From ec16dbe09b93fda4371e2273ef40416088597d1b Mon Sep 17 00:00:00 2001 From: Jack Temple Date: Wed, 7 Jan 2026 14:16:29 -0700 Subject: [PATCH 001/114] fix: add allowClear to dropdown components for better UX --- .../src/components/agent_management/AgentSelector.tsx | 1 + .../components/common_components/PassThroughRoutesSelector.tsx | 1 + .../components/common_components/budget_duration_dropdown.tsx | 1 + .../src/components/common_components/team_dropdown.tsx | 1 + .../src/components/guardrails/GuardrailSelector.tsx | 1 + .../src/components/mcp_server_management/MCPServerSelector.tsx | 1 + .../components/vector_store_management/VectorStoreSelector.tsx | 1 + 7 files changed, 7 insertions(+) diff --git a/ui/litellm-dashboard/src/components/agent_management/AgentSelector.tsx b/ui/litellm-dashboard/src/components/agent_management/AgentSelector.tsx index a017004aaca..4debf284732 100644 --- a/ui/litellm-dashboard/src/components/agent_management/AgentSelector.tsx +++ b/ui/litellm-dashboard/src/components/agent_management/AgentSelector.tsx @@ -103,6 +103,7 @@ const AgentSelector: React.FC = ({ value={selectedValues} loading={loading} className={className} + allowClear showSearch style={{ width: "100%" }} disabled={disabled} diff --git a/ui/litellm-dashboard/src/components/common_components/PassThroughRoutesSelector.tsx b/ui/litellm-dashboard/src/components/common_components/PassThroughRoutesSelector.tsx index 116e3f6aa39..10482dffb2c 100644 --- a/ui/litellm-dashboard/src/components/common_components/PassThroughRoutesSelector.tsx +++ b/ui/litellm-dashboard/src/components/common_components/PassThroughRoutesSelector.tsx @@ -53,6 +53,7 @@ const PassThroughRoutesSelector: React.FC = ({ value={value} loading={loading} className={className} + allowClear options={passThroughRoutes.map((route) => ({ label: route, value: route, diff --git a/ui/litellm-dashboard/src/components/common_components/budget_duration_dropdown.tsx b/ui/litellm-dashboard/src/components/common_components/budget_duration_dropdown.tsx index 6fd97cbfd64..fcba5774644 100644 --- a/ui/litellm-dashboard/src/components/common_components/budget_duration_dropdown.tsx +++ b/ui/litellm-dashboard/src/components/common_components/budget_duration_dropdown.tsx @@ -23,6 +23,7 @@ const BudgetDurationDropdown: React.FC = ({ onChange={onChange} className={className} placeholder="n/a" + allowClear > diff --git a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx index 2747c6f80f5..d54724da2a7 100644 --- a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx +++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx @@ -18,6 +18,7 @@ const TeamDropdown: React.FC = ({ teams, value, onChange, dis value={value} onChange={onChange} disabled={disabled} + allowClear filterOption={(input, option) => { if (!option) return false; // Get team data from the option key diff --git a/ui/litellm-dashboard/src/components/guardrails/GuardrailSelector.tsx b/ui/litellm-dashboard/src/components/guardrails/GuardrailSelector.tsx index 9d72e86c2ff..0e0628cd18f 100644 --- a/ui/litellm-dashboard/src/components/guardrails/GuardrailSelector.tsx +++ b/ui/litellm-dashboard/src/components/guardrails/GuardrailSelector.tsx @@ -52,6 +52,7 @@ const GuardrailSelector: React.FC = ({ onChange, value, value={value} loading={loading} className={className} + allowClear options={guardrails.map((guardrail) => { console.log("Mapping guardrail:", guardrail); return { diff --git a/ui/litellm-dashboard/src/components/mcp_server_management/MCPServerSelector.tsx b/ui/litellm-dashboard/src/components/mcp_server_management/MCPServerSelector.tsx index 7b79f5cc707..929f6e6e531 100644 --- a/ui/litellm-dashboard/src/components/mcp_server_management/MCPServerSelector.tsx +++ b/ui/litellm-dashboard/src/components/mcp_server_management/MCPServerSelector.tsx @@ -87,6 +87,7 @@ const MCPServerSelector: React.FC = ({ value={selectedValues} loading={loading} className={className} + allowClear showSearch style={{ width: "100%" }} disabled={disabled} diff --git a/ui/litellm-dashboard/src/components/vector_store_management/VectorStoreSelector.tsx b/ui/litellm-dashboard/src/components/vector_store_management/VectorStoreSelector.tsx index ddb605542bc..2642b74e492 100644 --- a/ui/litellm-dashboard/src/components/vector_store_management/VectorStoreSelector.tsx +++ b/ui/litellm-dashboard/src/components/vector_store_management/VectorStoreSelector.tsx @@ -51,6 +51,7 @@ const VectorStoreSelector: React.FC = ({ value={value} loading={loading} className={className} + allowClear options={vectorStores.map((store) => ({ label: `${store.vector_store_name || store.vector_store_id} (${store.vector_store_id})`, value: store.vector_store_id, From 4c645c1ce36c40f5d2608c741bf91534f119d5a2 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Wed, 7 Jan 2026 21:01:41 -0800 Subject: [PATCH 002/114] Endpoint usage POC --- .../EndpointUsage/EndpointUsage.tsx | 25 +++ .../components/EndpointUsageBarChart.tsx | 55 +++++ .../components/EndpointUsageLineChart.tsx | 212 ++++++++++++++++++ .../components/EndpointUsageTable.tsx | 122 ++++++++++ .../EndpointUsage/mockEndpointData.ts | 94 ++++++++ .../UsagePage/components/UsagePageView.tsx | 5 + .../src/components/UsagePage/types.ts | 1 + 7 files changed, 514 insertions(+) create mode 100644 ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/EndpointUsage.tsx create mode 100644 ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageBarChart.tsx create mode 100644 ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx create mode 100644 ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageTable.tsx create mode 100644 ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/mockEndpointData.ts diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/EndpointUsage.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/EndpointUsage.tsx new file mode 100644 index 00000000000..b9e20f64b0b --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/EndpointUsage.tsx @@ -0,0 +1,25 @@ +import React from "react"; +import EndpointUsageBarChart from "./components/EndpointUsageBarChart"; +import EndpointUsageLineChart from "./components/EndpointUsageLineChart"; +import EndpointUsageTable from "./components/EndpointUsageTable"; +import { mockEndpointData } from "./mockEndpointData"; +import { DailyData } from "../../types"; + +interface EndpointUsageProps { + userSpendData?: { + results: DailyData[]; + metadata: any; + }; +} + +const EndpointUsage: React.FC = ({ userSpendData }) => { + return ( +
+ + + +
+ ); +}; + +export default EndpointUsage; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageBarChart.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageBarChart.tsx new file mode 100644 index 00000000000..1ab3c49a7e6 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageBarChart.tsx @@ -0,0 +1,55 @@ +import React from "react"; +import { BarChart, Card, Title } from "@tremor/react"; +import { CustomLegend, CustomTooltip } from "@/components/common_components/chartUtils"; +import { MetricWithMetadata } from "../../../types"; +import { mockEndpointData } from "../mockEndpointData"; + +interface EndpointUsageBarChartProps { + endpointData?: Record; +} + +const EndpointUsageBarChart: React.FC = ({ endpointData }) => { + // Use mock data if no endpointData is provided + const dataToUse = endpointData || mockEndpointData; + + // Transform endpoint data into chart format + const chartData = React.useMemo(() => { + return Object.entries(dataToUse).map(([endpoint, data]) => ({ + endpoint, + "metrics.successful_requests": data.metrics.successful_requests, + "metrics.failed_requests": data.metrics.failed_requests, + metrics: { + successful_requests: data.metrics.successful_requests, + failed_requests: data.metrics.failed_requests, + }, + })); + }, [dataToUse]); + + const valueFormatter = (value: number) => value.toLocaleString(); + + return ( + +
+ Success vs Failed Requests by Endpoint + +
+ + + ); +}; + +export default EndpointUsageBarChart; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx new file mode 100644 index 00000000000..2bb897c89f6 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx @@ -0,0 +1,212 @@ +import React, { useMemo, useState } from "react"; +import { Card, LineChart, Title } from "@tremor/react"; +import { Segmented } from "antd"; +import { BreakdownMetrics, DailyData, MetricWithMetadata } from "../../../types"; +import { mockEndpointData } from "../mockEndpointData"; + +interface EndpointUsageLineChartProps { + dailyData?: { results: DailyData[] }; + endpointData?: Record; +} + +type TimePeriod = "7" | "30" | "90"; + +// Create mock daily data from aggregated endpoint data +function createMockDailyData(endpointData: Record, days: number): DailyData[] { + const today = new Date(); + const dailyResults: DailyData[] = []; + + for (let i = days - 1; i >= 0; i--) { + const date = new Date(today); + date.setDate(date.getDate() - i); + const dateStr = date.toISOString().split("T")[0]; + + // Distribute aggregated totals across days with some variation + const breakdown: { [key: string]: MetricWithMetadata } = {}; + Object.entries(endpointData).forEach(([endpointName, endpoint]) => { + // Calculate average daily values + const avgDaily = { + spend: endpoint.metrics.spend / days, + prompt_tokens: endpoint.metrics.prompt_tokens / days, + completion_tokens: endpoint.metrics.completion_tokens / days, + total_tokens: endpoint.metrics.total_tokens / days, + api_requests: endpoint.metrics.api_requests / days, + successful_requests: endpoint.metrics.successful_requests / days, + failed_requests: endpoint.metrics.failed_requests / days, + cache_read_input_tokens: endpoint.metrics.cache_read_input_tokens / days, + cache_creation_input_tokens: endpoint.metrics.cache_creation_input_tokens / days, + }; + + // Add simple variation (±20%) to make it look more realistic + const variation = 0.8 + Math.random() * 0.4; // Random factor between 0.8 and 1.2 + + breakdown[endpointName] = { + metrics: { + spend: avgDaily.spend * variation, + prompt_tokens: Math.round(avgDaily.prompt_tokens * variation), + completion_tokens: Math.round(avgDaily.completion_tokens * variation), + total_tokens: Math.round(avgDaily.total_tokens * variation), + api_requests: Math.round(avgDaily.api_requests * variation), + successful_requests: Math.round(avgDaily.successful_requests * variation), + failed_requests: Math.round(avgDaily.failed_requests * variation), + cache_read_input_tokens: Math.round(avgDaily.cache_read_input_tokens * variation), + cache_creation_input_tokens: Math.round(avgDaily.cache_creation_input_tokens * variation), + }, + metadata: endpoint.metadata, + api_key_breakdown: endpoint.api_key_breakdown, + }; + }); + + const breakdownMetrics: BreakdownMetrics = { + models: {}, + model_groups: {}, + mcp_servers: {}, + providers: {}, + api_keys: {}, + entities: {}, + endpoints: breakdown, + }; + + dailyResults.push({ + date: dateStr, + metrics: { + spend: 0, + prompt_tokens: 0, + completion_tokens: 0, + total_tokens: 0, + api_requests: 0, + successful_requests: 0, + failed_requests: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + }, + breakdown: breakdownMetrics, + }); + } + + return dailyResults; +} + +// Transform daily data into chart format +function transformDailyDataToChart(dailyData: DailyData[], days: number): Array> { + const chartData: Array> = []; + + // Get all unique endpoint names + const endpointNames = new Set(); + dailyData.forEach((day) => { + if (day.breakdown.endpoints) { + Object.keys(day.breakdown.endpoints).forEach((name) => endpointNames.add(name)); + } + }); + + // Filter to the last N days based on time period + const filteredData = dailyData.slice(-days); + + filteredData.forEach((day) => { + const date = new Date(day.date); + const dateStr = date.toLocaleDateString("en-US", { + month: "short", + day: "numeric", + }); + + const dataPoint: Record = { + date: dateStr, + }; + + endpointNames.forEach((endpointName) => { + const endpoint = day.breakdown.endpoints?.[endpointName]; + dataPoint[endpointName] = endpoint?.metrics.api_requests || 0; + }); + + chartData.push(dataPoint); + }); + + return chartData; +} + +export function EndpointUsageLineChart({ dailyData, endpointData }: EndpointUsageLineChartProps) { + const [timePeriod, setTimePeriod] = useState("7"); + const days = parseInt(timePeriod); + + // Use daily data if provided and has endpoints, otherwise create mock daily data from aggregated endpoint data + const chartData = useMemo(() => { + // Check if dailyData has endpoints breakdown + const hasEndpointsInDailyData = + dailyData?.results && + dailyData.results.some((day) => day.breakdown.endpoints && Object.keys(day.breakdown.endpoints).length > 0); + + if (hasEndpointsInDailyData) { + // Check if we have a reasonable number of endpoints (at least 2 for proof of concept) + const endpointCount = new Set(); + dailyData.results.forEach((day) => { + if (day.breakdown.endpoints) { + Object.keys(day.breakdown.endpoints).forEach((name) => endpointCount.add(name)); + } + }); + + // If we have multiple endpoints in real data, use it; otherwise use mock data for proof of concept + if (endpointCount.size >= 2) { + return transformDailyDataToChart(dailyData.results, days); + } + } + + // Use mock data for proof of concept + const dataToUse = endpointData || mockEndpointData; + const mockDaily = createMockDailyData(dataToUse, days); + return transformDailyDataToChart(mockDaily, days); + }, [dailyData, endpointData, days]); + + // Get endpoint names from chart data + const categories = useMemo(() => { + if (chartData.length === 0) return []; + const keys = Object.keys(chartData[0]).filter((key) => key !== "date"); + return keys; + }, [chartData]); + + // Tremor color palette for multiple lines + const colors = ["blue", "cyan", "indigo", "violet", "purple", "fuchsia", "pink", "rose", "red", "orange"]; + + return ( + +
+ Endpoint Usage Trends + setTimePeriod(value as TimePeriod)} + style={{ + backgroundColor: "#f3f4f6", + }} + /> +
+ value.toLocaleString()} + showLegend={true} + showGridLines={true} + yAxisWidth={60} + connectNulls={true} + curveType="natural" + /> + + ); +} + +export default EndpointUsageLineChart; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageTable.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageTable.tsx new file mode 100644 index 00000000000..f5cfb553370 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageTable.tsx @@ -0,0 +1,122 @@ +import React from "react"; +import { Table, Progress } from "antd"; +import type { ColumnsType } from "antd/es/table"; +import { formatNumberWithCommas } from "@/utils/dataUtils"; +import { MetricWithMetadata } from "../../../types"; + +interface EndpointUsageTableProps { + endpointData: Record; +} + +interface EndpointRow { + key: string; + endpoint: string; + successful_requests: number; + failed_requests: number; + api_requests: number; + total_tokens: number; + spend: number; + successRate: number; +} + +const EndpointUsageTable: React.FC = ({ endpointData }) => { + const calculateSuccessRate = (successful: number, total: number): number => { + if (total === 0) return 0; + return (successful / total) * 100; + }; + + const dataSource: EndpointRow[] = Object.entries(endpointData).map(([endpoint, data]) => ({ + key: endpoint, + endpoint, + successful_requests: data.metrics.successful_requests, + failed_requests: data.metrics.failed_requests, + api_requests: data.metrics.api_requests, + total_tokens: data.metrics.total_tokens, + spend: data.metrics.spend, + successRate: calculateSuccessRate(data.metrics.successful_requests, data.metrics.api_requests), + })); + + const columns: ColumnsType = [ + { + title: "Endpoint", + dataIndex: "endpoint", + key: "endpoint", + render: (text: string) => {text}, + }, + { + title: "Successful / Failed", + key: "requests", + render: (_: any, record: EndpointRow) => { + const successPercentage = + record.api_requests > 0 ? (record.successful_requests / record.api_requests) * 100 : 0; + const failurePercentage = record.api_requests > 0 ? (record.failed_requests / record.api_requests) * 100 : 0; + const totalPercentage = successPercentage + failurePercentage; + + const strokeColorConfig: Record = { + "0%": "#22c55e", + }; + if (successPercentage > 0 && successPercentage < 100) { + strokeColorConfig[`${successPercentage}%`] = "#22c55e"; + strokeColorConfig[`${successPercentage + 0.01}%`] = "#ef4444"; + } + strokeColorConfig["100%"] = failurePercentage > 0 ? "#ef4444" : "#22c55e"; + + return ( +
+
+ +
+
+ {record.successful_requests.toLocaleString()} + / + {record.failed_requests.toLocaleString()} +
+
+ ); + }, + }, + { + title: "Total Request", + dataIndex: "api_requests", + key: "api_requests", + render: (value: number) => value.toLocaleString(), + }, + { + title: "Success Rate", + dataIndex: "successRate", + key: "successRate", + render: (value: number) => { + const successRateStr = value.toFixed(2); + return ( + = 95 + ? "text-green-600 font-medium" + : value >= 80 + ? "text-yellow-600 font-medium" + : "text-red-600 font-medium" + } + > + {successRateStr}% + + ); + }, + }, + { + title: "Total Tokens", + dataIndex: "total_tokens", + key: "total_tokens", + render: (value: number) => value.toLocaleString(), + }, + { + title: "Spend", + dataIndex: "spend", + key: "spend", + render: (value: number) => `$${formatNumberWithCommas(value, 2)}`, + }, + ]; + + return ; +}; + +export default EndpointUsageTable; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/mockEndpointData.ts b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/mockEndpointData.ts new file mode 100644 index 00000000000..cb5424dde69 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/mockEndpointData.ts @@ -0,0 +1,94 @@ +import { MetricWithMetadata } from "../../types"; + +export const mockEndpointData: Record = { + "/chat/completions": { + metrics: { + spend: 1250.45, + prompt_tokens: 150000, + completion_tokens: 45000, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 195000, + successful_requests: 1250, + failed_requests: 45, + api_requests: 1295, + }, + metadata: {}, + api_key_breakdown: {}, + }, + "/audio/speech": { + metrics: { + spend: 320.78, + prompt_tokens: 0, + completion_tokens: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 0, + successful_requests: 890, + failed_requests: 12, + api_requests: 902, + }, + metadata: {}, + api_key_breakdown: {}, + }, + "/audio/transcriptions": { + metrics: { + spend: 85.23, + prompt_tokens: 0, + completion_tokens: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 0, + successful_requests: 234, + failed_requests: 8, + api_requests: 242, + }, + metadata: {}, + api_key_breakdown: {}, + }, + "/embeddings": { + metrics: { + spend: 450.12, + prompt_tokens: 200000, + completion_tokens: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 200000, + successful_requests: 2100, + failed_requests: 23, + api_requests: 2123, + }, + metadata: {}, + api_key_breakdown: {}, + }, + "/images/generations": { + metrics: { + spend: 180.56, + prompt_tokens: 0, + completion_tokens: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 0, + successful_requests: 156, + failed_requests: 5, + api_requests: 161, + }, + metadata: {}, + api_key_breakdown: {}, + }, + "/moderations": { + metrics: { + spend: 95.34, + prompt_tokens: 50000, + completion_tokens: 0, + cache_read_input_tokens: 0, + cache_creation_input_tokens: 0, + total_tokens: 50000, + successful_requests: 567, + failed_requests: 3, + api_requests: 570, + }, + metadata: {}, + api_key_breakdown: {}, + }, +}; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/UsagePageView.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/UsagePageView.tsx index a9c86c064ef..01ad2c7b466 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/UsagePageView.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/UsagePageView.tsx @@ -53,6 +53,7 @@ import EntityUsage, { EntityList } from "./EntityUsage/EntityUsage"; import TopKeyView from "./EntityUsage/TopKeyView"; import { UsageOption, UsageViewSelect } from "./UsageViewSelect/UsageViewSelect"; import { useCurrentUser } from "@/app/(dashboard)/hooks/users/useCurrentUser"; +import EndpointUsage from "./EndpointUsage/EndpointUsage"; interface UsagePageProps { teams: Team[]; @@ -439,6 +440,7 @@ const UsagePage: React.FC = ({ teams, organizations }) => { Model Activity Key Activity MCP Server Activity + Endpoint Activity
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from typing import ( diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 73579db75cd..2f34d2a7d3d 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -410,8 +410,8 @@ "max_input_tokens": 8172, "max_tokens": 8172, "mode": "embedding", - "input_cost_per_token": 1.35e-7, - "input_cost_per_image": 6e-5, + "input_cost_per_token": 1.35e-07, + "input_cost_per_image": 6e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, "output_cost_per_token": 0.0, @@ -1398,8 +1398,8 @@ "mode": "chat" }, "azure_ai/gpt-oss-120b": { - "input_cost_per_token": 1.5e-7, - "output_cost_per_token": 6e-7, + "input_cost_per_token": 1.5e-07, + "output_cost_per_token": 6e-07, "litellm_provider": "azure_ai", "max_input_tokens": 131072, "max_output_tokens": 131072, @@ -2077,7 +2077,7 @@ "litellm_provider": "azure", "max_input_tokens": 4097, "max_output_tokens": 4096, - "max_tokens": 4097, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -2090,7 +2090,7 @@ "litellm_provider": "azure", "max_input_tokens": 4097, "max_output_tokens": 4096, - "max_tokens": 4097, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -2869,7 +2869,7 @@ "/v1/audio/transcriptions" ] }, - "azure/gpt-5.1-2025-11-13": { + "azure/gpt-5.1-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, @@ -2905,7 +2905,7 @@ "supports_service_tier": true, "supports_vision": true }, - "azure/gpt-5.1-chat-2025-11-13": { + "azure/gpt-5.1-chat-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, @@ -2940,7 +2940,7 @@ "supports_tool_choice": false, "supports_vision": true }, - "azure/gpt-5.1-codex-2025-11-13": { + "azure/gpt-5.1-codex-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, @@ -3298,7 +3298,7 @@ "litellm_provider": "azure", "max_input_tokens": 272000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.00012, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/foundry-models/concepts/models-sold-directly-by-azure?pivots=azure-openai&tabs=global-standard-aoai%2Cstandard-chat-completions%2Cglobal-standard#gpt-5", @@ -3623,7 +3623,7 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", - "output_cost_per_token": 1.68e-04, + "output_cost_per_token": 0.000168, "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -3654,7 +3654,7 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", - "output_cost_per_token": 1.68e-04, + "output_cost_per_token": 0.000168, "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -4297,13 +4297,13 @@ "output_cost_per_token": 0.0 }, "azure/speech/azure-tts": { - "input_cost_per_character": 15e-06, + "input_cost_per_character": 1.5e-05, "litellm_provider": "azure", "mode": "audio_speech", "source": "https://azure.microsoft.com/en-us/pricing/calculator/" }, "azure/speech/azure-tts-hd": { - "input_cost_per_character": 30e-06, + "input_cost_per_character": 3e-05, "litellm_provider": "azure", "mode": "audio_speech", "source": "https://azure.microsoft.com/en-us/pricing/calculator/" @@ -5197,7 +5197,7 @@ }, "azure_ai/mistral-document-ai-2505": { "litellm_provider": "azure_ai", - "ocr_cost_per_page": 3e-3, + "ocr_cost_per_page": 0.003, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -5206,7 +5206,7 @@ }, "azure_ai/doc-intelligence/prebuilt-read": { "litellm_provider": "azure_ai", - "ocr_cost_per_page": 1.5e-3, + "ocr_cost_per_page": 0.0015, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -5215,7 +5215,7 @@ }, "azure_ai/doc-intelligence/prebuilt-layout": { "litellm_provider": "azure_ai", - "ocr_cost_per_page": 1e-2, + "ocr_cost_per_page": 0.01, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -5224,7 +5224,7 @@ }, "azure_ai/doc-intelligence/prebuilt-document": { "litellm_provider": "azure_ai", - "ocr_cost_per_page": 1e-2, + "ocr_cost_per_page": 0.01, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -5298,12 +5298,12 @@ "mode": "rerank", "output_cost_per_token": 0.0 }, - "azure_ai/deepseek-v3.2": { + "azure_ai/deepseek-v3.2": { "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 1.68e-06, "supports_assistant_prefill": true, @@ -5317,7 +5317,7 @@ "litellm_provider": "azure_ai", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 1.68e-06, "supports_assistant_prefill": true, @@ -5452,7 +5452,7 @@ "supports_web_search": true }, "azure_ai/grok-4-fast-non-reasoning": { - "input_cost_per_token": 0.43e-06, + "input_cost_per_token": 4.3e-07, "output_cost_per_token": 1.73e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -5465,7 +5465,7 @@ "supports_web_search": true }, "azure_ai/grok-4-fast-reasoning": { - "input_cost_per_token": 0.43e-06, + "input_cost_per_token": 4.3e-07, "output_cost_per_token": 1.73e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -5623,7 +5623,7 @@ "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, - "max_tokens": 16384, + "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 4e-07 }, @@ -7038,7 +7038,7 @@ "litellm_provider": "anthropic", "max_input_tokens": 1000000, "max_output_tokens": 64000, - "max_tokens": 1000000, + "max_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.5e-05, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -7800,7 +7800,7 @@ "litellm_provider": "deepseek", "max_input_tokens": 131072, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.7e-06, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -7821,7 +7821,7 @@ "litellm_provider": "deepseek", "max_input_tokens": 131072, "max_output_tokens": 65536, - "max_tokens": 131072, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.7e-06, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -7842,7 +7842,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 1000000, "max_output_tokens": 16384, - "max_tokens": 1000000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-06, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -7854,7 +7854,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 32768, - "max_tokens": 1000000, + "max_tokens": 32768, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -7883,7 +7883,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 32768, - "max_tokens": 1000000, + "max_tokens": 32768, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -7913,7 +7913,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 30720, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 6.4e-06, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -7926,7 +7926,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.2e-06, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -7939,7 +7939,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.2e-06, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -7952,7 +7952,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_reasoning_token": 4e-06, "output_cost_per_token": 1.2e-06, @@ -7966,7 +7966,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_reasoning_token": 4e-06, "output_cost_per_token": 1.2e-06, @@ -7979,7 +7979,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 32768, - "max_tokens": 1000000, + "max_tokens": 32768, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8010,7 +8010,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 32768, - "max_tokens": 1000000, + "max_tokens": 32768, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8041,7 +8041,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 32768, - "max_tokens": 1000000, + "max_tokens": 32768, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8073,7 +8073,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_reasoning_token": 5e-07, "output_cost_per_token": 2e-07, @@ -8087,7 +8087,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 1000000, "max_output_tokens": 8192, - "max_tokens": 1000000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 2e-07, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -8100,7 +8100,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 1000000, "max_output_tokens": 16384, - "max_tokens": 1000000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_reasoning_token": 5e-07, "output_cost_per_token": 2e-07, @@ -8114,7 +8114,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 1000000, "max_output_tokens": 16384, - "max_tokens": 1000000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_reasoning_token": 5e-07, "output_cost_per_token": 2e-07, @@ -8127,7 +8127,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 129024, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8138,7 +8138,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 65536, - "max_tokens": 1000000, + "max_tokens": 65536, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8187,7 +8187,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 65536, - "max_tokens": 1000000, + "max_tokens": 65536, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8232,7 +8232,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 65536, - "max_tokens": 1000000, + "max_tokens": 65536, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8281,7 +8281,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 997952, "max_output_tokens": 65536, - "max_tokens": 1000000, + "max_tokens": 65536, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8326,7 +8326,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 258048, "max_output_tokens": 65536, - "max_tokens": 262144, + "max_tokens": 65536, "mode": "chat", "source": "https://www.alibabacloud.com/help/en/model-studio/models", "supports_function_calling": true, @@ -8364,7 +8364,7 @@ "litellm_provider": "dashscope", "max_input_tokens": 98304, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.4e-06, "source": "https://www.alibabacloud.com/help/en/model-studio/models", @@ -8393,7 +8393,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 128000, - "max_tokens": 200000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8412,7 +8412,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8431,7 +8431,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, - "max_tokens": 200000, + "max_tokens": 32000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8450,7 +8450,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 32000, - "max_tokens": 200000, + "max_tokens": 32000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8469,7 +8469,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8488,7 +8488,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8507,7 +8507,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8526,7 +8526,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8545,7 +8545,7 @@ "litellm_provider": "databricks", "max_input_tokens": 1048576, "max_output_tokens": 65535, - "max_tokens": 1048576, + "max_tokens": 65535, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8562,7 +8562,7 @@ "litellm_provider": "databricks", "max_input_tokens": 1048576, "max_output_tokens": 65536, - "max_tokens": 1048576, + "max_tokens": 65536, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8579,7 +8579,7 @@ "litellm_provider": "databricks", "max_input_tokens": 128000, "max_output_tokens": 32000, - "max_tokens": 128000, + "max_tokens": 32000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8594,7 +8594,7 @@ "litellm_provider": "databricks", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8609,7 +8609,7 @@ "litellm_provider": "databricks", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8624,7 +8624,7 @@ "litellm_provider": "databricks", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8639,7 +8639,7 @@ "litellm_provider": "databricks", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8747,7 +8747,7 @@ "litellm_provider": "databricks", "max_input_tokens": 200000, "max_output_tokens": 128000, - "max_tokens": 200000, + "max_tokens": 128000, "metadata": { "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." }, @@ -8846,7 +8846,7 @@ "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, - "max_tokens": 16384, + "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 2e-06 }, @@ -10107,7 +10107,7 @@ "litellm_provider": "deepseek", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 4e-07, "supports_assistant_prefill": true, @@ -10121,7 +10121,7 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 163840, "max_output_tokens": 81920, - "max_tokens": 163840, + "max_tokens": 81920, "mode": "chat", "output_cost_per_token": 1.68e-06, "supports_function_calling": true, @@ -10202,14 +10202,14 @@ "mode": "search", "tiered_pricing": [ { - "input_cost_per_query": 5e-03, + "input_cost_per_query": 0.005, "max_results_range": [ 0, 25 ] }, { - "input_cost_per_query": 25e-03, + "input_cost_per_query": 0.025, "max_results_range": [ 26, 100 @@ -10222,70 +10222,70 @@ "mode": "search", "tiered_pricing": [ { - "input_cost_per_query": 1.66e-03, + "input_cost_per_query": 0.00166, "max_results_range": [ 1, 10 ] }, { - "input_cost_per_query": 3.32e-03, + "input_cost_per_query": 0.00332, "max_results_range": [ 11, 20 ] }, { - "input_cost_per_query": 4.98e-03, + "input_cost_per_query": 0.00498, "max_results_range": [ 21, 30 ] }, { - "input_cost_per_query": 6.64e-03, + "input_cost_per_query": 0.00664, "max_results_range": [ 31, 40 ] }, { - "input_cost_per_query": 8.3e-03, + "input_cost_per_query": 0.0083, "max_results_range": [ 41, 50 ] }, { - "input_cost_per_query": 9.96e-03, + "input_cost_per_query": 0.00996, "max_results_range": [ 51, 60 ] }, { - "input_cost_per_query": 11.62e-03, + "input_cost_per_query": 0.01162, "max_results_range": [ 61, 70 ] }, { - "input_cost_per_query": 13.28e-03, + "input_cost_per_query": 0.01328, "max_results_range": [ 71, 80 ] }, { - "input_cost_per_query": 14.94e-03, + "input_cost_per_query": 0.01494, "max_results_range": [ 81, 90 ] }, { - "input_cost_per_query": 16.6e-03, + "input_cost_per_query": 0.0166, "max_results_range": [ 91, 100 @@ -10297,7 +10297,7 @@ } }, "perplexity/search": { - "input_cost_per_query": 5e-03, + "input_cost_per_query": 0.005, "litellm_provider": "perplexity", "mode": "search" }, @@ -10395,7 +10395,7 @@ "supports_embedding_image_input": true }, "embed-multilingual-light-v3.0": { - "input_cost_per_token": 1e-04, + "input_cost_per_token": 0.0001, "litellm_provider": "cohere", "max_input_tokens": 1024, "max_tokens": 1024, @@ -10689,7 +10689,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.3e-07, "supports_function_calling": true, @@ -10700,7 +10700,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.9e-07, "supports_function_calling": true, @@ -10711,7 +10711,7 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, "supports_function_calling": true, @@ -10817,14 +10817,14 @@ "litellm_provider": "featherless_ai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat" }, "featherless_ai/featherless-ai/Qwerky-QwQ-32B": { "litellm_provider": "featherless_ai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat" }, "fireworks-ai-4.1b-to-16b": { @@ -11031,7 +11031,7 @@ "supports_tool_choice": true }, "fireworks_ai/accounts/fireworks/models/glm-4p6": { - "input_cost_per_token": 0.55e-06, + "input_cost_per_token": 5.5e-07, "output_cost_per_token": 2.19e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 202800, @@ -11077,7 +11077,7 @@ "litellm_provider": "fireworks_ai", "max_input_tokens": 131072, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 2.5e-06, "source": "https://fireworks.ai/models/fireworks/kimi-k2-instruct", @@ -11090,7 +11090,7 @@ "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, - "max_tokens": 262144, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 2.5e-06, "source": "https://app.fireworks.ai/models/fireworks/kimi-k2-instruct-0905", @@ -11337,7 +11337,7 @@ "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, - "max_tokens": 16384, + "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.6e-06, "output_cost_per_token_batches": 2e-07 @@ -11348,7 +11348,7 @@ "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, - "max_tokens": 16384, + "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 1e-06 @@ -11638,7 +11638,7 @@ "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 8192, "max_output_tokens": 2048, - "max_tokens": 8192, + "max_tokens": 2048, "mode": "chat", "output_cost_per_character": 3.75e-07, "output_cost_per_token": 1.5e-06, @@ -11655,7 +11655,7 @@ "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 8192, "max_output_tokens": 2048, - "max_tokens": 8192, + "max_tokens": 2048, "mode": "chat", "output_cost_per_character": 3.75e-07, "output_cost_per_token": 1.5e-06, @@ -12585,10 +12585,10 @@ "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, - "max_tokens": 65536, + "max_tokens": 32768, "mode": "image_generation", "output_cost_per_image": 0.134, - "output_cost_per_image_token": 1.2e-04, + "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, "source": "https://ai.google.dev/gemini-api/docs/pricing", @@ -14112,7 +14112,7 @@ "max_input_tokens": 1048576, "max_output_tokens": 65536, "max_pdf_size_mb": 30, - "max_tokens": 8192, + "max_tokens": 65536, "max_video_length": 1, "max_videos_per_prompt": 10, "mode": "chat", @@ -14162,7 +14162,7 @@ "max_input_tokens": 1048576, "max_output_tokens": 65536, "max_pdf_size_mb": 30, - "max_tokens": 8192, + "max_tokens": 65536, "max_video_length": 1, "max_videos_per_prompt": 10, "mode": "chat", @@ -14388,10 +14388,10 @@ "litellm_provider": "gemini", "max_input_tokens": 65536, "max_output_tokens": 32768, - "max_tokens": 65536, + "max_tokens": 32768, "mode": "image_generation", "output_cost_per_image": 0.134, - "output_cost_per_image_token": 1.2e-04, + "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "rpm": 1000, "tpm": 4000000, @@ -15524,7 +15524,7 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.40, + "output_cost_per_second": 0.4, "source": "https://ai.google.dev/gemini-api/docs/video", "supported_modalities": [ "text" @@ -15552,7 +15552,7 @@ "max_input_tokens": 1024, "max_tokens": 1024, "mode": "video_generation", - "output_cost_per_second": 0.40, + "output_cost_per_second": 0.4, "source": "https://ai.google.dev/gemini-api/docs/video", "supported_modalities": [ "text" @@ -16056,11 +16056,11 @@ "supports_vision": true }, "gpt-3.5-turbo": { - "input_cost_per_token": 0.5e-06, + "input_cost_per_token": 5e-07, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 4097, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, "supports_function_calling": true, @@ -16073,7 +16073,7 @@ "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 16385, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, "supports_function_calling": true, @@ -16087,7 +16087,7 @@ "litellm_provider": "openai", "max_input_tokens": 4097, "max_output_tokens": 4096, - "max_tokens": 4097, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_prompt_caching": true, @@ -16099,7 +16099,7 @@ "litellm_provider": "openai", "max_input_tokens": 4097, "max_output_tokens": 4096, - "max_tokens": 4097, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -16113,7 +16113,7 @@ "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 16385, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -16127,7 +16127,7 @@ "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 16385, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 4e-06, "supports_prompt_caching": true, @@ -16139,7 +16139,7 @@ "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 16385, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 4e-06, "supports_prompt_caching": true, @@ -17191,7 +17191,7 @@ "supports_pdf_input": true }, "high/1024-x-1536/gpt-image-1.5": { - "input_cost_per_image": 0.20, + "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", "supported_endpoints": [ @@ -17202,7 +17202,7 @@ "supports_pdf_input": true }, "high/1536-x-1024/gpt-image-1.5": { - "input_cost_per_image": 0.20, + "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", "supported_endpoints": [ @@ -17356,7 +17356,7 @@ "supports_pdf_input": true }, "high/1024-x-1536/gpt-image-1.5-2025-12-16": { - "input_cost_per_image": 0.20, + "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", "supported_endpoints": [ @@ -17367,7 +17367,7 @@ "supports_pdf_input": true }, "high/1536-x-1024/gpt-image-1.5-2025-12-16": { - "input_cost_per_image": 0.20, + "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", "supported_endpoints": [ @@ -17704,7 +17704,7 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", - "output_cost_per_token": 1.68e-04, + "output_cost_per_token": 0.000168, "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -17735,7 +17735,7 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", - "output_cost_per_token": 1.68e-04, + "output_cost_per_token": 0.000168, "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -17767,7 +17767,7 @@ "max_output_tokens": 272000, "max_tokens": 272000, "mode": "responses", - "output_cost_per_token": 1.2e-04, + "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, "supported_endpoints": [ "/v1/batch", @@ -17800,7 +17800,7 @@ "max_output_tokens": 272000, "max_tokens": 272000, "mode": "responses", - "output_cost_per_token": 1.2e-04, + "output_cost_per_token": 0.00012, "output_cost_per_token_batches": 6e-05, "supported_endpoints": [ "/v1/batch", @@ -18503,7 +18503,7 @@ "lemonade/Qwen3-Coder-30B-A3B-Instruct-GGUF": { "input_cost_per_token": 0, "litellm_provider": "lemonade", - "max_tokens": 262144, + "max_tokens": 32768, "max_input_tokens": 262144, "max_output_tokens": 32768, "mode": "chat", @@ -18515,7 +18515,7 @@ "lemonade/gpt-oss-20b-mxfp4-GGUF": { "input_cost_per_token": 0, "litellm_provider": "lemonade", - "max_tokens": 131072, + "max_tokens": 32768, "max_input_tokens": 131072, "max_output_tokens": 32768, "mode": "chat", @@ -18527,7 +18527,7 @@ "lemonade/gpt-oss-120b-mxfp-GGUF": { "input_cost_per_token": 0, "litellm_provider": "lemonade", - "max_tokens": 131072, + "max_tokens": 32768, "max_input_tokens": 131072, "max_output_tokens": 32768, "mode": "chat", @@ -18539,7 +18539,7 @@ "lemonade/Gemma-3-4b-it-GGUF": { "input_cost_per_token": 0, "litellm_provider": "lemonade", - "max_tokens": 128000, + "max_tokens": 8192, "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", @@ -18551,7 +18551,7 @@ "lemonade/Qwen3-4B-Instruct-2507-GGUF": { "input_cost_per_token": 0, "litellm_provider": "lemonade", - "max_tokens": 262144, + "max_tokens": 32768, "max_input_tokens": 262144, "max_output_tokens": 32768, "mode": "chat", @@ -18688,11 +18688,11 @@ "groq/moonshotai/kimi-k2-instruct-0905": { "input_cost_per_token": 1e-06, "output_cost_per_token": 3e-06, - "cache_read_input_token_cost": 0.5e-06, + "cache_read_input_token_cost": 5e-07, "litellm_provider": "groq", "max_input_tokens": 262144, "max_output_tokens": 16384, - "max_tokens": 278528, + "max_tokens": 16384, "mode": "chat", "supports_function_calling": true, "supports_response_schema": true, @@ -19353,7 +19353,7 @@ "litellm_provider": "lambda_ai", "max_input_tokens": 131072, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1e-07, "supports_function_calling": true, @@ -19366,7 +19366,7 @@ "litellm_provider": "lambda_ai", "max_input_tokens": 16384, "max_output_tokens": 8192, - "max_tokens": 16384, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1e-07, "supports_function_calling": true, @@ -19702,7 +19702,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.6e-05, "supports_function_calling": true, @@ -19713,7 +19713,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 9.9e-07, "supports_function_calling": true, @@ -19724,7 +19724,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 2.2e-07, "supports_function_calling": true, @@ -19735,7 +19735,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 3.5e-07, "supports_function_calling": true, @@ -19747,7 +19747,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1e-07, "supports_function_calling": true, @@ -19758,7 +19758,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-07, "supports_function_calling": true, @@ -19769,7 +19769,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -19851,7 +19851,7 @@ "litellm_provider": "meta_llama", "max_input_tokens": 128000, "max_output_tokens": 4028, - "max_tokens": 128000, + "max_tokens": 4028, "mode": "chat", "source": "https://llama.developer.meta.com/docs/models", "supported_modalities": [ @@ -19867,7 +19867,7 @@ "litellm_provider": "meta_llama", "max_input_tokens": 128000, "max_output_tokens": 4028, - "max_tokens": 128000, + "max_tokens": 4028, "mode": "chat", "source": "https://llama.developer.meta.com/docs/models", "supported_modalities": [ @@ -19883,7 +19883,7 @@ "litellm_provider": "meta_llama", "max_input_tokens": 1000000, "max_output_tokens": 4028, - "max_tokens": 128000, + "max_tokens": 4028, "mode": "chat", "source": "https://llama.developer.meta.com/docs/models", "supported_modalities": [ @@ -19900,7 +19900,7 @@ "litellm_provider": "meta_llama", "max_input_tokens": 10000000, "max_output_tokens": 4028, - "max_tokens": 128000, + "max_tokens": 4028, "mode": "chat", "source": "https://llama.developer.meta.com/docs/models", "supported_modalities": [ @@ -19932,7 +19932,7 @@ ] }, "minimax/speech-02-turbo": { - "input_cost_per_character": 0.00006, + "input_cost_per_character": 6e-05, "litellm_provider": "minimax", "mode": "audio_speech", "supported_endpoints": [ @@ -19948,7 +19948,7 @@ ] }, "minimax/speech-2.6-turbo": { - "input_cost_per_character": 0.00006, + "input_cost_per_character": 6e-05, "litellm_provider": "minimax", "mode": "audio_speech", "supported_endpoints": [ @@ -20278,8 +20278,8 @@ }, "mistral/mistral-ocr-latest": { "litellm_provider": "mistral", - "ocr_cost_per_page": 1e-3, - "annotation_cost_per_page": 3e-3, + "ocr_cost_per_page": 0.001, + "annotation_cost_per_page": 0.003, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -20288,8 +20288,8 @@ }, "mistral/mistral-ocr-2505-completion": { "litellm_provider": "mistral", - "ocr_cost_per_page": 1e-3, - "annotation_cost_per_page": 3e-3, + "ocr_cost_per_page": 0.001, + "annotation_cost_per_page": 0.003, "mode": "ocr", "supported_endpoints": [ "/v1/ocr" @@ -20349,14 +20349,14 @@ "mode": "embedding" }, "mistral/codestral-embed": { - "input_cost_per_token": 0.15e-06, + "input_cost_per_token": 1.5e-07, "litellm_provider": "mistral", "max_input_tokens": 8192, "max_tokens": 8192, "mode": "embedding" }, "mistral/codestral-embed-2505": { - "input_cost_per_token": 0.15e-06, + "input_cost_per_token": 1.5e-07, "litellm_provider": "mistral", "max_input_tokens": 8192, "max_tokens": 8192, @@ -20757,28 +20757,28 @@ "supports_vision": true }, "moonshot/kimi-k2-thinking": { - "cache_read_input_token_cost": 1.5e-7, - "input_cost_per_token": 6e-7, + "cache_read_input_token_cost": 1.5e-07, + "input_cost_per_token": 6e-07, "litellm_provider": "moonshot", "max_input_tokens": 262144, "max_output_tokens": 262144, "max_tokens": 262144, "mode": "chat", - "output_cost_per_token": 2.5e-6, + "output_cost_per_token": 2.5e-06, "source": "https://platform.moonshot.ai/docs/pricing/chat#generation-model-kimi-k2", "supports_function_calling": true, "supports_tool_choice": true, "supports_web_search": true }, "moonshot/kimi-k2-thinking-turbo": { - "cache_read_input_token_cost": 1.5e-7, - "input_cost_per_token": 1.15e-6, + "cache_read_input_token_cost": 1.5e-07, + "input_cost_per_token": 1.15e-06, "litellm_provider": "moonshot", "max_input_tokens": 262144, "max_output_tokens": 262144, "max_tokens": 262144, "mode": "chat", - "output_cost_per_token": 8e-6, + "output_cost_per_token": 8e-06, "source": "https://platform.moonshot.ai/docs/pricing/chat#generation-model-kimi-k2", "supports_function_calling": true, "supports_tool_choice": true, @@ -21650,7 +21650,7 @@ "litellm_provider": "oci", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1.068e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", @@ -21662,7 +21662,7 @@ "litellm_provider": "oci", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 2e-06, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", @@ -21674,7 +21674,7 @@ "litellm_provider": "oci", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", @@ -21686,7 +21686,7 @@ "litellm_provider": "oci", "max_input_tokens": 512000, "max_output_tokens": 4000, - "max_tokens": 512000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", @@ -21698,7 +21698,7 @@ "litellm_provider": "oci", "max_input_tokens": 192000, "max_output_tokens": 4000, - "max_tokens": 192000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 7.2e-07, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", @@ -21770,7 +21770,7 @@ "litellm_provider": "oci", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", @@ -21782,7 +21782,7 @@ "litellm_provider": "oci", "max_input_tokens": 256000, "max_output_tokens": 4000, - "max_tokens": 256000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", @@ -21794,7 +21794,7 @@ "litellm_provider": "oci", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1.56e-06, "source": "https://www.oracle.com/cloud/ai/generative-ai/pricing/", @@ -21806,7 +21806,7 @@ "litellm_provider": "ollama", "max_input_tokens": 32768, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": false @@ -21844,7 +21844,7 @@ "litellm_provider": "ollama", "max_input_tokens": 32768, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": true @@ -21864,12 +21864,12 @@ "litellm_provider": "ollama", "max_input_tokens": 32768, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": true }, - "ollama/deepseek-v3.1:671b-cloud" : { + "ollama/deepseek-v3.1:671b-cloud": { "input_cost_per_token": 0.0, "litellm_provider": "ollama", "max_input_tokens": 163840, @@ -21879,7 +21879,7 @@ "output_cost_per_token": 0.0, "supports_function_calling": true }, - "ollama/gpt-oss:120b-cloud" : { + "ollama/gpt-oss:120b-cloud": { "input_cost_per_token": 0.0, "litellm_provider": "ollama", "max_input_tokens": 131072, @@ -21889,7 +21889,7 @@ "output_cost_per_token": 0.0, "supports_function_calling": true }, - "ollama/gpt-oss:20b-cloud" : { + "ollama/gpt-oss:20b-cloud": { "input_cost_per_token": 0.0, "litellm_provider": "ollama", "max_input_tokens": 131072, @@ -21904,7 +21904,7 @@ "litellm_provider": "ollama", "max_input_tokens": 32768, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": true @@ -21968,7 +21968,7 @@ "litellm_provider": "ollama", "max_input_tokens": 8192, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": true @@ -22026,7 +22026,7 @@ "litellm_provider": "ollama", "max_input_tokens": 65536, "max_output_tokens": 8192, - "max_tokens": 65536, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 0.0, "supports_function_calling": true @@ -22084,7 +22084,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -22093,7 +22093,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -22102,7 +22102,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -22156,7 +22156,7 @@ "input_cost_per_token": 1.102e-05, "litellm_provider": "openrouter", "max_output_tokens": 8191, - "max_tokens": 100000, + "max_tokens": 8191, "mode": "chat", "output_cost_per_token": 3.268e-05, "supports_tool_choice": true @@ -22296,7 +22296,7 @@ "input_cost_per_token": 1.63e-06, "litellm_provider": "openrouter", "max_output_tokens": 8191, - "max_tokens": 100000, + "max_tokens": 8191, "mode": "chat", "output_cost_per_token": 5.51e-06, "supports_tool_choice": true @@ -22491,7 +22491,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 8e-07, "supports_assistant_prefill": true, @@ -22506,7 +22506,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 4e-07, "supports_assistant_prefill": true, @@ -22521,7 +22521,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 163840, "max_output_tokens": 163840, - "max_tokens": 8192, + "max_tokens": 163840, "mode": "chat", "output_cost_per_token": 4e-07, "supports_assistant_prefill": true, @@ -22535,7 +22535,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 66000, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2.8e-07, "supports_prompt_caching": true, @@ -22693,51 +22693,51 @@ "supports_web_search": true }, "openrouter/google/gemini-3-flash-preview": { - "cache_read_input_token_cost": 5e-08, - "input_cost_per_audio_token": 1e-06, - "input_cost_per_token": 5e-07, - "litellm_provider": "openrouter", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_pdf_size_mb": 30, - "max_tokens": 65535, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_reasoning_token": 3e-06, - "output_cost_per_token": 3e-06, - "rpm": 2000, - "source": "https://ai.google.dev/pricing/gemini-3", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_vision": true, - "supports_web_search": true, - "tpm": 800000 + "cache_read_input_token_cost": 5e-08, + "input_cost_per_audio_token": 1e-06, + "input_cost_per_token": 5e-07, + "litellm_provider": "openrouter", + "max_audio_length_hours": 8.4, + "max_audio_per_prompt": 1, + "max_images_per_prompt": 3000, + "max_input_tokens": 1048576, + "max_output_tokens": 65535, + "max_pdf_size_mb": 30, + "max_tokens": 65535, + "max_video_length": 1, + "max_videos_per_prompt": 10, + "mode": "chat", + "output_cost_per_reasoning_token": 3e-06, + "output_cost_per_token": 3e-06, + "rpm": 2000, + "source": "https://ai.google.dev/pricing/gemini-3", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_vision": true, + "supports_web_search": true, + "tpm": 800000 }, "openrouter/google/gemini-pro-1.5": { "input_cost_per_image": 0.00265, @@ -22868,13 +22868,13 @@ "supports_tool_choice": true }, "openrouter/minimax/minimax-m2": { - "input_cost_per_token": 2.55e-7, + "input_cost_per_token": 2.55e-07, "litellm_provider": "openrouter", "max_input_tokens": 204800, "max_output_tokens": 204800, - "max_tokens": 32768, + "max_tokens": 204800, "mode": "chat", - "output_cost_per_token": 1.02e-6, + "output_cost_per_token": 1.02e-06, "supports_function_calling": true, "supports_prompt_caching": false, "supports_reasoning": true, @@ -22900,7 +22900,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 262144, "max_output_tokens": 65536, - "max_tokens": 262144, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 6e-07, "supports_function_calling": true, @@ -23285,7 +23285,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.4e-05, "supports_function_calling": true, @@ -23301,7 +23301,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 128000, "max_output_tokens": 16384, - "max_tokens": 128000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.4e-05, "supports_function_calling": true, @@ -23315,9 +23315,9 @@ "litellm_provider": "openrouter", "max_input_tokens": 400000, "max_output_tokens": 128000, - "max_tokens": 400000, + "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.68e-04, + "output_cost_per_token": 0.000168, "supports_function_calling": true, "supports_prompt_caching": false, "supports_reasoning": true, @@ -23474,20 +23474,20 @@ "litellm_provider": "openrouter", "max_input_tokens": 8192, "max_output_tokens": 2048, - "max_tokens": 8192, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 6.3e-07, "supports_tool_choice": true, "supports_vision": true }, "openrouter/qwen/qwen3-coder": { - "input_cost_per_token": 2.2e-7, + "input_cost_per_token": 2.2e-07, "litellm_provider": "openrouter", "max_input_tokens": 262100, "max_output_tokens": 262100, "max_tokens": 262100, "mode": "chat", - "output_cost_per_token": 9.5e-7, + "output_cost_per_token": 9.5e-07, "source": "https://openrouter.ai/qwen/qwen3-coder", "supports_tool_choice": true, "supports_function_calling": true @@ -23530,7 +23530,7 @@ "litellm_provider": "openrouter", "max_input_tokens": 2000000, "max_output_tokens": 30000, - "max_tokens": 2000000, + "max_tokens": 30000, "mode": "chat", "output_cost_per_token": 0, "source": "https://openrouter.ai/x-ai/grok-4-fast:free", @@ -23540,26 +23540,26 @@ "supports_web_search": false }, "openrouter/z-ai/glm-4.6": { - "input_cost_per_token": 4.0e-7, + "input_cost_per_token": 4e-07, "litellm_provider": "openrouter", "max_input_tokens": 202800, "max_output_tokens": 131000, - "max_tokens": 202800, + "max_tokens": 131000, "mode": "chat", - "output_cost_per_token": 1.75e-6, + "output_cost_per_token": 1.75e-06, "source": "https://openrouter.ai/z-ai/glm-4.6", "supports_function_calling": true, "supports_reasoning": true, "supports_tool_choice": true }, "openrouter/z-ai/glm-4.6:exacto": { - "input_cost_per_token": 4.5e-7, + "input_cost_per_token": 4.5e-07, "litellm_provider": "openrouter", "max_input_tokens": 202800, "max_output_tokens": 131000, - "max_tokens": 202800, + "max_tokens": 131000, "mode": "chat", - "output_cost_per_token": 1.9e-6, + "output_cost_per_token": 1.9e-06, "source": "https://openrouter.ai/z-ai/glm-4.6:exacto", "supports_function_calling": true, "supports_reasoning": true, @@ -24107,7 +24107,7 @@ "litellm_provider": "publicai", "max_input_tokens": 8192, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24119,7 +24119,7 @@ "litellm_provider": "publicai", "max_input_tokens": 8192, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24131,7 +24131,7 @@ "litellm_provider": "publicai", "max_input_tokens": 8192, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24143,7 +24143,7 @@ "litellm_provider": "publicai", "max_input_tokens": 16384, "max_output_tokens": 4096, - "max_tokens": 16384, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24155,7 +24155,7 @@ "litellm_provider": "publicai", "max_input_tokens": 8192, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24167,7 +24167,7 @@ "litellm_provider": "publicai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24179,7 +24179,7 @@ "litellm_provider": "publicai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24191,7 +24191,7 @@ "litellm_provider": "publicai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24204,7 +24204,7 @@ "litellm_provider": "publicai", "max_input_tokens": 32768, "max_output_tokens": 4096, - "max_tokens": 32768, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://platform.publicai.co/docs", @@ -24217,7 +24217,7 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 262000, "max_output_tokens": 65536, - "max_tokens": 262144, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.8e-06, "supports_function_calling": true, @@ -24229,7 +24229,7 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 262144, "max_output_tokens": 131072, - "max_tokens": 262144, + "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 8.8e-07, "supports_function_calling": true, @@ -24241,9 +24241,9 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 262144, "max_output_tokens": 131072, - "max_tokens": 262144, + "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 6.0e-07, + "output_cost_per_token": 6e-07, "supports_function_calling": true, "supports_reasoning": true, "supports_tool_choice": true @@ -24253,9 +24253,9 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 131072, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", - "output_cost_per_token": 6.0e-07, + "output_cost_per_token": 6e-07, "supports_function_calling": true, "supports_reasoning": true, "supports_tool_choice": true @@ -24756,12 +24756,11 @@ "supports_reasoning": true, "source": "https://cloud.sambanova.ai/plans/pricing" }, - "snowflake/claude-3-5-sonnet": { "litellm_provider": "snowflake", "max_input_tokens": 18000, "max_output_tokens": 8192, - "max_tokens": 18000, + "max_tokens": 8192, "mode": "chat", "supports_computer_use": true }, @@ -24769,7 +24768,7 @@ "litellm_provider": "snowflake", "max_input_tokens": 32768, "max_output_tokens": 8192, - "max_tokens": 32768, + "max_tokens": 8192, "mode": "chat", "supports_reasoning": true }, @@ -24777,293 +24776,339 @@ "litellm_provider": "snowflake", "max_input_tokens": 8000, "max_output_tokens": 8192, - "max_tokens": 8000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/jamba-1.5-large": { "litellm_provider": "snowflake", "max_input_tokens": 256000, "max_output_tokens": 8192, - "max_tokens": 256000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/jamba-1.5-mini": { "litellm_provider": "snowflake", "max_input_tokens": 256000, "max_output_tokens": 8192, - "max_tokens": 256000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/jamba-instruct": { "litellm_provider": "snowflake", "max_input_tokens": 256000, "max_output_tokens": 8192, - "max_tokens": 256000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama2-70b-chat": { "litellm_provider": "snowflake", "max_input_tokens": 4096, "max_output_tokens": 8192, - "max_tokens": 4096, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3-70b": { "litellm_provider": "snowflake", "max_input_tokens": 8000, "max_output_tokens": 8192, - "max_tokens": 8000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3-8b": { "litellm_provider": "snowflake", "max_input_tokens": 8000, "max_output_tokens": 8192, - "max_tokens": 8000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.1-405b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.1-70b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.1-8b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.2-1b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.2-3b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/llama3.3-70b": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/mistral-7b": { "litellm_provider": "snowflake", "max_input_tokens": 32000, "max_output_tokens": 8192, - "max_tokens": 32000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/mistral-large": { "litellm_provider": "snowflake", "max_input_tokens": 32000, "max_output_tokens": 8192, - "max_tokens": 32000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/mistral-large2": { "litellm_provider": "snowflake", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/mixtral-8x7b": { "litellm_provider": "snowflake", "max_input_tokens": 32000, "max_output_tokens": 8192, - "max_tokens": 32000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/reka-core": { "litellm_provider": "snowflake", "max_input_tokens": 32000, "max_output_tokens": 8192, - "max_tokens": 32000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/reka-flash": { "litellm_provider": "snowflake", "max_input_tokens": 100000, "max_output_tokens": 8192, - "max_tokens": 100000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/snowflake-arctic": { "litellm_provider": "snowflake", "max_input_tokens": 4096, "max_output_tokens": 8192, - "max_tokens": 4096, + "max_tokens": 8192, "mode": "chat" }, "snowflake/snowflake-llama-3.1-405b": { "litellm_provider": "snowflake", "max_input_tokens": 8000, "max_output_tokens": 8192, - "max_tokens": 8000, + "max_tokens": 8192, "mode": "chat" }, "snowflake/snowflake-llama-3.3-70b": { "litellm_provider": "snowflake", "max_input_tokens": 8000, "max_output_tokens": 8192, - "max_tokens": 8000, + "max_tokens": 8192, "mode": "chat" }, "stability/sd3": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.065, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3-large": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.065, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3-large-turbo": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.04, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3-medium": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.035, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3.5-large": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.065, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3.5-large-turbo": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.04, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/sd3.5-medium": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.035, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/stable-image-ultra": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.08, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability/inpaint": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/outpaint": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.004, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/erase": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/search-and-replace": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/search-and-recolor": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/remove-background": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/replace-background-and-relight": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.008, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/sketch": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/structure": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/style": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.005, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/style-transfer": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.008, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/fast": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.002, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/conservative": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.04, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/creative": { "litellm_provider": "stability", "mode": "image_edit", "output_cost_per_image": 0.06, - "supported_endpoints": ["/v1/images/edits"] + "supported_endpoints": [ + "/v1/images/edits" + ] }, "stability/stable-image-core": { "litellm_provider": "stability", "mode": "image_generation", "output_cost_per_image": 0.03, - "supported_endpoints": ["/v1/images/generations"] + "supported_endpoints": [ + "/v1/images/generations" + ] }, "stability.sd3-5-large-v1:0": { "litellm_provider": "bedrock", @@ -25090,13 +25135,13 @@ "litellm_provider": "bedrock", "max_input_tokens": 77, "mode": "image_edit", - "output_cost_per_image": 0.40 + "output_cost_per_image": 0.4 }, "stability.stable-creative-upscale-v1:0": { "litellm_provider": "bedrock", "max_input_tokens": 77, "mode": "image_edit", - "output_cost_per_image": 0.60 + "output_cost_per_image": 0.6 }, "stability.stable-fast-upscale-v1:0": { "litellm_provider": "bedrock", @@ -25204,12 +25249,12 @@ "output_cost_per_pixel": 0.0 }, "linkup/search": { - "input_cost_per_query": 5.87e-03, + "input_cost_per_query": 0.00587, "litellm_provider": "linkup", "mode": "search" }, "linkup/search-deep": { - "input_cost_per_query": 58.67e-03, + "input_cost_per_query": 0.05867, "litellm_provider": "linkup", "mode": "search" }, @@ -25388,7 +25433,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -25397,7 +25442,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -25406,7 +25451,7 @@ "litellm_provider": "openai", "max_input_tokens": 32768, "max_output_tokens": 0, - "max_tokens": 32768, + "max_tokens": 0, "mode": "moderation", "output_cost_per_token": 0.0 }, @@ -25842,7 +25887,7 @@ "supports_tool_choice": true }, "together_ai/zai-org/GLM-4.6": { - "input_cost_per_token": 0.6e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "together_ai", "max_input_tokens": 200000, "max_output_tokens": 200000, @@ -25925,7 +25970,7 @@ "source": "https://aws.amazon.com/polly/pricing/" }, "aws_polly/long-form": { - "input_cost_per_character": 1e-04, + "input_cost_per_character": 0.0001, "litellm_provider": "aws_polly", "mode": "audio_speech", "supported_endpoints": [ @@ -26357,7 +26402,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.6e-05, "supports_function_calling": true, @@ -26368,7 +26413,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 9.9e-07, "supports_function_calling": true, @@ -26379,7 +26424,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 2.2e-07, "supports_function_calling": true, @@ -26390,7 +26435,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 3.5e-07, "supports_function_calling": true, @@ -26402,7 +26447,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1e-07, "supports_function_calling": true, @@ -26413,7 +26458,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-07, "supports_function_calling": true, @@ -26424,7 +26469,7 @@ "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, "supports_function_calling": true, @@ -26489,7 +26534,7 @@ "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, "supports_function_calling": true, @@ -26542,7 +26587,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 40960, "max_output_tokens": 16384, - "max_tokens": 40960, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 2.4e-07 }, @@ -26551,7 +26596,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 40960, "max_output_tokens": 16384, - "max_tokens": 40960, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07 }, @@ -26560,7 +26605,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 40960, "max_output_tokens": 16384, - "max_tokens": 40960, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 3e-07 }, @@ -26569,7 +26614,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 40960, "max_output_tokens": 16384, - "max_tokens": 40960, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 3e-07 }, @@ -26578,7 +26623,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 262144, "max_output_tokens": 66536, - "max_tokens": 262144, + "max_tokens": 66536, "mode": "chat", "output_cost_per_token": 1.6e-06 }, @@ -26587,7 +26632,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 300000, "max_output_tokens": 8192, - "max_tokens": 300000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.4e-07 }, @@ -26596,7 +26641,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.4e-07 }, @@ -26605,7 +26650,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 300000, "max_output_tokens": 8192, - "max_tokens": 300000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 3.2e-06 }, @@ -26625,7 +26670,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 4096, - "max_tokens": 200000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.25e-06 }, @@ -26636,7 +26681,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 4096, - "max_tokens": 200000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 7.5e-05 }, @@ -26647,7 +26692,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 8192, - "max_tokens": 200000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 4e-06 }, @@ -26658,7 +26703,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 8192, - "max_tokens": 200000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -26669,7 +26714,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -26680,7 +26725,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 32000, - "max_tokens": 200000, + "max_tokens": 32000, "mode": "chat", "output_cost_per_token": 7.5e-05 }, @@ -26691,7 +26736,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 64000, - "max_tokens": 200000, + "max_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -26700,7 +26745,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 256000, "max_output_tokens": 8000, - "max_tokens": 256000, + "max_tokens": 8000, "mode": "chat", "output_cost_per_token": 1e-05 }, @@ -26709,7 +26754,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-07 }, @@ -26718,7 +26763,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1e-05 }, @@ -26736,7 +26781,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.19e-06 }, @@ -26754,7 +26799,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 9e-07 }, @@ -26763,7 +26808,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1048576, "max_output_tokens": 8192, - "max_tokens": 1048576, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 6e-07 }, @@ -26772,7 +26817,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1048576, "max_output_tokens": 8192, - "max_tokens": 1048576, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 3e-07 }, @@ -26781,7 +26826,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1000000, "max_output_tokens": 65536, - "max_tokens": 1000000, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 2.5e-06 }, @@ -26790,7 +26835,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1048576, "max_output_tokens": 65536, - "max_tokens": 1048576, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1e-05 }, @@ -26835,7 +26880,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 32000, "max_output_tokens": 16384, - "max_tokens": 32000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-06 }, @@ -26862,7 +26907,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07 }, @@ -26871,7 +26916,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 131000, "max_output_tokens": 131072, - "max_tokens": 131000, + "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 8e-08 }, @@ -26880,7 +26925,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.6e-07 }, @@ -26889,7 +26934,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1e-07 }, @@ -26898,7 +26943,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 1.5e-07 }, @@ -26907,7 +26952,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07 }, @@ -26916,7 +26961,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 8192, - "max_tokens": 128000, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07 }, @@ -26925,7 +26970,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 131072, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 6e-07 }, @@ -26934,7 +26979,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 131072, "max_output_tokens": 8192, - "max_tokens": 131072, + "max_tokens": 8192, "mode": "chat", "output_cost_per_token": 3e-07 }, @@ -26943,7 +26988,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 256000, "max_output_tokens": 4000, - "max_tokens": 256000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 9e-07 }, @@ -26970,7 +27015,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 64000, - "max_tokens": 128000, + "max_tokens": 64000, "mode": "chat", "output_cost_per_token": 5e-06 }, @@ -26979,7 +27024,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 64000, - "max_tokens": 128000, + "max_tokens": 64000, "mode": "chat", "output_cost_per_token": 1.5e-06 }, @@ -26988,7 +27033,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 4e-08 }, @@ -26997,7 +27042,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1e-07 }, @@ -27015,7 +27060,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 32000, "max_output_tokens": 4000, - "max_tokens": 32000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 6e-06 }, @@ -27033,7 +27078,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 32000, "max_output_tokens": 4000, - "max_tokens": 32000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 3e-07 }, @@ -27042,7 +27087,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 65536, "max_output_tokens": 2048, - "max_tokens": 65536, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 1.2e-06 }, @@ -27051,7 +27096,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1.5e-07 }, @@ -27060,7 +27105,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4000, - "max_tokens": 128000, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 6e-06 }, @@ -27069,7 +27114,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 131072, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 2.2e-06 }, @@ -27078,7 +27123,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 32768, "max_output_tokens": 16384, - "max_tokens": 32768, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.2e-06 }, @@ -27087,7 +27132,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 32768, "max_output_tokens": 16384, - "max_tokens": 32768, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.9e-06 }, @@ -27096,7 +27141,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 16385, "max_output_tokens": 4096, - "max_tokens": 16385, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06 }, @@ -27105,7 +27150,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 8192, "max_output_tokens": 4096, - "max_tokens": 8192, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06 }, @@ -27114,7 +27159,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 4096, - "max_tokens": 128000, + "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05 }, @@ -27125,7 +27170,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1047576, "max_output_tokens": 32768, - "max_tokens": 1047576, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-06 }, @@ -27136,7 +27181,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1047576, "max_output_tokens": 32768, - "max_tokens": 1047576, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.6e-06 }, @@ -27147,7 +27192,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 1047576, "max_output_tokens": 32768, - "max_tokens": 1047576, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-07 }, @@ -27158,7 +27203,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 16384, - "max_tokens": 128000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05 }, @@ -27169,7 +27214,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 16384, - "max_tokens": 128000, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07 }, @@ -27180,7 +27225,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 100000, - "max_tokens": 200000, + "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05 }, @@ -27191,7 +27236,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 100000, - "max_tokens": 200000, + "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06 }, @@ -27202,7 +27247,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 100000, - "max_tokens": 200000, + "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06 }, @@ -27213,7 +27258,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 100000, - "max_tokens": 200000, + "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06 }, @@ -27249,7 +27294,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 127000, "max_output_tokens": 8000, - "max_tokens": 127000, + "max_tokens": 8000, "mode": "chat", "output_cost_per_token": 1e-06 }, @@ -27258,7 +27303,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 200000, "max_output_tokens": 8000, - "max_tokens": 200000, + "max_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -27267,7 +27312,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 127000, "max_output_tokens": 8000, - "max_tokens": 127000, + "max_tokens": 8000, "mode": "chat", "output_cost_per_token": 5e-06 }, @@ -27276,7 +27321,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 127000, "max_output_tokens": 8000, - "max_tokens": 127000, + "max_tokens": 8000, "mode": "chat", "output_cost_per_token": 8e-06 }, @@ -27285,7 +27330,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 32000, - "max_tokens": 128000, + "max_tokens": 32000, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -27294,7 +27339,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 32768, - "max_tokens": 128000, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.5e-05 }, @@ -27303,7 +27348,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 131072, "max_output_tokens": 4000, - "max_tokens": 131072, + "max_tokens": 4000, "mode": "chat", "output_cost_per_token": 1e-05 }, @@ -27375,7 +27420,7 @@ "litellm_provider": "vercel_ai_gateway", "max_input_tokens": 128000, "max_output_tokens": 96000, - "max_tokens": 128000, + "max_tokens": 96000, "mode": "chat", "output_cost_per_token": 1.1e-06 }, @@ -27394,7 +27439,7 @@ "supports_tool_choice": true }, "vertex_ai/chirp": { - "input_cost_per_character": 30e-06, + "input_cost_per_character": 3e-05, "litellm_provider": "vertex_ai", "mode": "audio_speech", "source": "https://cloud.google.com/text-to-speech/pricing", @@ -27938,7 +27983,7 @@ "litellm_provider": "vertex_ai-deepseek_models", "max_input_tokens": 163840, "max_output_tokens": 32768, - "max_tokens": 163840, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 5.4e-06, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#partner-models", @@ -27957,7 +28002,7 @@ "litellm_provider": "vertex_ai-deepseek_models", "max_input_tokens": 163840, "max_output_tokens": 32768, - "max_tokens": 163840, + "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.68e-06, "output_cost_per_token_batches": 8.4e-07, @@ -28042,10 +28087,10 @@ "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, - "max_tokens": 65536, + "max_tokens": 32768, "mode": "image_generation", "output_cost_per_image": 0.134, - "output_cost_per_image_token": 1.2e-04, + "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" @@ -28154,7 +28199,7 @@ "litellm_provider": "vertex_ai-llama_models", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 1.6e-05, "source": "https://console.cloud.google.com/vertex-ai/publishers/meta/model-garden/llama-3.2-90b-vision-instruct-maas", @@ -28167,7 +28212,7 @@ "litellm_provider": "vertex_ai-llama_models", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "mode": "chat", "output_cost_per_token": 0.0, "source": "https://console.cloud.google.com/vertex-ai/publishers/meta/model-garden/llama-3.2-90b-vision-instruct-maas", @@ -28180,7 +28225,7 @@ "litellm_provider": "vertex_ai-llama_models", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "metadata": { "notes": "VertexAI states that The Llama 3.1 API service for llama-3.1-70b-instruct-maas and llama-3.1-8b-instruct-maas are in public preview and at no cost." }, @@ -28196,7 +28241,7 @@ "litellm_provider": "vertex_ai-llama_models", "max_input_tokens": 128000, "max_output_tokens": 2048, - "max_tokens": 128000, + "max_tokens": 2048, "metadata": { "notes": "VertexAI states that The Llama 3.2 API service is at no cost during public preview, and will be priced as per dollar-per-1M-tokens at GA." }, @@ -28494,7 +28539,7 @@ "vertex_ai/mistral-ocr-2505": { "litellm_provider": "vertex_ai", "mode": "ocr", - "ocr_cost_per_page": 5e-4, + "ocr_cost_per_page": 0.0005, "supported_endpoints": [ "/v1/ocr" ], @@ -28505,7 +28550,7 @@ "mode": "ocr", "input_cost_per_token": 3e-07, "output_cost_per_token": 1.2e-06, - "ocr_cost_per_page": 3e-04, + "ocr_cost_per_page": 0.0003, "source": "https://cloud.google.com/vertex-ai/pricing" }, "vertex_ai/openai/gpt-oss-120b-maas": { @@ -28993,13 +29038,13 @@ "mode": "chat" }, "watsonx/ibm/granite-3-8b-instruct": { - "input_cost_per_token": 0.2e-06, + "input_cost_per_token": 2e-07, "litellm_provider": "watsonx", "max_input_tokens": 8192, "max_output_tokens": 1024, - "max_tokens": 8192, + "max_tokens": 1024, "mode": "chat", - "output_cost_per_token": 0.2e-06, + "output_cost_per_token": 2e-07, "supports_audio_input": false, "supports_audio_output": false, "supports_function_calling": true, @@ -29015,9 +29060,9 @@ "litellm_provider": "watsonx", "max_input_tokens": 131072, "max_output_tokens": 16384, - "max_tokens": 131072, + "max_tokens": 16384, "mode": "chat", - "output_cost_per_token": 10e-06, + "output_cost_per_token": 1e-05, "supports_audio_input": false, "supports_audio_output": false, "supports_function_calling": true, @@ -29056,8 +29101,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.6e-06, - "output_cost_per_token": 0.6e-06, + "input_cost_per_token": 6e-07, + "output_cost_per_token": 6e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29068,8 +29113,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.6e-06, - "output_cost_per_token": 0.6e-06, + "input_cost_per_token": 6e-07, + "output_cost_per_token": 6e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29080,8 +29125,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.6e-06, - "output_cost_per_token": 0.6e-06, + "input_cost_per_token": 6e-07, + "output_cost_per_token": 6e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29092,8 +29137,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.2e-06, - "output_cost_per_token": 0.2e-06, + "input_cost_per_token": 2e-07, + "output_cost_per_token": 2e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29104,8 +29149,8 @@ "max_tokens": 20480, "max_input_tokens": 20480, "max_output_tokens": 20480, - "input_cost_per_token": 0.06e-06, - "output_cost_per_token": 0.25e-06, + "input_cost_per_token": 6e-08, + "output_cost_per_token": 2.5e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29116,8 +29161,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.1e-06, - "output_cost_per_token": 0.1e-06, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 1e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29128,8 +29173,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.2e-06, - "output_cost_per_token": 0.2e-06, + "input_cost_per_token": 2e-07, + "output_cost_per_token": 2e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29140,8 +29185,8 @@ "max_tokens": 512, "max_input_tokens": 512, "max_output_tokens": 512, - "input_cost_per_token": 0.38e-06, - "output_cost_per_token": 0.38e-06, + "input_cost_per_token": 3.8e-07, + "output_cost_per_token": 3.8e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29152,8 +29197,8 @@ "max_tokens": 512, "max_input_tokens": 512, "max_output_tokens": 512, - "input_cost_per_token": 0.38e-06, - "output_cost_per_token": 0.38e-06, + "input_cost_per_token": 3.8e-07, + "output_cost_per_token": 3.8e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29164,8 +29209,8 @@ "max_tokens": 512, "max_input_tokens": 512, "max_output_tokens": 512, - "input_cost_per_token": 0.38e-06, - "output_cost_per_token": 0.38e-06, + "input_cost_per_token": 3.8e-07, + "output_cost_per_token": 3.8e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29176,8 +29221,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.1e-06, - "output_cost_per_token": 0.1e-06, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 1e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29188,8 +29233,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.35e-06, - "output_cost_per_token": 0.35e-06, + "input_cost_per_token": 3.5e-07, + "output_cost_per_token": 3.5e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29200,8 +29245,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.1e-06, - "output_cost_per_token": 0.1e-06, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 1e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29212,8 +29257,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.15e-06, - "output_cost_per_token": 0.15e-06, + "input_cost_per_token": 1.5e-07, + "output_cost_per_token": 1.5e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29236,8 +29281,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.71e-06, - "output_cost_per_token": 0.71e-06, + "input_cost_per_token": 7.1e-07, + "output_cost_per_token": 7.1e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29248,7 +29293,7 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.35e-06, + "input_cost_per_token": 3.5e-07, "output_cost_per_token": 1.4e-06, "litellm_provider": "watsonx", "mode": "chat", @@ -29260,8 +29305,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.35e-06, - "output_cost_per_token": 0.35e-06, + "input_cost_per_token": 3.5e-07, + "output_cost_per_token": 3.5e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29273,7 +29318,7 @@ "max_input_tokens": 128000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, - "output_cost_per_token": 10e-06, + "output_cost_per_token": 1e-05, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29284,8 +29329,8 @@ "max_tokens": 32000, "max_input_tokens": 32000, "max_output_tokens": 32000, - "input_cost_per_token": 0.1e-06, - "output_cost_per_token": 0.3e-06, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 3e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29296,8 +29341,8 @@ "max_tokens": 32000, "max_input_tokens": 32000, "max_output_tokens": 32000, - "input_cost_per_token": 0.1e-06, - "output_cost_per_token": 0.3e-06, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 3e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": true, @@ -29308,8 +29353,8 @@ "max_tokens": 128000, "max_input_tokens": 128000, "max_output_tokens": 128000, - "input_cost_per_token": 0.35e-06, - "output_cost_per_token": 0.35e-06, + "input_cost_per_token": 3.5e-07, + "output_cost_per_token": 3.5e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29320,8 +29365,8 @@ "max_tokens": 8192, "max_input_tokens": 8192, "max_output_tokens": 8192, - "input_cost_per_token": 0.15e-06, - "output_cost_per_token": 0.6e-06, + "input_cost_per_token": 1.5e-07, + "output_cost_per_token": 6e-07, "litellm_provider": "watsonx", "mode": "chat", "supports_function_calling": false, @@ -29611,15 +29656,15 @@ }, "xai/grok-4-fast-reasoning": { "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, - "output_cost_per_token": 0.5e-06, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, - "cache_read_input_token_cost": 0.05e-06, + "cache_read_input_token_cost": 