- Remove unsupported
- Keep supported + + LP->>Provider: Request with filtered headers + Note over LP,Provider: anthropic-beta: header2
(header1, header3 removed) + + Provider-->>LP: Success response + LP-->>CC: Response +``` \ No newline at end of file diff --git a/docs/my-website/img/release_notes/mcp_internet.png b/docs/my-website/img/release_notes/mcp_internet.png new file mode 100644 index 00000000000..d24d2a20870 Binary files /dev/null and b/docs/my-website/img/release_notes/mcp_internet.png differ diff --git a/docs/my-website/img/ui_team_soft_budget_alerts.png b/docs/my-website/img/ui_team_soft_budget_alerts.png new file mode 100644 index 00000000000..9627b5f1daa Binary files /dev/null and b/docs/my-website/img/ui_team_soft_budget_alerts.png differ diff --git a/docs/my-website/img/ui_team_soft_budget_email_example.png b/docs/my-website/img/ui_team_soft_budget_email_example.png new file mode 100644 index 00000000000..0cd83487112 Binary files /dev/null and b/docs/my-website/img/ui_team_soft_budget_email_example.png differ diff --git a/docs/my-website/release_notes/v1.81.6.md b/docs/my-website/release_notes/v1.81.6.md index ef19276f2cf..d349afa65f9 100644 --- a/docs/my-website/release_notes/v1.81.6.md +++ b/docs/my-website/release_notes/v1.81.6.md @@ -1,5 +1,5 @@ --- -title: "v1.81.6 - Logs v2 with Tool Call Tracing" +title: "[Preview] v1.81.6 - Logs v2 with Tool Call Tracing" slug: "v1-81-6" date: 2026-01-31T00:00:00 authors: diff --git a/docs/my-website/release_notes/v1.81.9.md b/docs/my-website/release_notes/v1.81.9.md new file mode 100644 index 00000000000..c34d3056cae --- /dev/null +++ b/docs/my-website/release_notes/v1.81.9.md @@ -0,0 +1,372 @@ +--- +title: "[Preview] v1.81.9 - Control which MCP Servers are exposed on the Internet" +slug: "v1-81-9" +date: 2026-02-07T00:00:00 +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 +--- + +## Deploy this version + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; +import Image from '@theme/IdealImage'; + +
+
+ );
+}
diff --git a/docs/my-website/src/components/MiddlewareDiagrams/BenchmarkVisualization.tsx b/docs/my-website/src/components/MiddlewareDiagrams/BenchmarkVisualization.tsx
new file mode 100644
index 00000000000..b2b34d9d044
--- /dev/null
+++ b/docs/my-website/src/components/MiddlewareDiagrams/BenchmarkVisualization.tsx
@@ -0,0 +1,337 @@
+import React, { useState, useEffect, useRef, useCallback } from 'react';
+import styles from './styles.module.css';
+
+/* ── Constants ── */
+const TOTAL_REQUESTS = 50_000;
+const DURATION_AFTER_MS = 8_000; // "After" column finishes in 8s
+const DURATION_BEFORE_MS = 13_920; // 74% slower → 8000 * 1.74
+const TICK_MS = 50;
+const RESET_PAUSE_MS = 2_000;
+const MAX_DOTS = 14;
+
+const BEFORE_RPS = 3_785;
+const AFTER_RPS = 6_577;
+const BEFORE_P50 = 21;
+const AFTER_P50 = 13;
+
+const BEFORE_LAYERS = [
+ { label: 'ab client', warning: false },
+ { label: 'uvicorn \u00B7 1 worker', warning: false },
+ { label: 'ASGI Middleware', warning: false },
+ { label: 'BaseHTTPMiddleware', warning: true },
+ { label: 'GET /health \u2192 "ok"', warning: false },
+];
+
+const AFTER_LAYERS = [
+ { label: 'ab client', warning: false },
+ { label: 'uvicorn \u00B7 1 worker', warning: false },
+ { label: 'ASGI Middleware', warning: false },
+ { label: 'ASGI Middleware', warning: false },
+ { label: 'GET /health \u2192 "ok"', warning: false },
+];
+
+const BENCHMARK_RUNS = [
+ { config: 'Before (1 ASGI + 1 BaseHTTP)', run: 1, rps: 3596, p50: 21 },
+ { config: 'Before (1 ASGI + 1 BaseHTTP)', run: 2, rps: 3599, p50: 21 },
+ { config: 'Before (1 ASGI + 1 BaseHTTP)', run: 3, rps: 4161, p50: 21 },
+ { config: 'After (2x Pure ASGI)', run: 1, rps: 6504, p50: 13 },
+ { config: 'After (2x Pure ASGI)', run: 2, rps: 6631, p50: 13 },
+ { config: 'After (2x Pure ASGI)', run: 3, rps: 6595, p50: 13 },
+];
+
+/* ── Dot type ── */
+interface Dot {
+ id: number;
+ progress: number; // 0..1 (top to bottom)
+}
+
+/* ── Component ── */
+export default function BenchmarkVisualization() {
+ const [elapsed, setElapsed] = useState(0);
+ const [running, setRunning] = useState(false);
+ const [afterDone, setAfterDone] = useState(false);
+ const [beforeDone, setBeforeDone] = useState(false);
+ const [tableOpen, setTableOpen] = useState(false);
+ const [beforeDots, setBeforeDots] = useState7 steps per request
+
+ {STAGES.map((stage, i) => (
+
+
+
+ ))}
+ handleStageClick(i)}
+ role="button"
+ tabIndex={0}
+ onKeyDown={(e) => {
+ if (e.key === 'Enter' || e.key === ' ') handleStageClick(i);
+ }}
+ >
+
+ {i + 1}
+ {stage.label}
+ {stage.subtitle}
+
+ {expandedStage !== null && (
+
+
+ {STAGES[expandedStage].code}
+
+ )}
+
+ | null>(null);
+
+ const clearTimer = useCallback(() => {
+ if (timerRef.current !== null) {
+ clearTimeout(timerRef.current);
+ timerRef.current = null;
+ }
+ }, []);
+
+ useEffect(() => {
+ const advance = () => {
+ setActiveStage((prev) => {
+ const next = (prev + 1) % STAGES.length;
+ if (next === 0) {
+ timerRef.current = setTimeout(() => {
+ timerRef.current = setTimeout(advance, INTERVAL_MS);
+ }, PAUSE_MS);
+ return next;
+ }
+ timerRef.current = setTimeout(advance, INTERVAL_MS);
+ return next;
+ });
+ };
+
+ timerRef.current = setTimeout(advance, INTERVAL_MS);
+ return clearTimer;
+ }, [clearTimer]);
+
+ return (
+
" + + # Use team alias or generic greeting + team_alias = event.team_alias or "Team" + + email_html_content = TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE.format( + email_logo_url=email_params.logo_url, + team_alias=team_alias, + soft_budget=soft_budget_str, + spend=spend_str, + max_budget_info=max_budget_info, + base_url=email_params.base_url, + email_support_contact=email_params.support_contact, + ) + + # Send email to all recipients + await self.send_email( + from_email=self.DEFAULT_LITELLM_EMAIL, + to_email=recipient_emails, + subject=email_params.subject, + html_body=email_html_content, + ) + pass + async def send_max_budget_alert_email(self, event: WebhookEvent): """ Send email to user when max budget alert threshold is reached @@ -285,15 +364,36 @@ class BaseEmailLogger(CustomLogger): # - Don't re-alert, if alert already sent _cache: DualCache = self.internal_usage_cache - # percent of max_budget left to spend - if user_info.max_budget is None and user_info.soft_budget is None: - return - # For soft_budget alerts, check if we've already sent an alert if type == "soft_budget": + # For team soft budget alerts, we only need team soft_budget to be set + # For other entity types, we need either max_budget or soft_budget + if user_info.event_group == Litellm_EntityType.TEAM: + if user_info.soft_budget is None: + return + # For team soft budget alerts, require alert_emails to be configured + # Team soft budget alerts are sent via metadata.soft_budget_alerting_emails + if user_info.alert_emails is None or len(user_info.alert_emails) == 0: + verbose_proxy_logger.debug( + "Skipping team soft budget email alert: no alert_emails configured", + ) + return + else: + # For non-team alerts, require either max_budget or soft_budget + if user_info.max_budget is None and user_info.soft_budget is None: + return if user_info.soft_budget is not None and user_info.spend >= user_info.soft_budget: # Generate cache key based on event type and identifier - _id = user_info.token or user_info.user_id or "default_id" + # Use appropriate ID based on event_group to ensure unique cache keys per entity type + if user_info.event_group == Litellm_EntityType.TEAM: + _id = user_info.team_id or "default_id" + elif user_info.event_group == Litellm_EntityType.ORGANIZATION: + _id = user_info.organization_id or "default_id" + elif user_info.event_group == Litellm_EntityType.USER: + _id = user_info.user_id or "default_id" + else: + # For KEY and other types, use token or user_id + _id = user_info.token or user_info.user_id or "default_id" _cache_key = f"email_budget_alerts:soft_budget_crossed:{_id}" # Check if we've already sent this alert @@ -318,10 +418,15 @@ class BaseEmailLogger(CustomLogger): projected_exceeded_date=user_info.projected_exceeded_date, projected_spend=user_info.projected_spend, event_group=user_info.event_group, + alert_emails=user_info.alert_emails, ) try: - await self.send_soft_budget_alert_email(webhook_event) + # Use team-specific function for team alerts, otherwise use standard function + if user_info.event_group == Litellm_EntityType.TEAM: + await self.send_team_soft_budget_alert_email(webhook_event) + else: + await self.send_soft_budget_alert_email(webhook_event) # Cache the alert to prevent duplicate sends await _cache.async_set_cache( diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index c5aaa0a3407..eca5cdb97df 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-enterprise" -version = "0.1.29" +version = "0.1.31" description = "Package for LiteLLM Enterprise features" authors = ["BerriAI"] readme = "README.md" @@ -22,7 +22,7 @@ requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "0.1.29" +version = "0.1.31" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-enterprise==", diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl new file mode 100644 index 00000000000..90b36bd78ac Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz new file mode 100644 index 00000000000..64607235479 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl new file mode 100644 index 00000000000..deb9653aa78 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz new file mode 100644 index 00000000000..212194e31e2 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl new file mode 100644 index 00000000000..a4872243ae6 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz new file mode 100644 index 00000000000..643be22aa42 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz differ diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql new file mode 100644 index 00000000000..a64f1de342f --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_TeamTable" ADD COLUMN "soft_budget" DOUBLE PRECISION; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql new file mode 100644 index 00000000000..1efde3dbe0f --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_MCPServerTable" ADD COLUMN "available_on_public_internet" BOOLEAN NOT NULL DEFAULT false; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql new file mode 100644 index 00000000000..abfb153061b --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_DeletedTeamTable" ADD COLUMN "soft_budget" DOUBLE PRECISION; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql new file mode 100644 index 00000000000..572eea9b529 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql @@ -0,0 +1,8 @@ +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_user_id_team_id_idx" ON "LiteLLM_VerificationToken"("user_id", "team_id"); + +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_team_id_idx" ON "LiteLLM_VerificationToken"("team_id"); + +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_budget_reset_at_expires_idx" ON "LiteLLM_VerificationToken"("budget_reset_at", "expires"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index dc49036cb15..b1ca1f71c9e 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -113,6 +113,7 @@ model LiteLLM_TeamTable { members_with_roles Json @default("{}") metadata Json @default("{}") max_budget Float? + soft_budget Float? spend Float @default(0.0) models String[] max_parallel_requests Int? @@ -147,6 +148,7 @@ model LiteLLM_DeletedTeamTable { members_with_roles Json @default("{}") metadata Json @default("{}") max_budget Float? + soft_budget Float? spend Float @default(0.0) models String[] max_parallel_requests Int? @@ -262,6 +264,7 @@ model LiteLLM_MCPServerTable { token_url String? registration_url String? allow_all_keys Boolean @default(false) + available_on_public_internet Boolean @default(false) } // Generate Tokens for Proxy @@ -307,6 +310,16 @@ model LiteLLM_VerificationToken { litellm_budget_table LiteLLM_BudgetTable? @relation(fields: [budget_id], references: [budget_id]) litellm_organization_table LiteLLM_OrganizationTable? @relation(fields: [organization_id], references: [organization_id]) object_permission LiteLLM_ObjectPermissionTable? @relation(fields: [object_permission_id], references: [object_permission_id]) + + // SELECT COUNT(*) FROM (SELECT "public"."LiteLLM_VerificationToken"."token" FROM "public"."LiteLLM_VerificationToken" WHERE ("public"."LiteLLM_VerificationToken"."user_id" = $1 AND ("public"."LiteLLM_VerificationToken"."team_id" IS NULL OR "public"."LiteLLM_VerificationToken"."team_id" <> $2)) OFFSET $3 ) AS "sub" + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE "public"."LiteLLM_VerificationToken"."user_id" = $1 OFFSET $2 + @@index([user_id, team_id]) + + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE "public"."LiteLLM_VerificationToken"."team_id" = $1 OFFSET $2 + @@index([team_id]) + + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE (("public"."LiteLLM_VerificationToken"."expires" IS NULL OR "public"."LiteLLM_VerificationToken"."expires" > $1) AND "public"."LiteLLM_VerificationToken"."budget_reset_at" < $2) OFFSET $3 + @@index([budget_reset_at, expires]) } // Audit table for deleted keys - preserves spend and key information for historical tracking diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index d43b591686c..8937858bbd9 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-proxy-extras" -version = "0.4.30" +version = "0.4.33" 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 = "0.4.30" +version = "0.4.33" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-proxy-extras==", diff --git a/litellm/a2a_protocol/__init__.py b/litellm/a2a_protocol/__init__.py index d8d349bb98a..85c03687e25 100644 --- a/litellm/a2a_protocol/__init__.py +++ b/litellm/a2a_protocol/__init__.py @@ -39,6 +39,12 @@ Example usage (class-based): """ from litellm.a2a_protocol.client import A2AClient +from litellm.a2a_protocol.exceptions import ( + A2AAgentCardError, + A2AConnectionError, + A2AError, + A2ALocalhostURLError, +) from litellm.a2a_protocol.main import ( aget_agent_card, asend_message, @@ -49,11 +55,19 @@ from litellm.a2a_protocol.main