] for t in get_virtual_tool_definitions()] + assert MCP_TOOL_SEARCH_TOOL_NAME in names + + def test_has_mcp_tool_call(self) -> None: + names = [t["name"] for t in get_virtual_tool_definitions()] + assert MCP_TOOL_CALL_TOOL_NAME in names + + def test_mcp_tool_search_schema_has_query(self) -> None: + tools = get_virtual_tool_definitions() + search_tool = next(t for t in tools if t["name"] == MCP_TOOL_SEARCH_TOOL_NAME) + props = search_tool["inputSchema"]["properties"] + assert "query" in props + assert search_tool["inputSchema"]["required"] == ["query"] + + def test_mcp_tool_call_schema_has_tool_name_and_arguments(self) -> None: + tools = get_virtual_tool_definitions() + call_tool = next(t for t in tools if t["name"] == MCP_TOOL_CALL_TOOL_NAME) + props = call_tool["inputSchema"]["properties"] + assert "tool_name" in props + assert "arguments" in props + assert "tool_name" in call_tool["inputSchema"]["required"] + + def test_all_tools_have_description(self) -> None: + for tool in get_virtual_tool_definitions(): + assert tool.get("description"), f"{tool['name']} missing description" + + def test_definitions_construct_mcp_protocol_tool(self) -> None: + """The MCP protocol list_tools handler builds mcp.types.Tool(**d) from + each definition, so the dict keys must stay valid Tool fields.""" + from mcp.types import Tool + + built = [Tool(**d) for d in get_virtual_tool_definitions()] + assert {t.name for t in built} == { + MCP_TOOL_SEARCH_TOOL_NAME, + MCP_TOOL_CALL_TOOL_NAME, + } + + +class TestListToolRestApiWithToolSearch: + @pytest.mark.asyncio + async def test_returns_only_virtual_tools_when_flag_enabled(self) -> None: + from litellm.proxy._experimental.mcp_server.rest_endpoints import router + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm( + mcp_tool_search_enabled=True, + mcp_servers=["github", "slack"], + ), + ) + + mock_request = MagicMock() + mock_request.headers = {} + + list_fn = next( + r.endpoint + for r in router.routes + if hasattr(r, "path") and r.path.endswith("/tools/list") and hasattr(r, "methods") and "GET" in r.methods + ) + + result = await list_fn( + request=mock_request, + server_id=None, + include_disabled_tools=False, + user_api_key_dict=user_api_key_dict, + ) + + assert result["error"] is None + tool_names = [t["name"] for t in result["tools"]] + assert set(tool_names) == {MCP_TOOL_SEARCH_TOOL_NAME, MCP_TOOL_CALL_TOOL_NAME} + + @pytest.mark.asyncio + async def test_returns_full_catalog_when_flag_disabled(self) -> None: + from litellm.proxy._experimental.mcp_server.rest_endpoints import router + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm( + mcp_tool_search_enabled=False, + mcp_servers=["github"], + ), + ) + + mock_request = MagicMock() + mock_request.headers = {} + + fake_tools = [ + { + "name": "github-create_issue", + "description": "Create issue", + "inputSchema": {"type": "object"}, + } + ] + + list_fn = next( + r.endpoint + for r in router.routes + if hasattr(r, "path") and r.path.endswith("/tools/list") and hasattr(r, "methods") and "GET" in r.methods + ) + + with ( + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints.build_effective_auth_contexts", + new_callable=AsyncMock, + return_value=[user_api_key_dict], + ), + patch("litellm.proxy._experimental.mcp_server.rest_endpoints.global_mcp_server_manager") as mock_manager, + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_tools_for_single_server", + new_callable=AsyncMock, + return_value=fake_tools, + ), + patch("litellm.proxy._experimental.mcp_server.rest_endpoints.IPAddressUtils"), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._prefetch_user_oauth_creds", + new_callable=AsyncMock, + return_value={}, + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_oauth2_server_ids", + return_value=[], + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_server_auth_header", + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_user_oauth_extra_headers", + new_callable=AsyncMock, + return_value=None, + ), + ): + mock_manager.get_allowed_mcp_servers = AsyncMock(return_value=["github"]) + mock_manager.filter_server_ids_by_ip_with_info = MagicMock(return_value=(["github"], 0)) + mock_manager.get_mcp_server_by_id = MagicMock(return_value=MagicMock(name="github", server_id="github")) + result = await list_fn( + request=mock_request, + server_id=None, + include_disabled_tools=False, + user_api_key_dict=user_api_key_dict, + ) + + tool_names = [t["name"] for t in result["tools"]] + assert MCP_TOOL_SEARCH_TOOL_NAME not in tool_names + assert "github-create_issue" in tool_names + + @pytest.mark.asyncio + async def test_admin_include_disabled_tools_bypasses_virtual_catalog(self) -> None: + """Regression: an admin listing with include_disabled_tools must see the + real catalog (to configure allowlists) even when mcp_tool_search_enabled is + set, instead of the two virtual tools.""" + from litellm.proxy._experimental.mcp_server.rest_endpoints import router + + user_api_key_dict = UserAPIKeyAuth( + api_key="admin_key", + user_role=LitellmUserRoles.PROXY_ADMIN, + object_permission=_make_perm( + mcp_tool_search_enabled=True, + mcp_servers=["github"], + ), + ) + + mock_request = MagicMock() + mock_request.headers = {} + + fake_tools = [ + { + "name": "github-create_issue", + "description": "Create issue", + "inputSchema": {"type": "object"}, + } + ] + + list_fn = next( + r.endpoint + for r in router.routes + if hasattr(r, "path") and r.path.endswith("/tools/list") and hasattr(r, "methods") and "GET" in r.methods + ) + + with ( + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints.build_effective_auth_contexts", + new_callable=AsyncMock, + return_value=[user_api_key_dict], + ), + patch("litellm.proxy._experimental.mcp_server.rest_endpoints.global_mcp_server_manager") as mock_manager, + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_tools_for_single_server", + new_callable=AsyncMock, + return_value=fake_tools, + ), + patch("litellm.proxy._experimental.mcp_server.rest_endpoints.IPAddressUtils"), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._prefetch_user_oauth_creds", + new_callable=AsyncMock, + return_value={}, + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_oauth2_server_ids", + return_value=[], + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_server_auth_header", + return_value=None, + ), + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints._get_user_oauth_extra_headers", + new_callable=AsyncMock, + return_value=None, + ), + ): + mock_manager.get_allowed_mcp_servers = AsyncMock(return_value=["github"]) + mock_manager.filter_server_ids_by_ip_with_info = MagicMock(return_value=(["github"], 0)) + mock_manager.get_mcp_server_by_id = MagicMock(return_value=MagicMock(name="github", server_id="github")) + result = await list_fn( + request=mock_request, + server_id=None, + include_disabled_tools=True, + user_api_key_dict=user_api_key_dict, + ) + + tool_names = [t["name"] for t in result["tools"]] + assert MCP_TOOL_SEARCH_TOOL_NAME not in tool_names + assert "github-create_issue" in tool_names + + +class TestCallToolRestApiVirtualTools: + def _make_request(self, body: dict[str, Any]) -> MagicMock: + mock_request = MagicMock() + mock_request.json = AsyncMock(return_value=body) + mock_request.headers = {} + mock_request.url = MagicMock() + mock_request.url.path = "/mcp-rest/tools/call" + return mock_request + + def _get_call_fn(self) -> Any: + from litellm.proxy._experimental.mcp_server.rest_endpoints import router + + return next( + r.endpoint + for r in router.routes + if hasattr(r, "path") and r.path.endswith("/tools/call") and hasattr(r, "methods") and "POST" in r.methods + ) + + @pytest.mark.asyncio + async def test_mcp_tool_search_call_returns_tool_defs(self) -> None: + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm( + mcp_tool_search_enabled=True, + mcp_servers=["github"], + ), + ) + + request = self._make_request({"name": MCP_TOOL_SEARCH_TOOL_NAME, "arguments": {"query": "create issue"}}) + + mock_tool = MagicMock() + mock_tool.name = "github-create_issue" + mock_tool.description = "Create a GitHub issue" + mock_tool.inputSchema = {"type": "object", "properties": {}} + + with patch( + "litellm.proxy._experimental.mcp_server.server._list_mcp_tools", + new_callable=AsyncMock, + return_value=[mock_tool], + ): + result = await self._get_call_fn()( + request=request, + user_api_key_dict=user_api_key_dict, + ) + + assert result.content + assert result.content[0].type == "text" + returned_tools = json.loads(result.content[0].text) + assert isinstance(returned_tools, list) + assert any(t["name"] == "github-create_issue" for t in returned_tools) + + @pytest.mark.asyncio + async def test_mcp_tool_call_executes_discovered_tool(self) -> None: + from mcp.types import CallToolResult, TextContent + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm( + mcp_tool_search_enabled=True, + mcp_servers=["github"], + ), + ) + + request = self._make_request( + { + "name": MCP_TOOL_CALL_TOOL_NAME, + "arguments": { + "tool_name": "github-create_issue", + "arguments": {"title": "bug", "repo": "myrepo"}, + }, + } + ) + + fake_result = CallToolResult( + content=[TextContent(type="text", text="Issue created")], + isError=False, + ) + + with ( + patch( + "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", + new_callable=AsyncMock, + return_value=[MagicMock()], + ), + patch( + "litellm.proxy._experimental.mcp_server.server.execute_mcp_tool", + new_callable=AsyncMock, + return_value=fake_result, + ) as mock_execute, + ): + result = await self._get_call_fn()( + request=request, + user_api_key_dict=user_api_key_dict, + ) + + mock_execute.assert_awaited_once() + assert mock_execute.await_args.kwargs["name"] == "github-create_issue" + + assert result.isError is False + assert result.content[0].text == "Issue created" + + @pytest.mark.asyncio + async def test_mcp_tool_call_forwards_client_ip_for_ip_filtering(self) -> None: + """Regression: the virtual call path must resolve allowed servers with the + request's client IP so IP-restricted servers (available_on_public_internet: + false) cannot be reached from a public IP.""" + from mcp.types import CallToolResult, TextContent + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm(mcp_tool_search_enabled=True, mcp_servers=["github"]), + ) + request = self._make_request( + { + "name": MCP_TOOL_CALL_TOOL_NAME, + "arguments": {"tool_name": "github-create_issue", "arguments": {}}, + } + ) + + fake_result = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) + + with ( + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints.IPAddressUtils.get_mcp_client_ip", + return_value="203.0.113.7", + ), + patch( + "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", + new_callable=AsyncMock, + return_value=[MagicMock()], + ) as mock_allowed, + patch( + "litellm.proxy._experimental.mcp_server.server.execute_mcp_tool", + new_callable=AsyncMock, + return_value=fake_result, + ), + ): + await self._get_call_fn()(request=request, user_api_key_dict=user_api_key_dict) + + mock_allowed.assert_awaited_once() + assert mock_allowed.await_args.kwargs["client_ip"] == "203.0.113.7" + + @pytest.mark.asyncio + async def test_mcp_tool_search_forwards_client_ip_for_ip_filtering(self) -> None: + """Search must list tools through the IP-filtered catalog, not the raw one.""" + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm(mcp_tool_search_enabled=True, mcp_servers=["github"]), + ) + request = self._make_request({"name": MCP_TOOL_SEARCH_TOOL_NAME, "arguments": {"query": "issue"}}) + + with ( + patch( + "litellm.proxy._experimental.mcp_server.rest_endpoints.IPAddressUtils.get_mcp_client_ip", + return_value="203.0.113.7", + ), + patch( + "litellm.proxy._experimental.mcp_server.server._list_mcp_tools", + new_callable=AsyncMock, + return_value=[], + ) as mock_list, + ): + await self._get_call_fn()(request=request, user_api_key_dict=user_api_key_dict) + + mock_list.assert_awaited_once() + assert mock_list.await_args.kwargs["client_ip"] == "203.0.113.7" + + @pytest.mark.asyncio + async def test_mcp_tool_search_requires_flag_enabled(self) -> None: + from fastapi import HTTPException + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_key", + object_permission=_make_perm(mcp_tool_search_enabled=False), + ) + + request = self._make_request({"name": MCP_TOOL_SEARCH_TOOL_NAME, "arguments": {"query": "create issue"}}) + + with pytest.raises(HTTPException) as exc_info: + await self._get_call_fn()( + request=request, + user_api_key_dict=user_api_key_dict, + ) + + assert exc_info.value.status_code in (400, 403, 404) + + +class TestDispatchVirtualMcpTool: + """Covers the SSE/protocol-path interception helper in server.py.""" + + @pytest.mark.asyncio + async def test_returns_none_for_non_virtual_tool(self) -> None: + from litellm.proxy._experimental.mcp_server.server import ( + _dispatch_virtual_mcp_tool, + ) + + result = await _dispatch_virtual_mcp_tool( + name="github-create_issue", + arguments={}, + user_api_key_auth=UserAPIKeyAuth(api_key="k"), + client_ip=None, + ) + assert result is None + + @pytest.mark.asyncio + async def test_rejects_when_flag_disabled(self) -> None: + from litellm.proxy._experimental.mcp_server.server import ( + _dispatch_virtual_mcp_tool, + ) + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=False)) + result = await _dispatch_virtual_mcp_tool( + name=MCP_TOOL_SEARCH_TOOL_NAME, + arguments={"query": "x"}, + user_api_key_auth=uak, + client_ip=None, + ) + assert result is not None + assert result.isError is True + + @pytest.mark.asyncio + async def test_routes_search_with_client_ip(self) -> None: + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with patch( + "litellm.proxy._experimental.mcp_server.tool_search.handle_mcp_tool_search", + new_callable=AsyncMock, + return_value="SEARCH_RESULT", + ) as mock_search: + result = await srv._dispatch_virtual_mcp_tool( + name=MCP_TOOL_SEARCH_TOOL_NAME, + arguments={"query": "q", "top_k": 3}, + user_api_key_auth=uak, + client_ip="203.0.113.9", + ) + + assert result == "SEARCH_RESULT" + assert mock_search.await_args.kwargs["client_ip"] == "203.0.113.9" + assert mock_search.await_args.kwargs["query"] == "q" + assert mock_search.await_args.kwargs["top_k"] == 3 + + @pytest.mark.asyncio + async def test_routes_call_with_client_ip(self) -> None: + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with patch( + "litellm.proxy._experimental.mcp_server.tool_search.handle_mcp_tool_call", + new_callable=AsyncMock, + return_value="CALL_RESULT", + ) as mock_call: + result = await srv._dispatch_virtual_mcp_tool( + name=MCP_TOOL_CALL_TOOL_NAME, + arguments={"tool_name": "math-add", "arguments": {"a": 1, "b": 2}}, + user_api_key_auth=uak, + client_ip="203.0.113.9", + mcp_auth_header="bearer-xyz", + mcp_server_auth_headers={"github": {"Authorization": "Bearer gh"}}, + oauth2_headers={"Authorization": "Bearer oauth"}, + raw_headers={"x-mcp-auth": "tok"}, + ) + + assert result == "CALL_RESULT" + kw = mock_call.await_args.kwargs + assert kw["tool_name"] == "math-add" + assert kw["client_ip"] == "203.0.113.9" + assert kw["mcp_auth_header"] == "bearer-xyz" + assert kw["mcp_server_auth_headers"] == {"github": {"Authorization": "Bearer gh"}} + assert kw["oauth2_headers"] == {"Authorization": "Bearer oauth"} + assert kw["raw_headers"] == {"x-mcp-auth": "tok"} + + @pytest.mark.asyncio + async def test_call_builds_and_forwards_logging_obj(self) -> None: + """Regression: the SSE dispatch must run the pre-call pipeline and forward + the resulting logging object to handle_mcp_tool_call, otherwise mcp_tool_call + over /mcp/ skips spend logging and guardrails (unlike the REST path).""" + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + sentinel_logging_obj = object() + with ( + patch.object( + srv, + "_build_virtual_call_logging_obj", + new_callable=AsyncMock, + return_value=sentinel_logging_obj, + ) as mock_build, + patch( + "litellm.proxy._experimental.mcp_server.tool_search.handle_mcp_tool_call", + new_callable=AsyncMock, + return_value="CALL_RESULT", + ) as mock_call, + ): + await srv._dispatch_virtual_mcp_tool( + name=MCP_TOOL_CALL_TOOL_NAME, + arguments={"tool_name": "math-add", "arguments": {"a": 1}}, + user_api_key_auth=uak, + client_ip=None, + ) + + assert mock_build.await_count == 1 + assert mock_call.await_args.kwargs["litellm_logging_obj"] is sentinel_logging_obj + + @pytest.mark.asyncio + async def test_search_coerces_non_int_top_k(self) -> None: + """Regression: a non-integer top_k from an MCP client must not raise; it + falls back to the default instead of ValueError propagating out.""" + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with patch( + "litellm.proxy._experimental.mcp_server.tool_search.handle_mcp_tool_search", + new_callable=AsyncMock, + return_value="SEARCH_RESULT", + ) as mock_search: + await srv._dispatch_virtual_mcp_tool( + name=MCP_TOOL_SEARCH_TOOL_NAME, + arguments={"query": "issue", "top_k": "not-a-number"}, + user_api_key_auth=uak, + client_ip=None, + ) + + assert mock_search.await_args.kwargs["top_k"] == 5 + + @pytest.mark.asyncio + async def test_call_handler_forwards_auth_headers_to_execute(self) -> None: + """Regression: per-request auth headers must reach execute_mcp_tool so + upstream MCP servers needing pass-through auth can be called.""" + from mcp.types import CallToolResult, TextContent + + from litellm.proxy._experimental.mcp_server.tool_search import ( + handle_mcp_tool_call, + ) + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + fake = CallToolResult(content=[TextContent(type="text", text="ok")], isError=False) + with ( + patch( + "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", + new_callable=AsyncMock, + return_value=[MagicMock()], + ) as mock_allowed, + patch( + "litellm.proxy._experimental.mcp_server.server.execute_mcp_tool", + new_callable=AsyncMock, + return_value=fake, + ) as mock_exec, + ): + sentinel_logging_obj = object() + await handle_mcp_tool_call( + tool_name="github-create_issue", + arguments={}, + user_api_key_dict=uak, + mcp_servers=["github"], + mcp_auth_header="bearer-xyz", + mcp_server_auth_headers={"github": {"Authorization": "Bearer gh"}}, + oauth2_headers={"Authorization": "Bearer oauth"}, + raw_headers={"x-mcp-auth": "tok"}, + litellm_logging_obj=sentinel_logging_obj, + ) + + kw = mock_exec.await_args.kwargs + assert kw["mcp_auth_header"] == "bearer-xyz" + assert kw["mcp_server_auth_headers"] == {"github": {"Authorization": "Bearer gh"}} + assert kw["oauth2_headers"] == {"Authorization": "Bearer oauth"} + assert kw["raw_headers"] == {"x-mcp-auth": "tok"} + # Spend logging: the logging object must reach execute_mcp_tool + assert kw["litellm_logging_obj"] is sentinel_logging_obj + # Scoped session: the requested mcp_servers scope must reach server resolution + assert mock_allowed.await_args.kwargs["mcp_servers"] == ["github"] + + @pytest.mark.asyncio + async def test_call_rejected_when_no_accessible_servers(self) -> None: + """Regression: a key with no accessible MCP servers must not reach + execute_mcp_tool, where an unprefixed local tool name would otherwise + run via the local registry without a server permission check.""" + from fastapi import HTTPException + + from litellm.proxy._experimental.mcp_server.tool_search import ( + handle_mcp_tool_call, + ) + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with ( + patch( + "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", + new_callable=AsyncMock, + return_value=[], + ), + patch( + "litellm.proxy._experimental.mcp_server.server.execute_mcp_tool", + new_callable=AsyncMock, + ) as mock_exec, + ): + with pytest.raises(HTTPException) as exc_info: + await handle_mcp_tool_call( + tool_name="local_secret_tool", + arguments={}, + user_api_key_dict=uak, + ) + + assert exc_info.value.status_code == 403 + mock_exec.assert_not_awaited() + + +class TestCaptureHostProgressCallback: + """Covers the host progress-forwarding helper extracted from the tool call path.""" + + def test_returns_none_when_request_context_unavailable(self) -> None: + from litellm.proxy._experimental.mcp_server.server import ( + _capture_host_progress_callback, + ) + + class _NoCtx: + @property + def request_context(self): # type: ignore[no-untyped-def] + raise RuntimeError("no context") + + assert _capture_host_progress_callback(_NoCtx()) is None + + def test_returns_none_when_no_progress_token(self) -> None: + from litellm.proxy._experimental.mcp_server.server import ( + _capture_host_progress_callback, + ) + + host = MagicMock() + host.request_context.meta.progressToken = None + assert _capture_host_progress_callback(host) is None + + def test_returns_callable_when_token_present(self) -> None: + from litellm.proxy._experimental.mcp_server.server import ( + _capture_host_progress_callback, + ) + + host = MagicMock() + host.request_context.meta.progressToken = "tok12345" + host.request_context.session = MagicMock() + assert callable(_capture_host_progress_callback(host)) + + +class TestHandleListToolsVirtual: + """Covers the protocol list_tools early-return when the flag is enabled.""" + + @pytest.mark.asyncio + async def test_returns_virtual_tools_when_flag_enabled(self) -> None: + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with patch( + "litellm.proxy._experimental.mcp_server.server.get_or_extract_auth_context", + new_callable=AsyncMock, + return_value=(uak, None, None, None, None, None, None), + ): + tools = await srv.handle_list_tools() + + assert {t.name for t in tools} == { + MCP_TOOL_SEARCH_TOOL_NAME, + MCP_TOOL_CALL_TOOL_NAME, + } + + +class TestMcpServerToolCallErrorHandling: + """The protocol tool-call handler must convert virtual-tool errors to an + isError CallToolResult instead of letting them raise out of the handler.""" + + @pytest.mark.asyncio + async def test_virtual_tool_error_returns_iserror_not_raised(self) -> None: + from fastapi import HTTPException + + from litellm.proxy._experimental.mcp_server import server as srv + + uak = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True)) + with ( + patch( + "litellm.proxy._experimental.mcp_server.server.get_or_extract_auth_context", + new_callable=AsyncMock, + return_value=(uak, None, None, None, None, None, None), + ), + patch( + "litellm.proxy._experimental.mcp_server.server._dispatch_virtual_mcp_tool", + new_callable=AsyncMock, + side_effect=HTTPException(status_code=403, detail="User not allowed to call this tool"), + ), + ): + result = await srv.mcp_server_tool_call( + name=MCP_TOOL_CALL_TOOL_NAME, + arguments={"tool_name": "other-server-tool", "arguments": {}}, + ) + + assert result.isError is True + assert "User not allowed to call this tool" in result.content[0].text diff --git a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py index d4089b23e81..5fbc3c4869b 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py @@ -718,6 +718,7 @@ _EXPECTED_CUSTOMER = { "mcp_toolsets": None, "blocked_tools": [], "search_tools": [], + "mcp_tool_search_enabled": None, }, } diff --git a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py index 26c8c774812..0981c4239ee 100644 --- a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py +++ b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py @@ -87,6 +87,38 @@ async def test_set_object_permission(): assert result["models"] == ["gpt-4"] +@pytest.mark.asyncio +async def test_set_object_permission_persists_mcp_tool_search_enabled(): + """ + Regression: mcp_tool_search_enabled must be carried into the Prisma create + payload so it persists to LiteLLM_ObjectPermissionTable. The field was + present on the Pydantic models but missing from the create path, so keys + generated with mcp_tool_search_enabled=True silently lost the flag. + """ + mock_prisma_client = MagicMock() + mock_created_permission = MagicMock() + mock_created_permission.object_permission_id = "perm_id" + mock_prisma_client.db.litellm_objectpermissiontable.create = AsyncMock( + return_value=mock_created_permission + ) + + data_json = { + "object_permission": { + "mcp_servers": ["server_a"], + "mcp_tool_search_enabled": True, + }, + } + + await _set_object_permission(data_json=data_json, prisma_client=mock_prisma_client) + + created_data = ( + mock_prisma_client.db.litellm_objectpermissiontable.create.call_args.kwargs[ + "data" + ] + ) + assert created_data["mcp_tool_search_enabled"] is True + + # ---- Tests for _extract_requested_mcp_server_ids ---- diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts index f15eaf9ea1f..ddf2040cd04 100644 --- a/ui/litellm-dashboard/src/lib/http/schema.d.ts +++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts @@ -25107,6 +25107,8 @@ export interface components { mcp_tool_permissions?: { [key: string]: string[]; } | null; + /** Mcp Tool Search Enabled */ + mcp_tool_search_enabled?: boolean | null; /** Mcp Toolsets */ mcp_toolsets?: string[] | null; /** Models */ @@ -25150,6 +25152,8 @@ export interface components { mcp_tool_permissions?: { [key: string]: string[]; } | null; + /** Mcp Tool Search Enabled */ + mcp_tool_search_enabled?: boolean | null; /** Mcp Toolsets */ mcp_toolsets?: string[] | null; /** From 13b590c8ec8d5c0d69bdd6e6affe51a57976fd4b Mon Sep 17 00:00:00 2001 From: tin-berri Date: Tue, 30 Jun 2026 21:23:49 -0700 Subject: [PATCH 53/79] fix(proxy): hydrate MCP server registry from DB on startup when store_model_in_db is false (#31775) MCP servers created through the UI are persisted to the database independent of store_model_in_db, but the in-memory registry that GET /v1/mcp/server reads was hydrated from the database only through add_deployment, which runs solely when store_model_in_db is True. On a DB-backed single-instance proxy with store_model_in_db unset the registry started empty after a restart, so the MCP Servers page showed nothing until an add or edit triggered a reload. Hydrate the registry from the database on startup regardless of store_model_in_db via a new ProxyConfig.init_mcp_servers_from_db, honoring supported_db_objects. --- litellm/proxy/proxy_server.py | 7 +++ tests/test_litellm/proxy/test_proxy_server.py | 60 +++++++++++++++++++ 2 files changed, 67 insertions(+) diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 2f6c48a751b..6d64843fab0 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -6314,6 +6314,10 @@ class ProxyConfig: "litellm.proxy.proxy_server.py::ProxyConfig:_init_mcp_servers_in_db - {}".format(str(e)) ) + async def init_mcp_servers_from_db(self) -> None: + if self._should_load_db_object(object_type="mcp"): + await self._init_mcp_servers_in_db() + async def _init_agents_in_db(self, prisma_client: PrismaClient): from litellm.proxy.agent_endpoints.agent_registry import ( global_agent_registry as AGENT_REGISTRY, @@ -7561,6 +7565,9 @@ class ProxyStartupEvent: ) await proxy_config.get_credentials(prisma_client=prisma_client) + if store_model_in_db is not True: + await proxy_config.init_mcp_servers_from_db() + await cls._initialize_slack_alerting_jobs( scheduler=scheduler, general_settings=general_settings, diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 88d9ad0d968..0d6cd972459 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -754,6 +754,66 @@ async def test_initialize_scheduled_jobs_credentials(monkeypatch): assert len(mock_scheduler_calls) > 0 +@pytest.mark.asyncio +async def test_initialize_scheduled_jobs_hydrates_mcp_when_store_model_in_db_false(monkeypatch): + """ + Regression (LIT-4128): MCP servers created via the UI are persisted to the DB + regardless of store_model_in_db, but the in-memory registry that GET + /v1/mcp/server reads is hydrated from the DB only by the store_model_in_db + model-sync loop (add_deployment). On a DB-backed proxy with store_model_in_db + unset the registry must still be hydrated on startup so previously-added + servers survive a restart instead of showing an empty list until a write. + """ + monkeypatch.delenv("DISABLE_PRISMA_SCHEMA_UPDATE", raising=False) + monkeypatch.delenv("STORE_MODEL_IN_DB", raising=False) + from litellm.proxy.proxy_server import ProxyStartupEvent + from litellm.proxy.utils import ProxyLogging + + mock_prisma_client = MagicMock() + mock_proxy_logging = MagicMock(spec=ProxyLogging) + mock_proxy_logging.slack_alerting_instance = MagicMock() + mock_proxy_config = AsyncMock() + + with ( + patch("litellm.proxy.proxy_server.proxy_config", mock_proxy_config), + patch("litellm.proxy.proxy_server.store_model_in_db", False), + ): + await ProxyStartupEvent.initialize_scheduled_background_jobs( + general_settings={}, + prisma_client=mock_prisma_client, + proxy_budget_rescheduler_min_time=1, + proxy_budget_rescheduler_max_time=2, + proxy_batch_write_at=5, + proxy_logging_obj=mock_proxy_logging, + ) + + mock_proxy_config.add_deployment.assert_not_called() + mock_proxy_config.init_mcp_servers_from_db.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_init_mcp_servers_from_db_respects_supported_db_objects(monkeypatch): + """ + init_mcp_servers_from_db hydrates MCP from the DB by default but skips it when + an explicit supported_db_objects allowlist omits "mcp". + """ + from litellm.proxy.proxy_server import ProxyConfig + + config = ProxyConfig() + with patch.object(config, "_init_mcp_servers_in_db", new=AsyncMock()) as mock_init: + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + await config.init_mcp_servers_from_db() + mock_init.assert_awaited_once() + + mock_init.reset_mock() + monkeypatch.setattr( + "litellm.proxy.proxy_server.general_settings", + {"supported_db_objects": ["models"]}, + ) + await config.init_mcp_servers_from_db() + mock_init.assert_not_awaited() + + def test_update_config_fields_deep_merge_db_wins(): from litellm.proxy.proxy_server import ProxyConfig From e1415962049cfdc3f94522c697aaee4b25948e08 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 08:12:35 -0700 Subject: [PATCH 54/79] refactor(lint): collapse type/lint budgets to a single per-rule limit (#31883) * chore(lint): raise basedpyright per-rule slack to 50% of baseline The per-rule ceilings in basedpyright-code-budget.json sat at roughly 10% slack over baseline, which several in-flight PRs are already bumping into. Raise the slack on every rule to at least 50% of its baseline so there is ample headroom for a long while, while never lowering any rule that already had more generous slack (e.g. reportReturnType stays at 100). Co-authored-by: Mateo Wang * refactor(lint): collapse type/lint budgets to a single per-rule limit The three non-frontend budget files (ruff-strict, type-discipline, basedpyright-code) tracked a per-rule baseline and slack whose sum was the ceiling. Nothing consumed the split beyond that sum, so this replaces both keys with a single limit equal to the old baseline + slack; the original baselines live in git history if anyone needs them. The gate scripts and the ratchet guard now read limit directly. lint-budget-update no longer re-captures raw counts; it ratchets each rule's limit down by the number of violations this branch cleared since its branch point (the merge-base), so the granted headroom shrinks by exactly what was fixed and a limit never rises. The ratchet guard reads either schema so it still compares correctly across the migration boundary. Co-authored-by: Mateo Wang * chore(lint): surface staged-vs-working parity for pre-commit and budget-update make pre-commit selects which checks to run from the staged index but runs the linters over the working tree, so unstaged edits to tracked files and untracked files skew a green/red away from what a commit of only the staged changes would produce. There is no safe in-place way to lint the index, so the script now warns when unstaged or untracked changes are present, and CLAUDE.md documents that you must stage everything first for both make pre-commit and make lint-budget-update to predict CI correctly. Co-authored-by: Mateo Wang * docs(lint): list type-discipline budget in lint-budget-update instruction --------- Co-authored-by: Cursor Agent Co-authored-by: Mateo Wang --- CLAUDE.md | 4 +- Makefile | 23 +- basedpyright-code-budget.json | 144 +++---- ruff-strict-budget.json | 366 ++++++------------ scripts/budget_ratchet_check.py | 89 ++--- scripts/pre_commit_lint.sh | 16 + scripts/ruff_strict_gate.py | 55 ++- scripts/type_check_gate.py | 100 +++-- scripts/type_discipline_gate.py | 68 ++-- .../test_litellm/test_budget_ratchet_check.py | 76 ++-- tests/test_litellm/test_ruff_strict_gate.py | 36 +- tests/test_litellm/test_type_check_gate.py | 67 ++-- .../test_litellm/test_type_discipline_gate.py | 36 +- type-discipline-budget.json | 24 +- 14 files changed, 515 insertions(+), 589 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 83bf3e22d27..86bd89156a3 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -33,9 +33,9 @@ If you ever make public-facing PR descriptions, comments, issues, commit message Don't hesitate to use values in .env to get needed API keys and other secrets, as long as you never add them to conversation history, commit them, or include them in GitHub issues / PRs -Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed +Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed. For `make pre-commit` to work properly you must stage your changes first (git add): it reports CI red or green based on what would happen if you committed your staged changes, but it runs the linters over the working tree, so any unstaged edits to tracked files or untracked files are folded into the result and will skew it away from what CI (which only sees your commit) would report -When you fix violations gated by `ruff-strict-budget.json` or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered baselines so the ceilings ratchet down instead of leaving stale headroom +When you fix violations gated by `ruff-strict-budget.json`, `type-discipline-budget.json`, or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered limits so the ceilings ratchet down instead of leaving stale headroom. It lowers each rule's limit by the number of violations this branch cleared since its branch point and never raises one, measured against the working tree, so stage exactly the fixes you're committing before running it; crediting unstaged fixes you won't commit would over-tighten the limits and turn CI red once the committed subset is checked If you're trying to create a new function that relies on untyped stuff, instead of adding more Any's and pushing `reportAny` / `reportExplicitAny` closer to their basedpyright ceilings, just validate it in the caller with Pydantic (a model or `TypeAdapter` that returns the typed thing or raises will do) and then pass the now typed variable in diff --git a/Makefile b/Makefile index fb927148c80..c3fa21c156c 100644 --- a/Makefile +++ b/Makefile @@ -5,7 +5,7 @@ test-unit-integrations test-unit-core-utils test-unit-other test-unit-root \ test-proxy-unit-a test-proxy-unit-b test-integration test-unit-helm \ info lint lint-dev format \ - lint-basedpyright lint-basedpyright-budget-update \ + lint-basedpyright lint-basedpyright-budget-update lint-type-discipline lint-type-discipline-budget-update \ lint-ruff-budget lint-ruff-budget-update lint-budget-update lint-gate \ install-dev install-proxy-dev install-test-deps install-hooks \ install-helm-unittest check-circular-imports check-import-safety pre-commit \ @@ -27,12 +27,12 @@ help: @echo " make lint - Run all linting (Ruff, basedpyright, format check, circular imports, import safety)" @echo " make lint-ruff - Run Ruff linting only" @echo " make lint-basedpyright - Run basedpyright strict, gated by per-rule error counts" - @echo " make lint-basedpyright-budget-update - Re-capture the basedpyright per-rule budget (ratchet)" + @echo " make lint-basedpyright-budget-update - Ratchet basedpyright limits down by what this branch fixed" @echo " make lint-format - Check ruff format formatting (matches CI)" - @echo " make lint-ruff-budget - Gate the codebase total of each strict ruff rule against its ceiling" + @echo " make lint-ruff-budget - Gate the codebase total of each strict ruff rule against its limit" @echo " make lint-gate - Strict ruff gate in CI-parity mode (fetches staging, simulates the merge)" - @echo " make lint-ruff-budget-update - Re-capture per-rule baselines in ruff-strict-budget.json (ratchet)" - @echo " make lint-budget-update - Re-capture all ratchet budgets (ruff + basedpyright)" + @echo " make lint-ruff-budget-update - Ratchet ruff-strict-budget.json limits down by what this branch fixed" + @echo " make lint-budget-update - Ratchet all budgets down (ruff + type-discipline + basedpyright)" @echo " make check-circular-imports - Check for circular imports" @echo " make check-import-safety - Check import safety" @echo " make test - Run all tests" @@ -164,7 +164,9 @@ lint-basedpyright: install-dev lint-fetch-base lint-type-discipline: install-dev lint-fetch-base $(UV_RUN) python scripts/type_discipline_gate.py --base origin/litellm_internal_staging -lint-basedpyright-budget-update: install-dev +# --update lowers each limit by what this branch fixed since its branch point, so +# it needs the base ref fetched to resolve the merge-base. +lint-basedpyright-budget-update: install-dev lint-fetch-base ($(UV_RUN) basedpyright --outputjson || true) | $(UV_RUN) python scripts/type_check_gate.py --update lint-format: format-check @@ -177,11 +179,14 @@ lint-ruff-budget: install-dev lint-gate: install-dev lint-fetch-base $(UV_RUN) python scripts/ruff_strict_gate.py --base origin/litellm_internal_staging -lint-ruff-budget-update: install-dev +lint-ruff-budget-update: install-dev lint-fetch-base $(UV_RUN) python scripts/ruff_strict_gate.py --update -# Ratchet all budgets in one shot (ruff strict + basedpyright) -lint-budget-update: lint-ruff-budget-update lint-basedpyright-budget-update +lint-type-discipline-budget-update: install-dev lint-fetch-base + $(UV_RUN) python scripts/type_discipline_gate.py --update + +# Ratchet all budgets in one shot (ruff strict + type-discipline + basedpyright) +lint-budget-update: lint-ruff-budget-update lint-type-discipline-budget-update lint-basedpyright-budget-update check-circular-imports: install-dev cd litellm && $(UV_RUN) python ../tests/documentation_tests/test_circular_imports.py && cd .. diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json index f2b54e1f889..79e6af05978 100644 --- a/basedpyright-code-budget.json +++ b/basedpyright-code-budget.json @@ -1,194 +1,146 @@ { "reportAny": { - "baseline": 24989, - "slack": 2500 + "limit": 37484 }, "reportArgumentType": { - "baseline": 1814, - "slack": 180 + "limit": 2721 }, "reportAssignmentType": { - "baseline": 220, - "slack": 22 + "limit": 330 }, "reportAttributeAccessIssue": { - "baseline": 346, - "slack": 35 + "limit": 519 }, "reportCallIssue": { - "baseline": 87, - "slack": 10 + "limit": 131 }, "reportConstantRedefinition": { - "baseline": 39, - "slack": 4 + "limit": 59 }, "reportDeprecated": { - "baseline": 217, - "slack": 22 + "limit": 326 }, "reportDuplicateImport": { - "baseline": 28, - "slack": 3 + "limit": 42 }, "reportExplicitAny": { - "baseline": 6931, - "slack": 700 + "limit": 10397 }, "reportFunctionMemberAccess": { - "baseline": 7, - "slack": 3 + "limit": 11 }, "reportGeneralTypeIssues": { - "baseline": 151, - "slack": 15 + "limit": 227 }, "reportIncompatibleMethodOverride": { - "baseline": 52, - "slack": 5 + "limit": 78 }, "reportIncompatibleVariableOverride": { - "baseline": 