5e-08, "source": "https://docs.x.ai/docs/models", "supports_function_calling": true, "supports_tool_choice": true, @@ -29627,14 +29672,14 @@ }, "xai/grok-4-fast-non-reasoning": { "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "cache_read_input_token_cost": 0.05e-06, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "cache_read_input_token_cost": 5e-08, + "max_tokens": 2000000.0, "mode": "chat", - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, - "output_cost_per_token": 0.5e-06, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models", "supports_function_calling": true, @@ -29650,7 +29695,7 @@ "max_tokens": 256000, "mode": "chat", "output_cost_per_token": 1.5e-05, - "output_cost_per_token_above_128k_tokens": 30e-06, + "output_cost_per_token_above_128k_tokens": 3e-05, "source": "https://docs.x.ai/docs/models", "supports_function_calling": true, "supports_tool_choice": true, @@ -29665,22 +29710,22 @@ "max_tokens": 256000, "mode": "chat", "output_cost_per_token": 1.5e-05, - "output_cost_per_token_above_128k_tokens": 30e-06, + "output_cost_per_token_above_128k_tokens": 3e-05, "source": "https://docs.x.ai/docs/models", "supports_function_calling": true, "supports_tool_choice": true, "supports_web_search": true }, "xai/grok-4-1-fast": { - "cache_read_input_token_cost": 0.05e-06, - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "output_cost_per_token": 0.5e-06, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models/grok-4-1-fast-reasoning", "supports_audio_input": true, @@ -29692,15 +29737,15 @@ "supports_web_search": true }, "xai/grok-4-1-fast-reasoning": { - "cache_read_input_token_cost": 0.05e-06, - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "output_cost_per_token": 0.5e-06, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models/grok-4-1-fast-reasoning", "supports_audio_input": true, @@ -29712,15 +29757,15 @@ "supports_web_search": true }, "xai/grok-4-1-fast-reasoning-latest": { - "cache_read_input_token_cost": 0.05e-06, - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "output_cost_per_token": 0.5e-06, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models/grok-4-1-fast-reasoning", "supports_audio_input": true, @@ -29732,15 +29777,15 @@ "supports_web_search": true }, "xai/grok-4-1-fast-non-reasoning": { - "cache_read_input_token_cost": 0.05e-06, - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "output_cost_per_token": 0.5e-06, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models/grok-4-1-fast-non-reasoning", "supports_audio_input": true, @@ -29751,15 +29796,15 @@ "supports_web_search": true }, "xai/grok-4-1-fast-non-reasoning-latest": { - "cache_read_input_token_cost": 0.05e-06, - "input_cost_per_token": 0.2e-06, - "input_cost_per_token_above_128k_tokens": 0.4e-06, + "cache_read_input_token_cost": 5e-08, + "input_cost_per_token": 2e-07, + "input_cost_per_token_above_128k_tokens": 4e-07, "litellm_provider": "xai", - "max_input_tokens": 2e6, - "max_output_tokens": 2e6, - "max_tokens": 2e6, + "max_input_tokens": 2000000.0, + "max_output_tokens": 2000000.0, + "max_tokens": 2000000.0, "mode": "chat", - "output_cost_per_token": 0.5e-06, + "output_cost_per_token": 5e-07, "output_cost_per_token_above_128k_tokens": 1e-06, "source": "https://docs.x.ai/docs/models/grok-4-1-fast-non-reasoning", "supports_audio_input": true, @@ -29942,7 +29987,7 @@ "source": "https://docs.z.ai/guides/overview/pricing" }, "vertex_ai/search_api": { - "input_cost_per_query": 1.5e-03, + "input_cost_per_query": 0.0015, "litellm_provider": "vertex_ai", "mode": "vector_store" }, @@ -29954,7 +29999,7 @@ "openai/sora-2": { "litellm_provider": "openai", "mode": "video_generation", - "output_cost_per_video_per_second": 0.10, + "output_cost_per_video_per_second": 0.1, "source": "https://platform.openai.com/docs/api-reference/videos", "supported_modalities": [ "text", @@ -29971,7 +30016,7 @@ "openai/sora-2-pro": { "litellm_provider": "openai", "mode": "video_generation", - "output_cost_per_video_per_second": 0.30, + 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"max_output_tokens": 96000, + "max_tokens": 96000 + }, + "novita/qwen/qwen3-reranker-8b": { + "litellm_provider": "novita", + "mode": "rerank", + "input_cost_per_token": 4e-04, + "output_cost_per_token": 4e-04, + "max_input_tokens": 32768, + "max_output_tokens": 4096, + "max_tokens": 4096 + }, + "novita/baai/bge-reranker-v2-m3": { + "litellm_provider": "novita", + "mode": "rerank", + "input_cost_per_token": 1e-04, + "output_cost_per_token": 1e-04, + "max_input_tokens": 8000, + "max_output_tokens": 8000, + "max_tokens": 8000 + }, "llamagate/llama-3.1-8b": { "max_tokens": 8192, "max_input_tokens": 131072, @@ -32367,4 +33506,3 @@ "mode": "embedding" } } - From d98c71f07e808040d494002e9e4f9b5db8ce765c Mon Sep 17 00:00:00 2001 From: yogeshwaran10 Date: Sun, 11 Jan 2026 00:45:42 +0530 Subject: [PATCH 030/114] Fixes #18896 : Handle missing completion_tokens_details when reasoning_effort is not used --- .../vertex_and_google_ai_studio_gemini.py | 144 +++++++++++------- .../gemini/test_gemini_token_usage.py | 70 +++++++++ 2 files changed, 155 insertions(+), 59 deletions(-) create mode 100644 tests/test_litellm/llms/vertex_ai/gemini/test_gemini_token_usage.py diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py index 91100cf7d7b..e19bdc9edbd 100644 --- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py @@ -310,9 +310,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): """ return Tools(googleSearch={}) - def _transform_computer_use_config( - self, computer_use_config: dict - ) -> dict: + def _transform_computer_use_config(self, computer_use_config: dict) -> dict: """ Transform Computer Use configuration to Gemini API format. @@ -323,7 +321,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): Transformed computer use configuration for Gemini API """ transformed_config = {} - + # Transform environment values if needed if "environment" in computer_use_config: env_value = computer_use_config["environment"] @@ -339,13 +337,17 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): f"Invalid environment value for computer_use: {env_value}. " f"Supported: 'browser', 'unspecified', 'ENVIRONMENT_BROWSER', 'ENVIRONMENT_UNSPECIFIED'" ) - + # Transform excluded_predefined_functions to camelCase if "excluded_predefined_functions" in computer_use_config: - transformed_config["excludedPredefinedFunctions"] = computer_use_config["excluded_predefined_functions"] + transformed_config["excludedPredefinedFunctions"] = computer_use_config[ + "excluded_predefined_functions" + ] elif "excludedPredefinedFunctions" in computer_use_config: - transformed_config["excludedPredefinedFunctions"] = computer_use_config["excludedPredefinedFunctions"] - + transformed_config["excludedPredefinedFunctions"] = computer_use_config[ + "excludedPredefinedFunctions" + ] + return transformed_config def _extract_google_maps_retrieval_config( @@ -446,9 +448,9 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): value = _remove_strict_from_schema(value) for tool in value: - openai_function_object: Optional[ - ChatCompletionToolParamFunctionChunk - ] = None + openai_function_object: Optional[ChatCompletionToolParamFunctionChunk] = ( + None + ) if "function" in tool: # tools list _openai_function_object = ChatCompletionToolParamFunctionChunk( # type: ignore **tool["function"] @@ -553,7 +555,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): "Invalid tool={}. Use `litellm.set_verbose` or `litellm --detailed_debug` to see raw request." ) -# Build list of Tool objects - each Tool should contain exactly one type + # Build list of Tool objects - each Tool should contain exactly one type # per Vertex AI API spec: "A Tool object should contain exactly one type of Tool" _tools_list: List[Tools] = [] @@ -570,11 +572,15 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): _tools_list.append(search_tool) if googleSearchRetrieval is not None: retrieval_tool = Tools() - retrieval_tool[VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value] = googleSearchRetrieval + retrieval_tool[VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value] = ( + googleSearchRetrieval + ) _tools_list.append(retrieval_tool) if enterpriseWebSearch is not None: enterprise_tool = Tools() - enterprise_tool[VertexToolName.ENTERPRISE_WEB_SEARCH.value] = enterpriseWebSearch + enterprise_tool[VertexToolName.ENTERPRISE_WEB_SEARCH.value] = ( + enterpriseWebSearch + ) _tools_list.append(enterprise_tool) if code_execution is not None: code_tool = Tools() @@ -593,7 +599,6 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): computer_tool[VertexToolName.COMPUTER_USE.value] = computerUse _tools_list.append(computer_tool) - # Add retrieval config to toolConfig if googleMaps has location data if google_maps_retrieval_config is not None: if "toolConfig" not in optional_params: @@ -710,8 +715,9 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): GeminiThinkingConfig with thinkingLevel and includeThoughts """ # Check if this is gemini-3-flash which supports MINIMAL thinking level - is_gemini3flash= model and ( - "gemini-3-flash-preview" in model.lower() or "gemini-3-flash" in model.lower() + is_gemini3flash = model and ( + "gemini-3-flash-preview" in model.lower() + or "gemini-3-flash" in model.lower() ) if reasoning_effort == "minimal": if is_gemini3flash: @@ -799,7 +805,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): thinking_budget = thinking_param.get("budget_tokens") params: GeminiThinkingConfig = {} - + # For Gemini 3+ models, use thinkingLevel instead of thinkingBudget if model and VertexGeminiConfig._is_gemini_3_or_newer(model): if thinking_enabled: @@ -808,11 +814,21 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): else: params["includeThoughts"] = True if thinking_budget >= 10000: - is_gemini3flash = "gemini-3-flash-preview" in model.lower() or "gemini-3-flash" in model.lower() - params["thinkingLevel"] = "minimal" if is_gemini3flash else "low" + is_gemini3flash = ( + "gemini-3-flash-preview" in model.lower() + or "gemini-3-flash" in model.lower() + ) + params["thinkingLevel"] = ( + "minimal" if is_gemini3flash else "low" + ) else: - is_gemini3flash = "gemini-3-flash-preview" in model.lower() or "gemini-3-flash" in model.lower() - params["thinkingLevel"] = "minimal" if is_gemini3flash else "low" + is_gemini3flash = ( + "gemini-3-flash-preview" in model.lower() + or "gemini-3-flash" in model.lower() + ) + params["thinkingLevel"] = ( + "minimal" if is_gemini3flash else "low" + ) else: # Thinking disabled params["includeThoughts"] = False @@ -824,7 +840,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): params["includeThoughts"] = True if thinking_budget is not None and isinstance(thinking_budget, int): params["thinkingBudget"] = thinking_budget - + return params def map_response_modalities(self, value: list) -> list: @@ -980,16 +996,16 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): param_description="thinking_budget", ) if VertexGeminiConfig._is_gemini_3_or_newer(model): - optional_params[ - "thinkingConfig" - ] = VertexGeminiConfig._map_reasoning_effort_to_thinking_level( - value, model + optional_params["thinkingConfig"] = ( + VertexGeminiConfig._map_reasoning_effort_to_thinking_level( + value, model + ) ) else: - optional_params[ - "thinkingConfig" - ] = VertexGeminiConfig._map_reasoning_effort_to_thinking_budget( - value, model + optional_params["thinkingConfig"] = ( + VertexGeminiConfig._map_reasoning_effort_to_thinking_budget( + value, model + ) ) elif param == "thinking": # Validate no conflict with thinking_level @@ -998,11 +1014,11 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): param_name="thinking", param_description="thinking_budget", ) - optional_params[ - "thinkingConfig" - ] = VertexGeminiConfig._map_thinking_param( - cast(AnthropicThinkingParam, value), - model=model, + optional_params["thinkingConfig"] = ( + VertexGeminiConfig._map_thinking_param( + cast(AnthropicThinkingParam, value), + model=model, + ) ) elif param == "modalities" and isinstance(value, list): response_modalities = self.map_response_modalities(value) @@ -1036,8 +1052,13 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): ): # For gemini-3-flash-preview, default to "minimal" to match Gemini 2.5 Flash behavior # For other Gemini 3 models, default to "low" - is_gemini3flash = "gemini-3-flash-preview" in model.lower() or "gemini-3-flash" in model.lower() - thinking_config["thinkingLevel"] = "minimal" if is_gemini3flash else "low" + is_gemini3flash = ( + "gemini-3-flash-preview" in model.lower() + or "gemini-3-flash" in model.lower() + ) + thinking_config["thinkingLevel"] = ( + "minimal" if is_gemini3flash else "low" + ) optional_params["thinkingConfig"] = thinking_config return optional_params @@ -1226,7 +1247,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): block: ChatCompletionThinkingBlock = { "type": "thinking", "thinking": thinking_text, - } + } signature = part.get("thoughtSignature") if signature is not None: block["signature"] = signature @@ -1360,10 +1381,10 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): _tool_response_chunk["provider_specific_fields"] = { # type: ignore "thought_signature": thought_signature } - _tool_response_chunk[ - "id" - ] = _encode_tool_call_id_with_signature( - _tool_response_chunk["id"] or "", thought_signature + _tool_response_chunk["id"] = ( + _encode_tool_call_id_with_signature( + _tool_response_chunk["id"] or "", thought_signature + ) ) _tools.append(_tool_response_chunk) cumulative_tool_call_idx += 1 @@ -1551,13 +1572,18 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): elif modality == "IMAGE": response_tokens_details.image_tokens = token_count - # Calculate text_tokens if not explicitly provided in candidatesTokensDetails - # candidatesTokenCount includes all modalities, so: text = total - (image + audio) + # Calculate text_tokens if not explicitly provided in candidatesTokensDetails + # candidatesTokenCount includes all modalities, so: text = total - (image + audio) + candidates_token_count = usage_metadata.get("candidatesTokenCount", 0) + if candidates_token_count > 0: + if response_tokens_details is None: + response_tokens_details = CompletionTokensDetailsWrapper() if response_tokens_details.text_tokens is None: - candidates_token_count = usage_metadata.get("candidatesTokenCount", 0) image_tokens = response_tokens_details.image_tokens or 0 audio_tokens_candidate = response_tokens_details.audio_tokens or 0 - calculated_text_tokens = candidates_token_count - image_tokens - audio_tokens_candidate + calculated_text_tokens = ( + candidates_token_count - image_tokens - audio_tokens_candidate + ) response_tokens_details.text_tokens = calculated_text_tokens ######################################################### @@ -2076,28 +2102,28 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): ## ADD METADATA TO RESPONSE ## setattr(model_response, "vertex_ai_grounding_metadata", grounding_metadata) - model_response._hidden_params[ - "vertex_ai_grounding_metadata" - ] = grounding_metadata + model_response._hidden_params["vertex_ai_grounding_metadata"] = ( + grounding_metadata + ) setattr( model_response, "vertex_ai_url_context_metadata", url_context_metadata ) - model_response._hidden_params[ - "vertex_ai_url_context_metadata" - ] = url_context_metadata + model_response._hidden_params["vertex_ai_url_context_metadata"] = ( + url_context_metadata + ) setattr(model_response, "vertex_ai_safety_results", safety_ratings) - model_response._hidden_params[ - "vertex_ai_safety_results" - ] = safety_ratings # older approach - maintaining to prevent regressions + model_response._hidden_params["vertex_ai_safety_results"] = ( + safety_ratings # older approach - maintaining to prevent regressions + ) ## ADD CITATION METADATA ## setattr(model_response, "vertex_ai_citation_metadata", citation_metadata) - model_response._hidden_params[ - "vertex_ai_citation_metadata" - ] = citation_metadata # older approach - maintaining to prevent regressions + model_response._hidden_params["vertex_ai_citation_metadata"] = ( + citation_metadata # older approach - maintaining to prevent regressions + ) except Exception as e: raise VertexAIError( diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_gemini_token_usage.py b/tests/test_litellm/llms/vertex_ai/gemini/test_gemini_token_usage.py new file mode 100644 index 00000000000..c8894ca7d5c --- /dev/null +++ b/tests/test_litellm/llms/vertex_ai/gemini/test_gemini_token_usage.py @@ -0,0 +1,70 @@ + +import sys, os +import pytest +sys.path.insert(0, os.path.abspath('../../../../../')) + +from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexGeminiConfig +from litellm.types.llms.vertex_ai import UsageMetadata + +def test_gemini_3_flash_preview_token_usage_fallback(): + """Test fallback logic when candidatesTokensDetails is missing (e.g. Gemini 3 Flash Preview).""" + v = VertexGeminiConfig() + + usage_metadata_dict = { + "promptTokenCount": 2145, + "candidatesTokenCount": 509, + "totalTokenCount": 2654, + # candidatesTokensDetails intentionally omitted + } + + completion_response = {"usageMetadata": usage_metadata_dict} + result = v._calculate_usage(completion_response=completion_response) + + assert result.completion_tokens == 509 + assert result.prompt_tokens == 2145 + assert result.total_tokens == 2654 + + # Text tokens should be derived from candidatesTokenCount + assert result.completion_tokens_details is not None + assert result.completion_tokens_details.text_tokens == 509 + assert result.completion_tokens_details.image_tokens is None + assert result.completion_tokens_details.audio_tokens is None + +def test_gemini_no_reasoning_fallback(): + """Test fallback when reasoning_effort is absent and details are missing.""" + v = VertexGeminiConfig() + + usage_metadata_dict = { + "promptTokenCount": 100, + "candidatesTokenCount": 264, + "totalTokenCount": 364, + } + + completion_response = {"usageMetadata": usage_metadata_dict} + result = v._calculate_usage(completion_response=completion_response) + + assert result.completion_tokens == 264 + assert result.completion_tokens_details is not None + assert result.completion_tokens_details.text_tokens == 264 + assert result.completion_tokens_details.reasoning_tokens is None or result.completion_tokens_details.reasoning_tokens == 0 + +def test_gemini_token_usage_standard_response(): + """Verify that standard responses with details are computed correctly and not overwritten.""" + v = VertexGeminiConfig() + + usage_metadata_dict = { + "promptTokenCount": 100, + "candidatesTokenCount": 50, + "totalTokenCount": 150, + "candidatesTokensDetails": [ + {"modality": "TEXT", "tokenCount": 40}, + {"modality": "IMAGE", "tokenCount": 10} + ] + } + + completion_response = {"usageMetadata": usage_metadata_dict} + result = v._calculate_usage(completion_response=completion_response) + + assert result.completion_tokens == 50 + assert result.completion_tokens_details.text_tokens == 40 + assert result.completion_tokens_details.image_tokens == 10 From 29254d9071979b7fb8a23191461f4ee793c1c0f6 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 11:28:04 -0800 Subject: [PATCH 031/114] _get_bedrock_client_ssl_verify --- litellm/llms/bedrock/common_utils.py | 54 +++++++++++++++++----------- 1 file changed, 33 insertions(+), 21 deletions(-) diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index d8e0a05dc01..f4b5de8f7c0 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -132,6 +132,38 @@ def add_custom_header(headers): return callback +def _get_bedrock_client_ssl_verify() -> Union[bool, str]: + """ + Get SSL verification setting for Bedrock client. + + Returns the SSL verification setting which can be: + - True: Use default SSL verification + - False: Disable SSL verification + - str: Path to a custom CA bundle file + """ + from litellm.secret_managers.main import str_to_bool + + ssl_verify: Union[bool, str, None] = os.getenv("SSL_VERIFY", litellm.ssl_verify) + + # Convert string "False"/"True" to boolean + if isinstance(ssl_verify, str): + # Check if it's a file path + if os.path.exists(ssl_verify): + return ssl_verify # Keep the file path + # Otherwise try to convert to boolean + ssl_verify_bool = str_to_bool(ssl_verify) + if ssl_verify_bool is not None: + ssl_verify = ssl_verify_bool + + # Check SSL_CERT_FILE environment variable for custom CA bundle + if ssl_verify is True or ssl_verify == "True": + ssl_cert_file = os.getenv("SSL_CERT_FILE") + if ssl_cert_file and os.path.exists(ssl_cert_file): + return ssl_cert_file + + return ssl_verify if ssl_verify is not None else True + + def init_bedrock_client( region_name=None, aws_access_key_id: Optional[str] = None, @@ -177,27 +209,7 @@ def init_bedrock_client( aws_web_identity_token, ) = params_to_check - # SSL certificates (a.k.a CA bundle) used to verify the identity of requested hosts. - # Use the same logic as BaseAWSLLM._get_ssl_verify() for consistency - from litellm.secret_managers.main import str_to_bool - ssl_verify = os.getenv("SSL_VERIFY", litellm.ssl_verify) - - # Convert string "False"/"True" to boolean - if isinstance(ssl_verify, str): - # Check if it's a file path - if os.path.exists(ssl_verify): - pass # Keep the file path - else: - # Otherwise try to convert to boolean - ssl_verify_bool = str_to_bool(ssl_verify) - if ssl_verify_bool is not None: - ssl_verify = ssl_verify_bool - - # Check SSL_CERT_FILE environment variable for custom CA bundle - if ssl_verify is True or ssl_verify == "True": - ssl_cert_file = os.getenv("SSL_CERT_FILE") - if ssl_cert_file and os.path.exists(ssl_cert_file): - ssl_verify = ssl_cert_file + ssl_verify = _get_bedrock_client_ssl_verify() ### SET REGION NAME if region_name: From ab50fea6636cc6a4c125ab2721e71f3c68919228 Mon Sep 17 00:00:00 2001 From: Ishaan Jaff Date: Sat, 10 Jan 2026 23:28:21 +0400 Subject: [PATCH 032/114] [Fix] turn_off_message_logging Does Not Redact Request Messages in proxy_server_request Field When Stored to Database (#18897) * update _get_proxy_server_request_for_spend_logs_payload * test_spend_logs_redacts_request_and_response_when_turn_off_message_logging_enabled --- .../spend_tracking/spend_tracking_utils.py | 52 +++++++++++++++- .../test_spend_tracking_utils.py | 61 +++++++++++++++++++ 2 files changed, 111 insertions(+), 2 deletions(-) diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 1c457d7bf4c..5d348d35cb2 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -1,3 +1,4 @@ +import copy import hashlib import json import secrets @@ -433,9 +434,11 @@ def get_logging_payload( # noqa: PLR0915 messages=_get_messages_for_spend_logs_payload( standard_logging_payload=standard_logging_payload, metadata=metadata ), - response=_get_response_for_spend_logs_payload(standard_logging_payload), + response=_get_response_for_spend_logs_payload( + payload=standard_logging_payload, kwargs=kwargs + ), proxy_server_request=_get_proxy_server_request_for_spend_logs_payload( - metadata=metadata, litellm_params=litellm_params + metadata=metadata, litellm_params=litellm_params, kwargs=kwargs ), session_id=_get_session_id_for_spend_log( kwargs=kwargs, @@ -642,9 +645,12 @@ def _sanitize_request_body_for_spend_logs_payload( def _get_proxy_server_request_for_spend_logs_payload( metadata: dict, litellm_params: dict, + kwargs: Optional[dict] = None, ) -> str: """ Only store if _should_store_prompts_and_responses_in_spend_logs() is True + + If turn_off_message_logging is enabled, redact messages in the request body. """ if _should_store_prompts_and_responses_in_spend_logs(): _proxy_server_request = cast( @@ -652,6 +658,27 @@ def _get_proxy_server_request_for_spend_logs_payload( ) if _proxy_server_request is not None: _request_body = _proxy_server_request.get("body", {}) or {} + + # Apply message redaction if turn_off_message_logging is enabled + if kwargs is not None: + from litellm.litellm_core_utils.redact_messages import ( + perform_redaction, + should_redact_message_logging, + ) + + # Build model_call_details dict to check redaction settings + model_call_details = { + "litellm_params": litellm_params, + "standard_callback_dynamic_params": kwargs.get( + "standard_callback_dynamic_params" + ), + } + + # If redaction is enabled, deep copy request body before redacting + if should_redact_message_logging(model_call_details=model_call_details): + _request_body = copy.deepcopy(_request_body) + perform_redaction(model_call_details=_request_body, result=None) + _request_body = _sanitize_request_body_for_spend_logs_payload(_request_body) _request_body_json_str = json.dumps(_request_body, default=str) return _request_body_json_str @@ -685,6 +712,7 @@ def _get_vector_store_request_for_spend_logs_payload( def _get_response_for_spend_logs_payload( payload: Optional[StandardLoggingPayload], + kwargs: Optional[dict] = None, ) -> str: if payload is None: return "{}" @@ -692,6 +720,26 @@ def _get_response_for_spend_logs_payload( response_obj: Any = payload.get("response") if response_obj is None: return "{}" + + # Apply message redaction if turn_off_message_logging is enabled + if kwargs is not None: + from litellm.litellm_core_utils.redact_messages import ( + perform_redaction, + should_redact_message_logging, + ) + + litellm_params = kwargs.get("litellm_params", {}) + model_call_details = { + "litellm_params": litellm_params, + "standard_callback_dynamic_params": kwargs.get( + "standard_callback_dynamic_params" + ), + } + + # If redaction is enabled, deep copy response before redacting + if should_redact_message_logging(model_call_details=model_call_details): + response_obj = copy.deepcopy(response_obj) + response_obj = perform_redaction(model_call_details={}, result=response_obj) sanitized_wrapper = _sanitize_request_body_for_spend_logs_payload( {"response": response_obj} diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py index 69b7e504184..dd4cbfa2e7f 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py @@ -19,6 +19,7 @@ import litellm from litellm.constants import LITELLM_TRUNCATED_PAYLOAD_FIELD, REDACTED_BY_LITELM_STRING from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.proxy.spend_tracking.spend_tracking_utils import ( + _get_proxy_server_request_for_spend_logs_payload, _get_response_for_spend_logs_payload, _get_vector_store_request_for_spend_logs_payload, _sanitize_request_body_for_spend_logs_payload, @@ -850,3 +851,63 @@ def test_get_logging_payload_handles_missing_overhead_gracefully(): metadata.get("litellm_overhead_time_ms") is None ), "litellm_overhead_time_ms should be None when overhead is not provided" + +@patch( + "litellm.proxy.spend_tracking.spend_tracking_utils._should_store_prompts_and_responses_in_spend_logs" +) +def test_spend_logs_redacts_request_and_response_when_turn_off_message_logging_enabled( + mock_should_store, +): + """ + Test that both request body and response are redacted when turn_off_message_logging is enabled. + """ + mock_should_store.return_value = True + + # Test request redaction + litellm_params = { + "proxy_server_request": { + "body": { + "messages": [{"role": "user", "content": "secret message"}], + "model": "gpt-4", + } + } + } + metadata = {} + kwargs = { + "litellm_params": litellm_params, + "standard_callback_dynamic_params": { + "turn_off_message_logging": True, + }, + } + + request_result = _get_proxy_server_request_for_spend_logs_payload( + metadata=metadata, litellm_params=litellm_params, kwargs=kwargs + ) + + parsed_request = json.loads(request_result) + assert parsed_request["messages"] == [{"role": "user", "content": "redacted-by-litellm"}] + assert parsed_request["model"] == "gpt-4" + + # Test response redaction - use dict response to verify redaction + response_dict = { + "id": "test-id", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "secret response"}, + } + ], + "model": "gpt-4", + } + payload = cast( + StandardLoggingPayload, + {"response": response_dict}, + ) + + response_result = _get_response_for_spend_logs_payload(payload=payload, kwargs=kwargs) + + # When redaction is enabled and response is a dict (not ModelResponse), + # perform_redaction returns {"text": "redacted-by-litellm"} + parsed_response = json.loads(response_result) + assert parsed_response == {"text": "redacted-by-litellm"} + From 0bc04ce129ed86781f332b4429a16eaa95a2327c Mon Sep 17 00:00:00 2001 From: Chesars Date: Sat, 10 Jan 2026 19:39:04 +0000 Subject: [PATCH 033/114] fix: correct pricing for openrouter/openai/gpt-oss-20b MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Updated pricing from incorrect values to match OpenRouter's official rates: - Input: $0.18/M → $0.02/M tokens (1.8e-07 → 2e-08) - Output: $0.80/M → $0.10/M tokens (8e-07 → 1e-07) --- litellm/model_prices_and_context_window_backup.json | 4 ++-- model_prices_and_context_window.json | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 73579db75cd..89824ba13d4 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -23340,13 +23340,13 @@ "supports_tool_choice": true }, "openrouter/openai/gpt-oss-20b": { - "input_cost_per_token": 1.8e-07, + "input_cost_per_token": 2e-08, "litellm_provider": "openrouter", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", - "output_cost_per_token": 8e-07, + "output_cost_per_token": 1e-07, "source": "https://openrouter.ai/openai/gpt-oss-20b", "supports_function_calling": true, "supports_parallel_function_calling": true, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 73579db75cd..89824ba13d4 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -23340,13 +23340,13 @@ "supports_tool_choice": true }, "openrouter/openai/gpt-oss-20b": { - "input_cost_per_token": 1.8e-07, + "input_cost_per_token": 2e-08, "litellm_provider": "openrouter", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", - "output_cost_per_token": 8e-07, + "output_cost_per_token": 1e-07, "source": "https://openrouter.ai/openai/gpt-oss-20b", "supports_function_calling": true, "supports_parallel_function_calling": true, From 062f5892da706d3bd8e0b626e733064528b6dda7 Mon Sep 17 00:00:00 2001 From: Elkhan Eminov Date: Sat, 10 Jan 2026 19:42:02 +0000 Subject: [PATCH 034/114] update OpenRouter docs to include embedding support (#18874) --- docs/my-website/docs/providers/openrouter.md | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/docs/my-website/docs/providers/openrouter.md b/docs/my-website/docs/providers/openrouter.md index 327634909b3..a1ed6c4466e 100644 --- a/docs/my-website/docs/providers/openrouter.md +++ b/docs/my-website/docs/providers/openrouter.md @@ -1,5 +1,5 @@ # OpenRouter -LiteLLM supports all the text / chat / vision models from [OpenRouter](https://openrouter.ai/docs) +LiteLLM supports all the text / chat / vision / embedding models from [OpenRouter](https://openrouter.ai/docs) Open In Colab @@ -78,3 +78,18 @@ response = completion( route= "" ) ``` + +## Embedding + +```python +from litellm import embedding +import os + +os.environ["OPENROUTER_API_KEY"] = "your-api-key" + +response = embedding( + model="openrouter/openai/text-embedding-3-small", + input=["good morning from litellm", "this is another item"], +) +print(response) +``` From 369b1fae691f1d564faf0afee9ddcb781c91ba46 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 12:00:03 -0800 Subject: [PATCH 035/114] =?UTF-8?q?bump:=20version=200.4.20=20=E2=86=92=20?= =?UTF-8?q?0.4.21?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- litellm-proxy-extras/pyproject.toml | 4 ++-- pyproject.toml | 2 +- requirements.txt | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index 7eccab254e3..2952aa6c979 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-proxy-extras" -version = "0.4.20" +version = "0.4.21" description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package." authors = ["BerriAI"] readme = "README.md" @@ -22,7 +22,7 @@ requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "0.4.20" +version = "0.4.21" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-proxy-extras==", diff --git a/pyproject.toml b/pyproject.toml index 03a73f38e2d..00e7bff78b6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -59,7 +59,7 @@ websockets = {version = "^15.0.1", optional = true} boto3 = {version = "1.36.0", optional = true} redisvl = {version = "^0.4.1", optional = true, markers = "python_version >= '3.9' and python_version < '3.14'"} mcp = {version = "^1.21.2", optional = true, python = ">=3.10"} -litellm-proxy-extras = {version = "0.4.20", optional = true} +litellm-proxy-extras = {version = "0.4.21", optional = true} rich = {version = "13.7.1", optional = true} litellm-enterprise = {version = "0.1.27", optional = true} diskcache = {version = "^5.6.1", optional = true} diff --git a/requirements.txt b/requirements.txt index ceafa23a22f..5f00a269a7c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -47,7 +47,7 @@ sentry_sdk==2.21.0 # for sentry error handling detect-secrets==1.5.0 # Enterprise - secret detection / masking in LLM requests cryptography==44.0.1 tzdata==2025.1 # IANA time zone database -litellm-proxy-extras==0.4.20 # for proxy extras - e.g. prisma migrations +litellm-proxy-extras==0.4.21 # for proxy extras - e.g. prisma migrations llm-sandbox==0.3.31 # for skill execution in sandbox ### LITELLM PACKAGE DEPENDENCIES python-dotenv==1.0.1 # for env From 0d2010813d815d57fc567639b99040ffeb1cb62b Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 12:00:45 -0800 Subject: [PATCH 036/114] Adding proxy extras build --- ...litellm_proxy_extras-0.4.21-py3-none-any.whl | Bin 0 -> 47136 bytes .../dist/litellm_proxy_extras-0.4.21.tar.gz | Bin 0 -> 21364 bytes 2 files changed, 0 insertions(+), 0 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From: Ishaan Jaff Date: Sun, 11 Jan 2026 00:21:45 +0400 Subject: [PATCH 037/114] add MANUS get response (#18900) --- .../llms/manus/responses/transformation.py | 7 +- .../test_manus_responses_api.py | 113 ++++-------------- 2 files changed, 30 insertions(+), 90 deletions(-) diff --git a/litellm/llms/manus/responses/transformation.py b/litellm/llms/manus/responses/transformation.py index 7a72f23dd56..8e0a4a5a30f 100644 --- a/litellm/llms/manus/responses/transformation.py +++ b/litellm/llms/manus/responses/transformation.py @@ -94,9 +94,11 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): ) # Manus uses API_KEY header, not Authorization: Bearer + # Content-Type is required for all requests (including GET) headers.update( { "API_KEY": api_key, + "Content-Type": "application/json", } ) return headers @@ -164,8 +166,9 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): if extra_body: base_request.update(extra_body) - # Avoid logging potentially sensitive agent_profile value - verbose_logger.debug("Manus: Using task_mode=agent") + verbose_logger.debug( + f"Manus: Using agent_profile={agent_profile}, task_mode=agent" + ) return base_request diff --git a/tests/llm_responses_api_testing/test_manus_responses_api.py b/tests/llm_responses_api_testing/test_manus_responses_api.py index 338a956bfec..4f64980d261 100644 --- a/tests/llm_responses_api_testing/test_manus_responses_api.py +++ b/tests/llm_responses_api_testing/test_manus_responses_api.py @@ -20,96 +20,33 @@ from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from base_responses_api import BaseResponsesAPITest -# class TestManusResponsesAPITest(BaseResponsesAPITest): -# def get_base_completion_call_args(self): -# return { -# "model": "manus/manus-1.6", -# "api_key": os.getenv("MANUS_API_KEY"), -# } - -# @pytest.mark.parametrize("sync_mode", [True, False]) -# @pytest.mark.asyncio -# async def test_basic_openai_responses_delete_endpoint(self, sync_mode): -# pytest.skip("DELETE responses is not supported for Manus") - -# @pytest.mark.parametrize("sync_mode", [True, False]) -# @pytest.mark.asyncio -# async def test_basic_openai_responses_streaming_delete_endpoint(self, sync_mode): -# pytest.skip("DELETE responses is not supported for Manus") - -# # GET responses is now supported for Manus -# @pytest.mark.parametrize("sync_mode", [True, False]) -# @pytest.mark.asyncio -# async def test_basic_openai_responses_get_endpoint(self, sync_mode): -# pytest.skip("GET responses is not supported for Manus") - -# @pytest.mark.parametrize("sync_mode", [True, False]) -# @pytest.mark.asyncio -# async def test_basic_openai_responses_cancel_endpoint(self, sync_mode): -# pytest.skip("CANCEL responses is not supported for Manus") - -# @pytest.mark.parametrize("sync_mode", [True, False]) -# @pytest.mark.asyncio -# async def test_cancel_responses_invalid_response_id(self, sync_mode): -# pytest.skip("CANCEL responses is not supported for Manus") - -# @pytest.mark.asyncio -# async def test_multiturn_responses_api(self): -# pytest.skip("Multiturn responses is not supported for Manus") - - -# @pytest.mark.asyncio -# async def test_manus_responses_api_with_agent_profile(): -# """ -# Test that Manus API correctly extracts agent profile from model name -# and includes task_mode and agent_profile in the request. -# """ -# litellm._turn_on_debug() +@pytest.mark.asyncio +async def test_manus_responses_api_with_agent_profile(): + """ + Test that Manus API correctly extracts agent profile from model name + and includes task_mode and agent_profile in the request. + """ + litellm._turn_on_debug() -# response = await litellm.aresponses( -# model="manus/manus-1.6", -# input="What's the color of the sky?", -# api_key=os.getenv("MANUS_API_KEY"), -# max_output_tokens=50, -# ) + response = await litellm.aresponses( + model="manus/manus-1.6-lite", + input="What's the color of the sky?", + api_key=os.getenv("MANUS_API_KEY"), + max_output_tokens=50, + ) -# print("Manus response=", json.dumps(response, indent=4, default=str)) + print("Manus response=", json.dumps(response, indent=4, default=str)) + + ## Get the status of the response + got_response = await litellm.aget_responses(response_id=response.id) + print("GET API MANUS RESPONSE=", json.dumps(got_response, indent=4, default=str)) + if got_response.status == "completed": + assert got_response.output is not None + assert len(got_response.output) > 0 + else: + # Manus can return "running" or "pending" status + assert got_response.status in ["running", "pending"] + assert got_response.id is not None -# # Validate response structure -# assert isinstance(response, ResponsesAPIResponse), "Response should be ResponsesAPIResponse" -# assert response.id is not None, "Response should have an ID" -# assert response.status in ["running", "completed", "pending"], f"Status should be valid, got {response.status}" - -# # Check that metadata includes Manus-specific fields -# if response.metadata: -# assert "task_id" in response.metadata or "task_url" in response.metadata, ( -# "Manus response should include task_id or task_url in metadata" -# ) -# @pytest.mark.asyncio -# async def test_manus_responses_api_different_agent_profiles(): -# """ -# Test that different agent profiles work correctly. -# """ -# litellm._turn_on_debug() - -# # Test with different agent profile variants -# agent_profiles = ["manus-1.6", "manus-1.6-lite", "manus-1.6-max"] - -# for profile in agent_profiles: -# try: -# response = await litellm.aresponses( -# model=f"manus/{profile}", -# input="Hello", -# api_key=os.getenv("MANUS_API_KEY"), -# max_output_tokens=20, -# ) - -# assert response.id is not None, f"Response for {profile} should have an ID" -# print(f"✓ {profile} works: {response.id}") -# except Exception as e: -# # Some profiles might not be available, that's okay -# print(f"⚠ {profile} not available: {e}") -# pass - From ff938e7c27c800550c74f01faf0f29bc74b2294d Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 13:04:11 -0800 Subject: [PATCH 038/114] v1.80.13 docs work in progress --- .../release_notes/v1.80.13/index.md | 175 ++++++++++++++++++ 1 file changed, 175 insertions(+) create mode 100644 docs/my-website/release_notes/v1.80.13/index.md diff --git a/docs/my-website/release_notes/v1.80.13/index.md b/docs/my-website/release_notes/v1.80.13/index.md new file mode 100644 index 00000000000..d895f4b0185 --- /dev/null +++ b/docs/my-website/release_notes/v1.80.13/index.md @@ -0,0 +1,175 @@ +--- +title: "[Preview] v1.80.13 - Google Interactions API" +slug: "v1-80-13" +date: 2026-01-10T10:00:00 +authors: + - name: Krrish Dholakia + title: CEO, LiteLLM + url: https://www.linkedin.com/in/krish-d/ + image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg + - name: Ishaan Jaff + title: CTO, LiteLLM + url: https://www.linkedin.com/in/reffajnaahsi/ + image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg +hide_table_of_contents: false +--- + +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +## Deploy this version + + + + +``` showLineNumbers title="docker run litellm" +docker run \ +-e STORE_MODEL_IN_DB=True \ +-p 4000:4000 \ +docker.litellm.ai/berriai/litellm:v1.80.13.rc.1 +``` + + + + + +``` showLineNumbers title="pip install litellm" +pip install litellm==1.80.13 +``` + + + + +--- + +## Key Highlights + +- **UI Usage - Endpoint Activity** - Users can now see Endpoint Activity Metrics in the UI. + + +--- + +### UI Usage - Endpoint Activity + + + +Users can now see Endpoint Activity Metrics in the UI. + +--- + +## New Providers and Endpoints + +### New Providers (X new providers) + +| Provider | Supported LiteLLM Endpoints | Description | +| -------- | ------------------- | ----------- | + + +### New LLM API Endpoints (X new endpoints) + +| Endpoint | Method | Description | Documentation | +| -------- | ------ | ----------- | ------------- | + + +--- + +## New Models / Updated Models + +#### New Model Support (X new models) + +| Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) | Features | +| -------- | ----- | -------------- | ------------------- | -------------------- | -------- | + + +#### Features + + +### Bug Fixes + + +--- + +## LLM API Endpoints + +#### Features + + + +#### Bugs + + + +--- + +## Management Endpoints / UI + +#### Features + + +#### Bugs + + + +--- + +## AI Integrations + +### Logging + + +### Guardrails + + + +### Secret Managers + + + +--- + +## Spend Tracking, Budgets and Rate Limiting + + + +--- + +## MCP Gateway + + + +--- + +## Agent Gateway (A2A) + + + +--- + +## Performance / Loadbalancing / Reliability improvements + + +--- + +## Documentation Updates + + +--- + +## Infrastructure / CI/CD + + +--- + +## New Contributors + + +--- + +## Full Changelog + +**[View complete changelog on GitHub](https://github.com/BerriAI/litellm/compare/v1.80.11...v1.80.13.rc.1)** + From 5c46053307d8d187aff876b83a2d4bb70decefc9 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 13:15:23 -0800 Subject: [PATCH 039/114] Adding image --- docs/my-website/img/ui_endpoint_activity.png | Bin 0 -> 515228 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 docs/my-website/img/ui_endpoint_activity.png diff --git a/docs/my-website/img/ui_endpoint_activity.png b/docs/my-website/img/ui_endpoint_activity.png new file mode 100644 index 0000000000000000000000000000000000000000..e2550066a077468350a7a2b82a25386d6f1f23ff GIT binary patch literal 515228 zcmeFZdsNcd{x@#ZOr4oZr|IV1ndx*>)6~qoa+*qKvNTh~yntzH-Z1YMRBAkBd1E?e zTBcTvsURXM;ti<0P#T&Uq9Rfd-Vg{CK@s?Uobx;D`7Y=A?`hV0p0$o^sjwG|&))C- zzP{eCy>Fj)bJ_Nd?l&458ry#P`P2msjqjdmXng(pZ<~M-XZ^dCz`w7r{(LcBL&MZ{ z?RP_^=dG7uV-#&8^6DLSwbpS%R z@o!PTax-_w%F|yKM+y_6xv<)NEG#TOzEKmH-@2cYf5F#{0B@h|)Oq&BpN0c5TLU-z 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zDW_PtBZhg-@61WiNf>60&|^nod1p@^{EKmaSGv>ATrdXQ^ak)amrxRwLeLAMHsxPO`9Va9?dH933S*LFJRAm`W`Mow!O@@XUFMp#kWl4@|1XWzKnfi6<`RmtO!ki|e^e5@EK;`Qk&9#h+&*#P1vB z4xmaGM%h?3o8)lof$xie8~gejilAm+5!COtqm`J{ZF~l@Zu4!!e)51dY8PJ4q91e* z6f$mxY0LB2P>>DvKz_LND%WcYhF{qaBzq&APCN4Er%0$Hf>Cva_R~sW0}>MZkm{Qx zFBPJ&lgr>Mf^At5#TH#(Uva0I`fJJX4>VCf!ZSZY^B z#lll=ifhuYs{MK1DyXVR9O$q-!@+>y3mJb~rE6YScy$@MBCPLvm~Hb|;zuOkkNCCU zk(-;a~$8qc`aK3A^ZiLVM5Ttlu|(0LMP+ z?yDW81;U)&yZa3u)st!eqY{y|G)6hbF^8u_b{&xA9Hc&-fp9r%)EA2SGA%hh0VTY( zoMY{Dnenb8by?utp~3Ync_Sr}{0%qy7; TKEqDwrEaw}^wf!}R#*Q8>0KV5 literal 0 HcmV?d00001 From e3fe02148d455d0fade389224a13b1705594195e Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 13:20:43 -0800 Subject: [PATCH 040/114] _mask_sequence --- tests/code_coverage_tests/recursive_detector.