import ( from litellm.types.agents import LiteLLMSendMessageResponse __all__ = [ + # Client "A2AClient", + # Functions "asend_message", "send_message", "asend_message_streaming", "aget_agent_card", "create_a2a_client", + # Response types "LiteLLMSendMessageResponse", + # Exceptions + "A2AError", + "A2AConnectionError", + "A2AAgentCardError", + "A2ALocalhostURLError", ] diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py index 7c4c5af149d..4c5dd3e3ba6 100644 --- a/litellm/a2a_protocol/card_resolver.py +++ b/litellm/a2a_protocol/card_resolver.py @@ -7,6 +7,7 @@ Extends the A2A SDK's card resolver to support multiple well-known paths. from typing import TYPE_CHECKING, Any, Dict, Optional from litellm._logging import verbose_logger +from litellm.constants import LOCALHOST_URL_PATTERNS if TYPE_CHECKING: from a2a.types import AgentCard @@ -26,15 +27,61 @@ except ImportError: pass +def is_localhost_or_internal_url(url: Optional[str]) -> bool: + """ + Check if a URL is a localhost or internal URL. + + This detects common development URLs that are accidentally left in + agent cards when deploying to production. + + Args: + url: The URL to check + + Returns: + True if the URL is localhost/internal + """ + if not url: + return False + + url_lower = url.lower() + + return any(pattern in url_lower for pattern in LOCALHOST_URL_PATTERNS) + + +def fix_agent_card_url(agent_card: "AgentCard", base_url: str) -> "AgentCard": + """ + Fix the agent card URL if it contains a localhost/internal address. + + Many A2A agents are deployed with agent cards that contain internal URLs + like "http://0.0.0.0:8001/" or "http://localhost:8000/". This function + replaces such URLs with the provided base_url. + + Args: + agent_card: The agent card to fix + base_url: The base URL to use as replacement + + Returns: + The agent card with the URL fixed if necessary + """ + card_url = getattr(agent_card, "url", None) + + if card_url and is_localhost_or_internal_url(card_url): + # Normalize base_url to ensure it ends with / + fixed_url = base_url.rstrip("/") + "/" + agent_card.url = fixed_url + + return agent_card + + class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] """ Custom A2A card resolver that supports multiple well-known paths. - + Extends the base A2ACardResolver to try both: - /.well-known/agent-card.json (standard) - /.well-known/agent.json (previous/alternative) """ - + async def get_agent_card( self, relative_card_path: Optional[str] = None, @@ -42,17 +89,17 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] ) -> "AgentCard": """ Fetch the agent card, trying multiple well-known paths. - + First tries the standard path, then falls back to the previous path. - + Args: relative_card_path: Optional path to the agent card endpoint. If None, tries both well-known paths. http_kwargs: Optional dictionary of keyword arguments to pass to httpx.get - + Returns: AgentCard from the A2A agent - + Raises: A2AClientHTTPError or A2AClientJSONError if both paths fail """ @@ -62,13 +109,13 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] relative_card_path=relative_card_path, http_kwargs=http_kwargs, ) - + # Try both well-known paths paths = [ AGENT_CARD_WELL_KNOWN_PATH, PREV_AGENT_CARD_WELL_KNOWN_PATH, ] - + last_error = None for path in paths: try: @@ -85,11 +132,11 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] ) last_error = e continue - + # If we get here, all paths failed - re-raise the last error if last_error is not None: raise last_error - + # This shouldn't happen, but just in case raise Exception( f"Failed to fetch agent card from {self.base_url}. " diff --git a/litellm/a2a_protocol/exception_mapping_utils.py b/litellm/a2a_protocol/exception_mapping_utils.py new file mode 100644 index 00000000000..49dbb22b158 --- /dev/null +++ b/litellm/a2a_protocol/exception_mapping_utils.py @@ -0,0 +1,203 @@ +""" +A2A Protocol Exception Mapping Utils. + +Maps A2A SDK exceptions to LiteLLM A2A exception types. +""" + +from typing import TYPE_CHECKING, Any, Optional + +from litellm._logging import verbose_logger +from litellm.a2a_protocol.card_resolver import ( + fix_agent_card_url, + is_localhost_or_internal_url, +) +from litellm.a2a_protocol.exceptions import ( + A2AAgentCardError, + A2AConnectionError, + A2AError, + A2ALocalhostURLError, +) +from litellm.constants import CONNECTION_ERROR_PATTERNS + +if TYPE_CHECKING: + from a2a.client import A2AClient as A2AClientType + + +# Runtime import +A2A_SDK_AVAILABLE = False +try: + from a2a.client import A2AClient as _A2AClient # type: ignore[no-redef] + + A2A_SDK_AVAILABLE = True +except ImportError: + _A2AClient = None # type: ignore[assignment, misc] + + +class A2AExceptionCheckers: + """ + Helper class for checking various A2A error conditions. + """ + + @staticmethod + def is_connection_error(error_str: str) -> bool: + """ + Check if an error string indicates a connection error. + + Args: + error_str: The error string to check + + Returns: + True if the error indicates a connection issue + """ + if not isinstance(error_str, str): + return False + + error_str_lower = error_str.lower() + return any(pattern in error_str_lower for pattern in CONNECTION_ERROR_PATTERNS) + + @staticmethod + def is_localhost_url(url: Optional[str]) -> bool: + """ + Check if a URL is a localhost/internal URL. + + Args: + url: The URL to check + + Returns: + True if the URL is localhost/internal + """ + return is_localhost_or_internal_url(url) + + @staticmethod + def is_agent_card_error(error_str: str) -> bool: + """ + Check if an error string indicates an agent card error. + + Args: + error_str: The error string to check + + Returns: + True if the error is related to agent card fetching/parsing + """ + if not isinstance(error_str, str): + return False + + error_str_lower = error_str.lower() + agent_card_patterns = [ + "agent card", + "agent-card", + ".well-known", + "card not found", + "invalid agent", + ] + return any(pattern in error_str_lower for pattern in agent_card_patterns) + + +def map_a2a_exception( + original_exception: Exception, + card_url: Optional[str] = None, + api_base: Optional[str] = None, + model: Optional[str] = None, +) -> Exception: + """ + Map an A2A SDK exception to a LiteLLM A2A exception type. + + Args: + original_exception: The original exception from the A2A SDK + card_url: The URL from the agent card (if available) + api_base: The original API base URL + model: The model/agent name + + Returns: + A mapped LiteLLM A2A exception + + Raises: + A2ALocalhostURLError: If the error is a connection error to a localhost URL + A2AConnectionError: If the error is a general connection error + A2AAgentCardError: If the error is related to agent card issues + A2AError: For other A2A-related errors + """ + error_str = str(original_exception) + + # Check for localhost URL connection error (special case - retryable) + if ( + card_url + and api_base + and A2AExceptionCheckers.is_localhost_url(card_url) + and A2AExceptionCheckers.is_connection_error(error_str) + ): + raise A2ALocalhostURLError( + localhost_url=card_url, + base_url=api_base, + original_error=original_exception, + model=model, + ) + + # Check for agent card errors + if A2AExceptionCheckers.is_agent_card_error(error_str): + raise A2AAgentCardError( + message=error_str, + url=api_base, + model=model, + ) + + # Check for general connection errors + if A2AExceptionCheckers.is_connection_error(error_str): + raise A2AConnectionError( + message=error_str, + url=card_url or api_base, + model=model, + ) + + # Default: wrap in generic A2AError + raise A2AError( + message=error_str, + model=model, + ) + + +def handle_a2a_localhost_retry( + error: A2ALocalhostURLError, + agent_card: Any, + a2a_client: "A2AClientType", + is_streaming: bool = False, +) -> "A2AClientType": + """ + Handle A2ALocalhostURLError by fixing the URL and creating a new client. + + This is called when we catch an A2ALocalhostURLError and want to retry + with the corrected URL. + + Args: + error: The localhost URL error + agent_card: The agent card object to fix + a2a_client: The current A2A client + is_streaming: Whether this is a streaming request (for logging) + + Returns: + A new A2A client with the fixed URL + + Raises: + ImportError: If the A2A SDK is not installed + """ + if not A2A_SDK_AVAILABLE or _A2AClient is None: + raise ImportError( + "A2A SDK is required for localhost retry handling. " + "Install it with: pip install a2a" + ) + + request_type = "streaming " if is_streaming else "" + verbose_logger.warning( + f"A2A {request_type}request to '{error.localhost_url}' failed: {error.original_error}. " + f"Agent card contains localhost/internal URL. " + f"Retrying with base_url '{error.base_url}'." + ) + + # Fix the agent card URL + fix_agent_card_url(agent_card, error.base_url) + + # Create a new client with the fixed agent card (transport caches URL) + return _A2AClient( + httpx_client=a2a_client._transport.httpx_client, # type: ignore[union-attr] + agent_card=agent_card, + ) diff --git a/litellm/a2a_protocol/exceptions.py b/litellm/a2a_protocol/exceptions.py new file mode 100644 index 00000000000..546b23105be --- /dev/null +++ b/litellm/a2a_protocol/exceptions.py @@ -0,0 +1,150 @@ +""" +A2A Protocol Exceptions. + +Custom exception types for A2A protocol operations, following LiteLLM's exception pattern. +""" + +from typing import Optional + +import httpx + + +class A2AError(Exception): + """ + Base exception for A2A protocol errors. + + Follows the same pattern as LiteLLM's main exceptions. + """ + + def __init__( + self, + message: str, + status_code: int = 500, + llm_provider: str = "a2a_agent", + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + max_retries: Optional[int] = None, + num_retries: Optional[int] = None, + ): + self.status_code = status_code + self.message = f"litellm.A2AError: {message}" + self.llm_provider = llm_provider + self.model = model + self.litellm_debug_info = litellm_debug_info + self.max_retries = max_retries + self.num_retries = num_retries + self.response = response or httpx.Response( + status_code=self.status_code, + request=httpx.Request(method="POST", url="https://litellm.ai"), + ) + super().__init__(self.message) + + def __str__(self) -> str: + _message = self.message + if self.num_retries: + _message += f" LiteLLM Retried: {self.num_retries} times" + if self.max_retries: + _message += f", LiteLLM Max Retries: {self.max_retries}" + return _message + + def __repr__(self) -> str: + return self.__str__() + + +class A2AConnectionError(A2AError): + """ + Raised when connection to an A2A agent fails. + + This typically occurs when: + - The agent is unreachable + - The agent card contains a localhost/internal URL + - Network issues prevent connection + """ + + def __init__( + self, + message: str, + url: Optional[str] = None, + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + max_retries: Optional[int] = None, + num_retries: Optional[int] = None, + ): + self.url = url + super().__init__( + message=message, + status_code=503, + llm_provider="a2a_agent", + model=model, + response=response, + litellm_debug_info=litellm_debug_info, + max_retries=max_retries, + num_retries=num_retries, + ) + + +class A2AAgentCardError(A2AError): + """ + Raised when there's an issue with the agent card. + + This includes: + - Failed to fetch agent card + - Invalid agent card format + - Missing required fields + """ + + def __init__( + self, + message: str, + url: Optional[str] = None, + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + ): + self.url = url + super().__init__( + message=message, + status_code=404, + llm_provider="a2a_agent", + model=model, + response=response, + litellm_debug_info=litellm_debug_info, + ) + + +class A2ALocalhostURLError(A2AConnectionError): + """ + Raised when an agent card contains a localhost/internal URL. + + Many A2A agents are deployed with agent cards that contain internal URLs + like "http://0.0.0.0:8001/" or "http://localhost:8000/". This error + indicates that the URL needs to be corrected and the request should be retried. + + Attributes: + localhost_url: The localhost/internal URL found in the agent card + base_url: The public base URL that should be used instead + original_error: The original connection error that was raised + """ + + def __init__( + self, + localhost_url: str, + base_url: str, + original_error: Optional[Exception] = None, + model: Optional[str] = None, + ): + self.localhost_url = localhost_url + self.base_url = base_url + self.original_error = original_error + + message = ( + f"Agent card contains localhost/internal URL '{localhost_url}'. " + f"Retrying with base URL '{base_url}'." + ) + super().