8, - "slack": 3 + "limit": 12 }, "reportInconsistentOverload": { - "baseline": 12, - "slack": 3 + "limit": 18 }, "reportIndexIssue": { - "baseline": 26, - "slack": 3 + "limit": 39 }, "reportInvalidTypeForm": { - "baseline": 23, - "slack": 3 + "limit": 35 }, "reportInvalidTypeVarUse": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "reportMatchNotExhaustive": { - "baseline": 1, - "slack": 0 + "limit": 2 }, "reportMissingParameterType": { - "baseline": 3933, - "slack": 390 + "limit": 5900 }, "reportMissingTypeArgument": { - "baseline": 10612, - "slack": 1000 + "limit": 15918 }, "reportMissingTypeStubs": { - "baseline": 27, - "slack": 10 + "limit": 41 }, "reportOperatorIssue": { - "baseline": 6, - "slack": 3 + "limit": 9 }, "reportOptionalCall": { - "baseline": 4, - "slack": 3 + "limit": 7 }, "reportOptionalIterable": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "reportOptionalMemberAccess": { - "baseline": 724, - "slack": 72 + "limit": 1086 }, "reportOptionalOperand": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "reportOptionalSubscript": { - "baseline": 11, - "slack": 3 + "limit": 17 }, "reportPossiblyUnboundVariable": { - "baseline": 52, - "slack": 10 + "limit": 78 }, "reportPrivateUsage": { - "baseline": 1625, - "slack": 160 + "limit": 2438 }, "reportRedeclaration": { - "baseline": 8, - "slack": 3 + "limit": 12 }, "reportReturnType": { - "baseline": 126, - "slack": 100 + "limit": 226 }, "reportTypedDictNotRequiredAccess": { - "baseline": 20, - "slack": 3 + "limit": 30 }, "reportUndefinedVariable": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "reportUnknownArgumentType": { - "baseline": 30603, - "slack": 3000 + "limit": 45905 }, "reportUnknownLambdaType": { - "baseline": 75, - "slack": 10 + "limit": 113 }, "reportUnknownMemberType": { - "baseline": 27037, - "slack": 2500 + "limit": 40556 }, "reportUnknownParameterType": { - "baseline": 13612, - "slack": 1000 + "limit": 20418 }, "reportUnknownVariableType": { - "baseline": 21445, - "slack": 2000 + "limit": 32168 }, "reportUnnecessaryCast": { - "baseline": 118, - "slack": 10 + "limit": 177 }, "reportUnnecessaryComparison": { - "baseline": 683, - "slack": 100 + "limit": 1025 }, "reportUnnecessaryContains": { - "baseline": 4, - "slack": 3 + "limit": 7 }, "reportUnnecessaryIsInstance": { - "baseline": 808, - "slack": 80 + "limit": 1212 }, "reportUntypedBaseClass": { - "baseline": 110, - "slack": 11 + "limit": 165 }, "reportUntypedFunctionDecorator": { - "baseline": 22, - "slack": 3 + "limit": 33 }, "reportUnusedClass": { - "baseline": 22, - "slack": 3 + "limit": 33 }, "reportUnusedFunction": { - "baseline": 137, - "slack": 10 + "limit": 206 }, "reportUnusedImport": { - "baseline": 670, - "slack": 50 + "limit": 1005 }, "reportUnusedVariable": { - "baseline": 865, - "slack": 50 + "limit": 1298 } } diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json index 10c820324ea..be62f8a9d67 100644 --- a/ruff-strict-budget.json +++ b/ruff-strict-budget.json @@ -1,490 +1,368 @@ { "ANN001": { - "baseline": 2865, - "slack": 287 + "limit": 3152 }, "ANN002": { - "baseline": 64, - "slack": 5 + "limit": 69 }, "ANN003": { - "baseline": 759, - "slack": 76 + "limit": 835 }, "ANN201": { - "baseline": 1944, - "slack": 194 + "limit": 2138 }, "ANN202": { - "baseline": 858, - "slack": 86 + "limit": 944 }, "ANN204": { - "baseline": 658, - "slack": 66 + "limit": 724 }, "ANN205": { - "baseline": 117, - "slack": 10 + "limit": 127 }, "ANN206": { - "baseline": 120, - "slack": 10 + "limit": 130 }, "ANN401": { - "baseline": 1886, - "slack": 189 + "limit": 2075 }, "ASYNC230": { - "baseline": 11, - "slack": 3 + "limit": 14 }, "B004": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "B006": { - "baseline": 180, - "slack": 10 + "limit": 190 }, "B008": { - "baseline": 490, - "slack": 15 + "limit": 505 }, "B009": { - "baseline": 79, - "slack": 5 + "limit": 84 }, "B010": { - "baseline": 187, - "slack": 10 + "limit": 197 }, "B018": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "B019": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "B021": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "B026": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "B033": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "BLE001": { - "baseline": 2854, - "slack": 50 + "limit": 2904 }, "C401": { - "baseline": 8, - "slack": 3 + "limit": 11 }, "C404": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "C405": { - "baseline": 20, - "slack": 3 + "limit": 23 }, "C408": { - "baseline": 11, - "slack": 3 + "limit": 14 }, "C414": { - "baseline": 4, - "slack": 3 + "limit": 7 }, "C419": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "C901": { - "baseline": 301, - "slack": 15 + "limit": 316 }, "D419": { - "baseline": 6, - "slack": 3 + "limit": 9 }, "DTZ001": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "DTZ003": { - "baseline": 30, - "slack": 3 + "limit": 33 }, "DTZ005": { - "baseline": 229, - "slack": 15 + "limit": 244 }, "DTZ006": { - "baseline": 10, - "slack": 3 + "limit": 13 }, "DTZ007": { - "baseline": 20, - "slack": 3 + "limit": 23 }, "DTZ011": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "EXE001": { - "baseline": 4, - "slack": 3 + "limit": 7 }, "EXE002": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "F401": { - "baseline": 20, - "slack": 3 + "limit": 23 }, "FURB136": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "FURB168": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "FURB188": { - "baseline": 49, - "slack": 3 + "limit": 52 }, "I001": { - "baseline": 258, - "slack": 15 + "limit": 273 }, "LOG015": { - "baseline": 5, - "slack": 3 + "limit": 8 }, "N999": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PERF102": { - "baseline": 27, - "slack": 3 + "limit": 30 }, "PERF401": { - "baseline": 136, - "slack": 10 + "limit": 146 }, "PERF402": { - "baseline": 6, - "slack": 3 + "limit": 9 }, "PERF403": { - "baseline": 69, - "slack": 5 + "limit": 74 }, "PIE790": { - "baseline": 263, - "slack": 15 + "limit": 278 }, "PIE800": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PIE804": { - "baseline": 21, - "slack": 3 + "limit": 24 }, "PIE810": { - "baseline": 41, - "slack": 3 + "limit": 44 }, "PLC0206": { - "baseline": 28, - "slack": 3 + "limit": 31 }, "PLC0208": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PLC0414": { - "baseline": 35, - "slack": 3 + "limit": 38 }, "PLR0124": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PLR0206": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PLR0402": { - "baseline": 6, - "slack": 3 + "limit": 9 }, "PLR1704": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "PLR1711": { - "baseline": 31, - "slack": 3 + "limit": 34 }, "PLR1714": { - "baseline": 252, - "slack": 15 + "limit": 267 }, "PLR1730": { - "baseline": 7, - "slack": 3 + "limit": 10 }, "PLR2044": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PLW0127": { - "baseline": 41, - "slack": 3 + "limit": 44 }, "PLW0133": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "PLW0602": { - "baseline": 215, - "slack": 15 + "limit": 230 }, "PLW0603": { - "baseline": 183, - "slack": 10 + "limit": 193 }, "PLW1508": { - "baseline": 188, - "slack": 10 + "limit": 198 }, "PLW1510": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "PYI030": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "PYI036": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "PYI041": { - "baseline": 9, - "slack": 3 + "limit": 12 }, "PYI064": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "RET501": { - "baseline": 35, - "slack": 3 + "limit": 38 }, "RET504": { - "baseline": 702, - "slack": 20 + "limit": 722 }, "RUF010": { - "baseline": 844, - "slack": 30 + "limit": 874 }, "RUF012": { - "baseline": 158, - "slack": 10 + "limit": 168 }, "RUF015": { - "baseline": 8, - "slack": 3 + "limit": 11 }, "RUF019": { - "baseline": 38, - "slack": 3 + "limit": 41 }, "RUF022": { - "baseline": 80, - "slack": 5 + "limit": 85 }, "RUF023": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "RUF046": { - "baseline": 5, - "slack": 3 + "limit": 8 }, "RUF051": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "RUF059": { - "baseline": 69, - "slack": 5 + "limit": 74 }, "RUF100": { - "baseline": 465, - "slack": 15 + "limit": 480 }, "S110": { - "baseline": 222, - "slack": 15 + "limit": 237 }, "S112": { - "baseline": 21, - "slack": 3 + "limit": 24 }, "SIM101": { - "baseline": 58, - "slack": 5 + "limit": 63 }, "SIM102": { - "baseline": 311, - "slack": 15 + "limit": 326 }, "SIM103": { - "baseline": 119, - "slack": 10 + "limit": 129 }, "SIM113": { - "baseline": 3, - "slack": 3 + "limit": 6 }, "SIM114": { - "baseline": 103, - "slack": 10 + "limit": 113 }, "SIM115": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "SIM117": { - "baseline": 7, - "slack": 3 + "limit": 10 }, "SIM118": { - "baseline": 104, - "slack": 10 + "limit": 114 }, "SIM201": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "SIM210": { - "baseline": 9, - "slack": 3 + "limit": 12 }, "SIM211": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "SIM222": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "SIM401": { - "baseline": 9, - "slack": 3 + "limit": 12 }, "TC004": { - "baseline": 5, - "slack": 3 + "limit": 8 }, "TC005": { - "baseline": 6, - "slack": 3 + "limit": 9 }, "TID251": { - "baseline": 2664, - "slack": 50 + "limit": 2714 }, "TRY002": { - "baseline": 528, - "slack": 20 + "limit": 548 }, "TRY004": { - "baseline": 93, - "slack": 5 + "limit": 98 }, "TRY201": { - "baseline": 409, - "slack": 15 + "limit": 424 }, "TRY203": { - "baseline": 113, - "slack": 10 + "limit": 123 }, "TRY300": { - "baseline": 853, - "slack": 30 + "limit": 883 }, "UP006": { - "baseline": 12941, - "slack": 100 + "limit": 13041 }, "UP007": { - "baseline": 2520, - "slack": 50 + "limit": 2570 }, "UP008": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "UP012": { - "baseline": 4, - "slack": 3 + "limit": 7 }, "UP018": { - "baseline": 18, - "slack": 3 + "limit": 21 }, "UP024": { - "baseline": 12, - "slack": 3 + "limit": 15 }, "UP028": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "UP031": { - "baseline": 2, - "slack": 3 + "limit": 5 }, "UP032": { - "baseline": 609, - "slack": 20 + "limit": 629 }, "UP034": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "UP035": { - "baseline": 2250, - "slack": 50 + "limit": 2300 }, "UP036": { - "baseline": 1, - "slack": 3 + "limit": 4 }, "UP037": { - "baseline": 100, - "slack": 5 + "limit": 105 }, "UP045": { - "baseline": 18417, - "slack": 100 + "limit": 18517 } } diff --git a/scripts/budget_ratchet_check.py b/scripts/budget_ratchet_check.py index df9815d6557..10a78483643 100644 --- a/scripts/budget_ratchet_check.py +++ b/scripts/budget_ratchet_check.py @@ -1,19 +1,16 @@ #!/usr/bin/env python3 -"""Non-gating ratchet guard: budget baselines and ceilings may only fall, never rise. +"""Non-gating ratchet guard: budget limits may only fall, never rise. Every `*-budget.json` file (ruff-strict, type-discipline, basedpyright-code) is a -one-way ratchet: each rule's ceiling is `baseline + slack`, and both the recorded -`baseline` (the live violation count) and that ceiling are meant to be driven DOWN -over time. This check compares every budget file against its own content at the -merge-base with the target branch and fails (exits 1, red) if: +one-way ratchet: each rule's ceiling is its `limit`, and that limit is meant to be +driven DOWN over time. This check compares every budget file against its own +content at the merge-base with the target branch and fails (exits 1, red) if: - * a rule's ceiling (`baseline + slack`) went up, - * a rule's `baseline` went up, even if `slack` was lowered to keep the ceiling - flat (a higher baseline bakes in more accepted debt and must be acknowledged), + * a rule's `limit` went up, * a rule was dropped from a budget (its ceiling effectively became infinite), or * an entire budget file was deleted. -New rules and lowered/equal baselines and ceilings are fine. +New rules and lowered/equal limits are fine. This is deliberately NOT a gating check. It should turn the run red so that a loosening is impossible to miss in review, but it must stay OUT of the @@ -89,19 +86,21 @@ def _load_base(rel: str, ref: str) -> dict | None: return json.loads(proc.stdout) -def _baselines(budget: dict) -> dict[str, int]: - """Map each rule to its recorded baseline; skip malformed specs.""" - return { - rule: int(spec.get("baseline", 0)) - for rule, spec in budget.items() - if isinstance(spec, dict) - } +def _ceiling(spec: dict) -> int: + """A rule's ceiling: its `limit`, or legacy `baseline + slack`. + + The base side of the diff can predate the `limit` migration, so a spec is read + under either schema and the two are compared on the same footing. + """ + if "limit" in spec: + return int(spec["limit"]) + return int(spec.get("baseline", 0)) + int(spec.get("slack", 0)) -def _caps(budget: dict) -> dict[str, int]: - """Map each rule to its ceiling (baseline + slack); skip malformed specs.""" +def _limits(budget: dict) -> dict[str, int]: + """Map each rule to its ceiling; skip malformed specs.""" return { - rule: int(spec.get("baseline", 0)) + int(spec.get("slack", 0)) + rule: _ceiling(spec) for rule, spec in budget.items() if isinstance(spec, dict) } @@ -109,54 +108,32 @@ def _caps(budget: dict) -> dict[str, int]: def _regression_detail( rule: str, - base_caps: dict[str, int], - head_caps: dict[str, int], - base_baselines: dict[str, int], - head_baselines: dict[str, int], + base_limits: dict[str, int], + head_limits: dict[str, int], ) -> str | None: """Why `rule` regressed vs base, or None when it held flat or fell. - A dropped rule is terminal; otherwise a raised ceiling and a raised baseline are - independent loosenings (the latter catches a baseline bump masked by a slack cut), - so both reasons are reported when both apply. + A dropped rule is terminal; otherwise the only loosening left is a raised limit. """ - base_cap = base_caps[rule] - if rule not in head_caps: - return f"rule dropped (ceiling {base_cap} -> removed)" - reasons = tuple( - message - for raised, message in ( - ( - head_caps[rule] > base_cap, - f"ceiling raised {base_cap} -> {head_caps[rule]}", - ), - ( - head_baselines[rule] > base_baselines[rule], - f"baseline raised {base_baselines[rule]} -> {head_baselines[rule]}", - ), - ) - if raised - ) - return "; ".join(reasons) or None + base_limit = base_limits[rule] + if rule not in head_limits: + return f"rule dropped (limit {base_limit} -> removed)" + if head_limits[rule] > base_limit: + return f"limit raised {base_limit} -> {head_limits[rule]}" + return None def regressions_for(rel: str, base: dict | None, head: dict | None) -> list[Regression]: if base is None: return [] # new budget file: nothing to ratchet against yet if head is None: - return [Regression(rel, "*", "budget file was deleted (every ceiling removed)")] + return [Regression(rel, "*", "budget file was deleted (every limit removed)")] - base_caps, head_caps = _caps(base), _caps(head) - base_baselines, head_baselines = _baselines(base), _baselines(head) + base_limits, head_limits = _limits(base), _limits(head) return [ Regression(rel, rule, detail) - for rule in sorted(base_caps) - if ( - detail := _regression_detail( - rule, base_caps, head_caps, base_baselines, head_baselines - ) - ) - is not None + for rule in sorted(base_limits) + if (detail := _regression_detail(rule, base_limits, head_limits)) is not None ] @@ -191,7 +168,7 @@ def main() -> int: if regressions: print( - f"FAIL: budget baseline(s)/ceiling(s) loosened vs base {args.base} (merge-base {ref[:12]}):" + f"FAIL: budget limit(s) loosened vs base {args.base} (merge-base {ref[:12]}):" ) for reg in regressions: print(f" {reg.budget} {reg.rule}: {reg.detail}") @@ -203,7 +180,7 @@ def main() -> int: return 1 suffix = f" ({', '.join(checked)})" if checked else "" - print(f"OK: no budget ceiling increased vs base {args.base}{suffix}") + print(f"OK: no budget limit increased vs base {args.base}{suffix}") return 0 diff --git a/scripts/pre_commit_lint.sh b/scripts/pre_commit_lint.sh index 0852e9e0ca2..d667d6758e1 100755 --- a/scripts/pre_commit_lint.sh +++ b/scripts/pre_commit_lint.sh @@ -36,6 +36,22 @@ spec_files=$(staged_match '^(litellm/(proxy|types)/.*|ui/litellm-dashboard/(scri ui_prettier_files=$(staged_match '^ui/litellm-dashboard/.*\.(js|jsx|ts|tsx|mjs|cjs|json|css|scss|md|mdx|yml|yaml|html)$') ui_eslint_files=$(staged_match '^ui/litellm-dashboard/.*\.(js|jsx|ts|tsx|mjs|cjs)$') +# CI lints the committed tree, so this script predicts CI for what you have STAGED +# (every trigger above reads `git diff --cached`). The tools it runs, though, read +# the working tree, so unstaged edits to tracked files and untracked files fold +# into the result and a green/red here won't match a commit of just the staged +# changes. There's no safe way to lint the index in place, so surface the gap +# instead of hiding it: stage everything you intend to commit before trusting a +# pass. This only warns; it never blocks or touches your changes. +unstaged=$(git diff --name-only) +untracked=$(git ls-files --others --exclude-standard) +if [ -n "$unstaged" ] || [ -n "$untracked" ]; then + echo "pre-commit: NOTE - unstaged/untracked changes are included in these checks but" >&2 + echo " won't be in a commit of only your staged changes, so this result may differ from" >&2 + echo " CI. Stage everything you intend to commit (git add) for an accurate prediction:" >&2 + printf '%s\n' "$unstaged" "$untracked" | sed '/^$/d' | sed 's/^/ /' >&2 +fi + lint_dashboard() { ( rc=0 diff --git a/scripts/ruff_strict_gate.py b/scripts/ruff_strict_gate.py index 5951a1215ed..5273e4805f6 100644 --- a/scripts/ruff_strict_gate.py +++ b/scripts/ruff_strict_gate.py @@ -1,10 +1,12 @@ #!/usr/bin/env python3 """Total-count gate for the strict ruff rules in ruff-strict.toml. -Each rule has a hard ceiling (baseline + slack) in ruff-strict-budget.json. The -gate counts each rule across the whole tree and fails when a rule is both over -its ceiling and higher than the base it merges into, so a change is blamed for -the violations it adds, never for drift that already exists in the base. +Each rule has a hard ``limit`` in ruff-strict-budget.json. The gate counts each +rule across the whole tree and fails when a rule is both over its limit and +higher than the base it merges into, so a change is blamed for the violations it +adds, never for drift that already exists in the base. ``--update`` ratchets each +rule's limit down by the number of violations this branch fixed relative to its +branch point (the merge-base). """ import argparse @@ -90,7 +92,7 @@ def base_counts(ref: str) -> dict: def evaluate(head: dict, base: dict, budget: dict) -> list: breaches = [] for rule, spec in budget.items(): - cap = spec["baseline"] + spec["slack"] + cap = spec["limit"] total = head.get(rule, 0) if total > cap and total > base.get(rule, 0): breaches.append(Breach(rule, total, cap, total - base.get(rule, 0))) @@ -128,26 +130,49 @@ def cmd_check(base: str) -> None: _run(["git", "diff", base_point, "--unified=0", "--no-color", "--", TARGET]) ), ) - print(f"FAIL: strict-rule totals exceed their ceiling (base {base}):") + print(f"FAIL: strict-rule totals exceed their limit (base {base}):") for breach in breaches: print( - f" {breach.rule}: total {breach.total} over cap {breach.cap} (this change added {breach.added})" + f" {breach.rule}: total {breach.total} over limit {breach.cap} (this change added {breach.added})" ) for violation in sorted(v for v in new if v.code == breach.rule): print(f" {violation.file}:{violation.line}") print( - "Reduce the new violations or remove an equal number elsewhere; the ceiling is baseline + slack in ruff-strict-budget.json." + "Reduce the new violations or remove an equal number elsewhere; the ceiling is the limit in ruff-strict-budget.json." ) raise SystemExit(1) -def cmd_update() -> None: +def ratcheted_budget(budget: dict, current: dict, base: dict) -> dict: + """Each rule's limit lowered by the violations `current` fixed vs `base`. + + `base` is the count at the branch point (the commit this branch diverged + from). The drop is clamped to what was actually cleared (a rule that grew + stays put), so the limit only ever falls. + """ + return { + rule: { + "limit": max(0, spec["limit"] - max(0, base.get(rule, 0) - current.get(rule, 0))) + } + for rule, spec in sorted(budget.items()) + } + + +def cmd_update(base_ref: str = DEFAULT_BASE) -> None: + """Ratchet each rule's limit down by the violations this branch fixed. + + The working-tree count is compared against a ruff pass over a detached + worktree at the branch point (the merge-base with `base_ref`), so a branch's + fixes tighten its own ceilings by exactly what they cleared since it diverged. + """ budget = json.loads(BUDGET_PATH.read_text()) - head = count_by_rule(head_violations()) - for rule in budget: - budget[rule]["baseline"] = head.get(rule, 0) - BUDGET_PATH.write_text(json.dumps(budget, indent=2, sort_keys=True) + "\n") - print("Re-captured per-rule baselines from the current tree") + base_point = _run(["git", "merge-base", base_ref, "HEAD"]).strip() or base_ref + updated = ratcheted_budget( + budget, count_by_rule(head_violations()), base_counts(base_point) + ) + BUDGET_PATH.write_text(json.dumps(updated, indent=2, sort_keys=True) + "\n") + cleared = sum(budget[rule]["limit"] - updated[rule]["limit"] for rule in updated) + print(f"Ratcheted strict-rule limits down by {cleared} violations this branch fixed") def main() -> None: @@ -155,7 +180,7 @@ def main() -> None: parser.add_argument("--base", default=DEFAULT_BASE) parser.add_argument("--update", action="store_true") args = parser.parse_args() - cmd_update() if args.update else cmd_check(args.base) + cmd_update(args.base) if args.update else cmd_check(args.base) if __name__ == "__main__": diff --git a/scripts/type_check_gate.py b/scripts/type_check_gate.py index 2ef332d91ea..256fc433d8d 100644 --- a/scripts/type_check_gate.py +++ b/scripts/type_check_gate.py @@ -3,20 +3,22 @@ basedpyright's ``--outputjson`` is reduced to a count of errors per *rule* (``reportAny``, ``reportArgumentType``, ...) and checked against a committed -budget of the form ``{rule: {baseline, slack}}``, the same shape as +budget of the form ``{rule: {limit}}``, the same shape as ``ruff-strict-budget.json``. A rule fails only when its codebase-wide total is -both over its ceiling (``baseline + slack``) *and* higher than the count on the -base it merges into, so a change is blamed for the errors it adds, never for -drift that already sits in the base. That ``> base`` guard is what stops an -unrelated PR from inheriting a red once two PRs each land near the ceiling and -their sum crosses it: the bystander's count equals its base, so it is spared, -while any PR that actually grows the rule past the cap still fails. +both over its ``limit`` *and* higher than the count on the base it merges into, +so a change is blamed for the errors it adds, never for drift that already sits +in the base. That ``> base`` guard is what stops an unrelated PR from inheriting +a red once two PRs each land near the limit and their sum crosses it: the +bystander's count equals its base, so it is spared, while any PR that actually +grows the rule past its limit still fails. Head counts are read from stdin (the caller runs basedpyright once and pipes ``--outputjson`` in); the base count is a second basedpyright pass over a detached worktree at the merge-base, run under the same environment so import -resolution matches. ``--update`` re-captures the absolute per-rule baselines for -the ratchet, preserving each rule's slack. +resolution matches. ``--update`` ratchets each rule's ``limit`` down by the +number of errors this branch fixed relative to its branch point (the merge-base), +so the headroom you were granted shrinks by exactly what you cleared and never +grows. ``--outputjson`` is used rather than text diagnostics because the latter wrap across lines, leaving the ``(reportRule)`` on a continuation line away from the @@ -44,10 +46,10 @@ DEFAULT_BASE = "origin/litellm_internal_staging" # Bucket for a basedpyright diagnostic with no `rule`. Counted so it's gated. UNCODED = "" -# Ceiling for a rule that shows up at HEAD but isn't in the budget at all -- a -# brand-new error category (new construct, or a tool/version change). baseline -# is treated as 0, so the rule fails once it clears this much slack. -DEFAULT_SLACK = 10 +# Limit for a rule that shows up at HEAD but isn't in the budget at all -- a +# brand-new error category (new construct, or a tool/version change). The rule +# fails once it clears this many errors. +DEFAULT_LIMIT = 10 class Breach(NamedTuple): @@ -57,13 +59,6 @@ class Breach(NamedTuple): added: int -def _seed_slack(baseline: int) -> int: - """Slack written for a rule first captured into a budget; busy rules get - more headroom, mirroring the tiering in ruff-strict-budget.json. Existing - rules keep whatever slack their JSON already declares.""" - return 10 if baseline >= 50 else 3 - - def _to_relative(raw: str, root: Path) -> str | None: path = Path(raw) absolute = path if path.is_absolute() else root / path @@ -142,7 +137,7 @@ def evaluate( breaches = [] for code, total in head.items(): spec = budget.get(code) - cap = spec["baseline"] + spec["slack"] if spec else DEFAULT_SLACK + cap = spec["limit"] if spec else DEFAULT_LIMIT prior = base.get(code, 0) if total > cap and total > prior: breaches.append(Breach(code, total, cap, total - prior)) @@ -155,24 +150,47 @@ def is_vacuous_run( """True when nothing was parsed but the budget expects errors -- the signature of a type checker that crashed or produced no output. The CI pipe swallows the tool's exit code (`tool || true`), so without this guard an - empty run would clear every ceiling and pass silently.""" - return not counts and any(spec["baseline"] for spec in budget.values()) + empty run would clear every limit and pass silently.""" + return not counts and any(spec["limit"] for spec in budget.values()) -def cmd_update(counts: Mapping[str, int]) -> None: - existing = json.loads(BUDGET_PATH.read_text()) if BUDGET_PATH.exists() else {} - budget = { +def ratcheted_budget( + budget: Mapping[str, Mapping[str, int]], + current: Mapping[str, int], + base: Mapping[str, int], +) -> dict[str, dict[str, int]]: + """Each rule's limit lowered by the errors `current` fixed vs `base`. + + `base` is the count at the branch point (the commit this branch diverged + from). The drop is clamped to what was actually cleared (a rule that grew + stays put), so the limit only ever falls. Rules absent from the budget are + dropped: a genuinely new error category is added to the JSON deliberately, + not on update. + """ + return { code: { - "baseline": count, - "slack": ( - existing[code]["slack"] if code in existing else _seed_slack(count) - ), + "limit": max(0, spec["limit"] - max(0, base.get(code, 0) - current.get(code, 0))) } - for code, count in sorted(counts.items()) + for code, spec in sorted(budget.items()) } - BUDGET_PATH.write_text(json.dumps(budget, indent=2, sort_keys=True) + "\n") + + +def cmd_update(current: Mapping[str, int], base_ref: str = DEFAULT_BASE) -> None: + """Ratchet each rule's limit down by the errors this branch fixed. + + `current` is the working-tree count (piped in); the reference count comes + from a second basedpyright pass over a detached worktree at the branch point + (the merge-base with `base_ref`), so a branch's fixes tighten its own ceilings + by exactly what they cleared since it diverged, and limits never rise. + """ + budget = json.loads(BUDGET_PATH.read_text()) if BUDGET_PATH.exists() else {} + base_point = _run(["git", "merge-base", base_ref, "HEAD"]).strip() or base_ref + updated = ratcheted_budget(budget, current, base_counts(base_point)) + BUDGET_PATH.write_text(json.dumps(updated, indent=2, sort_keys=True) + "\n") + cleared = sum(budget[code]["limit"] - updated[code]["limit"] for code in updated) print( - f"Re-captured basedpyright per-rule budget: {len(budget)} rules, {sum(counts.values())} errors total" + f"Ratcheted basedpyright limits down by {cleared} errors this branch fixed " + f"across {len(updated)} rules" ) @@ -180,10 +198,10 @@ def cmd_check(base_ref: str) -> None: budget = json.loads(BUDGET_PATH.read_text()) head = count_basedpyright(sys.stdin.read()) if is_vacuous_run(head, budget): - expected = sum(spec["baseline"] for spec in budget.values()) + expected = sum(spec["limit"] for spec in budget.values()) print( - f"FAIL: basedpyright produced no errors, but {BUDGET_PATH.name} expects " - f"~{expected}. The type checker almost certainly crashed or emitted " + f"FAIL: basedpyright produced no errors, but {BUDGET_PATH.name} allows " + f"up to ~{expected}. The type checker almost certainly crashed or emitted " f"nothing; refusing to certify a vacuous run." ) raise SystemExit(1) @@ -199,17 +217,17 @@ def cmd_check(base_ref: str) -> None: breaches = evaluate(head, base, budget) if not breaches: print( - f"OK: every rule is within its basedpyright ceiling or no higher than base ({sum(head.values())} errors total)" + f"OK: every rule is within its basedpyright limit or no higher than base ({sum(head.values())} errors total)" ) return - print("FAIL: basedpyright errors exceed the per-rule ceiling:") + print("FAIL: basedpyright errors exceed the per-rule limit:") for breach in breaches: print( - f" {breach.code}: total {breach.total} over cap {breach.cap} (this change added {breach.added})" + f" {breach.code}: total {breach.total} over limit {breach.cap} (this change added {breach.added})" ) print( "Reduce the new errors or remove an equal number elsewhere; the ceiling is " - "baseline + slack in basedpyright-code-budget.json." + "the limit in basedpyright-code-budget.json." ) summary = "; ".join(f"{b.code} {b.total}/{b.cap} (+{b.added})" for b in breaches) print(f"BREACHED RULES: {summary}") @@ -222,7 +240,7 @@ def main() -> None: parser.add_argument("--update", action="store_true") args = parser.parse_args() if args.update: - cmd_update(count_basedpyright(sys.stdin.read())) + cmd_update(count_basedpyright(sys.stdin.read()), args.base) else: cmd_check(args.base) diff --git a/scripts/type_discipline_gate.py b/scripts/type_discipline_gate.py index c111486e56a..bd63a42dcab 100644 --- a/scripts/type_discipline_gate.py +++ b/scripts/type_discipline_gate.py @@ -2,18 +2,19 @@ """Total-count gate for the LIT* rules in scripts/check_type_discipline.py. Sibling of scripts/ruff_strict_gate.py. Each rule listed in -type-discipline-budget.json has a hard ceiling (baseline + slack). The gate counts -each rule across the whole `litellm` tree and fails when a rule is both over its -ceiling and higher than the base it merges into, so a change is blamed for the -violations it adds, never for drift that already exists in the base. +type-discipline-budget.json has a hard ``limit``. The gate counts each rule +across the whole `litellm` tree and fails when a rule is both over its limit and +higher than the base it merges into, so a change is blamed for the violations it +adds, never for drift that already exists in the base. Rules not present in the budget are ignored, but today every rule the checker emits is gated: LIT001 (mutable collection in any annotation), LIT002 (mutable-collection construction), LIT003/LIT004 (noqa / ignore without codes or -reason), LIT006 (cast), and LIT008 (`**kwargs`) carry slack-buffered ceilings to -ratchet down; LIT005 (`*-ok` suppression without a reason) is frozen at slack 0 -so any net-new reasonless suppression trips the gate; and LIT007 (TypeGuard/TypeIs) -is a hard zero. Re-baseline with `--update` to ratchet a ceiling down. +reason), LIT006 (cast), and LIT008 (`**kwargs`) carry limits above their current +count to ratchet down; LIT005 (`*-ok` suppression without a reason) is frozen at +limit 0 so any net-new reasonless suppression trips the gate; and LIT007 +(TypeGuard/TypeIs) is a hard zero. ``--update`` ratchets a limit down by the +violations this branch fixed relative to its branch point (the merge-base). """ import argparse @@ -104,21 +105,21 @@ def base_counts(ref: str) -> dict: def over_ceiling(head: dict, budget: dict) -> frozenset: - """Rules whose head count already exceeds baseline + slack. + """Rules whose head count already exceeds their limit. - A rule can only breach when it is over its ceiling, so when none are the base + A rule can only breach when it is over its limit, so when none are the base comparison cannot change the verdict and the base worktree scan can be skipped. """ return frozenset( rule for rule, spec in budget.items() - if head.get(rule, 0) > spec["baseline"] + spec["slack"] + if head.get(rule, 0) > spec["limit"] ) def evaluate(head: dict, base: dict, budget: dict) -> list: breaches = [] for rule, spec in budget.items(): - cap = spec["baseline"] + spec["slack"] + cap = spec["limit"] total = head.get(rule, 0) if total > cap and total > base.get(rule, 0): breaches.append(Breach(rule, total, cap, total - base.get(rule, 0))) @@ -160,10 +161,10 @@ def cmd_check(base: str) -> None: _run(["git", "diff", base_point, "--unified=0", "--no-color", "--", TARGET]) ), ) - print(f"FAIL: LIT-rule totals exceed their ceiling (base {base}):") + print(f"FAIL: LIT-rule totals exceed their limit (base {base}):") for breach in breaches: print( - f" {breach.rule}: total {breach.total} over cap {breach.cap} (this change added {breach.added})" + f" {breach.rule}: total {breach.total} over limit {breach.cap} (this change added {breach.added})" ) for violation in sorted(v for v in new if v.code == breach.rule): print(f" {violation.file}:{violation.line}") @@ -171,19 +172,42 @@ def cmd_check(base: str) -> None: "Remove the new violations, give each a reason (`# noqa: XXX # `, " "`# pyright: ignore[rule] # `, `# mutable-ok: `, " "`# cast-ok: `, `# guard-ok: `, `# kwargs-ok: `), or " - "remove an equal number elsewhere; the ceiling is baseline + slack in " + "remove an equal number elsewhere; the ceiling is the limit in " "type-discipline-budget.json." ) raise SystemExit(1) -def cmd_update() -> None: +def ratcheted_budget(budget: dict, current: dict, base: dict) -> dict: + """Each rule's limit lowered by the violations `current` fixed vs `base`. + + `base` is the count at the branch point (the commit this branch diverged + from). The drop is clamped to what was actually cleared (a rule that grew + stays put), so the limit only ever falls. + """ + return { + rule: { + "limit": max(0, spec["limit"] - max(0, base.get(rule, 0) - current.get(rule, 0))) + } + for rule, spec in sorted(budget.items()) + } + + +def cmd_update(base_ref: str = DEFAULT_BASE) -> None: + """Ratchet each rule's limit down by the violations this branch fixed. + + The working-tree count is compared against a checker pass over a detached + worktree at the branch point (the merge-base with `base_ref`), so a branch's + fixes tighten its own ceilings by exactly what they cleared since it diverged. + """ budget = json.loads(BUDGET_PATH.read_text()) - head = count_by_rule(head_violations()) - for rule in budget: - budget[rule]["baseline"] = head.get(rule, 0) - BUDGET_PATH.write_text(json.dumps(budget, indent=2, sort_keys=True) + "\n") - print("Re-captured per-rule baselines from the current tree") + base_point = _run(["git", "merge-base", base_ref, "HEAD"]).strip() or base_ref + updated = ratcheted_budget( + budget, count_by_rule(head_violations()), base_counts(base_point) + ) + BUDGET_PATH.write_text(json.dumps(updated, indent=2, sort_keys=True) + "\n") + cleared = sum(budget[rule]["limit"] - updated[rule]["limit"] for rule in updated) + print(f"Ratcheted LIT-rule limits down by {cleared} violations this branch fixed") def main() -> None: @@ -191,7 +215,7 @@ def main() -> None: parser.add_argument("--base", default=DEFAULT_BASE) parser.add_argument("--update", action="store_true") args = parser.parse_args() - cmd_update() if args.update else cmd_check(args.base) + cmd_update(args.base) if args.update else cmd_check(args.base) if __name__ == "__main__": diff --git a/tests/test_litellm/test_budget_ratchet_check.py b/tests/test_litellm/test_budget_ratchet_check.py index 77cee8a485c..1972c1b6386 100644 --- a/tests/test_litellm/test_budget_ratchet_check.py +++ b/tests/test_litellm/test_budget_ratchet_check.py @@ -1,9 +1,8 @@ """Tests for scripts/budget_ratchet_check.py. -The guard's contract is "baselines and ceilings may only fall": a raised ceiling, a -raised baseline (even when slack is cut to keep the ceiling flat), a dropped rule, or -a deleted file is a regression, while a lowered/equal baseline and ceiling, a brand-new -rule, or a brand-new budget file is fine. Each branch is pinned here. +The guard's contract is "limits may only fall": a raised limit, a dropped rule, or +a deleted file is a regression, while a lowered/equal limit, a brand-new rule, or a +brand-new budget file is fine. Each branch is pinned here. """ import importlib.util @@ -19,69 +18,64 @@ ratchet = importlib.util.module_from_spec(_spec) _spec.loader.exec_module(ratchet) -def _spec_of(baseline, slack): - return {"baseline": baseline, "slack": slack} +def _spec_of(limit): + return {"limit": limit} -def test_caps_sum_baseline_and_slack_and_skip_malformed(): - caps = ratchet._caps({"LIT006": _spec_of(1013, 10), "junk": 5}) - assert caps == {"LIT006": 1023} # malformed (non-dict) spec ignored +def test_limits_read_the_limit_and_skip_malformed(): + limits = ratchet._limits({"LIT006": _spec_of(1023), "junk": 5}) + assert limits == {"LIT006": 1023} # malformed (non-dict) spec ignored -def test_raised_ceiling_is_a_regression(): - base = {"LIT006": _spec_of(1013, 10)} - head = {"LIT006": _spec_of(1013, 11)} # cap 1023 -> 1024 +def test_limits_fall_back_to_legacy_baseline_plus_slack(): + # The base side of a diff can predate the `limit` migration; its ceiling is + # baseline + slack, read on the same footing as a new-schema `limit`. + assert ratchet._limits({"LIT006": {"baseline": 1013, "slack": 10}}) == {"LIT006": 1023} + + +def test_migration_from_legacy_schema_to_equal_limit_is_clean(): + # baseline+slack (1023) -> limit 1023 is the same ceiling, so no regression. + base = {"LIT006": {"baseline": 1013, "slack": 10}} + assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1023)}) == [] + # ...and a genuine raise across the migration is still caught. + regs = ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1024)}) + assert [r.rule for r in regs] == ["LIT006"] and "1023 -> 1024" in regs[0].detail + + +def test_raised_limit_is_a_regression(): + base = {"LIT006": _spec_of(1023)} + head = {"LIT006": _spec_of(1024)} regs = ratchet.regressions_for("b.json", base, head) assert [r.rule for r in regs] == ["LIT006"] assert "1023 -> 1024" in regs[0].detail -def test_lowered_or_equal_ceiling_is_clean(): - base = {"LIT006": _spec_of(1013, 10)} - # baseline drops, slack flat -> ceiling falls - assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1000, 10)}) == [] +def test_lowered_or_equal_limit_is_clean(): + base = {"LIT006": _spec_of(1023)} + # limit drops + assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1000)}) == [] # nothing changes - assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1013, 10)}) == [] - # slack cut while baseline holds -> ceiling falls, baseline flat - assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1013, 0)}) == [] - - -def test_raised_baseline_is_a_regression_even_when_ceiling_held_flat(): - # baseline 1013 -> 1023 with slack cut 10 -> 0 keeps the ceiling at 1023, but a - # higher baseline bakes in more accepted debt and must still surface as a regression - base = {"LIT006": _spec_of(1013, 10)} - regs = ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1023, 0)}) - assert [r.rule for r in regs] == ["LIT006"] - assert "baseline raised 1013 -> 1023" in regs[0].detail - assert "ceiling raised" not in regs[0].detail - - -def test_raised_baseline_and_ceiling_report_both_reasons(): - base = {"LIT006": _spec_of(1013, 10)} - regs = ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1100, 10)}) - assert [r.rule for r in regs] == ["LIT006"] - assert "ceiling raised 1023 -> 1110" in regs[0].detail - assert "baseline raised 1013 -> 1100" in regs[0].detail + assert ratchet.regressions_for("b.json", base, {"LIT006": _spec_of(1023)}) == [] def test_dropped_rule_is_a_regression(): - regs = ratchet.regressions_for("b.json", {"LIT007": _spec_of(0, 0)}, {}) + regs = ratchet.regressions_for("b.json", {"LIT007": _spec_of(0)}, {}) assert [r.rule for r in regs] == ["LIT007"] assert "dropped" in regs[0].detail def test_new_rule_in_head_is_clean(): - assert ratchet.regressions_for("b.json", {}, {"new-rule": _spec_of(5, 0)}) == [] + assert ratchet.regressions_for("b.json", {}, {"new-rule": _spec_of(5)}) == [] def test_deleted_budget_file_is_a_regression(): - regs = ratchet.regressions_for("b.json", {"LIT006": _spec_of(1, 0)}, None) + regs = ratchet.regressions_for("b.json", {"LIT006": _spec_of(1)}, None) assert [r.rule for r in regs] == ["*"] assert "deleted" in regs[0].detail def test_new_budget_file_has_nothing_to_ratchet(): - assert ratchet.regressions_for("b.json", None, {"LIT006": _spec_of(1, 0)}) == [] + assert ratchet.regressions_for("b.json", None, {"LIT006": _spec_of(1)}) == [] def test_default_budgets_watch_every_budget_file_in_the_repo(): diff --git a/tests/test_litellm/test_ruff_strict_gate.py b/tests/test_litellm/test_ruff_strict_gate.py index 22255f0555e..ec8f49730dd 100644 --- a/tests/test_litellm/test_ruff_strict_gate.py +++ b/tests/test_litellm/test_ruff_strict_gate.py @@ -11,16 +11,16 @@ _spec.loader.exec_module(gate) Violation = gate.Violation -def rule(name, baseline, slack): - return {name: {"baseline": baseline, "slack": slack}} +def rule(name, limit): + return {name: {"limit": limit}} def test_under_ceiling_passes(): - assert gate.evaluate({"ANN001": 100}, {"ANN001": 100}, rule("ANN001", 90, 20)) == [] + assert gate.evaluate({"ANN001": 100}, {"ANN001": 100}, rule("ANN001", 110)) == [] -def test_ceiling_is_baseline_plus_slack_boundary(): - budget = rule("ANN001", 90, 20) # cap 110 +def test_ceiling_is_the_limit_boundary(): + budget = rule("ANN001", 110) at = gate.evaluate({"ANN001": 110}, {"ANN001": 90}, budget) over = gate.evaluate({"ANN001": 111}, {"ANN001": 90}, budget) assert at == [] @@ -30,23 +30,23 @@ def test_ceiling_is_baseline_plus_slack_boundary(): def test_over_ceiling_and_change_added_fails(): - breaches = gate.evaluate({"C901": 11}, {"C901": 9}, rule("C901", 10, 0)) + breaches = gate.evaluate({"C901": 11}, {"C901": 9}, rule("C901", 10)) assert [b.rule for b in breaches] == ["C901"] assert breaches[0].added == 2 def test_base_already_over_ceiling_change_added_nothing_is_not_blamed(): - # drift safety: base is over cap, this change leaves the count where it is - assert gate.evaluate({"C901": 15}, {"C901": 15}, rule("C901", 10, 0)) == [] + # drift safety: base is over limit, this change leaves the count where it is + assert gate.evaluate({"C901": 15}, {"C901": 15}, rule("C901", 10)) == [] def test_change_that_reduces_an_over_ceiling_rule_is_not_blamed(): - # still over cap, but moving the right direction - assert gate.evaluate({"C901": 14}, {"C901": 16}, rule("C901", 10, 0)) == [] + # still over limit, but moving the right direction + assert gate.evaluate({"C901": 14}, {"C901": 16}, rule("C901", 10)) == [] def test_rules_are_independent(): - budget = {**rule("ANN001", 100, 50), **rule("C901", 10, 0)} + budget = {**rule("ANN001", 150), **rule("C901", 10)} breaches = gate.evaluate( {"ANN001": 130, "C901": 11}, {"ANN001": 100, "C901": 10}, budget ) @@ -54,7 +54,19 @@ def test_rules_are_independent(): def test_missing_rule_counts_as_zero(): - assert gate.evaluate({}, {}, rule("C901", 0, 0)) == [] + assert gate.evaluate({}, {}, rule("C901", 0)) == [] + + +def test_update_ratchets_limit_down_by_what_the_branch_fixed_never_up(): + budget = {**rule("ANN001", 150), **rule("C901", 10)} + # ANN001 fixed 20 (100 -> 80) so its limit falls 150 -> 130; C901 grew, so its + # limit holds flat at 10 (a fix must never loosen a ceiling). + current = {"ANN001": 80, "C901": 12} + base = {"ANN001": 100, "C901": 9} + assert gate.ratcheted_budget(budget, current, base) == { + "ANN001": {"limit": 130}, + "C901": {"limit": 10}, + } def test_parse_changed_lines_maps_added_lines_per_file(): diff --git a/tests/test_litellm/test_type_check_gate.py b/tests/test_litellm/test_type_check_gate.py index e99ad0a4f41..3faf46c87de 100644 --- a/tests/test_litellm/test_type_check_gate.py +++ b/tests/test_litellm/test_type_check_gate.py @@ -55,77 +55,98 @@ def test_paths_outside_repo_are_skipped(): def test_at_or_under_ceiling_passes(): - budget = {"no-any-return": {"baseline": 5, "slack": 0}} + budget = {"no-any-return": {"limit": 5}} assert gate.evaluate({"no-any-return": 5}, {}, budget) == [] def test_one_more_error_than_ceiling_fails(): - budget = {"no-any-return": {"baseline": 5, "slack": 0}} + budget = {"no-any-return": {"limit": 5}} assert gate.evaluate({"no-any-return": 6}, {}, budget) == [ gate.Breach("no-any-return", 6, 5, 6) ] -def test_slack_absorbs_small_increase_then_fails_past_it(): - budget = {"arg-type": {"baseline": 5, "slack": 5}} +def test_limit_absorbs_increase_up_to_it_then_fails_past_it(): + budget = {"arg-type": {"limit": 10}} assert gate.evaluate({"arg-type": 10}, {}, budget) == [] assert gate.evaluate({"arg-type": 11}, {}, budget) == [ gate.Breach("arg-type", 11, 10, 11) ] -def test_unbudgeted_new_code_uses_default_slack(): - assert gate.evaluate({"brand-new": gate.DEFAULT_SLACK}, {}, {}) == [] - assert gate.evaluate({"brand-new": gate.DEFAULT_SLACK + 1}, {}, {}) == [ +def test_unbudgeted_new_code_uses_default_limit(): + assert gate.evaluate({"brand-new": gate.DEFAULT_LIMIT}, {}, {}) == [] + assert gate.evaluate({"brand-new": gate.DEFAULT_LIMIT + 1}, {}, {}) == [ gate.Breach( "brand-new", - gate.DEFAULT_SLACK + 1, - gate.DEFAULT_SLACK, - gate.DEFAULT_SLACK + 1, + gate.DEFAULT_LIMIT + 1, + gate.DEFAULT_LIMIT, + gate.DEFAULT_LIMIT + 1, ) ] def test_drift_already_over_cap_in_base_is_not_blamed_on_a_flat_change(): - # The bystander case: a rule sits over its ceiling because two earlier PRs + # The bystander case: a rule sits over its limit because two earlier PRs # summed past it. A PR that branches off that base and adds nothing must pass - # -- total > cap but total == base, so the `> base` guard spares it. - budget = {"arg-type": {"baseline": 5, "slack": 5}} + # -- total > limit but total == base, so the `> base` guard spares it. + budget = {"arg-type": {"limit": 10}} assert gate.evaluate({"arg-type": 12}, {"arg-type": 12}, budget) == [] def test_change_that_grows_an_over_cap_rule_is_blamed_for_only_what_it_added(): - # Over cap AND above base: blamed, and `added` is the delta vs base, not the + # Over limit AND above base: blamed, and `added` is the delta vs base, not the # whole overage, so the message points at this change's contribution. - budget = {"arg-type": {"baseline": 5, "slack": 5}} + budget = {"arg-type": {"limit": 10}} assert gate.evaluate({"arg-type": 14}, {"arg-type": 12}, budget) == [ gate.Breach("arg-type", 14, 10, 2) ] def test_reducing_an_over_cap_rule_below_base_passes(): - budget = {"arg-type": {"baseline": 5, "slack": 5}} + budget = {"arg-type": {"limit": 10}} assert gate.evaluate({"arg-type": 11}, {"arg-type": 12}, budget) == [] def test_no_output_against_a_nonempty_budget_is_a_vacuous_run(): # A crashed type checker emits nothing; the gate must not certify it as clean. - budget = {"no-untyped-def": {"baseline": 4888, "slack": 10}} + budget = {"no-untyped-def": {"limit": 4898}} assert gate.is_vacuous_run({}, budget) is True def test_genuine_zero_and_empty_budget_are_not_vacuous(): assert gate.is_vacuous_run({}, {}) is False + assert gate.is_vacuous_run({}, {"no-untyped-def": {"limit": 0}}) is False assert ( - gate.is_vacuous_run({}, {"no-untyped-def": {"baseline": 0, "slack": 3}}) - is False - ) - assert ( - gate.is_vacuous_run({"arg-type": 1}, {"arg-type": {"baseline": 9, "slack": 1}}) - is False + gate.is_vacuous_run({"arg-type": 1}, {"arg-type": {"limit": 10}}) is False ) +def test_update_ratchets_a_limit_down_by_what_the_branch_fixed(): + # A rule that dropped from 40 (branch point) to 30 (current) fixed 10, so its + # limit of 100 falls to 90 -- the granted headroom (60) is preserved, not the + # raw count. + budget = {"reportAny": {"limit": 100}} + assert gate.ratcheted_budget(budget, {"reportAny": 30}, {"reportAny": 40}) == { + "reportAny": {"limit": 90} + } + + +def test_update_never_raises_a_limit_when_a_rule_grows(): + # Adding violations must not loosen the ceiling; the limit holds flat. + budget = {"reportAny": {"limit": 100}} + assert gate.ratcheted_budget(budget, {"reportAny": 55}, {"reportAny": 40}) == { + "reportAny": {"limit": 100} + } + + +def test_update_clamps_a_limit_at_zero_never_negative(): + budget = {"reportAny": {"limit": 5}} + assert gate.ratcheted_budget(budget, {"reportAny": 0}, {"reportAny": 40}) == { + "reportAny": {"limit": 0} + } + + def test_malformed_basedpyright_json_exits_loudly_not_as_zero_errors(): import pytest diff --git a/tests/test_litellm/test_type_discipline_gate.py b/tests/test_litellm/test_type_discipline_gate.py index d7d827685a6..8424d480fa6 100644 --- a/tests/test_litellm/test_type_discipline_gate.py +++ b/tests/test_litellm/test_type_discipline_gate.py @@ -14,27 +14,39 @@ gate = importlib.util.module_from_spec(_spec) _spec.loader.exec_module(gate) -def _budget(baseline, slack): - return {"LIT006": {"baseline": baseline, "slack": slack}} +def _budget(limit): + return {"LIT006": {"limit": limit}} -def test_over_ceiling_flags_only_counts_above_baseline_plus_slack(): - budget = _budget(10, 2) # cap 12 - assert gate.over_ceiling({"LIT006": 12}, budget) == frozenset() # at cap - assert gate.over_ceiling({"LIT006": 13}, budget) == frozenset({"LIT006"}) # over cap +def test_over_ceiling_flags_only_counts_above_the_limit(): + budget = _budget(12) + assert gate.over_ceiling({"LIT006": 12}, budget) == frozenset() # at limit + assert gate.over_ceiling({"LIT006": 13}, budget) == frozenset({"LIT006"}) # over limit assert gate.over_ceiling({}, budget) == frozenset() # missing rule counts as zero def test_over_ceiling_is_independent_across_rules(): - budget = {"LIT001": {"baseline": 5, "slack": 0}, "LIT006": {"baseline": 10, "slack": 0}} + budget = {"LIT001": {"limit": 5}, "LIT006": {"limit": 10}} assert gate.over_ceiling({"LIT001": 6, "LIT006": 10}, budget) == frozenset({"LIT001"}) -def test_evaluate_blames_only_a_rule_over_cap_and_over_base(): - budget = _budget(10, 0) # cap 10 - # over cap and grown vs base -> breach +def test_evaluate_blames_only_a_rule_over_limit_and_over_base(): + budget = _budget(10) + # over limit and grown vs base -> breach assert [b.rule for b in gate.evaluate({"LIT006": 12}, {"LIT006": 9}, budget)] == ["LIT006"] - # over cap but flat vs base (pre-existing drift) -> not blamed + # over limit but flat vs base (pre-existing drift) -> not blamed assert gate.evaluate({"LIT006": 12}, {"LIT006": 12}, budget) == [] - # within cap -> not blamed regardless of base + # within limit -> not blamed regardless of base assert gate.evaluate({"LIT006": 10}, {"LIT006": 0}, budget) == [] + + +def test_update_ratchets_limit_down_by_what_the_branch_fixed_never_up(): + budget = {"LIT001": {"limit": 100}, "LIT006": {"limit": 10}} + # LIT001 fixed 15 (60 -> 45) so its limit falls 100 -> 85; LIT006 grew, so its + # limit holds flat at 10. + current = {"LIT001": 45, "LIT006": 12} + base = {"LIT001": 60, "LIT006": 9} + assert gate.ratcheted_budget(budget, current, base) == { + "LIT001": {"limit": 85}, + "LIT006": {"limit": 10}, + } diff --git a/type-discipline-budget.json b/type-discipline-budget.json index a6588ac89aa..aa16b30b215 100644 --- a/type-discipline-budget.json +++ b/type-discipline-budget.json @@ -1,34 +1,26 @@ { "LIT001": { - "baseline": 21452, - "slack": 2000 + "limit": 23452 }, "LIT002": { - "baseline": 25022, - "slack": 2500 + "limit": 27522 }, "LIT003": { - "baseline": 397, - "slack": 25 + "limit": 422 }, "LIT004": { - "baseline": 2515, - "slack": 50 + "limit": 2565 }, "LIT005": { - "baseline": 0, - "slack": 0 + "limit": 0 }, "LIT006": { - "baseline": 1013, - "slack": 100 + "limit": 1113 }, "LIT007": { - "baseline": 0, - "slack": 0 + "limit": 0 }, "LIT008": { - "baseline": 914, - "slack": 90 + "limit": 1004 } } From 3e0bd71ee933957610bd6faeda4e800420f5e8ed Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Wed, 1 Jul 2026 10:25:32 -0700 Subject: [PATCH 55/79] feat(ui): disclaim that the Update API Key modal only rotates api_key (#31805) * feat(ui): disclaim that the Update API Key modal only rotates api_key An adversarial review of the credential-rotation work noted the modal always writes litellm_params.api_key, so models that authenticate with an Azure AD token, AWS credentials, or a Vertex service-account JSON are not rotated by it. Adds a warning Alert to the modal so users are not misled into thinking those secrets were rotated; broadening the modal to those providers is a follow-up * Update ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * style(ui): prettier-format the credential modal --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --- .../src/components/update_model_credentials_modal.tsx | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx b/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx index 238207a4aa8..b98f0ec3242 100644 --- a/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx +++ b/ui/litellm-dashboard/src/components/update_model_credentials_modal.tsx @@ -1,4 +1,4 @@ -import { Button, Form, Input, Modal, Typography } from "antd"; +import { Alert, Button, Form, Input, Modal, Typography } from "antd"; import { useState } from "react"; import { modelPatchUpdateCall } from "./networking"; import NotificationsManager from "./molecules/notifications_manager"; @@ -56,8 +56,15 @@ export default function UpdateModelCredentialsModal({ return ( - Rotate this model's API key. Only the new key is sent; the rest of the deployment is left untouched. + Update this model's API key. Only the new key is sent; the rest of the deployment configuration is left + untouched. +
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openai + +client = openai.OpenAI( + api_key="${_||"YOUR_LITELLM_API_KEY"}", + base_url="${k}" +)`;switch(f){case a.CHAT:{let e=Object.keys(j).length>0,r="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();r=`, + extra_body=${e}`}let o=C.length>0?C:[{role:"user",content:w}];t=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${z}", + messages=${JSON.stringify(o,null,4)}${r} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${z}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${S}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${r} +# ) +# print(response_with_file) +`;break}case a.RESPONSES:{let e=Object.keys(j).length>0,r="";if(e){let e=JSON.stringify({metadata:j},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();r=`, + extra_body=${e}`}let o=C.length>0?C:[{role:"user",content:w}];t=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${z}", + input=${JSON.stringify(o,null,4)}${r} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${z}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${S}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${r} +# ) +# print(response_with_file.output_text) +`;break}case a.IMAGE:t="azure"===v?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${z}", + prompt="${n}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${S}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${z}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case a.IMAGE_EDITS:t="azure"===v?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${S}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${z}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${S}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${z}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case a.EMBEDDINGS:t=` +response = client.embeddings.create( + input="${n||"Your string here"}", + model="${z}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case a.TRANSCRIPTION:t=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${z}", + file=audio_file${n?`, + prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case a.SPEECH:t=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${z}", + input="${n||"Your text to convert to speech here"}", + voice="${g}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + +# Save the audio to a file 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openai + +client = openai.OpenAI( + api_key="${_||"YOUR_LITELLM_API_KEY"}", + base_url="${$}" +)`;switch(f){case r.CHAT:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`, + extra_body=${e}`}let o=A.length>0?A:[{role:"user",content:I}];t=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${S}", + messages=${JSON.stringify(o,null,4)}${i} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${S}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${C}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${i} +# ) +# print(response_with_file) +`;break}case r.RESPONSES:{let e=Object.keys(w).length>0,i="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();i=`, + extra_body=${e}`}let o=A.length>0?A:[{role:"user",content:I}];t=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${S}", + input=${JSON.stringify(o,null,4)}${i} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${S}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${C}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${i} +# ) +# print(response_with_file.output_text) +`;break}case r.IMAGE:t="azure"===v?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${S}", + prompt="${n}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${C}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${S}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case r.IMAGE_EDITS:t="azure"===v?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${C}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${S}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${C}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${S}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case r.EMBEDDINGS:t=` +response = client.embeddings.create( + input="${n||"Your string here"}", + model="${S}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case r.TRANSCRIPTION:t=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${S}", + file=audio_file${n?`, + prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case r.SPEECH:t=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${S}", + input="${n||"Your text to convert to speech here"}", + voice="${h}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + +# Save the audio to a file 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os.environ/AWS_SECRET_ACCESS_KEY + +litellm_settings: + callbacks: ["datadog"] # logs llm success + failure logs on datadog + service_callback: ["datadog"] # logs redis, postgres failures on datadog + +general_settings: + store_prompts_in_spend_logs: true diff --git a/litellm/proxy/_new_secret_config.yaml b/litellm/proxy/_new_secret_config.yaml new file mode 100644 index 00000000000..703fe6adc41 --- /dev/null +++ b/litellm/proxy/_new_secret_config.yaml @@ -0,0 +1,83 @@ +# model_list: +# - model_name: claude-sonnet-4-6 +# litellm_params: {model: anthropic/claude-sonnet-4-6} +# model_info: +# litellm_routing_preferences: +# quality_tier: 1 +# keywords: [tin] +# - model_name: gpt-4o-mini +# litellm_params: {model: openai/gpt-4o-mini} +# model_info: +# litellm_routing_preferences: +# quality_tier: 1 +# keywords: [] +# - model_name: gpt-4o +# litellm_params: {model: openai/gpt-4o} +# model_info: +# litellm_routing_preferences: +# quality_tier: 2 +# keywords: [vision, function_calling] +# - model_name: opus +# litellm_params: {model: anthropic/claude-opus-4-7} +# model_info: +# litellm_routing_preferences: +# quality_tier: 3 +# keywords: ["architecture", "design"] +# - model_name: my-quality-router +# litellm_params: +# model: auto_router/adaptive_router +# adaptive_router_default_model: gpt-4o-mini +# adaptive_router_config: +# available_models: [gpt-4o-mini, gpt-4o, opus, claude-sonnet-4-6] +# Example proxy config for the adaptive router (v0). +# +# Wires one logical router ("smart-cheap-router") that adaptively picks between +# two real deployments ("fast" and "smart") based on per-session feedback signals. +# +# How to use from a client: +# POST /v1/chat/completions { "model": "smart-cheap-router", ... } +# Add { "metadata": { "litellm_session_id": "" } } to enable +# sticky-session routing within a conversation. +# +# Required env vars: OPENAI_API_KEY, DATABASE_URL. + +model_list: + # ---- The adaptive router "control" deployment ------------------------- + # `model_name` is what clients call. `available_models` lists the underlying + # deployments the router is allowed to pick from (must match other model_name + # entries in this list). + - model_name: smart-cheap-router + litellm_params: + model: auto_router/adaptive_router + adaptive_router_config: + available_models: ["fast", "smart"] + weights: + quality: 0.7 + cost: 0.3 + + # ---- Underlying deployments the router picks from --------------------- + - model_name: fast + litellm_params: + model: anthropic/claude-sonnet-4-6 + api_key: os.environ/ANTHROPIC_API_KEY + input_cost_per_token: 0.00000015 + model_info: + adaptive_router_preferences: + quality_tier: 2 + strengths: [] + + - model_name: smart + litellm_params: + model: anthropic/claude-opus-4-7 + api_key: os.environ/ANTHROPIC_API_KEY + input_cost_per_token: 0.0000050 + model_info: + adaptive_router_preferences: + quality_tier: 3 + strengths: ["code_generation", "technical_design", "analytical_reasoning"] + +litellm_settings: + drop_params: True + +general_settings: + master_key: sk-1234 # REPLACE in production diff --git a/litellm/proxy/_super_secret_config.yaml b/litellm/proxy/_super_secret_config.yaml new file mode 100644 index 00000000000..b993b9cdfef --- /dev/null +++ b/litellm/proxy/_super_secret_config.yaml @@ -0,0 +1,110 @@ +model_list: +- model_name: claude-3-5-sonnet + litellm_params: + model: claude-3-haiku-20240307 +# - model_name: gemini-1.5-flash-gemini +# litellm_params: +# model: vertex_ai_beta/gemini-1.5-flash +# api_base: https://gateway.ai.cloudflare.com/v1/fa4cdcab1f32b95ca3b53fd36043d691/test/google-vertex-ai/v1/projects/adroit-crow-413218/locations/us-central1/publishers/google/models/gemini-1.5-flash +- litellm_params: + api_base: http://0.0.0.0:8080 + api_key: '' + model: gpt-4o + rpm: 800 + input_cost_per_token: 300 + model_name: gpt-4o +- model_name: llama3-70b-8192 + litellm_params: + model: groq/llama3-70b-8192 +- model_name: fake-openai-endpoint + litellm_params: + model: predibase/llama-3-8b-instruct + api_key: os.environ/PREDIBASE_API_KEY + tenant_id: os.environ/PREDIBASE_TENANT_ID + max_new_tokens: 256 +# - litellm_params: +# api_base: https://my-endpoint-europe-berri-992.openai.azure.com/ +# api_key: os.environ/AZURE_EUROPE_API_KEY +# model: azure/gpt-35-turbo +# rpm: 10 +# model_name: gpt-3.5-turbo-fake-model +- litellm_params: + api_base: https://openai-gpt-4-test-v-1.openai.azure.com + api_key: os.environ/AZURE_API_KEY + api_version: 2024-02-15-preview + model: azure/chatgpt-v-2 + tpm: 100 + model_name: gpt-3.5-turbo +- litellm_params: + model: anthropic.claude-3-sonnet-20240229-v1:0 + model_name: bedrock-anthropic-claude-3 +- litellm_params: + model: claude-3-haiku-20240307 + model_name: anthropic-claude-3 +- litellm_params: + api_base: https://openai-gpt-4-test-v-1.openai.azure.com/ + api_key: os.environ/AZURE_API_KEY + api_version: 2024-02-15-preview + model: azure/chatgpt-v-2 + drop_params: True + tpm: 100 + model_name: gpt-3.5-turbo +- model_name: tts + litellm_params: + model: openai/tts-1 +- model_name: gpt-4-turbo-preview + litellm_params: + api_base: https://openai-france-1234.openai.azure.com + api_key: os.environ/AZURE_FRANCE_API_KEY + api_version: 2024-02-15-preview + model: azure/gpt-turbo +- model_name: text-embedding + litellm_params: + model: textembedding-gecko-multilingual@001 + vertex_project: my-project-9d5c + vertex_location: us-central1 +- model_name: lbl/command-r-plus + litellm_params: + model: openai/lbl/command-r-plus + api_key: "os.environ/VLLM_API_KEY" + api_base: http://vllm-command:8000/v1 + rpm: 1000 + input_cost_per_token: 0 + output_cost_per_token: 0 + model_info: + max_input_tokens: 80920 + +# litellm_settings: +# callbacks: ["dynamic_rate_limiter"] +# # success_callback: ["langfuse"] +# # failure_callback: ["langfuse"] +# # default_team_settings: +# # - team_id: proj1 +# # success_callback: ["langfuse"] +# # langfuse_public_key: os.environ/LANGFUSE_PUBLIC_KEY +# # langfuse_secret: os.environ/LANGFUSE_SECRET +# # langfuse_host: https://us.cloud.langfuse.com +# # - team_id: proj2 +# # success_callback: ["langfuse"] +# # langfuse_public_key: os.environ/LANGFUSE_PUBLIC_KEY +# # langfuse_secret: os.environ/LANGFUSE_SECRET +# # langfuse_host: https://us.cloud.langfuse.com + +assistant_settings: + custom_llm_provider: openai + litellm_params: + api_key: os.environ/OPENAI_API_KEY + + +router_settings: + enable_pre_call_checks: true + + +litellm_settings: + callbacks: ["s3"] + +# general_settings: +# # alerting: ["slack"] +# enable_jwt_auth: True +# litellm_jwtauth: +# team_id_jwt_field: "client_id" \ No newline at end of file diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 6d64843fab0..c85faeba1a6 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -1438,31 +1438,6 @@ def _get_cors_config( origins, allow_cors_credentials = _get_cors_config() -def _restructure_ui_html_files(ui_root: str) -> None: - """Ensure each exported HTML route is available as /index.html.""" - - for current_root, _, files in os.walk(ui_root): - rel_root = os.path.relpath(current_root, ui_root) - first_segment = "" if rel_root == "." else rel_root.split(os.sep)[0] - - if first_segment in {"_next", "litellm-asset-prefix"}: - continue - - for filename in files: - if not filename.endswith(".html") or filename == "index.html": - continue - - file_path = os.path.join(current_root, filename) - target_dir = os.path.splitext(file_path)[0] - target_path = os.path.join(target_dir, "index.html") - - os.makedirs(target_dir, exist_ok=True) - try: - os.replace(file_path, target_path) - except FileNotFoundError: - continue - - # get current directory try: current_dir = os.path.dirname(os.path.abspath(__file__)) @@ -1697,17 +1672,43 @@ try: # # Mount the _next directory at the root level app.mount( "/_next", - StaticFiles(directory=os.path.join(ui_path, "_next"), check_dir=False), + StaticFiles(directory=os.path.join(ui_path, "_next")), name="next_static", ) app.mount( f"{litellm_asset_prefix}/_next", - StaticFiles(directory=os.path.join(ui_path, "_next"), check_dir=False), + StaticFiles(directory=os.path.join(ui_path, "_next")), name="next_static", ) # print(f"mounted _next at {server_root_path}/ui/_next") - app.mount("/ui", StaticFiles(directory=ui_path, html=True, check_dir=False), name="ui") + app.mount("/ui", StaticFiles(directory=ui_path, html=True), name="ui") + + def _restructure_ui_html_files(ui_root: str) -> None: + """Ensure each exported HTML route is available as /index.html.""" + + for current_root, _, files in os.walk(ui_root): + rel_root = os.path.relpath(current_root, ui_root) + first_segment = "" if rel_root == "." else rel_root.split(os.sep)[0] + + # Ignore Next.js asset directories + if first_segment in {"_next", "litellm-asset-prefix"}: + continue + + for filename in files: + if not filename.endswith(".html") or filename == "index.html": + continue + + file_path = os.path.join(current_root, filename) + target_dir = os.path.splitext(file_path)[0] + target_path = os.path.join(target_dir, "index.html") + + os.makedirs(target_dir, exist_ok=True) + try: + os.replace(file_path, target_path) + except FileNotFoundError: + # Another process may have already moved this file. + continue # Handle HTML file restructuring # Only restructure if: @@ -13636,9 +13637,7 @@ async def get_favicon(): ) current_dir = os.path.dirname(os.path.abspath(__file__)) - built_favicon = os.path.join(current_dir, "_experimental", "out", "favicon.ico") - bundled_favicon = os.path.join(current_dir, "swagger", "favicon.ico") - default_favicon = built_favicon if os.path.exists(built_favicon) else bundled_favicon + default_favicon = os.path.join(current_dir, "_experimental", "out", "favicon.ico") favicon_url = os.getenv("LITELLM_FAVICON_URL", "") diff --git a/tests/proxy_admin_ui_tests/test-results/.last-run.json b/tests/proxy_admin_ui_tests/test-results/.last-run.json new file mode 100644 index 00000000000..cbcc1fbac11 --- /dev/null +++ b/tests/proxy_admin_ui_tests/test-results/.last-run.json @@ -0,0 +1,4 @@ +{ + "status": "passed", + "failedTests": [] +} \ No newline at end of file diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 0d6cd972459..68122bbba3b 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -604,17 +604,9 @@ def test_ui_extensionless_route_requires_restructure(tmp_path): assert "login" in response.text -def test_admin_ui_export_serves_nested_extensionless_routes(tmp_path): - from litellm.proxy import proxy_server - - out_dir = tmp_path / "out" - (out_dir / "_next").mkdir(parents=True) - (out_dir / "index.html").write_text("home") - callback_src = out_dir / "mcp" / "oauth" / "callback.html" - callback_src.parent.mkdir(parents=True) - callback_src.write_text("callback") - - proxy_server._restructure_ui_html_files(str(out_dir)) +def test_admin_ui_export_serves_nested_extensionless_routes(): + out_dir = Path(litellm.__file__).parent / "proxy" / "_experimental" / "out" + assert out_dir.is_dir(), f"missing UI export at {out_dir}" nested_html_offenders = [ path.relative_to(out_dir).as_posix() diff --git a/ui/litellm-dashboard/build_ui.sh b/ui/litellm-dashboard/build_ui.sh index b59301233ec..aa346c12edc 100755 --- a/ui/litellm-dashboard/build_ui.sh +++ b/ui/litellm-dashboard/build_ui.sh @@ -49,8 +49,7 @@ if [ $? -eq 0 ]; then # Specify the destination directory destination_dir="../../litellm/proxy/_experimental/out" - # Ensure the destination directory exists, then clear it - mkdir -p "$destination_dir" + # Remove existing files in the destination directory rm -rf "$destination_dir"/* # Copy the contents of the output directory to the specified destination diff --git a/ui/litellm-dashboard/build_ui_custom_path.sh b/ui/litellm-dashboard/build_ui_custom_path.sh index 93d8c080b76..a92927f8ea7 100755 --- a/ui/litellm-dashboard/build_ui_custom_path.sh +++ b/ui/litellm-dashboard/build_ui_custom_path.sh @@ -55,8 +55,7 @@ if [ $? -eq 0 ]; then # Specify the destination directory destination_dir="../../litellm/proxy/_experimental/out" - # Ensure the destination directory exists, then clear it - mkdir -p "$destination_dir" + # Remove existing files in the destination directory rm -rf "$destination_dir"/* # Copy the contents of the output directory to the specified destination From ae6dbb4a9bc744412ef4ab2f3e65c8bee51c9846 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Wed, 1 Jul 2026 14:09:07 -0700 Subject: [PATCH 57/79] fix(scripts): resolve worktree root before relative_to in type_check_gate (#31906) On macOS, tempfile.mkdtemp returns a path under /var/folders, a symlink to /private/var. The base pass in type_check_gate.py resolved each diagnostic path (yielding /private/var/...) but not the worktree root, so relative_to raised ValueError for every diagnostic, base counts came back empty, and the vacuous-run guard failed every local make lint-basedpyright run. type_discipline_gate.py already resolves root the same way; ruff_strict_gate.py counts rule codes without touching worktree paths, so it is unaffected. CI runs Linux where the temp dir is not a symlink, which is why this only bit local macOS runs --- scripts/type_check_gate.py | 2 +- tests/test_litellm/test_type_check_gate.py | 15 +++++++++++++++ 2 files changed, 16 insertions(+), 1 deletion(-) diff --git a/scripts/type_check_gate.py b/scripts/type_check_gate.py index 256fc433d8d..d3837cc2c0d 100644 --- a/scripts/type_check_gate.py +++ b/scripts/type_check_gate.py @@ -63,7 +63,7 @@ def _to_relative(raw: str, root: Path) -> str | None: path = Path(raw) absolute = path if path.is_absolute() else root / path try: - return absolute.resolve().relative_to(root).as_posix() + return absolute.resolve().relative_to(root.resolve()).as_posix() except ValueError: return None diff --git a/tests/test_litellm/test_type_check_gate.py b/tests/test_litellm/test_type_check_gate.py index 3faf46c87de..e602bf6e66f 100644 --- a/tests/test_litellm/test_type_check_gate.py +++ b/tests/test_litellm/test_type_check_gate.py @@ -54,6 +54,21 @@ def test_paths_outside_repo_are_skipped(): assert gate.count_basedpyright(payload) == {} +def test_symlinked_root_keeps_diagnostics_in_tree(tmp_path): + real = tmp_path / "real" + real.mkdir() + link = tmp_path / "link" + link.symlink_to(real) + payload = json.dumps( + { + "generalDiagnostics": [ + _bpr(link / "litellm" / "x.py", "error", "reportArgumentType") + ] + } + ) + assert gate.count_basedpyright(payload, root=link) == {"reportArgumentType": 1} + + def test_at_or_under_ceiling_passes(): budget = {"no-any-return": {"limit": 5}} assert gate.evaluate({"no-any-return": 5}, {}, budget) == [] From 7e993446d8c4abd7b3ad2c289529f279ce0db863 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Wed, 1 Jul 2026 15:44:30 -0700 Subject: [PATCH 58/79] feat(bedrock_mantle): add xai.grok-4.3 to model cost map for SigV4 auth (#31916) Register bedrock_mantle/xai.grok-4.3 with /v1/responses in supported_endpoints so the data-driven gate routes it through BedrockMantleResponsesAPIConfig (which inherits SigV4 signing via BedrockMantleAuthMixin). Without this entry the model falls through to None and forces bearer-token-only auth. Pricing sourced from AWS Bedrock pricing page. Closes #31196 Co-authored-by: unknown <> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- ...odel_prices_and_context_window_backup.json | 20 +++++++++++++++++++ model_prices_and_context_window.json | 20 +++++++++++++++++++ ...bedrock_mantle_responses_transformation.py | 10 ++++++++++ 3 files changed, 50 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b16e1015255..8dfd3d0036a 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -42887,6 +42887,26 @@ "supports_tool_choice": true, "supports_vision": true }, + "bedrock_mantle/xai.grok-4.3": { + "input_cost_per_token": 1.25e-06, + "output_cost_per_token": 2.5e-06, + "cache_read_input_token_cost": 2e-07, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 131072, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "volcengine/doubao-seed-2-0-pro-260215": { "litellm_provider": "volcengine", "max_input_tokens": 256000, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 3e4c5b947a1..6ab6f1bda46 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -43122,6 +43122,26 @@ "supports_tool_choice": true, "supports_vision": true }, + "bedrock_mantle/xai.grok-4.3": { + "input_cost_per_token": 1.25e-06, + "output_cost_per_token": 2.5e-06, + "cache_read_input_token_cost": 2e-07, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 131072, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "source": "https://aws.amazon.com/bedrock/pricing/" + }, "volcengine/doubao-seed-2-0-pro-260215": { "litellm_provider": "volcengine", "max_input_tokens": 256000, diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py index 94efc7c51ef..aafaf401700 100644 --- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py +++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py @@ -452,6 +452,16 @@ class TestBedrockMantleResponsesRegistry: assert isinstance(cfg, BedrockMantleResponsesAPIConfig) assert cfg.use_openai_path is True + def test_registry_returns_native_config_for_xai_grok(self, local_cost_map): + from litellm.utils import ProviderConfigManager + + cfg = ProviderConfigManager.get_provider_responses_api_config( + provider="bedrock_mantle", + model="xai.grok-4.3", + ) + assert isinstance(cfg, BedrockMantleResponsesAPIConfig) + assert cfg.use_openai_path is False + def test_unmapped_frontier_model_falls_through_to_none(self, restore_model_cost): # The gate is data-driven, not name-based: an unseen model not yet in the # price map (e.g. a future gpt-6) has no capability signal, so it falls From 700afbb6b23dffd00c04f69b0e1ce59362ad8f11 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 16:26:38 -0700 Subject: [PATCH 59/79] chore: make CLAUDE.md rules more concise (#31892) --- CLAUDE.