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/code_coverage_tests/recursive_detector.py b/tests/code_coverage_tests/recursive_detector.py index 20e6a381e5b..2a460f621b2 100644 --- a/tests/code_coverage_tests/recursive_detector.py +++ b/tests/code_coverage_tests/recursive_detector.py @@ -35,6 +35,7 @@ IGNORE_FUNCTIONS = [ "_fix_enum_types", # max depth set. "_collect_argument_paths", # max depth set. "_split_text", # max depth set. + "_mask_sequence", # max depth set. "_delete_nested_value_custom", # max depth set (bounded by number of path segments). "filter_exceptions_from_params", # max depth set (default 20) to prevent infinite recursion. "__getattr__", # lazy loading pattern in litellm/__init__.py with proper caching to prevent infinite recursion. From 3c3ed3bcfbf9caeb2abe9f06e5348a9ad6ce6122 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 13:25:31 -0800 Subject: [PATCH 041/114] fix resposne api utils --- litellm/llms/bedrock/base_aws_llm.py | 44 +-- litellm/llms/bedrock/common_utils.py | 2 +- litellm/llms/bedrock/files/handler.py | 1 - .../llms/bedrock/test_bedrock_ssl_verify.py | 349 ------------------ 4 files changed, 4 insertions(+), 392 deletions(-) delete mode 100644 tests/test_litellm/llms/bedrock/test_bedrock_ssl_verify.py diff --git a/litellm/llms/bedrock/base_aws_llm.py b/litellm/llms/bedrock/base_aws_llm.py index 18e9deb53b0..e9cea23ea4a 100644 --- a/litellm/llms/bedrock/base_aws_llm.py +++ b/litellm/llms/bedrock/base_aws_llm.py @@ -74,41 +74,6 @@ class BaseAWSLLM: "aws_external_id", ] - def _get_ssl_verify(self): - """ - Get SSL verification setting for boto3 clients. - - This ensures that custom CA certificates are properly used for all AWS API calls, - including STS and Bedrock services. - - Returns: - Union[bool, str]: SSL verification setting - False to disable, True to enable, - or a string path to a CA bundle file - """ - import litellm - from litellm.secret_managers.main import str_to_bool - - # Check environment variable first (highest priority) - ssl_verify = os.getenv("SSL_VERIFY", litellm.ssl_verify) - - # Convert string "False"/"True" to boolean - if isinstance(ssl_verify, str): - # Check if it's a file path - if os.path.exists(ssl_verify): - return ssl_verify - # Otherwise try to convert to boolean - ssl_verify_bool = str_to_bool(ssl_verify) - if ssl_verify_bool is not None: - ssl_verify = ssl_verify_bool - - # Check SSL_CERT_FILE environment variable for custom CA bundle - if ssl_verify is True or ssl_verify == "True": - ssl_cert_file = os.getenv("SSL_CERT_FILE") - if ssl_cert_file and os.path.exists(ssl_cert_file): - return ssl_cert_file - - return ssl_verify - def get_cache_key(self, credential_args: Dict[str, Optional[str]]) -> str: """ Generate a unique cache key based on the credential arguments. @@ -604,7 +569,6 @@ class BaseAWSLLM: "sts", region_name=aws_region_name, endpoint_url=sts_endpoint, - verify=self._get_ssl_verify(), ) # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html @@ -661,7 +625,7 @@ class BaseAWSLLM: # Create an STS client without credentials with tracer.trace("boto3.client(sts) for manual IRSA"): - sts_client = boto3.client("sts", region_name=region, verify=self._get_ssl_verify()) + sts_client = boto3.client("sts", region_name=region) # Manually assume the IRSA role with the session name verbose_logger.debug( @@ -684,7 +648,6 @@ class BaseAWSLLM: aws_access_key_id=irsa_creds["AccessKeyId"], aws_secret_access_key=irsa_creds["SecretAccessKey"], aws_session_token=irsa_creds["SessionToken"], - verify=self._get_ssl_verify(), ) # Get current caller identity for debugging @@ -723,7 +686,7 @@ class BaseAWSLLM: verbose_logger.debug("Same account role assumption, using automatic IRSA") with tracer.trace("boto3.client(sts) with automatic IRSA"): - sts_client = boto3.client("sts", region_name=region, verify=self._get_ssl_verify()) + sts_client = boto3.client("sts", region_name=region) # Get current caller identity for debugging try: @@ -846,7 +809,7 @@ class BaseAWSLLM: # This allows the web identity token to work automatically if aws_access_key_id is None and aws_secret_access_key is None: with tracer.trace("boto3.client(sts)"): - sts_client = boto3.client("sts", verify=self._get_ssl_verify()) + sts_client = boto3.client("sts") else: with tracer.trace("boto3.client(sts)"): sts_client = boto3.client( @@ -854,7 +817,6 @@ class BaseAWSLLM: aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key, aws_session_token=aws_session_token, - verify=self._get_ssl_verify(), ) assume_role_params = { diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index f4b5de8f7c0..d62a8bae425 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -260,7 +260,7 @@ def init_bedrock_client( status_code=401, ) - sts_client = boto3.client("sts", verify=ssl_verify) + sts_client = boto3.client("sts") # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts/client/assume_role_with_web_identity.html diff --git a/litellm/llms/bedrock/files/handler.py b/litellm/llms/bedrock/files/handler.py index 0350271dc44..d6177e090d5 100644 --- a/litellm/llms/bedrock/files/handler.py +++ b/litellm/llms/bedrock/files/handler.py @@ -142,7 +142,6 @@ class BedrockFilesHandler(BaseAWSLLM): aws_secret_access_key=credentials.secret_key, aws_session_token=credentials.token, region_name=aws_region_name, - verify=self._get_ssl_verify(), ) # Download file from S3 diff --git a/tests/test_litellm/llms/bedrock/test_bedrock_ssl_verify.py b/tests/test_litellm/llms/bedrock/test_bedrock_ssl_verify.py deleted file mode 100644 index 9142de295ea..00000000000 --- a/tests/test_litellm/llms/bedrock/test_bedrock_ssl_verify.py +++ /dev/null @@ -1,349 +0,0 @@ -""" -Test SSL verification for AWS Bedrock boto3 clients. - -This test ensures that custom CA certificates are properly passed to all boto3 clients -(STS and Bedrock services) to support internal certificate authorities. - -Issue: https://github.com/BerriAI/litellm/issues/XXXX -User reported that SSL_CERT_FILE environment variable and ssl_verify config were not -being applied to boto3 clients, causing "certificate verify failed" errors. -""" - -import os -import sys -import tempfile -from unittest.mock import MagicMock, Mock, patch - -import pytest - -sys.path.insert(0, os.path.abspath("../..")) - -import litellm -from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM -from litellm.llms.bedrock.common_utils import init_bedrock_client - - -class TestBedrockSSLVerify: - """Test suite for SSL verification in Bedrock boto3 clients.""" - - def test_base_aws_llm_get_ssl_verify_default(self): - """Test that _get_ssl_verify returns default value when no custom config is set.""" - base_aws = BaseAWSLLM() - - # Clear any environment variables - os.environ.pop("SSL_VERIFY", None) - os.environ.pop("SSL_CERT_FILE", None) - - # Reset litellm.ssl_verify to default - litellm.ssl_verify = True - - ssl_verify = base_aws._get_ssl_verify() - assert ssl_verify is True - - def test_base_aws_llm_get_ssl_verify_false(self): - """Test that _get_ssl_verify returns False when SSL verification is disabled.""" - base_aws = BaseAWSLLM() - - # Set SSL_VERIFY to False via environment - os.environ["SSL_VERIFY"] = "False" - - ssl_verify = base_aws._get_ssl_verify() - assert ssl_verify is False - - # Clean up - os.environ.pop("SSL_VERIFY", None) - - def test_base_aws_llm_get_ssl_verify_custom_ca_bundle(self): - """Test that _get_ssl_verify returns custom CA bundle path when SSL_CERT_FILE is set.""" - base_aws = BaseAWSLLM() - - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set SSL_CERT_FILE environment variable - os.environ["SSL_CERT_FILE"] = ca_bundle_path - os.environ.pop("SSL_VERIFY", None) - litellm.ssl_verify = True - - ssl_verify = base_aws._get_ssl_verify() - assert ssl_verify == ca_bundle_path - finally: - # Clean up - os.environ.pop("SSL_CERT_FILE", None) - os.unlink(ca_bundle_path) - - def test_base_aws_llm_get_ssl_verify_litellm_config(self): - """Test that _get_ssl_verify uses litellm.ssl_verify when set.""" - base_aws = BaseAWSLLM() - - # Clear environment variables - os.environ.pop("SSL_VERIFY", None) - os.environ.pop("SSL_CERT_FILE", None) - - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set litellm.ssl_verify to custom CA bundle - litellm.ssl_verify = ca_bundle_path - - ssl_verify = base_aws._get_ssl_verify() - # When ssl_verify is a path, it should be returned directly - assert ssl_verify == ca_bundle_path - finally: - # Clean up - litellm.ssl_verify = True - os.unlink(ca_bundle_path) - - @patch("boto3.client") - def test_init_bedrock_client_passes_ssl_verify_to_sts(self, mock_boto3_client): - """Test that init_bedrock_client passes ssl_verify to STS client.""" - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set SSL_CERT_FILE environment variable - os.environ["SSL_CERT_FILE"] = ca_bundle_path - litellm.ssl_verify = True - - # Mock the STS client and Bedrock client - mock_sts_client = MagicMock() - mock_sts_response = { - "Credentials": { - "AccessKeyId": "test_access_key", - "SecretAccessKey": "test_secret_key", - "SessionToken": "test_session_token", - } - } - mock_sts_client.assume_role.return_value = mock_sts_response - - mock_bedrock_client = MagicMock() - - # Configure mock to return different clients based on service name - def side_effect(service_name=None, **kwargs): - if service_name == "sts": - return mock_sts_client - elif service_name == "bedrock-runtime": - return mock_bedrock_client - return MagicMock() - - mock_boto3_client.side_effect = side_effect - - # Call init_bedrock_client with role assumption - client = init_bedrock_client( - aws_region_name="us-west-2", - aws_access_key_id="test_key", - aws_secret_access_key="test_secret", - aws_role_name="arn:aws:iam::123456789012:role/test-role", - aws_session_name="test-session", - ) - - # Verify that boto3.client was called with verify parameter for STS - sts_calls = [ - call for call in mock_boto3_client.call_args_list - if (len(call[0]) > 0 and call[0][0] == "sts") or - ("service_name" not in call[1]) # STS calls don't use service_name kwarg - ] - - assert len(sts_calls) > 0, "STS client should have been created" - - # Check that verify parameter was passed to STS client - sts_call = sts_calls[0] - assert "verify" in sts_call[1], "verify parameter should be passed to STS client" - assert sts_call[1]["verify"] == ca_bundle_path, f"verify should be set to CA bundle path, got {sts_call[1]['verify']}" - - # Verify that boto3.client was called with verify parameter for Bedrock - bedrock_calls = [ - call for call in mock_boto3_client.call_args_list - if "service_name" in call[1] and call[1]["service_name"] == "bedrock-runtime" - ] - - assert len(bedrock_calls) > 0, "Bedrock client should have been created" - - bedrock_call = bedrock_calls[0] - assert "verify" in bedrock_call[1], "verify parameter should be passed to Bedrock client" - assert bedrock_call[1]["verify"] == ca_bundle_path, f"verify should be set to CA bundle path, got {bedrock_call[1]['verify']}" - - finally: - # Clean up - os.environ.pop("SSL_CERT_FILE", None) - os.unlink(ca_bundle_path) - - @patch("boto3.client") - def test_base_aws_llm_auth_with_role_passes_ssl_verify(self, mock_boto3_client): - """Test that _auth_with_aws_role passes ssl_verify to STS client.""" - base_aws = BaseAWSLLM() - - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set SSL_CERT_FILE environment variable - os.environ["SSL_CERT_FILE"] = ca_bundle_path - litellm.ssl_verify = True - - # Mock the STS client - mock_sts_client = MagicMock() - mock_sts_response = { - "Credentials": { - "AccessKeyId": "test_access_key", - "SecretAccessKey": "test_secret_key", - "SessionToken": "test_session_token", - "Expiration": "2025-01-10T00:00:00Z", - } - } - - # Convert Expiration to datetime - from datetime import datetime, timezone - mock_sts_response["Credentials"]["Expiration"] = datetime.now(timezone.utc) - - mock_sts_client.assume_role.return_value = mock_sts_response - mock_boto3_client.return_value = mock_sts_client - - # Call _auth_with_aws_role - credentials, ttl = base_aws._auth_with_aws_role( - aws_access_key_id="test_key", - aws_secret_access_key="test_secret", - aws_session_token=None, - aws_role_name="arn:aws:iam::123456789012:role/test-role", - aws_session_name="test-session", - ) - - # Verify that boto3.client was called with verify parameter - assert mock_boto3_client.called, "boto3.client should have been called" - - call_kwargs = mock_boto3_client.call_args[1] - assert "verify" in call_kwargs, "verify parameter should be passed to STS client" - assert call_kwargs["verify"] == ca_bundle_path, f"verify should be set to CA bundle path, got {call_kwargs['verify']}" - - finally: - # Clean up - os.environ.pop("SSL_CERT_FILE", None) - os.unlink(ca_bundle_path) - - @patch("litellm.llms.bedrock.base_aws_llm.get_secret") - @patch("boto3.client") - def test_base_aws_llm_auth_with_web_identity_passes_ssl_verify(self, mock_boto3_client, mock_get_secret): - """Test that _auth_with_web_identity_token passes ssl_verify to STS client.""" - base_aws = BaseAWSLLM() - - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set SSL_CERT_FILE environment variable - os.environ["SSL_CERT_FILE"] = ca_bundle_path - litellm.ssl_verify = True - - # Mock get_secret to return the token - mock_get_secret.return_value = "mocked_oidc_token" - - # Mock the STS client - mock_sts_client = MagicMock() - mock_sts_response = { - "Credentials": { - "AccessKeyId": "test_access_key", - "SecretAccessKey": "test_secret_key", - "SessionToken": "test_session_token", - }, - "PackedPolicySize": 100, - } - - mock_sts_client.assume_role_with_web_identity.return_value = mock_sts_response - - # Mock boto3.Session - mock_session = MagicMock() - mock_credentials = MagicMock() - mock_session.get_credentials.return_value = mock_credentials - - mock_boto3_client.return_value = mock_sts_client - - with patch("boto3.Session", return_value=mock_session): - # Call _auth_with_web_identity_token - credentials, ttl = base_aws._auth_with_web_identity_token( - aws_web_identity_token="test_token", - aws_role_name="arn:aws:iam::123456789012:role/test-role", - aws_session_name="test-session", - aws_region_name="us-west-2", - aws_sts_endpoint=None, - ) - - # Verify that boto3.client was called with verify parameter - assert mock_boto3_client.called, "boto3.client should have been called" - - call_kwargs = mock_boto3_client.call_args[1] - assert "verify" in call_kwargs, "verify parameter should be passed to STS client" - assert call_kwargs["verify"] == ca_bundle_path, f"verify should be set to CA bundle path, got {call_kwargs['verify']}" - - finally: - # Clean up - os.environ.pop("SSL_CERT_FILE", None) - os.unlink(ca_bundle_path) - - def test_ssl_verify_priority_env_over_litellm_config(self): - """Test that SSL_VERIFY environment variable takes priority over litellm.ssl_verify.""" - base_aws = BaseAWSLLM() - - # Set litellm.ssl_verify to True - litellm.ssl_verify = True - - # Set SSL_VERIFY environment variable to False - os.environ["SSL_VERIFY"] = "False" - - try: - ssl_verify = base_aws._get_ssl_verify() - assert ssl_verify is False, "Environment variable should take priority" - finally: - # Clean up - os.environ.pop("SSL_VERIFY", None) - litellm.ssl_verify = True - - def test_ssl_cert_file_priority_over_default(self): - """Test that SSL_CERT_FILE takes priority when ssl_verify is True.""" - base_aws = BaseAWSLLM() - - # Create a temporary CA bundle file - with tempfile.NamedTemporaryFile(mode="w", suffix=".pem", delete=False) as f: - f.write("-----BEGIN CERTIFICATE-----\n") - f.write("FAKE CERTIFICATE FOR TESTING\n") - f.write("-----END CERTIFICATE-----\n") - ca_bundle_path = f.name - - try: - # Set SSL_CERT_FILE environment variable - os.environ["SSL_CERT_FILE"] = ca_bundle_path - os.environ.pop("SSL_VERIFY", None) - litellm.ssl_verify = True - - ssl_verify = base_aws._get_ssl_verify() - assert ssl_verify == ca_bundle_path, "SSL_CERT_FILE should be used when ssl_verify is True" - finally: - # Clean up - os.environ.pop("SSL_CERT_FILE", None) - os.unlink(ca_bundle_path) - - -if __name__ == "__main__": - # Run tests - pytest.main([__file__, "-v", "-s"]) From c0cf8bc27d0110149bcac4d8b73a297ca8da099c Mon Sep 17 00:00:00 2001 From: Ishaan Jaff Date: Sun, 11 Jan 2026 01:27:54 +0400 Subject: [PATCH 042/114] [Feat] Manus FILES API - Add File upload, get, delete, list (#18904) * add MANUS get response * init TwoStepFileUploadRequest * init TwoStepFileUploadConfig * add async_create_file to handle 2 step uploads * init ManusFilesConfig * add add get_provider_files_config MANUS * fix validate_environment * test_manus_files_api_e2e_all_methods * aws fix base * init files API MANUS * test_manus_responses_api_with_file_upload * mypy lint fixes * fix BedrockFilesConfig * manus docs * docs manus * mypy lint * add add fix resposne api utils MANUS --- docs/my-website/docs/providers/manus.md | 177 ++++- litellm/files/main.py | 198 ++++- litellm/llms/base_llm/files/transformation.py | 93 ++- litellm/llms/bedrock/files/transformation.py | 69 +- litellm/llms/custom_httpx/llm_http_handler.py | 737 +++++++++++++++--- litellm/llms/gemini/files/transformation.py | 66 ++ litellm/llms/manus/files/__init__.py | 2 + litellm/llms/manus/files/transformation.py | 439 +++++++++++ .../llms/vertex_ai/files/transformation.py | 68 +- litellm/responses/utils.py | 13 +- litellm/types/files.py | 42 +- litellm/utils.py | 7 +- provider_endpoints_support.json | 1 + .../test_manus_files_all_methods.py | 72 ++ .../test_manus_files_all_methods.py | 71 ++ .../test_manus_responses_api.py | 95 ++- .../llms/bedrock/test_base_aws_llm.py | 11 +- 17 files changed, 2020 insertions(+), 141 deletions(-) create mode 100644 litellm/llms/manus/files/__init__.py create mode 100644 litellm/llms/manus/files/transformation.py create mode 100644 tests/batches_tests/test_manus_files_all_methods.py create mode 100644 tests/llm_responses_api_testing/test_manus_files_all_methods.py diff --git a/docs/my-website/docs/providers/manus.md b/docs/my-website/docs/providers/manus.md index 2981ec6d247..92bf2b9b966 100644 --- a/docs/my-website/docs/providers/manus.md +++ b/docs/my-website/docs/providers/manus.md @@ -9,7 +9,7 @@ Use Manus AI agents through LiteLLM's OpenAI-compatible Responses API. |----------|---------| | Description | Manus is an AI agent platform for complex reasoning tasks, document analysis, and multi-step workflows with asynchronous task execution. | | Provider Route on LiteLLM | `manus/{agent_profile}` | -| Supported Operations | `/responses` (Responses API) | +| Supported Operations | `/responses` (Responses API), `/files` (Files API) | | Provider Doc | [Manus API ↗](https://open.manus.im/docs/openai-compatibility) | ## Model Format @@ -188,7 +188,182 @@ For production applications, use [webhooks](https://open.manus.im/docs/webhooks) | `max_output_tokens` | ✅ | Limits response length | | `previous_response_id` | ✅ | For multi-turn conversations | +## Files API + +Manus supports file uploads for document analysis and processing. Files can be uploaded and then referenced in Responses API calls. + +### LiteLLM Python SDK + +```python showLineNumbers title="Upload, Use, Retrieve, and Delete Files" +import litellm +import os + +# Set API key +os.environ["MANUS_API_KEY"] = "your-manus-api-key" + +# Upload file +file_content = b"This is a document for analysis." +created_file = await litellm.acreate_file( + file=("document.txt", file_content), + purpose="assistants", + custom_llm_provider="manus", +) +print(f"Uploaded file: {created_file.id}") + +# Use file with Responses API +response = await litellm.aresponses( + model="manus/manus-1.6", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": "Summarize this document."}, + {"type": "input_file", "file_id": created_file.id}, + ], + }, + ], + extra_body={"task_mode": "agent", "agent_profile": "manus-1.6-agent"}, +) +print(f"Response: {response.id}") + +# Retrieve file +retrieved_file = await litellm.afile_retrieve( + file_id=created_file.id, + custom_llm_provider="manus", +) +print(f"File details: {retrieved_file.filename}, {retrieved_file.bytes} bytes") + +# Delete file +deleted_file = await litellm.afile_delete( + file_id=created_file.id, + custom_llm_provider="manus", +) +print(f"Deleted: {deleted_file.deleted}") +``` + +### LiteLLM AI Gateway + + + + +```bash showLineNumbers title="Upload File" +# Upload file +curl -X POST http://localhost:4000/v1/files \ + -H "Authorization: Bearer your-proxy-key" \ + -F "file=@document.txt" \ + -F "purpose=assistants" \ + -F "custom_llm_provider=manus" + +# Response +{ + "id": "file_abc123", + "object": "file", + "bytes": 1024, + "created_at": 1234567890, + "filename": "document.txt", + "purpose": "assistants", + "status": "uploaded" +} +``` + +```bash showLineNumbers title="Use File with Responses API" +# Create response with file +curl -X POST http://localhost:4000/responses \ + -H "Authorization: Bearer your-proxy-key" \ + -H "Content-Type: application/json" \ + -d '{ + "model": "manus-agent", + "input": [ + { + "role": "user", + "content": [ + {"type": "input_text", "text": "Summarize this document."}, + {"type": "input_file", "file_id": "file_abc123"} + ] + } + ] + }' +``` + +```bash showLineNumbers title="Retrieve File" +# Get file details +curl http://localhost:4000/v1/files/file_abc123 \ + -H "Authorization: Bearer your-proxy-key" + +# Response +{ + "id": "file_abc123", + "object": "file", + "bytes": 1024, + "created_at": 1234567890, + "filename": "document.txt", + "purpose": "assistants", + "status": "uploaded" +} +``` + +```bash showLineNumbers title="Delete File" +# Delete file +curl -X DELETE http://localhost:4000/v1/files/file_abc123 \ + -H "Authorization: Bearer your-proxy-key" + +# Response +{ + "id": "file_abc123", + "object": "file", + "deleted": true +} +``` + + + + +```python showLineNumbers title="Upload, Use, Retrieve, and Delete Files" +import openai + +client = openai.OpenAI( + base_url="http://localhost:4000", + api_key="your-proxy-key" +) + +# Upload file +with open("document.txt", "rb") as f: + created_file = client.files.create( + file=f, + purpose="assistants", + extra_body={"custom_llm_provider": "manus"} + ) +print(f"Uploaded file: {created_file.id}") + +# Use file with Responses API +response = client.responses.create( + model="manus-agent", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": "Summarize this document."}, + {"type": "input_file", "file_id": created_file.id} + ] + } + ] +) +print(f"Response: {response.id}") + +# Retrieve file +retrieved_file = client.files.retrieve(created_file.id) +print(f"File: {retrieved_file.filename}, {retrieved_file.bytes} bytes") + +# Delete file +deleted_file = client.files.delete(created_file.id) +print(f"Deleted: {deleted_file.deleted}") +``` + + + + ## Related Documentation - [LiteLLM Responses API](/docs/response_api) +- [LiteLLM Files API](/docs/proxy/litellm_managed_files) - [Manus OpenAI Compatibility](https://open.manus.im/docs/openai-compatibility) diff --git a/litellm/files/main.py b/litellm/files/main.py index a7c82290c29..913ec84626d 100644 --- a/litellm/files/main.py +++ b/litellm/files/main.py @@ -8,6 +8,7 @@ https://platform.openai.com/docs/api-reference/files import asyncio import contextvars import os +import time from functools import partial from typing import Any, Coroutine, Dict, Literal, Optional, Union, cast @@ -60,7 +61,7 @@ async def acreate_file( file: FileTypes, purpose: Literal["assistants", "batch", "fine-tune"], expires_after: Optional[FileExpiresAfter] = None, - custom_llm_provider: Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm"] = "openai", + custom_llm_provider: Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "manus"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -105,7 +106,7 @@ def create_file( file: FileTypes, purpose: Literal["assistants", "batch", "fine-tune"], expires_after: Optional[FileExpiresAfter] = None, - custom_llm_provider: Optional[Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm"]] = None, + custom_llm_provider: Optional[Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "manus"]] = None, extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -274,7 +275,7 @@ def create_file( ) else: raise litellm.exceptions.BadRequestError( - message="LiteLLM doesn't support {} for 'create_file'. Only ['openai', 'azure', 'vertex_ai'] are supported.".format( + message="LiteLLM doesn't support {} for 'create_file'. Only ['openai', 'azure', 'vertex_ai', 'manus'] are supported.".format( custom_llm_provider ), model="n/a", @@ -293,7 +294,7 @@ def create_file( @client async def afile_retrieve( file_id: str, - custom_llm_provider: Literal["openai", "azure", "hosted_vllm"] = "openai", + custom_llm_provider: Literal["openai", "azure", "hosted_vllm", "manus"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -334,7 +335,7 @@ async def afile_retrieve( @client def file_retrieve( file_id: str, - custom_llm_provider: Literal["openai", "azure", "hosted_vllm"] = "openai", + custom_llm_provider: Literal["openai", "azure", "hosted_vllm", "manus"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -428,18 +429,60 @@ def file_retrieve( file_id=file_id, ) else: - raise litellm.exceptions.BadRequestError( - message="LiteLLM doesn't support {} for 'file_retrieve'. Only 'openai' and 'azure' are supported.".format( - custom_llm_provider - ), - model="n/a", - llm_provider=custom_llm_provider, - response=httpx.Response( - status_code=400, - content="Unsupported provider", - request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore - ), + # Try using provider config pattern (for Manus, Bedrock, etc.) + provider_config = ProviderConfigManager.get_provider_files_config( + model="", + provider=LlmProviders(custom_llm_provider), ) + if provider_config is not None: + litellm_params_dict = get_litellm_params(**kwargs) + litellm_params_dict["api_key"] = optional_params.api_key + litellm_params_dict["api_base"] = optional_params.api_base + + logging_obj = kwargs.get("litellm_logging_obj") + if logging_obj is None: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as LiteLLMLoggingObj, + ) + logging_obj = LiteLLMLoggingObj( + model="", + messages=[], + stream=False, + call_type="afile_retrieve" if _is_async else "file_retrieve", + start_time=time.time(), + litellm_call_id=kwargs.get("litellm_call_id", str(uuid.uuid4())), + function_id=str(kwargs.get("id") or ""), + ) + + client = kwargs.get("client") + response = base_llm_http_handler.retrieve_file( + file_id=file_id, + provider_config=provider_config, + litellm_params=litellm_params_dict, + headers=extra_headers or {}, + logging_obj=logging_obj, + _is_async=_is_async, + client=( + client + if client is not None + and isinstance(client, (HTTPHandler, AsyncHTTPHandler)) + else None + ), + timeout=timeout, + ) + else: + raise litellm.exceptions.BadRequestError( + message="LiteLLM doesn't support {} for 'file_retrieve'. Only 'openai', 'azure', and 'manus' are supported.".format( + custom_llm_provider + ), + model="n/a", + llm_provider=custom_llm_provider, + response=httpx.Response( + status_code=400, + content="Unsupported provider", + request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore + ), + ) return cast(FileObject, response) except Exception as e: @@ -450,7 +493,7 @@ def file_retrieve( @client async def afile_delete( file_id: str, - custom_llm_provider: Literal["openai", "azure"] = "openai", + custom_llm_provider: Literal["openai", "azure", "manus"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -494,7 +537,7 @@ async def afile_delete( def file_delete( file_id: str, model: Optional[str] = None, - custom_llm_provider: Union[Literal["openai", "azure"], str] = "openai", + custom_llm_provider: Union[Literal["openai", "azure", "manus"], str] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -596,18 +639,58 @@ def file_delete( litellm_params=litellm_params_dict, ) else: - raise litellm.exceptions.BadRequestError( - message="LiteLLM doesn't support {} for 'delete_batch'. Only 'openai' is supported.".format( - custom_llm_provider - ), - model="n/a", - llm_provider=custom_llm_provider, - response=httpx.Response( - status_code=400, - content="Unsupported provider", - request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore - ), + # Try using provider config pattern (for Manus, Bedrock, etc.) + provider_config = ProviderConfigManager.get_provider_files_config( + model="", + provider=LlmProviders(custom_llm_provider), ) + if provider_config is not None: + litellm_params_dict["api_key"] = optional_params.api_key + litellm_params_dict["api_base"] = optional_params.api_base + + logging_obj = kwargs.get("litellm_logging_obj") + if logging_obj is None: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as LiteLLMLoggingObj, + ) + logging_obj = LiteLLMLoggingObj( + model="", + messages=[], + stream=False, + call_type="afile_delete" if _is_async else "file_delete", + start_time=time.time(), + litellm_call_id=kwargs.get("litellm_call_id", str(uuid.uuid4())), + function_id=str(kwargs.get("id") or ""), + ) + + response = base_llm_http_handler.delete_file( + file_id=file_id, + provider_config=provider_config, + litellm_params=litellm_params_dict, + headers=extra_headers or {}, + logging_obj=logging_obj, + _is_async=_is_async, + client=( + client + if client is not None + and isinstance(client, (HTTPHandler, AsyncHTTPHandler)) + else None + ), + timeout=timeout, + ) + else: + raise litellm.exceptions.BadRequestError( + message="LiteLLM doesn't support {} for 'file_delete'. Only 'openai', 'azure', and 'manus' are supported.".format( + custom_llm_provider + ), + model="n/a", + llm_provider=custom_llm_provider, + response=httpx.Response( + status_code=400, + content="Unsupported provider", + request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"), # type: ignore + ), + ) return cast(FileDeleted, response) except Exception as e: raise e @@ -616,7 +699,7 @@ def file_delete( # List files @client async def afile_list( - custom_llm_provider: Literal["openai", "azure"] = "openai", + custom_llm_provider: Literal["openai", "azure", "manus"] = "openai", purpose: Optional[str] = None, extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, @@ -657,7 +740,7 @@ async def afile_list( @client def file_list( - custom_llm_provider: Literal["openai", "azure"] = "openai", + custom_llm_provider: Literal["openai", "azure", "manus"] = "openai", purpose: Optional[str] = None, extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, @@ -687,7 +770,50 @@ def file_list( timeout = 600.0 _is_async = kwargs.pop("is_async", False) is True - if custom_llm_provider in OPENAI_COMPATIBLE_BATCH_AND_FILES_PROVIDERS: + + # Check if provider has a custom files config (e.g., Manus, Bedrock, Vertex AI) + provider_config = ProviderConfigManager.get_provider_files_config( + model="", + provider=LlmProviders(custom_llm_provider), + ) + if provider_config is not None: + litellm_params_dict = get_litellm_params(**kwargs) + litellm_params_dict["api_key"] = optional_params.api_key + litellm_params_dict["api_base"] = optional_params.api_base + + logging_obj = kwargs.get("litellm_logging_obj") + if logging_obj is None: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as LiteLLMLoggingObj, + ) + logging_obj = LiteLLMLoggingObj( + model="", + messages=[], + stream=False, + call_type="afile_list" if _is_async else "file_list", + start_time=time.time(), + litellm_call_id=kwargs.get("litellm_call_id", str(uuid.uuid4())), + function_id=str(kwargs.get("id", "")), + ) + + client = kwargs.get("client") + response = base_llm_http_handler.list_files( + purpose=purpose, + provider_config=provider_config, + litellm_params=litellm_params_dict, + headers=extra_headers or {}, + logging_obj=logging_obj, + _is_async=_is_async, + client=( + client + if client is not None + and isinstance(client, (HTTPHandler, AsyncHTTPHandler)) + else None + ), + timeout=timeout, + ) + return response + elif custom_llm_provider in OPENAI_COMPATIBLE_BATCH_AND_FILES_PROVIDERS: # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there api_base = ( optional_params.api_base @@ -752,7 +878,7 @@ def file_list( ) else: raise litellm.exceptions.BadRequestError( - message="LiteLLM doesn't support {} for 'file_list'. Only 'openai' and 'azure' are supported.".format( + message="LiteLLM doesn't support {} for 'file_list'. Only 'openai', 'azure', and 'manus' are supported.".format( custom_llm_provider ), model="n/a", @@ -771,7 +897,7 @@ def file_list( @client async def afile_content( file_id: str, - custom_llm_provider: Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "anthropic"] = "openai", + custom_llm_provider: Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "anthropic", "manus"] = "openai", extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, **kwargs, @@ -816,7 +942,7 @@ def file_content( file_id: str, model: Optional[str] = None, custom_llm_provider: Optional[ - Union[Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "anthropic"], str] + Union[Literal["openai", "azure", "vertex_ai", "bedrock", "hosted_vllm", "anthropic", "manus"], str] ] = None, extra_headers: Optional[Dict[str, str]] = None, extra_body: Optional[Dict[str, str]] = None, @@ -977,7 +1103,7 @@ def file_content( ) else: raise litellm.exceptions.BadRequestError( - message="LiteLLM doesn't support {} for 'custom_llm_provider'. Supported providers are 'openai', 'azure', 'vertex_ai', 'bedrock'.".format( + message="LiteLLM doesn't support {} for 'file_content'. Supported providers are 'openai', 'azure', 'vertex_ai', 'bedrock', 'manus'.".format( custom_llm_provider ), model="n/a", diff --git a/litellm/llms/base_llm/files/transformation.py b/litellm/llms/base_llm/files/transformation.py index 35b76479cdc..7b0a1868f19 100644 --- a/litellm/llms/base_llm/files/transformation.py +++ b/litellm/llms/base_llm/files/transformation.py @@ -2,11 +2,14 @@ from abc import ABC, abstractmethod from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union import httpx +from openai.types.file_deleted import FileDeleted from litellm.proxy._types import UserAPIKeyAuth +from litellm.types.files import TwoStepFileUploadConfig from litellm.types.llms.openai import ( AllMessageValues, CreateFileRequest, + FileContentRequest, OpenAICreateFileRequestOptionalParams, OpenAIFileObject, OpenAIFilesPurpose, @@ -75,7 +78,15 @@ class BaseFilesConfig(BaseConfig): create_file_data: CreateFileRequest, optional_params: dict, litellm_params: dict, - ) -> Union[dict, str, bytes]: + ) -> Union[dict, str, bytes, "TwoStepFileUploadConfig"]: + """ + Transform OpenAI-style file creation request into provider-specific format. + + Returns: + - dict: For pre-signed single-step uploads (e.g., Bedrock S3) + - str/bytes: For traditional file uploads + - TwoStepFileUploadConfig: For two-step upload process (e.g., Manus, GCS) + """ pass @abstractmethod @@ -88,6 +99,86 @@ class BaseFilesConfig(BaseConfig): ) -> OpenAIFileObject: pass + @abstractmethod + def transform_retrieve_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Transform file retrieve request into provider-specific format.""" + pass + + @abstractmethod + def transform_retrieve_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + """Transform file retrieve response into OpenAI format.""" + pass + + @abstractmethod + def transform_delete_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Transform file delete request into provider-specific format.""" + pass + + @abstractmethod + def transform_delete_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> "FileDeleted": + """Transform file delete response into OpenAI format.""" + pass + + @abstractmethod + def transform_list_files_request( + self, + purpose: Optional[str], + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Transform file list request into provider-specific format.""" + pass + + @abstractmethod + def transform_list_files_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> List[OpenAIFileObject]: + """Transform file list response into OpenAI format.""" + pass + + @abstractmethod + def transform_file_content_request( + self, + file_content_request: "FileContentRequest", + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Transform file content request into provider-specific format.""" + pass + + @abstractmethod + def transform_file_content_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> "HttpxBinaryResponseContent": + """Transform file content response into OpenAI format.""" + pass + def transform_request( self, model: str, diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py index 0a95cf9168f..fdcbe1a8242 100644 --- a/litellm/llms/bedrock/files/transformation.py +++ b/litellm/llms/bedrock/files/transformation.py @@ -1,12 +1,14 @@ import json import os import time -from litellm._uuid import uuid from typing import Any, Dict, List, Optional, Tuple, Union +import httpx from httpx import Headers, Response +from openai.types.file_deleted import FileDeleted from litellm._logging import verbose_logger +from litellm._uuid import uuid from litellm.files.utils import FilesAPIUtils from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data from litellm.llms.base_llm.chat.transformation import BaseLLMException @@ -18,6 +20,7 @@ from litellm.types.llms.openai import ( AllMessageValues, CreateFileRequest, FileTypes, + HttpxBinaryResponseContent, OpenAICreateFileRequestOptionalParams, OpenAIFileObject, PathLike, @@ -539,6 +542,70 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): status_code=status_code, message=error_message, headers=headers ) + def transform_retrieve_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("BedrockFilesConfig does not support file retrieval") + + def transform_retrieve_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + raise NotImplementedError("BedrockFilesConfig does not support file retrieval") + + def transform_delete_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("BedrockFilesConfig does not support file deletion") + + def transform_delete_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> FileDeleted: + raise NotImplementedError("BedrockFilesConfig does not support file deletion") + + def transform_list_files_request( + self, + purpose: Optional[str], + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("BedrockFilesConfig does not support file listing") + + def transform_list_files_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> List[OpenAIFileObject]: + raise NotImplementedError("BedrockFilesConfig does not support file listing") + + def transform_file_content_request( + self, + file_content_request, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("BedrockFilesConfig does not support file content retrieval") + + def transform_file_content_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> HttpxBinaryResponseContent: + raise NotImplementedError("BedrockFilesConfig does not support file content retrieval") + class BedrockJsonlFilesTransformation: """ diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index ea740400664..1da6e61252f 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -14,6 +14,7 @@ from typing import ( ) import httpx # type: ignore +from openai.types.file_deleted import FileDeleted import litellm import litellm.litellm_core_utils @@ -71,6 +72,7 @@ from litellm.types.containers.main import ( ContainerObject, DeleteContainerResult, ) +from litellm.types.files import TwoStepFileUploadConfig from litellm.types.llms.anthropic_messages.anthropic_response import ( AnthropicMessagesResponse, ) @@ -82,6 +84,7 @@ from litellm.types.llms.anthropic_skills import ( from litellm.types.llms.openai import ( CreateBatchRequest, CreateFileRequest, + FileContentRequest, HttpxBinaryResponseContent, OpenAIFileObject, ResponseInputParam, @@ -2782,6 +2785,38 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, ) + def _extract_upload_url_from_response( + self, + response: httpx.Response, + upload_url_location: str, + upload_url_key: str = "upload_url", + ) -> tuple[Optional[str], Optional[dict]]: + """ + Extract upload URL from initial file creation response. + + Args: + response: HTTP response from initial file creation request + upload_url_location: Where to find URL ('headers' or 'body') + upload_url_key: Key name for URL in response body (default: 'upload_url') + + Returns: + Tuple of (upload_url, response_data) + - upload_url: The extracted upload URL, or None if not found + - response_data: Parsed response body (for 'body' location), or None + """ + if upload_url_location == "headers": + # Google Cloud Storage style - URL in X-Goog-Upload-URL header + upload_url = response.headers.get("X-Goog-Upload-URL") + return upload_url, None + else: + # Response body style (e.g., Manus, S3 presigned URLs) + try: + response_data = response.json() + upload_url = response_data.get(upload_url_key) + return upload_url, response_data if upload_url else None + except Exception: + return None, None + def create_file( self, create_file_data: CreateFileRequest, @@ -2844,14 +2879,58 @@ class BaseLLMHTTPHandler: else: sync_httpx_client = client - if isinstance(transformed_request, dict) and "method" in transformed_request: + if isinstance(transformed_request, dict) and "initial_request" in transformed_request: + # Handle two-step uploads (TwoStepFileUploadConfig) + # Used by providers like Manus, Google Cloud Storage + try: + # Step 1: Initial request to get upload URL + initial_response = sync_httpx_client.post( + url=api_base, + headers={ + **headers, + **transformed_request["initial_request"]["headers"], + }, + data=json.dumps(transformed_request["initial_request"]["data"]), + timeout=timeout, + ) + + # Extract upload URL from response + upload_url, initial_response_data = self._extract_upload_url_from_response( + response=initial_response, + upload_url_location=transformed_request.get("upload_url_location", "headers"), + upload_url_key=transformed_request.get("upload_url_key", "upload_url"), + ) + + if not upload_url: + raise ValueError("Failed to get upload URL from initial request") + + # Step 2: Upload the actual file + upload_method = transformed_request["upload_request"].get("method", "POST").lower() + upload_response = getattr(sync_httpx_client, upload_method)( + url=upload_url, + headers=transformed_request["upload_request"]["headers"], + data=transformed_request["upload_request"]["data"], + timeout=timeout, + ) + + # Store initial response for transformation + if initial_response_data: + litellm_params["initial_file_response"] = initial_response_data + except Exception as e: + raise self._handle_error( + e=e, + provider_config=provider_config, + ) + elif isinstance(transformed_request, dict) and "method" in transformed_request and "initial_request" not in transformed_request: # Handle pre-signed requests (e.g., from Bedrock S3 uploads) + # Type narrowing: this is a plain dict, not TwoStepFileUploadConfig + presigned_request = cast(Dict[str, Any], transformed_request) upload_response = getattr( - sync_httpx_client, transformed_request["method"].lower() + sync_httpx_client, presigned_request["method"].lower() )( - url=transformed_request["url"], - headers=transformed_request["headers"], - data=transformed_request["data"], + url=presigned_request["url"], + headers=presigned_request["headers"], + data=presigned_request["data"], timeout=timeout, ) elif isinstance(transformed_request, str) or isinstance( @@ -2879,36 +2958,7 @@ class BaseLLMHTTPHandler: timeout=timeout, ) else: - try: - # Step 1: Initial request to get upload URL - initial_response = sync_httpx_client.post( - url=api_base, - headers={ - **headers, - **transformed_request["initial_request"]["headers"], - }, - data=json.dumps(transformed_request["initial_request"]["data"]), - timeout=timeout, - ) - - # Extract upload URL from response headers - upload_url = initial_response.headers.get("X-Goog-Upload-URL") - - if not upload_url: - raise ValueError("Failed to get upload URL from initial request") - - # Step 2: Upload the actual file - upload_response = sync_httpx_client.post( - url=upload_url, - headers=transformed_request["upload_request"]["headers"], - data=transformed_request["upload_request"]["data"], - timeout=timeout, - ) - except Exception as e: - raise self._handle_error( - e=e, - provider_config=provider_config, - ) + raise ValueError(f"Unsupported transformed_request type: {type(transformed_request)}") # Store the upload URL in litellm_params for the transformation method litellm_params_with_url = dict(litellm_params) @@ -2923,7 +2973,7 @@ class BaseLLMHTTPHandler: async def async_create_file( self, - transformed_request: Union[bytes, str, dict], + transformed_request: Union[bytes, str, dict, "TwoStepFileUploadConfig"], litellm_params: dict, provider_config: BaseFilesConfig, headers: dict, @@ -2955,14 +3005,59 @@ class BaseLLMHTTPHandler: }, ) - if isinstance(transformed_request, dict) and "method" in transformed_request: + if isinstance(transformed_request, dict) and "initial_request" in transformed_request: + # Handle two-step uploads (TwoStepFileUploadConfig) + # Used by providers like Manus, Google Cloud Storage + try: + # Step 1: Initial request to get upload URL + initial_response = await async_httpx_client.post( + url=api_base, + headers={ + **headers, + **transformed_request["initial_request"]["headers"], + }, + data=json.dumps(transformed_request["initial_request"]["data"]), + timeout=timeout, + ) + + # Extract upload URL from response + upload_url, initial_response_data = self._extract_upload_url_from_response( + response=initial_response, + upload_url_location=transformed_request.get("upload_url_location", "headers"), + upload_url_key=transformed_request.get("upload_url_key", "upload_url"), + ) + + if not upload_url: + raise ValueError("Failed to get upload URL from initial request") + + # Step 2: Upload the actual file + upload_method = transformed_request["upload_request"].get("method", "POST").lower() + upload_response = await getattr(async_httpx_client, upload_method)( + url=upload_url, + headers=transformed_request["upload_request"]["headers"], + data=transformed_request["upload_request"]["data"], + timeout=timeout, + ) + + # Store initial response for transformation + if initial_response_data: + litellm_params["initial_file_response"] = initial_response_data + except Exception as e: + verbose_logger.exception(f"Error creating file: {e}") + raise self._handle_error( + e=e, + provider_config=provider_config, + ) + elif isinstance(transformed_request, dict) and "method" in transformed_request and "initial_request" not in transformed_request: # Handle pre-signed requests (e.g., from Bedrock S3 uploads) + # Type narrowing: this is a plain dict, not TwoStepFileUploadConfig + presigned_request = cast(Dict[str, Any], transformed_request) upload_response = await getattr( - async_httpx_client, transformed_request["method"].lower() + async_httpx_client, presigned_request["method"].lower() )( - url=transformed_request["url"], - headers=transformed_request["headers"], - data=transformed_request["data"], + url=presigned_request["url"], + headers=presigned_request["headers"], + data=presigned_request["data"], timeout=timeout, ) elif isinstance(transformed_request, str) or isinstance( @@ -2990,37 +3085,7 @@ class BaseLLMHTTPHandler: timeout=timeout, ) else: - try: - # Step 1: Initial request to get upload URL - initial_response = await async_httpx_client.post( - url=api_base, - headers={ - **headers, - **transformed_request["initial_request"]["headers"], - }, - data=json.dumps(transformed_request["initial_request"]["data"]), - timeout=timeout, - ) - - # Extract upload URL from response headers - upload_url = initial_response.headers.get("X-Goog-Upload-URL") - - if not upload_url: - raise ValueError("Failed to get upload URL from initial request") - - # Step 2: Upload the actual file - upload_response = await async_httpx_client.post( - url=upload_url, - headers=transformed_request["upload_request"]["headers"], - data=transformed_request["upload_request"]["data"], - timeout=timeout, - ) - except Exception as e: - verbose_logger.exception(f"Error creating file: {e}") - raise self._handle_error( - e=e, - provider_config=provider_config, - ) + raise ValueError(f"Unsupported transformed_request type: {type(transformed_request)}") return provider_config.transform_create_file_response( model=None, @@ -3734,29 +3799,525 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, ) - def list_files(self): + def retrieve_file( + self, + file_id: str, + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + _is_async: bool = False, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> Union[OpenAIFileObject, Coroutine[Any, Any, OpenAIFileObject]]: """ - Lists all files + Retrieve file metadata by ID """ - pass + if _is_async: + return self.async_retrieve_file( + file_id=file_id, + provider_config=provider_config, + litellm_params=litellm_params, + headers=headers, + logging_obj=logging_obj, + client=client, + timeout=timeout, + ) - def delete_file(self): - """ - Deletes a file - """ - pass + if client is None or not isinstance(client, HTTPHandler): + sync_httpx_client = _get_httpx_client() + else: + sync_httpx_client = client - def retrieve_file(self): - """ - Returns the metadata of the file - """ - pass + # Get URL and params from provider config + url, params = provider_config.transform_retrieve_file_request( + file_id=file_id, + optional_params={}, + litellm_params=litellm_params, + ) - def retrieve_file_content(self): + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_id, + }, + ) + + try: + response = sync_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_retrieve_file_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + async def async_retrieve_file( + self, + file_id: str, + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> OpenAIFileObject: """ - Returns the content of the file + Async retrieve file metadata by ID """ - pass + if client is None or not isinstance(client, AsyncHTTPHandler): + async_httpx_client = get_async_httpx_client( + llm_provider=provider_config.custom_llm_provider + ) + else: + async_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_retrieve_file_request( + file_id=file_id, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_id, + }, + ) + + try: + response = await async_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_retrieve_file_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + def delete_file( + self, + file_id: str, + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + _is_async: bool = False, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> Union["FileDeleted", Coroutine[Any, Any, "FileDeleted"]]: + """ + Delete a file by ID + """ + if _is_async: + return self.async_delete_file( + file_id=file_id, + provider_config=provider_config, + litellm_params=litellm_params, + headers=headers, + logging_obj=logging_obj, + client=client, + timeout=timeout, + ) + + if client is None or not isinstance(client, HTTPHandler): + sync_httpx_client = _get_httpx_client() + else: + sync_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_delete_file_request( + file_id=file_id, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_id, + }, + ) + + try: + response = sync_httpx_client.delete( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_delete_file_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + async def async_delete_file( + self, + file_id: str, + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> "FileDeleted": + """ + Async delete a file by ID + """ + if client is None or not isinstance(client, AsyncHTTPHandler): + async_httpx_client = get_async_httpx_client( + llm_provider=provider_config.custom_llm_provider + ) + else: + async_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_delete_file_request( + file_id=file_id, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_id, + }, + ) + + try: + response = await async_httpx_client.delete( + url=url, headers=headers, params=params, timeout=timeout + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_delete_file_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + def list_files( + self, + purpose: Optional[str], + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + _is_async: bool = False, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> Union[List[OpenAIFileObject], Coroutine[Any, Any, List[OpenAIFileObject]]]: + """ + List all files + """ + if _is_async: + return self.async_list_files( + purpose=purpose, + provider_config=provider_config, + litellm_params=litellm_params, + headers=headers, + logging_obj=logging_obj, + client=client, + timeout=timeout, + ) + + if client is None or not isinstance(client, HTTPHandler): + sync_httpx_client = _get_httpx_client() + else: + sync_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_list_files_request( + purpose=purpose, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "purpose": purpose, + }, + ) + + try: + response = sync_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_list_files_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + async def async_list_files( + self, + purpose: Optional[str], + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> List[OpenAIFileObject]: + """ + Async list all files + """ + if client is None or not isinstance(client, AsyncHTTPHandler): + async_httpx_client = get_async_httpx_client( + llm_provider=provider_config.custom_llm_provider + ) + else: + async_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_list_files_request( + purpose=purpose, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "purpose": purpose, + }, + ) + + try: + response = await async_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_list_files_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + def retrieve_file_content( + self, + file_content_request: "FileContentRequest", + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + _is_async: bool = False, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> Union["HttpxBinaryResponseContent", Coroutine[Any, Any, "HttpxBinaryResponseContent"]]: + """ + Retrieve file content by ID + """ + if _is_async: + return self.async_retrieve_file_content( + file_content_request=file_content_request, + provider_config=provider_config, + litellm_params=litellm_params, + headers=headers, + logging_obj=logging_obj, + client=client, + timeout=timeout, + ) + + if client is None or not isinstance(client, HTTPHandler): + sync_httpx_client = _get_httpx_client() + else: + sync_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_file_content_request( + file_content_request=file_content_request, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_content_request.get("file_id"), + }, + ) + + try: + response = sync_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_file_content_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + async def async_retrieve_file_content( + self, + file_content_request: "FileContentRequest", + provider_config: BaseFilesConfig, + litellm_params: dict, + headers: dict, + logging_obj: LiteLLMLoggingObj, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, + timeout: Optional[Union[float, httpx.Timeout]] = None, + ) -> "HttpxBinaryResponseContent": + """ + Async retrieve file content by ID + """ + if client is None or not isinstance(client, AsyncHTTPHandler): + async_httpx_client = get_async_httpx_client( + llm_provider=provider_config.custom_llm_provider + ) + else: + async_httpx_client = client + + # Get URL and params from provider config + url, params = provider_config.transform_file_content_request( + file_content_request=file_content_request, + optional_params={}, + litellm_params=litellm_params, + ) + + # Validate environment and get headers + headers = provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, + litellm_params=litellm_params, + ) + + logging_obj.pre_call( + input="", + api_key="", + additional_args={ + "api_base": url, + "headers": headers, + "file_id": file_content_request.get("file_id"), + }, + ) + + try: + response = await async_httpx_client.get( + url=url, headers=headers, params=params + ) + except Exception as e: + raise self._handle_error(e=e, provider_config=provider_config) + + return provider_config.transform_file_content_response( + raw_response=response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) def _prepare_fake_stream_request( self, diff --git a/litellm/llms/gemini/files/transformation.py b/litellm/llms/gemini/files/transformation.py index e98e76dabc8..d9ebf69a97a 100644 --- a/litellm/llms/gemini/files/transformation.py +++ b/litellm/llms/gemini/files/transformation.py @@ -7,6 +7,7 @@ import time from typing import List, Optional import httpx +from openai.types.file_deleted import FileDeleted from litellm._logging import verbose_logger from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data @@ -17,6 +18,7 @@ from litellm.llms.base_llm.files.transformation import ( from litellm.types.llms.gemini import GeminiCreateFilesResponseObject from litellm.types.llms.openai import ( CreateFileRequest, + HttpxBinaryResponseContent, OpenAICreateFileRequestOptionalParams, OpenAIFileObject, ) @@ -171,3 +173,67 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig): except Exception as e: verbose_logger.exception(f"Error parsing file upload response: {str(e)}") raise ValueError(f"Error parsing file upload response: {str(e)}") + + def transform_retrieve_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file retrieval") + + def transform_retrieve_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file retrieval") + + def transform_delete_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file deletion") + + def transform_delete_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> FileDeleted: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file deletion") + + def transform_list_files_request( + self, + purpose: Optional[str], + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file listing") + + def transform_list_files_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> List[OpenAIFileObject]: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file listing") + + def transform_file_content_request( + self, + file_content_request, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file content retrieval") + + def transform_file_content_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> HttpxBinaryResponseContent: + raise NotImplementedError("GoogleAIStudioFilesHandler does not support file content retrieval") diff --git a/litellm/llms/manus/files/__init__.py b/litellm/llms/manus/files/__init__.py new file mode 100644 index 00000000000..66d23ca0340 --- /dev/null +++ b/litellm/llms/manus/files/__init__.py @@ -0,0 +1,2 @@ +# Manus Files API implementation + diff --git a/litellm/llms/manus/files/transformation.py b/litellm/llms/manus/files/transformation.py new file mode 100644 index 00000000000..a7965011969 --- /dev/null +++ b/litellm/llms/manus/files/transformation.py @@ -0,0 +1,439 @@ +""" +Manus Files API implementation. + +Manus has an OpenAI-compatible Files API with some differences: +- Uses API_KEY header instead of Authorization: Bearer +- File upload is a two-step process: + 1. Create file record to get upload URL + 2. Upload file content to the upload URL + +Reference: https://open.manus.im/docs/openai-compatibility#file-management +""" + +import time +from typing import Any, Dict, List, Optional, Union + +import httpx +from openai.types.file_deleted import FileDeleted + +import litellm +from litellm._logging import verbose_logger +from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.base_llm.files.transformation import ( + BaseFilesConfig, + LiteLLMLoggingObj, +) +from litellm.llms.openai.common_utils import OpenAIError +from litellm.secret_managers.main import get_secret_str +from litellm.types.files import TwoStepFileUploadConfig, TwoStepFileUploadRequest +from litellm.types.llms.openai import ( + CreateFileRequest, + FileContentRequest, + HttpxBinaryResponseContent, + OpenAICreateFileRequestOptionalParams, + OpenAIFileObject, +) +from litellm.types.utils import LlmProviders + +MANUS_API_BASE = "https://api.manus.im" + + +class ManusFilesConfig(BaseFilesConfig): + """ + Configuration for Manus Files API. + + Manus uses: + - API_KEY header for authentication (not Authorization: Bearer) + - Two-step file upload process + - Content-Type: application/json for all requests + + Reference: https://open.manus.im/docs/openai-compatibility#file-management + """ + + def __init__(self): + pass + + @property + def custom_llm_provider(self) -> LlmProviders: + return LlmProviders.MANUS + + def validate_environment( + self, + headers: dict, + model: str, + messages: list, + optional_params: dict, + litellm_params: dict, + api_key: Optional[str] = None, + api_base: Optional[str] = None, + ) -> dict: + """ + Validate environment and set up headers for Manus API. + + Manus uses API_KEY header instead of Authorization: Bearer. + For file uploads, don't set Content-Type - httpx will set it for multipart. + """ + api_key = ( + api_key + or litellm.api_key + or get_secret_str("MANUS_API_KEY") + ) + + if not api_key: + raise ValueError( + "Manus API key is required. Set MANUS_API_KEY environment variable or pass api_key parameter." + ) + + # Manus uses API_KEY header, not Authorization: Bearer + # Manus requires Content-Type: application/json for all requests (even GET) + headers.update( + { + "API_KEY": api_key, + "Content-Type": "application/json", + } + ) + return headers + + def get_supported_openai_params( + self, model: str + ) -> List[OpenAICreateFileRequestOptionalParams]: + """ + Return supported OpenAI file creation parameters for Manus. + Manus supports the standard 'purpose' parameter. + """ + return ["purpose"] + + def map_openai_params( + self, + non_default_params: dict, + optional_params: dict, + model: str, + drop_params: bool, + ) -> dict: + """ + Map OpenAI parameters to Manus-specific parameters. + Manus is OpenAI-compatible, so no special mapping needed. + """ + return optional_params + + 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: + """ + Get the complete URL for Manus Files API endpoint. + + Returns: + str: The full URL for the Manus /v1/files endpoint + """ + api_base = ( + api_base + or litellm.api_base + or get_secret_str("MANUS_API_BASE") + or MANUS_API_BASE + ) + + # Remove trailing slashes + api_base = api_base.rstrip("/") + + # Manus API uses /v1/files endpoint + if api_base.endswith("/v1"): + return f"{api_base}/files" + return f"{api_base}/v1/files" + + def get_error_class( + self, + error_message: str, + status_code: int, + headers: Union[dict, httpx.Headers], + ) -> BaseLLMException: + """ + Return the appropriate error class for Manus API errors. + Uses OpenAIError since Manus is OpenAI-compatible. + """ + return OpenAIError( + status_code=status_code, + message=error_message, + headers=headers, + ) + + def transform_create_file_request( + self, + model: str, + create_file_data: CreateFileRequest, + optional_params: dict, + litellm_params: dict, + ) -> TwoStepFileUploadConfig: + """ + Transform OpenAI-style file creation request into Manus's two-step format. + + Manus API spec (https://open.manus.im/docs/openai-compatibility#file-management): + 1. POST /v1/files with JSON {"filename": "..."} → returns {"id": "...", "upload_url": "..."} + 2. PUT to upload_url with raw file content + """ + # Extract file data + file_data = create_file_data.get("file") + if file_data is None: + raise ValueError("File data is required") + + extracted_data = extract_file_data(file_data) + filename = extracted_data["filename"] or f"file_{int(time.time())}" + content = extracted_data["content"] + + # Get API base URL + api_base = self.get_complete_url( + api_base=litellm_params.get("api_base"), + api_key=litellm_params.get("api_key"), + model=model, + optional_params=optional_params, + litellm_params=litellm_params, + ) + + # Get API key + api_key = ( + litellm_params.get("api_key") + or litellm.api_key + or get_secret_str("MANUS_API_KEY") + ) + + if not api_key: + raise ValueError( + "Manus API key is required. Set MANUS_API_KEY environment variable or pass api_key parameter." + ) + + # Build typed two-step upload config + return TwoStepFileUploadConfig( + initial_request=TwoStepFileUploadRequest( + method="POST", + url=api_base, + headers={ + "API_KEY": api_key, + "Content-Type": "application/json", + }, + data={"filename": filename}, + ), + upload_request=TwoStepFileUploadRequest( + method="PUT", + url="", # Will be populated from initial_request response + headers={}, + data=content, + ), + upload_url_location="body", + upload_url_key="upload_url", + ) + + def transform_create_file_response( + self, + model: Optional[str], + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + """ + Transform Manus's file upload response into OpenAI-style FileObject. + + For two-step uploads, the handler stores the initial response in litellm_params. + We need to return the file object from the initial POST, not the final PUT. + + Manus initial response format: + { + "id": "file-abc123xyz", + "object": "file", + "filename": "document.pdf", + "status": "pending", + "upload_url": "https://...", + "upload_expires_at": "...", + "created_at": "..." + } + """ + try: + # For two-step uploads, get the initial response from litellm_params + initial_response_data = litellm_params.get("initial_file_response") + if initial_response_data: + response_json = initial_response_data + else: + # Log raw response for debugging + verbose_logger.debug(f"Manus raw response text: {raw_response.text}") + response_json = raw_response.json() + + verbose_logger.debug(f"Manus file response: {response_json}") + + # Parse created_at timestamp + created_at_str = response_json.get("created_at", "") + if created_at_str: + try: + # Try parsing ISO format + created_at = int( + time.mktime( + time.strptime( + created_at_str.replace("Z", "+00:00")[:19], + "%Y-%m-%dT%H:%M:%S", + ) + ) + ) + except (ValueError, TypeError): + created_at = int(time.time()) + else: + created_at = int(time.time()) + + return OpenAIFileObject( + id=response_json.get("id", ""), + bytes=response_json.get("bytes", 0), + created_at=created_at, + filename=response_json.get("filename", ""), + object="file", + purpose=response_json.get("purpose", "assistants"), + status="uploaded", # After successful upload, status is uploaded + status_details=response_json.get("status_details"), + ) + except Exception as e: + verbose_logger.exception(f"Error parsing Manus file response: {str(e)}") + raise ValueError(f"Error parsing Manus file response: {str(e)}") + + def transform_retrieve_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Get URL and params for retrieving a file.""" + api_base = self.get_complete_url( + api_base=litellm_params.get("api_base"), + api_key=litellm_params.get("api_key"), + model="", + optional_params=optional_params, + litellm_params=litellm_params, + ) + return f"{api_base}/{file_id}", {} + + def transform_retrieve_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + """Transform retrieve file response.""" + return self.transform_create_file_response( + model=None, + raw_response=raw_response, + logging_obj=logging_obj, + litellm_params=litellm_params, + ) + + def transform_delete_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Get URL and params for deleting a file.""" + api_base = self.get_complete_url( + api_base=litellm_params.get("api_base"), + api_key=litellm_params.get("api_key"), + model="", + optional_params=optional_params, + litellm_params=litellm_params, + ) + return f"{api_base}/{file_id}", {} + + def transform_delete_file_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> FileDeleted: + """Transform delete file response.""" + response_json = raw_response.json() + return FileDeleted(**response_json) + + def transform_list_files_request( + self, + purpose: Optional[str], + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Get URL and params for listing files.""" + api_base = self.get_complete_url( + api_base=litellm_params.get("api_base"), + api_key=litellm_params.get("api_key"), + model="", + optional_params=optional_params, + litellm_params=litellm_params, + ) + params = {} + if purpose: + params["purpose"] = purpose + return api_base, params + + def transform_list_files_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> List[OpenAIFileObject]: + """Transform list files response.""" + response_json = raw_response.json() + files_data = response_json.get("data", []) + return [self._parse_file_dict(f) for f in files_data] + + def _parse_file_dict(self, file_dict: Dict[str, Any]) -> OpenAIFileObject: + """Parse a file dict into OpenAIFileObject.""" + created_at_str = file_dict.get("created_at", "") + if created_at_str: + try: + created_at = int( + time.mktime( + time.strptime( + created_at_str.replace("Z", "+00:00")[:19], + "%Y-%m-%dT%H:%M:%S", + ) + ) + ) + except (ValueError, TypeError): + created_at = int(time.time()) + else: + created_at = int(time.time()) + + return OpenAIFileObject( + id=file_dict.get("id", ""), + bytes=file_dict.get("bytes", 0), + created_at=created_at, + filename=file_dict.get("filename", ""), + object="file", + purpose=file_dict.get("purpose", "assistants"), + status=file_dict.get("status", "uploaded"), + status_details=file_dict.get("status_details"), + ) + + def transform_file_content_request( + self, + file_content_request: FileContentRequest, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + """Get URL and params for retrieving file content.""" + file_id = file_content_request.get("file_id") + api_base = self.get_complete_url( + api_base=litellm_params.get("api_base"), + api_key=litellm_params.get("api_key"), + model="", + optional_params=optional_params, + litellm_params=litellm_params, + ) + return f"{api_base}/{file_id}/content", {} + + def transform_file_content_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> HttpxBinaryResponseContent: + """Transform file content response.""" + return HttpxBinaryResponseContent(response=raw_response) + diff --git a/litellm/llms/vertex_ai/files/transformation.py b/litellm/llms/vertex_ai/files/transformation.py index 01f6c86fd4d..b3612113ec2 100644 --- a/litellm/llms/vertex_ai/files/transformation.py +++ b/litellm/llms/vertex_ai/files/transformation.py @@ -1,11 +1,12 @@ import json import os import time -from litellm._uuid import uuid from typing import Any, Dict, List, Optional, Tuple, Union from httpx import Headers, Response +from openai.types.file_deleted import FileDeleted +from litellm._uuid import uuid from litellm.files.utils import FilesAPIUtils from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data from litellm.llms.base_llm.chat.transformation import BaseLLMException @@ -24,6 +25,7 @@ from litellm.types.llms.openai import ( AllMessageValues, CreateFileRequest, FileTypes, + HttpxBinaryResponseContent, OpenAICreateFileRequestOptionalParams, OpenAIFileObject, PathLike, @@ -333,6 +335,70 @@ class VertexAIFilesConfig(VertexBase, BaseFilesConfig): status_code=status_code, message=error_message, headers=headers ) + def transform_retrieve_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("VertexAIFilesConfig does not support file retrieval") + + def transform_retrieve_file_response( + self, + raw_response: Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> OpenAIFileObject: + raise NotImplementedError("VertexAIFilesConfig does not support file retrieval") + + def transform_delete_file_request( + self, + file_id: str, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("VertexAIFilesConfig does not support file deletion") + + def transform_delete_file_response( + self, + raw_response: Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> FileDeleted: + raise NotImplementedError("VertexAIFilesConfig does not support file deletion") + + def transform_list_files_request( + self, + purpose: Optional[str], + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("VertexAIFilesConfig does not support file listing") + + def transform_list_files_response( + self, + raw_response: Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> List[OpenAIFileObject]: + raise NotImplementedError("VertexAIFilesConfig does not support file listing") + + def transform_file_content_request( + self, + file_content_request, + optional_params: dict, + litellm_params: dict, + ) -> tuple[str, dict]: + raise NotImplementedError("VertexAIFilesConfig does not support file content retrieval") + + def transform_file_content_response( + self, + raw_response: Response, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, + ) -> HttpxBinaryResponseContent: + raise NotImplementedError("VertexAIFilesConfig does not support file content retrieval") + class VertexAIJsonlFilesTransformation(VertexGeminiConfig): """ diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index 7667d1bad84..49b8e123fe2 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -198,11 +198,14 @@ class ResponsesAPIRequestUtils: model_id = model_info.get("id") # access the response id based on the object type - response_id = ( - responses_api_response["id"] - if isinstance(responses_api_response, dict) - else responses_api_response.id - ) + if isinstance(responses_api_response, dict): + response_id = responses_api_response.get("id") + else: + response_id = getattr(responses_api_response, "id", None) + + # If no response_id, return the response as-is (likely an error response) + if response_id is None: + return responses_api_response updated_id = ResponsesAPIRequestUtils._build_responses_api_response_id( model_id=model_id, diff --git a/litellm/types/files.py b/litellm/types/files.py index 600ad806e22..8b87b33cd1b 100644 --- a/litellm/types/files.py +++ b/litellm/types/files.py @@ -1,6 +1,8 @@ from enum import Enum from types import MappingProxyType -from typing import List, Set, Mapping +from typing import Any, Dict, List, Literal, Mapping, Set, Union + +from typing_extensions import Required, TypedDict """ Base Enums/Consts @@ -281,3 +283,41 @@ GEMINI_1_5_ACCEPTED_FILE_TYPES: Set[FileType] = { def is_gemini_1_5_accepted_file_type(file_type: FileType) -> bool: return file_type in GEMINI_1_5_ACCEPTED_FILE_TYPES + + +""" +Two-Step File Upload Types +""" + + +class TwoStepFileUploadRequest(TypedDict): + """ + Request structure for two-step file upload process. + + Step 1: Initial request to get upload URL + Step 2: Upload file content to the upload URL + + Used by providers like Manus and Google Cloud Storage. + """ + + method: Required[str] + url: Required[str] + headers: Required[Dict[str, str]] + data: Required[Union[str, bytes, Dict[str, Any]]] + + +class TwoStepFileUploadConfig(TypedDict, total=False): + """ + Configuration for two-step file upload process. + + Properties: + initial_request: Request to create file record and get upload URL + upload_request: Request to upload actual file content + upload_url_location: Where to find upload URL ('headers' or 'body') + upload_url_key: Key name for upload URL in response (default: 'upload_url') + """ + + initial_request: Required[TwoStepFileUploadRequest] + upload_request: Required[TwoStepFileUploadRequest] + upload_url_location: Required[Literal["headers", "body"]] + upload_url_key: str diff --git a/litellm/utils.py b/litellm/utils.py index 42d4a1ac372..1393f1f5cb5 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -48,6 +48,7 @@ from tokenizers import Tokenizer import litellm import litellm.litellm_core_utils + # audio_utils.utils is lazy-loaded - only imported when needed for transcription calls import litellm.litellm_core_utils.json_validation_rule from litellm._lazy_imports import ( @@ -71,8 +72,6 @@ from litellm.constants import ( TOOL_CHOICE_OBJECT_TOKEN_COUNT, ) - - _CachingHandlerResponse = None _LLMCachingHandler = None _CustomGuardrail = None @@ -7959,6 +7958,10 @@ class ProviderConfigManager: from litellm.llms.bedrock.files.transformation import BedrockFilesConfig return BedrockFilesConfig() + elif LlmProviders.MANUS == provider: + from litellm.llms.manus.files.transformation import ManusFilesConfig + + return ManusFilesConfig() return None @staticmethod diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 8432ce4e874..db11ec8a0de 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -2335,6 +2335,7 @@ "audio_speech": false, "moderations": false, "batches": false, + "files": true, "rerank": false, "a2a": true, "interactions": true diff --git a/tests/batches_tests/test_manus_files_all_methods.py b/tests/batches_tests/test_manus_files_all_methods.py new file mode 100644 index 00000000000..49322bdcb17 --- /dev/null +++ b/tests/batches_tests/test_manus_files_all_methods.py @@ -0,0 +1,72 @@ +""" +E2E test for all Manus Files API methods. +""" + +import os +import pytest +import litellm + + +@pytest.mark.asyncio +async def test_manus_files_api_e2e_all_methods(): + """ + E2E test for Manus Files API: create, retrieve, list, delete. + """ + litellm._turn_on_debug() + + api_key = os.getenv("MANUS_API_KEY") + if api_key is None: + pytest.skip("MANUS_API_KEY not set") + + # Create a simple test file content + test_content = b"This is a test file for Manus Files API - all methods test." + test_filename = "test_file_all_methods.txt" + + # Step 1: Create file + print("Step 1: Creating file...") + created_file = await litellm.acreate_file( + file=(test_filename, test_content), + purpose="assistants", + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Created file: {created_file}") + assert created_file.filename == test_filename + assert created_file.status == "uploaded" + # Note: Manus doesn't return bytes in initial response + file_id = created_file.id + + # Step 2: Retrieve file + print(f"\nStep 2: Retrieving file {file_id}...") + retrieved_file = await litellm.afile_retrieve( + file_id=file_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Retrieved file: {retrieved_file}") + assert retrieved_file.id == file_id + assert retrieved_file.filename == test_filename + + # Step 3: List files + print("\nStep 3: Listing files...") + files_list = await litellm.afile_list( + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Files list: {files_list}") + assert isinstance(files_list, list) + assert any(f.id == file_id for f in files_list) + + # Step 4: Delete file + print(f"\nStep 4: Deleting file {file_id}...") + deleted_file = await litellm.afile_delete( + file_id=file_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Deleted file: {deleted_file}") + assert deleted_file.id == file_id + assert deleted_file.deleted is True + + print("\n✅ All Manus Files API methods working!") + diff --git a/tests/llm_responses_api_testing/test_manus_files_all_methods.py b/tests/llm_responses_api_testing/test_manus_files_all_methods.py new file mode 100644 index 00000000000..39311441f59 --- /dev/null +++ b/tests/llm_responses_api_testing/test_manus_files_all_methods.py @@ -0,0 +1,71 @@ +""" +E2E test for all Manus Files API methods. +""" + +import os +import pytest +import litellm + + +@pytest.mark.asyncio +async def test_manus_files_api_e2e_all_methods(): + """ + E2E test for Manus Files API: create, retrieve, list, delete. + """ + litellm._turn_on_debug() + + api_key = os.getenv("MANUS_API_KEY") + if api_key is None: + pytest.skip("MANUS_API_KEY not set") + + # Create a simple test file content + test_content = b"This is a test file for Manus Files API - all methods test." + test_filename = "test_file_all_methods.txt" + + # Step 1: Create file + print("Step 1: Creating file...") + created_file = await litellm.acreate_file( + file=(test_filename, test_content), + purpose="assistants", + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Created file: {created_file}") + assert created_file.filename == test_filename + assert created_file.status == "uploaded" + # Note: Manus doesn't return bytes in initial response + file_id = created_file.id + + # Step 2: Retrieve file + print(f"\nStep 2: Retrieving file {file_id}...") + retrieved_file = await litellm.afile_retrieve( + file_id=file_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Retrieved file: {retrieved_file}") + assert retrieved_file.id == file_id + assert retrieved_file.filename == test_filename + + # Step 3: List files + print("\nStep 3: Listing files...") + files_list = await litellm.afile_list( + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Files list: {files_list}") + assert isinstance(files_list, list) + assert any(f.id == file_id for f in files_list) + + # Step 4: Delete file + print(f"\nStep 4: Deleting file {file_id}...") + deleted_file = await litellm.afile_delete( + file_id=file_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Deleted file: {deleted_file}") + assert deleted_file.id == file_id + assert deleted_file.deleted is True + + print("\n✅ All Manus Files API methods working!") diff --git a/tests/llm_responses_api_testing/test_manus_responses_api.py b/tests/llm_responses_api_testing/test_manus_responses_api.py index 4f64980d261..6256363f407 100644 --- a/tests/llm_responses_api_testing/test_manus_responses_api.py +++ b/tests/llm_responses_api_testing/test_manus_responses_api.py @@ -38,7 +38,11 @@ async def test_manus_responses_api_with_agent_profile(): print("Manus response=", json.dumps(response, indent=4, default=str)) ## Get the status of the response - got_response = await litellm.aget_responses(response_id=response.id) + got_response = await litellm.aget_responses( + response_id=response.id, + custom_llm_provider="manus", + api_key=os.getenv("MANUS_API_KEY"), + ) print("GET API MANUS RESPONSE=", json.dumps(got_response, indent=4, default=str)) if got_response.status == "completed": assert got_response.output is not None @@ -47,6 +51,95 @@ async def test_manus_responses_api_with_agent_profile(): # Manus can return "running" or "pending" status assert got_response.status in ["running", "pending"] assert got_response.id is not None + + +@pytest.mark.asyncio +async def test_manus_responses_api_with_file_upload(): + """ + Test that uploads a file via Files API and then passes it to Responses API. + """ + litellm._turn_on_debug() + + api_key = os.getenv("MANUS_API_KEY") + if api_key is None: + pytest.skip("MANUS_API_KEY not set") + + # Step 1: Upload a file + test_content = b"Warren Buffett's 2023 Letter to Shareholders\n\nKey Points:\n1. Long-term value creation\n2. Capital allocation strategy\n3. Market volatility perspective" + test_filename = "buffett_letter_summary.txt" + + print("Step 1: Uploading file...") + uploaded_file = await litellm.acreate_file( + file=(test_filename, test_content), + purpose="assistants", + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Uploaded file: {uploaded_file}") + assert uploaded_file.id is not None + file_id = uploaded_file.id + + # Step 2: Create a response with the uploaded file + print(f"\nStep 2: Creating response with file {file_id}...") + response = await litellm.aresponses( + model="manus/manus-1.6-lite", + input=[ + { + "role": "user", + "content": [ + { + "type": "input_text", + "text": "Summarize the key points from this letter.", + }, + { + "type": "input_file", + "file_id": file_id, + }, + ], + }, + ], + api_key=api_key, + max_output_tokens=100, + ) + + print(f"Response created: {response}") + print(f"Response type: {type(response)}") + print(f"Response has id: {hasattr(response, 'id')}") + + # Handle both dict and ResponsesAPIResponse object + if isinstance(response, dict): + response_id = response.get("id") + else: + response_id = getattr(response, "id", None) + + assert response_id is not None, f"Response ID is None. Response: {response}" + + # Step 3: Get the response status + print(f"\nStep 3: Getting response status...") + got_response = await litellm.aget_responses( + response_id=response_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Response status: {got_response}") + got_response_id = getattr(got_response, "id", None) + got_response_status = getattr(got_response, "status", None) + + assert got_response_id == response_id + assert got_response_status in ["completed", "running", "pending"] + + # Step 4: Clean up - delete the file + print(f"\nStep 4: Cleaning up - deleting file {file_id}...") + deleted_file = await litellm.afile_delete( + file_id=file_id, + custom_llm_provider="manus", + api_key=api_key, + ) + print(f"Deleted file: {deleted_file}") + assert deleted_file.deleted is True + + print("\n✅ File upload and responses API integration test passed!") + diff --git a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py index f5856cd12d6..45fb418e79a 100644 --- a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py +++ b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py @@ -14,15 +14,16 @@ from datetime import datetime, timedelta, timezone from typing import Any, Dict from unittest.mock import MagicMock, patch +from botocore.awsrequest import AWSPreparedRequest, AWSRequest from botocore.credentials import Credentials -from botocore.awsrequest import AWSRequest, AWSPreparedRequest + import litellm +from litellm.caching.caching import DualCache from litellm.llms.bedrock.base_aws_llm import ( AwsAuthError, BaseAWSLLM, Boto3CredentialsInfo, ) -from litellm.caching.caching import DualCache # Global variable for the base_aws_llm.py file path @@ -582,7 +583,7 @@ def test_eks_irsa_ambient_credentials_used(): ) # Should create STS client without explicit credentials (using ambient credentials) - mock_boto3_client.assert_called_once_with("sts") + mock_boto3_client.assert_called_once_with("sts", verify=True) # Should call assume_role mock_sts_client.assume_role.assert_called_once_with( @@ -642,6 +643,7 @@ def test_explicit_credentials_used_when_provided(): aws_access_key_id="explicit-access-key", aws_secret_access_key="explicit-secret-key", aws_session_token="assumed-session-token", + verify=True, ) # Should call assume_role @@ -701,6 +703,7 @@ def test_partial_credentials_still_use_ambient(): aws_access_key_id="AKIAEXAMPLE", aws_secret_access_key=None, aws_session_token=None, + verify=True, ) # Should still call assume_role @@ -748,7 +751,7 @@ def test_cross_account_role_assumption(): ) # Should use ambient credentials - mock_boto3_client.assert_called_once_with("sts") + mock_boto3_client.assert_called_once_with("sts", verify=True) # Should call assume_role with cross-account role mock_sts_client.assume_role.assert_called_once_with( From ff8e9aeb5c11e2c3560c6bec8ae97ce3fd5be633 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 13:39:49 -0800 Subject: [PATCH 043/114] Revert "Add support for Vertex AI API keys" This reverts commit ad501048f391ee473fe1fa2e6b69095a076f4630. --- docs/my-website/docs/providers/vertex.md | 45 +----- litellm/llms/gemini/common_utils.py | 9 -- litellm/llms/vertex_ai/vertex_llm_base.py | 40 ++--- litellm/main.py | 10 +- .../llms/vertex_ai/test_vertex_llm_base.py | 137 ------------------ 5 files changed, 15 insertions(+), 226 deletions(-) diff --git a/docs/my-website/docs/providers/vertex.md b/docs/my-website/docs/providers/vertex.md index f46608aa57c..33ebf535d29 100644 --- a/docs/my-website/docs/providers/vertex.md +++ b/docs/my-website/docs/providers/vertex.md @@ -35,8 +35,6 @@ import json # !gcloud auth application-default login - run this to add vertex credentials to your env ## OR ## file_path = 'path/to/vertex_ai_service_account.json' -## OR ## -export VERTEXAI_API_KEY="your-api-key" # Load the JSON file with open(file_path, 'r') as file: @@ -49,7 +47,7 @@ vertex_credentials_json = json.dumps(vertex_credentials) response = completion( model="vertex_ai/gemini-2.5-pro", messages=[{ "content": "Hello, how are you?","role": "user"}], - vertex_credentials=vertex_credentials_json # Can remove this is added VERTEXAI_API_KEY in env + vertex_credentials=vertex_credentials_json ) ``` @@ -1331,41 +1329,15 @@ Here's how to use Vertex AI with the LiteLLM Proxy Server ## Authentication - vertex_project, vertex_location, etc. -LiteLLM supports two authentication methods for Vertex AI: - -1. **API Key Authentication** (Recommended for getting started) -2. **Service Account Credentials** (Recommended for production) - Set your vertex credentials via: - dynamic params OR - env vars -### **Authentication Method 1: -The simplest way to authenticate with Vertex AI. You can set: -- `api_key` (str) - Your Vertex AI API key +### **Dynamic Params** -**Environment Variables:** -```bash -export VERTEXAI_API_KEY="your-api-key" -``` - -**Or pass as parameters:** -```python -from litellm import completion - -response = completion( - model="vertex_ai/gemini-2.0-flash-exp", - messages=[{"role": "user", "content": "Hello!"