__init__( + message=message, + url=localhost_url, + model=model, + ) diff --git a/litellm/a2a_protocol/main.py b/litellm/a2a_protocol/main.py index b326f9e7ed5..642dfaf023c 100644 --- a/litellm/a2a_protocol/main.py +++ b/litellm/a2a_protocol/main.py @@ -44,6 +44,11 @@ except ImportError: # Import our custom card resolver that supports multiple well-known paths from litellm.a2a_protocol.card_resolver import LiteLLMA2ACardResolver +from litellm.a2a_protocol.exception_mapping_utils import ( + handle_a2a_localhost_retry, + map_a2a_exception, +) +from litellm.a2a_protocol.exceptions import A2ALocalhostURLError # Use our custom resolver instead of the default A2A SDK resolver A2ACardResolver = LiteLLMA2ACardResolver @@ -244,10 +249,50 @@ async def asend_message( verbose_logger.info(f"A2A send_message request_id={request.id}, agent={agent_name}") - a2a_response = await a2a_client.send_message(request) + # Get agent card URL for localhost retry logic + agent_card = getattr(a2a_client, "_litellm_agent_card", None) or getattr( + a2a_client, "agent_card", None + ) + card_url = getattr(agent_card, "url", None) if agent_card else None + + # Retry loop: if connection fails due to localhost URL in agent card, retry with fixed URL + a2a_response = None + for _ in range(2): # max 2 attempts: original + 1 retry + try: + a2a_response = await a2a_client.send_message(request) + break # success, exit retry loop + except A2ALocalhostURLError as e: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=e, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=False, + ) + card_url = agent_card.url if agent_card else None + except Exception as e: + # Map exception - will raise A2ALocalhostURLError if applicable + try: + map_a2a_exception(e, card_url, api_base, model=agent_name) + except A2ALocalhostURLError as localhost_err: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=localhost_err, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=False, + ) + card_url = agent_card.url if agent_card else None + continue + except Exception: + # Re-raise the mapped exception + raise verbose_logger.info(f"A2A send_message completed, request_id={request.id}") + # a2a_response is guaranteed to be set if we reach here (loop breaks on success or raises) + assert a2a_response is not None + # Wrap in LiteLLM response type for _hidden_params support response = LiteLLMSendMessageResponse.from_a2a_response(a2a_response) @@ -307,6 +352,48 @@ def send_message( ) +def _build_streaming_logging_obj( + request: "SendStreamingMessageRequest", + agent_name: str, + agent_id: Optional[str], + litellm_params: Optional[Dict[str, Any]], + metadata: Optional[Dict[str, Any]], + proxy_server_request: Optional[Dict[str, Any]], +) -> Logging: + """Build logging object for streaming A2A requests.""" + start_time = datetime.datetime.now() + model = f"a2a_agent/{agent_name}" + + logging_obj = Logging( + model=model, + messages=[{"role": "user", "content": "streaming-request"}], + stream=False, + call_type="asend_message_streaming", + start_time=start_time, + litellm_call_id=str(request.id), + function_id=str(request.id), + ) + logging_obj.model = model + logging_obj.custom_llm_provider = "a2a_agent" + logging_obj.model_call_details["model"] = model + logging_obj.model_call_details["custom_llm_provider"] = "a2a_agent" + if agent_id: + logging_obj.model_call_details["agent_id"] = agent_id + + _litellm_params = litellm_params.copy() if litellm_params else {} + if metadata: + _litellm_params["metadata"] = metadata + if proxy_server_request: + _litellm_params["proxy_server_request"] = proxy_server_request + + logging_obj.litellm_params = _litellm_params + logging_obj.optional_params = _litellm_params + logging_obj.model_call_details["litellm_params"] = _litellm_params + logging_obj.model_call_details["metadata"] = metadata or {} + + return logging_obj + + async def asend_message_streaming( a2a_client: Optional["A2AClientType"] = None, request: Optional["SendStreamingMessageRequest"] = None, @@ -403,55 +490,72 @@ async def asend_message_streaming( verbose_logger.info(f"A2A send_message_streaming request_id={request.id}") - # Track for logging - start_time = datetime.datetime.now() - stream = a2a_client.send_message_streaming(request) - # Build logging object for streaming completion callbacks agent_card = getattr(a2a_client, "_litellm_agent_card", None) or getattr( a2a_client, "agent_card", None ) + card_url = getattr(agent_card, "url", None) if agent_card else None agent_name = getattr(agent_card, "name", "unknown") if agent_card else "unknown" - model = f"a2a_agent/{agent_name}" - logging_obj = Logging( - model=model, - messages=[{"role": "user", "content": "streaming-request"}], - stream=False, # complete response logging after stream ends - call_type="asend_message_streaming", - start_time=start_time, - litellm_call_id=str(request.id), - function_id=str(request.id), - ) - logging_obj.model = model - logging_obj.custom_llm_provider = "a2a_agent" - logging_obj.model_call_details["model"] = model - logging_obj.model_call_details["custom_llm_provider"] = "a2a_agent" - if agent_id: - logging_obj.model_call_details["agent_id"] = agent_id - - # Propagate litellm_params for spend logging (includes cost_per_query, etc.) - _litellm_params = litellm_params.copy() if litellm_params else {} - # Merge metadata into litellm_params.metadata (required for proxy cost tracking) - if metadata: - _litellm_params["metadata"] = metadata - if proxy_server_request: - _litellm_params["proxy_server_request"] = proxy_server_request - - logging_obj.litellm_params = _litellm_params - logging_obj.optional_params = _litellm_params # used by cost calc - logging_obj.model_call_details["litellm_params"] = _litellm_params - logging_obj.model_call_details["metadata"] = metadata or {} - - iterator = A2AStreamingIterator( - stream=stream, + logging_obj = _build_streaming_logging_obj( request=request, - logging_obj=logging_obj, agent_name=agent_name, + agent_id=agent_id, + litellm_params=litellm_params, + metadata=metadata, + proxy_server_request=proxy_server_request, ) - async for chunk in iterator: - yield chunk + # Retry loop: if connection fails due to localhost URL in agent card, retry with fixed URL + # Connection errors in streaming typically occur on first chunk iteration + first_chunk = True + for attempt in range(2): # max 2 attempts: original + 1 retry + stream = a2a_client.send_message_streaming(request) + iterator = A2AStreamingIterator( + stream=stream, + request=request, + logging_obj=logging_obj, + agent_name=agent_name, + ) + + try: + first_chunk = True + async for chunk in iterator: + if first_chunk: + first_chunk = False # connection succeeded + yield chunk + return # stream completed successfully + except A2ALocalhostURLError as e: + # Only retry on first chunk, not mid-stream + if first_chunk and attempt == 0: + a2a_client = handle_a2a_localhost_retry( + error=e, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=True, + ) + card_url = agent_card.url if agent_card else None + else: + raise + except Exception as e: + # Only map exception on first chunk + if first_chunk and attempt == 0: + try: + map_a2a_exception(e, card_url, api_base, model=agent_name) + except A2ALocalhostURLError as localhost_err: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=localhost_err, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=True, + ) + card_url = agent_card.url if agent_card else None + continue + except Exception: + # Re-raise the mapped exception + raise + raise async def create_a2a_client( diff --git a/litellm/anthropic_beta_headers_config.json b/litellm/anthropic_beta_headers_config.json new file mode 100644 index 00000000000..193091c0176 --- /dev/null +++ b/litellm/anthropic_beta_headers_config.json @@ -0,0 +1,30 @@ +{ + "description": "Unsupported Anthropic beta headers for each provider. Headers listed here will be dropped. Headers not listed are passed through as-is.", + "anthropic": [], + "azure_ai": [], + "bedrock_converse": [ + "prompt-caching-scope-2026-01-05", + "bash_20250124", + "bash_20241022", + "text_editor_20250124", + "text_editor_20241022", + "compact-2026-01-12", + "advanced-tool-use-2025-11-20", + "web-fetch-2025-09-10", + "code-execution-2025-08-25", + "skills-2025-10-02", + "files-api-2025-04-14" + ], + "bedrock": [ + "advanced-tool-use-2025-11-20", + "prompt-caching-scope-2026-01-05", + "structured-outputs-2025-11-13", + "web-fetch-2025-09-10", + "code-execution-2025-08-25", + "skills-2025-10-02", + "files-api-2025-04-14" + ], + "vertex_ai": [ + "prompt-caching-scope-2026-01-05" + ] +} diff --git a/litellm/anthropic_beta_headers_manager.py b/litellm/anthropic_beta_headers_manager.py new file mode 100644 index 00000000000..2643f4c03fa --- /dev/null +++ b/litellm/anthropic_beta_headers_manager.py @@ -0,0 +1,221 @@ +""" +Centralized manager for Anthropic beta headers across different providers. + +This module provides utilities to: +1. Load beta header configuration from JSON (lists unsupported headers per provider) +2. Filter out unsupported beta headers +3. Handle provider-specific header name mappings (e.g., advanced-tool-use -> tool-search-tool) + +Design: +- JSON config lists UNSUPPORTED headers for each provider +- Headers not in the unsupported list are passed through +- Header mappings allow renaming headers for specific providers +""" + +import json +import os +from typing import Dict, List, Optional, Set + +from litellm.litellm_core_utils.litellm_logging import verbose_logger + +# Cache for the loaded configuration +_BETA_HEADERS_CONFIG: Optional[Dict] = None + + +def _load_beta_headers_config() -> Dict: + """ + Load the beta headers configuration from JSON file. + Uses caching to avoid repeated file reads. + + Returns: + Dict containing the beta headers configuration + """ + global _BETA_HEADERS_CONFIG + + if _BETA_HEADERS_CONFIG is not None: + return _BETA_HEADERS_CONFIG + + config_path = os.path.join( + os.path.dirname(__file__), + "anthropic_beta_headers_config.json" + ) + + try: + with open(config_path, "r") as f: + _BETA_HEADERS_CONFIG = json.load(f) + verbose_logger.debug(f"Loaded beta headers config from {config_path}") + return _BETA_HEADERS_CONFIG + except Exception as e: + verbose_logger.error(f"Failed to load beta headers config: {e}") + # Return empty config as fallback + return { + "anthropic": [], + "azure_ai": [], + "bedrock": [], + "bedrock_converse": [], + "vertex_ai": [] + } + + +def get_provider_name(provider: str) -> str: + """ + Resolve provider aliases to canonical provider names. + + Args: + provider: Provider name (may be an alias) + + Returns: + Canonical provider name + """ + config = _load_beta_headers_config() + aliases = config.get("provider_aliases", {}) + return aliases.get(provider, provider) + + +def filter_and_transform_beta_headers( + beta_headers: List[str], + provider: str, +) -> List[str]: + """ + Filter beta headers based on provider's unsupported list. + + This function: + 1. Removes headers that are in the provider's unsupported list + 2. Passes through all other headers as-is + + Note: Header transformations/mappings (e.g., advanced-tool-use -> tool-search-tool) + are handled in each provider's transformation code, not here. + + Args: + beta_headers: List of Anthropic beta header values + provider: Provider name (e.g., "anthropic", "bedrock", "vertex_ai") + + Returns: + List of filtered beta headers for the provider + """ + if not beta_headers: + return [] + + config = _load_beta_headers_config() + provider = get_provider_name(provider) + + # Get unsupported headers for this provider + unsupported_headers = set(config.get(provider, [])) + + filtered_headers: Set[str] = set() + + for header in beta_headers: + header = header.strip() + + # Skip if header is unsupported + if header in unsupported_headers: + verbose_logger.debug( + f"Dropping unsupported beta header '{header}' for provider '{provider}'" + ) + continue + + # Pass through as-is + filtered_headers.add(header) + + return sorted(list(filtered_headers)) + + +def is_beta_header_supported( + beta_header: str, + provider: str, +) -> bool: + """ + Check if a specific beta header is supported by a provider. + + Args: + beta_header: The Anthropic beta header value + provider: Provider name + + Returns: + True if the header is supported (not in unsupported list), False otherwise + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + unsupported_headers = set(config.get(provider, [])) + return beta_header not in unsupported_headers + + +def get_provider_beta_header( + anthropic_beta_header: str, + provider: str, +) -> Optional[str]: + """ + Check if a beta header is supported by a provider. + + Note: This does NOT handle header transformations/mappings. + Those are handled in each provider's transformation code. + + Args: + anthropic_beta_header: The Anthropic beta header value + provider: Provider name + + Returns: + The original header if supported, or None if unsupported + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + + # Check if unsupported + unsupported_headers = set(config.get(provider, [])) + if anthropic_beta_header in unsupported_headers: + return None + + return anthropic_beta_header + + +def update_headers_with_filtered_beta( + headers: dict, + provider: str, +) -> dict: + """ + Update headers dict by filtering and transforming anthropic-beta header values. + Modifies the headers dict in place and returns it. + + Args: + headers: Request headers dict (will be modified in place) + provider: Provider name + + Returns: + Updated headers dict + """ + existing_beta = headers.get("anthropic-beta") + if not existing_beta: + return headers + + # Parse existing beta headers + beta_values = [b.strip() for b in existing_beta.split(",") if b.strip()] + + # Filter and transform based on provider + filtered_beta_values = filter_and_transform_beta_headers( + beta_headers=beta_values, + provider=provider, + ) + + # Update or remove the header + if filtered_beta_values: + headers["anthropic-beta"] = ",".join(filtered_beta_values) + else: + # Remove the header if no values remain + headers.pop("anthropic-beta", None) + + return headers + + +def get_unsupported_headers(provider: str) -> List[str]: + """ + Get all beta headers that are unsupported by a provider. + + Args: + provider: Provider name + + Returns: + List of unsupported Anthropic beta header names + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + return config.get(provider, []) diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py index ea7e3f5a979..03d09ecc041 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -1123,7 +1123,7 @@ class RedisCache(BaseCache): redis_client = redis_async.Redis(**self.redis_kwargs) # Test the connection - ping_result = await redis_client.ping() + ping_result = await redis_client.ping() # type: ignore[misc] # Close the connection await redis_client.aclose() # type: ignore[attr-defined] diff --git a/litellm/caching/redis_cluster_cache.py b/litellm/caching/redis_cluster_cache.py index 91fcf1d7288..664578c8700 100644 --- a/litellm/caching/redis_cluster_cache.py +++ b/litellm/caching/redis_cluster_cache.py @@ -83,7 +83,7 @@ class RedisClusterCache(RedisCache): ) # Test the connection - ping_result = await redis_client.ping() # type: ignore[attr-defined] + ping_result = await redis_client.ping() # type: ignore[attr-defined, misc] # Close the connection await redis_client.aclose() # type: ignore[attr-defined] diff --git a/litellm/constants.py b/litellm/constants.py index 872ad899f84..3c618723d64 