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 86bd89156a3..a492aabd02d 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -33,9 +33,9 @@ If you ever make public-facing PR descriptions, comments, issues, commit message Don't hesitate to use values in .env to get needed API keys and other secrets, as long as you never add them to conversation history, commit them, or include them in GitHub issues / PRs -Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed. For `make pre-commit` to work properly you must stage your changes first (git add): it reports CI red or green based on what would happen if you committed your staged changes, but it runs the linters over the working tree, so any unstaged edits to tracked files or untracked files are folded into the result and will skew it away from what CI (which only sees your commit) would report +Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed. It only runs when there are staged frontend and/or backend changes and calculates violations, generates types, etc. based on the worktree, so stage what you need or stash/delete unwanted files in litellm/ or ui/ (where backend and frontend lint run, respectively) before running it. If it fails because dashboard api types are stale, it already regenerated them for you. You just need to stage the schema.d.ts, re-run `make pre-commit` to confirm it passes, and commit -When you fix violations gated by `ruff-strict-budget.json`, `type-discipline-budget.json`, or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered limits so the ceilings ratchet down instead of leaving stale headroom. It lowers each rule's limit by the number of violations this branch cleared since its branch point and never raises one, measured against the working tree, so stage exactly the fixes you're committing before running it; crediting unstaged fixes you won't commit would over-tighten the limits and turn CI red once the committed subset is checked +When you fix violations gated by `ruff-strict-budget.json`, `type-discipline-budget.json`, or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered limits so the ceilings ratchet down instead of leaving stale headroom. It measures the working tree, so it must contain exactly the fixes you're committing If you're trying to create a new function that relies on untyped stuff, instead of adding more Any's and pushing `reportAny` / `reportExplicitAny` closer to their basedpyright ceilings, just validate it in the caller with Pydantic (a model or `TypeAdapter` that returns the typed thing or raises will do) and then pass the now typed variable in From a2f5bb1868ad68619f2cf2f858203ebe6c51dc1d Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Wed, 1 Jul 2026 17:05:49 -0700 Subject: [PATCH 60/79] fix(proxy): authorize /health/test_connection against loaded deployment's team_id (VERIA-441) (#31767) * fix(proxy): authorize /health/test_connection against loaded deployment's team_id (VERIA-441) POST /health/test_connection looked up a deployment by request-supplied model_info.id, dumped its litellm_params (including api_key) into the outbound probe, merged request params over it, and then authorized the call against the caller-supplied model_info.team_id. A team admin could pass another team's deployment id together with their own team_id and an attacker-controlled api_base, sending the victim team's provider key to that URL. Capture the loaded deployment's model_info alongside its litellm_params in both the id-lookup and the model_name fallback paths, and pass that captured value to can_user_make_model_call. When no deployment is loaded (caller is probing fresh, request-supplied credentials), keep using the request body's model_info; no foreign deployment is in scope and the existing role check still requires admin or team-admin. Add two regression tests that wrap (not mock) ModelManagementAuthChecks.can_user_make_model_call, one per resolution path, asserting HTTP 403 and that the auth check was reached with the loaded deployment's team_id. Both fail on the pre-fix code. * test(health): add positive-path regression through real auth (VERIA-441) The two deny tests already exercise the real (wrapped) ModelManagementAuthChecks. Add a matching positive-path test so a mutation that swaps the auth team_id for a deny-all value on the legit path also fails: loaded deployment owned by team-X, caller admin of team-X -> asserts HTTP 200 and that the auth check ran with the LOADED deployment's team_id. * refactor(test): rename health endpoint tests for clarity (VERIA-441) Rename test functions and variables from attacker/victim/owner framing to neutral team-a/team-b terminology. Update docstrings to remove exploit-specific language. Tests remain functionally identical, covering deny paths (cross-team deployments) and the positive path (same-team deployments). --- .../health_endpoints/_health_endpoints.py | 6 +- .../health_endpoints/test_health_endpoints.py | 303 ++++++++++++++++++ 2 files changed, 308 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index c20991b8d43..2b3ec231ac8 100644 --- a/litellm/proxy/health_endpoints/_health_endpoints.py +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -1807,6 +1807,7 @@ async def test_model_connection( # Look up model configuration from router if model name is provided # This gets the litellm_params from proxy config (with resolved env vars) config_litellm_params: dict = {} + loaded_model_info: Optional[dict] = None if llm_router is not None: # Prefer disambiguation by deployment id (`model_info.id`) when # the caller supplies it. This is required when multiple @@ -1825,6 +1826,7 @@ async def test_model_connection( if deployment_by_id is not None: config_litellm_params = deployment_by_id.litellm_params.model_dump(exclude_none=True) + loaded_model_info = deployment_by_id.model_info.model_dump(exclude_none=True) elif model_name: # Fall back to model_name lookup for callers (e.g. the # "Add Model" wizard, or curl) that don't supply an id. @@ -1846,6 +1848,7 @@ async def test_model_connection( # config. These already have resolved environment # variables from proxy config. config_litellm_params = dict(deployments[0].get("litellm_params", {})) + loaded_model_info = dict(deployments[0].get("model_info") or {}) except Exception as e: verbose_proxy_logger.debug( f"Could not find model {model_name} in router: {e}. Proceeding with request params only." @@ -1856,11 +1859,12 @@ async def test_model_connection( litellm_params = {**config_litellm_params, **request_litellm_params} ## Auth check + auth_model_info = loaded_model_info if loaded_model_info is not None else model_info await ModelManagementAuthChecks.can_user_make_model_call( model_params=Deployment( model_name="test_model", litellm_params=LiteLLM_Params(**litellm_params), - model_info=model_info, + model_info=auth_model_info, ), user_api_key_dict=user_api_key_dict, prisma_client=prisma_client, diff --git a/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py b/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py index a04ad5598df..917bedcb93f 100644 --- a/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py +++ b/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py @@ -696,6 +696,309 @@ async def test_test_model_connection_falls_back_to_deployments_zero_without_id() assert model_params.get("api_key") == "fake-key-A" +@pytest.mark.asyncio +async def test_test_model_connection_uses_loaded_deployment_team_id(): + """ + /health/test_connection must authorize using the team_id of the + deployment it actually loaded (by model_info.id), not the team_id + supplied in the request body. Requesting team A's deployment while + authenticated as an admin of team B must be denied. + """ + from fastapi import HTTPException + + from litellm.proxy._types import LiteLLM_TeamTable + from litellm.proxy.management_endpoints.model_management_endpoints import ( + ModelManagementAuthChecks, + ) + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + mock_request = MagicMock() + + requester_team_id = "team-b" + deployment_owner_team_id = "team-a" + deployment_id = "team-a-deployment-id" + + requester_user_api_key_dict = UserAPIKeyAuth( + token="requester-token", + user_id="team-b-admin-user", + team_id=requester_team_id, + user_role=LitellmUserRoles.INTERNAL_USER, + ) + + mock_prisma_client = MagicMock() + + other_team_deployment = Deployment( + model_name="team-a-model", + litellm_params=LiteLLM_Params( + model="openai/gpt-4o", + api_base="https://team-a-api.invalid/v1", + api_key="TEAM-A-API-KEY", + ), + model_info=ModelInfo(id=deployment_id, team_id=deployment_owner_team_id), + ) + + mock_router = MagicMock() + mock_router.get_deployment.return_value = other_team_deployment + + async def fake_find_unique(*, where): + team_id = where["team_id"] + if team_id == requester_team_id: + return SimpleNamespace( + model_dump=lambda: LiteLLM_TeamTable( + team_id=requester_team_id, + members_with_roles=[ + { + "user_id": "team-b-admin-user", + "role": "admin", + } + ], + ).model_dump() + ) + if team_id == deployment_owner_team_id: + return SimpleNamespace( + model_dump=lambda: LiteLLM_TeamTable( + team_id=deployment_owner_team_id, + members_with_roles=[], + ).model_dump() + ) + return None + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client), + patch("litellm.proxy.proxy_server.llm_router", mock_router), + patch("litellm.proxy.proxy_server.premium_user", True), + patch.object( + ModelManagementAuthChecks, + "can_user_make_model_call", + wraps=ModelManagementAuthChecks.can_user_make_model_call, + ) as spy_auth_check, + patch( + "litellm.proxy.management_endpoints.model_management_endpoints.TeamRepository" + ) as MockTeamRepo, + ): + mock_team_repo_instance = MagicMock() + mock_team_repo_instance.table.find_unique = AsyncMock( + side_effect=fake_find_unique + ) + MockTeamRepo.return_value = mock_team_repo_instance + + with pytest.raises(HTTPException) as exc_info: + await health_test_model_connection( + request=mock_request, + mode="chat", + litellm_params={ + "model": "openai/gpt-4o", + "api_base": "https://swapped-base.invalid/v1", + }, + model_info={ + "id": deployment_id, + "team_id": requester_team_id, + }, + user_api_key_dict=requester_user_api_key_dict, + ) + + assert exc_info.value.status_code == 403 + assert spy_auth_check.called + passed_model_params = spy_auth_check.call_args.kwargs["model_params"] + assert passed_model_params.model_info.team_id == deployment_owner_team_id, ( + "Auth check must run against the loaded deployment's team_id " + f"({deployment_owner_team_id!r}); got " + f"{passed_model_params.model_info.team_id!r}." + ) + + +@pytest.mark.asyncio +async def test_test_model_connection_uses_loaded_deployment_team_id_via_model_name_fallback(): + """ + Companion to the id-lookup case: when the caller provides only a model + name (no `model_info.id`) and that name resolves via the router's + `model_name` fallback to a deployment owned by a different team, the + auth check must still run against the loaded deployment's `team_id`, + not the caller-supplied one in the request body. + """ + from fastapi import HTTPException + + from litellm.proxy._types import LiteLLM_TeamTable + from litellm.proxy.management_endpoints.model_management_endpoints import ( + ModelManagementAuthChecks, + ) + + mock_request = MagicMock() + + requester_team_id = "team-b-2" + deployment_owner_team_id = "team-a-2" + + requester_user_api_key_dict = UserAPIKeyAuth( + token="requester-token-2", + user_id="team-b-admin-user-2", + team_id=requester_team_id, + user_role=LitellmUserRoles.INTERNAL_USER, + ) + + mock_prisma_client = MagicMock() + + other_team_deployment_dict = { + "model_name": "shared-model-name", + "litellm_params": { + "model": "openai/gpt-4o", + "api_base": "https://team-a-api-2.invalid/v1", + "api_key": "TEAM-A-API-KEY-2", + }, + "model_info": { + "id": "team-a-deployment-id-2", + "team_id": deployment_owner_team_id, + }, + } + + mock_router = MagicMock() + mock_router.get_model_list.return_value = [other_team_deployment_dict] + + async def fake_find_unique(*, where): + return SimpleNamespace( + model_dump=lambda: LiteLLM_TeamTable( + team_id=where["team_id"], + members_with_roles=( + [{"user_id": "team-b-admin-user-2", "role": "admin"}] + if where["team_id"] == requester_team_id + else [] + ), + ).model_dump() + ) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client), + patch("litellm.proxy.proxy_server.llm_router", mock_router), + patch("litellm.proxy.proxy_server.premium_user", True), + patch.object( + ModelManagementAuthChecks, + "can_user_make_model_call", + wraps=ModelManagementAuthChecks.can_user_make_model_call, + ) as spy_auth_check, + patch( + "litellm.proxy.management_endpoints.model_management_endpoints.TeamRepository" + ) as MockTeamRepo, + ): + mock_team_repo_instance = MagicMock() + mock_team_repo_instance.table.find_unique = AsyncMock( + side_effect=fake_find_unique + ) + MockTeamRepo.return_value = mock_team_repo_instance + + with pytest.raises(HTTPException) as exc_info: + await health_test_model_connection( + request=mock_request, + mode="chat", + litellm_params={ + "model": "shared-model-name", + "api_base": "https://swapped-base-2.invalid/v1", + }, + model_info={"team_id": requester_team_id}, + user_api_key_dict=requester_user_api_key_dict, + ) + + assert exc_info.value.status_code == 403 + + passed_model_params = spy_auth_check.call_args.kwargs["model_params"] + assert passed_model_params.model_info.team_id == deployment_owner_team_id + + +@pytest.mark.asyncio +async def test_test_model_connection_authorized_team_admin_passes_real_auth(): + """ + Positive-path companion to the deny tests above. When the caller is a + genuine admin of the team that owns the loaded deployment, the real + (unmocked) auth check must pass and the endpoint must reach the outbound + health probe. Guards against a regression that swaps the auth `team_id` + for something deny-all on the legit path. + """ + from litellm.proxy._types import LiteLLM_TeamTable + from litellm.proxy.management_endpoints.model_management_endpoints import ( + ModelManagementAuthChecks, + ) + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + mock_request = MagicMock() + + owner_team_id = "team-owner" + owner_admin_user_id = "team-owner-admin" + owned_deployment_id = "owned-deployment-id" + + owner_admin_api_key_dict = UserAPIKeyAuth( + token="owner-admin-token", + user_id=owner_admin_user_id, + team_id=owner_team_id, + user_role=LitellmUserRoles.INTERNAL_USER, + ) + + mock_prisma_client = MagicMock() + + owned_deployment = Deployment( + model_name="owner-model", + litellm_params=LiteLLM_Params( + model="openai/gpt-4o-mini", + api_base="https://owner-real-api.invalid/v1", + api_key="owner-team-api-key", + ), + model_info=ModelInfo(id=owned_deployment_id, team_id=owner_team_id), + ) + + mock_router = MagicMock() + mock_router.get_deployment.return_value = owned_deployment + + async def fake_find_unique(*, where): + if where["team_id"] == owner_team_id: + return SimpleNamespace( + model_dump=lambda: LiteLLM_TeamTable( + team_id=owner_team_id, + members_with_roles=[ + {"user_id": owner_admin_user_id, "role": "admin"} + ], + ).model_dump() + ) + return None + + health_result = {"status": "healthy", "response_time_ms": 50} + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client), + patch("litellm.proxy.proxy_server.llm_router", mock_router), + patch("litellm.proxy.proxy_server.premium_user", True), + patch.object( + ModelManagementAuthChecks, + "can_user_make_model_call", + wraps=ModelManagementAuthChecks.can_user_make_model_call, + ) as spy_auth_check, + patch( + "litellm.proxy.management_endpoints.model_management_endpoints.TeamRepository" + ) as MockTeamRepo, + patch( + "litellm.proxy.health_endpoints._health_endpoints.litellm.ahealth_check", + AsyncMock(return_value=health_result), + ), + patch( + "litellm.proxy.health_endpoints._health_endpoints.run_with_timeout", + AsyncMock(return_value=health_result), + ), + ): + mock_team_repo_instance = MagicMock() + mock_team_repo_instance.table.find_unique = AsyncMock( + side_effect=fake_find_unique + ) + MockTeamRepo.return_value = mock_team_repo_instance + + result = await health_test_model_connection( + request=mock_request, + mode="chat", + litellm_params={"model": "openai/gpt-4o-mini"}, + model_info={"id": owned_deployment_id, "team_id": owner_team_id}, + user_api_key_dict=owner_admin_api_key_dict, + ) + + assert result["status"] == "success" + passed_model_params = spy_auth_check.call_args.kwargs["model_params"] + assert passed_model_params.model_info.team_id == owner_team_id + + @pytest.mark.asyncio @pytest.mark.parametrize( "status,error_message", From 99c65ea6ddc3b5d4f13b7f7d21ff24a897f4ffa7 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Wed, 1 Jul 2026 17:06:03 -0700 Subject: [PATCH 61/79] fix(proxy): admin-gate `permissions` on /key/update and /key/regenerate (LIT-4092) (#31810) The `_check_permissions_caller_permission` helper introduced in #31469 was only wired into `_common_key_generation_helper`. This change wires it into `_validate_update_key_data` and `regenerate_key_fn` so the three write paths share the admin gate, and refactors the helper to accept the full request model so it can key on `"permissions" in data.model_fields_set` rather than truthiness. The presence check keeps the model-level omit default flowing through unchanged while treating any explicit value (including `{}` / `null`) as an admin-only write. In `regenerate_key_fn` the gate is placed before the `premium_user` license check so the rejection is consistent across premium and non-premium deployments. That ordering is pinned by `test_regenerate_key_non_admin_permissions_rejected_before_enterprise_gate` Tests in tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py: - test_update_key_non_admin_permissions_non_empty_rejected - test_update_key_non_admin_permissions_explicit_empty_rejected - test_update_key_non_admin_permissions_explicit_null_rejected - test_update_key_non_admin_omits_permissions_succeeds (control) - test_update_key_admin_can_set_permissions (control) - test_regenerate_key_non_admin_permissions_rejected - test_regenerate_key_non_admin_permissions_explicit_empty_rejected - test_permissions_explicit_empty_rejected_for_non_admin_on_generate - test_regenerate_key_non_admin_permissions_rejected_before_enterprise_gate Mutation-killed against gate removal on either wire, against reverting the helper to a truthiness check, and against reordering the gate past the enterprise-license check --- .../key_management_endpoints.py | 24 +- .../test_key_management_endpoints.py | 267 ++++++++++++++++++ 2 files changed, 283 insertions(+), 8 deletions(-) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 523cb9b74e5..f0473edded5 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -563,18 +563,18 @@ def _check_allowed_routes_caller_permission( def _check_permissions_caller_permission( - permissions: Optional[dict], + data: GenerateRequestBase, user_api_key_dict: UserAPIKeyAuth, ) -> None: """ - Only proxy admins may set the `permissions` dict on a key. + Require PROXY_ADMIN when `permissions` is present in the request body. - The field grants ambient capabilities (e.g. `get_spend_routes` exposes - `/global/spend/*`), so it must follow the same admin gate as - `allowed_routes`. Without this gate a non-admin can self-grant capabilities - they do not hold, including read access to global spend. + Presence is detected via `data.model_fields_set` so a caller that + omits the field (default flows through) is distinct from one that + sends any explicit value. """ - if not permissions: + permissions_in_request = "permissions" in data.model_fields_set + if not permissions_in_request and not data.permissions: return if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value: return @@ -840,7 +840,7 @@ async def _common_key_generation_helper( team_table=team_table, ) _check_permissions_caller_permission( - permissions=data.permissions, + data=data, user_api_key_dict=user_api_key_dict, ) @@ -2236,6 +2236,10 @@ async def _validate_update_key_data( data=data, user_api_key_dict=user_api_key_dict, ) + _check_permissions_caller_permission( + data=data, + user_api_key_dict=user_api_key_dict, + ) _validate_caller_can_change_key_ownership( data=data, @@ -4552,6 +4556,10 @@ async def regenerate_key_fn( data=data, user_api_key_dict=user_api_key_dict, ) + _check_permissions_caller_permission( + data=data, + user_api_key_dict=user_api_key_dict, + ) # Mirror /key/generate's post-handle_key_type recheck so a # non-admin can't elevate via a key_type preset that the # regenerate flow would otherwise carry through unchecked. diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index ae62be8799f..601fa2c6d78 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -13644,3 +13644,270 @@ async def test_permissions_admin_can_set_any(monkeypatch): team_table=None, ) assert result is not None + + +@pytest.mark.asyncio +async def test_permissions_explicit_empty_rejected_for_non_admin_on_generate(monkeypatch): + """`_common_key_generation_helper` rejects a non-admin when + `permissions` is present in the request body, even as `{}`. Omit-default + stays allowed; that carve-out lives in + `test_permissions_empty_default_allowed_for_non_admin`.""" + monkeypatch.setattr( + "litellm.proxy.management_endpoints.key_management_endpoints.litellm.default_key_generate_params", + None, + raising=False, + ) + caller = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + user_id="user-1", + max_budget=100.0, + ) + request = GenerateKeyRequest(permissions={}) + assert "permissions" in request.model_fields_set + with pytest.raises(HTTPException) as exc_info: + await _common_key_generation_helper( + data=request, + user_api_key_dict=caller, + litellm_changed_by=None, + team_table=None, + ) + assert exc_info.value.status_code == 403 + assert "permissions" in str(exc_info.value.detail) + + +def _make_personal_key_row_for_alice(): + return MagicMock( + token="hashed_alice_personal_key", + user_id="alice", + team_id=None, + created_by="alice", + max_budget=None, + organization_id=None, + project_id=None, + ) + + +def _make_alice_internal_user(): + return UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-alice", + user_id="alice", + ) + + +@pytest.mark.asyncio +async def test_update_key_non_admin_permissions_non_empty_rejected(monkeypatch): + """`_validate_update_key_data` rejects a non-admin when `permissions` + is present in the request body (personal-key fast-path caller).""" + mock_prisma_client = AsyncMock() + mock_prisma_client.jsonify_object = lambda data: data + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + data = UpdateKeyRequest( + key="sk-alice-personal", + permissions={"get_spend_routes": True}, + ) + + with pytest.raises(HTTPException) as exc: + await _validate_update_key_data( + data=data, + existing_key_row=_make_personal_key_row_for_alice(), + user_api_key_dict=_make_alice_internal_user(), + llm_router=None, + premium_user=True, + prisma_client=mock_prisma_client, + user_api_key_cache=MagicMock(), + ) + assert exc.value.status_code == 403 + assert "permissions" in str(exc.value.detail) + + +@pytest.mark.asyncio +async def test_update_key_non_admin_permissions_explicit_empty_rejected(monkeypatch): + """`_validate_update_key_data` rejects a non-admin when `permissions` + is present as `{}` in the request body. The value matches the model + default but `model_fields_set` distinguishes the two.""" + mock_prisma_client = AsyncMock() + mock_prisma_client.jsonify_object = lambda data: data + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + data = UpdateKeyRequest( + key="sk-alice-personal", + permissions={}, + ) + assert "permissions" in data.model_fields_set + + with pytest.raises(HTTPException) as exc: + await _validate_update_key_data( + data=data, + existing_key_row=_make_personal_key_row_for_alice(), + user_api_key_dict=_make_alice_internal_user(), + llm_router=None, + premium_user=True, + prisma_client=mock_prisma_client, + user_api_key_cache=MagicMock(), + ) + assert exc.value.status_code == 403 + assert "permissions" in str(exc.value.detail) + + +@pytest.mark.asyncio +async def test_update_key_non_admin_permissions_explicit_null_rejected(monkeypatch): + """`_validate_update_key_data` rejects a non-admin when `permissions` + is present as `null` in the request body.""" + mock_prisma_client = AsyncMock() + mock_prisma_client.jsonify_object = lambda data: data + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + data = UpdateKeyRequest( + key="sk-alice-personal", + permissions=None, + ) + assert "permissions" in data.model_fields_set + + with pytest.raises(HTTPException) as exc: + await _validate_update_key_data( + data=data, + existing_key_row=_make_personal_key_row_for_alice(), + user_api_key_dict=_make_alice_internal_user(), + llm_router=None, + premium_user=True, + prisma_client=mock_prisma_client, + user_api_key_cache=MagicMock(), + ) + assert exc.value.status_code == 403 + assert "permissions" in str(exc.value.detail) + + +@pytest.mark.asyncio +async def test_update_key_non_admin_omits_permissions_succeeds(monkeypatch): + """`_validate_update_key_data` accepts a non-admin owner when + `permissions` is absent from the request body (personal-key fast path + on an unrelated field).""" + mock_prisma_client = AsyncMock() + mock_prisma_client.jsonify_object = lambda data: data + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + data = UpdateKeyRequest(key="sk-alice-personal", tpm_limit=42) + assert "permissions" not in data.model_fields_set + + await _validate_update_key_data( + data=data, + existing_key_row=_make_personal_key_row_for_alice(), + user_api_key_dict=_make_alice_internal_user(), + llm_router=None, + premium_user=True, + prisma_client=mock_prisma_client, + user_api_key_cache=MagicMock(), + ) + + +@pytest.mark.asyncio +async def test_update_key_admin_can_set_permissions(monkeypatch): + """`_validate_update_key_data` accepts a PROXY_ADMIN caller for every + shape of `permissions` in the request body.""" + mock_prisma_client = AsyncMock() + mock_prisma_client.jsonify_object = lambda data: data + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + admin = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-admin", + user_id="admin-1", + ) + for permissions_value in ({"get_spend_routes": True}, {}, None): + data = UpdateKeyRequest( + key="sk-alice-personal", + permissions=permissions_value, + ) + await _validate_update_key_data( + data=data, + existing_key_row=_make_personal_key_row_for_alice(), + user_api_key_dict=admin, + llm_router=None, + premium_user=True, + prisma_client=mock_prisma_client, + user_api_key_cache=MagicMock(), + ) + + +@pytest.mark.asyncio +async def test_regenerate_key_non_admin_permissions_rejected(monkeypatch): + """`regenerate_key_fn` rejects a non-admin when `permissions` is + present in the request body, before any DB work.""" + from litellm.proxy._types import RegenerateKeyRequest + from litellm.proxy.management_endpoints.key_management_endpoints import ( + regenerate_key_fn, + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + + data = RegenerateKeyRequest( + key="sk-alice-personal", + permissions={"get_spend_routes": True}, + ) + + with pytest.raises(ProxyException) as exc: + await regenerate_key_fn( + key=None, + data=data, + user_api_key_dict=_make_alice_internal_user(), + litellm_changed_by=None, + ) + assert int(exc.value.code) == 403 + assert "permissions" in str(exc.value.message) + + +@pytest.mark.asyncio +async def test_regenerate_key_non_admin_permissions_explicit_empty_rejected(monkeypatch): + """`regenerate_key_fn` rejects a non-admin when `permissions` is + present as `{}` in the request body.""" + from litellm.proxy._types import RegenerateKeyRequest + from litellm.proxy.management_endpoints.key_management_endpoints import ( + regenerate_key_fn, + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + + data = RegenerateKeyRequest(key="sk-alice-personal", permissions={}) + assert "permissions" in data.model_fields_set + + with pytest.raises(ProxyException) as exc: + await regenerate_key_fn( + key=None, + data=data, + user_api_key_dict=_make_alice_internal_user(), + litellm_changed_by=None, + ) + assert int(exc.value.code) == 403 + assert "permissions" in str(exc.value.message) + + +@pytest.mark.asyncio +async def test_regenerate_key_non_admin_permissions_rejected_before_enterprise_gate(monkeypatch): + """`regenerate_key_fn` runs `_check_permissions_caller_permission` + before the `premium_user` check, so a non-premium proxy still returns + the permissions rejection (403) rather than the enterprise-license + error (500) when a non-admin sends `permissions`.""" + from litellm.proxy._types import RegenerateKeyRequest + from litellm.proxy.management_endpoints.key_management_endpoints import ( + regenerate_key_fn, + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False) + + data = RegenerateKeyRequest( + key="sk-alice-personal", + permissions={"get_spend_routes": True}, + ) + + with pytest.raises(ProxyException) as exc: + await regenerate_key_fn( + key=None, + data=data, + user_api_key_dict=_make_alice_internal_user(), + litellm_changed_by=None, + ) + assert int(exc.value.code) == 403 + assert "permissions" in str(exc.value.message) + assert "Enterprise" not in str(exc.value.message) From 0b0fd6a4d1d1e743e29523f400bc1106d6782354 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 17:16:21 -0700 Subject: [PATCH 62/79] feat(github_copilot): route /v1/messages to Copilot native Anthropic endpoint (#31802) * feat(github_copilot): route /v1/messages to Copilot native Anthropic endpoint Add a GitHub Copilot Anthropic Messages transformation that routes supported Claude models through the native /v1/messages endpoint. This covers request URL construction, default headers, and supported model metadata. * fix(github_copilot): address PR review feedback Tighten the Anthropic Messages environment validation and web search interception behavior after review feedback. Avoid treating non-web-search requests as web-search-only paths. * style(github_copilot): apply black formatting Apply Black formatting to the GitHub Copilot Anthropic Messages tests. * test(github_copilot): cover ProviderConfigManager dispatch for Anthropic Messages Add coverage for ProviderConfigManager dispatch when GitHub Copilot models use the Anthropic Messages API, including non-Anthropic models returning no config. * fix(github_copilot): apply messages-proxy intent header to /v1/messages Set the messages-proxy interaction header for GitHub Copilot Anthropic Messages requests so /v1/messages uses the expected Copilot intent. * fix(github_copilot): use modern generic annotations Replace legacy typing generics in the GitHub Copilot Anthropic Messages transformation so the strict Ruff budget gate stays within its ceiling. * refactor(github_copilot): decouple web-search short-circuit and harden /v1/messages URL Address review feedback on the Copilot native Anthropic messages path. Replace the hardcoded LlmProviders.GITHUB_COPILOT check in the web-search interception handler with a handles_web_search_natively() method on BaseAnthropicMessagesConfig (default True), overridden to False in GithubCopilotAnthropicMessagesConfig. Provider-specific behavior now lives in llms/ and the handler stays provider-agnostic, so a future provider in the same situation needs no carve-out here. In get_complete_url, reuse the already-resolved api_base returned by validate_anthropic_messages_environment instead of reading the authenticator a second time, removing redundant I/O and the mid-request inconsistency window. The caller-supplied base is still discarded in validate, which is the security boundary. Normalize a trailing slash on the base in both methods so a tenant-specific host never yields a double-slash //v1/messages URL. * fix(github_copilot): forward anthropic-beta headers on /v1/messages The Copilot config inherited should_filter_anthropic_beta_headers()==True from BaseAnthropicMessagesConfig, so update_headers_with_filtered_beta stripped every anthropic-beta value after validate_anthropic_messages_environment injected them (github_copilot has no mapping in anthropic_beta_headers_config.json). That silently disabled header-gated features like context_management and structured outputs on the native passthrough. Override the hook to False, matching OpenAILikeAnthropicMessagesConfig. * test(github_copilot): remove dead branch in beta-header regression test The anthropic-beta filtering test guarded the fix with an if branch on should_filter_anthropic_beta_headers(), which is always False, so the branch was unreachable. Replace it with a direct assertion that running the provider-scoped filter for github_copilot strips every beta value, proving why the override is load-bearing and catching a regression that flips it back on. --------- Co-authored-by: ririnto Co-authored-by: Cursor Agent --- .../websearch_interception/handler.py | 21 +- .../anthropic_messages/transformation.py | 13 + .../llms/github_copilot/messages/__init__.py | 0 .../github_copilot/messages/transformation.py | 118 +++++++ ...odel_prices_and_context_window_backup.json | 9 +- litellm/utils.py | 7 + .../llms/github_copilot/messages/__init__.py | 0 ..._github_copilot_messages_transformation.py | 328 ++++++++++++++++++ 8 files changed, 485 insertions(+), 11 deletions(-) create mode 100644 litellm/llms/github_copilot/messages/__init__.py create mode 100644 litellm/llms/github_copilot/messages/transformation.py create mode 100644 tests/test_litellm/llms/github_copilot/messages/__init__.py create mode 100644 tests/test_litellm/llms/github_copilot/messages/test_github_copilot_messages_transformation.py diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py index bfae6d5b7b0..60100e8c2fd 100644 --- a/litellm/integrations/websearch_interception/handler.py +++ b/litellm/integrations/websearch_interception/handler.py @@ -120,21 +120,26 @@ class WebSearchInterceptionLogger(CustomLogger): if self.enabled_providers is not None and provider_str not in self.enabled_providers: return None - # Only short-circuit for providers without native Anthropic Messages - # support. Providers that have a BaseAnthropicMessagesConfig (bedrock, - # vertex_ai, azure_ai, anthropic) already use the agentic loop, which - # includes a follow-up LLM call to synthesize the answer from search - # results. Short-circuiting those would skip that synthesis step and - # return raw search text — a regression for existing users. + # Only short-circuit for providers whose Anthropic Messages agentic loop + # does not run web_search itself. Providers that have a + # BaseAnthropicMessagesConfig which handles web search natively (bedrock, + # vertex_ai, azure_ai, anthropic) already perform the search plus a + # follow-up LLM synthesis step; short-circuiting those would skip that + # synthesis and return raw search text — a regression for existing users. + # + # github_copilot has a BaseAnthropicMessagesConfig (added for thinking + # passthrough) but does not handle web_search natively, so its config + # returns handles_web_search_natively() == False and we still short-circuit + # web-search-only requests against it. try: provider_enum = LlmProviders(provider_str) anthropic_config = ProviderConfigManager.get_provider_anthropic_messages_config( model=model, provider=provider_enum ) - if anthropic_config is not None: + if anthropic_config is not None and anthropic_config.handles_web_search_natively(): verbose_logger.debug( f"WebSearchInterception: Skipping short-circuit for {provider_str} " - "(provider has native Anthropic Messages support, using agentic loop)" + "(provider handles web search natively via the agentic loop)" ) return None except (ValueError, Exception): diff --git a/litellm/llms/base_llm/anthropic_messages/transformation.py b/litellm/llms/base_llm/anthropic_messages/transformation.py index 966995bc571..448c1d07009 100644 --- a/litellm/llms/base_llm/anthropic_messages/transformation.py +++ b/litellm/llms/base_llm/anthropic_messages/transformation.py @@ -114,6 +114,19 @@ class BaseAnthropicMessagesConfig(ABC): """ return True + def handles_web_search_natively(self) -> bool: + """ + Whether the upstream this config routes to executes ``web_search`` tools + itself as part of its Anthropic Messages agentic loop. + + The web-search interception handler short-circuits web-search-only + requests (running the search itself and returning synthetic results) only + for providers that do NOT. Providers whose agentic loop already performs + the search plus a follow-up synthesis step (bedrock, vertex_ai, ...) + return True so those requests flow through untouched. + """ + return True + def get_async_streaming_response_iterator( self, model: str, diff --git a/litellm/llms/github_copilot/messages/__init__.py b/litellm/llms/github_copilot/messages/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/github_copilot/messages/transformation.py b/litellm/llms/github_copilot/messages/transformation.py new file mode 100644 index 00000000000..fb3f0a4e159 --- /dev/null +++ b/litellm/llms/github_copilot/messages/transformation.py @@ -0,0 +1,118 @@ +from typing import Any, Optional + +from litellm.exceptions import AuthenticationError +from litellm.llms.anthropic.experimental_pass_through.messages.transformation import ( + AnthropicMessagesConfig, +) + +from ..authenticator import Authenticator +from ..common_utils import ( + DEFAULT_GITHUB_COPILOT_API_BASE, + GetAPIKeyError, + get_copilot_default_headers, +) + +_MESSAGES_PROXY_API_VERSION = "2026-06-01" + + +class GithubCopilotAnthropicMessagesConfig(AnthropicMessagesConfig): + """ + GitHub Copilot implementation of Anthropic messages API. + Routes requests to Copilot's /v1/messages endpoint with appropriate authentication and headers. + """ + + def __init__(self) -> None: + super().