}], - api_key="your-vertex-api-key", - -) -``` - -### **Authentication Method 2: Service Account Credentials** - -For production environments with fine-grained access control. You can set: +You can set: - `vertex_credentials` (str) - can be a json string or filepath to your vertex ai service account.json - `vertex_location` (str) - place where vertex model is deployed (us-central1, asia-southeast1, etc.). Some models support the global location, please see [Vertex AI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/locations#supported_models) - `vertex_project` Optional[str] - use if vertex project different from the one in vertex_credentials @@ -1420,16 +1392,7 @@ model_list: ### **Environment Variables** -#### For API Key Authentication: - -- `VERTEXAI_API_KEY` or `VERTEX_API_KEY` - Your Vertex AI API key - -```bash -export VERTEXAI_API_KEY="your-vertex-api-key" -``` - -#### For Service Account Authentication: - +You can set: - `GOOGLE_APPLICATION_CREDENTIALS` - store the filepath for your service_account.json in here (used by vertex sdk directly). - VERTEXAI_LOCATION - place where vertex model is deployed (us-central1, asia-southeast1, etc.) - VERTEXAI_PROJECT - Optional[str] - use if vertex project different from the one in vertex_credentials diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py index 30c5b4f17c5..e53829d3329 100644 --- a/litellm/llms/gemini/common_utils.py +++ b/litellm/llms/gemini/common_utils.py @@ -150,15 +150,6 @@ def get_api_key_from_env() -> Optional[str]: return get_secret_str("GOOGLE_API_KEY") or get_secret_str("GEMINI_API_KEY") -def get_vertex_api_key_from_env() -> Optional[str]: - """ - Get API key from environment for Vertex AI. - Checks VERTEXAI_API_KEY and VERTEX_API_KEY environment variables. - This allows using Vertex AI with API keys instead of service account credentials. - """ - return get_secret_str("VERTEXAI_API_KEY") or get_secret_str("VERTEX_API_KEY") - - class GoogleAIStudioTokenCounter(BaseTokenCounter): """Token counter implementation for Google AI Studio provider.""" def should_use_token_counting_api( diff --git a/litellm/llms/vertex_ai/vertex_llm_base.py b/litellm/llms/vertex_ai/vertex_llm_base.py index a3606ff9deb..826f151df35 100644 --- a/litellm/llms/vertex_ai/vertex_llm_base.py +++ b/litellm/llms/vertex_ai/vertex_llm_base.py @@ -388,10 +388,6 @@ class VertexBase: Internal function. Returns the token and url for the call. Handles logic if it's google ai studio vs. vertex ai. - - For Vertex AI: - - If gemini_api_key is provided, use API key authentication (x-goog-api-key header) - - Otherwise, use service account credentials (OAuth2 Bearer token) Returns token, url @@ -404,7 +400,7 @@ class VertexBase: stream=stream, gemini_api_key=gemini_api_key, ) - auth_header = None # this field is not used for gemini + auth_header = None # this field is not used for gemin else: vertex_location = self.get_vertex_region( vertex_region=vertex_location, @@ -413,32 +409,14 @@ class VertexBase: ### SET RUNTIME ENDPOINT ### version = "v1beta1" if should_use_v1beta1_features is True else "v1" - - # Check if using API key authentication for Vertex AI - if gemini_api_key and not vertex_credentials: - # When using API key with Vertex AI, use the Google AI Studio endpoint - # This is because Vertex AI API keys work with generativelanguage.googleapis.com - verbose_logger.debug( - f"Using Vertex AI API key authentication for model: {model} - routing to Google AI Studio endpoint" - ) - url, endpoint = _get_gemini_url( - mode=mode, - model=model, - stream=stream, - gemini_api_key=gemini_api_key, - ) - # API key is already included in the URL by _get_gemini_url - auth_header = None - else: - # Use OAuth2 Bearer token authentication (traditional Vertex AI) - url, endpoint = _get_vertex_url( - mode=mode, - model=model, - stream=stream, - vertex_project=vertex_project, - vertex_location=vertex_location, - vertex_api_version=version, - ) + url, endpoint = _get_vertex_url( + mode=mode, + model=model, + stream=stream, + vertex_project=vertex_project, + vertex_location=vertex_location, + vertex_api_version=version, + ) return self._check_custom_proxy( api_base=api_base, diff --git a/litellm/main.py b/litellm/main.py index 10e3bcac04b..6905d8f6a87 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -189,7 +189,7 @@ from .llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler from .llms.custom_llm import CustomLLM, custom_chat_llm_router from .llms.databricks.embed.handler import DatabricksEmbeddingHandler from .llms.deprecated_providers import aleph_alpha, palm -from .llms.gemini.common_utils import get_api_key_from_env, get_vertex_api_key_from_env +from .llms.gemini.common_utils import get_api_key_from_env from .llms.groq.chat.handler import GroqChatCompletion from .llms.heroku.chat.transformation import HerokuChatConfig from .llms.huggingface.embedding.handler import HuggingFaceEmbedding @@ -3230,12 +3230,6 @@ def completion( # type: ignore # noqa: PLR0915 or get_secret("VERTEXAI_CREDENTIALS") ) - vertex_api_key = ( - api_key - or get_vertex_api_key_from_env() - or litellm.api_key - ) - api_base = api_base or litellm.api_base or get_secret("VERTEXAI_API_BASE") new_params = safe_deep_copy(optional_params or {}) @@ -3277,7 +3271,7 @@ def completion( # type: ignore # noqa: PLR0915 vertex_location=vertex_ai_location, vertex_project=vertex_ai_project, vertex_credentials=vertex_credentials, - gemini_api_key=vertex_api_key, # Support for Vertex AI API Key + gemini_api_key=None, logging_obj=logging, acompletion=acompletion, timeout=timeout, diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py index 80d65991acb..389c8446135 100644 --- a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py +++ b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py @@ -13,7 +13,6 @@ sys.path.insert( import litellm from litellm.llms.vertex_ai.vertex_llm_base import VertexBase -from litellm.llms.vertex_ai.common_utils import _get_gemini_url def run_sync(coro): @@ -1049,139 +1048,3 @@ class TestVertexBase: MockCredentials.from_info.assert_called_once_with(json_obj) mock_creds.with_scopes.assert_called_once_with(scopes) assert result == "scoped_creds" - - def test_get_token_and_url_with_api_key(self): - """Test that API key authentication routes to Google AI Studio endpoint""" - vertex_base = VertexBase() - - # Test with API key and no credentials - should use Google AI Studio endpoint - auth_header, url = vertex_base._get_token_and_url( - model="gemini-2.0-flash-exp", - auth_header=None, - gemini_api_key="test-api-key-123", - vertex_project="test-project", - vertex_location="us-central1", - vertex_credentials=None, # No service account credentials - stream=False, - custom_llm_provider="vertex_ai", - api_base=None, - should_use_v1beta1_features=False, - mode="chat", - ) - - # Should route to Google AI Studio endpoint - assert "generativelanguage.googleapis.com" in url - assert "gemini-2.0-flash-exp" in url - assert "key=test-api-key-123" in url - assert auth_header is None # API key is in URL, not header - - def test_get_token_and_url_with_credentials(self): - """Test that service account credentials route to Vertex AI endpoint""" - vertex_base = VertexBase() - - mock_creds = MagicMock() - mock_creds.token = "mock-bearer-token" - mock_creds.expired = False - - with patch.object( - vertex_base, "_ensure_access_token", return_value=("mock-bearer-token", "test-project") - ): - # Test with credentials - should use Vertex AI endpoint - auth_header, url = vertex_base._get_token_and_url( - model="gemini-2.0-flash-exp", - auth_header="mock-bearer-token", - gemini_api_key=None, - vertex_project="test-project", - vertex_location="us-central1", - vertex_credentials={"type": "service_account"}, - stream=False, - custom_llm_provider="vertex_ai", - api_base=None, - should_use_v1beta1_features=False, - mode="chat", - ) - - # Should route to Vertex AI endpoint - assert "aiplatform.googleapis.com" in url - assert "projects/test-project" in url - assert "locations/us-central1" in url - assert auth_header == "mock-bearer-token" - - def test_get_token_and_url_api_key_with_streaming(self): - """Test API key authentication with streaming enabled""" - vertex_base = VertexBase() - - auth_header, url = vertex_base._get_token_and_url( - model="gemini-2.0-flash-exp", - auth_header=None, - gemini_api_key="test-api-key-456", - vertex_project="test-project", - vertex_location="us-central1", - vertex_credentials=None, - stream=True, # Streaming enabled - custom_llm_provider="vertex_ai", - api_base=None, - should_use_v1beta1_features=False, - mode="chat", - ) - - # Should route to Google AI Studio endpoint with streaming - assert "generativelanguage.googleapis.com" in url - assert "streamGenerateContent" in url - assert "key=test-api-key-456" in url - assert "alt=sse" in url - assert auth_header is None - - def test_get_token_and_url_api_key_priority(self): - """Test that credentials take priority over API key when both are provided""" - vertex_base = VertexBase() - - # When both API key and credentials are provided, credentials take priority - mock_creds = MagicMock() - mock_creds.token = "mock-bearer-token" - mock_creds.expired = False - - with patch.object( - vertex_base, "_ensure_access_token", return_value=("mock-bearer-token", "test-project") - ): - auth_header, url = vertex_base._get_token_and_url( - model="gemini-2.0-flash-exp", - auth_header="mock-bearer-token", - gemini_api_key="test-api-key-789", - vertex_project="test-project", - vertex_location="us-central1", - vertex_credentials={"type": "service_account"}, # Credentials provided - stream=False, - custom_llm_provider="vertex_ai", - api_base=None, - should_use_v1beta1_features=False, - mode="chat", - ) - - # Should use Vertex AI endpoint with Bearer token (credentials take priority) - assert "aiplatform.googleapis.com" in url - assert auth_header == "mock-bearer-token" - - def test_get_token_and_url_with_embedding_mode(self): - """Test API key authentication with embedding mode""" - vertex_base = VertexBase() - - auth_header, url = vertex_base._get_token_and_url( - model="text-embedding-004", - auth_header=None, - gemini_api_key="test-embedding-key", - vertex_project="test-project", - vertex_location="us-central1", - vertex_credentials=None, - stream=False, - custom_llm_provider="vertex_ai", - api_base=None, - should_use_v1beta1_features=False, - mode="embedding", - ) - - # Should route to Google AI Studio endpoint for embeddings - assert "generativelanguage.googleapis.com" in url - assert "embedContent" in url - assert "key=test-embedding-key" in url - assert auth_header is None \ No newline at end of file From b1c122056fa0b6e41f5bf6124deb7dd68ba87da4 Mon Sep 17 00:00:00 2001 From: Ishaan Jaff Date: Sun, 11 Jan 2026 01:49:43 +0400 Subject: [PATCH 044/114] Revert "fix: Improve error messages and validation for wildcard routing with multiple credentials" (#18907) --- litellm/router.py | 22 +++------------------- 1 file changed, 3 insertions(+), 19 deletions(-) diff --git a/litellm/router.py b/litellm/router.py index 364e6719300..638df49ac05 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -4486,21 +4486,9 @@ class Router: if hasattr(original_exception, "message"): # add the available fallbacks to the exception - deployment_info = "" - if kwargs is not None: - metadata = kwargs.get('metadata', {}) - if metadata and 'deployment' in metadata: - deployment_info = f"\nUsed Deployment: {metadata['deployment']}" - if 'model_info' in metadata: - model_info = metadata['model_info'] - if isinstance(model_info, dict): - deployment_info += f"\nDeployment ID: {model_info.get('id', 'unknown')}" - - original_exception.message += ( # type: ignore - f". Received Model Group={model_group}" - f"\nAvailable Model Group Fallbacks={fallback_model_group}" - f"{deployment_info}" - f"\n\n💡 Tip: If using wildcard patterns (e.g., 'openai/*'), ensure all matching deployments have credentials with access to this model." + original_exception.message += ". Received Model Group={}\nAvailable Model Group Fallbacks={}".format( # type: ignore + model_group, + fallback_model_group, ) if len(fallback_failure_exception_str) > 0: original_exception.message += ( # type: ignore @@ -7679,10 +7667,6 @@ class Router: ) if pattern_deployments: - verbose_router_logger.debug( - f"Pattern match for model='{model}': Found {len(pattern_deployments)} deployments. " - f"Deployment IDs: {[d.get('model_info', {}).get('id', 'unknown') for d in pattern_deployments]}" - ) return model, pattern_deployments if ( From 35c636ba97959fb6f684923552e2e146995f1341 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 13:52:45 -0800 Subject: [PATCH 045/114] test_health_check_not_called_when_disabled --- tests/proxy_unit_tests/test_proxy_server.py | 8 ++++++-- tests/proxy_unit_tests/test_proxy_utils.py | 4 ++++ 2 files changed, 10 insertions(+), 2 deletions(-) diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index 8d3b0fee48f..0db1240544a 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -642,8 +642,8 @@ def test_embedding(mock_aembedding, client_no_auth): during_call_kwargs = mock_during_hook.await_args_list[0].kwargs assert ( - during_call_kwargs.get("call_type") == "embeddings" - ), f"expected during_call_hook to receive call_type='embeddings', got {during_call_kwargs.get('call_type')}" + during_call_kwargs.get("call_type") == "embedding" + ), f"expected during_call_hook to receive call_type='embedding', got {during_call_kwargs.get('call_type')}" except Exception as e: pytest.fail(f"LiteLLM Proxy test failed. Exception - {str(e)}") @@ -2185,6 +2185,10 @@ async def test_proxy_server_prisma_setup(): mock_client._set_spend_logs_row_count_in_proxy_state = ( AsyncMock() ) # Mock the _set_spend_logs_row_count_in_proxy_state method + # Mock the db attribute with start_token_refresh_task for RDS IAM token refresh + mock_db = MagicMock() + mock_db.start_token_refresh_task = AsyncMock() + mock_client.db = mock_db await ProxyStartupEvent._setup_prisma_client( database_url=os.getenv("DATABASE_URL"), diff --git a/tests/proxy_unit_tests/test_proxy_utils.py b/tests/proxy_unit_tests/test_proxy_utils.py index 5c3c3948920..64f1ec24234 100644 --- a/tests/proxy_unit_tests/test_proxy_utils.py +++ b/tests/proxy_unit_tests/test_proxy_utils.py @@ -1574,6 +1574,10 @@ async def test_health_check_not_called_when_disabled(monkeypatch): mock_prisma.health_check = AsyncMock() mock_prisma.check_view_exists = AsyncMock() mock_prisma._set_spend_logs_row_count_in_proxy_state = AsyncMock() + # Mock the db attribute with start_token_refresh_task for RDS IAM token refresh + mock_db = MagicMock() + mock_db.start_token_refresh_task = AsyncMock() + mock_prisma.db = mock_db # Mock PrismaClient constructor monkeypatch.setattr( "litellm.proxy.proxy_server.PrismaClient", lambda **kwargs: mock_prisma From 6b7f11484700c643ea31615189e8e42b91286deb Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 13:54:59 -0800 Subject: [PATCH 046/114] test_lists_with_sensitive_keys_are_masked --- .../litellm_core_utils/test_sensitive_data_masker.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/tests/test_litellm/litellm_core_utils/test_sensitive_data_masker.py b/tests/test_litellm/litellm_core_utils/test_sensitive_data_masker.py index 9f0a1ae8ffe..b9f17aa4c7f 100644 --- a/tests/test_litellm/litellm_core_utils/test_sensitive_data_masker.py +++ b/tests/test_litellm/litellm_core_utils/test_sensitive_data_masker.py @@ -108,14 +108,16 @@ def test_lists_with_sensitive_keys_are_masked(): """ masker = SensitiveDataMasker() data = { - "api_key": ["sk-123", "sk-456"], + "api_key": ["sk-1234567890abcdef", "sk-9876543210fedcba"], "tags": ["prod", "test"], } masked = masker.mask_dict(data) # sensitive key list entries should be masked - assert masked["api_key"][0] != "sk-123" + assert masked["api_key"][0] != "sk-1234567890abcdef" assert "*" in masked["api_key"][0] + assert masked["api_key"][1] != "sk-9876543210fedcba" + assert "*" in masked["api_key"][1] # non-sensitive list should remain unchanged assert masked["tags"] == ["prod", "test"] From 69aaad5e69d24dafa18ea6f9189c702a38a65776 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:00:54 -0800 Subject: [PATCH 047/114] Revert "added extraction of top level metadata for custom lables in prometheus callbacks (#18087)" This reverts commit 14a4a9c0319c984beb7ef0113b659fd850f2990a. --- litellm/integrations/prometheus.py | 1 - .../test_prometheus_logging_callbacks.py | 118 ------------------ 2 files changed, 119 deletions(-) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index c32a7b75c51..63eff5c2c9e 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -884,7 +884,6 @@ class PrometheusLogger(CustomLogger): } combined_metadata: Dict[str, Any] = { - **top_level_fields, # Include top-level fields first **(_requester_metadata if _requester_metadata else {}), **(user_api_key_auth_metadata if user_api_key_auth_metadata else {}), } diff --git a/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py b/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py index 2f92afb3824..e8fe4dd3393 100644 --- a/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py +++ b/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py @@ -1124,124 +1124,6 @@ def test_get_custom_labels_from_metadata_tags(monkeypatch): assert get_custom_labels_from_metadata(metadata) == {} -def test_get_custom_labels_from_top_level_metadata(monkeypatch): - """ - Test that get_custom_labels_from_metadata can extract fields from top-level metadata, - such as requester_ip_address, not just from nested dictionaries like requester_metadata. - """ - monkeypatch.setattr( - "litellm.custom_prometheus_metadata_labels", - ["requester_ip_address", "user_api_key_alias"], - ) - # Simulate metadata structure with top-level fields - metadata = { - "requester_ip_address": "10.48.203.20", # Top-level field - "user_api_key_alias": "TestAlias", # Top-level field - "requester_metadata": {"nested_field": "nested_value"}, # Nested dict (excluded) - "user_api_key_auth_metadata": {"another_nested": "value"}, # Nested dict (excluded) - } - result = get_custom_labels_from_metadata(metadata) - assert result == { - "requester_ip_address": "10.48.203.20", - "user_api_key_alias": "TestAlias", - } - - -def test_get_custom_labels_from_top_level_and_nested_metadata(monkeypatch): - """ - Test that get_custom_labels_from_metadata can extract fields from both top-level - and nested metadata (requester_metadata, user_api_key_auth_metadata). - """ - monkeypatch.setattr( - "litellm.custom_prometheus_metadata_labels", - [ - "requester_ip_address", # Top-level - "metadata.foo", # From requester_metadata - "metadata.bar", # From user_api_key_auth_metadata - ], - ) - # Simulate combined_metadata structure as it would appear after merging - # This is what gets passed to get_custom_labels_from_metadata - combined_metadata = { - "requester_ip_address": "10.48.203.20", # Top-level field - "foo": "bar_value", # From requester_metadata (spread) - "bar": "baz_value", # From user_api_key_auth_metadata (spread) - } - result = get_custom_labels_from_metadata(combined_metadata) - assert result == { - "requester_ip_address": "10.48.203.20", - "metadata_foo": "bar_value", - "metadata_bar": "baz_value", - } - - -async def test_async_log_success_event_with_top_level_metadata(prometheus_logger, monkeypatch): - """ - Test that async_log_success_event correctly extracts custom labels from top-level metadata - fields like requester_ip_address, not just from nested dictionaries. - """ - # Configure custom metadata labels to extract requester_ip_address - monkeypatch.setattr( - "litellm.custom_prometheus_metadata_labels", ["requester_ip_address"] - ) - - # Create standard logging payload with requester_ip_address at top-level metadata - standard_logging_object = create_standard_logging_payload() - standard_logging_object["metadata"]["requester_ip_address"] = "10.48.203.20" - standard_logging_object["metadata"]["requester_metadata"] = {} # Empty nested dict - standard_logging_object["metadata"]["user_api_key_auth_metadata"] = {} # Empty nested dict - - kwargs = { - "model": "gpt-3.5-turbo", - "stream": True, - "litellm_params": { - "metadata": { - "user_api_key": "test_key", - "user_api_key_user_id": "test_user", - "user_api_key_team_id": "test_team", - "user_api_key_end_user_id": "test_end_user", - } - }, - "start_time": datetime.now(), - "completion_start_time": datetime.now(), - "api_call_start_time": datetime.now(), - "end_time": datetime.now() + timedelta(seconds=1), - "standard_logging_object": standard_logging_object, - } - response_obj = MagicMock() - - # Mock the prometheus client methods - prometheus_logger.litellm_requests_metric = MagicMock() - prometheus_logger.litellm_spend_metric = MagicMock() - prometheus_logger.litellm_tokens_metric = MagicMock() - prometheus_logger.litellm_input_tokens_metric = MagicMock() - prometheus_logger.litellm_output_tokens_metric = MagicMock() - prometheus_logger.litellm_remaining_team_budget_metric = MagicMock() - prometheus_logger.litellm_remaining_api_key_budget_metric = MagicMock() - prometheus_logger.litellm_remaining_api_key_requests_for_model = MagicMock() - prometheus_logger.litellm_remaining_api_key_tokens_for_model = MagicMock() - prometheus_logger.litellm_llm_api_time_to_first_token_metric = MagicMock() - prometheus_logger.litellm_llm_api_latency_metric = MagicMock() - prometheus_logger.litellm_request_total_latency_metric = MagicMock() - - await prometheus_logger.async_log_success_event( - kwargs, response_obj, kwargs["start_time"], kwargs["end_time"] - ) - - # Verify that the metrics were called with labels including requester_ip_address - # Check that labels() was called - the actual labels dict should include requester_ip_address - assert prometheus_logger.litellm_requests_metric.labels.called - assert prometheus_logger.litellm_spend_metric.labels.called - - # Get the actual call arguments to verify requester_ip_address is included - # The custom labels should be extracted and included in the label factory - call_args = prometheus_logger.litellm_requests_metric.labels.call_args - assert call_args is not None - # The labels() method receives a dict with label names and values - # We can't easily assert the exact values without checking the internal implementation, - # but we've verified the function is called, which means the extraction happened - - def test_get_custom_labels_from_tags(monkeypatch): from litellm.integrations.prometheus import get_custom_labels_from_tags From f37ccca19c70dd937cfee01b77951e61318f9792 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:04:47 -0800 Subject: [PATCH 048/114] docs fix --- docs/my-website/release_notes/v1.80.11-stable/index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/my-website/release_notes/v1.80.11-stable/index.md b/docs/my-website/release_notes/v1.80.11-stable/index.md index b671b795602..ea0e6083dfc 100644 --- a/docs/my-website/release_notes/v1.80.11-stable/index.md +++ b/docs/my-website/release_notes/v1.80.11-stable/index.md @@ -1,5 +1,5 @@ --- -title: "[Preview] v1.80.11 - Google Interactions API" +title: "v1.80.11 - Google Interactions API" slug: "v1-80-11" date: 2025-12-20T10:00:00 authors: @@ -27,7 +27,7 @@ import TabItem from '@theme/TabItem'; docker run \ -e STORE_MODEL_IN_DB=True \ -p 4000:4000 \ -docker.litellm.ai/berriai/litellm:v1.80.11.rc.1 +docker.litellm.ai/berriai/litellm:v1.80.11-stable ``` From 6a9041e67d8e816d6a970229a49ea6de2bcb43f8 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:08:11 -0800 Subject: [PATCH 049/114] Revert "aws fix base" This reverts commit 225f411abc122087d484fb41d495d340ce5abb80. --- tests/test_litellm/llms/bedrock/test_base_aws_llm.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py index 45fb418e79a..f5856cd12d6 100644 --- a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py +++ b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py @@ -14,16 +14,15 @@ from datetime import datetime, timedelta, timezone from typing import Any, Dict from unittest.mock import MagicMock, patch -from botocore.awsrequest import AWSPreparedRequest, AWSRequest from botocore.credentials import Credentials - +from botocore.awsrequest import AWSRequest, AWSPreparedRequest import litellm -from litellm.caching.caching import DualCache from litellm.llms.bedrock.base_aws_llm import ( AwsAuthError, BaseAWSLLM, Boto3CredentialsInfo, ) +from litellm.caching.caching import DualCache # Global variable for the base_aws_llm.py file path @@ -583,7 +582,7 @@ def test_eks_irsa_ambient_credentials_used(): ) # Should create STS client without explicit credentials (using ambient credentials) - mock_boto3_client.assert_called_once_with("sts", verify=True) + mock_boto3_client.assert_called_once_with("sts") # Should call assume_role mock_sts_client.assume_role.assert_called_once_with( @@ -643,7 +642,6 @@ def test_explicit_credentials_used_when_provided(): aws_access_key_id="explicit-access-key", aws_secret_access_key="explicit-secret-key", aws_session_token="assumed-session-token", - verify=True, ) # Should call assume_role @@ -703,7 +701,6 @@ def test_partial_credentials_still_use_ambient(): aws_access_key_id="AKIAEXAMPLE", aws_secret_access_key=None, aws_session_token=None, - verify=True, ) # Should still call assume_role @@ -751,7 +748,7 @@ def test_cross_account_role_assumption(): ) # Should use ambient credentials - mock_boto3_client.assert_called_once_with("sts", verify=True) + mock_boto3_client.assert_called_once_with("sts") # Should call assume_role with cross-account role mock_sts_client.assume_role.assert_called_once_with( From abeec38ada77633a398d75e79a721c6e1c7738d9 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:14:40 -0800 Subject: [PATCH 050/114] fix manus --- .../llms/manus/responses/transformation.py | 29 +++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/litellm/llms/manus/responses/transformation.py b/litellm/llms/manus/responses/transformation.py index 8e0a4a5a30f..fbbed19f8d4 100644 --- a/litellm/llms/manus/responses/transformation.py +++ b/litellm/llms/manus/responses/transformation.py @@ -1,3 +1,4 @@ +import uuid from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union import httpx @@ -227,6 +228,12 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): total_tokens=0, ) + # Ensure id is present - failed responses may not include it + if "id" not in raw_response_json or raw_response_json.get("id") is None: + # Generate a placeholder id for failed responses + # This allows the response object to be created even when the API doesn't return an id + raw_response_json["id"] = f"unknown-{uuid.uuid4().hex[:8]}" + try: response = ResponsesAPIResponse(**raw_response_json) except Exception: @@ -296,6 +303,28 @@ class ManusResponsesAPIConfig(OpenAIResponsesAPIConfig): raw_response_headers = dict(raw_response.headers) processed_headers = process_response_headers(raw_response_headers) + # Ensure reasoning, text, output, and usage are present with defaults + if "reasoning" not in raw_response_json or raw_response_json.get("reasoning") is None: + raw_response_json["reasoning"] = {} + + if "text" not in raw_response_json or raw_response_json.get("text") is None: + raw_response_json["text"] = {} + + if "output" not in raw_response_json or raw_response_json.get("output") is None: + raw_response_json["output"] = [] + + if "usage" not in raw_response_json or raw_response_json.get("usage") is None: + raw_response_json["usage"] = ResponseAPIUsage( + input_tokens=0, + output_tokens=0, + total_tokens=0, + ) + + # Ensure id is present - failed responses may not include it + if "id" not in raw_response_json or raw_response_json.get("id") is None: + # Generate a placeholder id for failed responses + raw_response_json["id"] = f"unknown-{uuid.uuid4().hex[:8]}" + try: response = ResponsesAPIResponse(**raw_response_json) except Exception: From 3223554905abc4885c5a218601da3e90dd0adeb0 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:15:28 -0800 Subject: [PATCH 051/114] bump --- poetry.lock | 8 ++++---- pyproject.toml | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/poetry.lock b/poetry.lock index 0a4ef10d09f..3bafdb157ca 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3081,15 +3081,15 @@ files = [ [[package]] name = "litellm-proxy-extras" -version = "0.4.18" +version = "0.4.21" description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package." optional = true python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8" groups = ["main"] markers = "extra == \"proxy\"" files = [ - {file = "litellm_proxy_extras-0.4.18-py3-none-any.whl", hash = "sha256:c3edee68bf8eb073c6158dcf7df05727dfc829e63c03a617fcb48853d11490df"}, - {file = "litellm_proxy_extras-0.4.18.tar.gz", hash = "sha256:898b28e3e74acdc29142906b84787ab05a90e30aa3c0c8aee849915e3a16adb3"}, + {file = "litellm_proxy_extras-0.4.21-py3-none-any.whl", hash = "sha256:83a1734e9773610945230606012e602bbcbfba1c60fde836d51102c1a296f166"}, + {file = "litellm_proxy_extras-0.4.21.tar.gz", hash = "sha256:fa0e012984aa8e5114f88f4bad53d6abb589e5ca3eab445f74f8ddeceb62d848"}, ] [[package]] @@ -7981,4 +7981,4 @@ utils = ["numpydoc"] [metadata] lock-version = "2.1" python-versions = ">=3.9,<4.0" -content-hash = "e9fd12b5ccc703ec156d98877452417083e3ac18b5970cb3a58c3bde09d267bb" +content-hash = "ea62b77c662ab9fc486e421c576f0868bcde16d62a24703ee1f4916a0465ffb2" diff --git a/pyproject.toml b/pyproject.toml index 00e7bff78b6..742f743b54d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -167,7 +167,7 @@ requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.80.13" +version = "1.80.14" version_files = [ "pyproject.toml:^version" ] From 46cbf673b607698948f0c89f642c5da457d2859a Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:16:55 -0800 Subject: [PATCH 052/114] fix code QA --- litellm/integrations/prometheus.py | 8 -------- 1 file changed, 8 deletions(-) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 63eff5c2c9e..bb9d6166b01 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -875,14 +875,6 @@ class PrometheusLogger(CustomLogger): # Include top-level metadata fields (excluding nested dictionaries) # This allows accessing fields like requester_ip_address from top-level metadata top_level_metadata = standard_logging_payload.get("metadata", {}) - top_level_fields: Dict[str, Any] = {} - if isinstance(top_level_metadata, dict): - top_level_fields = { - k: v - for k, v in top_level_metadata.items() - if not isinstance(v, dict) # Exclude nested dicts to avoid conflicts - } - combined_metadata: Dict[str, Any] = { **(_requester_metadata if _requester_metadata else {}), **(user_api_key_auth_metadata if user_api_key_auth_metadata else {}), From 7e6d0d7691ec55fdde440ec3f429c49e8dfaf37c Mon Sep 17 00:00:00 2001 From: akraines Date: Sun, 11 Jan 2026 00:23:45 +0200 Subject: [PATCH 053/114] fix: Support batch requests with comma-separated models in validate_model_access (#18909) This fixes a breaking change where batch completion requests with comma-separated model strings (e.g., 'gpt-3.5-turbo,fake-openai-endpoint') were failing validation. The validate_model_access function now: - Detects comma-separated model strings - Validates each model individually - Provides clear error messages for inaccessible models in batch requests - Maintains backward compatibility for single model validation Fixes test_batch_chat_completions test failure. --- litellm/proxy/utils.py | 30 ++++++++++++++++++++++-------- 1 file changed, 22 insertions(+), 8 deletions(-) diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 171898b1631..9ea2ea7d5c9 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -4479,21 +4479,35 @@ def validate_model_access( ) -> None: """ Validate that a model is accessible to the user. + Supports batch requests with comma-separated model IDs. Args: - model_id: The model ID to validate + model_id: The model ID to validate (can be comma-separated for batch requests) available_models: List of models available to the user Raises: HTTPException: If the model is not accessible """ - if model_id not in available_models: - raise HTTPException( - status_code=404, - detail="The model `{}` does not exist or is not accessible".format( - model_id - ), - ) + # Handle batch requests with comma-separated models + if "," in model_id: + models = [m.strip() for m in model_id.split(",")] + inaccessible_models = [m for m in models if m not in available_models] + if inaccessible_models: + raise HTTPException( + status_code=404, + detail="The following model(s) do not exist or are not accessible: {}".format( + ", ".join(inaccessible_models) + ), + ) + else: + # Single model validation + if model_id not in available_models: + raise HTTPException( + status_code=404, + detail="The model `{}` does not exist or is not accessible".format( + model_id + ), + ) def _path_matches_pattern(path: str, pattern: str) -> bool: From ab37a9872c88d6cecaba4539b7a3f455bf33a304 Mon Sep 17 00:00:00 2001 From: Shivam Rawat <161387515+shivamrawat1@users.noreply.github.com> Date: Sat, 10 Jan 2026 14:26:08 -0800 Subject: [PATCH 054/114] fixed _organization_max_budget_check so tests works (#18908) --- litellm/proxy/auth/auth_checks.py | 40 ++++++++++++++++++++++++++----- 1 file changed, 34 insertions(+), 6 deletions(-) diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 26778ece60e..843da0e3a0d 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -1794,11 +1794,20 @@ async def get_org_object( user_api_key_cache: DualCache, parent_otel_span: Optional[Span] = None, proxy_logging_obj: Optional[ProxyLogging] = None, + include_budget_table: bool = False, ) -> Optional[LiteLLM_OrganizationTable]: """ - Check if org id in proxy Org Table - if valid, return LiteLLM_OrganizationTable object - if not, then raise an error + + Args: + org_id: Organization ID to look up + prisma_client: Database client + user_api_key_cache: Cache for storing results + parent_otel_span: Optional OpenTelemetry span + proxy_logging_obj: Optional proxy logging object + include_budget_table: If True, includes litellm_budget_table in the query """ if prisma_client is None: raise Exception( @@ -1807,8 +1816,13 @@ async def get_org_object( if not isinstance(org_id, str): return None + # Use different cache key if budget table is included + cache_key = "org_id:{}".format(org_id) + if include_budget_table: + cache_key = "org_id:{}:with_budget".format(org_id) + # check if in cache - cached_org_obj = user_api_key_cache.async_get_cache(key="org_id:{}".format(org_id)) + cached_org_obj = user_api_key_cache.async_get_cache(key=cache_key) if cached_org_obj is not None: if isinstance(cached_org_obj, dict): return LiteLLM_OrganizationTable(**cached_org_obj) @@ -1816,13 +1830,24 @@ async def get_org_object( return cached_org_obj # else, check db try: + query_kwargs = {"where": {"organization_id": org_id}} + if include_budget_table: + query_kwargs["include"] = {"litellm_budget_table": True} + response = await prisma_client.db.litellm_organizationtable.find_unique( - where={"organization_id": org_id} + **query_kwargs ) if response is None: raise Exception + # Cache the result + await user_api_key_cache.async_set_cache( + key=cache_key, + value=response.model_dump() if hasattr(response, "model_dump") else response, + ttl=DEFAULT_IN_MEMORY_TTL, + ) + return response except Exception: raise Exception( @@ -2344,11 +2369,14 @@ async def _organization_max_budget_check( if org_id is None: return - # Get organization object with budget table to check current spend and max budget + # Get organization object with budget table - use get_org_object so it can be mocked in tests try: - org_table = await prisma_client.db.litellm_organizationtable.find_unique( - where={"organization_id": org_id}, - include={"litellm_budget_table": True}, + org_table = await get_org_object( + org_id=org_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + include_budget_table=True, ) except Exception: # If organization lookup fails, skip the check From 9b4f3308fc51d2f345274edf635f0f9ce24ee389 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:45:55 -0800 Subject: [PATCH 055/114] docs fix --- docs/my-website/release_notes/{v1.80.13 => v1.80.14}/index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) rename docs/my-website/release_notes/{v1.80.13 => v1.80.14}/index.md (97%) diff --git a/docs/my-website/release_notes/v1.80.13/index.md b/docs/my-website/release_notes/v1.80.14/index.md similarity index 97% rename from docs/my-website/release_notes/v1.80.13/index.md rename to docs/my-website/release_notes/v1.80.14/index.md index d895f4b0185..43d7c7eedac 100644 --- a/docs/my-website/release_notes/v1.80.13/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -1,6 +1,6 @@ --- -title: "[Preview] v1.80.13 - Google Interactions API" -slug: "v1-80-13" +title: "[Preview] v1.80.14 - Manus API Support" +slug: "v1-80-14" date: 2026-01-10T10:00:00 authors: - name: Krrish Dholakia From 17995c5192e33229d53d5c1306478b0cb220c94c Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:51:56 -0800 Subject: [PATCH 056/114] rc1 writeup --- .../release_notes/v1.80.14/index.md | 497 ++++++++++++++++-- 1 file changed, 458 insertions(+), 39 deletions(-) diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index 43d7c7eedac..9765487e690 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -1,5 +1,5 @@ --- -title: "[Preview] v1.80.14 - Manus API Support" +title: "v1.80.14 - Manus API Support" slug: "v1-80-14" date: 2026-01-10T10:00:00 authors: @@ -27,7 +27,7 @@ import TabItem from '@theme/TabItem'; docker run \ -e STORE_MODEL_IN_DB=True \ -p 4000:4000 \ -docker.litellm.ai/berriai/litellm:v1.80.13.rc.1 +docker.litellm.ai/berriai/litellm:v1.80.14-stable ``` @@ -35,7 +35,7 @@ docker.litellm.ai/berriai/litellm:v1.80.13.rc.1 ``` showLineNumbers title="pip install litellm" -pip install litellm==1.80.13 +pip install litellm==1.80.14 ``` @@ -45,6 +45,15 @@ pip install litellm==1.80.13 ## Key Highlights +- **Manus API Support** - [New provider support for Manus API on /responses and GET /responses endpoints](../../docs/providers/manus) +- **MiniMax Provider** - [Full support for MiniMax chat completions, TTS, and Anthropic native endpoint](../../docs/providers/minimax) +- **AWS Polly TTS** - [New TTS provider using AWS Polly API](../../docs/providers/aws_polly) +- **SSO Role Mapping** - Configure role mappings for SSO providers directly in the UI +- **Cost Estimator** - [New UI tool for estimating costs across multiple models and requests](../../docs/proxy/cost_estimator) +- **MCP Global Mode** - [Configure MCP servers globally with visibility controls](../../docs/mcp) +- **Interactions API Bridge** - [Use all LiteLLM providers with the Interactions API](../../docs/interactions) +- **RAG Query Endpoint** - [New RAG Search/Query endpoint for retrieval-augmented generation](../../docs/search/index) +- **92.7% Faster Provider Config Lookup** - Major performance improvement for provider configuration - **UI Usage - Endpoint Activity** - Users can now see Endpoint Activity Metrics in the UI. @@ -59,37 +68,129 @@ style={{width: '100%', display: 'block', margin: '2rem auto'}} Users can now see Endpoint Activity Metrics in the UI. ---- - -## New Providers and Endpoints - -### New Providers (X new providers) - -| Provider | Supported LiteLLM Endpoints | Description | -| -------- | ------------------- | ----------- | - - -### New LLM API Endpoints (X new endpoints) - -| Endpoint | Method | Description | Documentation | -| -------- | ------ | ----------- | ------------- | - - --- ## New Models / Updated Models -#### New Model Support (X new models) +#### New Model Support (100+ new models) | Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) | Features | | -------- | ----- | -------------- | ------------------- | -------------------- | -------- | - +| Azure | `azure/gpt-5.2` | 400K | $1.75 | $14.00 | Reasoning, vision, caching | +| Azure | `azure/gpt-5.2-chat` | 128K | $1.75 | $14.00 | Reasoning, vision | +| Azure | `azure/gpt-5.2-pro` | 400K | $21.00 | $168.00 | Reasoning, vision, web search | +| Azure | `azure/gpt-image-1.5` | - | Token-based | Token-based | Image generation/editing | +| Azure AI | `azure_ai/gpt-oss-120b` | 131K | $0.15 | $0.60 | Function calling | +| Azure AI | `azure_ai/flux.2-pro` | - | - | $0.04/image | Image generation | +| Azure AI | `azure_ai/deepseek-v3.2` | 164K | $0.58 | $1.68 | Reasoning, function calling | +| Bedrock | `amazon.nova-2-multimodal-embeddings-v1:0` | 8K | $0.135 | - | Multimodal embeddings | +| Bedrock | `writer.palmyra-x4-v1:0` | 128K | $2.50 | $10.00 | Function calling, PDF | +| Bedrock | `writer.palmyra-x5-v1:0` | 1M | $0.60 | $6.00 | Function calling, PDF | +| Bedrock | `moonshot.kimi-k2-v1:0` | - | - | - | Kimi K2 model | +| Cerebras | `cerebras/zai-glm-4.6` | 128K | $2.25 | $2.75 | Reasoning, function calling | +| GigaChat | `gigachat/GigaChat-2-Lite` | - | - | - | Chat completions | +| GigaChat | `gigachat/GigaChat-2-Max` | - | - | - | Chat completions | +| GigaChat | `gigachat/GigaChat-2-Pro` | - | - | - | Chat completions | +| Gemini | `gemini/veo-3.1-generate-001` | - | - | - | Video generation | +| Gemini | `gemini/veo-3.1-fast-generate-001` | - | - | - | Video generation | +| GitHub Copilot | 25+ models | Various | - | - | Chat completions | +| LlamaGate | 15+ models | Various | - | - | Chat, vision, embeddings | +| MiniMax | `minimax/abab7-chat-preview` | - | - | - | Chat completions | +| Novita | 80+ models | Various | Various | Various | Chat, vision, embeddings | +| OpenRouter | `openrouter/google/gemini-3-flash-preview` | - | - | - | Chat completions | +| Together AI | Multiple models | Various | Various | Various | Response schema support | +| Vertex AI | `vertex_ai/zai-glm-4.7` | - | - | - | GLM 4.7 support | #### Features +- **[Gemini](../../docs/providers/gemini)** + - Add image tokens in chat completion - [PR #18327](https://github.com/BerriAI/litellm/pull/18327) + - Add usage object in image generation - [PR #18328](https://github.com/BerriAI/litellm/pull/18328) + - Add thought signature support via tool call id - [PR #18374](https://github.com/BerriAI/litellm/pull/18374) + - Add thought signature for non tool call requests - [PR #18581](https://github.com/BerriAI/litellm/pull/18581) + - Preserve system instructions - [PR #18585](https://github.com/BerriAI/litellm/pull/18585) + - Fix Gemini 3 images in tool response - [PR #18190](https://github.com/BerriAI/litellm/pull/18190) + - Support snake_case for google_search tool parameters - [PR #18451](https://github.com/BerriAI/litellm/pull/18451) + - Google GenAI adapter inline data support - [PR #18477](https://github.com/BerriAI/litellm/pull/18477) + - Add deprecation_date for discontinued Google models - [PR #18550](https://github.com/BerriAI/litellm/pull/18550) +- **[Vertex AI](../../docs/providers/vertex)** + - Add centralized get_vertex_base_url() helper for global location support - [PR #18410](https://github.com/BerriAI/litellm/pull/18410) + - Convert image URLs to base64 for Vertex AI Anthropic - [PR #18497](https://github.com/BerriAI/litellm/pull/18497) + - Separate Tool objects for each tool type per API spec - [PR #18514](https://github.com/BerriAI/litellm/pull/18514) + - Add thought_signatures to VertexGeminiConfig - [PR #18853](https://github.com/BerriAI/litellm/pull/18853) + - Add support for Vertex AI API keys - [PR #18806](https://github.com/BerriAI/litellm/pull/18806) + - Add zai glm-4.7 model support - [PR #18782](https://github.com/BerriAI/litellm/pull/18782) +- **[Azure](../../docs/providers/azure)** + - Add Azure gpt-image-1.5 pricing to cost map - [PR #18347](https://github.com/BerriAI/litellm/pull/18347) + - Add azure/gpt-5.2-chat model - [PR #18361](https://github.com/BerriAI/litellm/pull/18361) + - Add support for image generation via Azure AD token - [PR #18413](https://github.com/BerriAI/litellm/pull/18413) + - Add logprobs support for Azure OpenAI GPT-5.2 model - [PR #18856](https://github.com/BerriAI/litellm/pull/18856) + - Add Azure BFL Flux 2 models for image generation and editing - [PR #18764](https://github.com/BerriAI/litellm/pull/18764), [PR #18766](https://github.com/BerriAI/litellm/pull/18766) +- **[Bedrock](../../docs/providers/bedrock)** + - Add Bedrock Kimi K2 model support - [PR #18797](https://github.com/BerriAI/litellm/pull/18797) + - Add support for model id in bedrock passthrough - [PR #18800](https://github.com/BerriAI/litellm/pull/18800) + - Add Bedrock as a backend API for token counting - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) + - Fix Nova model detection for Bedrock provider - [PR #18250](https://github.com/BerriAI/litellm/pull/18250) + - Ensure toolUse.input is always a dict when converting from OpenAI format - [PR #18414](https://github.com/BerriAI/litellm/pull/18414) +- **[Databricks](../../docs/providers/databricks)** + - Add enhanced authentication, security features, and custom user-agent support - [PR #18349](https://github.com/BerriAI/litellm/pull/18349) +- **[MiniMax](../../docs/providers/minimax)** + - Add MiniMax chat completion support - [PR #18380](https://github.com/BerriAI/litellm/pull/18380) + - Add Anthropic native endpoint support for MiniMax - [PR #18377](https://github.com/BerriAI/litellm/pull/18377) + - Add support for MiniMax TTS - [PR #18334](https://github.com/BerriAI/litellm/pull/18334) + - Add MiniMax provider support to UI dashboard - [PR #18496](https://github.com/BerriAI/litellm/pull/18496) +- **[Together AI](../../docs/providers/togetherai)** + - Add supports_response_schema to all supported Together AI models - [PR #18368](https://github.com/BerriAI/litellm/pull/18368) +- **[OpenRouter](../../docs/providers/openrouter)** + - Add OpenRouter embeddings API support - [PR #18391](https://github.com/BerriAI/litellm/pull/18391) +- **[Anthropic](../../docs/providers/anthropic)** + - Pass server_tool_use and tool_search_tool_result blocks - [PR #18770](https://github.com/BerriAI/litellm/pull/18770) + - Add Anthropic cache control option to image tool call results - [PR #18674](https://github.com/BerriAI/litellm/pull/18674) +- **[Ollama](../../docs/providers/ollama)** + - Add dimensions for ollama embedding - [PR #18536](https://github.com/BerriAI/litellm/pull/18536) + - Extract pure base64 data from data URLs for Ollama - [PR #18465](https://github.com/BerriAI/litellm/pull/18465) +- **[Watsonx](../../docs/providers/watsonx)** + - Add Watsonx fields support - [PR #18569](https://github.com/BerriAI/litellm/pull/18569) + - Fix Watsonx Audio Transcription - filter model field - [PR #18810](https://github.com/BerriAI/litellm/pull/18810) +- **[SAP](../../docs/providers/sap)** + - Add SAP creds for list in proxy UI - [PR #18375](https://github.com/BerriAI/litellm/pull/18375) + - Pass through extra params from allowed_openai_params - [PR #18432](https://github.com/BerriAI/litellm/pull/18432) + - Add client header for SAP AI Core Tracking - [PR #18714](https://github.com/BerriAI/litellm/pull/18714) +- **[Fireworks AI](../../docs/providers/fireworks_ai)** + - Correct deepseek-v3p2 pricing - [PR #18483](https://github.com/BerriAI/litellm/pull/18483) +- **[ZAI](../../docs/providers/zai)** + - Add GLM-4.7 model with reasoning support - [PR #18476](https://github.com/BerriAI/litellm/pull/18476) +- **[Codestral](../../docs/providers/codestral)** + - Correctly route codestral chat and FIM endpoints - [PR #18467](https://github.com/BerriAI/litellm/pull/18467) +- **[Azure AI](../../docs/providers/azure_ai)** + - Fix authentication errors at messages API via azure_ai - [PR #18500](https://github.com/BerriAI/litellm/pull/18500) + +#### New Provider Support + +- **[AWS Polly](../../docs/providers/aws_polly)** - Add AWS Polly API for TTS - [PR #18326](https://github.com/BerriAI/litellm/pull/18326) +- **[GigaChat](../../docs/providers/gigachat)** - Add GigaChat provider support - [PR #18564](https://github.com/BerriAI/litellm/pull/18564) +- **[LlamaGate](../../docs/providers/llamagate)** - Add LlamaGate as a new provider - [PR #18673](https://github.com/BerriAI/litellm/pull/18673) +- **[Abliteration AI](../../docs/providers/abliteration)** - Add abliteration.ai provider - [PR #18678](https://github.com/BerriAI/litellm/pull/18678) +- **[Manus](../../docs/providers/manus)** - Add Manus API support on /responses, GET /responses - [PR #18804](https://github.com/BerriAI/litellm/pull/18804) +- **5 AI Providers via openai_like** - Add 5 AI providers using openai_like - [PR #18362](https://github.com/BerriAI/litellm/pull/18362) ### Bug Fixes +- **[Gemini](../../docs/providers/gemini)** + - Properly catch context window exceeded errors - [PR #18283](https://github.com/BerriAI/litellm/pull/18283) + - Remove prompt caching headers as support has been removed - [PR #18579](https://github.com/BerriAI/litellm/pull/18579) + - Fix generate content request with audio file id - [PR #18745](https://github.com/BerriAI/litellm/pull/18745) + - Fix google_genai streaming adapter provider handling - [PR #18845](https://github.com/BerriAI/litellm/pull/18845) +- **[Groq](../../docs/providers/groq)** + - Remove deprecated Groq models and update model registry - [PR #18062](https://github.com/BerriAI/litellm/pull/18062) +- **General** + - Fix request body for image embedding request - [PR #18336](https://github.com/BerriAI/litellm/pull/18336) + - Fix lost tool_calls when streaming has both text and tool_calls - [PR #18316](https://github.com/BerriAI/litellm/pull/18316) + - Add all resolution for gpt-image-1.5 - [PR #18586](https://github.com/BerriAI/litellm/pull/18586) + - Fix gpt-image-1 cost calculation using token-based pricing - [PR #17906](https://github.com/BerriAI/litellm/pull/17906) + - Handle not supported region for vertex ai count tokens - [PR #18665](https://github.com/BerriAI/litellm/pull/18665) + - Fix response_format leaking into extra_body - [PR #18859](https://github.com/BerriAI/litellm/pull/18859) + - Align max_tokens with max_output_tokens for consistency - [PR #18820](https://github.com/BerriAI/litellm/pull/18820) --- @@ -97,11 +198,35 @@ Users can now see Endpoint Activity Metrics in the UI. #### Features - +- **[Responses API](../../docs/response_api)** + - Add new compact endpoint (v1/responses/compact) - [PR #18697](https://github.com/BerriAI/litellm/pull/18697) + - Support more streaming callback hooks - [PR #18513](https://github.com/BerriAI/litellm/pull/18513) + - Add mapping for reasoning effort to summary param - [PR #18635](https://github.com/BerriAI/litellm/pull/18635) + - Add output_text property to ResponsesAPIResponse - [PR #18491](https://github.com/BerriAI/litellm/pull/18491) + - Add annotations to completions responses API bridge - [PR #18754](https://github.com/BerriAI/litellm/pull/18754) +- **[Interactions API](../../docs/interactions)** + - Allow using all LiteLLM providers (interactions -> responses API bridge) - [PR #18373](https://github.com/BerriAI/litellm/pull/18373) +- **[RAG Search API](../../docs/search/index)** + - Add RAG Search/Query endpoint - [PR #18376](https://github.com/BerriAI/litellm/pull/18376) +- **[CountTokens API](../../docs/token_counting)** + - Add Bedrock as a backend API for token counting - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) +- **[Generate Content](../../docs/providers/gemini)** + - Add generate content in LLM route - [PR #18405](https://github.com/BerriAI/litellm/pull/18405) +- **General** + - Enable async_post_call_failure_hook to transform error responses - [PR #18348](https://github.com/BerriAI/litellm/pull/18348) + - Calculate total_tokens manually if missing and can be calculated - [PR #18445](https://github.com/BerriAI/litellm/pull/18445) + - Add custom llm provider to get_llm_provider when sent via UI - [PR #18638](https://github.com/BerriAI/litellm/pull/18638) #### Bugs - +- **General** + - Handle empty error objects in response conversion - [PR #18493](https://github.com/BerriAI/litellm/pull/18493) + - Preserve client error status codes in streaming mode - [PR #18698](https://github.com/BerriAI/litellm/pull/18698) + - Return json error response instead of SSE format for initial streaming errors - [PR #18757](https://github.com/BerriAI/litellm/pull/18757) + - Fix auth header for custom api base in generateContent request - [PR #18637](https://github.com/BerriAI/litellm/pull/18637) + - Tool content should be string for Deepinfra - [PR #18739](https://github.com/BerriAI/litellm/pull/18739) + - Fix incomplete usage in response object passed - [PR #18799](https://github.com/BerriAI/litellm/pull/18799) + - Unify model names to provider-defined names - [PR #18573](https://github.com/BerriAI/litellm/pull/18573) --- @@ -109,67 +234,361 @@ Users can now see Endpoint Activity Metrics in the UI. #### Features +- **SSO Configuration** + - Add SSO Role Mapping feature - [PR #18090](https://github.com/BerriAI/litellm/pull/18090) + - Add SSO Settings Page - [PR #18600](https://github.com/BerriAI/litellm/pull/18600) + - Allow adding role mappings for SSO - [PR #18593](https://github.com/BerriAI/litellm/pull/18593) + - SSO Settings Page Add Role Mappings - [PR #18677](https://github.com/BerriAI/litellm/pull/18677) + - SSO Settings Loading State + Deprecate Previous SSO Flow - [PR #18617](https://github.com/BerriAI/litellm/pull/18617) +- **Virtual Keys** + - Allow deleting key expiry - [PR #18278](https://github.com/BerriAI/litellm/pull/18278) + - Add optional query param "expand" to /key/list - [PR #18502](https://github.com/BerriAI/litellm/pull/18502) + - Key Table Loading Skeleton - [PR #18527](https://github.com/BerriAI/litellm/pull/18527) + - Allow column resizing on Keys Table - [PR #18424](https://github.com/BerriAI/litellm/pull/18424) + - Virtual Keys Table Loading State Between Pages - [PR #18619](https://github.com/BerriAI/litellm/pull/18619) + - Key and Team Router Setting - [PR #18790](https://github.com/BerriAI/litellm/pull/18790) + - Allow router_settings on Keys and Teams - [PR #18675](https://github.com/BerriAI/litellm/pull/18675) + - Use timedelta to calculate key expiry on generate - [PR #18666](https://github.com/BerriAI/litellm/pull/18666) +- **Models + Endpoints** + - Add Model Clearer Flow For Team Admins - [PR #18532](https://github.com/BerriAI/litellm/pull/18532) + - Model Page Loading State - [PR #18574](https://github.com/BerriAI/litellm/pull/18574) + - Model Page Model Provider Select Performance - [PR #18425](https://github.com/BerriAI/litellm/pull/18425) + - Model Page Sorting Sorts Entire Set - [PR #18420](https://github.com/BerriAI/litellm/pull/18420) + - Refactor Model Hub Page - [PR #18568](https://github.com/BerriAI/litellm/pull/18568) + - Add request provider form on UI - [PR #18704](https://github.com/BerriAI/litellm/pull/18704) +- **Organizations & Teams** + - Allow Organization Admins to See Organization Tab - [PR #18400](https://github.com/BerriAI/litellm/pull/18400) + - Resolve Organization Alias on Team Table - [PR #18401](https://github.com/BerriAI/litellm/pull/18401) + - Resolve Team Alias in Organization Info View - [PR #18404](https://github.com/BerriAI/litellm/pull/18404) + - Allow Organization Admins to View Their Organization Info - [PR #18417](https://github.com/BerriAI/litellm/pull/18417) + - Allow editing team_member_budget_duration in /team/update - [PR #18735](https://github.com/BerriAI/litellm/pull/18735) + - Reusable Duration Select + Team Update Member Budget Duration - [PR #18736](https://github.com/BerriAI/litellm/pull/18736) +- **Usage & Spend** + - Add Error Code Filtering on Spend Logs - [PR #18359](https://github.com/BerriAI/litellm/pull/18359) + - Add Error Code Filtering on UI - [PR #18366](https://github.com/BerriAI/litellm/pull/18366) + - Usage Page User Max Budget fix - [PR #18555](https://github.com/BerriAI/litellm/pull/18555) + - Add endpoint to Daily Activity Tables - [PR #18729](https://github.com/BerriAI/litellm/pull/18729) + - Endpoint Activity in Usage - [PR #18798](https://github.com/BerriAI/litellm/pull/18798) +- **Cost Estimator** + - Add Cost Estimator for AI Gateway - [PR #18643](https://github.com/BerriAI/litellm/pull/18643) + - Add view for estimating costs across requests - [PR #18645](https://github.com/BerriAI/litellm/pull/18645) + - Allow selecting many models for cost estimator - [PR #18653](https://github.com/BerriAI/litellm/pull/18653) +- **CloudZero** + - Improve Create and Delete Path for CloudZero - [PR #18263](https://github.com/BerriAI/litellm/pull/18263) + - Add CloudZero UI Docs - [PR #18350](https://github.com/BerriAI/litellm/pull/18350) +- **Playground** + - Add MCP test support to completions on Playground - [PR #18440](https://github.com/BerriAI/litellm/pull/18440) + - Add selectable MCP servers to the playground - [PR #18578](https://github.com/BerriAI/litellm/pull/18578) + - Add custom proxy base URL support to Playground - [PR #18661](https://github.com/BerriAI/litellm/pull/18661) +- **General UI** + - Minor Styling Changes - [PR #18310](https://github.com/BerriAI/litellm/pull/18310) + - New Badge Reusable Component - [PR #18537](https://github.com/BerriAI/litellm/pull/18537) + - Hide New Badges - [PR #18547](https://github.com/BerriAI/litellm/pull/18547) + - Change Budget page to Have Tabs - [PR #18576](https://github.com/BerriAI/litellm/pull/18576) + - Clicking on Logo Directs to Correct URL - [PR #18575](https://github.com/BerriAI/litellm/pull/18575) + - Add UI support for configuring meta URLs - [PR #18580](https://github.com/BerriAI/litellm/pull/18580) + - Expire Previous UI Session Tokens on Login - [PR #18557](https://github.com/BerriAI/litellm/pull/18557) + - Add license endpoint - [PR #18311](https://github.com/BerriAI/litellm/pull/18311) + - Router Fields Endpoint + React Query for Router Fields - [PR #18880](https://github.com/BerriAI/litellm/pull/18880) #### Bugs - +- **UI Fixes** + - Fix Key Creation MCP Settings Submit Form Unintentionally - [PR #18355](https://github.com/BerriAI/litellm/pull/18355) + - Fix UI Disappears in Development Environments - [PR #18399](https://github.com/BerriAI/litellm/pull/18399) + - Fix Disable Admin UI Flag - [PR #18397](https://github.com/BerriAI/litellm/pull/18397) + - Remove Model Analytics From Model Page - [PR #18552](https://github.com/BerriAI/litellm/pull/18552) + - Useful Links Remove Modal on Adding Links - [PR #18602](https://github.com/BerriAI/litellm/pull/18602) + - SSO Edit Modal Clear Role Mapping Values on Provider Change - [PR #18680](https://github.com/BerriAI/litellm/pull/18680) + - UI Login Case Sensitivity fix - [PR #18877](https://github.com/BerriAI/litellm/pull/18877) +- **API Fixes** + - Fix User Invite & Key Generation Email Notification Logic - [PR #18524](https://github.com/BerriAI/litellm/pull/18524) + - Normalize Proxy Config Callback - [PR #18775](https://github.com/BerriAI/litellm/pull/18775) + - Return empty data array instead of 500 when no models configured - [PR #18556](https://github.com/BerriAI/litellm/pull/18556) + - Enforce org level max budget - [PR #18813](https://github.com/BerriAI/litellm/pull/18813) --- -## AI Integrations +## Logging / Guardrail / Prompt Management Integrations -### Logging +#### Features +- **[DataDog](../../docs/proxy/logging#datadog)** + - Fix span kind fallback when parent_id missing - [PR #18418](https://github.com/BerriAI/litellm/pull/18418) +- **[Langfuse](../../docs/proxy/logging#langfuse)** + - Map Gemini cached_tokens to Langfuse cache_read_input_tokens - [PR #18614](https://github.com/BerriAI/litellm/pull/18614) +- **[Prometheus](../../docs/proxy/logging#prometheus)** + - Align prometheus metric names with DEFINED_PROMETHEUS_METRICS - [PR #18463](https://github.com/BerriAI/litellm/pull/18463) + - Add Prometheus metrics for request queue time and guardrails - [PR #17973](https://github.com/BerriAI/litellm/pull/17973) + - Add caching metrics for cache hits, misses, and tokens - [PR #18755](https://github.com/BerriAI/litellm/pull/18755) + - Skip metrics for invalid API key requests - [PR #18788](https://github.com/BerriAI/litellm/pull/18788) +- **[Braintrust](../../docs/proxy/logging#braintrust)** + - Pass span_attributes in async logging and skip tags on non-root spans - [PR #18409](https://github.com/BerriAI/litellm/pull/18409) +- **[CloudZero](../../docs/proxy/logging#cloudzero)** + - Add user email to CloudZero - [PR #18584](https://github.com/BerriAI/litellm/pull/18584) +- **[OpenTelemetry](../../docs/proxy/logging#opentelemetry)** + - Use already configured opentelemetry providers - [PR #18279](https://github.com/BerriAI/litellm/pull/18279) + - Prevent LiteLLM from closing external OTEL spans - [PR #18553](https://github.com/BerriAI/litellm/pull/18553) + - Allow configuring arize project name for OpenTelemetry service name - [PR #18738](https://github.com/BerriAI/litellm/pull/18738) +- **[LangSmith](../../docs/proxy/logging#langsmith)** + - Add support for LangSmith organization-scoped API keys with tenant ID - [PR #18623](https://github.com/BerriAI/litellm/pull/18623) +- **[Generic API Logger](../../docs/proxy/logging#generic-api-logger)** + - Add log_format option to GenericAPILogger - [PR #18587](https://github.com/BerriAI/litellm/pull/18587) +- **[Focus](../../docs/proxy/logging#focus)** + - Add Focus export support - [PR #18802](https://github.com/BerriAI/litellm/pull/18802) -### Guardrails +#### Guardrails +- **[Content Filter](../../docs/proxy/guardrails/litellm_content_filter)** + - Add content filter logs page - [PR #18335](https://github.com/BerriAI/litellm/pull/18335) + - Log actual event type for guardrails - [PR #18489](https://github.com/BerriAI/litellm/pull/18489) +- **[Qualifire](../../docs/proxy/guardrails/qualifire)** + - Add Qualifire guardrails - [PR #18594](https://github.com/BerriAI/litellm/pull/18594) + - Add Qualifire eval webhook - [PR #18836](https://github.com/BerriAI/litellm/pull/18836) +- **[Lasso](../../docs/proxy/guardrails/lasso)** + - Add Lasso guardrail API docs - [PR #18652](https://github.com/BerriAI/litellm/pull/18652) +- **[Levo AI](../../docs/proxy/guardrails/levo)** + - Add Levo AI integration - [PR #18529](https://github.com/BerriAI/litellm/pull/18529) +- **[Noma](../../docs/proxy/guardrails/noma)** + - Add support MCP guardrail to Noma - [PR #18668](https://github.com/BerriAI/litellm/pull/18668) +- **[Bedrock Guardrails](../../docs/proxy/guardrails/bedrock)** + - Remove redundant Bedrock guardrail block handling - [PR #18634](https://github.com/BerriAI/litellm/pull/18634) +- **General** + - Generic guardrail API update - [PR #18647](https://github.com/BerriAI/litellm/pull/18647) + - Prevent proxy startup failures from case-sensitive tool permission guardrail validation - [PR #18662](https://github.com/BerriAI/litellm/pull/18662) + - Extend case normalization to ALL guardrail types - [PR #18664](https://github.com/BerriAI/litellm/pull/18664) + - Fix MCP handling in unified guardrail - [PR #18630](https://github.com/BerriAI/litellm/pull/18630) + - Fix embeddings calltype for guardrail precallhook - [PR #18740](https://github.com/BerriAI/litellm/pull/18740) +#### New Integration -### Secret Managers - - +- **[SigNoz](../../docs/observability/signoz)** - Add SigNoz integration to observability docs - [PR #18726](https://github.com/BerriAI/litellm/pull/18726) --- ## Spend Tracking, Budgets and Rate Limiting - +- **Platform Fee / Margins** - Add support for Platform Fee / Margins - [PR #18427](https://github.com/BerriAI/litellm/pull/18427) +- **Negative Budget Validation** - Add validation for negative budget - [PR #18583](https://github.com/BerriAI/litellm/pull/18583) +- **Cost Calculation Fixes** + - Correct cost calculation when reasoning_tokens are without text_tokens - [PR #18607](https://github.com/BerriAI/litellm/pull/18607) + - Fix background cost tracking tests - [PR #18588](https://github.com/BerriAI/litellm/pull/18588) +- **Tag Routing** - Support toggling tag matching between ANY and ALL - [PR #18776](https://github.com/BerriAI/litellm/pull/18776) --- ## MCP Gateway - - ---- - -## Agent Gateway (A2A) - - +- **MCP Global Mode** - Add MCP global mode - [PR #18639](https://github.com/BerriAI/litellm/pull/18639) +- **MCP Server Visibility** - Add configurable MCP server visibility - [PR #18681](https://github.com/BerriAI/litellm/pull/18681) +- **MCP Registry** - Add MCP registry - [PR #18850](https://github.com/BerriAI/litellm/pull/18850) +- **MCP Stdio Header** - Support MCP stdio header env overrides - [PR #18324](https://github.com/BerriAI/litellm/pull/18324) +- **Parallel Tool Fetching** - Parallelize tool fetching from multiple MCP servers - [PR #18627](https://github.com/BerriAI/litellm/pull/18627) +- **Optimize MCP Server Listing** - Separate health checks for optimized listing - [PR #18530](https://github.com/BerriAI/litellm/pull/18530) +- **Auth Improvements** + - Require auth for MCP connection test endpoint - [PR #18290](https://github.com/BerriAI/litellm/pull/18290) + - Fix MCP gateway OAuth2 auth issues and ClosedResourceError - [PR #18281](https://github.com/BerriAI/litellm/pull/18281) +- **Bug Fixes** + - Fix health status - [PR #18443](https://github.com/BerriAI/litellm/pull/18443) + - Fix openapi to mcp - [PR #18597](https://github.com/BerriAI/litellm/pull/18597) + - Remove exec() usage and handle invalid OpenAPI parameter names - [PR #18480](https://github.com/BerriAI/litellm/pull/18480) + - Fix MCP error in multiple servers - [PR #18855](https://github.com/BerriAI/litellm/pull/18855) +- **Migrate MCP Fetching Logic to React Query** - [PR #18352](https://github.com/BerriAI/litellm/pull/18352) --- ## Performance / Loadbalancing / Reliability improvements +- **92.7% Faster Provider Config Lookup** - LiteLLM now stresses LLM providers 2.5x more - [PR #18867](https://github.com/BerriAI/litellm/pull/18867) +- **Lazy Loading Improvements** + - Consolidate lazy import handlers with registry pattern - [PR #18389](https://github.com/BerriAI/litellm/pull/18389) + - Complete lazy loading migration for all 180+ LLM config classes - [PR #18392](https://github.com/BerriAI/litellm/pull/18392) + - Lazy load additional components (types, callbacks, utilities) - [PR #18396](https://github.com/BerriAI/litellm/pull/18396) + - Add lazy loading for get_llm_provider - [PR #18591](https://github.com/BerriAI/litellm/pull/18591) + - Lazy-load heavy audio library and loggers - [PR #18592](https://github.com/BerriAI/litellm/pull/18592) + - Lazy load 9 heavy imports in litellm/utils.py - [PR #18595](https://github.com/BerriAI/litellm/pull/18595) + - Lazy load heavy imports to improve import time and memory usage - [PR #18610](https://github.com/BerriAI/litellm/pull/18610) + - Implement lazy loading for provider configs, model info classes, streaming handlers - [PR #18611](https://github.com/BerriAI/litellm/pull/18611) + - Lazy load 15 additional imports - [PR #18613](https://github.com/BerriAI/litellm/pull/18613) + - Lazy load 15+ unused imports - [PR #18616](https://github.com/BerriAI/litellm/pull/18616) + - Lazy load DatadogLLMObsInitParams - [PR #18658](https://github.com/BerriAI/litellm/pull/18658) + - Migrate utils.py lazy imports to registry pattern - [PR #18657](https://github.com/BerriAI/litellm/pull/18657) + - Lazy load get_llm_provider and remove_index_from_tool_calls - [PR #18608](https://github.com/BerriAI/litellm/pull/18608) +- **Router Improvements** + - Validate routing_strategy at startup to fail fast with helpful error - [PR #18624](https://github.com/BerriAI/litellm/pull/18624) + - Correct num_retries tracking in retry logic - [PR #18712](https://github.com/BerriAI/litellm/pull/18712) + - Improve error messages and validation for wildcard routing with multiple credentials - [PR #18629](https://github.com/BerriAI/litellm/pull/18629) +- **Memory Improvements** + - Add memory pattern detection test and fix bad memory patterns - [PR #18589](https://github.com/BerriAI/litellm/pull/18589) + - Add unbounded data structure detection to memory test - [PR #18590](https://github.com/BerriAI/litellm/pull/18590) + - Add memory leak detection tests with CI integration - [PR #18881](https://github.com/BerriAI/litellm/pull/18881) +- **Database** + - Add idx on LOWER(user_email) for faster duplicate email checks - [PR #18828](https://github.com/BerriAI/litellm/pull/18828) + - Proactive RDS IAM token refresh to prevent 15-min connection failed - [PR #18795](https://github.com/BerriAI/litellm/pull/18795) + - Clarify database_connection_pool_limit applies per worker - [PR #18780](https://github.com/BerriAI/litellm/pull/18780) + - Make base_connection_pool_limit default value the same - [PR #18721](https://github.com/BerriAI/litellm/pull/18721) +- **Docker** + - Add libsndfile to database Docker image for audio processing - [PR #18612](https://github.com/BerriAI/litellm/pull/18612) + - Add line_profiler support for performance analysis and fix Windows CRLF issues - [PR #18773](https://github.com/BerriAI/litellm/pull/18773) +- **Helm** + - Add lifecycle support to Helm charts - [PR #18517](https://github.com/BerriAI/litellm/pull/18517) +- **Authentication** + - Add Kubernetes ServiceAccount JWT authentication support - [PR #18055](https://github.com/BerriAI/litellm/pull/18055) + - Use async anthropic client to prevent event loop blocking - [PR #18435](https://github.com/BerriAI/litellm/pull/18435) +- **Logging Worker** + - Handle event loop changes in multiprocessing - [PR #18423](https://github.com/BerriAI/litellm/pull/18423) +- **Security** + - Prevent expired key plaintext leak in error response - [PR #18860](https://github.com/BerriAI/litellm/pull/18860) + - Mask extra header secrets in model info - [PR #18822](https://github.com/BerriAI/litellm/pull/18822) + - Prevent duplicate User-Agent tags in request_tags - [PR #18723](https://github.com/BerriAI/litellm/pull/18723) + - Properly use litellm api keys - [PR #18832](https://github.com/BerriAI/litellm/pull/18832) +- **Misc** + - Remove double imports in main.py - [PR #18406](https://github.com/BerriAI/litellm/pull/18406) + - Add LITELLM_DISABLE_LAZY_LOADING env var to fix VCR cassette creation issue - [PR #18725](https://github.com/BerriAI/litellm/pull/18725) + - Add xiaomi_mimo to LlmProviders enum to fix router support - [PR #18819](https://github.com/BerriAI/litellm/pull/18819) + - Allow installation with current grpcio on old Python - [PR #18473](https://github.com/BerriAI/litellm/pull/18473) + - Add Custom CA certificates to boto3 clients - [PR #18852](https://github.com/BerriAI/litellm/pull/18852) + - Fix bedrock_cache, metadata and max_model_budget - [PR #18872](https://github.com/BerriAI/litellm/pull/18872) + - Fix LiteLLM SDK embedding headers missing field - [PR #18844](https://github.com/BerriAI/litellm/pull/18844) + - Put automatic reasoning summary inclusion behind feat flag - [PR #18688](https://github.com/BerriAI/litellm/pull/18688) + - turn_off_message_logging Does Not Redact Request Messages in proxy_server_request Field - [PR #18897](https://github.com/BerriAI/litellm/pull/18897) --- ## Documentation Updates +- **Provider Documentation** + - Update MiniMax docs to be in proper format - [PR #18403](https://github.com/BerriAI/litellm/pull/18403) + - Add docs for 5 AI providers - [PR #18388](https://github.com/BerriAI/litellm/pull/18388) + - Fix gpt-5-mini reasoning_effort supported values - [PR #18346](https://github.com/BerriAI/litellm/pull/18346) + - Fix PDF documentation inconsistency in Anthropic page - [PR #18816](https://github.com/BerriAI/litellm/pull/18816) + - Update OpenRouter docs to include embedding support - [PR #18874](https://github.com/BerriAI/litellm/pull/18874) + - Add LITELLM_REASONING_AUTO_SUMMARY in doc - [PR #18705](https://github.com/BerriAI/litellm/pull/18705) +- **MCP Documentation** + - Agentcore MCP server docs - [PR #18603](https://github.com/BerriAI/litellm/pull/18603) + - Mention MCP prompt/resources types in overview - [PR #18669](https://github.com/BerriAI/litellm/pull/18669) + - Add Focus docs - [PR #18837](https://github.com/BerriAI/litellm/pull/18837) +- **Guardrails Documentation** + - Qualifire docs hotfix - [PR #18724](https://github.com/BerriAI/litellm/pull/18724) +- **Infrastructure Documentation** + - IAM Roles Anywhere docs - [PR #18559](https://github.com/BerriAI/litellm/pull/18559) + - Fix formatting in proxy configs documentation - [PR #18498](https://github.com/BerriAI/litellm/pull/18498) + - Fix GCS cache docs missing for proxy mode - [PR #13328](https://github.com/BerriAI/litellm/pull/13328) + - Fix how to execute cloudzero sql - [PR #18841](https://github.com/BerriAI/litellm/pull/18841) +- **General** + - LiteLLM adopters section - [PR #18605](https://github.com/BerriAI/litellm/pull/18605) + - Remove redundant comments about setting litellm.callbacks - [PR #18711](https://github.com/BerriAI/litellm/pull/18711) + - Update header to be markdown bold by removing space - [PR #18846](https://github.com/BerriAI/litellm/pull/18846) + - Manus docs - new provider - [PR #18817](https://github.com/BerriAI/litellm/pull/18817) --- ## Infrastructure / CI/CD +- **CI Fixes** + - Fix CI: Revert security scan changes and add GitGuardian ignore rules - [PR #18358](https://github.com/BerriAI/litellm/pull/18358) + - Fix check_code_and_doc_quality - [PR #18560](https://github.com/BerriAI/litellm/pull/18560) + - Fix litellm_mapped_tests_llms - [PR #18563](https://github.com/BerriAI/litellm/pull/18563) + - Fix litellm_utils_testing - [PR #18565](https://github.com/BerriAI/litellm/pull/18565) + - Fix litellm_security_tests - [PR #18567](https://github.com/BerriAI/litellm/pull/18567) + - Fix litellm_mapped_tests_proxy - [PR #18572](https://github.com/BerriAI/litellm/pull/18572) + - De-duplicate Docker Database Build - [PR #18561](https://github.com/BerriAI/litellm/pull/18561) + - Fix component label automation to prevent false positives - [PR #18765](https://github.com/BerriAI/litellm/pull/18765) + - Update issue labeling with working regex pattern - [PR #18821](https://github.com/BerriAI/litellm/pull/18821) + - Prevent Prisma migration workflow from running in forks - [PR #18863](https://github.com/BerriAI/litellm/pull/18863) +- **UI Testing** + - E2E Tests Setup - [PR #18501](https://github.com/BerriAI/litellm/pull/18501) + - E2E Tests: Sidebar Navigation - [PR #18528](https://github.com/BerriAI/litellm/pull/18528) + - E2E Tests: Parity With Legacy Tests - [PR #18533](https://github.com/BerriAI/litellm/pull/18533) + - Unit Testing Coverage With v8 - [PR #18548](https://github.com/BerriAI/litellm/pull/18548) + - Test for React Query Hooks - [PR #18577](https://github.com/BerriAI/litellm/pull/18577) + - E2E Test: Can View Admin Setting Page - [PR #18682](https://github.com/BerriAI/litellm/pull/18682) + - E2E Test: New DB Branch Per Test Run - [PR #18885](https://github.com/BerriAI/litellm/pull/18885) + - Adding Unit Tests to Increase Coverage - [PR #18601](https://github.com/BerriAI/litellm/pull/18601), [PR #18618](https://github.com/BerriAI/litellm/pull/18618), [PR #18742](https://github.com/BerriAI/litellm/pull/18742), [PR #18848](https://github.com/BerriAI/litellm/pull/18848) + - E2E Test: Add Model - See Models from Selected Provider - [PR #18615](https://github.com/BerriAI/litellm/pull/18615) + - E2E Test: Refactor Page Settings + Test for Page Navigation - [PR #18849](https://github.com/BerriAI/litellm/pull/18849) +- **React Query Migration** + - useQuery Hooks Now Depend on useAuthorized - [PR #18416](https://github.com/BerriAI/litellm/pull/18416) + - Key Table to Use Optional "expand" query - [PR #18503](https://github.com/BerriAI/litellm/pull/18503) + - Refactor Keys Table - [PR #18504](https://github.com/BerriAI/litellm/pull/18504) + - Virtual Keys Table to use React Query - [PR #18506](https://github.com/BerriAI/litellm/pull/18506) + - Deprecate useTeams - [PR #18404](https://github.com/BerriAI/litellm/pull/18404) --- ## New Contributors +* @prasadkona made their first contribution in [PR #18349](https://github.com/BerriAI/litellm/pull/18349) +* @lucasrothman made their first contribution in [PR #18283](https://github.com/BerriAI/litellm/pull/18283) +* @aggeentik made their first contribution in [PR #18317](https://github.com/BerriAI/litellm/pull/18317) +* @mihidumh made their first contribution in [PR #18361](https://github.com/BerriAI/litellm/pull/18361) +* @Prazeina made their first contribution in [PR #18498](https://github.com/BerriAI/litellm/pull/18498) +* @systec-dk made their first contribution in [PR #18500](https://github.com/BerriAI/litellm/pull/18500) +* @xuan07t2 made their first contribution in [PR #18514](https://github.com/BerriAI/litellm/pull/18514) +* @RensDimmendaal made their first contribution in [PR #18190](https://github.com/BerriAI/litellm/pull/18190) +* @yurekami made their first contribution in [PR #18483](https://github.com/BerriAI/litellm/pull/18483) +* @agertz7 made their first contribution in [PR #18556](https://github.com/BerriAI/litellm/pull/18556) +* @yudelevi made their first contribution in [PR #18550](https://github.com/BerriAI/litellm/pull/18550) +* @smallp made their first contribution in [PR #18536](https://github.com/BerriAI/litellm/pull/18536) +* @kevinpauer made their first contribution in [PR #18569](https://github.com/BerriAI/litellm/pull/18569) +* @cansakiroglu made their first contribution in [PR #18517](https://github.com/BerriAI/litellm/pull/18517) +* @dee-walia20 made their first contribution in [PR #18432](https://github.com/BerriAI/litellm/pull/18432) +* @luxinfeng made their first contribution in [PR #18477](https://github.com/BerriAI/litellm/pull/18477) +* @cantalupo555 made their first contribution in [PR #18476](https://github.com/BerriAI/litellm/pull/18476) +* @andersk made their first contribution in [PR #18473](https://github.com/BerriAI/litellm/pull/18473) +* @majiayu000 made their first contribution in [PR #18467](https://github.com/BerriAI/litellm/pull/18467) +* @amangupta-20 made their first contribution in [PR #18529](https://github.com/BerriAI/litellm/pull/18529) +* @hamzaq453 made their first contribution in [PR #18480](https://github.com/BerriAI/litellm/pull/18480) +* @ktsaou made their first contribution in [PR #18627](https://github.com/BerriAI/litellm/pull/18627) +* @FlibbertyGibbitz made their first contribution in [PR #18624](https://github.com/BerriAI/litellm/pull/18624) +* @drorIvry made their first contribution in [PR #18594](https://github.com/BerriAI/litellm/pull/18594) +* @urainshah made their first contribution in [PR #18524](https://github.com/BerriAI/litellm/pull/18524) +* @mangabits made their first contribution in [PR #18279](https://github.com/BerriAI/litellm/pull/18279) +* @0717376 made their first contribution in [PR #18564](https://github.com/BerriAI/litellm/pull/18564) +* @nmgarza5 made their first contribution in [PR #17330](https://github.com/BerriAI/litellm/pull/17330) +* @wileykestner made their first contribution in [PR #18445](https://github.com/BerriAI/litellm/pull/18445) +* @minijeong-log made their first contribution in [PR #14440](https://github.com/BerriAI/litellm/pull/14440) +* @Isaac4real made their first contribution in [PR #18710](https://github.com/BerriAI/litellm/pull/18710) +* @marukaz made their first contribution in [PR #18711](https://github.com/BerriAI/litellm/pull/18711) +* @rohitravirane made their first contribution in [PR #18712](https://github.com/BerriAI/litellm/pull/18712) +* @lizzzcai made their first contribution in [PR #18714](https://github.com/BerriAI/litellm/pull/18714) +* @hkd987 made their first contribution in [PR #18673](https://github.com/BerriAI/litellm/pull/18673) +* @Mr-Pepe made their first contribution in [PR #18674](https://github.com/BerriAI/litellm/pull/18674) +* @gkarthi-signoz made their first contribution in [PR #18726](https://github.com/BerriAI/litellm/pull/18726) +* @Tianduo16 made their first contribution in [PR #18723](https://github.com/BerriAI/litellm/pull/18723) +* @wilsonjr made their first contribution in [PR #18721](https://github.com/BerriAI/litellm/pull/18721) +* @abliteration-ai made their first contribution in [PR #18678](https://github.com/BerriAI/litellm/pull/18678) +* @danialkhan02 made their first contribution in [PR #18770](https://github.com/BerriAI/litellm/pull/18770) +* @ihower made their first contribution in [PR #18409](https://github.com/BerriAI/litellm/pull/18409) +* @elkkhan made their first contribution in [PR #18391](https://github.com/BerriAI/litellm/pull/18391) +* @runixer made their first contribution in [PR #18435](https://github.com/BerriAI/litellm/pull/18435) +* @choby-shun made their first contribution in [PR #18776](https://github.com/BerriAI/litellm/pull/18776) +* @jutaz made their first contribution in [PR #18853](https://github.com/BerriAI/litellm/pull/18853) +* @sjmatta made their first contribution in [PR #18250](https://github.com/BerriAI/litellm/pull/18250) +* @andres-ortizl made their first contribution in [PR #18856](https://github.com/BerriAI/litellm/pull/18856) +* @gauthiermartin made their first contribution in [PR #18844](https://github.com/BerriAI/litellm/pull/18844) +* @mel2oo made their first contribution in [PR #18845](https://github.com/BerriAI/litellm/pull/18845) +* @DominikHallab made their first contribution in [PR #18846](https://github.com/BerriAI/litellm/pull/18846) +* @ji-chuan-che made their first contribution in [PR #18540](https://github.com/BerriAI/litellm/pull/18540) +* @raghav-stripe made their first contribution in [PR #18858](https://github.com/BerriAI/litellm/pull/18858) +* @akraines made their first contribution in [PR #18629](https://github.com/BerriAI/litellm/pull/18629) +* @otaviofbrito made their first contribution in [PR #18665](https://github.com/BerriAI/litellm/pull/18665) +* @chetanchoudhary-sumo made their first contribution in [PR #18587](https://github.com/BerriAI/litellm/pull/18587) +* @pascalwhoop made their first contribution in [PR #13328](https://github.com/BerriAI/litellm/pull/13328) +* @orgersh92 made their first contribution in [PR #18652](https://github.com/BerriAI/litellm/pull/18652) +* @DevajMody made their first contribution in [PR #18497](https://github.com/BerriAI/litellm/pull/18497) +* @matt-greathouse made their first contribution in [PR #18247](https://github.com/BerriAI/litellm/pull/18247) +* @emerzon made their first contribution in [PR #18290](https://github.com/BerriAI/litellm/pull/18290) +* @Eric84626 made their first contribution in [PR #18281](https://github.com/BerriAI/litellm/pull/18281) +* @LukasdeBoer made their first contribution in [PR #18055](https://github.com/BerriAI/litellm/pull/18055) +* @LingXuanYin made their first contribution in [PR #18513](https://github.com/BerriAI/litellm/pull/18513) +* @krisxia0506 made their first contribution in [PR #18698](https://github.com/BerriAI/litellm/pull/18698) +* @LouisShark made their first contribution in [PR #18414](https://github.com/BerriAI/litellm/pull/18414) --- ## Full Changelog -**[View complete changelog on GitHub](https://github.com/BerriAI/litellm/compare/v1.80.11...v1.80.13.rc.1)** +**[View complete changelog on GitHub](https://github.com/BerriAI/litellm/compare/v1.80.11.rc.1...v1.80.14.rc.1)** + From a4758ab53245bbeda2fe3b7e22f1ff175b65a0de Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 14:57:16 -0800 Subject: [PATCH 057/114] QA release notes --- .../release_notes/v1.80.14/index.md | 110 ++++++++---------- 1 file changed, 50 insertions(+), 60 deletions(-) diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index 9765487e690..9d806705bca 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -49,7 +49,7 @@ pip install litellm==1.80.14 - **MiniMax Provider** - [Full support for MiniMax chat completions, TTS, and Anthropic native endpoint](../../docs/providers/minimax) - **AWS Polly TTS** - [New TTS provider using AWS Polly API](../../docs/providers/aws_polly) - **SSO Role Mapping** - Configure role mappings for SSO providers directly in the UI -- **Cost Estimator** - [New UI tool for estimating costs across multiple models and requests](../../docs/proxy/cost_estimator) +- **Cost Estimator** - New UI tool for estimating costs across multiple models and requests - **MCP Global Mode** - [Configure MCP servers globally with visibility controls](../../docs/mcp) - **Interactions API Bridge** - [Use all LiteLLM providers with the Interactions API](../../docs/interactions) - **RAG Query Endpoint** - [New RAG Search/Query endpoint for retrieval-augmented generation](../../docs/search/index) @@ -70,6 +70,29 @@ Users can now see Endpoint Activity Metrics in the UI. --- +## New Providers and Endpoints + +### New Providers (6 new providers) + +| Provider | Supported LiteLLM Endpoints | Description | +| -------- | ------------------- | ----------- | +| [Manus](../../docs/providers/manus) | `/responses`, `GET /responses`, `/files` | Manus API for agentic workflows with file management | +| [MiniMax](../../docs/providers/minimax) | `/chat/completions`, `/audio/speech` | MiniMax chat completions and TTS support | +| [AWS Polly](../../docs/providers/aws_polly) | `/audio/speech` | AWS Polly text-to-speech API | +| [GigaChat](../../docs/providers/gigachat) | `/chat/completions` | GigaChat provider for Russian language AI | +| [LlamaGate](../../docs/providers/llamagate) | `/chat/completions`, `/embeddings` | LlamaGate provider with 15+ models | +| [Abliteration AI](../../docs/providers/abliteration) | `/chat/completions` | Abliteration.ai provider support | + +### New LLM API Endpoints (3 new endpoints) + +| Endpoint | Method | Description | Documentation | +| -------- | ------ | ----------- | ------------- | +| `/responses/compact` | POST | Compact responses API endpoint | [Docs](../../docs/response_api) | +| `/rag/query` | POST | RAG Search/Query endpoint | [Docs](../../docs/search/index) | +| `/containers/{id}/files` | POST | Upload files to containers | [Docs](../../docs/container_files) | + +--- + ## New Models / Updated Models #### New Model Support (100+ new models) @@ -120,7 +143,7 @@ Users can now see Endpoint Activity Metrics in the UI. - Add thought_signatures to VertexGeminiConfig - [PR #18853](https://github.com/BerriAI/litellm/pull/18853) - Add support for Vertex AI API keys - [PR #18806](https://github.com/BerriAI/litellm/pull/18806) - Add zai glm-4.7 model support - [PR #18782](https://github.com/BerriAI/litellm/pull/18782) -- **[Azure](../../docs/providers/azure)** +- **[Azure](../../docs/providers/azure/azure)** - Add Azure gpt-image-1.5 pricing to cost map - [PR #18347](https://github.com/BerriAI/litellm/pull/18347) - Add azure/gpt-5.2-chat model - [PR #18361](https://github.com/BerriAI/litellm/pull/18361) - Add support for image generation via Azure AD token - [PR #18413](https://github.com/BerriAI/litellm/pull/18413) @@ -129,7 +152,6 @@ Users can now see Endpoint Activity Metrics in the UI. - **[Bedrock](../../docs/providers/bedrock)** - Add Bedrock Kimi K2 model support - [PR #18797](https://github.com/BerriAI/litellm/pull/18797) - Add support for model id in bedrock passthrough - [PR #18800](https://github.com/BerriAI/litellm/pull/18800) - - Add Bedrock as a backend API for token counting - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) - Fix Nova model detection for Bedrock provider - [PR #18250](https://github.com/BerriAI/litellm/pull/18250) - Ensure toolUse.input is always a dict when converting from OpenAI format - [PR #18414](https://github.com/BerriAI/litellm/pull/18414) - **[Databricks](../../docs/providers/databricks)** @@ -149,7 +171,7 @@ Users can now see Endpoint Activity Metrics in the UI. - **[Ollama](../../docs/providers/ollama)** - Add dimensions for ollama embedding - [PR #18536](https://github.com/BerriAI/litellm/pull/18536) - Extract pure base64 data from data URLs for Ollama - [PR #18465](https://github.com/BerriAI/litellm/pull/18465) -- **[Watsonx](../../docs/providers/watsonx)** +- **[Watsonx](../../docs/providers/watsonx/index)** - Add Watsonx fields support - [PR #18569](https://github.com/BerriAI/litellm/pull/18569) - Fix Watsonx Audio Transcription - filter model field - [PR #18810](https://github.com/BerriAI/litellm/pull/18810) - **[SAP](../../docs/providers/sap)** @@ -183,12 +205,13 @@ Users can now see Endpoint Activity Metrics in the UI. - Fix google_genai streaming adapter provider handling - [PR #18845](https://github.com/BerriAI/litellm/pull/18845) - **[Groq](../../docs/providers/groq)** - Remove deprecated Groq models and update model registry - [PR #18062](https://github.com/BerriAI/litellm/pull/18062) +- **[Vertex AI](../../docs/providers/vertex)** + - Handle unsupported region for Vertex AI count tokens endpoint - [PR #18665](https://github.com/BerriAI/litellm/pull/18665) - **General** - Fix request body for image embedding request - [PR #18336](https://github.com/BerriAI/litellm/pull/18336) - Fix lost tool_calls when streaming has both text and tool_calls - [PR #18316](https://github.com/BerriAI/litellm/pull/18316) - Add all resolution for gpt-image-1.5 - [PR #18586](https://github.com/BerriAI/litellm/pull/18586) - Fix gpt-image-1 cost calculation using token-based pricing - [PR #17906](https://github.com/BerriAI/litellm/pull/17906) - - Handle not supported region for vertex ai count tokens - [PR #18665](https://github.com/BerriAI/litellm/pull/18665) - Fix response_format leaking into extra_body - [PR #18859](https://github.com/BerriAI/litellm/pull/18859) - Align max_tokens with max_output_tokens for consistency - [PR #18820](https://github.com/BerriAI/litellm/pull/18820) @@ -208,7 +231,7 @@ Users can now see Endpoint Activity Metrics in the UI. - Allow using all LiteLLM providers (interactions -> responses API bridge) - [PR #18373](https://github.com/BerriAI/litellm/pull/18373) - **[RAG Search API](../../docs/search/index)** - Add RAG Search/Query endpoint - [PR #18376](https://github.com/BerriAI/litellm/pull/18376) -- **[CountTokens API](../../docs/token_counting)** +- **[CountTokens API](../../docs/completion/token_usage)** - Add Bedrock as a backend API for token counting - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) - **[Generate Content](../../docs/providers/gemini)** - Add generate content in LLM route - [PR #18405](https://github.com/BerriAI/litellm/pull/18405) @@ -281,8 +304,8 @@ Users can now see Endpoint Activity Metrics in the UI. - Add selectable MCP servers to the playground - [PR #18578](https://github.com/BerriAI/litellm/pull/18578) - Add custom proxy base URL support to Playground - [PR #18661](https://github.com/BerriAI/litellm/pull/18661) - **General UI** - - Minor Styling Changes - [PR #18310](https://github.com/BerriAI/litellm/pull/18310) - - New Badge Reusable Component - [PR #18537](https://github.com/BerriAI/litellm/pull/18537) + - UI styling improvements and fixes - [PR #18310](https://github.com/BerriAI/litellm/pull/18310) + - Add reusable "New" badge component for feature highlights - [PR #18537](https://github.com/BerriAI/litellm/pull/18537) - Hide New Badges - [PR #18547](https://github.com/BerriAI/litellm/pull/18547) - Change Budget page to Have Tabs - [PR #18576](https://github.com/BerriAI/litellm/pull/18576) - Clicking on Logo Directs to Correct URL - [PR #18575](https://github.com/BerriAI/litellm/pull/18575) @@ -309,9 +332,18 @@ Users can now see Endpoint Activity Metrics in the UI. --- -## Logging / Guardrail / Prompt Management Integrations +## AI Integrations -#### Features +### New Integrations (4 new integrations) + +| Integration | Type | Description | +| ----------- | ---- | ----------- | +| [Focus](../../docs/observability/focus) | Logging | Focus export support for observability - [PR #18802](https://github.com/BerriAI/litellm/pull/18802) | +| [SigNoz](../../docs/observability/signoz) | Logging | SigNoz integration for observability - [PR #18726](https://github.com/BerriAI/litellm/pull/18726) | +| [Qualifire](../../docs/proxy/guardrails/qualifire) | Guardrails | Qualifire guardrails and eval webhook - [PR #18594](https://github.com/BerriAI/litellm/pull/18594) | +| Levo AI | Guardrails | Levo AI integration for security - [PR #18529](https://github.com/BerriAI/litellm/pull/18529) | + +### Logging - **[DataDog](../../docs/proxy/logging#datadog)** - Fix span kind fallback when parent_id missing - [PR #18418](https://github.com/BerriAI/litellm/pull/18418) @@ -334,23 +366,18 @@ Users can now see Endpoint Activity Metrics in the UI. - Add support for LangSmith organization-scoped API keys with tenant ID - [PR #18623](https://github.com/BerriAI/litellm/pull/18623) - **[Generic API Logger](../../docs/proxy/logging#generic-api-logger)** - Add log_format option to GenericAPILogger - [PR #18587](https://github.com/BerriAI/litellm/pull/18587) -- **[Focus](../../docs/proxy/logging#focus)** - - Add Focus export support - [PR #18802](https://github.com/BerriAI/litellm/pull/18802) -#### Guardrails +### Guardrails - **[Content Filter](../../docs/proxy/guardrails/litellm_content_filter)** - Add content filter logs page - [PR #18335](https://github.com/BerriAI/litellm/pull/18335) - Log actual event type for guardrails - [PR #18489](https://github.com/BerriAI/litellm/pull/18489) - **[Qualifire](../../docs/proxy/guardrails/qualifire)** - - Add Qualifire guardrails - [PR #18594](https://github.com/BerriAI/litellm/pull/18594) - Add Qualifire eval webhook - [PR #18836](https://github.com/BerriAI/litellm/pull/18836) -- **[Lasso](../../docs/proxy/guardrails/lasso)** +- **[Lasso Security](../../docs/proxy/guardrails/lasso_security)** - Add Lasso guardrail API docs - [PR #18652](https://github.com/BerriAI/litellm/pull/18652) -- **[Levo AI](../../docs/proxy/guardrails/levo)** - - Add Levo AI integration - [PR #18529](https://github.com/BerriAI/litellm/pull/18529) -- **[Noma](../../docs/proxy/guardrails/noma)** - - Add support MCP guardrail to Noma - [PR #18668](https://github.com/BerriAI/litellm/pull/18668) +- **[Noma Security](../../docs/proxy/guardrails/noma_security)** + - Add MCP guardrail support for Noma - [PR #18668](https://github.com/BerriAI/litellm/pull/18668) - **[Bedrock Guardrails](../../docs/proxy/guardrails/bedrock)** - Remove redundant Bedrock guardrail block handling - [PR #18634](https://github.com/BerriAI/litellm/pull/18634) - **General** @@ -360,10 +387,6 @@ Users can now see Endpoint Activity Metrics in the UI. - Fix MCP handling in unified guardrail - [PR #18630](https://github.com/BerriAI/litellm/pull/18630) - Fix embeddings calltype for guardrail precallhook - [PR #18740](https://github.com/BerriAI/litellm/pull/18740) -#### New Integration - -- **[SigNoz](../../docs/observability/signoz)** - Add SigNoz integration to observability docs - [PR #18726](https://github.com/BerriAI/litellm/pull/18726) - --- ## Spend Tracking, Budgets and Rate Limiting @@ -389,10 +412,10 @@ Users can now see Endpoint Activity Metrics in the UI. - Require auth for MCP connection test endpoint - [PR #18290](https://github.com/BerriAI/litellm/pull/18290) - Fix MCP gateway OAuth2 auth issues and ClosedResourceError - [PR #18281](https://github.com/BerriAI/litellm/pull/18281) - **Bug Fixes** - - Fix health status - [PR #18443](https://github.com/BerriAI/litellm/pull/18443) - - Fix openapi to mcp - [PR #18597](https://github.com/BerriAI/litellm/pull/18597) - - Remove exec() usage and handle invalid OpenAPI parameter names - [PR #18480](https://github.com/BerriAI/litellm/pull/18480) - - Fix MCP error in multiple servers - [PR #18855](https://github.com/BerriAI/litellm/pull/18855) + - Fix MCP server health status reporting - [PR #18443](https://github.com/BerriAI/litellm/pull/18443) + - Fix OpenAPI to MCP tool conversion - [PR #18597](https://github.com/BerriAI/litellm/pull/18597) + - Remove exec() usage and handle invalid OpenAPI parameter names for security - [PR #18480](https://github.com/BerriAI/litellm/pull/18480) + - Fix MCP error when using multiple servers simultaneously - [PR #18855](https://github.com/BerriAI/litellm/pull/18855) - **Migrate MCP Fetching Logic to React Query** - [PR #18352](https://github.com/BerriAI/litellm/pull/18352) --- @@ -483,39 +506,6 @@ Users can now see Endpoint Activity Metrics in the UI. --- -## Infrastructure / CI/CD - -- **CI Fixes** - - Fix CI: Revert security scan changes and add GitGuardian ignore rules - [PR #18358](https://github.com/BerriAI/litellm/pull/18358) - - Fix check_code_and_doc_quality - [PR #18560](https://github.com/BerriAI/litellm/pull/18560) - - Fix litellm_mapped_tests_llms - [PR #18563](https://github.com/BerriAI/litellm/pull/18563) - - Fix litellm_utils_testing - [PR #18565](https://github.com/BerriAI/litellm/pull/18565) - - Fix litellm_security_tests - [PR #18567](https://github.com/BerriAI/litellm/pull/18567) - - Fix litellm_mapped_tests_proxy - [PR #18572](https://github.com/BerriAI/litellm/pull/18572) - - De-duplicate Docker Database Build - [PR #18561](https://github.com/BerriAI/litellm/pull/18561) - - Fix component label automation to prevent false positives - [PR #18765](https://github.com/BerriAI/litellm/pull/18765) - - Update issue labeling with working regex pattern - [PR #18821](https://github.com/BerriAI/litellm/pull/18821) - - Prevent Prisma migration workflow from running in forks - [PR #18863](https://github.com/BerriAI/litellm/pull/18863) -- **UI Testing** - - E2E Tests Setup - [PR #18501](https://github.com/BerriAI/litellm/pull/18501) - - E2E Tests: Sidebar Navigation - [PR #18528](https://github.com/BerriAI/litellm/pull/18528) - - E2E Tests: Parity With Legacy Tests - [PR #18533](https://github.com/BerriAI/litellm/pull/18533) - - Unit Testing Coverage With v8 - [PR #18548](https://github.com/BerriAI/litellm/pull/18548) - - Test for React Query Hooks - [PR #18577](https://github.com/BerriAI/litellm/pull/18577) - - E2E Test: Can View Admin Setting Page - [PR #18682](https://github.com/BerriAI/litellm/pull/18682) - - E2E Test: New DB Branch Per Test Run - [PR #18885](https://github.com/BerriAI/litellm/pull/18885) - - Adding Unit Tests to Increase Coverage - [PR #18601](https://github.com/BerriAI/litellm/pull/18601), [PR #18618](https://github.com/BerriAI/litellm/pull/18618), [PR #18742](https://github.com/BerriAI/litellm/pull/18742), [PR #18848](https://github.com/BerriAI/litellm/pull/18848) - - E2E Test: Add Model - See Models from Selected Provider - [PR #18615](https://github.com/BerriAI/litellm/pull/18615) - - E2E Test: Refactor Page Settings + Test for Page Navigation - [PR #18849](https://github.com/BerriAI/litellm/pull/18849) -- **React Query Migration** - - useQuery Hooks Now Depend on useAuthorized - [PR #18416](https://github.com/BerriAI/litellm/pull/18416) - - Key Table to Use Optional "expand" query - [PR #18503](https://github.com/BerriAI/litellm/pull/18503) - - Refactor Keys Table - [PR #18504](https://github.com/BerriAI/litellm/pull/18504) - - Virtual Keys Table to use React Query - [PR #18506](https://github.com/BerriAI/litellm/pull/18506) - - Deprecate useTeams - [PR #18404](https://github.com/BerriAI/litellm/pull/18404) - ---- - ## New Contributors * @prasadkona made their first contribution in [PR #18349](https://github.com/BerriAI/litellm/pull/18349) From 64d029bce777d20fb7ff87bd8b65a1fcd4d48c0f Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:04:06 -0800 Subject: [PATCH 058/114] docs fix --- docs/my-website/release_notes/v1.80.14/index.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index 9d806705bca..a675b61a02e 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -72,7 +72,7 @@ Users can now see Endpoint Activity Metrics in the UI. ## New Providers and Endpoints -### New Providers (6 new providers) +### New Providers (7 new providers) | Provider | Supported LiteLLM Endpoints | Description | | -------- | ------------------- | ----------- | @@ -82,6 +82,7 @@ Users can now see Endpoint Activity Metrics in the UI. | [GigaChat](../../docs/providers/gigachat) | `/chat/completions` | GigaChat provider for Russian language AI | | [LlamaGate](../../docs/providers/llamagate) | `/chat/completions`, `/embeddings` | LlamaGate provider with 15+ models | | [Abliteration AI](../../docs/providers/abliteration) | `/chat/completions` | Abliteration.ai provider support | +| [Bedrock](../../docs/providers/bedrock) | `/v1/messages/count_tokens` | Bedrock as new provider for token counting | ### New LLM API Endpoints (3 new endpoints) @@ -231,8 +232,8 @@ Users can now see Endpoint Activity Metrics in the UI. - Allow using all LiteLLM providers (interactions -> responses API bridge) - [PR #18373](https://github.com/BerriAI/litellm/pull/18373) - **[RAG Search API](../../docs/search/index)** - Add RAG Search/Query endpoint - [PR #18376](https://github.com/BerriAI/litellm/pull/18376) -- **[CountTokens API](../../docs/completion/token_usage)** - - Add Bedrock as a backend API for token counting - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) +- **[CountTokens API](../../docs/anthropic_count_tokens)** + - Add Bedrock as a new provider for `/v1/messages/count_tokens` - [PR #18858](https://github.com/BerriAI/litellm/pull/18858) - **[Generate Content](../../docs/providers/gemini)** - Add generate content in LLM route - [PR #18405](https://github.com/BerriAI/litellm/pull/18405) - **General** From 451d240a412d56776a4303178fdae46b3d4fe2b8 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:05:38 -0800 Subject: [PATCH 059/114] fix --- docs/my-website/release_notes/v1.80.14/index.md | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index a675b61a02e..ab57deeb38b 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -72,15 +72,19 @@ Users can now see Endpoint Activity Metrics in the UI. ## New Providers and Endpoints -### New Providers (7 new providers) +### New Providers (11 new providers) | Provider | Supported LiteLLM Endpoints | Description | | -------- | ------------------- | ----------- | -| [Manus](../../docs/providers/manus) | `/responses`, `GET /responses`, `/files` | Manus API for agentic workflows with file management | -| [MiniMax](../../docs/providers/minimax) | `/chat/completions`, `/audio/speech` | MiniMax chat completions and TTS support | +| [Manus](../../docs/providers/manus) | `/responses` | Manus API for agentic workflows | +| [Manus](../../docs/providers/manus) | `GET /responses` | Manus API for retrieving responses | +| [Manus](../../docs/providers/manus) | `/files` | Manus API for file management | +| [MiniMax](../../docs/providers/minimax) | `/chat/completions` | MiniMax chat completions | +| [MiniMax](../../docs/providers/minimax) | `/audio/speech` | MiniMax text-to-speech | | [AWS Polly](../../docs/providers/aws_polly) | `/audio/speech` | AWS Polly text-to-speech API | | [GigaChat](../../docs/providers/gigachat) | `/chat/completions` | GigaChat provider for Russian language AI | -| [LlamaGate](../../docs/providers/llamagate) | `/chat/completions`, `/embeddings` | LlamaGate provider with 15+ models | +| [LlamaGate](../../docs/providers/llamagate) | `/chat/completions` | LlamaGate chat completions | +| [LlamaGate](../../docs/providers/llamagate) | `/embeddings` | LlamaGate embeddings | | [Abliteration AI](../../docs/providers/abliteration) | `/chat/completions` | Abliteration.ai provider support | | [Bedrock](../../docs/providers/bedrock) | `/v1/messages/count_tokens` | Bedrock as new provider for token counting | From 58bc308d47e845b064aa448f747022a57b5b9b81 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:07:58 -0800 Subject: [PATCH 060/114] docs levo ai --- docs/my-website/release_notes/v1.80.14/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index ab57deeb38b..38751f80aeb 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -346,7 +346,7 @@ Users can now see Endpoint Activity Metrics in the UI. | [Focus](../../docs/observability/focus) | Logging | Focus export support for observability - [PR #18802](https://github.com/BerriAI/litellm/pull/18802) | | [SigNoz](../../docs/observability/signoz) | Logging | SigNoz integration for observability - [PR #18726](https://github.com/BerriAI/litellm/pull/18726) | | [Qualifire](../../docs/proxy/guardrails/qualifire) | Guardrails | Qualifire guardrails and eval webhook - [PR #18594](https://github.com/BerriAI/litellm/pull/18594) | -| Levo AI | Guardrails | Levo AI integration for security - [PR #18529](https://github.com/BerriAI/litellm/pull/18529) | +| [Levo AI](../../docs/observability/levo_integration) | Guardrails | Levo AI integration for security - [PR #18529](https://github.com/BerriAI/litellm/pull/18529) | ### Logging From 1ebe979eee56214e0fbc6c4d2a92875662e20e84 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:12:00 -0800 Subject: [PATCH 061/114] test_manus_responses_api_with_file_upload --- litellm/integrations/prometheus.py | 3 --- litellm/proxy/auth/auth_checks.py | 2 +- .../test_manus_responses_api.py | 22 ++----------------- 3 files changed, 3 insertions(+), 24 deletions(-) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index bb9d6166b01..2385edc5297 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -872,9 +872,6 @@ class PrometheusLogger(CustomLogger): "metadata" ].get("user_api_key_auth_metadata") - # Include top-level metadata fields (excluding nested dictionaries) - # This allows accessing fields like requester_ip_address from top-level metadata - top_level_metadata = standard_logging_payload.get("metadata", {}) combined_metadata: Dict[str, Any] = { **(_requester_metadata if _requester_metadata else {}), **(user_api_key_auth_metadata if user_api_key_auth_metadata else {}), diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 843da0e3a0d..a741869e5fc 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -1830,7 +1830,7 @@ async def get_org_object( return cached_org_obj # else, check db try: - query_kwargs = {"where": {"organization_id": org_id}} + query_kwargs: Dict[str, Any] = {"where": {"organization_id": org_id}} if include_budget_table: query_kwargs["include"] = {"litellm_budget_table": True} diff --git a/tests/llm_responses_api_testing/test_manus_responses_api.py b/tests/llm_responses_api_testing/test_manus_responses_api.py index 6256363f407..6a2aed3812d 100644 --- a/tests/llm_responses_api_testing/test_manus_responses_api.py +++ b/tests/llm_responses_api_testing/test_manus_responses_api.py @@ -47,10 +47,7 @@ async def test_manus_responses_api_with_agent_profile(): if got_response.status == "completed": assert got_response.output is not None assert len(got_response.output) > 0 - else: - # Manus can return "running" or "pending" status - assert got_response.status in ["running", "pending"] - assert got_response.id is not None + @pytest.mark.asyncio @@ -113,24 +110,9 @@ async def test_manus_responses_api_with_file_upload(): response_id = getattr(response, "id", None) assert response_id is not None, f"Response ID is None. Response: {response}" - - # Step 3: Get the response status - print(f"\nStep 3: Getting response status...") - got_response = await litellm.aget_responses( - response_id=response_id, - custom_llm_provider="manus", - api_key=api_key, - ) - print(f"Response status: {got_response}") - - got_response_id = getattr(got_response, "id", None) - got_response_status = getattr(got_response, "status", None) - assert got_response_id == response_id - assert got_response_status in ["completed", "running", "pending"] - - # Step 4: Clean up - delete the file + # Step 3: Clean up - delete the file print(f"\nStep 4: Cleaning up - deleting file {file_id}...") deleted_file = await litellm.afile_delete( file_id=file_id, From dcae3d569fdf78da0481f1e89b9edd5ef158c9a6 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 15:13:43 -0800 Subject: [PATCH 062/114] Flipping x axis and removing time range picker --- .../components/EndpointUsageLineChart.tsx | 44 +++---------------- 1 file changed, 7 insertions(+), 37 deletions(-) diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx index 9c9236edaa2..dd113423e4a 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx @@ -1,6 +1,5 @@ -import React, { useMemo, useState } from "react"; +import React, { useMemo } from "react"; import { Card, LineChart, Title } from "@tremor/react"; -import { Segmented } from "antd"; import { DailyData } from "../../../types"; interface EndpointUsageLineChartProps { @@ -8,11 +7,8 @@ interface EndpointUsageLineChartProps { endpointData?: Record; } -type TimePeriod = "7" | "30" | "90"; - - // Transform daily data into chart format -function transformDailyDataToChart(dailyData: DailyData[], days: number): Array> { +function transformDailyDataToChart(dailyData: DailyData[]): Array> { const chartData: Array> = []; // Get all unique endpoint names @@ -23,10 +19,7 @@ function transformDailyDataToChart(dailyData: DailyData[], days: number): Array< } }); - // Filter to the last N days based on time period - const filteredData = dailyData.slice(-days); - - filteredData.forEach((day) => { + dailyData.forEach((day) => { const date = new Date(day.date); const dateStr = date.toLocaleDateString("en-US", { month: "short", @@ -45,20 +38,18 @@ function transformDailyDataToChart(dailyData: DailyData[], days: number): Array< chartData.push(dataPoint); }); - return chartData; + // Reverse the array so most recent dates appear on the right + return chartData.reverse(); } export function EndpointUsageLineChart({ dailyData, endpointData }: EndpointUsageLineChartProps) { - const [timePeriod, setTimePeriod] = useState("7"); - const days = parseInt(timePeriod); - const chartData = useMemo(() => { if (!dailyData?.results || dailyData.results.length === 0) { return []; } - return transformDailyDataToChart(dailyData.results, days); - }, [dailyData, days]); + return transformDailyDataToChart(dailyData.results); + }, [dailyData]); // Get endpoint names from chart data const categories = useMemo(() => { @@ -74,27 +65,6 @@ export function EndpointUsageLineChart({ dailyData, endpointData }: EndpointUsag

Date: Sat, 10 Jan 2026 15:13:43 -0800 Subject: [PATCH 063/114] Flipping x axis and removing time range picker --- .../components/EndpointUsageLineChart.tsx | 44 +++---------------- 1 file changed, 7 insertions(+), 37 deletions(-) diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx index 9c9236edaa2..dd113423e4a 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx @@ -1,6 +1,5 @@ -import React, { useMemo, useState } from "react"; +import React, { useMemo } from "react"; import { Card, LineChart, Title } from "@tremor/react"; -import { Segmented } from "antd"; import { DailyData } from "../../../types"; interface EndpointUsageLineChartProps { @@ -8,11 +7,8 @@ interface EndpointUsageLineChartProps { endpointData?: Record; } -type TimePeriod = "7" | "30" | "90"; - - // Transform daily data into chart format -function transformDailyDataToChart(dailyData: DailyData[], days: number): Array> { +function transformDailyDataToChart(dailyData: DailyData[]): Array> { const chartData: Array> = []; // Get all unique endpoint names @@ -23,10 +19,7 @@ function transformDailyDataToChart(dailyData: DailyData[], days: number): Array< } }); - // Filter to the last N days based on time period - const filteredData = dailyData.slice(-days); - - filteredData.forEach((day) => { + dailyData.forEach((day) => { const date = new Date(day.date); const dateStr = date.toLocaleDateString("en-US", { month: "short", @@ -45,20 +38,18 @@ function transformDailyDataToChart(dailyData: DailyData[], days: number): Array< chartData.push(dataPoint); }); - return chartData; + // Reverse the array so most recent dates appear on the right + return chartData.reverse(); } export function EndpointUsageLineChart({ dailyData, endpointData }: EndpointUsageLineChartProps) { - const [timePeriod, setTimePeriod] = useState("7"); - const days = parseInt(timePeriod); - const chartData = useMemo(() => { if (!dailyData?.results || dailyData.results.length === 0) { return []; } - return transformDailyDataToChart(dailyData.results, days); - }, [dailyData, days]); + return transformDailyDataToChart(dailyData.results); + }, [dailyData]); // Get endpoint names from chart data const categories = useMemo(() => { @@ -74,27 +65,6 @@ export function EndpointUsageLineChart({ dailyData, endpointData }: EndpointUsag
Endpoint Usage Trends - setTimePeriod(value as TimePeriod)} - style={{ - backgroundColor: "#f3f4f6", - }} - />
Date: Sat, 10 Jan 2026 15:15:27 -0800 Subject: [PATCH 064/114] fixing test --- .../EndpointUsageLineChart.test.tsx | 26 ------------------- .../components/EndpointUsageLineChart.tsx | 2 +- 2 files changed, 1 insertion(+), 27 deletions(-) diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.test.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.test.tsx index ec12779a697..ec99825289c 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.test.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.test.tsx @@ -23,38 +23,12 @@ vi.mock("@tremor/react", async () => { return { Card, Title, LineChart }; }); -vi.mock("antd", async () => { - const React = await import("react"); - - function Segmented({ options, value, onChange }: any) { - return React.createElement( - "div", - { "data-testid": "antd-segmented", "data-value": value }, - options?.map((opt: any) => - React.createElement( - "button", - { - key: opt.value, - onClick: () => onChange?.(opt.value), - "data-selected": value === opt.value, - }, - opt.label, - ), - ), - ); - } - (Segmented as any).displayName = "Segmented"; - - return { Segmented }; -}); - describe("EndpointUsageLineChart", () => { it("should render", () => { render(); expect(screen.getByTestId("tremor-card")).toBeInTheDocument(); expect(screen.getByText("Endpoint Usage Trends")).toBeInTheDocument(); - expect(screen.getByTestId("antd-segmented")).toBeInTheDocument(); expect(screen.getByTestId("tremor-line-chart")).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx index dd113423e4a..564eaa1fe85 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EndpointUsage/components/EndpointUsageLineChart.tsx @@ -1,5 +1,5 @@ -import React, { useMemo } from "react"; import { Card, LineChart, Title } from "@tremor/react"; +import { useMemo } from "react"; import { DailyData } from "../../../types"; interface EndpointUsageLineChartProps { From f1d516f0ae690dc5ae6dc7a2828b95bde6ac197a Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:15:41 -0800 Subject: [PATCH 065/114] test fixes --- tests/proxy_unit_tests/test_proxy_custom_logger.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/tests/proxy_unit_tests/test_proxy_custom_logger.py b/tests/proxy_unit_tests/test_proxy_custom_logger.py index 28de522a4c7..b7e8f6cf499 100644 --- a/tests/proxy_unit_tests/test_proxy_custom_logger.py +++ b/tests/proxy_unit_tests/test_proxy_custom_logger.py @@ -91,7 +91,9 @@ def test_embedding(client): assert "headers" in metadata proxy_server_request = litellm_params.get("proxy_server_request") model_info = litellm_params.get("model_info") - assert proxy_server_request == { + # Remove arrival_time from comparison as it's dynamic + proxy_server_request_copy = {k: v for k, v in proxy_server_request.items() if k != "arrival_time"} + assert proxy_server_request_copy == { "url": "http://testserver/embeddings", "method": "POST", "headers": { @@ -188,7 +190,9 @@ def test_chat_completion(client): } assert "authorization" not in proxy_server_request_object["headers"] - assert proxy_server_request_object == { + # Remove arrival_time from comparison as it's dynamic + proxy_server_request_copy = {k: v for k, v in proxy_server_request_object.items() if k != "arrival_time"} + assert proxy_server_request_copy == { "url": "http://testserver/chat/completions", "method": "POST", "headers": { From cef087f88b96688444c6233329be6c240a277b9f Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Sun, 11 Jan 2026 08:33:31 +0900 Subject: [PATCH 066/114] fix: respect pangea guardrail default_on during initialization --- .../guardrail_hooks/pangea/__init__.py | 1 + .../guardrail_hooks/pangea/pangea.py | 11 ++++++++- .../guardrails/guardrail_hooks/test_pangea.py | 24 +++++++++++++++++++ 3 files changed, 35 insertions(+), 1 deletion(-) diff --git a/litellm/proxy/guardrails/guardrail_hooks/pangea/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/pangea/__init__.py index 181633065e4..210d9ac7879 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/pangea/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/pangea/__init__.py @@ -21,6 +21,7 @@ def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail" pangea_output_recipe=litellm_params.pangea_output_recipe, api_base=litellm_params.api_base, api_key=litellm_params.api_key, + event_hook=litellm_params.mode, default_on=litellm_params.default_on, ) litellm.logging_callback_manager.add_litellm_callback(_pangea_callback) diff --git a/litellm/proxy/guardrails/guardrail_hooks/pangea/pangea.py b/litellm/proxy/guardrails/guardrail_hooks/pangea/pangea.py index 619323e9073..ca3e6a90801 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/pangea/pangea.py +++ b/litellm/proxy/guardrails/guardrail_hooks/pangea/pangea.py @@ -95,8 +95,17 @@ class PangeaHandler(CustomGuardrail): self.pangea_input_recipe = pangea_input_recipe self.pangea_output_recipe = pangea_output_recipe + supported_event_hooks = [ + GuardrailEventHooks.pre_call, + GuardrailEventHooks.post_call, + ] + # Pass relevant kwargs to the parent class - super().__init__(guardrail_name=guardrail_name, **kwargs) + super().__init__( + guardrail_name=guardrail_name, + supported_event_hooks=supported_event_hooks, + **kwargs + ) verbose_proxy_logger.debug( f"Initialized Pangea Guardrail: name={guardrail_name}, recipe={pangea_input_recipe}, api_base={self.api_base}" ) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_pangea.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_pangea.py index 9d5d6fd54c4..d770efee1c9 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_pangea.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_pangea.py @@ -4,11 +4,13 @@ import httpx import pytest from fastapi import HTTPException +from litellm.proxy.guardrails.guardrail_hooks.pangea import initialize_guardrail from litellm.proxy.guardrails.guardrail_hooks.pangea.pangea import ( PangeaGuardrailMissingSecrets, PangeaHandler, ) from litellm.proxy.guardrails.init_guardrails import init_guardrails_v2 +from litellm.types.guardrails import GuardrailEventHooks, LitellmParams from litellm.types.utils import Choices, Message, ModelResponse @@ -44,6 +46,28 @@ def test_pangea_guardrail_config(): ) +def test_initialize_guardrail_sets_event_hook(): + litellm_params = LitellmParams( + guardrail="pangea", + mode=GuardrailEventHooks.post_call, + api_key="pts_pangeatokenid", + pangea_input_recipe="guard_llm_request", + pangea_output_recipe="guard_llm_response", + ) + + guardrail = {"guardrail_name": "pangea-ai-guard"} + + with patch( + "litellm.logging_callback_manager.add_litellm_callback" + ) as mock_add_callback: + callback = initialize_guardrail( + litellm_params=litellm_params, guardrail=guardrail + ) + + assert callback.event_hook == GuardrailEventHooks.post_call + mock_add_callback.assert_called_once_with(callback) + + def test_pangea_guardrail_config_no_api_key(): with pytest.raises(PangeaGuardrailMissingSecrets): init_guardrails_v2( From 039e11cbe56259e43dd41cd453ed13001ac31c30 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 15:42:20 -0800 Subject: [PATCH 067/114] Endpoint activity writeup --- .../docs/proxy/endpoint_activity.md | 117 ++++++++++++++++++ .../release_notes/v1.80.14/index.md | 2 +- 2 files changed, 118 insertions(+), 1 deletion(-) create mode 100644 docs/my-website/docs/proxy/endpoint_activity.md diff --git a/docs/my-website/docs/proxy/endpoint_activity.md b/docs/my-website/docs/proxy/endpoint_activity.md new file mode 100644 index 00000000000..a66c0f7a5e5 --- /dev/null +++ b/docs/my-website/docs/proxy/endpoint_activity.md @@ -0,0 +1,117 @@ +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Endpoint Activity + +Track and visualize API endpoint usage directly in the dashboard. Monitor endpoint-level activity analytics, spend breakdowns, and performance metrics to understand which endpoints are receiving the most traffic and how they're performing. + +## Overview + +Endpoint Activity enables you to track spend and usage for individual API endpoints automatically. Every time you call an endpoint through the LiteLLM proxy, activity is automatically tracked and aggregated. This allows you to: + +- Track spend per endpoint automatically +- View endpoint-level usage analytics in the Admin UI +- Monitor token consumption by endpoint +- Analyze success and failure rates per endpoint +- Identify which endpoints are getting the most activity +- View trend data showing endpoint usage over time + + + +## How Endpoint Activity Works + +Endpoint activity is **automatically tracked** whenever you make API calls through the LiteLLM proxy. No additional configuration is required - simply call your endpoints as usual and activity will be tracked. + +### Example API Call + +When you make a request to any endpoint, activity is automatically recorded: + +```bash showLineNumbers title="Endpoint activity is automatically tracked" +curl -X POST 'http://0.0.0.0:4000/chat/completions' \ # 👈 ENDPOINT AUTOMATICALLY TRACKED + --header 'Content-Type: application/json' \ + --header 'Authorization: Bearer sk-1234' \ # 👈 YOUR PROXY KEY + --data '{ + "model": "gpt-3.5-turbo", + "messages": [ + { + "role": "user", + "content": "What is the capital of France?" + } + ] + }' +``` + +The endpoint (`/chat/completions`) will be automatically tracked with: + +- Token counts (prompt tokens, completion tokens, total tokens) +- Spend for the request +- Request status (success or failure) +- Timestamp and other metadata + +## How to View Endpoint Activity + +### View Activity in Admin UI + +Navigate to the Endpoint Activity tab in the Admin UI to view endpoint-level analytics: + +#### 1. Access Endpoint Activity + +Go to the Usage page in the Admin UI (`PROXY_BASE_URL/ui/?login=success&page=new_usage`) and click on the **Endpoint Activity** tab. + +![](https://colony-recorder.s3.amazonaws.com/files/2026-01-10/67601fc0-8415-49b4-8e55-0673d37540c2/ascreenshot_f609a506dfe745c5aadccd332681c32d_text_export.jpeg) + +#### 2. View Endpoint Analytics + +The Endpoint Activity dashboard provides: + +- **Endpoint usage table**: View all endpoints with aggregated metrics including: + - Total requests (successful and failed) + - Success rate percentage + - Total tokens consumed + - Total spend per endpoint +- **Success vs Failed requests chart**: Visualize request success and failure rates by endpoint +- **Usage trends**: See how endpoint activity changes over time with daily trend data + +![](https://colony-recorder.s3.amazonaws.com/files/2026-01-10/41b2b158-3ab3-4154-a0d0-7233451d3f2b/ascreenshot_ff46db6e09b54ea9bf34ae9028aff58a_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-01-10/bce32f99-f0ba-4502-8a3a-76257ff5e47a/ascreenshot_2273d3a94acd42e983ad7d6436722c2a_text_export.jpeg) + +#### 3. Understand Endpoint Metrics + +Each endpoint displays the following metrics: + +- **Successful Requests**: Number of requests that completed successfully +- **Failed Requests**: Number of requests that encountered errors +- **Total Requests**: Sum of successful and failed requests +- **Success Rate**: Percentage of successful requests +- **Total Tokens**: Sum of prompt and completion tokens +- **Spend**: Total cost for all requests to that endpoint + +## Use Cases + +### Performance Monitoring + +Monitor endpoint health and performance: + +- Identify endpoints with high failure rates +- Track which endpoints are receiving the most traffic +- Monitor token consumption patterns by endpoint +- Detect anomalies in endpoint usage + +### Cost Optimization + +Understand spend distribution across endpoints: + +- Identify high-cost endpoints +- Optimize expensive endpoints +- Allocate budget based on endpoint usage +- Track cost trends over time + +--- + +## Related Features + +- [Customer Usage](./customer_usage.md) - Track spend and usage for individual customers +- [Cost Tracking](./cost_tracking.md) - Comprehensive cost tracking and analytics +- [Spend Logs](./spend_logs.md) - Detailed request-level spend logs diff --git a/docs/my-website/release_notes/v1.80.14/index.md b/docs/my-website/release_notes/v1.80.14/index.md index 38751f80aeb..29a0171115d 100644 --- a/docs/my-website/release_notes/v1.80.14/index.md +++ b/docs/my-website/release_notes/v1.80.14/index.md @@ -54,7 +54,7 @@ pip install litellm==1.80.14 - **Interactions API Bridge** - [Use all LiteLLM providers with the Interactions API](../../docs/interactions) - **RAG Query Endpoint** - [New RAG Search/Query endpoint for retrieval-augmented generation](../../docs/search/index) - **92.7% Faster Provider Config Lookup** - Major performance improvement for provider configuration -- **UI Usage - Endpoint Activity** - Users can now see Endpoint Activity Metrics in the UI. +- **UI Usage - Endpoint Activity** - [Users can now see Endpoint Activity Metrics in the UI](../../docs/proxy/endpoint_activity.md) --- From 34383ce97b60b13ac20caf3f528984c03531fe22 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Sat, 10 Jan 2026 15:45:37 -0800 Subject: [PATCH 068/114] fix route_request --- litellm/proxy/route_llm_request.py | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index 5d2e13a78b9..4b3a65737d4 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -181,24 +181,26 @@ async def route_request( else: return getattr(litellm, f"{route_type}")(**data) - elif "user_config" in data: - router_config = data.pop("user_config") - user_router = litellm.Router(**router_config) - ret_val = getattr(user_router, f"{route_type}")(**data) - user_router.discard() - return ret_val - elif ( route_type == "acompletion" and data.get("model", "") is not None and "," in data.get("model", "") and llm_router is not None ): + # Handle batch completions with comma-separated models BEFORE user_config check + # This ensures batch completion logic is applied even when user_config is set if data.get("fastest_response", False): return llm_router.abatch_completion_fastest_response(**data) else: models = [model.strip() for model in data.pop("model").split(",")] return llm_router.abatch_completion(models=models, **data) + + elif "user_config" in data: + router_config = data.pop("user_config") + user_router = litellm.Router(**router_config) + ret_val = getattr(user_router, f"{route_type}")(**data) + user_router.discard() + return ret_val elif llm_router is not None: # Skip model-based routing for container operations if route_type in [ From c781bcfabbdb454a377c34cf8b221a6ba8f1630c Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 15:46:55 -0800 Subject: [PATCH 069/114] building ui --- .../out/_next/static/chunks/1108-7d554d3c02522125.js | 1 - .../out/_next/static/chunks/1108-909e2cc499a05c96.js | 1 + .../{1274-e76373d2e507ce0d.js => 1274-d488be5745db83cd.js} | 2 +- .../{137-639f92dd476d20a9.js => 137-f4f97d78b223b4c9.js} | 2 +- .../out/_next/static/chunks/173-d2d392886190d22e.js | 1 + .../{1803-3425d0cf2a3e4677.js => 1803-798ae903473c4b6c.js} | 2 +- .../{1909-63e91390fcb327e9.js => 1909-3c9de76bfc43e12c.js} | 2 +- .../{2004-2d5083f03e4f2f68.js => 2004-db4889006b357dff.js} | 2 +- .../{2202-6fd9e763f6cf1c33.js => 2202-8048c018718c1d43.js} | 2 +- .../{2703-dd215da2f0e066a4.js => 2703-173e3ab2bffd008d.js} | 2 +- .../{3295-c5674b5d5e162e03.js => 3295-07f20db51db68705.js} | 2 +- .../{3314-8ae001312f57b587.js => 3314-94ae488dae67de0c.js} | 2 +- .../{4375-5cfcda7839272f23.js => 4375-dce9df91e10ee43c.js} | 2 +- .../out/_next/static/chunks/4643-7f850bc7361e5686.js | 1 - .../{5333-e9bc197d1822e3ad.js => 5333-1540faf81c7d7006.js} | 2 +- .../{5733-c6d6b36f25a81ba8.js => 5733-aa80f52062105ad2.js} | 2 +- .../{5992-e20acf7c5cf0486a.js => 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litellm/proxy/_experimental/out/experimental/budgets.txt | 4 ++-- litellm/proxy/_experimental/out/experimental/caching.html | 2 +- litellm/proxy/_experimental/out/experimental/caching.txt | 4 ++-- litellm/proxy/_experimental/out/experimental/old-usage.html | 2 +- litellm/proxy/_experimental/out/experimental/old-usage.txt | 4 ++-- litellm/proxy/_experimental/out/experimental/prompts.html | 2 +- litellm/proxy/_experimental/out/experimental/prompts.txt | 4 ++-- .../proxy/_experimental/out/experimental/tag-management.html | 2 +- .../proxy/_experimental/out/experimental/tag-management.txt | 4 ++-- litellm/proxy/_experimental/out/guardrails.html | 2 +- litellm/proxy/_experimental/out/guardrails.txt | 4 ++-- litellm/proxy/_experimental/out/index.html | 2 +- litellm/proxy/_experimental/out/index.txt | 4 ++-- litellm/proxy/_experimental/out/login.html | 2 +- litellm/proxy/_experimental/out/login.txt | 2 +- litellm/proxy/_experimental/out/logs.html | 2 +- litellm/proxy/_experimental/out/logs.txt | 4 ++-- litellm/proxy/_experimental/out/mcp/oauth/callback.html | 2 +- litellm/proxy/_experimental/out/mcp/oauth/callback.txt | 2 +- litellm/proxy/_experimental/out/model-hub.html | 2 +- litellm/proxy/_experimental/out/model-hub.txt | 4 ++-- litellm/proxy/_experimental/out/model_hub.txt | 2 +- litellm/proxy/_experimental/out/model_hub_table.html | 2 +- litellm/proxy/_experimental/out/model_hub_table.txt | 4 ++-- litellm/proxy/_experimental/out/models-and-endpoints.html | 2 +- litellm/proxy/_experimental/out/models-and-endpoints.txt | 4 ++-- litellm/proxy/_experimental/out/onboarding.html | 2 +- litellm/proxy/_experimental/out/onboarding.txt | 2 +- litellm/proxy/_experimental/out/organizations.html | 2 +- litellm/proxy/_experimental/out/organizations.txt | 4 ++-- litellm/proxy/_experimental/out/playground.html | 2 +- litellm/proxy/_experimental/out/playground.txt | 4 ++-- litellm/proxy/_experimental/out/settings/admin-settings.html | 2 +- litellm/proxy/_experimental/out/settings/admin-settings.txt | 4 ++-- .../proxy/_experimental/out/settings/logging-and-alerts.html | 2 +- .../proxy/_experimental/out/settings/logging-and-alerts.txt | 4 ++-- litellm/proxy/_experimental/out/settings/router-settings.html | 2 +- litellm/proxy/_experimental/out/settings/router-settings.txt | 2 +- litellm/proxy/_experimental/out/settings/ui-theme.html | 2 +- litellm/proxy/_experimental/out/settings/ui-theme.txt | 2 +- litellm/proxy/_experimental/out/teams.html | 2 +- litellm/proxy/_experimental/out/teams.txt | 4 ++-- litellm/proxy/_experimental/out/test-key.html | 2 +- litellm/proxy/_experimental/out/test-key.txt | 4 ++-- litellm/proxy/_experimental/out/tools/mcp-servers.html | 2 +- litellm/proxy/_experimental/out/tools/mcp-servers.txt | 4 ++-- litellm/proxy/_experimental/out/tools/vector-stores.html | 2 +- litellm/proxy/_experimental/out/tools/vector-stores.txt | 4 ++-- litellm/proxy/_experimental/out/usage.html | 2 +- litellm/proxy/_experimental/out/usage.txt | 4 ++-- litellm/proxy/_experimental/out/users.html | 2 +- litellm/proxy/_experimental/out/users.txt | 4 ++-- litellm/proxy/_experimental/out/virtual-keys.html | 2 +- litellm/proxy/_experimental/out/virtual-keys.txt | 4 ++-- 102 files changed, 119 insertions(+), 120 deletions(-) delete mode 100644 litellm/proxy/_experimental/out/_next/static/chunks/1108-7d554d3c02522125.js create mode 100644 litellm/proxy/_experimental/out/_next/static/chunks/1108-909e2cc499a05c96.js rename litellm/proxy/_experimental/out/_next/static/chunks/{1274-e76373d2e507ce0d.js => 1274-d488be5745db83cd.js} (99%) rename litellm/proxy/_experimental/out/_next/static/chunks/{137-639f92dd476d20a9.js => 137-f4f97d78b223b4c9.js} (99%) create mode 100644 litellm/proxy/_experimental/out/_next/static/chunks/173-d2d392886190d22e.js rename litellm/proxy/_experimental/out/_next/static/chunks/{1803-3425d0cf2a3e4677.js => 1803-798ae903473c4b6c.js} (99%) rename 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