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -306,6 +306,22 @@ DEFAULT_MAX_TOKENS_FOR_TRITON = int(os.getenv("DEFAULT_MAX_TOKENS_FOR_TRITON", 2 #### Networking settings #### request_timeout: float = float(os.getenv("REQUEST_TIMEOUT", 6000)) # time in seconds DEFAULT_A2A_AGENT_TIMEOUT: float = float(os.getenv("DEFAULT_A2A_AGENT_TIMEOUT", 6000)) # 10 minutes +# Patterns that indicate a localhost/internal URL in A2A agent cards that should be +# replaced with the original base_url. This is a common misconfiguration where +# developers deploy agents with development URLs in their agent cards. +LOCALHOST_URL_PATTERNS: List[str] = [ + "localhost", + "127.0.0.1", + "0.0.0.0", + "[::1]", # IPv6 localhost +] +# Patterns in error messages that indicate a connection failure +CONNECTION_ERROR_PATTERNS: List[str] = [ + "connect", + "connection", + "network", + "refused", +] STREAM_SSE_DONE_STRING: str = "[DONE]" STREAM_SSE_DATA_PREFIX: str = "data: " ### SPEND TRACKING ### @@ -970,6 +986,8 @@ BEDROCK_CONVERSE_MODELS = [ "openai.gpt-oss-120b-1:0", "anthropic.claude-haiku-4-5-20251001-v1:0", "anthropic.claude-sonnet-4-5-20250929-v1:0", + "anthropic.claude-opus-4-6-v1:0", + "anthropic.claude-opus-4-6-v1", "anthropic.claude-opus-4-1-20250805-v1:0", "anthropic.claude-opus-4-20250514-v1:0", "anthropic.claude-sonnet-4-20250514-v1:0", diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index bef4d52ce49..4ea22dbd90f 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -1,5 +1,6 @@ # What is this? ## File for 'response_cost' calculation in Logging +import logging import time from functools import lru_cache from typing import TYPE_CHECKING, Any, List, Literal, Optional, Tuple, Union, cast @@ -774,10 +775,11 @@ def _apply_cost_discount( discount_amount = original_cost * discount_percent final_cost = original_cost - discount_amount - verbose_logger.debug( - f"Applied {discount_percent*100}% discount to {custom_llm_provider}: " - f"${original_cost:.6f} -> ${final_cost:.6f} (saved ${discount_amount:.6f})" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Applied {discount_percent*100}% discount to {custom_llm_provider}: " + f"${original_cost:.6f} -> ${final_cost:.6f} (saved ${discount_amount:.6f})" + ) return final_cost, discount_percent, discount_amount @@ -807,17 +809,20 @@ def _apply_cost_margin( margin_config = None if custom_llm_provider and custom_llm_provider in litellm.cost_margin_config: margin_config = litellm.cost_margin_config[custom_llm_provider] - verbose_logger.debug( - f"Found provider-specific margin config for {custom_llm_provider}: {margin_config}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Found provider-specific margin config for {custom_llm_provider}: {margin_config}" + ) elif "global" in litellm.cost_margin_config: margin_config = litellm.cost_margin_config["global"] - verbose_logger.debug(f"Using global margin config: {margin_config}") + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug(f"Using global margin config: {margin_config}") else: - verbose_logger.debug( - f"No margin config found. Provider: {custom_llm_provider}, " - f"Available configs: {list(litellm.cost_margin_config.keys())}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"No margin config found. Provider: {custom_llm_provider}, " + f"Available configs: {list(litellm.cost_margin_config.keys())}" + ) if margin_config is not None: # Handle different margin config formats @@ -836,11 +841,12 @@ def _apply_cost_margin( final_cost = original_cost + margin_total_amount - verbose_logger.debug( - f"Applied margin to {custom_llm_provider or 'global'}: " - f"${original_cost:.6f} -> ${final_cost:.6f} " - f"(margin: {margin_percent*100 if margin_percent > 0 else 0}% + ${margin_fixed_amount:.6f} = ${margin_total_amount:.6f})" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Applied margin to {custom_llm_provider or 'global'}: " + f"${original_cost:.6f} -> ${final_cost:.6f} " + f"(margin: {margin_percent*100 if margin_percent > 0 else 0}% + ${margin_fixed_amount:.6f} = ${margin_total_amount:.6f})" + ) return final_cost, margin_percent, margin_fixed_amount, margin_total_amount @@ -1021,9 +1027,10 @@ def completion_cost( # noqa: PLR0915 for idx, model in enumerate(potential_model_names): try: - verbose_logger.debug( - f"selected model name for cost calculation: {model}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"selected model name for cost calculation: {model}" + ) if completion_response is not None and ( isinstance(completion_response, BaseModel) @@ -1411,37 +1418,47 @@ def completion_cost( # noqa: PLR0915 # Apply discount from module-level config if configured original_cost = _final_cost - _final_cost, discount_percent, discount_amount = _apply_cost_discount( - base_cost=_final_cost, - custom_llm_provider=custom_llm_provider, - ) + if litellm.cost_discount_config: + _final_cost, discount_percent, discount_amount = _apply_cost_discount( + base_cost=_final_cost, + custom_llm_provider=custom_llm_provider, + ) + else: + discount_percent = 0.0 + discount_amount = 0.0 # Apply margin from module-level config if configured - ( - _final_cost, - margin_percent, - margin_fixed_amount, - margin_total_amount, - ) = _apply_cost_margin( - base_cost=_final_cost, - custom_llm_provider=custom_llm_provider, - ) + if litellm.cost_margin_config: + ( + _final_cost, + margin_percent, + margin_fixed_amount, + margin_total_amount, + ) = _apply_cost_margin( + base_cost=_final_cost, + custom_llm_provider=custom_llm_provider, + ) + else: + margin_percent = 0.0 + margin_fixed_amount = 0.0 + margin_total_amount = 0.0 # Store cost breakdown in logging object if available - _store_cost_breakdown_in_logging_obj( - litellm_logging_obj=litellm_logging_obj, - prompt_tokens_cost_usd_dollar=prompt_tokens_cost_usd_dollar, - completion_tokens_cost_usd_dollar=completion_tokens_cost_usd_dollar, - cost_for_built_in_tools_cost_usd_dollar=cost_for_built_in_tools, - total_cost_usd_dollar=_final_cost, - additional_costs=additional_costs, - original_cost=original_cost, - discount_percent=discount_percent, - discount_amount=discount_amount, - margin_percent=margin_percent, - margin_fixed_amount=margin_fixed_amount, - margin_total_amount=margin_total_amount, - ) + if litellm_logging_obj is not None: + _store_cost_breakdown_in_logging_obj( + litellm_logging_obj=litellm_logging_obj, + prompt_tokens_cost_usd_dollar=prompt_tokens_cost_usd_dollar, + completion_tokens_cost_usd_dollar=completion_tokens_cost_usd_dollar, + cost_for_built_in_tools_cost_usd_dollar=cost_for_built_in_tools, + total_cost_usd_dollar=_final_cost, + original_cost=original_cost, + additional_costs=additional_costs, + discount_percent=discount_percent, + discount_amount=discount_amount, + margin_percent=margin_percent, + margin_fixed_amount=margin_fixed_amount, + margin_total_amount=margin_total_amount, + ) return _final_cost except Exception as e: @@ -2116,3 +2133,5 @@ def handle_realtime_stream_cost_calculation( total_cost = input_cost_per_token + output_cost_per_token return total_cost + + diff --git a/litellm/experimental_mcp_client/client.py b/litellm/experimental_mcp_client/client.py index 3e8f9bc337b..5e21ff9754f 100644 --- a/litellm/experimental_mcp_client/client.py +++ b/litellm/experimental_mcp_client/client.py @@ -209,6 +209,8 @@ class MCPClient: headers["X-API-Key"] = self._mcp_auth_value elif self.auth_type == MCPAuth.authorization: headers["Authorization"] = self._mcp_auth_value + elif self.auth_type == MCPAuth.oauth2: + headers["Authorization"] = f"Bearer {self._mcp_auth_value}" elif isinstance(self._mcp_auth_value, dict): headers.update(self._mcp_auth_value) diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index 1652ec2aa0c..bbd55a59bce 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -268,6 +268,7 @@ class CustomGuardrail(CustomLogger): """ Returns the guardrail(s) to be run from the metadata or root """ + if "guardrails" in data: return data["guardrails"] metadata = data.get("litellm_metadata") or data.get("metadata", {}) diff --git a/litellm/integrations/email_templates/templates.py b/litellm/integrations/email_templates/templates.py index 5de23db0f24..091351df2bb 100644 --- a/litellm/integrations/email_templates/templates.py +++ b/litellm/integrations/email_templates/templates.py @@ -85,6 +85,30 @@ SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ The LiteLLM team
""" +TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ +
+
+
+ + If you have any questions, please send an email to {email_support_contact}
+ + Best,
+ The LiteLLM team
+""" + MAX_BUDGET_ALERT_EMAIL_TEMPLATE = """
diff --git a/litellm/integrations/langfuse/langfuse_otel.py b/litellm/integrations/langfuse/langfuse_otel.py
index 08493a0e8ec..8955d3619f7 100644
--- a/litellm/integrations/langfuse/langfuse_otel.py
+++ b/litellm/integrations/langfuse/langfuse_otel.py
@@ -8,9 +8,8 @@ from litellm.integrations.arize import _utils
from litellm.integrations.langfuse.langfuse_otel_attributes import (
LangfuseLLMObsOTELAttributes,
)
-from litellm.integrations.opentelemetry import OpenTelemetry
+from litellm.integrations.opentelemetry import OpenTelemetry, OpenTelemetryConfig
from litellm.types.integrations.langfuse_otel import (
- LangfuseOtelConfig,
LangfuseSpanAttributes,
)
from litellm.types.utils import StandardCallbackDynamicParams
@@ -18,17 +17,8 @@ from litellm.types.utils import StandardCallbackDynamicParams
if TYPE_CHECKING:
from opentelemetry.trace import Span as _Span
- from litellm.integrations.opentelemetry import (
- OpenTelemetryConfig as _OpenTelemetryConfig,
- )
- from litellm.types.integrations.arize import Protocol as _Protocol
-
- Protocol = _Protocol
- OpenTelemetryConfig = _OpenTelemetryConfig
Span = Union[_Span, Any]
else:
- Protocol = Any
- OpenTelemetryConfig = Any
Span = Any
@@ -37,8 +27,12 @@ LANGFUSE_CLOUD_US_ENDPOINT = "https://us.cloud.langfuse.com/api/public/otel"
class LangfuseOtelLogger(OpenTelemetry):
- def __init__(self, *args, **kwargs):
- super().__init__(*args, **kwargs)
+ def __init__(self, config=None, *args, **kwargs):
+ # Prevent LangfuseOtelLogger from modifying global environment variables by constructing config manually
+ # and passing it to the parent OpenTelemetry class
+ if config is None:
+ config = self._create_open_telemetry_config_from_langfuse_env()
+ super().__init__(config=config, *args, **kwargs)
@staticmethod
def set_langfuse_otel_attributes(span: Span, kwargs, response_obj):
@@ -114,6 +108,10 @@ class LangfuseOtelLogger(OpenTelemetry):
for key, enum_attr in mapping.items():
if key in metadata and metadata[key] is not None:
value = metadata[key]
+ if key == "trace_id" and isinstance(value, str):
+ # trace_id must be 32 hex char no dashes for langfuse : Litellm sends uuid with dashes (might be breaking at some point)
+ value = value.replace("-", "")
+
if isinstance(value, (list, dict)):
try:
value = json.dumps(value)
@@ -265,8 +263,47 @@ class LangfuseOtelLogger(OpenTelemetry):
"""
return os.environ.get("LANGFUSE_OTEL_HOST") or os.environ.get("LANGFUSE_HOST")
+ def _create_open_telemetry_config_from_langfuse_env(self) -> OpenTelemetryConfig:
+ """
+ Creates OpenTelemetryConfig from Langfuse environment variables.
+ Does NOT modify global environment variables.
+ """
+ from litellm.integrations.opentelemetry import OpenTelemetryConfig
+
+ public_key = os.environ.get("LANGFUSE_PUBLIC_KEY", None)
+ secret_key = os.environ.get("LANGFUSE_SECRET_KEY", None)
+
+ if not public_key or not secret_key:
+ # If no keys, return default from env (likely logging to console or something else)
+ return OpenTelemetryConfig.from_env()
+
+ # Determine endpoint - default to US cloud
+ langfuse_host = LangfuseOtelLogger._get_langfuse_otel_host()
+
+ if langfuse_host:
+ # If LANGFUSE_HOST is provided, construct OTEL endpoint from it
+ if not langfuse_host.startswith("http"):
+ langfuse_host = "https://" + langfuse_host
+ endpoint = f"{langfuse_host.rstrip('/')}/api/public/otel"
+ verbose_logger.debug(f"Using Langfuse OTEL endpoint from host: {endpoint}")
+ else:
+ # Default to US cloud endpoint
+ endpoint = LANGFUSE_CLOUD_US_ENDPOINT
+ verbose_logger.debug(f"Using Langfuse US cloud endpoint: {endpoint}")
+
+ auth_header = LangfuseOtelLogger._get_langfuse_authorization_header(
+ public_key=public_key, secret_key=secret_key
+ )
+ otlp_auth_headers = f"Authorization={auth_header}"
+
+ return OpenTelemetryConfig(
+ exporter="otlp_http",
+ endpoint=endpoint,
+ headers=otlp_auth_headers,
+ )
+
@staticmethod
- def get_langfuse_otel_config() -> LangfuseOtelConfig:
+ def get_langfuse_otel_config() -> "OpenTelemetryConfig":
"""
Retrieves the Langfuse OpenTelemetry configuration based on environment variables.
@@ -276,7 +313,7 @@ class LangfuseOtelLogger(OpenTelemetry):
LANGFUSE_HOST: Optional. Custom Langfuse host URL. Defaults to US cloud.
Returns:
- LangfuseOtelConfig: A Pydantic model containing Langfuse OTEL configuration.
+ OpenTelemetryConfig: A Pydantic model containing Langfuse OTEL configuration.
Raises:
ValueError: If required keys are missing.
@@ -308,12 +345,14 @@ class LangfuseOtelLogger(OpenTelemetry):
)
otlp_auth_headers = f"Authorization={auth_header}"
- # Set standard OTEL environment variables
- os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = endpoint
- os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = otlp_auth_headers
+ # Prevent modification of global env vars which causes leakage
+ # os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = endpoint
+ # os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = otlp_auth_headers
- return LangfuseOtelConfig(
- otlp_auth_headers=otlp_auth_headers, protocol="otlp_http"
+ return OpenTelemetryConfig(
+ exporter="otlp_http",
+ endpoint=endpoint,
+ headers=otlp_auth_headers,
)
@staticmethod
diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py
index 18898be7dce..296a88f9a0b 100644
--- a/litellm/integrations/opentelemetry.py
+++ b/litellm/integrations/opentelemetry.py
@@ -599,9 +599,9 @@ class OpenTelemetry(CustomLogger):
def _get_dynamic_otel_headers_from_kwargs(self, kwargs) -> Optional[dict]:
"""Extract dynamic headers from kwargs if available."""