__init__() + self.authenticator = Authenticator() + + def handles_web_search_natively(self) -> bool: + """ + Copilot's /v1/messages endpoint does not execute ``web_search`` tools, so + the interception handler must short-circuit web-search-only requests + instead of routing them here. + """ + return False + + def should_filter_anthropic_beta_headers(self) -> bool: + """ + Copilot's /v1/messages is a native Anthropic Messages passthrough, so + ``anthropic-beta`` values injected by ``_update_headers_with_anthropic_beta`` + (context_management, structured outputs, ...) must reach the upstream + verbatim. The default provider-scoped filter would drop them because + github_copilot has no entry in ``anthropic_beta_headers_config.json``. + """ + return False + + def validate_anthropic_messages_environment( + self, + headers: dict, + model: str, + messages: list[Any], + optional_params: dict, + litellm_params: dict, + api_key: Optional[str] = None, + api_base: Optional[str] = None, + ) -> tuple[dict, Optional[str]]: + """ + Validate environment for GitHub Copilot and add Copilot-specific headers. + + The caller-supplied ``api_base`` is intentionally ignored. Routing this + request anywhere other than the authenticated Copilot endpoint would + leak the Copilot bearer token to a caller-controlled URL. + """ + # Always use the Copilot endpoint resolved from the authenticated + # session, never the caller-supplied api_base. rstrip so a + # tenant-specific base with a trailing slash does not yield a + # double-slash URL once "/v1/messages" is appended downstream. + dynamic_api_base = (self.authenticator.get_api_base() or DEFAULT_GITHUB_COPILOT_API_BASE).rstrip("/") + try: + dynamic_api_key = self.authenticator.get_api_key() + except GetAPIKeyError as e: + raise AuthenticationError( + model=model, + llm_provider="github_copilot", + message=str(e), + ) + + # Merge Copilot headers with provided headers + copilot_headers = get_copilot_default_headers(dynamic_api_key) + for key, value in copilot_headers.items(): + if key not in headers: + headers[key] = value + + headers["openai-intent"] = "messages-proxy" + headers["x-interaction-type"] = "messages-proxy" + headers["x-github-api-version"] = _MESSAGES_PROXY_API_VERSION + + if "anthropic-version" not in headers: + headers["anthropic-version"] = "2023-06-01" + + headers = self._update_headers_with_anthropic_beta( + headers, optional_params, custom_llm_provider="github_copilot" + ) + + return headers, dynamic_api_base + + def get_complete_url( + self, + api_base: Optional[str], + api_key: Optional[str], + model: str, + optional_params: dict, + litellm_params: dict, + stream: Optional[bool] = None, + ) -> str: + """ + Return the complete URL for GitHub Copilot /v1/messages endpoint. + + ``api_base`` here is the value already resolved by + ``validate_anthropic_messages_environment`` (the authenticated Copilot + host), not the raw caller-supplied base — that one is discarded there to + avoid leaking the Copilot bearer token to a caller-controlled URL. We + reuse it to avoid a second authenticator read, falling back to a fresh + resolution only if it was not provided. + """ + resolved = (api_base or self.authenticator.get_api_base() or DEFAULT_GITHUB_COPILOT_API_BASE).rstrip("/") + if not resolved.endswith("/v1/messages"): + resolved = f"{resolved}/v1/messages" + return resolved diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 8dfd3d0036a..b3058bb4214 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -19176,7 +19176,8 @@ "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ - "/v1/chat/completions" + "/v1/chat/completions", + "/v1/messages" ], "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -19189,7 +19190,8 @@ "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ - "/v1/chat/completions" + "/v1/chat/completions", + "/v1/messages" ], "supports_function_calling": true, "supports_parallel_function_calling": true, @@ -19242,7 +19244,8 @@ "max_tokens": 16000, "mode": "chat", "supported_endpoints": [ - "/v1/chat/completions" + "/v1/chat/completions", + "/v1/messages" ], "supports_function_calling": true, "supports_parallel_function_calling": true, diff --git a/litellm/utils.py b/litellm/utils.py index 45ce5332f1d..26d3ae32739 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -7984,6 +7984,13 @@ class ProviderConfigManager: ) return DeepSeekAnthropicMessagesConfig() + elif litellm.LlmProviders.GITHUB_COPILOT == provider: + if "claude" in model_lower: + from litellm.llms.github_copilot.messages.transformation import ( + GithubCopilotAnthropicMessagesConfig, + ) + + return GithubCopilotAnthropicMessagesConfig() return None @staticmethod diff --git a/tests/test_litellm/llms/github_copilot/messages/__init__.py b/tests/test_litellm/llms/github_copilot/messages/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/github_copilot/messages/test_github_copilot_messages_transformation.py b/tests/test_litellm/llms/github_copilot/messages/test_github_copilot_messages_transformation.py new file mode 100644 index 00000000000..01787c07d27 --- /dev/null +++ b/tests/test_litellm/llms/github_copilot/messages/test_github_copilot_messages_transformation.py @@ -0,0 +1,328 @@ +import os +import sys +from unittest.mock import MagicMock + +import pytest + +sys.path.insert(0, os.path.abspath("../..")) + +from litellm.exceptions import AuthenticationError +from litellm.llms.github_copilot.common_utils import GetAPIKeyError +from litellm.llms.github_copilot.messages.transformation import ( + GithubCopilotAnthropicMessagesConfig, +) + + +def test_github_copilot_anthropic_messages_config_init(): + """Test GithubCopilotAnthropicMessagesConfig initialization.""" + config = GithubCopilotAnthropicMessagesConfig() + assert config is not None + assert hasattr(config, "authenticator") + + +def test_github_copilot_anthropic_messages_get_complete_url(): + """get_complete_url builds the /v1/messages URL from the base it is handed. + + In the request flow that ``api_base`` is the value already resolved by + validate_anthropic_messages_environment (the authenticated Copilot host); the + caller-supplied base is discarded there, not here (see the validate tests). + """ + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_base.return_value = None + + # No api_base supplied and no authenticator base -> default Copilot endpoint. + url = config.get_complete_url( + api_base=None, + api_key=None, + model="github_copilot/claude-haiku-4.5", + optional_params={}, + litellm_params={}, + ) + assert url == "https://api.githubcopilot.com/v1/messages" + # Falls back to a single authenticator read, not a hard-coded second one. + config.authenticator.get_api_base.assert_called() + + # The resolved (validated) base passed in is reused verbatim; no extra read. + config.authenticator.get_api_base.reset_mock() + url = config.get_complete_url( + api_base="https://api.business.githubcopilot.com", + api_key=None, + model="github_copilot/claude-haiku-4.5", + optional_params={}, + litellm_params={}, + ) + assert url == "https://api.business.githubcopilot.com/v1/messages" + config.authenticator.get_api_base.assert_not_called() + + # A trailing slash on the base must not produce a double-slash URL. + url = config.get_complete_url( + api_base="https://api.business.githubcopilot.com/", + api_key=None, + model="github_copilot/claude-haiku-4.5", + optional_params={}, + litellm_params={}, + ) + assert url == "https://api.business.githubcopilot.com/v1/messages" + + # An already-complete /v1/messages base is left untouched. + url = config.get_complete_url( + api_base="https://api.githubcopilot.com/v1/messages", + api_key=None, + model="github_copilot/claude-haiku-4.5", + optional_params={}, + litellm_params={}, + ) + assert url == "https://api.githubcopilot.com/v1/messages" + + +def test_github_copilot_anthropic_messages_get_complete_url_normalizes_authenticator_trailing_slash(): + """A tenant base with a trailing slash from the authenticator fallback must + not yield a double-slash URL.""" + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_base.return_value = "https://api.business.githubcopilot.com/" + + url = config.get_complete_url( + api_base=None, + api_key=None, + model="github_copilot/claude-haiku-4.5", + optional_params={}, + litellm_params={}, + ) + assert url == "https://api.business.githubcopilot.com/v1/messages" + + +def test_github_copilot_anthropic_messages_validate_environment(): + """Test environment validation and header injection.""" + config = GithubCopilotAnthropicMessagesConfig() + + # Mock the authenticator + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key-123" + config.authenticator.get_api_base.return_value = None + + headers = {} + # Pass a hostile api_base to confirm it is ignored. + validated_headers, api_base = config.validate_anthropic_messages_environment( + headers=headers, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={}, + litellm_params={}, + api_key=None, + api_base="https://attacker.example.com", + ) + + assert "copilot-integration-id" in validated_headers + assert validated_headers["copilot-integration-id"] == "vscode-chat" + assert "Authorization" in validated_headers + assert "anthropic-version" in validated_headers + assert validated_headers["anthropic-version"] == "2023-06-01" + # /v1/messages must use the messages-proxy intent so the Copilot backend + # enables Anthropic-native features (context_management, thinking, etc.). + assert validated_headers["openai-intent"] == "messages-proxy" + assert validated_headers["x-interaction-type"] == "messages-proxy" + assert validated_headers["x-github-api-version"] == "2026-06-01" + assert api_base == "https://api.githubcopilot.com" + + +def test_github_copilot_anthropic_messages_validate_environment_injects_beta_headers(): + """Anthropic-beta headers must be auto-injected for advanced features + (context_management, output_format, etc.) — matches the parent + AnthropicMessagesConfig contract.""" + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key" + config.authenticator.get_api_base.return_value = None + + validated_headers, _ = config.validate_anthropic_messages_environment( + headers={}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={"output_format": {"type": "json_object"}}, + litellm_params={}, + api_key=None, + api_base=None, + ) + + assert "anthropic-beta" in validated_headers + assert "structured-outputs-2025-11-13" in validated_headers["anthropic-beta"] + + +def test_github_copilot_anthropic_messages_validate_environment_preserves_caller_anthropic_version(): + """Caller-supplied anthropic-version must be forwarded verbatim.""" + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key" + config.authenticator.get_api_base.return_value = None + + validated_headers, _ = config.validate_anthropic_messages_environment( + headers={"anthropic-version": "2024-10-22"}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={}, + litellm_params={}, + api_key=None, + api_base=None, + ) + + assert validated_headers["anthropic-version"] == "2024-10-22" + + +def test_github_copilot_anthropic_messages_validate_environment_injects_context_management_beta(): + """context_management in optional_params must trigger the corresponding + anthropic-beta header so the Copilot backend accepts the field.""" + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key" + config.authenticator.get_api_base.return_value = None + + validated_headers, _ = config.validate_anthropic_messages_environment( + headers={}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={"context_management": {"edits": [{"type": "clear_tool_uses_20250919"}]}}, + litellm_params={}, + api_key=None, + api_base=None, + ) + + assert validated_headers["openai-intent"] == "messages-proxy" + assert validated_headers["x-interaction-type"] == "messages-proxy" + assert "anthropic-beta" in validated_headers + assert "context-management-2025-06-27" in validated_headers["anthropic-beta"] + + +def test_github_copilot_anthropic_messages_validate_environment_auth_error(): + """Test error handling when authentication fails.""" + config = GithubCopilotAnthropicMessagesConfig() + + # Mock the authenticator to raise an error + config.authenticator = MagicMock() + config.authenticator.get_api_key.side_effect = GetAPIKeyError(status_code=401, message="No valid API key found") + + with pytest.raises(AuthenticationError): + config.validate_anthropic_messages_environment( + headers={}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={}, + litellm_params={}, + api_key=None, + api_base=None, + ) + + +def test_github_copilot_anthropic_messages_supported_params(): + """Test supported parameters list.""" + config = GithubCopilotAnthropicMessagesConfig() + params = config.get_supported_anthropic_messages_params("github_copilot/claude-haiku-4.5") + + # Should inherit from AnthropicMessagesConfig + assert "messages" in params + assert "model" in params + assert "max_tokens" in params + assert "thinking" in params + + +def test_provider_config_manager_dispatches_claude_to_copilot_messages_config(): + """ProviderConfigManager must return the Copilot Anthropic Messages config + for Claude models served via github_copilot.""" + from litellm.types.utils import LlmProviders + from litellm.utils import ProviderConfigManager + + config = ProviderConfigManager.get_provider_anthropic_messages_config( + model="github_copilot/claude-haiku-4.5", + provider=LlmProviders.GITHUB_COPILOT, + ) + + assert isinstance(config, GithubCopilotAnthropicMessagesConfig) + + +def test_provider_config_manager_skips_non_claude_copilot_models(): + """Non-Claude github_copilot models (e.g. gpt-*) must not be routed through + the Anthropic Messages dispatch.""" + from litellm.types.utils import LlmProviders + from litellm.utils import ProviderConfigManager + + config = ProviderConfigManager.get_provider_anthropic_messages_config( + model="github_copilot/gpt-5-mini", + provider=LlmProviders.GITHUB_COPILOT, + ) + + assert config is None + + +def test_github_copilot_anthropic_messages_validate_environment_normalizes_trailing_slash(): + """A tenant base with a trailing slash from the authenticator must be + normalized so the URL built downstream has no double slash.""" + config = GithubCopilotAnthropicMessagesConfig() + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key" + config.authenticator.get_api_base.return_value = "https://api.business.githubcopilot.com/" + + _, api_base = config.validate_anthropic_messages_environment( + headers={}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={}, + litellm_params={}, + api_key=None, + api_base="https://attacker.example.com", + ) + + assert api_base == "https://api.business.githubcopilot.com" + + +def test_github_copilot_config_disables_anthropic_beta_filtering(): + """Copilot's /v1/messages is a native Anthropic passthrough, so injected + anthropic-beta values (context_management, structured outputs, ...) must be + forwarded verbatim. The default provider-scoped filter would drop them + because github_copilot has no entry in the beta headers config; a regression + here would silently disable header-gated Anthropic features for Copilot.""" + from litellm.anthropic_beta_headers_manager import update_headers_with_filtered_beta + from litellm.llms.anthropic.experimental_pass_through.messages.transformation import ( + AnthropicMessagesConfig, + ) + + config = GithubCopilotAnthropicMessagesConfig() + assert config.should_filter_anthropic_beta_headers() is False + assert AnthropicMessagesConfig().should_filter_anthropic_beta_headers() is True + + config.authenticator = MagicMock() + config.authenticator.get_api_key.return_value = "gh.test-key" + config.authenticator.get_api_base.return_value = None + + headers, _ = config.validate_anthropic_messages_environment( + headers={}, + model="github_copilot/claude-haiku-4.5", + messages=[{"role": "user", "content": "Hello"}], + optional_params={"context_management": {"edits": [{"type": "clear_tool_uses_20250919"}]}}, + litellm_params={}, + api_key=None, + api_base=None, + ) + + assert "context-management-2025-06-27" in headers["anthropic-beta"] + + # The override is load-bearing: had the config opted into the provider-scoped + # filter, the handler would have run it and dropped every value, since + # github_copilot has no mapping. Prove that here so a regression that flips + # should_filter back on is caught as the silent feature breakage it causes. + stripped = update_headers_with_filtered_beta(headers=dict(headers), provider="github_copilot") + assert "anthropic-beta" not in stripped + + +def test_github_copilot_config_does_not_handle_web_search_natively(): + """Copilot's /v1/messages does not run web_search, so its config must report + handles_web_search_natively() == False. This is what keeps the web-search + interception handler short-circuiting Copilot instead of routing to it, even + though Copilot now has a BaseAnthropicMessagesConfig. The base Anthropic + config (bedrock/vertex/anthropic path) must report True.""" + from litellm.llms.anthropic.experimental_pass_through.messages.transformation import ( + AnthropicMessagesConfig, + ) + + assert GithubCopilotAnthropicMessagesConfig().handles_web_search_natively() is False + assert AnthropicMessagesConfig().handles_web_search_natively() is True From fde4c7c97ae49370dc7986326aace4c5fb7bd91b Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 17:31:07 -0700 Subject: [PATCH 63/79] feat(gdc): implement Google Distributed Cloud (GDC) Gemini provider (#31895) * feat(gdc): add Google Distributed Cloud Gemini provider support Introduce support for the Google Distributed Cloud (GDC) Gemini provider by adding "gdc" to the list of chat providers and enabling the gdc/ model prefix. The implementation defines a new GDCGeminiConfig class which handles authentication via Google Distributed Cloud service account credentials, manages token generation, formats GDC Gemini request URLs, and transforms request structures accordingly The PreProcessNonDefaultParams class is also updated to exclude vertex parameters from filtering when the custom LLM provider is GDC, allowing vertex parameters to be passed properly during GDC initialization * fix: resolve issues identified in PR #30702 * fix(gdc): harden credentials, fix vertex param filtering, add tests The supports_vertex_params branch regressed vertex_ai and vertex_ai_beta: the `if custom_llm_provider in [...]: pass` was a no-op, so those providers fell through to the config lookup, found no supports_vertex_params, and had their vertex_ params stripped. The check is now a single _provider_supports_vertex_params helper that keeps vertex_ params for the vertex family and for any config that opts in, and only swallows the expected ValueError from an unknown provider string instead of a blanket except GDC project and location now resolve from the deployment's litellm_params and the litellm.vertex_project / litellm.vertex_location globals before falling back to request optional_params, matching how vertex_ai resolves them, so a proxy caller can no longer route a request to a project the deployment did not expose A request api_key is no longer treated as a filesystem path, so a caller can't make the host open a local service-account file; api_key must be a literal service-account JSON string or a bearer token The opt-in token cache is hardened: the lock and cache dict are created in __init__ instead of via a racy hasattr lazy-init, the token is read inside the lock, and the audience is stripped of a trailing slash once so the cached and non-cached paths agree Also declares gdc_api_base, switches the lazy-import entry to the relative path every other entry uses, adds the missing trailing comma in the provider config map, and drops the api_base fallback that only ran when api_key was None Adds unit tests covering the vertex-param filter, deployment-over-request precedence, the api_key file-path rejection, URL construction branches, environment validation, token caching, and the gdc completion dispatch; transformation.py is fully covered * fix(gdc): prefer GDC-specific config, honor vertex_ai aliases, harden URL and bool parsing * fix(gdc): mint the GDCH token audience from the host, not the full base When api_base embedded /v1/projects/... and the deployment set project/location, get_complete_url rebuilt the request URL from the host while validate_environment still derived the token audience from the full original api_base, so the bearer token could target a different audience than the URL actually called. The audience is now the scheme://host of api_base in every case, matching the host get_complete_url builds against * fix(gdc): restrict JSON api_key to GDCH service accounts Only accept a credential whose type is gdch_service_account before calling google.auth.load_credentials_from_dict, so a caller-supplied external_account/identity_pool/pluggable credential carrying arbitrary token or credential_source endpoints is rejected before any token refresh runs. GDC only ever uses GDCH service accounts, and non-GDCH credentials could not have completed auth anyway (with_gdch_audience is GDCH-only), so this narrows the credential-refresh surface without changing valid GDC behavior. * fix(gdc): validate project and location as plain identifiers vertex_project and vertex_location can come from request params and were interpolated as raw path text into the GDC request URL and the x-goog-user-project header. A caller-supplied value containing / ? # or .. could reshape the path and make the proxy send its GDC-authorized request to a different endpoint under the configured host. Validate both against a strict identifier pattern before building the URL or header and raise an auth error otherwise; GCP project ids and locations are plain identifiers so valid deployments are unaffected. * fix(gdc): bind x-goog-user-project quota header to the deployment The quota project header was resolved with request-level vertex_project taking effect, so with a preformed deployment api_base a caller could set vertex_project to a different project and have it sent under the proxy's GDC credential, misattributing quota or billing. Resolve the header project the same way the URL is resolved: a preformed api_base without a deployment override binds to the project embedded in the URL, otherwise deployment and global config win over request params. This keeps the URL and the quota header consistent. * fix(gdc): always rebind x-goog-user-project, stripping caller-forwarded values The quota project header was only set when absent, so with client header forwarding an authenticated caller could send their own x-goog-user-project (any casing) and have it ride on the proxy's GDC credential, bypassing the deployment-derived binding. Strip every casing of the header and always set it from _effective_project before the request is signed. * fix(gdc): make a preformed api_base authoritative for project routing get_litellm_params copies caller-supplied vertex_project and vertex_location into litellm_params via OPTIONAL_KWARGS_KEYS, so litellm_params cannot be treated as a deployment-only source. The previous _deployment_overrides_path inference let an authenticated caller flip a pinned preformed api_base such as /v1/projects/pinned/... to /v1/projects/attacker/..., driving requests to a caller-chosen project with the proxy's configured GDC credentials and quota header A preformed /v1/projects/ api_base is now authoritative; get_complete_url returns it unchanged and _effective_project binds the x-goog-user-project quota header to the project embedded in that URL, so a caller can no longer redirect a pinned deployment or move the quota header off it. The two tests that asserted the override behavior are now regression tests that fail if the rewrite is reintroduced * fix(gdc): make a preformed api_base self-sufficient in get_complete_url get_complete_url resolved and required a params-derived vertex_project before returning a preformed /v1/projects/ api_base, so a deployment that pins its project in the api_base path was forced to also pass vertex_project or hit 'project is required'. validate_environment already extracts the project from a preformed URL and needs no such param, so the two paths disagreed The preformed-URL early return now runs before project/location resolution, matching validate_environment: a preformed api_base is returned as-is with no redundant param, and non-preformed bases still require vertex_project and vertex_location as before. Adds a regression test that a preformed base with no project/location params returns the URL unchanged --------- Co-authored-by: Paige O'Connor Co-authored-by: Tim Laubach --- litellm/__init__.py | 3 + litellm/_lazy_imports_registry.py | 5 + litellm/constants.py | 1 + .../get_llm_provider_logic.py | 2 + litellm/llms/gdc/__init__.py | 0 litellm/llms/gdc/chat/__init__.py | 0 litellm/llms/gdc/chat/transformation.py | 285 +++++++ litellm/main.py | 43 ++ litellm/types/utils.py | 1 + litellm/utils.py | 21 +- provider_endpoints_support.json | 10 + ruff-strict-budget.json | 2 +- .../gdc/chat/test_gdc_chat_transformation.py | 717 ++++++++++++++++++ tests/test_litellm/test_utils.py | 42 + 14 files changed, 1126 insertions(+), 6 deletions(-) create mode 100644 litellm/llms/gdc/__init__.py create mode 100644 litellm/llms/gdc/chat/__init__.py create mode 100644 litellm/llms/gdc/chat/transformation.py create mode 100644 tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py diff --git a/litellm/__init__.py b/litellm/__init__.py index 15e95ded906..9327e121b1d 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -263,6 +263,8 @@ azure_key: Optional[str] = None anthropic_key: Optional[str] = None replicate_key: Optional[str] = None bytez_key: Optional[str] = None +gdc_key: Optional[str] = None +gdc_api_base: Optional[str] = None cohere_key: Optional[str] = None infinity_key: Optional[str] = None clarifai_key: Optional[str] = None @@ -1787,6 +1789,7 @@ if TYPE_CHECKING: from .llms.nvidia_nim.embed import ( NvidiaNimEmbeddingConfig as NvidiaNimEmbeddingConfig, ) + from .llms.gdc.chat.transformation import GDCGeminiConfig as GDCGeminiConfig # Type stubs for lazy-loaded config instances openaiOSeriesConfig: OpenAIOSeriesConfig diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py index 4f131354d2e..0f9d3a560d1 100644 --- a/litellm/_lazy_imports_registry.py +++ b/litellm/_lazy_imports_registry.py @@ -323,6 +323,7 @@ LLM_CONFIG_NAMES = ( "SnowflakeEmbeddingConfig", "AmazonNovaChatConfig", "SonioxAudioTranscriptionConfig", + "GDCGeminiConfig", ) # Types that support lazy loading via _lazy_import_types @@ -1157,6 +1158,10 @@ _LLM_CONFIGS_IMPORT_MAP = { ".llms.dashscope.chat.transformation", "DashScopeChatConfig", ), + "GDCGeminiConfig": ( + ".llms.gdc.chat.transformation", + "GDCGeminiConfig", + ), "ModelScopeChatConfig": ( ".llms.modelscope.chat.transformation", "ModelScopeChatConfig", diff --git a/litellm/constants.py b/litellm/constants.py index 93aed83852b..6eb2779dcae 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -460,6 +460,7 @@ LITELLM_CHAT_PROVIDERS = [ "openai", "openai_like", "bytez", + "gdc", "xai", "custom_openai", "text-completion-openai", diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index 122d09c855b..a7a576ff167 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -446,6 +446,8 @@ def get_llm_provider( # bytez models elif model.startswith("bytez/"): custom_llm_provider = "bytez" + elif model.startswith("gdc/"): + custom_llm_provider = "gdc" elif model.startswith("lemonade/"): custom_llm_provider = "lemonade" elif model.startswith("heroku/"): diff --git a/litellm/llms/gdc/__init__.py b/litellm/llms/gdc/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/gdc/chat/__init__.py b/litellm/llms/gdc/chat/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/gdc/chat/transformation.py b/litellm/llms/gdc/chat/transformation.py new file mode 100644 index 00000000000..61631920a64 --- /dev/null +++ b/litellm/llms/gdc/chat/transformation.py @@ -0,0 +1,285 @@ +""" +GDC Gemini chat completion transformation +""" + +import json +import os +import re +import threading +from typing import Any, Final +from urllib.parse import urlsplit + +import litellm +from litellm.llms.openai_like.chat.transformation import OpenAILikeChatConfig + + +class GDCGeminiConfig(OpenAILikeChatConfig): + supports_vertex_params: bool = True # Tell LiteLLM utilities not to strip vertex_ params + _GDCH_CREDENTIAL_TYPE: Final[str] = "gdch_service_account" + _PATH_ID_PATTERN: Final[re.Pattern[str]] = re.compile(r"^[a-zA-Z0-9_-]+$") + + def __init__(self, **kwargs: Any) -> None: + super().__init__(**kwargs) + self._creds_lock = threading.Lock() + self._gdch_creds_cache: dict = {} + + def get_supported_openai_params(self, model: str) -> list: + return [ + "vertex_project", + "vertex_location", + ] + super().get_supported_openai_params(model) + + def _resolve_project(self, optional_params: dict, litellm_params: dict) -> str | None: + return ( + litellm_params.get("vertex_project") + or litellm_params.get("vertex_ai_project") + or getattr(litellm, "vertex_project", None) + or optional_params.get("vertex_project") + or optional_params.get("vertex_ai_project") + ) + + def _resolve_location(self, optional_params: dict, litellm_params: dict) -> str | None: + return ( + litellm_params.get("vertex_location") + or litellm_params.get("vertex_ai_location") + or getattr(litellm, "vertex_location", None) + or optional_params.get("vertex_location") + or optional_params.get("vertex_ai_location") + ) + + def _effective_project(self, api_base: str, optional_params: dict, litellm_params: dict) -> str | None: + match = re.search(r"/v1/projects/([^/]+)", api_base) + if match: + return match.group(1) + return self._resolve_project(optional_params, litellm_params) + + def _validate_path_id(self, value: str, field: str, model: str) -> str: + if not self._PATH_ID_PATTERN.match(value): + raise litellm.utils.AuthenticationError( + message=f"{field} must be a plain identifier of letters, digits, hyphens or underscores.", + llm_provider="gdc", + model=model, + ) + return value + + def get_complete_url( + self, + api_base: str | None, + api_key: str | None, + model: str, + optional_params: dict, + litellm_params: dict, + stream: bool | None = None, + ) -> str: + api_base = api_base or litellm.gdc_api_base or litellm.api_base + if not api_base: + raise litellm.utils.AuthenticationError( + message="api_base/host is required for GDC Gemini. Please set it or pass it.", + llm_provider="gdc", + model=model, + ) + + if not api_base.startswith("http"): + api_base = f"https://{api_base}" + + api_base = api_base.rstrip("/") + + if "/v1/projects/" in api_base: + return api_base + + project = self._resolve_project(optional_params, litellm_params) + + if not project: + raise litellm.utils.AuthenticationError( + message="project is required for GDC Gemini. Please pass vertex_project.", + llm_provider="gdc", + model=model, + ) + + location = self._resolve_location(optional_params, litellm_params) + + if not location: + raise litellm.utils.AuthenticationError( + message="location is required for GDC Gemini. Please pass vertex_location.", + llm_provider="gdc", + model=model, + ) + + project = self._validate_path_id(project, "vertex_project", model) + location = self._validate_path_id(location, "vertex_location", model) + + return f"{api_base}/v1/projects/{project}/locations/{location}/chat/completions" + + def _read_env_bool(self, val: Any, env_var: str, default: bool = True) -> bool | str: + def _parse(s: str) -> bool | str: + cleaned = s.strip().lower() + if cleaned in ("false", "0", "no", "off"): + return False + if cleaned in ("true", "1", "yes", "on"): + return True + return s + + if val is not None: + if isinstance(val, str): + return _parse(val) + return val + + _env_val = os.getenv(env_var) + if _env_val is None: + return default + return _parse(_env_val) + + def _fetch_auth(self, gdch_creds: Any, ssl_verify: bool | str) -> None: + import requests + from google.auth.transport import requests as auth_requests + + auth_session = requests.Session() + auth_session.verify = ssl_verify + auth_request = auth_requests.Request(session=auth_session) + gdch_creds.refresh(auth_request) + + def _cached_fetch_token(self, creds: Any, audience: str, ssl_verify: bool | str, api_key: str | None = None) -> str: + # Key cache by both audience and credential identity to prevent cross-caller contamination + cache_key = (audience.rstrip("/"), api_key or str(id(creds))) + + with self._creds_lock: + if cache_key not in self._gdch_creds_cache: + self._gdch_creds_cache[cache_key] = creds.with_gdch_audience(audience.rstrip("/")) + + gdch_creds = self._gdch_creds_cache[cache_key] + + if not getattr(gdch_creds, "valid", False) or not getattr(gdch_creds, "token", None): + self._fetch_auth(gdch_creds, ssl_verify) + + token = gdch_creds.token + + return token + + def _load_creds_from_key(self, api_key: str) -> tuple[Any, bool]: + import google.auth + + try: + json_obj = json.loads(api_key) + except json.JSONDecodeError: + return None, False + if not isinstance(json_obj, dict) or json_obj.get("type") != self._GDCH_CREDENTIAL_TYPE: + raise ValueError( + "GDC only accepts a GDCH service account credential as a JSON api_key " + '(expected "type": "gdch_service_account"). Other Google credential types are ' + "rejected so their token or external-account endpoints cannot drive server-side requests." + ) + creds, _ = google.auth.load_credentials_from_dict(json_obj) + return creds, True + + def validate_environment( + self, + headers: dict, + model: str, + messages: list[Any], + optional_params: dict, + litellm_params: dict, + api_key: str | None = None, + api_base: str | None = None, + ) -> dict: + import google.auth.exceptions + + api_base = api_base or litellm.gdc_api_base or litellm.api_base + if not api_base: + raise litellm.utils.AuthenticationError( + message="api_base/host is required for GDC Gemini. Please set it or pass it.", + llm_provider="gdc", + model=model, + ) + + if not api_key: + raise litellm.utils.AuthenticationError( + message="api_key is required for GDC Gemini. Please pass your service account string or token as the api_key.", + llm_provider="gdc", + model=model, + ) + + project = self._effective_project(api_base, optional_params, litellm_params) + if not project: + raise litellm.utils.AuthenticationError( + message="project is required for GDC Gemini. Please pass vertex_project.", + llm_provider="gdc", + model=model, + ) + project = self._validate_path_id(project, "vertex_project", model) + + _audience_parts = urlsplit(api_base if api_base.startswith("http") else f"https://{api_base}") + audience = f"{_audience_parts.scheme}://{_audience_parts.netloc}" + + try: + creds, is_service_account = self._load_creds_from_key(api_key) + except ( + google.auth.exceptions.GoogleAuthError, + ValueError, + TypeError, + KeyError, + AttributeError, + ) as e: + raise litellm.utils.AuthenticationError( + message=f"Failed to load service account credentials from api_key: {str(e)}", + llm_provider="gdc", + model=model, + ) from e + + if creds is not None: + ssl_verify = self._read_env_bool(litellm_params.get("ssl_verify"), "SSL_VERIFY", default=True) + if self._read_env_bool(litellm_params.get("gdc_token_caching"), "GDC_TOKEN_CACHING", default=False): + token = self._cached_fetch_token(creds, audience, ssl_verify, api_key) + else: + gdch_creds = creds.with_gdch_audience(audience) + self._fetch_auth(gdch_creds, ssl_verify) + token = gdch_creds.token + headers["Authorization"] = f"Bearer {token}" + + if "Authorization" not in headers and not is_service_account: + headers["Authorization"] = f"Bearer {api_key}" + + # Standardize necessary metadata headers + if "content-type" not in headers and "Content-Type" not in headers: + headers["Content-Type"] = "application/json" + + stale_quota_headers = tuple(h for h in headers if h.lower() == "x-goog-user-project") + for stale in stale_quota_headers: + headers.pop(stale, None) + headers["x-goog-user-project"] = f"projects/{project}" + + return headers + + def transform_request( + self, + model: str, + messages: list[Any], + optional_params: dict, + litellm_params: dict, + headers: dict, + ) -> dict: + """ + Transforms the request to the GDC provider + """ + if model.startswith("gdc/"): + model = model.split("/", 1)[1] + + data = super().transform_request( + model=model, + messages=messages, + optional_params=optional_params, + litellm_params=litellm_params, + headers=headers, + ) + + # Remove extra params used for routing/auth + for param in [ + "vertex_project", + "vertex_ai_project", + "vertex_location", + "vertex_ai_location", + "ssl_verify", + "gdc_token_caching", + ]: + data.pop(param, None) + + return data diff --git a/litellm/main.py b/litellm/main.py index 18d2c367f8d..567930a4999 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -210,6 +210,7 @@ from .llms.bedrock.embed.embedding import BedrockEmbedding from .llms.bedrock.image_edit.handler import BedrockImageEdit from .llms.bedrock.image_generation.image_handler import BedrockImageGeneration from .llms.bytez.chat.transformation import BytezChatConfig +from .llms.gdc.chat.transformation import GDCGeminiConfig from .llms.clarifai.chat.transformation import ClarifaiConfig from .llms.codestral.completion.handler import CodestralTextCompletion from .llms.cohere.embed import handler as cohere_embed @@ -318,6 +319,7 @@ google_batch_embeddings = GoogleBatchEmbeddings() vertex_partner_models_chat_completion = VertexAIPartnerModels() vertex_gemma_chat_completion = VertexAIGemmaModels() vertex_model_garden_chat_completion = VertexAIModelGardenModels() +gdc_transformation = GDCGeminiConfig() # vertex_text_to_speech is now replaced by VertexAITextToSpeechConfig sagemaker_llm = SagemakerLLM() watsonx_chat_completion = WatsonXChatHandler() @@ -4336,6 +4338,45 @@ def _complete_gradient_ai(ctx: _CompletionDispatchContext) -> _CompletionDispatc ) +def _complete_gdc(ctx: _CompletionDispatchContext) -> _CompletionDispatchResult: + acompletion = ctx.acompletion + api_base = ctx.api_base + api_key = ctx.api_key + client = ctx.client + custom_llm_provider = ctx.custom_llm_provider + headers = ctx.headers + litellm_params = ctx.litellm_params + logging = ctx.logging + messages = ctx.messages + model = ctx.model + model_response = ctx.model_response + optional_params = ctx.optional_params + stream = ctx.stream + timeout = ctx.timeout + + api_key = api_key or litellm.gdc_key or get_secret_str("GDC_API_KEY") or litellm.api_key + api_base = api_base or litellm.gdc_api_base or get_secret_str("GDC_API_BASE") or litellm.api_base + + return base_llm_http_handler.completion( + model=model, + messages=messages, + headers=headers, + model_response=model_response, + api_key=api_key, + api_base=api_base, + acompletion=acompletion, + logging_obj=logging, + optional_params=optional_params, + litellm_params=litellm_params, + timeout=timeout, # type: ignore + client=client, + custom_llm_provider=custom_llm_provider, + encoding=_get_encoding(), + stream=stream, + provider_config=gdc_transformation, + ) + + def _complete_bytez(ctx: _CompletionDispatchContext) -> _CompletionDispatchResult: acompletion = ctx.acompletion api_base = ctx.api_base @@ -5533,6 +5574,8 @@ def completion( # type: ignore elif custom_llm_provider == "gradient_ai": response = _complete_gradient_ai(_dispatch_ctx) + elif custom_llm_provider == "gdc": + response = _complete_gdc(_dispatch_ctx) elif custom_llm_provider == "bytez": response = _complete_bytez(_dispatch_ctx) elif custom_llm_provider == "lemonade": diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 4f0c0c21bce..0e2a6b24806 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -3369,6 +3369,7 @@ class LlmProviders(str, Enum): LITELLM_AGENT = "litellm_agent" CURSOR = "cursor" BEDROCK_MANTLE = "bedrock_mantle" + GDC = "gdc" # Create a set of all provider values for quick lookup diff --git a/litellm/utils.py b/litellm/utils.py index 26d3ae32739..226b94913b5 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -3497,6 +3497,17 @@ def filter_out_litellm_params(kwargs: dict) -> dict: return {key: value for key, value in kwargs.items() if key not in all_litellm_params} +def _provider_supports_vertex_params(custom_llm_provider: str) -> bool: + if custom_llm_provider in ("vertex_ai", "vertex_ai_beta"): + return True + try: + provider = LlmProviders(custom_llm_provider) + except ValueError: + return False + provider_config = ProviderConfigManager.get_provider_chat_config(model="", provider=provider) + return bool(getattr(provider_config, "supports_vertex_params", False)) + + class PreProcessNonDefaultParams: @staticmethod def base_pre_process_non_default_params( @@ -3518,11 +3529,7 @@ class PreProcessNonDefaultParams: continue elif k == "hf_model_name" and custom_llm_provider != "sagemaker": continue - elif ( - k.startswith("vertex_") - and custom_llm_provider != "vertex_ai" - and custom_llm_provider != "vertex_ai_beta" - ): # allow dynamically setting vertex ai init logic + elif k.startswith("vertex_") and not _provider_supports_vertex_params(custom_llm_provider): continue passed_params[k] = v @@ -7674,6 +7681,10 @@ class ProviderConfigManager: lambda: ProviderConfigManager._get_langflow_config(), False, ), + LlmProviders.GDC: ( + lambda: litellm.GDCGeminiConfig(), + False, + ), } @staticmethod diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index b137ec59a1f..edac8949f28 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -1059,6 +1059,16 @@ "interactions": true } }, + "gdc": { + "display_name": "Google Distributed Cloud (GDC)", + "url": "https://docs.litellm.ai/docs/providers/gdc", + "endpoints": { + "chat_completions": true, + "messages": false, + "responses": false, + "embeddings": false + } + }, "github_copilot": { "display_name": "GitHub Copilot (`github_copilot`)", "url": "https://docs.litellm.ai/docs/providers/github_copilot", diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json index be62f8a9d67..f5aa600ab84 100644 --- a/ruff-strict-budget.json +++ b/ruff-strict-budget.json @@ -180,7 +180,7 @@ "limit": 34 }, "PLR1714": { - "limit": 267 + "limit": 265 }, "PLR1730": { "limit": 10 diff --git a/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py b/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py new file mode 100644 index 00000000000..d106cf7ea21 --- /dev/null +++ b/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py @@ -0,0 +1,717 @@ +import os +import sys +from unittest.mock import MagicMock, patch + +import pytest + +# Adds the parent directory to the system path +sys.path.insert(0, os.path.abspath("../../../../..")) + +import litellm +from litellm.llms.gdc.chat.transformation import GDCGeminiConfig + +TEST_API_KEY = '{"type": "gdch_service_account", "project_id": "test-project"}' +TEST_MODEL = "gdc/gemini-2.5-flash" +TEST_API_BASE = "https://gdc-endpoint.com" +TEST_PROJECT = "test-project" +TEST_LOCATION = "test-location" + + +class TestGDCGeminiConfig: + def test_get_complete_url(self): + config = GDCGeminiConfig() + url = config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + litellm_params={}, + ) + assert ( + url + == f"{TEST_API_BASE}/v1/projects/{TEST_PROJECT}/locations/{TEST_LOCATION}/chat/completions" + ) + + def test_get_complete_url_adds_https_scheme(self): + config = GDCGeminiConfig() + url = config.get_complete_url( + api_base="gdc-endpoint.com", + api_key=None, + model=TEST_MODEL, + optional_params={}, + litellm_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + ) + assert url.startswith("https://gdc-endpoint.com/v1/projects/") + + def test_get_complete_url_preformed_base_returned_as_is(self): + config = GDCGeminiConfig() + preformed = f"{TEST_API_BASE}/v1/projects/{TEST_PROJECT}/locations/{TEST_LOCATION}/chat/completions" + url = config.get_complete_url( + api_base=preformed, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": TEST_PROJECT}, + litellm_params={}, + ) + assert url == preformed + + def test_get_complete_url_missing_api_base(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="api_base/host is required for GDC Gemini"): + config.get_complete_url( + api_base=None, + api_key=None, + model=TEST_MODEL, + optional_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + litellm_params={}, + ) + + def test_get_complete_url_missing_project(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="project is required for GDC Gemini"): + config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={}, + litellm_params={}, + ) + + def test_get_complete_url_missing_location(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="location is required for GDC Gemini"): + config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": TEST_PROJECT}, + litellm_params={}, + ) + + def test_get_complete_url_accepts_vertex_ai_aliases(self): + config = GDCGeminiConfig() + url = config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={}, + litellm_params={ + "vertex_ai_project": TEST_PROJECT, + "vertex_ai_location": TEST_LOCATION, + }, + ) + assert ( + url + == f"{TEST_API_BASE}/v1/projects/{TEST_PROJECT}/locations/{TEST_LOCATION}/chat/completions" + ) + + def test_get_complete_url_preformed_base_is_authoritative_over_litellm_params(self): + config = GDCGeminiConfig() + preformed = f"{TEST_API_BASE}/v1/projects/pinned-project/locations/pinned-loc/chat/completions" + url = config.get_complete_url( + api_base=preformed, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": "attacker-optional", "vertex_location": "attacker-loc"}, + litellm_params={ + "vertex_project": "attacker-project", + "vertex_location": "attacker-loc", + }, + ) + assert url == preformed + + def test_get_complete_url_preformed_base_needs_no_project_param(self): + config = GDCGeminiConfig() + preformed = f"{TEST_API_BASE}/v1/projects/pinned-project/locations/pinned-loc/chat/completions" + url = config.get_complete_url( + api_base=preformed, + api_key=None, + model=TEST_MODEL, + optional_params={}, + litellm_params={}, + ) + assert url == preformed + + def test_deployment_project_takes_precedence_over_request(self): + config = GDCGeminiConfig() + url = config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={ + "vertex_project": "caller-project", + "vertex_location": "caller-location", + }, + litellm_params={ + "vertex_project": "deployment-project", + "vertex_location": "deployment-location", + }, + ) + assert url == ( + f"{TEST_API_BASE}/v1/projects/deployment-project" + "/locations/deployment-location/chat/completions" + ) + + @patch("google.auth.load_credentials_from_dict") + @patch("requests.Session") + def test_validate_environment(self, mock_session, mock_load_creds): + mock_creds = MagicMock() + mock_creds.token = "mock-token" + mock_creds.with_gdch_audience.return_value = mock_creds + mock_load_creds.return_value = (mock_creds, None) + + mock_session_instance = MagicMock() + mock_session.return_value = mock_session_instance + + config = GDCGeminiConfig() + result = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + litellm_params={}, + api_key=TEST_API_KEY, + api_base=TEST_API_BASE, + ) + + assert result["Authorization"] == "Bearer mock-token" + assert result["Content-Type"] == "application/json" + assert result["x-goog-user-project"] == f"projects/{TEST_PROJECT}" + + mock_creds.with_gdch_audience.assert_called_once_with(TEST_API_BASE) + mock_creds.refresh.assert_called_once() + assert mock_session_instance.verify is True + + def test_validate_environment_strips_audience_trailing_slash(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "mock-token" + mock_creds.with_gdch_audience.return_value = mock_creds + + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ), patch("requests.Session"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key=TEST_API_KEY, + api_base="https://gdc-endpoint.com/", + ) + + mock_creds.with_gdch_audience.assert_called_once_with("https://gdc-endpoint.com") + + def test_validate_environment_audience_is_host_for_preformed_base(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "mock-token" + mock_creds.with_gdch_audience.return_value = mock_creds + + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ), patch("requests.Session"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={ + "vertex_project": "deployment-project", + "vertex_location": "deployment-loc", + }, + api_key=TEST_API_KEY, + api_base=f"{TEST_API_BASE}/v1/projects/embedded/locations/embedded/chat/completions", + ) + + mock_creds.with_gdch_audience.assert_called_once_with(TEST_API_BASE) + + def test_validate_environment_missing_api_base(self, monkeypatch): + monkeypatch.setattr(litellm, "api_base", None, raising=False) + monkeypatch.setattr(litellm, "gdc_api_base", None, raising=False) + config = GDCGeminiConfig() + with pytest.raises(Exception, match="api_base/host is required for GDC Gemini"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key=TEST_API_KEY, + api_base=None, + ) + + def test_validate_environment_missing_api_key(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="api_key is required for GDC Gemini"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key=None, + api_base=TEST_API_BASE, + ) + + def test_validate_environment_missing_project(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="project is required for GDC Gemini"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={}, + api_key=TEST_API_KEY, + api_base=TEST_API_BASE, + ) + + def test_validate_environment_raw_token_used_as_bearer(self): + config = GDCGeminiConfig() + headers = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key="ya29.raw-access-token", + api_base=TEST_API_BASE, + ) + assert headers["Authorization"] == "Bearer ya29.raw-access-token" + assert headers["x-goog-user-project"] == f"projects/{TEST_PROJECT}" + + def test_validate_environment_bad_credentials_raise_auth_error(self): + config = GDCGeminiConfig() + with patch( + "google.auth.load_credentials_from_dict", + side_effect=ValueError("bad creds"), + ): + with pytest.raises( + Exception, match="Failed to load service account credentials" + ): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key=TEST_API_KEY, + api_base=TEST_API_BASE, + ) + + def test_validate_environment_string_false_disables_token_caching(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "mock-token" + mock_creds.with_gdch_audience.return_value = mock_creds + + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ), patch("requests.Session"), patch.object( + config, "_cached_fetch_token" + ) as mock_cached: + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={ + "vertex_project": TEST_PROJECT, + "gdc_token_caching": "false", + }, + api_key=TEST_API_KEY, + api_base=TEST_API_BASE, + ) + + mock_cached.assert_not_called() + + def test_validate_environment_token_caching_path(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "cached-token" + mock_creds.valid = True + mock_creds.with_gdch_audience.return_value = mock_creds + + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ): + headers = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={ + "vertex_project": TEST_PROJECT, + "gdc_token_caching": True, + }, + api_key=TEST_API_KEY, + api_base=TEST_API_BASE, + ) + + assert headers["Authorization"] == "Bearer cached-token" + mock_creds.refresh.assert_not_called() + + def test_validate_environment_preserves_content_type_but_rebinds_quota_project(self): + config = GDCGeminiConfig() + headers = config.validate_environment( + headers={ + "Content-Type": "text/plain", + "x-goog-user-project": "projects/attacker", + }, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key="raw-token", + api_base=TEST_API_BASE, + ) + assert headers["Content-Type"] == "text/plain" + assert headers["x-goog-user-project"] == f"projects/{TEST_PROJECT}" + + @pytest.mark.parametrize( + "header_name", ["x-goog-user-project", "X-Goog-User-Project", "X-GOOG-USER-PROJECT"] + ) + def test_validate_environment_strips_caller_forwarded_quota_header(self, header_name): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "tok" + mock_creds.with_gdch_audience.return_value = mock_creds + preformed = f"{TEST_API_BASE}/v1/projects/deployment-proj/locations/us-central1/chat/completions" + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ): + headers = config.validate_environment( + headers={header_name: "projects/attacker"}, + model=TEST_MODEL, + messages=[], + optional_params={"vertex_project": "attacker-proj"}, + litellm_params={}, + api_key=TEST_API_KEY, + api_base=preformed, + ) + quota_values = [v for k, v in headers.items() if k.lower() == "x-goog-user-project"] + assert quota_values == ["projects/deployment-proj"] + + @pytest.mark.parametrize( + "bad", ["p/locations/l/chat/completions?", "a/b", "a?b", "a#b", "..", "a b", "a:b", "a%2Fb"] + ) + def test_get_complete_url_rejects_project_path_injection(self, bad): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="vertex_project must be a plain identifier"): + config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": bad, "vertex_location": TEST_LOCATION}, + litellm_params={}, + ) + + @pytest.mark.parametrize("bad", ["../../evil", "l/chat/completions", "l?x", ".."]) + def test_get_complete_url_rejects_location_path_injection(self, bad): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="vertex_location must be a plain identifier"): + config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": TEST_PROJECT, "vertex_location": bad}, + litellm_params={}, + ) + + @pytest.mark.parametrize("good", ["test-project", "us-central1", "123456", "proj_1", "MyProj-2"]) + def test_get_complete_url_accepts_valid_ids(self, good): + config = GDCGeminiConfig() + url = config.get_complete_url( + api_base=TEST_API_BASE, + api_key=None, + model=TEST_MODEL, + optional_params={"vertex_project": good, "vertex_location": good}, + litellm_params={}, + ) + assert url == f"{TEST_API_BASE}/v1/projects/{good}/locations/{good}/chat/completions" + + def test_validate_environment_rejects_project_path_injection(self): + config = GDCGeminiConfig() + with pytest.raises(Exception, match="vertex_project must be a plain identifier"): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={"vertex_project": "p/../admin"}, + litellm_params={}, + api_key="raw-token", + api_base=TEST_API_BASE, + ) + + def test_validate_environment_quota_header_bound_to_deployment_url(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "tok" + mock_creds.with_gdch_audience.return_value = mock_creds + preformed = f"{TEST_API_BASE}/v1/projects/deployment-proj/locations/us-central1/chat/completions" + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ): + headers = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={"vertex_project": "attacker-proj"}, + litellm_params={}, + api_key=TEST_API_KEY, + api_base=preformed, + ) + assert headers["x-goog-user-project"] == "projects/deployment-proj" + + def test_validate_environment_quota_header_pinned_to_preformed_url(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "tok" + mock_creds.with_gdch_audience.return_value = mock_creds + preformed = f"{TEST_API_BASE}/v1/projects/url-proj/locations/us-central1/chat/completions" + with patch( + "google.auth.load_credentials_from_dict", return_value=(mock_creds, None) + ): + headers = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={"vertex_project": "attacker-proj"}, + litellm_params={"vertex_project": "override-proj"}, + api_key=TEST_API_KEY, + api_base=preformed, + ) + assert headers["x-goog-user-project"] == "projects/url-proj" + + def test_transform_request(self): + config = GDCGeminiConfig() + data = config.transform_request( + model=TEST_MODEL, + messages=[{"role": "user", "content": "Hello"}], + optional_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + litellm_params={"ssl_verify": True}, + headers={}, + ) + assert data["model"] == "gemini-2.5-flash" + assert "vertex_project" not in data + assert "vertex_location" not in data + assert "ssl_verify" not in data + + def test_load_creds_from_key_ignores_file_paths(self, tmp_path): + config = GDCGeminiConfig() + creds_file = tmp_path / "service_account.json" + creds_file.write_text( + '{"type": "gdch_service_account", "project_id": "host-only-project"}' + ) + + creds, is_service_account = config._load_creds_from_key(str(creds_file)) + + assert creds is None + assert is_service_account is False + + def test_load_creds_from_key_rejects_non_gdch_credential_types(self): + config = GDCGeminiConfig() + external_account = ( + '{"type": "external_account", ' + '"token_url": "http://169.254.169.254/latest/api/token", ' + '"credential_source": {"url": "http://169.254.169.254/"}}' + ) + with patch( + "google.auth.load_credentials_from_dict", + return_value=(MagicMock(), None), + ) as mock_load: + with pytest.raises(ValueError, match="GDCH service account"): + config._load_creds_from_key(external_account) + mock_load.assert_not_called() + + def test_validate_environment_rejects_non_gdch_credential_without_refresh(self): + config = GDCGeminiConfig() + mock_creds = MagicMock() + mock_creds.token = "leaked-token" + mock_creds.with_gdch_audience.return_value = mock_creds + malicious = ( + '{"type": "external_account", ' + '"token_url": "http://169.254.169.254/latest/api/token"}' + ) + + with patch( + "google.auth.load_credentials_from_dict", + return_value=(mock_creds, None), + ) as mock_load, patch("requests.Session") as mock_session: + with pytest.raises( + Exception, match="Failed to load service account credentials" + ): + config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={"vertex_project": TEST_PROJECT}, + api_key=malicious, + api_base=TEST_API_BASE, + ) + + mock_load.assert_not_called() + mock_session.assert_not_called() + mock_creds.refresh.assert_not_called() + + def test_validate_environment_does_not_read_api_key_file_path(self, tmp_path): + config = GDCGeminiConfig() + creds_file = tmp_path / "service_account.json" + creds_file.write_text( + '{"type": "service_account", "project_id": "host-only-project"}' + ) + + headers = config.validate_environment( + headers={}, + model=TEST_MODEL, + messages=[], + optional_params={}, + litellm_params={ + "vertex_project": TEST_PROJECT, + "vertex_location": TEST_LOCATION, + }, + api_key=str(creds_file), + api_base=TEST_API_BASE, + ) + + assert headers["Authorization"] == f"Bearer {creds_file}" + assert headers["x-goog-user-project"] == f"projects/{TEST_PROJECT}" + + @pytest.mark.parametrize( + "val, env_value, default, expected", + [ + (True, None, True, True), + (False, "true", True, False), + ("literal", None, True, "literal"), + (None, None, True, True), + (None, None, False, False), + (None, "true", False, True), + (None, "1", False, True), + (None, "on", False, True), + (None, "false", True, False), + (None, "0", True, False), + (None, "off", True, False), + (None, "verbose", True, "verbose"), + ], + ) + def test_read_env_bool(self, monkeypatch, val, env_value, default, expected): + config = GDCGeminiConfig() + env_var = "GDC_TEST_FLAG" + if env_value is None: + monkeypatch.delenv(env_var, raising=False) + else: + monkeypatch.setenv(env_var, env_value) + assert config._read_env_bool(val, env_var, default=default) == expected + + def test_cached_fetch_token_keys_by_credential(self): + config = GDCGeminiConfig() + + def make_creds(token): + creds = MagicMock() + creds.with_gdch_audience.return_value = creds + creds.valid = True + creds.token = token + return creds + + creds_a = make_creds("token-a") + creds_b = make_creds("token-b") + + assert ( + config._cached_fetch_token(creds_a, TEST_API_BASE, True, api_key="key-a") + == "token-a" + ) + assert ( + config._cached_fetch_token(creds_b, TEST_API_BASE, True, api_key="key-b") + == "token-b" + ) + # same credential identity reuses the cached entry + config._cached_fetch_token(creds_a, TEST_API_BASE, True, api_key="key-a") + creds_a.with_gdch_audience.assert_called_once() + + def test_cached_fetch_token_refreshes_when_invalid(self): + config = GDCGeminiConfig() + creds = MagicMock() + creds.with_gdch_audience.return_value = creds + creds.valid = False + creds.token = "refreshed" + + with patch.object(config, "_fetch_auth") as mock_fetch: + token = config._cached_fetch_token( + creds, TEST_API_BASE, True, api_key="key" + ) + + assert token == "refreshed" + mock_fetch.assert_called_once() + + def test_init_sets_up_lock_and_cache(self): + config = GDCGeminiConfig() + assert config._gdch_creds_cache == {} + assert config._creds_lock is not None + + +class TestCompleteGDC: + @patch("litellm.main.base_llm_http_handler.completion") + def test_complete_gdc_resolves_key_and_base(self, mock_completion, monkeypatch): + from litellm.main import gdc_transformation + + mock_completion.return_value = MagicMock() + monkeypatch.setattr(litellm, "gdc_key", "resolved-key", raising=False) + monkeypatch.setattr( + litellm, "gdc_api_base", "https://resolved-base.com", raising=False + ) + monkeypatch.setattr(litellm, "api_base", None, raising=False) + + litellm.completion( + model="gdc/gemini-2.5-flash", + messages=[{"role": "user", "content": "hi"}], + vertex_project=TEST_PROJECT, + vertex_location=TEST_LOCATION, + ) + + assert mock_completion.called + _, kwargs = mock_completion.call_args + assert kwargs["custom_llm_provider"] == "gdc" + assert kwargs["api_key"] == "resolved-key" + assert kwargs["api_base"] == "https://resolved-base.com" + assert kwargs["provider_config"] is gdc_transformation + + @patch("litellm.main.base_llm_http_handler.completion") + def test_complete_gdc_prefers_gdc_api_base_over_global( + self, mock_completion, monkeypatch + ): + mock_completion.return_value = MagicMock() + monkeypatch.setattr(litellm, "gdc_key", "resolved-key", raising=False) + monkeypatch.setattr( + litellm, "gdc_api_base", "https://gdc-specific.com", raising=False + ) + monkeypatch.setattr( + litellm, "api_base", "https://other-provider.com", raising=False + ) + + litellm.completion( + model="gdc/gemini-2.5-flash", + messages=[{"role": "user", "content": "hi"}], + vertex_project=TEST_PROJECT, + vertex_location=TEST_LOCATION, + ) + + _, kwargs = mock_completion.call_args + assert kwargs["api_base"] == "https://gdc-specific.com" diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 6f9f26bf6dd..28b82cf035b 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -1345,6 +1345,48 @@ def test_pre_process_non_default_params(model, custom_llm_provider): } +@pytest.mark.parametrize( + "custom_llm_provider, expected", + [ + ("vertex_ai", True), + ("vertex_ai_beta", True), + ("gdc", True), + ("openai", False), + ("bedrock", False), + ("not_a_real_provider", False), + ], +) +def test_provider_supports_vertex_params(custom_llm_provider, expected): + from litellm.utils import _provider_supports_vertex_params + + assert _provider_supports_vertex_params(custom_llm_provider) is expected + + +@pytest.mark.parametrize( + "model, custom_llm_provider, should_keep", + [ + ("gemini-2.5-pro", "vertex_ai", True), + ("gemini-2.5-pro", "vertex_ai_beta", True), + ("gdc/gemini-2.5-flash", "gdc", True), + ("gpt-4o", "openai", False), + ], +) +def test_vertex_params_not_stripped_for_vertex_family( + model, custom_llm_provider, should_keep +): + optional_params = litellm.utils.get_optional_params( + model=model, + custom_llm_provider=custom_llm_provider, + vertex_project="my-project", + vertex_location="us-central1", + ) + assert ("vertex_project" in optional_params) is should_keep + assert ("vertex_location" in optional_params) is should_keep + if should_keep: + assert optional_params["vertex_project"] == "my-project" + assert optional_params["vertex_location"] == "us-central1" + + from litellm.utils import supports_function_calling From 6e023f7cf2f63b009408584bf16e3efcad73254f Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 17:45:57 -0700 Subject: [PATCH 64/79] fix(model_prices): apply claude-sonnet-5 introductory pricing through 2026-08-31 (#31917) * fix(model_prices): apply claude-sonnet-5 introductory pricing through 2026-08-31 Anthropic launched Sonnet 5 with introductory pricing of $2/$10 per million input/output tokens through August 31, 2026 (sticker price $3/$15 applies from September 1, 2026). Bedrock, Vertex AI, and Azure Foundry mirror the introductory rate. LiteLLM was charging the sticker price on all ten claude-sonnet-5 entries, over-billing by 50% during the introductory period. Update input, output, cache write (5m and 1h), and cache read costs on the base entries to the introductory rate, and keep the 10% cross-region premium on the us/eu/au/jp Bedrock inference profiles on top of it. Also add an anthropic-sonnet-5 entry to the dev proxy config. * test: document exact sticker prices to restore on 2026-09-01 --- ...odel_prices_and_context_window_backup.json | 100 +++++++++--------- litellm/proxy/dev_config.yaml | 4 + model_prices_and_context_window.json | 100 +++++++++--------- .../test_claude_sonnet_5_config.py | 41 ++++--- 4 files changed, 131 insertions(+), 114 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b3058bb4214..b249b951b8e 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1672,16 +1672,16 @@ "supports_minimal_reasoning_effort": true }, "anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1705,16 +1705,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "global.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1738,16 +1738,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1771,16 +1771,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1804,16 +1804,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1837,16 +1837,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "jp.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -2710,16 +2710,16 @@ "supports_vision": true }, "azure_ai/claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -10474,16 +10474,16 @@ "supports_web_search": true }, "claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "anthropic", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35210,16 +35210,16 @@ "supports_vision": true }, "vertex_ai/claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "vertex_ai-anthropic_models", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -42677,16 +42677,16 @@ } }, "vertex_ai/claude-sonnet-5@default": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "vertex_ai-anthropic_models", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, diff --git a/litellm/proxy/dev_config.yaml b/litellm/proxy/dev_config.yaml index 6078161c780..0dc90e658f2 100644 --- a/litellm/proxy/dev_config.yaml +++ b/litellm/proxy/dev_config.yaml @@ -28,6 +28,10 @@ model_list: litellm_params: model: anthropic/claude-opus-4-8 api_key: os.environ/ANTHROPIC_API_KEY + - model_name: anthropic-sonnet-5 + litellm_params: + model: anthropic/claude-sonnet-5 + api_key: os.environ/ANTHROPIC_API_KEY # ---------- Bedrock Invoke ---------- - model_name: bedrock-invoke-haiku-4-5 diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 6ab6f1bda46..9e9523193c7 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1672,16 +1672,16 @@ "supports_minimal_reasoning_effort": true }, "anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1705,16 +1705,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "global.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1738,16 +1738,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1771,16 +1771,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1804,16 +1804,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -1837,16 +1837,16 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "jp.anthropic.claude-sonnet-5": { - "cache_creation_input_token_cost": 4.125e-06, - "cache_creation_input_token_cost_above_1hr": 6.6e-06, - "cache_read_input_token_cost": 3.3e-07, - "input_cost_per_token": 3.3e-06, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, + "input_cost_per_token": 2.2e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.65e-05, + "output_cost_per_token": 1.1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -2710,16 +2710,16 @@ "supports_vision": true }, "azure_ai/claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -10474,16 +10474,16 @@ "supports_web_search": true }, "claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "anthropic", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -35384,16 +35384,16 @@ "supports_vision": true }, "vertex_ai/claude-sonnet-5": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "vertex_ai-anthropic_models", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -42909,16 +42909,16 @@ } }, "vertex_ai/claude-sonnet-5@default": { - "cache_creation_input_token_cost": 3.75e-06, - "cache_creation_input_token_cost_above_1hr": 6e-06, - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 3e-06, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, + "input_cost_per_token": 2e-06, "litellm_provider": "vertex_ai-anthropic_models", "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-05, + "output_cost_per_token": 1e-05, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, diff --git a/tests/test_litellm/test_claude_sonnet_5_config.py b/tests/test_litellm/test_claude_sonnet_5_config.py index 88a06aea95f..506ffa16597 100644 --- a/tests/test_litellm/test_claude_sonnet_5_config.py +++ b/tests/test_litellm/test_claude_sonnet_5_config.py @@ -76,12 +76,23 @@ def test_sonnet_5_pricing_and_capabilities(): assert info["max_output_tokens"] == 128000 assert info["max_tokens"] == 128000 - # Standard Sonnet pricing: $3 / $15 per MTok, with the 1.25x cache-write - # and 0.1x cache-read multipliers. - assert info["input_cost_per_token"] == 3e-06 - assert info["output_cost_per_token"] == 1.5e-05 - assert info["cache_creation_input_token_cost"] == 3.75e-06 - assert info["cache_read_input_token_cost"] == 3e-07 + # Introductory Sonnet 5 pricing through 2026-08-31: $2 / $10 per MTok, + # with the 1.25x cache-write and 0.1x cache-read multipliers. On + # 2026-09-01 flip these five fields back to the sticker rate, here and + # in both cost-map JSON files (all ten claude-sonnet-5 entries): + # input_cost_per_token: 3e-06 + # output_cost_per_token: 1.5e-05 + # cache_creation_input_token_cost: 3.75e-06 + # cache_creation_input_token_cost_above_1hr: 6e-06 + # cache_read_input_token_cost: 3e-07 + # Regional Bedrock profiles (us./eu./au./jp.) stay at 1.1x those values: + # 3.3e-06 / 1.65e-05 / 4.125e-06 / 6.6e-06 / 3.3e-07 (see + # test_sonnet_5_bedrock_regional_pricing below). + assert info["input_cost_per_token"] == 2e-06 + assert info["output_cost_per_token"] == 1e-05 + assert info["cache_creation_input_token_cost"] == 2.5e-06 + assert info["cache_creation_input_token_cost_above_1hr"] == 4e-06 + assert info["cache_read_input_token_cost"] == 2e-07 # gen-5 adaptive-thinking profile: effort-driven, no sampling params, no # assistant prefill. @@ -102,16 +113,18 @@ def test_sonnet_5_bedrock_regional_pricing(): model_data = _load_root_cost_map() base_pricing = { - "input_cost_per_token": 3e-06, - "output_cost_per_token": 1.5e-05, - "cache_creation_input_token_cost": 3.75e-06, - "cache_read_input_token_cost": 3e-07, + "input_cost_per_token": 2e-06, + "output_cost_per_token": 1e-05, + "cache_creation_input_token_cost": 2.5e-06, + "cache_creation_input_token_cost_above_1hr": 4e-06, + "cache_read_input_token_cost": 2e-07, } regional_pricing = { - "input_cost_per_token": 3.3e-06, - "output_cost_per_token": 1.65e-05, - "cache_creation_input_token_cost": 4.125e-06, - "cache_read_input_token_cost": 3.3e-07, + "input_cost_per_token": 2.2e-06, + "output_cost_per_token": 1.1e-05, + "cache_creation_input_token_cost": 2.75e-06, + "cache_creation_input_token_cost_above_1hr": 4.4e-06, + "cache_read_input_token_cost": 2.2e-07, } expected = { From 8ce6b4d712dcc0486a8b23fdb0ead55097f5bfc1 Mon Sep 17 00:00:00 2001 From: yucheng-berri Date: Wed, 1 Jul 2026 17:58:31 -0700 Subject: [PATCH 65/79] fix(proxy): tighten role gating on /get/config/callbacks response (#31745) The handler returned decrypted callback environment values and alerting routing values verbatim to callers who were not full PROXY_ADMIN. Gate those on full-admin role, matching the posture used on the sibling config-inspection endpoints. Non-sensitive routing fields (host / base URL / port style values) stay visible so the UI can still label which integration is wired up. Full PROXY_ADMIN sees everything unchanged so the edit form round-trips on save. Resolves LIT-4115. --- litellm/proxy/common_utils/callback_utils.py | 17 +- litellm/proxy/proxy_server.py | 64 +++++- tests/proxy_unit_tests/test_proxy_server.py | 12 +- .../proxy/proxy_server/test_routes_config.py | 216 ++++++++++++++++++ tests/test_litellm/proxy/test_proxy_server.py | 20 +- .../test_router_retry_policy_update.py | 8 +- 6 files changed, 315 insertions(+), 22 deletions(-) diff --git a/litellm/proxy/common_utils/callback_utils.py b/litellm/proxy/common_utils/callback_utils.py index 573763d6627..c644ecc3dae 100644 --- a/litellm/proxy/common_utils/callback_utils.py +++ b/litellm/proxy/common_utils/callback_utils.py @@ -611,10 +611,17 @@ def _transform_callback_vars(metadata: Any, transform: Callable[[str, Any], Any] return out -def _is_sensitive_callback_var(key: str) -> bool: - """Match codebase precedent: only credential-bearing fields get encrypted; - routing/identifier fields (host, base_url, project, region) stay plain.""" - if key in _EXTRA_SENSITIVE_CALLBACK_KEYS: +def is_sensitive_callback_key( + key: str, + extra: Optional[set[str]] = None, +) -> bool: + """Return ``True`` if ``key`` is present in ``extra`` (checked as-is), or + if its lowercase form is in ``_EXTRA_SENSITIVE_CALLBACK_KEYS``, or if + ``_CALLBACK_VAR_MASKER.is_sensitive_key`` matches it. + """ + if extra and key in extra: + return True + if key.lower() in _EXTRA_SENSITIVE_CALLBACK_KEYS: return True return _CALLBACK_VAR_MASKER.is_sensitive_key(key) @@ -622,7 +629,7 @@ def _is_sensitive_callback_var(key: str) -> bool: def _encrypt_if_plaintext(key: str, value: Any) -> Any: if not isinstance(value, str) or not value: return value - if not _is_sensitive_callback_var(key): + if not is_sensitive_callback_key(key): return value if value.startswith(_CALLBACK_VAR_ENCRYPTED_PREFIX): # Already encrypted — round-tripping ciphertext (e.g. UI Edit Settings diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index c85faeba1a6..9a338712187 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -102,6 +102,7 @@ from litellm.proxy._types import ( ) from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec from litellm.proxy.common_utils.callback_utils import ( + is_sensitive_callback_key, normalize_callback_names, process_callback, ) @@ -14310,6 +14311,50 @@ async def create_config_audit_log( ) +_EXTRA_SECRET_CALLBACK_ENV_VARS = frozenset( + { + "GALILEO_USERNAME", + "GENERIC_LOGGER_HEADERS", + "OTEL_HEADERS", + "SLACK_WEBHOOK_URL", + "SMTP_USERNAME", + } +) + + +def _redact_callback_env_vars(env_vars: dict[str, Optional[str]]) -> dict[str, Optional[str]]: + """Return a copy of ``env_vars`` with values for keys classified as + sensitive by ``is_sensitive_callback_key`` replaced with ``"REDACTED"``. + ``None`` values pass through unchanged. + """ + return { + key: ( + "REDACTED" + if value is not None and is_sensitive_callback_key(key, extra=_EXTRA_SECRET_CALLBACK_ENV_VARS) + else value + ) + for key, value in env_vars.items() + } + + +def _apply_callback_role_gate(entries: list, is_full_admin: bool) -> list: + if is_full_admin: + return entries + return [{**entry, "variables": _redact_callback_env_vars(entry.get("variables") or {})} for entry in entries] + + +def _apply_alerting_env_role_gate(env_vars: dict, is_full_admin: bool) -> dict: + if is_full_admin: + return mask_sensitive_keys(env_vars, _ALERTING_SENSITIVE_VARS) + return _redact_callback_env_vars(env_vars) + + +def _apply_webhook_role_gate(webhook_map, is_full_admin: bool): + if is_full_admin or not isinstance(webhook_map, dict): + return webhook_map + return {alert_type: "REDACTED" for alert_type in webhook_map} + + @router.get( "/config/field/info", tags=["config.yaml"], @@ -14720,7 +14765,9 @@ async def delete_callback( include_in_schema=False, dependencies=[Depends(user_api_key_auth)], ) -async def get_config(): +async def get_config( + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): """ For Admin UI - allows admin to view config via UI # return the callbacks and the env variables for the callback @@ -14735,6 +14782,8 @@ async def get_config(): _general_settings = config_data.get("general_settings", {}) environment_variables = config_data.get("environment_variables", {}) + is_full_admin = user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN + _success_callbacks = _litellm_settings.get("success_callback", []) _failure_callbacks = _litellm_settings.get("failure_callback", []) _success_and_failure_callbacks = _litellm_settings.get("callbacks", []) @@ -14776,6 +14825,8 @@ async def get_config(): for _callback in _success_and_failure_callbacks: _data_to_return.append(process_callback(_callback, "success_and_failure", environment_variables)) + _data_to_return = _apply_callback_role_gate(_data_to_return, is_full_admin) + # Check if slack alerting is on _alerting = _general_settings.get("alerting", []) alerting_data = [] @@ -14787,11 +14838,13 @@ async def get_config(): _var: (value if (value := environment_variables.get(_var)) is not None else os.getenv(_var)) for _var in _slack_vars } - _slack_env_vars = mask_sensitive_keys(_slack_env_vars, _ALERTING_SENSITIVE_VARS) + _slack_env_vars = _apply_alerting_env_role_gate(_slack_env_vars, is_full_admin) _alerting_types = proxy_logging_obj.slack_alerting_instance.alert_types _all_alert_types = proxy_logging_obj.slack_alerting_instance._all_possible_alert_types() - _alerts_to_webhook = proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url + _alerts_to_webhook = _apply_webhook_role_gate( + proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url, is_full_admin + ) alerting_data.append( { "name": "slack", @@ -14811,8 +14864,9 @@ async def get_config(): "EMAIL_LOGO_URL", "EMAIL_SUPPORT_CONTACT", ] - _email_env_vars = {_var: environment_variables.get(_var) for _var in _email_vars} - _email_env_vars = mask_sensitive_keys(_email_env_vars, _ALERTING_SENSITIVE_VARS) + _email_env_vars = _apply_alerting_env_role_gate( + {_var: environment_variables.get(_var) for _var in _email_vars}, is_full_admin + ) alerting_data.append( { diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index 921fbfa320f..212f7772cad 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -2844,7 +2844,9 @@ async def test_get_config_callbacks_with_all_types(client_no_auth): async def test_get_config_callbacks_environment_variables(client_no_auth): """ Test that /get/config/callbacks correctly includes environment variables - for each callback type. Values are returned as-is from the config (no decryption). + for each callback type. Under ``client_no_auth`` the resolved role is + not ``PROXY_ADMIN``, so values matched by the redaction helper come back + as ``"REDACTED"`` and other values pass through verbatim. """ from litellm.proxy.proxy_server import ProxyConfig @@ -2886,12 +2888,11 @@ async def test_get_config_callbacks_environment_variables(client_no_auth): assert langfuse_callback["type"] == "success" assert "variables" in langfuse_callback - # Verify langfuse env vars are present (values returned as-is, no decryption) langfuse_vars = langfuse_callback["variables"] assert "LANGFUSE_PUBLIC_KEY" in langfuse_vars - assert langfuse_vars["LANGFUSE_PUBLIC_KEY"] == "test-public-key" + assert langfuse_vars["LANGFUSE_PUBLIC_KEY"] == "REDACTED" assert "LANGFUSE_SECRET_KEY" in langfuse_vars - assert langfuse_vars["LANGFUSE_SECRET_KEY"] == "test-secret-key" + assert langfuse_vars["LANGFUSE_SECRET_KEY"] == "REDACTED" assert "LANGFUSE_HOST" in langfuse_vars assert langfuse_vars["LANGFUSE_HOST"] == "https://cloud.langfuse.com" @@ -2901,14 +2902,13 @@ async def test_get_config_callbacks_environment_variables(client_no_auth): assert otel_callback["type"] == "success_and_failure" assert "variables" in otel_callback - # Verify otel env vars are present otel_vars = otel_callback["variables"] assert "OTEL_EXPORTER" in otel_vars assert otel_vars["OTEL_EXPORTER"] == "otlp" assert "OTEL_ENDPOINT" in otel_vars assert otel_vars["OTEL_ENDPOINT"] == "http://localhost:4317" assert "OTEL_HEADERS" in otel_vars - assert otel_vars["OTEL_HEADERS"] == "key=value" + assert otel_vars["OTEL_HEADERS"] == "REDACTED" @pytest.mark.asyncio diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_config.py b/tests/test_litellm/proxy/proxy_server/test_routes_config.py index df14dc5b5dc..4ac6fc46a61 100644 --- a/tests/test_litellm/proxy/proxy_server/test_routes_config.py +++ b/tests/test_litellm/proxy/proxy_server/test_routes_config.py @@ -741,6 +741,222 @@ def test_get_config_callbacks_internal_error(client, auth_as, mock_prisma, monke ) +_CALLBACK_ENV_FIXTURE = { + "LANGFUSE_PUBLIC_KEY": "pk-public-1234567890", + "LANGFUSE_SECRET_KEY": "sk-langfuse-super-secret", + "LANGFUSE_HOST": "https://cloud.langfuse.com", + "DD_API_KEY": "dd-super-secret-api-key", + "DD_SITE": "datadoghq.com", + "OTEL_HEADERS": "Authorization=Bearer otel-super-secret", + "OTEL_ENDPOINT": "https://otlp.example.com", + "SLACK_WEBHOOK_URL": "https://hooks.slack.com/services/T000/B000/SLACK-WEBHOOK-FIXTURE-SECRET", +} + + +def _install_callbacks_config(monkeypatch, mock_prisma): + from litellm.proxy import proxy_server as ps + + _install_litellm_config(mock_prisma) + monkeypatch.setattr(ps, "prisma_client", mock_prisma) + monkeypatch.setattr(ps, "llm_router", None) + + fake_proxy_config = MagicMock() + fake_proxy_config.get_config = AsyncMock( + return_value={ + "litellm_settings": {"success_callback": ["langfuse", "datadog", "otel"]}, + "general_settings": {"alerting": ["slack"]}, + "environment_variables": dict(_CALLBACK_ENV_FIXTURE), + } + ) + monkeypatch.setattr(ps, "proxy_config", fake_proxy_config) + + +def _callback_variables(body: dict, name: str) -> dict: + return next( + cb["variables"] for cb in body["callbacks"] if cb["name"] == name + ) + + +def