- standard_callback_dynamic_params: Optional[StandardCallbackDynamicParams] = (
- kwargs.get("standard_callback_dynamic_params")
- )
+ standard_callback_dynamic_params: Optional[
+ StandardCallbackDynamicParams
+ ] = kwargs.get("standard_callback_dynamic_params")
if not standard_callback_dynamic_params:
return None
@@ -619,7 +619,9 @@ class OpenTelemetry(CustomLogger):
# Prevents thread exhaustion by reusing providers for the same credential sets (e.g. per-team keys)
cache_key = str(sorted(dynamic_headers.items()))
if cache_key in self._tracer_provider_cache:
- return self._tracer_provider_cache[cache_key].get_tracer(LITELLM_TRACER_NAME)
+ return self._tracer_provider_cache[cache_key].get_tracer(
+ LITELLM_TRACER_NAME
+ )
# Create a temporary tracer provider with dynamic headers
temp_provider = TracerProvider(resource=self._get_litellm_resource(self.config))
@@ -674,7 +676,10 @@ class OpenTelemetry(CustomLogger):
kwargs, response_obj, start_time, end_time, span
)
# Ensure proxy-request parent span is annotated with the actual operation kind
- if parent_span is not None and parent_span.name == LITELLM_PROXY_REQUEST_SPAN_NAME:
+ if (
+ parent_span is not None
+ and parent_span.name == LITELLM_PROXY_REQUEST_SPAN_NAME
+ ):
self.set_attributes(parent_span, kwargs, response_obj)
else:
# Do not create primary span (keep hierarchy shallow when parent exists)
@@ -1003,14 +1008,11 @@ class OpenTelemetry(CustomLogger):
# TODO: Refactor to use the proper OTEL Logs API instead of directly creating SDK LogRecords
from opentelemetry._logs import SeverityNumber, get_logger, get_logger_provider
+
try:
- from opentelemetry.sdk._logs import (
- LogRecord as SdkLogRecord, # type: ignore[attr-defined] # OTEL < 1.39.0
- )
+ from opentelemetry.sdk._logs import LogRecord as SdkLogRecord # type: ignore[attr-defined] # OTEL < 1.39.0
except ImportError:
- from opentelemetry.sdk._logs._internal import (
- LogRecord as SdkLogRecord, # OTEL >= 1.39.0
- )
+ from opentelemetry.sdk._logs._internal import LogRecord as SdkLogRecord # type: ignore[attr-defined, no-redef] # OTEL >= 1.39.0
otel_logger = get_logger(LITELLM_LOGGER_NAME)
@@ -1618,7 +1620,6 @@ class OpenTelemetry(CustomLogger):
for idx, choice in enumerate(response_obj.get("choices")):
if choice.get("finish_reason"):
-
message = choice.get("message")
tool_calls = message.get("tool_calls")
if tool_calls:
@@ -1631,7 +1632,9 @@ class OpenTelemetry(CustomLogger):
)
except Exception as e:
- self.handle_callback_failure(callback_name=self.callback_name or "opentelemetry")
+ self.handle_callback_failure(
+ callback_name=self.callback_name or "opentelemetry"
+ )
verbose_logger.exception(
"OpenTelemetry logging error in set_attributes %s", str(e)
)
@@ -1722,6 +1725,7 @@ class OpenTelemetry(CustomLogger):
def set_raw_request_attributes(self, span: Span, kwargs, response_obj):
try:
+ self.set_attributes(span, kwargs, response_obj)
kwargs.get("optional_params", {})
litellm_params = kwargs.get("litellm_params", {}) or {}
custom_llm_provider = litellm_params.get("custom_llm_provider", "Unknown")
diff --git a/litellm/integrations/posthog.py b/litellm/integrations/posthog.py
index dd7c3627b87..c4b6e843d60 100644
--- a/litellm/integrations/posthog.py
+++ b/litellm/integrations/posthog.py
@@ -17,6 +17,7 @@ from typing import Any, Dict, Optional, Tuple
from litellm._logging import verbose_logger
from litellm._uuid import uuid
from litellm.integrations.custom_batch_logger import CustomBatchLogger
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
from litellm.integrations.posthog_mock_client import (
should_use_posthog_mock,
create_mock_posthog_client,
@@ -100,7 +101,7 @@ class PostHogLogger(CustomBatchLogger):
response = self.sync_client.post(
url=capture_url,
- json=payload,
+ content=safe_dumps(payload),
headers=headers,
)
response.raise_for_status()
@@ -356,7 +357,7 @@ class PostHogLogger(CustomBatchLogger):
response = await self.async_client.post(
url=capture_url,
- json=payload,
+ content=safe_dumps(payload),
headers=headers,
)
response.raise_for_status()
@@ -438,7 +439,7 @@ class PostHogLogger(CustomBatchLogger):
response = self.sync_client.post(
url=capture_url,
- json=payload,
+ content=safe_dumps(payload),
headers=headers,
)
response.raise_for_status()
diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 00c38eac188..0a61dab0680 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -1,6 +1,7 @@
# used for /metrics endpoint on LiteLLM Proxy
#### What this does ####
# On success, log events to Prometheus
+import asyncio
import os
import sys
from datetime import datetime, timedelta
@@ -1188,28 +1189,34 @@ class PrometheusLogger(CustomLogger):
_user_spend = _metadata.get("user_api_key_user_spend", None)
_user_max_budget = _metadata.get("user_api_key_user_max_budget", None)
- await self._set_api_key_budget_metrics_after_api_request(
- user_api_key=user_api_key,
- user_api_key_alias=user_api_key_alias,
- response_cost=response_cost,
- key_max_budget=_api_key_max_budget,
- key_spend=_api_key_spend,
- )
-
- await self._set_team_budget_metrics_after_api_request(
- user_api_team=user_api_team,
- user_api_team_alias=user_api_team_alias,
- team_spend=_team_spend,
- team_max_budget=_team_max_budget,
- response_cost=response_cost,
- )
-
- await self._set_user_budget_metrics_after_api_request(
- user_id=user_id,
- user_spend=_user_spend,
- user_max_budget=_user_max_budget,
- response_cost=response_cost,
+ results = await asyncio.gather(
+ self._set_api_key_budget_metrics_after_api_request(
+ user_api_key=user_api_key,
+ user_api_key_alias=user_api_key_alias,
+ response_cost=response_cost,
+ key_max_budget=_api_key_max_budget,
+ key_spend=_api_key_spend,
+ ),
+ self._set_team_budget_metrics_after_api_request(
+ user_api_team=user_api_team,
+ user_api_team_alias=user_api_team_alias,
+ team_spend=_team_spend,
+ team_max_budget=_team_max_budget,
+ response_cost=response_cost,
+ ),
+ self._set_user_budget_metrics_after_api_request(
+ user_id=user_id,
+ user_spend=_user_spend,
+ user_max_budget=_user_max_budget,
+ response_cost=response_cost,
+ ),
+ return_exceptions=True,
)
+ for i, r in enumerate(results):
+ if isinstance(r, Exception):
+ verbose_logger.debug(
+ f"[Non-Blocking] Prometheus: Budget metric lookup {['key', 'team', 'user'][i]} failed: {r}"
+ )
def _increment_top_level_request_and_spend_metrics(
self,
@@ -2898,12 +2905,14 @@ class PrometheusLogger(CustomLogger):
max_budget=max_budget,
)
try:
+ # Note: Setting check_db_only=True bypasses cache and hits DB on every request,
+ # causing huge latency increase and CPU spikes. Keep check_db_only=False.
user_info = await get_user_object(
user_id=user_id,
prisma_client=prisma_client,
user_api_key_cache=user_api_key_cache,
user_id_upsert=False,
- check_db_only=True,
+ check_db_only=False,
)
except Exception as e:
verbose_logger.debug(
diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py
index 00695cbfb5b..7c8e2ebeaff 100644
--- a/litellm/litellm_core_utils/core_helpers.py
+++ b/litellm/litellm_core_utils/core_helpers.py
@@ -94,8 +94,8 @@ def map_finish_reason(
return "length"
elif finish_reason == "tool_use": # anthropic
return "tool_calls"
- elif finish_reason == "content_filtered":
- return "content_filter"
+ elif finish_reason == "compaction":
+ return "length"
return finish_reason
diff --git a/litellm/litellm_core_utils/get_litellm_params.py b/litellm/litellm_core_utils/get_litellm_params.py
index 060e98fd49f..36a8dfdb5a6 100644
--- a/litellm/litellm_core_utils/get_litellm_params.py
+++ b/litellm/litellm_core_utils/get_litellm_params.py
@@ -1,19 +1,48 @@
from typing import Optional
+# Pre-define optional kwargs keys as frozenset for O(1) lookups
+# These are extracted from kwargs only if present, avoiding unnecessary .get() calls
+_OPTIONAL_KWARGS_KEYS = frozenset({
+ "azure_ad_token",
+ "tenant_id",
+ "client_id",
+ "client_secret",
+ "azure_username",
+ "azure_password",
+ "azure_scope",
+ "timeout",
+ "bucket_name",
+ "vertex_credentials",
+ "vertex_project",
+ "vertex_location",
+ "vertex_ai_project",
+ "vertex_ai_location",
+ "vertex_ai_credentials",
+ "aws_region_name",
+ "aws_access_key_id",
+ "aws_secret_access_key",
+ "aws_session_token",
+ "aws_session_name",
+ "aws_profile_name",
+ "aws_role_name",
+ "aws_web_identity_token",
+ "aws_sts_endpoint",
+ "aws_external_id",
+ "aws_bedrock_runtime_endpoint",
+ "tpm",
+ "rpm",
+})
+
+
def _get_base_model_from_litellm_call_metadata(
metadata: Optional[dict],
) -> Optional[str]:
if metadata is None:
return None
-
- if metadata is not None:
- model_info = metadata.get("model_info", {})
-
- if model_info is not None:
- base_model = model_info.get("base_model", None)
- if base_model is not None:
- return base_model
+ model_info = metadata.get("model_info")
+ if model_info:
+ return model_info.get("base_model")
return None
@@ -66,6 +95,7 @@ def get_litellm_params(
litellm_request_debug: Optional[bool] = None,
**kwargs,
) -> dict:
+ # Build base dict with explicit parameters (always included)
litellm_params = {
"acompletion": acompletion,
"api_key": api_key,
@@ -112,37 +142,15 @@ def get_litellm_params(
"ssl_verify": ssl_verify,
"merge_reasoning_content_in_choices": merge_reasoning_content_in_choices,
"api_version": api_version,
- "azure_ad_token": kwargs.get("azure_ad_token"),
- "tenant_id": kwargs.get("tenant_id"),
- "client_id": kwargs.get("client_id"),
- "client_secret": kwargs.get("client_secret"),
- "azure_username": kwargs.get("azure_username"),
- "azure_password": kwargs.get("azure_password"),
- "azure_scope": kwargs.get("azure_scope"),
"max_retries": max_retries,
- "timeout": kwargs.get("timeout"),
- "bucket_name": kwargs.get("bucket_name"),
- "vertex_credentials": kwargs.get("vertex_credentials"),
- "vertex_project": kwargs.get("vertex_project"),
- "vertex_location": kwargs.get("vertex_location"),
- "vertex_ai_project": kwargs.get("vertex_ai_project"),
- "vertex_ai_location": kwargs.get("vertex_ai_location"),
- "vertex_ai_credentials": kwargs.get("vertex_ai_credentials"),
"use_litellm_proxy": use_litellm_proxy,
"litellm_request_debug": litellm_request_debug,
- "aws_region_name": kwargs.get("aws_region_name"),
- # AWS credentials for Bedrock/Sagemaker
- "aws_access_key_id": kwargs.get("aws_access_key_id"),
- "aws_secret_access_key": kwargs.get("aws_secret_access_key"),
- "aws_session_token": kwargs.get("aws_session_token"),
- "aws_session_name": kwargs.get("aws_session_name"),
- "aws_profile_name": kwargs.get("aws_profile_name"),
- "aws_role_name": kwargs.get("aws_role_name"),
- "aws_web_identity_token": kwargs.get("aws_web_identity_token"),
- "aws_sts_endpoint": kwargs.get("aws_sts_endpoint"),
- "aws_external_id": kwargs.get("aws_external_id"),
- "aws_bedrock_runtime_endpoint": kwargs.get("aws_bedrock_runtime_endpoint"),
- "tpm": kwargs.get("tpm"),
- "rpm": kwargs.get("rpm"),
}
+
+ # Sparse extraction: only add kwargs keys that are actually present
+ if kwargs:
+ for key in _OPTIONAL_KWARGS_KEYS:
+ if key in kwargs:
+ litellm_params[key] = kwargs[key]
+
return litellm_params
diff --git a/litellm/litellm_core_utils/initialize_dynamic_callback_params.py b/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
index c425319b4d4..ff521d47804 100644
--- a/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
+++ b/litellm/litellm_core_utils/initialize_dynamic_callback_params.py
@@ -1,8 +1,35 @@
from typing import Dict, Optional
-
from litellm.secret_managers.main import get_secret_str
from litellm.types.utils import StandardCallbackDynamicParams
+# Hardcoded list of supported callback params to avoid runtime inspection issues with TypedDict
+_supported_callback_params = [
+ "langfuse_public_key",
+ "langfuse_secret",
+ "langfuse_secret_key",
+ "langfuse_host",
+ "langfuse_prompt_version",
+ "gcs_bucket_name",
+ "gcs_path_service_account",
+ "langsmith_api_key",
+ "langsmith_project",
+ "langsmith_base_url",
+ "langsmith_sampling_rate",
+ "langsmith_tenant_id",
+ "humanloop_api_key",
+ "arize_api_key",
+ "arize_space_key",
+ "arize_space_id",
+ "posthog_api_key",
+ "posthog_host",
+ "braintrust_api_key",
+ "braintrust_project",
+ "braintrust_host",
+ "slack_webhook_url",
+ "lunary_public_key",
+ "turn_off_message_logging",
+]
+
def initialize_standard_callback_dynamic_params(
kwargs: Optional[Dict] = None,
@@ -15,13 +42,10 @@ def initialize_standard_callback_dynamic_params(
standard_callback_dynamic_params = StandardCallbackDynamicParams()
if kwargs:
- _supported_callback_params = (
- StandardCallbackDynamicParams.__annotations__.keys()
- )
-
+ # 1. Check top-level kwargs
for param in _supported_callback_params:
if param in kwargs:
- _param_value = kwargs.pop(param)
+ _param_value = kwargs.get(param)
if (
_param_value is not None
and isinstance(_param_value, str)
@@ -30,4 +54,22 @@ def initialize_standard_callback_dynamic_params(
_param_value = get_secret_str(secret_name=_param_value)
standard_callback_dynamic_params[param] = _param_value # type: ignore
+ # 2. Fallback: check "metadata" or "litellm_params" -> "metadata"
+ metadata = (kwargs.get("metadata") or {}).copy()
+ litellm_params = kwargs.get("litellm_params") or {}
+ if isinstance(litellm_params, dict):
+ metadata.update(litellm_params.get("metadata") or {})
+
+ if isinstance(metadata, dict):