test_get_config_callbacks_redacts_secret_env_vars_for_view_only_admin( + client, auth_as, mock_prisma, monkeypatch +): + from litellm.proxy._types import LitellmUserRoles + + _install_callbacks_config(monkeypatch, mock_prisma) + + with auth_as(LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY): + response = client.get("/get/config/callbacks") + assert response.status_code == 200 + body = response.json() + + for secret in ( + _CALLBACK_ENV_FIXTURE["LANGFUSE_SECRET_KEY"], + _CALLBACK_ENV_FIXTURE["DD_API_KEY"], + _CALLBACK_ENV_FIXTURE["OTEL_HEADERS"], + _CALLBACK_ENV_FIXTURE["LANGFUSE_PUBLIC_KEY"], + ): + assert secret not in response.text + + langfuse_vars = _callback_variables(body, "langfuse") + assert langfuse_vars["LANGFUSE_PUBLIC_KEY"] == "REDACTED" + assert langfuse_vars["LANGFUSE_SECRET_KEY"] == "REDACTED" + assert langfuse_vars["LANGFUSE_HOST"] == _CALLBACK_ENV_FIXTURE["LANGFUSE_HOST"] + + datadog_vars = _callback_variables(body, "datadog") + assert datadog_vars["DD_API_KEY"] == "REDACTED" + assert datadog_vars["DD_SITE"] == _CALLBACK_ENV_FIXTURE["DD_SITE"] + + otel_vars = _callback_variables(body, "otel") + assert otel_vars["OTEL_HEADERS"] == "REDACTED" + assert otel_vars["OTEL_ENDPOINT"] == _CALLBACK_ENV_FIXTURE["OTEL_ENDPOINT"] + + +def test_get_config_callbacks_full_admin_still_sees_secret_env_vars( + client, auth_as, mock_prisma, monkeypatch +): + from litellm.proxy._types import LitellmUserRoles + + _install_callbacks_config(monkeypatch, mock_prisma) + + with auth_as(LitellmUserRoles.PROXY_ADMIN): + response = client.get("/get/config/callbacks") + assert response.status_code == 200 + body = response.json() + + langfuse_vars = _callback_variables(body, "langfuse") + assert langfuse_vars["LANGFUSE_SECRET_KEY"] == _CALLBACK_ENV_FIXTURE["LANGFUSE_SECRET_KEY"] + assert langfuse_vars["LANGFUSE_PUBLIC_KEY"] == _CALLBACK_ENV_FIXTURE["LANGFUSE_PUBLIC_KEY"] + + datadog_vars = _callback_variables(body, "datadog") + assert datadog_vars["DD_API_KEY"] == _CALLBACK_ENV_FIXTURE["DD_API_KEY"] + + otel_vars = _callback_variables(body, "otel") + assert otel_vars["OTEL_HEADERS"] == _CALLBACK_ENV_FIXTURE["OTEL_HEADERS"] + + +def test_get_config_callbacks_redacts_slack_webhook_urls_for_view_only_admin( + client, auth_as, mock_prisma, monkeypatch +): + from litellm.proxy import proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + _install_callbacks_config(monkeypatch, mock_prisma) + + webhooks = { + "spend_reports": "https://hooks.slack.com/services/T000/B000/SPEND-WEBHOOK-SECRET", + "budget_alerts": "https://hooks.slack.com/services/T000/B111/BUDGET-WEBHOOK-SECRET", + } + monkeypatch.setattr( + ps.proxy_logging_obj.slack_alerting_instance, + "alert_to_webhook_url", + webhooks, + raising=False, + ) + + def _slack_block(body): + return next(a for a in body["alerts"] if a["name"] == "slack") + + with auth_as(LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY): + view_resp = client.get("/get/config/callbacks") + assert view_resp.status_code == 200 + for url in webhooks.values(): + assert url not in view_resp.text + assert _CALLBACK_ENV_FIXTURE["SLACK_WEBHOOK_URL"] not in view_resp.text + view_slack = _slack_block(view_resp.json()) + assert view_slack["alerts_to_webhook"] == { + "spend_reports": "REDACTED", + "budget_alerts": "REDACTED", + } + assert view_slack["variables"]["SLACK_WEBHOOK_URL"] == "REDACTED" + + with auth_as(LitellmUserRoles.PROXY_ADMIN): + admin_resp = client.get("/get/config/callbacks") + assert admin_resp.status_code == 200 + admin_slack = _slack_block(admin_resp.json()) + assert admin_slack["alerts_to_webhook"] == webhooks + assert admin_slack["variables"]["SLACK_WEBHOOK_URL"] != "REDACTED" + + +def test_redact_callback_env_vars_helper_handles_none_and_non_secret_keys(): + from litellm.proxy import proxy_server as ps + + out = ps._redact_callback_env_vars( + { + "LANGFUSE_SECRET_KEY": "sk-leak", + "LANGFUSE_HOST": "https://cloud.langfuse.com", + "DD_API_KEY": None, + "GALILEO_USERNAME": "galileo-user-1234", + "GENERIC_LOGGER_HEADERS": "Authorization=Bearer x", + "GCS_PATH_SERVICE_ACCOUNT": "/etc/secrets/gcs.json", + "SLACK_WEBHOOK_URL": "https://hooks.slack.com/services/T/B/token", + "SMTP_USERNAME": "smtp-user-1234", + } + ) + assert out == { + "LANGFUSE_SECRET_KEY": "REDACTED", + "LANGFUSE_HOST": "https://cloud.langfuse.com", + "DD_API_KEY": None, + "GALILEO_USERNAME": "REDACTED", + "GENERIC_LOGGER_HEADERS": "REDACTED", + "GCS_PATH_SERVICE_ACCOUNT": "REDACTED", + "SLACK_WEBHOOK_URL": "REDACTED", + "SMTP_USERNAME": "REDACTED", + } + + +def test_get_config_callbacks_redacts_email_alerting_vars_for_view_only_admin( + client, auth_as, mock_prisma, monkeypatch +): + from litellm.proxy import proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + _install_litellm_config(mock_prisma) + monkeypatch.setattr(ps, "prisma_client", mock_prisma) + monkeypatch.setattr(ps, "llm_router", None) + + fake_proxy_config = MagicMock() + fake_proxy_config.get_config = AsyncMock( + return_value={ + "litellm_settings": {"success_callback": []}, + "general_settings": {"alerting": ["email"]}, + "environment_variables": { + "SMTP_HOST": "smtp.resend.com", + "SMTP_PORT": "587", + "SMTP_USERNAME": "smtp-user-fixture-1234", + "SMTP_PASSWORD": "smtp-password-fixture-1234", + "SMTP_SENDER_EMAIL": "alerts@example.com", + "TEST_EMAIL_ADDRESS": "admin@example.com", + "EMAIL_LOGO_URL": "https://example.com/logo.png", + "EMAIL_SUPPORT_CONTACT": "support@example.com", + }, + } + ) + monkeypatch.setattr(ps, "proxy_config", fake_proxy_config) + + def _email_block(body): + return next(a for a in body["alerts"] if a["name"] == "email") + + with auth_as(LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY): + view_resp = client.get("/get/config/callbacks") + assert view_resp.status_code == 200 + for secret in ("smtp-user-fixture-1234", "smtp-password-fixture-1234"): + assert secret not in view_resp.text + view_email = _email_block(view_resp.json())["variables"] + assert view_email["SMTP_PASSWORD"] == "REDACTED" + assert view_email["SMTP_USERNAME"] == "REDACTED" + assert view_email["SMTP_HOST"] == "smtp.resend.com" + assert view_email["SMTP_PORT"] == "587" + assert view_email["SMTP_SENDER_EMAIL"] == "alerts@example.com" + + with auth_as(LitellmUserRoles.PROXY_ADMIN): + admin_resp = client.get("/get/config/callbacks") + assert admin_resp.status_code == 200 + admin_email = _email_block(admin_resp.json())["variables"] + assert admin_email["SMTP_USERNAME"] == "smtp-user-fixture-1234" + assert admin_email["SMTP_PASSWORD"] != "REDACTED" + assert admin_email["SMTP_HOST"] == "smtp.resend.com" + + # --------------------------------------------------------------------------- # GET /config/yaml # --------------------------------------------------------------------------- diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 68122bbba3b..533c37e690e 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -896,7 +896,9 @@ def test_get_config_custom_callback_api_env_vars(monkeypatch): # Bypass auth dependency original_overrides = app.dependency_overrides.copy() - app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) client = TestClient(app) try: @@ -950,7 +952,9 @@ def test_get_config_returns_email_settings(monkeypatch): monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data)) original_overrides = app.dependency_overrides.copy() - app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) client = TestClient(app) try: @@ -1007,7 +1011,9 @@ def test_get_config_returns_slack_webhook(monkeypatch): monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data)) original_overrides = app.dependency_overrides.copy() - app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) client = TestClient(app) try: @@ -1061,7 +1067,9 @@ def test_get_config_cleared_slack_webhook_not_overridden_by_os_env(monkeypatch): monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data)) original_overrides = app.dependency_overrides.copy() - app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) client = TestClient(app) try: @@ -5205,7 +5213,9 @@ def test_get_config_normalizes_string_callbacks(monkeypatch): monkeypatch.setattr(proxy_config, "get_config", AsyncMock(return_value=config_data)) original_overrides = app.dependency_overrides.copy() - app.dependency_overrides[user_api_key_auth] = lambda: MagicMock() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) client = TestClient(app) try: diff --git a/tests/test_litellm/test_router_retry_policy_update.py b/tests/test_litellm/test_router_retry_policy_update.py index 450391fd503..3fc6bc71b84 100644 --- a/tests/test_litellm/test_router_retry_policy_update.py +++ b/tests/test_litellm/test_router_retry_policy_update.py @@ -273,7 +273,13 @@ async def test_config_update_persists_and_reads_back_retry_policy(monkeypatch): assert isinstance(router.retry_policy, RetryPolicy) assert router.retry_policy.RateLimitErrorRetries == 7 - read_back = (await proxy_server.get_config())["router_settings"]["retry_policy"] + read_back = ( + await proxy_server.get_config( + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234" + ) + ) + )["router_settings"]["retry_policy"] assert read_back.BadRequestErrorRetries == 5 assert read_back.TimeoutErrorRetries == 3 assert read_back.RateLimitErrorRetries == 7 From bd9db3691ed7f6d37f4c7cb85243113c20bc2821 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 18:44:57 -0700 Subject: [PATCH 66/79] chore(lint): remove dead E501 config, fix stale blame-ignore SHAs, note 120 line width (#31927) * chore(lint): remove dead E501 config, fix stale blame-ignore SHAs, note 120 width in CLAUDE.md E501 sat in both lint.ignore and lint.extend-select in ruff.toml; ignore wins, so no line length was linted at all (verified: a 130-char line passes ruff check while T201 fires). Remove it from both lists so the config tells the truth: the formatter's wrap width is the only line-length control, matching how the repo has actually behaved since E501 was ignored in Oct 2024 .git-blame-ignore-revs listed the pre-squash PR-head SHAs for the two ruff reformat commits (#31317, #31518), which never landed on the branch, so git blame ignored nothing. Replace them with the squash-merge SHAs that are actually in history Also document in CLAUDE.md that the line length is 120 (ruff.toml), not 88, so agents stop wrapping to the old Black width * fix: make CLAUDE.md more concise * fix: make the guideline more clear --- .git-blame-ignore-revs | 4 ++-- CLAUDE.md | 2 ++ Makefile | 2 +- ruff.toml | 4 ++-- 4 files changed, 7 insertions(+), 5 deletions(-) diff --git a/.git-blame-ignore-revs b/.git-blame-ignore-revs index 7e705ec4f8f..2527239b904 100644 --- a/.git-blame-ignore-revs +++ b/.git-blame-ignore-revs @@ -13,7 +13,7 @@ 7edf3a9cb55548b143df1692f4ed7c4681d7fcf7 # style: reformat litellm/ with ruff format (#31317) -430b5b8f1b12dc261a49fda99ac5d1b22381a428 +17bfd415aeb5a57fb646b5cc67da1c730aa7c50b # style: unify ruff format width on 120 (#31518) -3dfbeabe626d203ac9de86024519d9a96c484ce4 +48b5a5a0cc5a694a11219416ee0b6eb6e620e74e diff --git a/CLAUDE.md b/CLAUDE.md index a492aabd02d..7d9a6367f18 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -33,6 +33,8 @@ If you ever make public-facing PR descriptions, comments, issues, commit message Don't hesitate to use values in .env to get needed API keys and other secrets, as long as you never add them to conversation history, commit them, or include them in GitHub issues / PRs +Python max line length is 120, not 88 + Run tests before you commit. Also, run `make pre-commit` right before each commit, which generates types (as needed) and formats/lints your code. Any errors found must be fixed. It only runs when there are staged frontend and/or backend changes and calculates violations, generates types, etc. based on the worktree, so stage what you need or stash/delete unwanted files in litellm/ or ui/ (where backend and frontend lint run, respectively) before running it. If it fails because dashboard api types are stale, it already regenerated them for you. You just need to stage the schema.d.ts, re-run `make pre-commit` to confirm it passes, and commit When you fix violations gated by `ruff-strict-budget.json`, `type-discipline-budget.json`, or `basedpyright-code-budget.json`, run `make lint-budget-update` and commit the lowered limits so the ceilings ratchet down instead of leaving stale headroom. It measures the working tree, so it must contain exactly the fixes you're committing diff --git a/Makefile b/Makefile index c3fa21c156c..2cc4ec3e45a 100644 --- a/Makefile +++ b/Makefile @@ -88,7 +88,7 @@ install-hooks: # Formatting # Wrap width is ruff.toml's single source of truth (line-length = 120), shared by the -# formatter, E501, and the import sorter so there's no 88-vs-120 split to reconcile. +# formatter and the import sorter so there's no 88-vs-120 split to reconcile. format: install-dev cd litellm && $(UV_RUN) ruff format --exclude '/enterprise/' . && cd .. diff --git a/ruff.toml b/ruff.toml index a09bc663ff1..2ea9d7260fb 100644 --- a/ruff.toml +++ b/ruff.toml @@ -1,5 +1,5 @@ -lint.ignore = ["F405", "E402", "E501", "F403"] -lint.extend-select = ["E501", "T20", "PGH004", "RUF008", "RUF009", "RUF100"] +lint.ignore = ["F405", "E402", "F403"] +lint.extend-select = ["T20", "PGH004", "RUF008", "RUF009", "RUF100"] # RUF100 (unused-noqa) only knows the rules enabled in THIS config, so it would strip # `# noqa` directives that protect rules enforced elsewhere. List those codes as external # so RUF100 leaves their directives alone: the strict gate (ruff-strict.toml) and upstream From 85f924148a299903fadf568e40b53f8b888016ae Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 19:08:17 -0700 Subject: [PATCH 67/79] fix(bedrock/converse): drop toolSpec.strict for Opus 4.7/4.8 (#31582) (#31923) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix(bedrock/converse): drop toolSpec.strict for Opus 4.7/4.8 Bedrock Converse routes Claude Opus 4.7/4.8 through an Anthropic-compatible validator that maps toolSpec to the native tool shape and rejects the extra `strict` key with `tools.N.custom.strict: Extra inputs are not permitted`, even though Anthropic's native API accepts `strict` as a top-level tool field for the same models. Sonnet 4.5/4.6 and Opus <=4.6 accept `toolSpec.strict` unchanged. The existing gate `get_bedrock_base_model(model).startswith("anthropic")` (introduced in #29814 to forward `strict` for Claude on Bedrock Converse) is too broad and regressed Opus 4.7/4.8 callers — see #31582. Replace the inline check with a small `bedrock_converse_supports_strict_tools` helper that excludes the Opus 4.7/4.8 family from strict forwarding. All other Anthropic models on Bedrock keep the existing behavior. Closes #31582. * fix(bedrock/converse): move strict-tools regression to a clean test file The original regression test was added to test_litellm_core_utils_prompt_templates_factory.py, which has pre-existing ruff-format violations throughout (multi-line asserts that fit on one line). The lint workflow runs `ruff format --check` on changed files only, so touching that file surfaces those pre-existing violations and fails CI for unrelated reasons. Move the #31582 regression coverage into a new dedicated test file so the format check stays green. Also collapses the helper's `not any(...)` onto a single line to satisfy ruff format. Covers: #31582 * refactor(bedrock/converse): drive strict-tools gate from model cost map Replace the hardcoded Opus 4.7/4.8 pattern list with a bedrock_converse_supports_strict_tools flag on the affected entries in model_prices_and_context_window.json, resolved via get_model_info with a local cost map fallback, so future models with the same restriction only need a JSON update * chore: revert unrelated credential_migration.py reformat --------- Co-authored-by: ly-wang19 --- .../prompt_templates/factory.py | 9 +- litellm/llms/bedrock/common_utils.py | 47 ++++++++ ...odel_prices_and_context_window_backup.json | 11 ++ litellm/types/utils.py | 1 + litellm/utils.py | 1 + model_prices_and_context_window.json | 11 ++ ...edrock_converse_strict_tools_opus_47_48.py | 107 ++++++++++++++++++ tests/test_litellm/test_utils.py | 1 + 8 files changed, 185 insertions(+), 3 deletions(-) create mode 100644 tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index c2448430387..c1635158d3b 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -5035,15 +5035,18 @@ def _bedrock_tools_pt(tools: List, model: Optional[str] = None) -> List[BedrockT ] """ from litellm.llms.bedrock.common_utils import ( - get_bedrock_base_model, + bedrock_converse_supports_strict_tools, normalize_json_schema_custom_types_to_object, ) from litellm.litellm_core_utils.prompt_templates.common_utils import unpack_defs _valid_json_schema_root_types = frozenset(("array", "boolean", "integer", "null", "number", "object", "string")) # Only Claude on Bedrock honours strict tool schemas; other families - # (Nova, Llama, GPT-OSS) reject the strict field outright. - supports_strict_tools = bool(model and get_bedrock_base_model(model).startswith("anthropic")) + # (Nova, Llama, GPT-OSS) reject the strict field outright. Opus 4.7/4.8 + # also reject `strict` on Bedrock Converse (see #31582) — their validator + # maps toolSpec to the native Anthropic tool shape, which has no strict + # field, even though Anthropic's native API accepts it as a top-level key. + supports_strict_tools = bool(model and bedrock_converse_supports_strict_tools(model)) tool_block_list: List[BedrockToolBlock] = [] for tool_idx, tool in enumerate(tools): # Check if tool is already a BedrockToolBlock (e.g., systemTool for Nova grounding) diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index 467e1050c99..df432a4d7e3 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -4,9 +4,11 @@ from __future__ import annotations Common utilities used across bedrock chat/embedding/image generation """ +import contextlib import functools import json import os +import re from typing import ( TYPE_CHECKING, Any, @@ -718,6 +720,51 @@ def is_claude_4_5_on_bedrock(model: str) -> bool: return any(pattern in model_lower for pattern in claude_4_5_patterns) +_BEDROCK_MODEL_VERSION_SUFFIX_RE = re.compile(r"-v\d+(?::\d+)?$") + + +def bedrock_converse_supports_strict_tools(model: str) -> bool: + """ + Whether ``toolSpec.strict`` can be forwarded to Bedrock Converse for ``model``. + + Non-Anthropic Bedrock families (Nova, Llama, GPT-OSS) reject the field + outright. Anthropic models forward it unless their entry in + ``model_prices_and_context_window.json`` sets + ``bedrock_converse_supports_strict_tools: false`` — Bedrock routes those + (Opus 4.7/4.8, see #31582) through a stricter validator that rejects the + ``strict`` key on ``toolSpec`` even though Anthropic's native API accepts + it as a top-level tool field. + """ + base = get_bedrock_base_model(model) + if not base.startswith("anthropic"): + return False + flag = _get_bedrock_converse_strict_tools_flag(base) + return flag if flag is not None else True + + +def _get_bedrock_converse_strict_tools_flag(base_model: str) -> Optional[bool]: + candidates = dict.fromkeys((base_model, _BEDROCK_MODEL_VERSION_SUFFIX_RE.sub("", base_model))) + for candidate in candidates: + with contextlib.suppress(Exception): + model_info = get_cached_model_info()( + model=candidate, + custom_llm_provider="bedrock", + ) + + flag = model_info.get("bedrock_converse_supports_strict_tools") + if isinstance(flag, bool): + return flag + + model_cost_key = model_info.get("key") + if isinstance(model_cost_key, str): + local_flag = ( + _get_local_model_cost_map().get(model_cost_key, {}).get("bedrock_converse_supports_strict_tools") + ) + if isinstance(local_flag, bool): + return local_flag + return None + + def normalize_bedrock_opus_output_config_effort(model: str, output_config: Any) -> None: """ Normalize Anthropic ``output_config.effort`` values for Bedrock Opus ids. diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index b249b951b8e..1a45731e915 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1154,6 +1154,7 @@ "bedrock_output_config_effort_ceiling": "max" }, "anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1203,6 +1204,7 @@ "supports_output_config": true }, "global.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1237,6 +1239,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1271,6 +1274,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1305,6 +1309,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1471,6 +1476,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1505,6 +1511,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "global.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1539,6 +1546,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1573,6 +1581,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1607,6 +1616,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1641,6 +1651,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "jp.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "cache_creation_input_token_cost": 6.875e-06, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 0e2a6b24806..997498803ac 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -152,6 +152,7 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_output_config: Optional[bool] supports_image_size: Optional[bool] bedrock_output_config_effort_ceiling: Optional[Literal["low", "medium", "high", "max", "xhigh"]] + bedrock_converse_supports_strict_tools: Optional[bool] class SearchContextCostPerQuery(TypedDict, total=False): diff --git a/litellm/utils.py b/litellm/utils.py index 226b94913b5..b5f77d75b93 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -5465,6 +5465,7 @@ def _get_model_info_helper( supports_xhigh_reasoning_effort=_model_info.get("supports_xhigh_reasoning_effort", None), supports_max_reasoning_effort=_model_info.get("supports_max_reasoning_effort", None), bedrock_output_config_effort_ceiling=_model_info.get("bedrock_output_config_effort_ceiling", None), + bedrock_converse_supports_strict_tools=_model_info.get("bedrock_converse_supports_strict_tools", None), supports_computer_use=_model_info.get("supports_computer_use", None), search_context_cost_per_query=_model_info.get("search_context_cost_per_query", None), web_search_billing_unit=_model_info.get("web_search_billing_unit", None), diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 9e9523193c7..006c04f5ecb 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1154,6 +1154,7 @@ "bedrock_output_config_effort_ceiling": "max" }, "anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1203,6 +1204,7 @@ "supports_output_config": true }, "global.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1237,6 +1239,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1271,6 +1274,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1305,6 +1309,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1471,6 +1476,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1505,6 +1511,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "global.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1539,6 +1546,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "us.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1573,6 +1581,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "eu.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1607,6 +1616,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "au.anthropic.claude-opus-4-8": { + "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -1641,6 +1651,7 @@ "bedrock_output_config_effort_ceiling": "xhigh" }, "jp.anthropic.claude-opus-4-7": { + "bedrock_converse_supports_strict_tools": false, "cache_creation_input_token_cost": 6.875e-06, "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 5.5e-06, diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py new file mode 100644 index 00000000000..26096c49468 --- /dev/null +++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_bedrock_converse_strict_tools_opus_47_48.py @@ -0,0 +1,107 @@ +"""Regression tests for Bedrock Converse ``toolSpec.strict`` forwarding. + +Bedrock Converse routes Claude Opus 4.7/4.8 through an Anthropic-compatible +validator that rejects ``toolSpec.strict`` even though Anthropic's native API +accepts ``strict`` as a top-level tool field for the same models. See +BerriAI/litellm#31582. +""" + +import pytest + +from litellm.litellm_core_utils.prompt_templates.factory import _bedrock_tools_pt +from litellm.llms.bedrock.common_utils import bedrock_converse_supports_strict_tools + + +_STRICT_TOOL = [ + { + "type": "function", + "function": { + "name": "get_weather", + "strict": True, + "description": "Get the weather for a city", + "parameters": { + "type": "object", + "properties": { + "city": {"type": "string"}, + "unit": {"type": "string", "enum": ["celsius"]}, + }, + "required": ["city", "unit"], + "additionalProperties": False, + }, + }, + } +] + + +@pytest.mark.parametrize( + "model_id", + [ + "bedrock/us.anthropic.claude-opus-4-7", + "bedrock/us.anthropic.claude-opus-4-8", + "anthropic.claude-opus-4-7", + "anthropic.claude-opus-4-8", + "anthropic.claude-opus-4-7-v1:0", + "bedrock/eu.anthropic.claude-opus-4-8-v1:0", + "bedrock/global.anthropic.claude-opus-4-7", + ], +) +def test_bedrock_tools_pt_strict_dropped_for_opus_47_48(model_id: str) -> None: + """Opus 4.7/4.8 on Bedrock Converse reject toolSpec.strict — must be dropped.""" + result = _bedrock_tools_pt(_STRICT_TOOL, model=model_id) + assert "strict" not in result[0]["toolSpec"], f"strict leaked into toolSpec for {model_id}: {result[0]['toolSpec']}" + + +@pytest.mark.parametrize( + "model_id", + [ + "anthropic.claude-sonnet-4-5-20250929-v1:0", + "bedrock/us.anthropic.claude-sonnet-4-6", + "bedrock/us.anthropic.claude-opus-4-6", + "bedrock/us.anthropic.claude-opus-4-5", + ], +) +def test_bedrock_tools_pt_strict_kept_for_other_anthropic(model_id: str) -> None: + """Sonnet 4.5/4.6 and Opus <=4.6 accept toolSpec.strict — keep forwarding it.""" + result = _bedrock_tools_pt(_STRICT_TOOL, model=model_id) + assert result[0]["toolSpec"]["strict"] is True, f"strict missing for {model_id}: {result[0]['toolSpec']}" + + +@pytest.mark.parametrize( + "model_id", + [ + "us.amazon.nova-micro-v1:0", + "meta.llama3-2-11b-instruct-v1:0", + ], +) +def test_bedrock_tools_pt_strict_dropped_for_non_anthropic(model_id: str) -> None: + """Non-Anthropic Bedrock families reject toolSpec.strict — must be dropped.""" + result = _bedrock_tools_pt(_STRICT_TOOL, model=model_id) + assert "strict" not in result[0]["toolSpec"] + + +def test_bedrock_converse_supports_strict_tools_helper() -> None: + """Direct check for the gate helper used by factory.py.""" + assert bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-7") is False + assert bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-8") is False + assert bedrock_converse_supports_strict_tools("anthropic.claude-sonnet-4-5-20250929-v1:0") is True + assert bedrock_converse_supports_strict_tools("bedrock/us.anthropic.claude-opus-4-6") is True + assert bedrock_converse_supports_strict_tools("us.amazon.nova-micro-v1:0") is False + assert bedrock_converse_supports_strict_tools("") is False + + +@pytest.mark.parametrize( + "cost_map_key", + [ + "anthropic.claude-opus-4-7", + "us.anthropic.claude-opus-4-7", + "anthropic.claude-opus-4-8", + "us.anthropic.claude-opus-4-8", + ], +) +def test_strict_tools_flag_set_in_model_cost_map(cost_map_key: str) -> None: + """The gate is driven by ``bedrock_converse_supports_strict_tools: false`` in + ``model_prices_and_context_window.json``, not hardcoded model patterns.""" + from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap + + cost_map = GetModelCostMap.load_local_model_cost_map() + assert cost_map[cost_map_key]["bedrock_converse_supports_strict_tools"] is False diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 28b82cf035b..2432b377d54 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -858,6 +858,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "type": "string", "enum": ["low", "medium", "high", "max", "xhigh"], }, + "bedrock_converse_supports_strict_tools": {"type": "boolean"}, "tpm": {"type": "number"}, "provider_specific_entry": {"type": "object"}, "supported_endpoints": { From c4f28ce2874f82473f171d055335c322ba5cf31b Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 1 Jul 2026 19:11:18 -0700 Subject: [PATCH 68/79] fix(bedrock): trigger Nova Sonic generation on response.create so realtime sessions stop hanging (#31924) * fix(bedrock): trigger Nova Sonic generation on response.create so realtime sessions stop hanging (LIT-2239) * fix(bedrock): reopen audio content at client sample rate after trigger block * test(bedrock): cover realtime handler disconnect flush and stream-end guard * fix(bedrock): always close realtime input stream even if close flush fails * fix(lint): use contextlib.suppress in bedrock realtime cleanup to satisfy BLE001 budget * fix(bedrock): suppress bedrock close send errors per-message so promptEnd/sessionEnd still flush --------- Co-authored-by: Cursor Agent --- litellm/llms/bedrock/realtime/handler.py | 37 ++- .../llms/bedrock/realtime/transformation.py | 146 ++++++++- .../llms/bedrock/realtime/trigger_audio.py | 208 ++++++++++++ ruff-strict-budget.json | 4 +- .../realtime/test_bedrock_realtime_handler.py | 174 +++++++++++ .../test_bedrock_realtime_transformation.py | 295 +++++++++++++----- 6 files changed, 768 insertions(+), 96 deletions(-) create mode 100644 litellm/llms/bedrock/realtime/trigger_audio.py create mode 100644 tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py diff --git a/litellm/llms/bedrock/realtime/handler.py b/litellm/llms/bedrock/realtime/handler.py index 6db2571090a..557ee3348d5 100644 --- a/litellm/llms/bedrock/realtime/handler.py +++ b/litellm/llms/bedrock/realtime/handler.py @@ -5,6 +5,7 @@ This uses aws_sdk_bedrock_runtime for bidirectional streaming with Nova Sonic. """ import asyncio +import contextlib import json from typing import Any, Optional @@ -156,12 +157,19 @@ class BedrockRealtime(BaseAWSLLM): session_state: dict, ): """Forward messages from client WebSocket to Bedrock stream.""" - try: - from aws_sdk_bedrock_runtime.models import ( - BidirectionalInputPayloadPart, - InvokeModelWithBidirectionalStreamInputChunk, - ) + from aws_sdk_bedrock_runtime.models import ( + BidirectionalInputPayloadPart, + InvokeModelWithBidirectionalStreamInputChunk, + ) + async def send_to_bedrock(bedrock_message: str) -> None: + event = InvokeModelWithBidirectionalStreamInputChunk( + value=BidirectionalInputPayloadPart(bytes_=bedrock_message.encode("utf-8")) + ) + await bedrock_stream.input_stream.send(event) + verbose_proxy_logger.debug(f"Bedrock Realtime: Sent to Bedrock: {bedrock_message[:200]}") + + try: while True: # Receive message from client message = await client_ws.receive_text() @@ -176,19 +184,15 @@ class BedrockRealtime(BaseAWSLLM): # Send transformed messages to Bedrock for bedrock_message in transformed_messages: - event = InvokeModelWithBidirectionalStreamInputChunk( - value=BidirectionalInputPayloadPart(bytes_=bedrock_message.encode("utf-8")) - ) - await bedrock_stream.input_stream.send(event) - verbose_proxy_logger.debug(f"Bedrock Realtime: Sent to Bedrock: {bedrock_message[:200]}") + await send_to_bedrock(bedrock_message) except Exception as e: verbose_proxy_logger.debug(f"Client to Bedrock forwarding ended: {e}", exc_info=True) - # Close the Bedrock stream input - try: + for close_message in transformation_config.session_close_messages(): + with contextlib.suppress(Exception): + await send_to_bedrock(close_message) + with contextlib.suppress(Exception): await bedrock_stream.input_stream.close() - except Exception: - pass async def _forward_bedrock_to_client( self, @@ -206,6 +210,10 @@ class BedrockRealtime(BaseAWSLLM): output = await bedrock_stream.await_output() result = await output[1].receive() + if result is None: + verbose_proxy_logger.debug("Bedrock Realtime: Bedrock stream ended") + break + if result.value and result.value.bytes_: bedrock_response = result.value.bytes_.decode("utf-8") verbose_proxy_logger.debug(f"Bedrock Realtime: Received from Bedrock: {bedrock_response[:200]}") @@ -252,6 +260,7 @@ class BedrockRealtime(BaseAWSLLM): except Exception as e: verbose_proxy_logger.debug(f"Bedrock to client forwarding ended: {e}", exc_info=True) + finally: # Close the client WebSocket try: await client_ws.close() diff --git a/litellm/llms/bedrock/realtime/transformation.py b/litellm/llms/bedrock/realtime/transformation.py index 498567a4ecf..fe5f0584e03 100644 --- a/litellm/llms/bedrock/realtime/transformation.py +++ b/litellm/llms/bedrock/realtime/transformation.py @@ -4,14 +4,18 @@ This file contains the transformation logic for Bedrock Nova Sonic realtime API. Transforms between OpenAI Realtime API format and Bedrock Nova Sonic format. """ +import base64 import json import uuid as uuid_lib from typing import Any, List, Optional, Union +from pydantic import BaseModel + from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig +from litellm.llms.bedrock.realtime.trigger_audio import ready_trigger_pcm from litellm.types.llms.openai import ( OpenAIRealtimeContentPartDone, OpenAIRealtimeDoneEvent, @@ -35,6 +39,17 @@ from litellm.types.realtime import ( from litellm.utils import get_empty_usage +class BedrockContentEnd(BaseModel): + stopReason: Optional[str] = None + + +TRIGGER_AUDIO_SAMPLE_RATE_HERTZ = 16000 +TRIGGER_AUDIO_BYTES_PER_SECOND = TRIGGER_AUDIO_SAMPLE_RATE_HERTZ * 2 +TRIGGER_LEADING_SILENCE = bytes(TRIGGER_AUDIO_BYTES_PER_SECOND // 2) +TRIGGER_TRAILING_SILENCE = bytes(TRIGGER_AUDIO_BYTES_PER_SECOND * 3) +TRIGGER_AUDIO_CHUNK_SIZE = 1024 + + class BedrockRealtimeConfig(BaseRealtimeConfig): """Configuration for Bedrock Nova Sonic realtime transformations.""" @@ -43,6 +58,8 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): self.prompt_name = str(uuid_lib.uuid4()) self.content_name = str(uuid_lib.uuid4()) self.audio_content_name = str(uuid_lib.uuid4()) + self.prompt_started = False + self.client_audio_streamed = False # Default configuration values # Inference configuration @@ -247,6 +264,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): prompt_start = {"event": {"promptStart": prompt_start_config}} messages.append(json.dumps(prompt_start)) + self.prompt_started = True # Send system prompt if provided instructions = session_config.get("instructions") @@ -304,8 +322,22 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): List of Bedrock format messages (JSON strings) """ verbose_logger.debug("Handling input_audio_buffer.append") + self.client_audio_streamed = True messages: List[str] = [] + if hasattr(self, "_audio_content_started") and self._audio_content_sample_rate != self.input_sample_rate_hertz: + mismatched_content_end = { + "event": { + "contentEnd": { + "promptName": self.prompt_name, + "contentName": self.audio_content_name, + } + } + } + messages.append(json.dumps(mismatched_content_end)) + delattr(self, "_audio_content_started") + self.audio_content_name = str(uuid_lib.uuid4()) + # Check if we need to start audio content if not hasattr(self, "_audio_content_started"): audio_content_start = { @@ -329,6 +361,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): } messages.append(json.dumps(audio_content_start)) self._audio_content_started = True + self._audio_content_sample_rate = self.input_sample_rate_hertz # Send audio chunk audio_data = json_message.get("audio", "") @@ -383,7 +416,6 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): List of Bedrock format messages (JSON strings) """ verbose_logger.debug("Handling conversation.item.create") - messages: List[str] = [] item = json_message.get("item", {}) item_type = item.get("type") @@ -392,6 +424,8 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): if item_type == "function_call_output": return self.transform_conversation_item_create_tool_result_event(json_message) + messages: list[str] = [] + # Handle regular message if item_type == "message": content = item.get("content", []) @@ -443,6 +477,12 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): """ Transform response.create event to Bedrock format. + Nova Sonic only starts generating after it detects user speech, so text-only + sessions never get a response on their own. Injecting a short spoken "ready" + utterance (followed by silence) makes the model respond to the pending + interactive text input. Sessions where the client streams its own audio rely + on Nova Sonic's built-in turn detection instead. + Args: json_message: OpenAI response.create message @@ -450,8 +490,53 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): List of Bedrock format messages (JSON strings) """ verbose_logger.debug("Handling response.create") - # Bedrock starts generating automatically, no explicit trigger needed - return [] + if not self.prompt_started or self.client_audio_streamed: + return [] + + messages: list[str] = [] + if not hasattr(self, "_audio_content_started"): + trigger_content_start = { + "event": { + "contentStart": { + "promptName": self.prompt_name, + "contentName": self.audio_content_name, + "type": "AUDIO", + "interactive": True, + "role": "USER", + "audioInputConfiguration": { + "mediaType": self.input_media_type, + "sampleRateHertz": TRIGGER_AUDIO_SAMPLE_RATE_HERTZ, + "sampleSizeBits": self.input_sample_size_bits, + "channelCount": self.input_channel_count, + "audioType": self.input_audio_type, + "encoding": self.input_encoding, + }, + } + } + } + messages.append(json.dumps(trigger_content_start)) + self._audio_content_started = True + self._audio_content_sample_rate = TRIGGER_AUDIO_SAMPLE_RATE_HERTZ + + messages.extend(self._response_trigger_audio_messages()) + return messages + + def _response_trigger_audio_messages(self) -> list[str]: + pcm = TRIGGER_LEADING_SILENCE + ready_trigger_pcm() + TRIGGER_TRAILING_SILENCE + return [ + json.dumps( + { + "event": { + "audioInput": { + "promptName": self.prompt_name, + "contentName": self.audio_content_name, + "content": base64.b64encode(pcm[offset : offset + TRIGGER_AUDIO_CHUNK_SIZE]).decode(), + } + } + } + ) + for offset in range(0, len(pcm), TRIGGER_AUDIO_CHUNK_SIZE) + ] def transform_response_cancel_event(self, json_message: dict) -> List[str]: """ @@ -467,6 +552,35 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): # Send interrupt signal if needed return [] + def session_close_messages(self) -> list[str]: + """ + Build the Bedrock events that gracefully close the session + (contentEnd for any open audio content, promptEnd, sessionEnd). + + Returns: + List of Bedrock format messages (JSON strings) + """ + if not self.prompt_started: + return [] + + messages: list[str] = [] + if hasattr(self, "_audio_content_started"): + audio_content_end = { + "event": { + "contentEnd": { + "promptName": self.prompt_name, + "contentName": self.audio_content_name, + } + } + } + messages.append(json.dumps(audio_content_end)) + delattr(self, "_audio_content_started") + + messages.append(json.dumps({"event": {"promptEnd": {"promptName": self.prompt_name}}})) + messages.append(json.dumps({"event": {"sessionEnd": {}}})) + self.prompt_started = False + return messages + def transform_realtime_request( self, message: str, @@ -837,10 +951,11 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): Optional[ALL_DELTA_TYPES], ]: """ - Transform Bedrock promptEnd event to OpenAI