+ for param in _supported_callback_params:
+ if param not in standard_callback_dynamic_params and param in metadata:
+ _param_value = metadata.get(param)
+ if (
+ _param_value is not None
+ and isinstance(_param_value, str)
+ and "os.environ/" in _param_value
+ ):
+ _param_value = get_secret_str(secret_name=_param_value)
+ standard_callback_dynamic_params[param] = _param_value # type: ignore
+
return standard_callback_dynamic_params
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 1b3a687f1f3..7ae62718af0 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -203,6 +203,10 @@ except Exception as e:
EnterpriseStandardLoggingPayloadSetupVAR = None
_in_memory_loggers: List[Any] = []
+_STANDARD_LOGGING_METADATA_KEYS: frozenset = frozenset(
+ StandardLoggingMetadata.__annotations__.keys()
+)
+
### GLOBAL VARIABLES ###
# Cache custom pricing keys as frozenset for O(1) lookups instead of looping through 49 keys
@@ -522,7 +526,8 @@ class Logging(LiteLLMLoggingBaseClass):
}
self.litellm_request_debug = litellm_params.get("litellm_request_debug", False)
self.logger_fn = litellm_params.get("logger_fn", None)
- verbose_logger.debug(f"self.optional_params: {self.optional_params}")
+ if _is_debugging_on() or self.litellm_request_debug:
+ verbose_logger.debug(f"self.optional_params: {self.optional_params}")
self.model_call_details.update(
{
@@ -3917,18 +3922,6 @@ def _init_custom_logger_compatible_class( # noqa: PLR0915
return langfuse_logger # type: ignore
elif logging_integration == "langfuse_otel":
from litellm.integrations.langfuse.langfuse_otel import LangfuseOtelLogger
- from litellm.integrations.opentelemetry import (
- OpenTelemetry,
- OpenTelemetryConfig,
- )
-
- langfuse_otel_config = LangfuseOtelLogger.get_langfuse_otel_config()
-
- # The endpoint and headers are now set as environment variables by get_langfuse_otel_config()
- otel_config = OpenTelemetryConfig(
- exporter=langfuse_otel_config.protocol,
- headers=langfuse_otel_config.otlp_auth_headers,
- )
for callback in _in_memory_loggers:
if (
@@ -3936,8 +3929,10 @@ def _init_custom_logger_compatible_class( # noqa: PLR0915
and callback.callback_name == "langfuse_otel"
):
return callback # type: ignore
+ # Allow LangfuseOtelLogger to initialize its own config safely
+ # This prevents startup crashes if LANGFUSE keys are not in env (e.g. for dynamic usage)
_otel_logger = LangfuseOtelLogger(
- config=otel_config, callback_name="langfuse_otel"
+ config=None, callback_name="langfuse_otel"
)
_in_memory_loggers.append(_otel_logger)
return _otel_logger # type: ignore
@@ -4525,17 +4520,12 @@ class StandardLoggingPayloadSetup:
user_api_key_auth_metadata=None,
)
if isinstance(metadata, dict):
- # Filter the metadata dictionary to include only the specified keys
- supported_keys = StandardLoggingMetadata.__annotations__.keys()
- for key in supported_keys:
- if key in metadata:
- clean_metadata[key] = metadata[key] # type: ignore
+ for key in metadata.keys() & _STANDARD_LOGGING_METADATA_KEYS:
+ clean_metadata[key] = metadata[key] # type: ignore
- if metadata.get("user_api_key") is not None:
- if is_valid_sha256_hash(str(metadata.get("user_api_key"))):
- clean_metadata["user_api_key_hash"] = metadata.get(
- "user_api_key"
- ) # this is the hash
+ user_api_key = metadata.get("user_api_key")
+ if user_api_key and isinstance(user_api_key, str) and is_valid_sha256_hash(user_api_key):
+ clean_metadata["user_api_key_hash"] = user_api_key
_potential_requester_metadata = metadata.get(
"metadata", None
) # check if user passed metadata in the sdk request - e.g. metadata for langsmith logging - https://docs.litellm.ai/docs/observability/langsmith_integration#set-langsmith-fields
diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index 53d2ca2f23f..f9ecd78ff1c 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -2190,6 +2190,16 @@ def anthropic_messages_pt( # noqa: PLR0915
while msg_i < len(messages) and messages[msg_i]["role"] == "assistant":
assistant_content_block: ChatCompletionAssistantMessage = messages[msg_i] # type: ignore
+ # Extract compaction_blocks from provider_specific_fields and add them first
+ _provider_specific_fields_raw = assistant_content_block.get(
+ "provider_specific_fields"
+ )
+ if isinstance(_provider_specific_fields_raw, dict):
+ _compaction_blocks = _provider_specific_fields_raw.get("compaction_blocks")
+ if _compaction_blocks and isinstance(_compaction_blocks, list):
+ # Add compaction blocks at the beginning of assistant content : https://platform.claude.com/docs/en/build-with-claude/compaction
+ assistant_content.extend(_compaction_blocks) # type: ignore
+
thinking_blocks = assistant_content_block.get("thinking_blocks", None)
if (
thinking_blocks is not None
diff --git a/litellm/litellm_core_utils/redact_messages.py b/litellm/litellm_core_utils/redact_messages.py
index 0effed3db70..aa763dc9899 100644
--- a/litellm/litellm_core_utils/redact_messages.py
+++ b/litellm/litellm_core_utils/redact_messages.py
@@ -130,6 +130,11 @@ def perform_redaction(model_call_details: dict, result):
def should_redact_message_logging(model_call_details: dict) -> bool:
"""
Determine if message logging should be redacted.
+
+ Priority order:
+ 1. Dynamic parameter (turn_off_message_logging in request)
+ 2. Headers (litellm-disable-message-redaction / litellm-enable-message-redaction)
+ 3. Global setting (litellm.turn_off_message_logging)
"""
litellm_params = model_call_details.get("litellm_params", {})
@@ -139,36 +144,36 @@ def should_redact_message_logging(model_call_details: dict) -> bool:
# Get headers from the metadata
request_headers = metadata.get("headers", {}) if isinstance(metadata, dict) else {}
- possible_request_headers = [
+ # Check for headers that explicitly control redaction
+ if request_headers and bool(
+ request_headers.get("litellm-disable-message-redaction", False)
+ ):
+ # User explicitly disabled redaction via header
+ return False
+
+ possible_enable_headers = [
"litellm-enable-message-redaction", # old header. maintain backwards compatibility
"x-litellm-enable-message-redaction", # new header
]
is_redaction_enabled_via_header = False
- for header in possible_request_headers:
+ for header in possible_enable_headers:
if bool(request_headers.get(header, False)):
is_redaction_enabled_via_header = True
break
- # check if user opted out of logging message/response to callbacks
- if (
- litellm.turn_off_message_logging is not True
- and is_redaction_enabled_via_header is not True
- and _get_turn_off_message_logging_from_dynamic_params(model_call_details)
- is not True
- ):
- return False
-
- if request_headers and bool(
- request_headers.get("litellm-disable-message-redaction", False)
- ):
- return False
-
- # user has OPTED OUT of message redaction
- if _get_turn_off_message_logging_from_dynamic_params(model_call_details) is False:
- return False
-
- return True
+ # Priority 1: Check dynamic parameter first (if explicitly set)
+ dynamic_turn_off = _get_turn_off_message_logging_from_dynamic_params(model_call_details)
+ if dynamic_turn_off is not None:
+ # Dynamic parameter is explicitly set, use it
+ return dynamic_turn_off
+
+ # Priority 2: Check if header explicitly enables redaction
+ if is_redaction_enabled_via_header:
+ return True
+
+ # Priority 3: Fall back to global setting
+ return litellm.turn_off_message_logging is True
def redact_message_input_output_from_logging(
diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py
index a99bd1cd0f3..6b9e51034c0 100644
--- a/litellm/litellm_core_utils/token_counter.py
+++ b/litellm/litellm_core_utils/token_counter.py
@@ -706,7 +706,7 @@ def _count_content_list(
if isinstance(c, str):
num_tokens += count_function(c)
elif c["type"] == "text":
- num_tokens += count_function(c.get("text", ""))
+ num_tokens += count_function(str(c.get("text", "")))
elif c["type"] == "image_url":
image_url = c.get("image_url")
num_tokens += _count_image_tokens(
@@ -722,7 +722,7 @@ def _count_content_list(
elif c["type"] == "thinking":
# Claude extended thinking content block
# Count the thinking text and skip signature (opaque signature blob)
- thinking_text = c.get("thinking", "")
+ thinking_text = str(c.get("thinking", ""))
if thinking_text:
num_tokens += count_function(thinking_text)
else:
diff --git a/litellm/llms/a2a/chat/guardrail_translation/README.md b/litellm/llms/a2a/chat/guardrail_translation/README.md
new file mode 100644
index 00000000000..1e18f5cda3a
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/README.md
@@ -0,0 +1,155 @@
+# A2A Protocol Guardrail Translation Handler
+
+Handler for processing A2A (Agent-to-Agent) Protocol messages with guardrails.
+
+## Overview
+
+This handler processes A2A JSON-RPC 2.0 input/output by:
+1. Extracting text from message parts (`kind: "text"`)
+2. Applying guardrails to text content
+3. Mapping guardrailed text back to original structure
+
+## A2A Protocol Format
+
+### Input Format (JSON-RPC 2.0)
+
+```json
+{
+ "jsonrpc": "2.0",
+ "id": "request-id",
+ "method": "message/send",
+ "params": {
+ "message": {
+ "kind": "message",
+ "messageId": "...",
+ "role": "user",
+ "parts": [
+ {"kind": "text", "text": "Hello, my SSN is 123-45-6789"}
+ ]
+ },
+ "metadata": {
+ "guardrails": ["block-ssn"]
+ }
+ }
+}
+```
+
+### Output Formats
+
+The handler supports multiple A2A response formats:
+
+**Direct message:**
+```json
+{
+ "result": {
+ "kind": "message",
+ "parts": [{"kind": "text", "text": "Response text"}]
+ }
+}
+```
+
+**Nested message:**
+```json
+{
+ "result": {
+ "message": {
+ "parts": [{"kind": "text", "text": "Response text"}]
+ }
+ }
+}
+```
+
+**Task with artifacts:**
+```json
+{
+ "result": {
+ "kind": "task",
+ "artifacts": [
+ {"parts": [{"kind": "text", "text": "Artifact text"}]}
+ ]
+ }
+}
+```
+
+**Task with status message:**
+```json
+{
+ "result": {
+ "kind": "task",
+ "status": {
+ "message": {
+ "parts": [{"kind": "text", "text": "Status message"}]
+ }
+ }
+ }
+}
+```
+
+**Streaming artifact-update:**
+```json
+{
+ "result": {
+ "kind": "artifact-update",
+ "artifact": {
+ "parts": [{"kind": "text", "text": "Streaming text"}]
+ }
+ }
+}
+```
+
+## Usage
+
+The handler is automatically discovered and applied when guardrails are used with A2A endpoints.
+
+### Via LiteLLM Proxy
+
+```bash
+curl -X POST 'http://localhost:4000/a2a/my-agent' \
+-H 'Content-Type: application/json' \
+-H 'Authorization: Bearer your-api-key' \
+-d '{
+ "jsonrpc": "2.0",
+ "id": "1",
+ "method": "message/send",
+ "params": {
+ "message": {
+ "kind": "message",
+ "messageId": "msg-1",
+ "role": "user",
+ "parts": [{"kind": "text", "text": "Hello, my SSN is 123-45-6789"}]
+ },
+ "metadata": {
+ "guardrails": ["block-ssn"]
+ }
+ }
+}'
+```
+
+### Specifying Guardrails
+
+Guardrails can be specified in the A2A request via the `metadata.guardrails` field:
+
+```json
+{
+ "params": {
+ "message": {...},
+ "metadata": {
+ "guardrails": ["block-ssn", "pii-filter"]
+ }
+ }
+}
+```
+
+## Extension
+
+Override these methods to customize behavior:
+
+- `_extract_texts_from_result()`: Custom text extraction from A2A responses
+- `_extract_texts_from_parts()`: Custom text extraction from message parts
+- `_apply_text_to_path()`: Custom application of guardrailed text
+
+## Call Types
+
+This handler is registered for:
+- `CallTypes.send_message`: Synchronous A2A message sending
+- `CallTypes.asend_message`: Asynchronous A2A message sending
diff --git a/litellm/llms/a2a/chat/guardrail_translation/__init__.py b/litellm/llms/a2a/chat/guardrail_translation/__init__.py
new file mode 100644
index 00000000000..13c20677485
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/__init__.py
@@ -0,0 +1,11 @@
+"""A2A Protocol handler for Unified Guardrails."""
+
+from litellm.llms.a2a.chat.guardrail_translation.handler import A2AGuardrailHandler
+from litellm.types.utils import CallTypes
+
+guardrail_translation_mappings = {
+ CallTypes.send_message: A2AGuardrailHandler,
+ CallTypes.asend_message: A2AGuardrailHandler,
+}
+
+__all__ = ["guardrail_translation_mappings"]
diff --git a/litellm/llms/a2a/chat/guardrail_translation/handler.py b/litellm/llms/a2a/chat/guardrail_translation/handler.py
new file mode 100644
index 00000000000..770453f2def
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/handler.py
@@ -0,0 +1,315 @@
+"""
+A2A Protocol Handler for Unified Guardrails
+
+This module provides guardrail translation support for A2A (Agent-to-Agent) Protocol.
+It handles both JSON-RPC 2.0 input requests and output responses, extracting text
+from message parts and applying guardrails.
+
+A2A Protocol Format:
+- Input: JSON-RPC 2.0 with params.message.parts containing text parts
+- Output: JSON-RPC 2.0 with result containing message/artifact parts
+"""
+
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
+
+from litellm._logging import verbose_proxy_logger
+from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.types.utils import GenericGuardrailAPIInputs
+
+if TYPE_CHECKING:
+ from litellm.integrations.custom_guardrail import CustomGuardrail
+ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+ from litellm.proxy._types import UserAPIKeyAuth
+
+
+class A2AGuardrailHandler(BaseTranslation):
+ """
+ Handler for processing A2A Protocol messages with guardrails.
+
+ This class provides methods to:
+ 1. Process input messages (pre-call hook) - extracts text from A2A message parts
+ 2. Process output responses (post-call hook) - extracts text from A2A response parts
+
+ A2A Message Format:
+ - Input: params.message.parts[].text (where kind == "text")
+ - Output: result.message.parts[].text or result.artifacts[].parts[].text
+ """
+
+ async def process_input_messages(
+ self,
+ data: dict,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
+ ) -> Any:
+ """
+ Process A2A input messages by applying guardrails to text content.
+
+ Extracts text from A2A message parts and applies guardrails.
+
+ Args:
+ data: The A2A JSON-RPC 2.0 request data
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+
+ Returns:
+ Modified data with guardrails applied to text content
+ """
+ # A2A request format: { "params": { "message": { "parts": [...] } } }
+ params = data.get("params", {})
+ message = params.get("message", {})
+ parts = message.get("parts", [])
+
+ if not parts:
+ verbose_proxy_logger.debug("A2A: No parts in message, skipping guardrail")
+ return data
+
+ texts_to_check: List[str] = []
+ text_part_indices: List[int] = [] # Track which parts contain text
+
+ # Step 1: Extract text from all text parts
+ for part_idx, part in enumerate(parts):
+ if part.get("kind") == "text":
+ text = part.get("text", "")
+ if text:
+ texts_to_check.append(text)
+ text_part_indices.append(part_idx)
+
+ # Step 2: Apply guardrail to all texts in batch
+ if texts_to_check:
+ inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
+
+ # Pass the structured A2A message to guardrails
+ inputs["structured_messages"] = [message]
+
+ # Include agent model info if available
+ model = data.get("model")
+ if model:
+ inputs["model"] = model
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=data,
+ input_type="request",
+ logging_obj=litellm_logging_obj,
+ )
+
+ guardrailed_texts = guardrailed_inputs.get("texts", [])
+
+ # Step 3: Apply guardrailed text back to original parts
+ if guardrailed_texts and len(guardrailed_texts) == len(text_part_indices):
+ for task_idx, part_idx in enumerate(text_part_indices):
+ parts[part_idx]["text"] = guardrailed_texts[task_idx]
+
+ verbose_proxy_logger.debug("A2A: Processed input message: %s", message)
+
+ return data
+
+ async def process_output_response(
+ self,
+ response: Any,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
+ user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+ ) -> Any:
+ """
+ Process A2A output response by applying guardrails to text content.
+
+ Handles multiple A2A response formats:
+ - Direct message: {"result": {"kind": "message", "parts": [...]}}
+ - Nested message: {"result": {"message": {"parts": [...]}}}
+ - Task with artifacts: {"result": {"kind": "task", "artifacts": [{"parts": [...]}]}}
+ - Task with status message: {"result": {"kind": "task", "status": {"message": {"parts": [...]}}}}
+
+ Args:
+ response: A2A JSON-RPC 2.0 response dict or object
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+ user_api_key_dict: User API key metadata
+
+ Returns:
+ Modified response with guardrails applied to text content
+ """
+ # Handle both dict and Pydantic model responses
+ if hasattr(response, "model_dump"):
+ response_dict = response.model_dump()
+ is_pydantic = True
+ elif isinstance(response, dict):
+ response_dict = response
+ is_pydantic = False
+ else:
+ verbose_proxy_logger.warning(
+ "A2A: Unknown response type %s, skipping guardrail", type(response)
+ )
+ return response
+
+ result = response_dict.get("result", {})
+ if not result or not isinstance(result, dict):
+ verbose_proxy_logger.debug("A2A: No result in response, skipping guardrail")
+ return response
+
+ # Find all text-containing parts in the response
+ texts_to_check: List[str] = []
+ # Each mapping is (path_to_parts_list, part_index)
+ # path_to_parts_list is a tuple of keys to navigate to the parts list
+ task_mappings: List[Tuple[Tuple[str, ...], int]] = []
+
+ # Extract texts from all possible locations
+ self._extract_texts_from_result(
+ result=result,
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ if not texts_to_check:
+ verbose_proxy_logger.debug("A2A: No text content in response")
+ return response
+
+ # Step 2: Apply guardrail to all texts in batch
+ # Create a request_data dict with response info and user API key metadata
+ request_data: dict = {"response": response_dict}
+
+ # Add user API key metadata with prefixed keys
+ user_metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
+ if user_metadata:
+ request_data["litellm_metadata"] = user_metadata
+
+ inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=request_data,
+ input_type="response",
+ logging_obj=litellm_logging_obj,
+ )
+
+ guardrailed_texts = guardrailed_inputs.get("texts", [])
+
+ # Step 3: Apply guardrailed text back to original response
+ if guardrailed_texts and len(guardrailed_texts) == len(task_mappings):
+ for task_idx, (path, part_idx) in enumerate(task_mappings):
+ self._apply_text_to_path(
+ result=result,
+ path=path,
+ part_idx=part_idx,
+ text=guardrailed_texts[task_idx],
+ )
+
+ verbose_proxy_logger.debug("A2A: Processed output response")
+
+ # Update the original response
+ if is_pydantic:
+ # For Pydantic models, we need to update the underlying dict
+ # and the model will reflect the changes
+ response_dict["result"] = result
+ return response
+ else:
+ response["result"] = result
+ return response
+
+ def _extract_texts_from_result(
+ self,
+ result: Dict[str, Any],
+ texts_to_check: List[str],
+ task_mappings: List[Tuple[Tuple[str, ...], int]],
+ ) -> None:
+ """
+ Extract text from all possible locations in an A2A result.
+
+ Handles multiple response formats:
+ 1. Direct message with parts: {"parts": [...]}
+ 2. Nested message: {"message": {"parts": [...]}}
+ 3. Task with artifacts: {"artifacts": [{"parts": [...]}]}
+ 4. Task with status message: {"status": {"message": {"parts": [...]}}}
+ 5. Streaming artifact-update: {"artifact": {"parts": [...]}}
+ """
+ # Case 1: Direct parts in result (direct message)
+ if "parts" in result:
+ self._extract_texts_from_parts(
+ parts=result["parts"],
+ path=("parts",),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 2: Nested message
+ message = result.get("message")
+ if message and isinstance(message, dict) and "parts" in message:
+ self._extract_texts_from_parts(
+ parts=message["parts"],
+ path=("message", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 3: Streaming artifact-update (singular artifact)
+ artifact = result.get("artifact")
+ if artifact and isinstance(artifact, dict) and "parts" in artifact:
+ self._extract_texts_from_parts(
+ parts=artifact["parts"],
+ path=("artifact", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 4: Task with status message
+ status = result.get("status", {})
+ if isinstance(status, dict):
+ status_message = status.get("message")
+ if (
+ status_message
+ and isinstance(status_message, dict)
+ and "parts" in status_message
+ ):
+ self._extract_texts_from_parts(
+ parts=status_message["parts"],
+ path=("status", "message", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 5: Task with artifacts (plural, array)
+ artifacts = result.get("artifacts", [])
+ if artifacts and isinstance(artifacts, list):
+ for artifact_idx, art in enumerate(artifacts):
+ if isinstance(art, dict) and "parts" in art:
+ self._extract_texts_from_parts(
+ parts=art["parts"],
+ path=("artifacts", str(artifact_idx), "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ def _extract_texts_from_parts(
+ self,
+ parts: List[Dict[str, Any]],
+ path: Tuple[str, ...],
+ texts_to_check: List[str],
+ task_mappings: List[Tuple[Tuple[str, ...], int]],
+ ) -> None:
+ """Extract text from message parts."""
+ for part_idx, part in enumerate(parts):
+ if part.get("kind") == "text":
+ text = part.get("text", "")
+ if text:
+ texts_to_check.append(text)
+ task_mappings.append((path, part_idx))
+
+ def _apply_text_to_path(
+ self,
+ result: Dict[Union[str, int], Any],
+ path: Tuple[str, ...],
+ part_idx: int,
+ text: str,
+ ) -> None:
+ """Apply guardrailed text back to the specified path in the result."""
+ # Navigate to the parts list
+ current = result
+ for key in path:
+ if key.isdigit():
+ # Array index
+ current = current[int(key)]
+ else:
+ current = current[key]
+
+ # Update the text in the part
+ current[part_idx]["text"] = text
diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py
index 6a9aafd076b..485e95d6489 100644
--- a/litellm/llms/anthropic/chat/handler.py
+++ b/litellm/llms/anthropic/chat/handler.py
@@ -512,6 +512,9 @@ class ModelResponseIterator:
# Accumulate web_search_tool_result blocks for multi-turn reconstruction
# See: https://github.com/BerriAI/litellm/issues/17737
self.web_search_results: List[Dict[str, Any]] = []
+
+ # Accumulate compaction blocks for multi-turn reconstruction
+ self.compaction_blocks: List[Dict[str, Any]] = []
def check_empty_tool_call_args(self) -> bool:
"""
@@ -592,6 +595,12 @@ class ModelResponseIterator:
)
]
provider_specific_fields["thinking_blocks"] = thinking_blocks
+ elif "content" in content_block["delta"] and content_block["delta"].get("type") == "compaction_delta":
+ # Handle compaction delta
+ provider_specific_fields["compaction_delta"] = {
+ "type": "compaction_delta",
+ "content": content_block["delta"]["content"]
+ }
return text, tool_use, thinking_blocks, provider_specific_fields
@@ -721,6 +730,20 @@ class ModelResponseIterator:
provider_specific_fields=provider_specific_fields,
)
+ elif content_block_start["content_block"]["type"] == "compaction":
+ # Handle compaction blocks
+ # The full content comes in content_block_start
+ self.compaction_blocks.append(
+ content_block_start["content_block"]
+ )
+ provider_specific_fields["compaction_blocks"] = (
+ self.compaction_blocks
+ )
+ provider_specific_fields["compaction_start"] = {
+ "type": "compaction",
+ "content": content_block_start["content_block"].get("content", "")
+ }
+
elif content_block_start["content_block"]["type"].endswith("_tool_result"):
# Handle all tool result types (web_search, bash_code_execution, text_editor, etc.)
content_type = content_block_start["content_block"]["type"]
diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index 1b61b533275..02b8d952445 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -170,9 +170,10 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
tool_call["caller"] = cast(Dict[str, Any], anthropic_tool_content["caller"]) # type: ignore[typeddict-item]
return tool_call
- def _is_claude_opus_4_5(self, model: str) -> bool:
+ @staticmethod
+ def _is_claude_opus_4_6(model: str) -> bool:
"""Check if the model is Claude Opus 4.5."""
- return "opus-4-5" in model.lower() or "opus_4_5" in model.lower()
+ return "opus-4-6" in model.lower() or "opus_4_6" in model.lower()
def get_supported_openai_params(self, model: str):
params = [
@@ -659,32 +660,38 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
@staticmethod
def _map_reasoning_effort(
- reasoning_effort: Optional[Union[REASONING_EFFORT, str]],
+ reasoning_effort: Optional[Union[REASONING_EFFORT, str]],
+ model: str,
) -> Optional[AnthropicThinkingParam]:
- if reasoning_effort is None:
- return None
- elif reasoning_effort == "low":
+ if AnthropicConfig._is_claude_opus_4_6(model):
return AnthropicThinkingParam(
- type="enabled",
- budget_tokens=DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
- )
- elif reasoning_effort == "medium":
- return AnthropicThinkingParam(
- type="enabled",
- budget_tokens=DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
- )
- elif reasoning_effort == "high":
- return AnthropicThinkingParam(
- type="enabled",
- budget_tokens=DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
- )
- elif reasoning_effort == "minimal":
- return AnthropicThinkingParam(
- type="enabled",
- budget_tokens=DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
+ type="adaptive",
)
else:
- raise ValueError(f"Unmapped reasoning effort: {reasoning_effort}")
+ if reasoning_effort is None:
+ return None
+ elif reasoning_effort == "low":
+ return AnthropicThinkingParam(
+ type="enabled",
+ budget_tokens=DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET,
+ )
+ elif reasoning_effort == "medium":
+ return AnthropicThinkingParam(
+ type="enabled",
+ budget_tokens=DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
+ )
+ elif reasoning_effort == "high":
+ return AnthropicThinkingParam(
+ type="enabled",
+ budget_tokens=DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
+ )
+ elif reasoning_effort == "minimal":
+ return AnthropicThinkingParam(
+ type="enabled",
+ budget_tokens=DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET,
+ )
+ else:
+ raise ValueError(f"Unmapped reasoning effort: {reasoning_effort}")
def _extract_json_schema_from_response_format(
self, value: Optional[dict]
@@ -860,13 +867,8 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
if param == "thinking":
optional_params["thinking"] = value
elif param == "reasoning_effort" and isinstance(value, str):
- # For Claude Opus 4.5, map reasoning_effort to output_config
- if self._is_claude_opus_4_5(model):
- optional_params["output_config"] = {"effort": value}
-
- # For other models, map to thinking parameter
optional_params["thinking"] = AnthropicConfig._map_reasoning_effort(
- value
+ reasoning_effort=value, model=model
)
elif param == "web_search_options" and isinstance(value, dict):
hosted_web_search_tool = self.map_web_search_tool(
@@ -877,6 +879,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
)
elif param == "extra_headers":
optional_params["extra_headers"] = value
+ elif param == "context_management" and isinstance(value, dict):
+ # Pass through Anthropic-specific context_management parameter
+ optional_params["context_management"] = value
## handle thinking tokens
self.update_optional_params_with_thinking_tokens(
@@ -1026,9 +1031,37 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
if beta_value not in existing_values:
headers["anthropic-beta"] = f"{existing_beta}, {beta_value}"
- def _ensure_context_management_beta_header(self, headers: dict) -> None:
- beta_value = ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
- self._ensure_beta_header(headers, beta_value)
+ def _ensure_context_management_beta_header(
+ self, headers: dict, context_management: dict
+ ) -> None:
+ """
+ Add appropriate beta headers based on context_management edits.