response.done. + Transform a Bedrock end-of-response event (promptEnd, completionEnd, or an + END_TURN contentEnd) to OpenAI response.done. Args: - event: Bedrock promptEnd event + event: Bedrock event that ends the response current_response_id: Current response ID current_conversation_id: Current conversation ID @@ -848,7 +963,18 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): Tuple of (events, reset_output_item_id, reset_response_id, reset_delta_type) """ verbose_logger.debug("Handling promptEnd") + return self._response_done_events(current_response_id, current_conversation_id) + def _response_done_events( + self, + current_response_id: Optional[str], + current_conversation_id: Optional[str], + ) -> tuple[ + List[OpenAIRealtimeEvents], + Optional[str], + Optional[str], + Optional[ALL_DELTA_TYPES], + ]: if not current_response_id or not current_conversation_id: return [], None, None, None @@ -1084,6 +1210,14 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): current_delta_chunks, ) returned_messages.extend(events) + if BedrockContentEnd.model_validate(event["contentEnd"]).stopReason == "END_TURN": + ( + done_events, + current_output_item_id, + current_response_id, + current_delta_type, + ) = self._response_done_events(current_response_id, current_conversation_id) + returned_messages.extend(done_events) elif "toolUse" in event: events, tool_call_id, tool_name = self.transform_tool_use_event( @@ -1093,7 +1227,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig): # Store tool call info for potential use verbose_logger.debug(f"Tool use event: {tool_name} (ID: {tool_call_id})") - elif "promptEnd" in event: + elif "promptEnd" in event or "completionEnd" in event: ( events, current_output_item_id, diff --git a/litellm/llms/bedrock/realtime/trigger_audio.py b/litellm/llms/bedrock/realtime/trigger_audio.py new file mode 100644 index 00000000000..5783dae54bb --- /dev/null +++ b/litellm/llms/bedrock/realtime/trigger_audio.py @@ -0,0 +1,208 @@ +""" +Pre-rendered spoken "ready" trigger audio (16kHz, 16-bit, mono PCM), generated with Amazon Polly. + +Amazon Nova Sonic v1 only starts generating after it hears the user speak, so text-only realtime +sessions inject this short utterance to trigger a response (same approach as Pipecat's +AWSNovaSonicLLMService assistant-response trigger). +""" + +import base64 +import gzip +from functools import lru_cache + +READY_TRIGGER_PCM_16KHZ_MONO_GZIP_B64 = ( + "H4sIANGpRWoC/517dXQcR9Bnw+Duis3MzMwkc8xsxxTZMTMzM0PMmJhBjpmZmWKQZSaxFrQ80H0lJXf3vXf/nev17ExPQ3Xh" + "r2wPQv8/f/D/uMP/zxv8f64YkSyiWU1AIpCcRSqyICtQCApF4SgSRaHsKCfKjfKhgqgIKo5KobKoPKqEqqFaqC5qgBqjFqg1" + "ao86o+6oF+qDYtAgNBSNQKPQODQeTUZT0Uw0B81D89ECtAgtRcvRMrQCrQRahVajNWgtWo/+QBvQJrQRbQbagraibWg70Da4" + "2/rf7zbozxyxCcaug1krYZXFaCGai2ajGWgKmgi7jYFdh6ABqB/qjXqgLqgd8NUcNQUe66CaqDJwXQaVhDMUgNNkh7NZ4bSc" + "69zLXTyVJ/Kv/BN/z9/w5/w+0B1+g1/kZ/gpfoL/zQ/xA/wvvovv5Jv5Fmjr+Tq+lq/iS/kioPl8Fp+eRRP4KKBhfBDvw3vw" + "Lrw978jb8Fa8JW8B1JQ34PV5Q2iZ1wa8Ea/Da/Ja0Gpm9TTmzXgT3hzGt+a/wNz2vBPM78TbwtyW0NuIV+fVeCWgCrwyUHmg" + "yll9NWClOrwurNA0a42GMLYerFoN3pf7j8rwYkBFeWFehOcHKshz8dw8Ow/nUTyCh/IwaDYuc4mrPATIBs8WeJMNxmTnOWF0" + 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"WoNz/vsHAW4lsIqUJbd/v8KWQH4yXKX/VpeyrlAI//elNs36Jf/d/89vuDMl+b+/7/73G+/MHTL34P9jv/97/ffd/3369/d/" + "AYxHlHJ2PgAA" +) + + +@lru_cache(maxsize=1) +def ready_trigger_pcm() -> bytes: + return gzip.decompress(base64.b64decode(READY_TRIGGER_PCM_16KHZ_MONO_GZIP_B64)) diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json index f5aa600ab84..85ff7fcbf7d 100644 --- a/ruff-strict-budget.json +++ b/ruff-strict-budget.json @@ -60,7 +60,7 @@ "limit": 4 }, "BLE001": { - "limit": 2904 + "limit": 2903 }, "C401": { "limit": 11 @@ -255,7 +255,7 @@ "limit": 480 }, "S110": { - "limit": 237 + "limit": 236 }, "S112": { "limit": 24 diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py new file mode 100644 index 00000000000..18e48169bc1 --- /dev/null +++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py @@ -0,0 +1,174 @@ +import json +import os +import sys +import types +from unittest.mock import MagicMock + +import pytest + +sys.path.insert(0, os.path.abspath("../../../../..")) # Adds the parent directory to the system path + +from litellm.llms.bedrock.realtime.handler import BedrockRealtime +from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig + + +class FakePayloadPart: + def __init__(self, bytes_): + self.bytes_ = bytes_ + + +class FakeInputChunk: + def __init__(self, value): + self.value = value + + +class FakeInputStream: + def __init__(self): + self.sent = [] + self.closed = False + + async def send(self, event): + self.sent.append(event) + + async def close(self): + self.closed = True + + +class SendFailingInputStream(FakeInputStream): + async def send(self, event): + raise RuntimeError("bedrock send failed") + + +class FailOnPromptEndStream(FakeInputStream): + async def send(self, event): + payload = json.loads(event.value.bytes_.decode("utf-8")) + if "promptEnd" in payload.get("event", {}): + raise RuntimeError("bedrock rejected promptEnd") + self.sent.append(event) + + +class FakeBedrockStream: + def __init__(self, input_stream=None): + self.input_stream = input_stream if input_stream is not None else FakeInputStream() + + +class DisconnectingClientWS: + def __init__(self, messages): + self._messages = list(messages) + + async def receive_text(self): + if self._messages: + return self._messages.pop(0) + raise RuntimeError("client disconnected") + + +class ClosableClientWS: + def __init__(self): + self.closed = False + + async def close(self): + self.closed = True + + +class EndedBedrockReceiver: + async def receive(self): + return None + + +class EndedBedrockStream: + async def await_output(self): + return (None, EndedBedrockReceiver()) + + +@pytest.fixture +def stub_aws_models(monkeypatch): + package = types.ModuleType("aws_sdk_bedrock_runtime") + models = types.ModuleType("aws_sdk_bedrock_runtime.models") + models.BidirectionalInputPayloadPart = FakePayloadPart + models.InvokeModelWithBidirectionalStreamInputChunk = FakeInputChunk + package.models = models + monkeypatch.setitem(sys.modules, "aws_sdk_bedrock_runtime", package) + monkeypatch.setitem(sys.modules, "aws_sdk_bedrock_runtime.models", models) + + +class TestBedrockRealtimeHandler: + """Client disconnect must close the Bedrock session gracefully (LIT-2239 regression)""" + + @pytest.mark.asyncio + async def test_client_disconnect_flushes_session_close_messages(self, stub_aws_models): + handler = BedrockRealtime() + config = BedrockRealtimeConfig() + stream = FakeBedrockStream() + client_ws = DisconnectingClientWS( + [json.dumps({"type": "session.update", "session": {"instructions": "You are helpful."}})] + ) + + await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}) + + sent_events = [json.loads(chunk.value.bytes_.decode("utf-8")) for chunk in stream.input_stream.sent] + event_names = [next(iter(event["event"])) for event in sent_events] + assert event_names[0] == "sessionStart" + assert event_names[-2:] == ["promptEnd", "sessionEnd"] + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_client_disconnect_before_session_update_sends_nothing(self, stub_aws_models): + handler = BedrockRealtime() + config = BedrockRealtimeConfig() + stream = FakeBedrockStream() + + await handler._forward_client_to_bedrock( + DisconnectingClientWS([]), stream, config, "amazon.nova-sonic-v1:0", {} + ) + + assert stream.input_stream.sent == [] + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_input_stream_closed_even_when_close_flush_fails(self, stub_aws_models): + handler = BedrockRealtime() + config = BedrockRealtimeConfig() + stream = FakeBedrockStream(input_stream=SendFailingInputStream()) + client_ws = DisconnectingClientWS( + [json.dumps({"type": "session.update", "session": {"instructions": "You are helpful."}})] + ) + + await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}) + + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_close_flush_continues_after_partial_send_failure(self, stub_aws_models): + handler = BedrockRealtime() + config = BedrockRealtimeConfig() + stream = FakeBedrockStream(input_stream=FailOnPromptEndStream()) + client_ws = DisconnectingClientWS( + [json.dumps({"type": "session.update", "session": {"instructions": "You are helpful."}})] + ) + + await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}) + + sent_events = [json.loads(chunk.value.bytes_.decode("utf-8")) for chunk in stream.input_stream.sent] + event_names = [next(iter(event["event"])) for event in sent_events] + assert "sessionEnd" in event_names + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_bedrock_stream_end_closes_client_websocket(self): + handler = BedrockRealtime() + client_ws = ClosableClientWS() + + await handler._forward_bedrock_to_client( + EndedBedrockStream(), + client_ws, + BedrockRealtimeConfig(), + "amazon.nova-sonic-v1:0", + MagicMock(), + {}, + ) + + assert client_ws.closed + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py index bf15727f4b4..a68aa603b26 100644 --- a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py +++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py @@ -5,11 +5,16 @@ from unittest.mock import MagicMock import pytest -sys.path.insert( - 0, os.path.abspath("../../../../..") -) # Adds the parent directory to the system path +sys.path.insert(0, os.path.abspath("../../../../..")) # Adds the parent directory to the system path -from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig +import base64 + +from litellm.llms.bedrock.realtime.transformation import ( + TRIGGER_LEADING_SILENCE, + TRIGGER_TRAILING_SILENCE, + BedrockRealtimeConfig, +) +from litellm.llms.bedrock.realtime.trigger_audio import ready_trigger_pcm from litellm.types.llms.openai import OpenAIRealtimeEventTypes @@ -67,19 +72,14 @@ class TestBedrockRealtimeConfig: } ] - session_config = config.session_configuration_request( - "amazon.nova-sonic-v1:0", tools=tools - ) + session_config = config.session_configuration_request("amazon.nova-sonic-v1:0", tools=tools) session_dict = json.loads(session_config) prompt_start = session_dict["prompt_start"]["event"]["promptStart"] assert "toolConfiguration" in prompt_start assert "tools" in prompt_start["toolConfiguration"] assert len(prompt_start["toolConfiguration"]["tools"]) == 1 - assert ( - prompt_start["toolConfiguration"]["tools"][0]["toolSpec"]["name"] - == "get_weather" - ) + assert prompt_start["toolConfiguration"]["tools"][0]["toolSpec"]["name"] == "get_weather" def test_transform_tools_to_bedrock_format(self): """Test OpenAI tool format to Bedrock format transformation""" @@ -93,9 +93,7 @@ class TestBedrockRealtimeConfig: "description": "Get current weather", "parameters": { "type": "object", - "properties": { - "location": {"type": "string", "description": "City name"} - }, + "properties": {"location": {"type": "string", "description": "City name"}}, "required": ["location"], }, }, @@ -120,18 +118,11 @@ class TestBedrockRealtimeConfig: # Test PCM16 format assert config._map_audio_format_to_sample_rate("pcm16", is_output=True) == 24000 - assert ( - config._map_audio_format_to_sample_rate("pcm16", is_output=False) == 16000 - ) + assert config._map_audio_format_to_sample_rate("pcm16", is_output=False) == 16000 # Test G.711 formats - assert ( - config._map_audio_format_to_sample_rate("g711_ulaw", is_output=True) == 8000 - ) - assert ( - config._map_audio_format_to_sample_rate("g711_alaw", is_output=False) - == 8000 - ) + assert config._map_audio_format_to_sample_rate("g711_ulaw", is_output=True) == 8000 + assert config._map_audio_format_to_sample_rate("g711_alaw", is_output=False) == 8000 def test_transform_session_update_event(self): """Test session.update event transformation""" @@ -158,12 +149,7 @@ class TestBedrockRealtimeConfig: # Verify session start message session_start = json.loads(messages[0]) - assert ( - session_start["event"]["sessionStart"]["inferenceConfiguration"][ - "temperature" - ] - == 0.9 - ) + assert session_start["event"]["sessionStart"]["inferenceConfiguration"]["temperature"] == 0.9 def test_transform_session_update_with_tools(self): """Test session.update with tools""" @@ -237,12 +223,7 @@ class TestBedrockRealtimeConfig: content_start = json.loads(messages[0]) assert content_start["event"]["contentStart"]["type"] == "TOOL" assert content_start["event"]["contentStart"]["role"] == "TOOL" - assert ( - content_start["event"]["contentStart"]["toolResultInputConfiguration"][ - "toolUseId" - ] - == "call_123" - ) + assert content_start["event"]["contentStart"]["toolResultInputConfiguration"]["toolUseId"] == "call_123" def test_transform_input_audio_buffer_append(self): """Test input_audio_buffer.append transformation""" @@ -260,12 +241,7 @@ class TestBedrockRealtimeConfig: content_start = json.loads(messages[0]) assert content_start["event"]["contentStart"]["type"] == "AUDIO" - assert ( - content_start["event"]["contentStart"]["audioInputConfiguration"][ - "sampleRateHertz" - ] - == 16000 - ) + assert content_start["event"]["contentStart"]["audioInputConfiguration"]["sampleRateHertz"] == 16000 audio_input = json.loads(messages[1]) assert audio_input["event"]["audioInput"]["content"] == "base64_audio_data_here" @@ -286,6 +262,144 @@ class TestBedrockRealtimeConfig: assert "contentEnd" in content_end["event"] +class TestBedrockRealtimeResponseCreate: + """response.create must trigger Nova Sonic generation (LIT-2239 regression)""" + + def _start_session(self, config): + config.transform_realtime_request( + json.dumps( + { + "type": "session.update", + "session": {"instructions": "You are a helpful assistant."}, + } + ), + "amazon.nova-sonic-v1:0", + ) + + def test_response_create_before_session_update_is_noop(self): + config = BedrockRealtimeConfig() + + messages = config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + + assert messages == [] + + def test_response_create_emits_spoken_trigger_audio(self): + config = BedrockRealtimeConfig() + self._start_session(config) + + messages = config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + + assert len(messages) > 1 + + content_start = json.loads(messages[0])["event"]["contentStart"] + assert content_start["promptName"] == config.prompt_name + assert content_start["contentName"] == config.audio_content_name + assert content_start["type"] == "AUDIO" + assert content_start["interactive"] is True + assert content_start["role"] == "USER" + assert content_start["audioInputConfiguration"]["sampleRateHertz"] == 16000 + + audio_events = [json.loads(message)["event"]["audioInput"] for message in messages[1:]] + assert all(event["promptName"] == config.prompt_name for event in audio_events) + assert all(event["contentName"] == config.audio_content_name for event in audio_events) + + sent_pcm = b"".join(base64.b64decode(event["content"]) for event in audio_events) + assert sent_pcm == TRIGGER_LEADING_SILENCE + ready_trigger_pcm() + TRIGGER_TRAILING_SILENCE + + def test_second_response_create_reuses_open_audio_content(self): + config = BedrockRealtimeConfig() + self._start_session(config) + + first = config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + second = config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + + assert len(second) == len(first) - 1 + assert all("audioInput" in json.loads(message)["event"] for message in second) + + def test_response_create_is_noop_when_client_streams_audio(self): + config = BedrockRealtimeConfig() + self._start_session(config) + config.transform_realtime_request( + json.dumps({"type": "input_audio_buffer.append", "audio": "c2lsZW5jZQ=="}), + "amazon.nova-sonic-v1:0", + ) + + messages = config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + + assert messages == [] + + def test_client_audio_after_trigger_reopens_block_at_client_sample_rate(self): + config = BedrockRealtimeConfig() + config.transform_realtime_request( + json.dumps( + { + "type": "session.update", + "session": { + "instructions": "You are a helpful assistant.", + "input_audio_format": "g711_ulaw", + }, + } + ), + "amazon.nova-sonic-v1:0", + ) + config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + trigger_content_name = config.audio_content_name + + messages = config.transform_realtime_request( + json.dumps({"type": "input_audio_buffer.append", "audio": "c2lsZW5jZQ=="}), + "amazon.nova-sonic-v1:0", + ) + + events = [json.loads(message)["event"] for message in messages] + assert [next(iter(event)) for event in events] == [ + "contentEnd", + "contentStart", + "audioInput", + ] + assert events[0]["contentEnd"]["contentName"] == trigger_content_name + new_content_start = events[1]["contentStart"] + assert new_content_start["contentName"] == config.audio_content_name + assert new_content_start["contentName"] != trigger_content_name + assert new_content_start["audioInputConfiguration"]["sampleRateHertz"] == 8000 + assert events[2]["audioInput"]["contentName"] == config.audio_content_name + + def test_client_audio_after_trigger_reuses_block_at_matching_sample_rate(self): + config = BedrockRealtimeConfig() + self._start_session(config) + config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + trigger_content_name = config.audio_content_name + + messages = config.transform_realtime_request( + json.dumps({"type": "input_audio_buffer.append", "audio": "c2lsZW5jZQ=="}), + "amazon.nova-sonic-v1:0", + ) + + assert len(messages) == 1 + audio_input = json.loads(messages[0])["event"]["audioInput"] + assert audio_input["contentName"] == trigger_content_name + + def test_session_close_messages_close_audio_prompt_and_session(self): + config = BedrockRealtimeConfig() + self._start_session(config) + config.transform_realtime_request(json.dumps({"type": "response.create"}), "amazon.nova-sonic-v1:0") + + close_messages = [json.loads(message)["event"] for message in config.session_close_messages()] + + assert [next(iter(event)) for event in close_messages] == [ + "contentEnd", + "promptEnd", + "sessionEnd", + ] + assert close_messages[0]["contentEnd"]["contentName"] == config.audio_content_name + assert close_messages[1]["promptEnd"]["promptName"] == config.prompt_name + assert config.session_close_messages() == [] + + def test_session_close_messages_before_session_update_is_empty(self): + config = BedrockRealtimeConfig() + + assert config.session_close_messages() == [] + + class TestBedrockRealtimeResponseTransformation: """Test suite for response transformation""" @@ -296,11 +410,7 @@ class TestBedrockRealtimeResponseTransformation: logging_obj.litellm_trace_id = "trace_123" bedrock_message = { - "event": { - "sessionStart": { - "inferenceConfiguration": {"maxTokens": 1024, "temperature": 0.7} - } - } + "event": {"sessionStart": {"inferenceConfiguration": {"maxTokens": 1024, "temperature": 0.7}}} } result = config.transform_realtime_response( @@ -330,9 +440,7 @@ class TestBedrockRealtimeResponseTransformation: logging_obj.litellm_trace_id = "trace_123" # First create a content start to initialize IDs - content_start_message = { - "event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}} - } + content_start_message = {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}} result1 = config.transform_realtime_response( json.dumps(content_start_message), @@ -368,9 +476,7 @@ class TestBedrockRealtimeResponseTransformation: ) # Check for text delta - text_deltas = [ - msg for msg in result2["response"] if msg["type"] == "response.text.delta" - ] + text_deltas = [msg for msg in result2["response"] if msg["type"] == "response.text.delta"] assert len(text_deltas) == 1 assert text_deltas[0]["delta"] == "Hello, world!" @@ -384,9 +490,7 @@ class TestBedrockRealtimeResponseTransformation: logging_obj.litellm_trace_id = "trace_123" # First create a content start for audio - content_start_message = { - "event": {"contentStart": {"role": "ASSISTANT", "type": "AUDIO"}} - } + content_start_message = {"event": {"contentStart": {"role": "ASSISTANT", "type": "AUDIO"}}} result1 = config.transform_realtime_response( json.dumps(content_start_message), @@ -404,9 +508,7 @@ class TestBedrockRealtimeResponseTransformation: ) # Now send audio output - audio_output_message = { - "event": {"audioOutput": {"content": "base64_audio_content"}} - } + audio_output_message = {"event": {"audioOutput": {"content": "base64_audio_content"}}} result2 = config.transform_realtime_response( json.dumps(audio_output_message), @@ -424,9 +526,7 @@ class TestBedrockRealtimeResponseTransformation: ) # Check for audio delta - audio_deltas = [ - msg for msg in result2["response"] if msg["type"] == "response.audio.delta" - ] + audio_deltas = [msg for msg in result2["response"] if msg["type"] == "response.audio.delta"] assert len(audio_deltas) == 1 assert audio_deltas[0]["delta"] == "base64_audio_content" @@ -504,14 +604,67 @@ class TestBedrockRealtimeResponseTransformation: # Should have text.done, content_part.done, and output_item.done assert len(result["response"]) == 3 - text_done = [ - msg for msg in result["response"] if msg["type"] == "response.text.done" - ][0] + text_done = [msg for msg in result["response"] if msg["type"] == "response.text.done"][0] assert text_done["text"] == "Hello, world!" # Delta chunks should be reset assert result["current_delta_chunks"] is None + def test_content_end_end_turn_emits_response_done(self): + """END_TURN contentEnd must produce response.done (LIT-2239 regression)""" + config = BedrockRealtimeConfig() + logging_obj = MagicMock() + logging_obj.litellm_trace_id = "trace_123" + + content_end_message = {"event": {"contentEnd": {"stopReason": "END_TURN", "type": "AUDIO"}}} + + result = config.transform_realtime_response( + json.dumps(content_end_message), + "amazon.nova-sonic-v1:0", + logging_obj, + realtime_response_transform_input={ + "session_configuration_request": json.dumps({"configured": True}), + "current_output_item_id": "item_123", + "current_response_id": "resp_123", + "current_conversation_id": "conv_123", + "current_delta_chunks": [], + "current_item_chunks": [], + "current_delta_type": "audio", + }, + ) + + response_done_events = [msg for msg in result["response"] if msg["type"] == "response.done"] + assert len(response_done_events) == 1 + assert response_done_events[0]["response"]["status"] == "completed" + assert result["current_output_item_id"] is None + assert result["current_response_id"] is None + assert result["current_delta_type"] is None + + def test_content_end_partial_turn_does_not_emit_response_done(self): + config = BedrockRealtimeConfig() + logging_obj = MagicMock() + logging_obj.litellm_trace_id = "trace_123" + + content_end_message = {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN", "type": "TEXT"}}} + + result = config.transform_realtime_response( + json.dumps(content_end_message), + "amazon.nova-sonic-v1:0", + logging_obj, + realtime_response_transform_input={ + "session_configuration_request": json.dumps({"configured": True}), + "current_output_item_id": "item_123", + "current_response_id": "resp_123", + "current_conversation_id": "conv_123", + "current_delta_chunks": [], + "current_item_chunks": [], + "current_delta_type": "text", + }, + ) + + assert all(msg["type"] != "response.done" for msg in result["response"]) + assert result["current_response_id"] == "resp_123" + def test_transform_prompt_end_response(self): """Test promptEnd response transformation""" config = BedrockRealtimeConfig() @@ -552,9 +705,7 @@ class TestBedrockRealtimeResponseTransformation: logging_obj.litellm_trace_id = "trace_123" # Create a sequence of messages - content_start = { - "event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}} - } + content_start = {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}} text_output1 = {"event": {"textOutput": {"content": "Hello"}}} text_output2 = {"event": {"textOutput": {"content": " world"}}} @@ -600,9 +751,7 @@ class TestBedrockRealtimeResponseTransformation: logging_obj.litellm_trace_id = "trace_123" # Create a sequence of messages - content_start = { - "event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}} - } + content_start = {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}} text_output = {"event": {"textOutput": {"content": "Hello"}}} all_events = [] @@ -636,9 +785,7 @@ class TestBedrockRealtimeResponseTransformation: ) # Check all response_ids are the same - response_ids = [ - event["response_id"] for event in all_events if "response_id" in event - ] + response_ids = [event["response_id"] for event in all_events if "response_id" in event] assert len(set(response_ids)) == 1, "Response IDs should be consistent" From 2a9dbc4c0d2673ee50469229fff60776ceb68c1f Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Wed, 1 Jul 2026 20:13:58 -0700 Subject: [PATCH 69/79] chore(ui): remove unused dep, delete dead file, and unblock knip (#31933) Knip flagged remark-gfm as unused and date-fns as imported-but-undeclared, so drop remark-gfm (which prunes its transitive markdown subtree from the lockfile) and declare date-fns, which keyExpiryUtils.ts imports but only received transitively. Also delete the dead memory/components/index.tsx barrel, since nothing imports it once the page pulls MemoryView from its module directly Knip itself could not run: its Playwright plugin imports every config referenced by a --config flag in package.json scripts, and migration.serverRootPath.config.ts threw at import time when SERVER_ROOT_PATH was unset. Move that guard into a config-specific globalSetup so importing the config is side-effect-free; the check still fires loudly before any test runs when the prefix is missing --- .../migration.serverRootPath.config.ts | 10 +- .../migration.serverRootPath.globalSetup.ts | 12 + ui/litellm-dashboard/package-lock.json | 295 +----------------- ui/litellm-dashboard/package.json | 2 +- .../(dashboard)/memory/components/index.tsx | 1 - 5 files changed, 15 insertions(+), 305 deletions(-) create mode 100644 ui/litellm-dashboard/e2e_tests/migration.serverRootPath.globalSetup.ts delete mode 100644 ui/litellm-dashboard/src/app/(dashboard)/memory/components/index.tsx diff --git a/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.config.ts b/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.config.ts index 205348463c8..d32f59b16bf 100644 --- a/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.config.ts +++ b/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.config.ts @@ -6,14 +6,6 @@ import { defineConfig, devices } from "@playwright/test"; * running. globalSetup logs in at `${SERVER_ROOT_PATH}/ui/login` so the admin * storage state is valid under the prefix. */ -if (!process.env.SERVER_ROOT_PATH) { - throw new Error( - "migration.serverRootPath.config.ts requires SERVER_ROOT_PATH to be set (e.g. SERVER_ROOT_PATH=/litellm). " + - "Without it this config silently re-runs the default mount and never exercises the prefix. " + - "For the root-less run use the default playwright.config.ts (npm run e2e:migration).", - ); -} - export default defineConfig({ testDir: "./tests/migration", testMatch: ["migratedPages.spec.ts"], @@ -34,5 +26,5 @@ export default defineConfig({ projects: [{ name: "chromium", use: { ...devices["Desktop Chrome"] } }], timeout: 3 * 60 * 1000, expect: { timeout: 10 * 1000 }, - globalSetup: require.resolve("./globalSetup"), + globalSetup: require.resolve("./migration.serverRootPath.globalSetup"), }); diff --git a/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.globalSetup.ts b/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.globalSetup.ts new file mode 100644 index 00000000000..d11f49dae74 --- /dev/null +++ b/ui/litellm-dashboard/e2e_tests/migration.serverRootPath.globalSetup.ts @@ -0,0 +1,12 @@ +import globalSetup from "./globalSetup"; + +export default async function migrationServerRootPathGlobalSetup() { + if (!process.env.SERVER_ROOT_PATH) { + throw new Error( + "migration.serverRootPath.config.ts requires SERVER_ROOT_PATH to be set (e.g. SERVER_ROOT_PATH=/litellm). " + + "Without it this config silently re-runs the default mount and never exercises the prefix. " + + "For the root-less run use the default playwright.config.ts (npm run e2e:migration).", + ); + } + await globalSetup(); +} diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index 2afc145d15b..828edde278b 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -18,6 +18,7 @@ "@types/papaparse": "5.5.2", "antd": "5.29.3", "cva": "1.0.0-beta.4", + "date-fns": "3.6.0", "dayjs": "1.11.19", "jwt-decode": "4.0.0", "lucide-react": "0.513.0", @@ -31,7 +32,6 @@ "react-json-view-lite": "2.5.0", "react-markdown": "9.1.0", "react-syntax-highlighter": "15.6.6", - "remark-gfm": "4.0.1", "tailwind-merge": "3.4.0", "uuid": "14.0.0" }, @@ -8601,16 +8601,6 @@ "url": "https://github.com/sponsors/sindresorhus" } }, - "node_modules/markdown-table": { - "version": "3.0.4", - "resolved": "https://registry.npmjs.org/markdown-table/-/markdown-table-3.0.4.tgz", - "integrity": "sha512-wiYz4+JrLyb/DqW2hkFJxP7Vd7JuTDm77fvbM8VfEQdmSMqcImWeeRbHwZjBjIFki/VaMK2BhFi7oUUZeM5bqw==", - 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} - }, "node_modules/require-from-string": { "version": "2.0.2", "resolved": "https://registry.npmjs.org/require-from-string/-/require-from-string-2.0.2.tgz", diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index a8948f4be34..0097e8c6559 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -34,6 +34,7 @@ "@types/papaparse": "5.5.2", "antd": "5.29.3", "cva": "1.0.0-beta.4", + "date-fns": "3.6.0", "dayjs": "1.11.19", "jwt-decode": "4.0.0", "lucide-react": "0.513.0", @@ -47,7 +48,6 @@ "react-json-view-lite": "2.5.0", "react-markdown": "9.1.0", "react-syntax-highlighter": "15.6.6", - "remark-gfm": "4.0.1", "tailwind-merge": "3.4.0", "uuid": "14.0.0" }, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/memory/components/index.tsx b/ui/litellm-dashboard/src/app/(dashboard)/memory/components/index.tsx deleted file mode 100644 index 8b1c720148a..00000000000 --- a/ui/litellm-dashboard/src/app/(dashboard)/memory/components/index.tsx +++ /dev/null @@ -1 +0,0 @@ -export { MemoryView, default } from "./MemoryView"; From 3d644e1f9dd5985a7796051b9b08b696e7e19ba7 Mon Sep 17 00:00:00 2001 From: ryan-crabbe-berri Date: Wed, 1 Jul 2026 20:14:07 -0700 Subject: [PATCH 70/79] refactor(ui): colocate users page into route-level _components (#31897) Moves the user-management component tree (view_users plus BulkEditUsers, edit_user, DefaultUserSettings, user_edit_view, and the view_users table/columns/info-view) out of the shared src/components dump into the users route segment under _components, now that the app router owns the route. The page imports from a trimmed ./_components barrel UserInfo moves into networking.tsx beside UserListResponse, its real owner: networking defines the user API response shapes that embed it, and previously reached up into a view folder (components/view_users/types) to import the type. Defining it in networking removes that backwards data-layer-to-view dependency and drains the view_users/ folder entirely. CreateUserButton and onboarding_link stay in components/ since the create-key flow also consumes them Relative imports in the moved files are rewritten to @/components/* absolute paths, and the eight pre-existing eslint-suppressions entries are re-keyed to the new paths so the move stays behavior and lint neutral Verified: the moved suites pass with the same 75 assertions as before the move, tsc and eslint are clean, and next build compiles the /users route --- ui/litellm-dashboard/eslint-suppressions.json | 16 ++++++++-------- .../users/_components}/BulkEditUsers.test.tsx | 8 ++++---- .../users/_components}/BulkEditUsers.tsx | 4 ++-- .../_components}/DefaultUserSettings.test.tsx | 8 ++++---- .../users/_components}/DefaultUserSettings.tsx | 10 ++++++---- .../users/_components}/edit_user.tsx | 4 ++-- .../(dashboard)/users/_components/index.tsx | 1 + .../users/_components}/user_edit_view.test.tsx | 6 +++--- .../users/_components}/user_edit_view.tsx | 8 ++++---- .../users/_components}/view_users.test.tsx | 4 ++-- .../users/_components}/view_users.tsx | 14 +++++++------- .../users/_components}/view_users/columns.tsx | 2 +- .../_components}/view_users/table.test.tsx | 2 +- .../users/_components}/view_users/table.tsx | 2 +- .../view_users/user_info_view.test.tsx | 2 +- .../_components}/view_users/user_info_view.tsx | 12 ++++++------ .../src/app/(dashboard)/users/page.tsx | 2 +- .../src/components/networking.tsx | 18 ++++++++++++++++-- .../src/components/view_users/types.ts | 15 --------------- .../tests/CreateKeyPage.expiredToken.test.tsx | 1 - 20 files changed, 70 insertions(+), 69 deletions(-) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/BulkEditUsers.test.tsx (97%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/BulkEditUsers.tsx (99%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/DefaultUserSettings.test.tsx (94%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/DefaultUserSettings.tsx (97%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/edit_user.tsx (95%) create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/users/_components/index.tsx rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/user_edit_view.test.tsx (98%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/user_edit_view.tsx (95%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users.test.tsx (98%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users.tsx (97%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users/columns.tsx (99%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users/table.test.tsx (99%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users/table.tsx (99%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users/user_info_view.test.tsx (99%) rename ui/litellm-dashboard/src/{components => app/(dashboard)/users/_components}/view_users/user_info_view.tsx (98%) delete mode 100644 ui/litellm-dashboard/src/components/view_users/types.ts diff --git a/ui/litellm-dashboard/eslint-suppressions.json b/ui/litellm-dashboard/eslint-suppressions.json index 7a3c8f4a42c..7ea13deb934 100644 --- a/ui/litellm-dashboard/eslint-suppressions.json +++ b/ui/litellm-dashboard/eslint-suppressions.json @@ -376,7 +376,7 @@ "count": 1 } }, - "src/components/DefaultUserSettings.tsx": { + "src/app/(dashboard)/users/_components/DefaultUserSettings.tsx": { "no-restricted-imports": { "count": 1 } @@ -1001,7 +1001,7 @@ "count": 1 } }, - "src/components/edit_user.tsx": { + "src/app/(dashboard)/users/_components/edit_user.tsx": { "no-restricted-imports": { "count": 1 } @@ -1957,12 +1957,12 @@ "count": 2 } }, - "src/components/user_edit_view.test.tsx": { + "src/app/(dashboard)/users/_components/user_edit_view.test.tsx": { "react/display-name": { "count": 1 } }, - "src/components/user_edit_view.tsx": { + "src/app/(dashboard)/users/_components/user_edit_view.tsx": { "no-restricted-imports": { "count": 1 }, @@ -2047,7 +2047,7 @@ "count": 2 } }, - "src/components/view_users.tsx": { + "src/app/(dashboard)/users/_components/view_users.tsx": { "no-restricted-imports": { "count": 1 }, @@ -2055,7 +2055,7 @@ "count": 1 } }, - "src/components/view_users/columns.tsx": { + "src/app/(dashboard)/users/_components/view_users/columns.tsx": { "max-params": { "count": 1 }, @@ -2063,12 +2063,12 @@ "count": 1 } }, - "src/components/view_users/table.tsx": { + "src/app/(dashboard)/users/_components/view_users/table.tsx": { "no-restricted-imports": { "count": 1 } }, - "src/components/view_users/user_info_view.tsx": { + "src/app/(dashboard)/users/_components/view_users/user_info_view.tsx": { "no-restricted-imports": { "count": 1 }, diff --git a/ui/litellm-dashboard/src/components/BulkEditUsers.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.test.tsx similarity index 97% rename from ui/litellm-dashboard/src/components/BulkEditUsers.test.tsx rename to ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.test.tsx index f0af295017e..f16f5325952 100644 --- a/ui/litellm-dashboard/src/components/BulkEditUsers.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.test.tsx @@ -1,11 +1,11 @@ import userEvent from "@testing-library/user-event"; import { describe, expect, it, vi, beforeEach } from "vitest"; -import { renderWithProviders, screen, waitFor } from "../../tests/test-utils"; +import { renderWithProviders, screen, waitFor } from "../../../../../tests/test-utils"; import BulkEditUserModal from "./BulkEditUsers"; -import { userBulkUpdateUserCall, teamBulkMemberAddCall } from "./networking"; -import NotificationsManager from "./molecules/notifications_manager"; +import { userBulkUpdateUserCall, teamBulkMemberAddCall } from "@/components/networking"; +import NotificationsManager from "@/components/molecules/notifications_manager"; -vi.mock("./networking", () => ({ +vi.mock("@/components/networking", () => ({ userBulkUpdateUserCall: vi.fn(), teamBulkMemberAddCall: vi.fn(), })); diff --git a/ui/litellm-dashboard/src/components/BulkEditUsers.tsx b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.tsx similarity index 99% rename from ui/litellm-dashboard/src/components/BulkEditUsers.tsx rename to ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.tsx index 7bcfd793604..f22de171d68 100644 --- a/ui/litellm-dashboard/src/components/BulkEditUsers.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/BulkEditUsers.tsx @@ -1,8 +1,8 @@ import React, { useState } from "react"; import { Modal, Typography, Divider, Table, Select, InputNumber, Card, Space, Checkbox } from "antd"; -import { userBulkUpdateUserCall, teamBulkMemberAddCall, Member } from "./networking"; +import { userBulkUpdateUserCall, teamBulkMemberAddCall, Member } from "@/components/networking"; import { UserEditView } from "./user_edit_view"; -import NotificationsManager from "./molecules/notifications_manager"; +import NotificationsManager from "@/components/molecules/notifications_manager"; import MessageManager from "@/components/molecules/message_manager"; const { Text, Title } = Typography; diff --git a/ui/litellm-dashboard/src/components/DefaultUserSettings.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/DefaultUserSettings.test.tsx similarity index 94% rename from ui/litellm-dashboard/src/components/DefaultUserSettings.test.tsx rename to ui/litellm-dashboard/src/app/(dashboard)/users/_components/DefaultUserSettings.test.tsx index 78d50fa7f31..06dafcfcffd 100644 --- a/ui/litellm-dashboard/src/components/DefaultUserSettings.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/users/_components/DefaultUserSettings.test.tsx @@ -1,15 +1,15 @@ import { act, fireEvent, render, screen, waitFor } from "@testing-library/react"; import { beforeEach, describe, expect, it, vi } from "vitest"; import DefaultUserSettings from "./DefaultUserSettings"; -import * as networking from "./networking"; +import * as networking from "@/components/networking"; -vi.mock("./networking", () => ({ +vi.mock("@/components/networking", () => ({ getInternalUserSettings: vi.fn(), updateInternalUserSettings: vi.fn(), modelAvailableCall: vi.fn(), })); -vi.mock("./common_components/budget_duration_dropdown", () => ({ +vi.mock("@/components/common_components/budget_duration_dropdown", () => ({ default: ({ value, onChange }: { value: string | null; onChange: (value: string | null) => void }) => (

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