+ - If any edit has type "compact_20260112", add compact-2026-01-12 header
+ - For all other edits, add context-management-2025-06-27 header
+ """
+ edits = context_management.get("edits", [])
+
+ has_compact = False
+ has_other = False
+
+ for edit in edits:
+ edit_type = edit.get("type", "")
+ if edit_type == "compact_20260112":
+ has_compact = True
+ else:
+ has_other = True
+
+ # Add compact header if any compact edits exist
+ if has_compact:
+ self._ensure_beta_header(
+ headers, ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value
+ )
+
+ # Add context management header if any other edits exist
+ if has_other:
+ self._ensure_beta_header(
+ headers, ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
+ )
def update_headers_with_optional_anthropic_beta(
self, headers: dict, optional_params: dict
@@ -1056,7 +1089,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
headers, ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
)
if optional_params.get("context_management") is not None:
- self._ensure_context_management_beta_header(headers)
+ self._ensure_context_management_beta_header(
+ headers, optional_params["context_management"]
+ )
if optional_params.get("output_format") is not None:
self._ensure_beta_header(
headers, ANTHROPIC_BETA_HEADER_VALUES.STRUCTURED_OUTPUT_2025_09_25.value
@@ -1225,6 +1260,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
List[ChatCompletionToolCallChunk],
Optional[List[Any]],
Optional[List[Any]],
+ Optional[List[Any]],
]:
text_content = ""
citations: Optional[List[Any]] = None
@@ -1237,6 +1273,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
tool_calls: List[ChatCompletionToolCallChunk] = []
web_search_results: Optional[List[Any]] = None
tool_results: Optional[List[Any]] = None
+ compaction_blocks: Optional[List[Any]] = None
for idx, content in enumerate(completion_response["content"]):
if content["type"] == "text":
text_content += content["text"]
@@ -1278,6 +1315,12 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
thinking_blocks.append(
cast(ChatCompletionRedactedThinkingBlock, content)
)
+
+ ## COMPACTION
+ elif content["type"] == "compaction":
+ if compaction_blocks is None:
+ compaction_blocks = []
+ compaction_blocks.append(content)
## CITATIONS
if content.get("citations") is not None:
@@ -1299,7 +1342,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
if thinking_content is not None:
reasoning_content += thinking_content
- return text_content, citations, thinking_blocks, reasoning_content, tool_calls, web_search_results, tool_results
+ return text_content, citations, thinking_blocks, reasoning_content, tool_calls, web_search_results, tool_results, compaction_blocks
def calculate_usage(
self,
@@ -1316,6 +1359,10 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
cache_creation_token_details: Optional[CacheCreationTokenDetails] = None
web_search_requests: Optional[int] = None
tool_search_requests: Optional[int] = None
+ inference_geo: Optional[str] = None
+ if "inference_geo" in _usage and _usage["inference_geo"] is not None:
+ inference_geo = _usage["inference_geo"]
+
if (
"cache_creation_input_tokens" in _usage
and _usage["cache_creation_input_tokens"] is not None
@@ -1399,6 +1446,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
if (web_search_requests is not None or tool_search_requests is not None)
else None
),
+ inference_geo=inference_geo,
)
return usage
@@ -1442,6 +1490,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
tool_calls,
web_search_results,
tool_results,
+ compaction_blocks,
) = self.extract_response_content(completion_response=completion_response)
if (
@@ -1469,6 +1518,8 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
provider_specific_fields["tool_results"] = tool_results
if container is not None:
provider_specific_fields["container"] = container
+ if compaction_blocks is not None:
+ provider_specific_fields["compaction_blocks"] = compaction_blocks
_message = litellm.Message(
tool_calls=tool_calls,
@@ -1477,6 +1528,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
thinking_blocks=thinking_blocks,
reasoning_content=reasoning_content,
)
+ _message.provider_specific_fields = provider_specific_fields
## HANDLE JSON MODE - anthropic returns single function call
json_mode_message = self._transform_response_for_json_mode(
@@ -1507,18 +1559,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
model_response.created = int(time.time())
model_response.model = completion_response["model"]
- context_management_response = completion_response.get("context_management")
- if context_management_response is not None:
- _hidden_params["context_management"] = context_management_response
- try:
- model_response.__dict__["context_management"] = (
- context_management_response
- )
- except Exception:
- pass
-
model_response._hidden_params = _hidden_params
-
return model_response
def get_prefix_prompt(self, messages: List[AllMessageValues]) -> Optional[str]:
diff --git a/litellm/llms/anthropic/cost_calculation.py b/litellm/llms/anthropic/cost_calculation.py
index 8f34eb00ce5..11b61cc92f0 100644
--- a/litellm/llms/anthropic/cost_calculation.py
+++ b/litellm/llms/anthropic/cost_calculation.py
@@ -22,10 +22,17 @@ def cost_per_token(model: str, usage: "Usage") -> Tuple[float, float]:
Returns:
Tuple[float, float] - prompt_cost_in_usd, completion_cost_in_usd
"""
- return generic_cost_per_token(
- model=model, usage=usage, custom_llm_provider="anthropic"
+ # If usage has inference_geo, prepend it as prefix to model name
+ if hasattr(usage, "inference_geo") and usage.inference_geo and usage.inference_geo.lower() not in ["global", "not_available"]:
+ model_with_geo_prefix = f"{usage.inference_geo}/{model}"
+ else:
+ model_with_geo_prefix = model
+ prompt_cost, completion_cost = generic_cost_per_token(
+ model=model_with_geo_prefix, usage=usage, custom_llm_provider="anthropic"
)
+ return prompt_cost, completion_cost
+
def get_cost_for_anthropic_web_search(
model_info: Optional["ModelInfo"] = None,
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
index 308bf367d06..bb40f9df266 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
@@ -2,6 +2,9 @@ from typing import Any, AsyncIterator, Dict, List, Optional, Tuple
import httpx
+from litellm.anthropic_beta_headers_manager import (
+ update_headers_with_filtered_beta,
+)
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.litellm_core_utils.litellm_logging import verbose_logger
from litellm.llms.base_llm.anthropic_messages.transformation import (
@@ -90,6 +93,11 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
optional_params=optional_params,
)
+ headers = update_headers_with_filtered_beta(
+ headers=headers,
+ provider="anthropic",
+ )
+
return headers, api_base
def transform_anthropic_messages_request(
@@ -189,8 +197,27 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
beta_values.update(b.strip() for b in existing_beta.split(","))
# Check for context management
- if optional_params.get("context_management") is not None:
- beta_values.add(ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value)
+ context_management_param = optional_params.get("context_management")
+ if context_management_param is not None:
+ # Check edits array for compact_20260112 type
+ edits = context_management_param.get("edits", [])
+ has_compact = False
+ has_other = False
+
+ for edit in edits:
+ edit_type = edit.get("type", "")
+ if edit_type == "compact_20260112":
+ has_compact = True
+ else:
+ has_other = True
+
+ # Add compact header if any compact edits exist
+ if has_compact:
+ beta_values.add(ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value)
+
+ # Add context management header if any other edits exist
+ if has_other:
+ beta_values.add(ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value)
# Check for structured outputs
if optional_params.get("output_format") is not None:
diff --git a/litellm/llms/azure_ai/anthropic/transformation.py b/litellm/llms/azure_ai/anthropic/transformation.py
index 2d8d3b987c7..753bc9c08eb 100644
--- a/litellm/llms/azure_ai/anthropic/transformation.py
+++ b/litellm/llms/azure_ai/anthropic/transformation.py
@@ -3,6 +3,9 @@ Azure Anthropic transformation config - extends AnthropicConfig with Azure authe
"""
from typing import TYPE_CHECKING, Dict, List, Optional, Union
+from litellm.anthropic_beta_headers_manager import (
+ update_headers_with_filtered_beta,
+)
from litellm.llms.anthropic.chat.transformation import AnthropicConfig
from litellm.llms.azure.common_utils import BaseAzureLLM
from litellm.types.llms.openai import AllMessageValues
@@ -87,6 +90,12 @@ class AzureAnthropicConfig(AnthropicConfig):
if "anthropic-version" not in headers:
headers["anthropic-version"] = "2023-06-01"
+ # Filter out unsupported beta headers for Azure AI
+ headers = update_headers_with_filtered_beta(
+ headers=headers,
+ provider="azure_ai",
+ )
+
return headers
def transform_request(
diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index f6d7e128580..7fc51263ebb 100644
--- a/litellm/llms/bedrock/chat/converse_transformation.py
+++ b/litellm/llms/bedrock/chat/converse_transformation.py
@@ -11,6 +11,9 @@ import httpx
import litellm
from litellm._logging import verbose_logger
+from litellm.anthropic_beta_headers_manager import (
+ filter_and_transform_beta_headers,
+)
from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
from litellm.litellm_core_utils.core_helpers import (
filter_exceptions_from_params,
@@ -66,6 +69,7 @@ from ..common_utils import (
BedrockModelInfo,
get_anthropic_beta_from_headers,
get_bedrock_tool_name,
+ is_claude_4_5_on_bedrock,
)
# Computer use tool prefixes supported by Bedrock
@@ -81,6 +85,7 @@ BEDROCK_COMPUTER_USE_TOOLS = [
UNSUPPORTED_BEDROCK_CONVERSE_BETA_PATTERNS = [
"advanced-tool-use", # Bedrock Converse doesn't support advanced-tool-use beta headers
"prompt-caching", # Prompt caching not supported in Converse API
+ "compact-2026-01-12", # The compact beta feature is not currently supported on the Converse and ConverseStream APIs
]
@@ -306,9 +311,7 @@ class AmazonConverseConfig(BaseConfig):
return "nova-2-lite" in model_without_region
def _map_web_search_options(
- self,
- web_search_options: dict,
- model: str
+ self, web_search_options: dict, model: str
) -> Optional[BedrockToolBlock]:
"""
Map web_search_options to Nova grounding systemTool.
@@ -431,7 +434,7 @@ class AmazonConverseConfig(BaseConfig):
else:
# Anthropic and other models: convert to thinking parameter
optional_params["thinking"] = AnthropicConfig._map_reasoning_effort(
- reasoning_effort
+ reasoning_effort=reasoning_effort, model=model
)
def get_supported_openai_params(self, model: str) -> List[str]:
@@ -617,37 +620,6 @@ class AmazonConverseConfig(BaseConfig):
return transformed_tools
- def _filter_unsupported_beta_headers_for_bedrock(
- self, model: str, beta_list: list
- ) -> list:
- """
- Remove beta headers that are not supported on Bedrock Converse API for the given model.
-
- Extended thinking beta headers are only supported on specific Claude 4+ models.
- Some beta headers are universally unsupported on Bedrock Converse API.
-
- Args:
- model: The model name
- beta_list: The list of beta headers to filter
-
- Returns:
- Filtered list of beta headers
- """
- filtered_betas = []
-
- # 1. Filter out beta headers that are universally unsupported on Bedrock Converse
- for beta in beta_list:
- should_keep = True
- for unsupported_pattern in UNSUPPORTED_BEDROCK_CONVERSE_BETA_PATTERNS:
- if unsupported_pattern in beta.lower():
- should_keep = False
- break
-
- if should_keep:
- filtered_betas.append(beta)
-
- return filtered_betas
-
def _separate_computer_use_tools(
self, tools: List[OpenAIChatCompletionToolParam], model: str
) -> Tuple[
@@ -808,11 +780,11 @@ class AmazonConverseConfig(BaseConfig):
if param == "web_search_options" and isinstance(value, dict):
# Note: we use `isinstance(value, dict)` instead of `value and isinstance(value, dict)`
# because empty dict {} is falsy but is a valid way to enable Nova grounding
- grounding_tool = self._map_web_search_options(value, model)
- if grounding_tool is not None:
- optional_params = self._add_tools_to_optional_params(
- optional_params=optional_params, tools=[grounding_tool]
- )
+ grounding_tool = self._map_web_search_options(value, model)
+ if grounding_tool is not None:
+ optional_params = self._add_tools_to_optional_params(
+ optional_params=optional_params, tools=[grounding_tool]
+ )
# Only update thinking tokens for non-GPT-OSS models and non-Nova-Lite-2 models
# Nova Lite 2 handles token budgeting differently through reasoningConfig
@@ -926,6 +898,7 @@ class AmazonConverseConfig(BaseConfig):
ChatCompletionAssistantMessage,
],
block_type: Literal["system"],
+ model: Optional[str] = None,
) -> Optional[SystemContentBlock]:
pass
@@ -939,6 +912,7 @@ class AmazonConverseConfig(BaseConfig):
ChatCompletionAssistantMessage,
],
block_type: Literal["content_block"],
+ model: Optional[str] = None,
) -> Optional[ContentBlock]:
pass
@@ -951,16 +925,26 @@ class AmazonConverseConfig(BaseConfig):
ChatCompletionAssistantMessage,
],
block_type: Literal["system", "content_block"],
+ model: Optional[str] = None,
) -> Optional[Union[SystemContentBlock, ContentBlock]]:
- if message_block.get("cache_control", None) is None:
+ cache_control = message_block.get("cache_control", None)
+ if cache_control is None:
return None
+
+ cache_point = CachePointBlock(type="default")
+ if isinstance(cache_control, dict) and "ttl" in cache_control:
+ ttl = cache_control["ttl"]
+ if ttl in ["5m", "1h"] and model is not None:
+ if is_claude_4_5_on_bedrock(model):
+ cache_point["ttl"] = ttl
+
if block_type == "system":
- return SystemContentBlock(cachePoint=CachePointBlock(type="default"))
+ return SystemContentBlock(cachePoint=cache_point)
else:
- return ContentBlock(cachePoint=CachePointBlock(type="default"))
+ return ContentBlock(cachePoint=cache_point)
def _transform_system_message(
- self, messages: List[AllMessageValues]
+ self, messages: List[AllMessageValues], model: Optional[str] = None
) -> Tuple[List[AllMessageValues], List[SystemContentBlock]]:
system_prompt_indices = []
system_content_blocks: List[SystemContentBlock] = []
@@ -972,7 +956,7 @@ class AmazonConverseConfig(BaseConfig):
SystemContentBlock(text=message["content"])
)
cache_block = self._get_cache_point_block(
- message, block_type="system"
+ message, block_type="system", model=model
)
if cache_block:
system_content_blocks.append(cache_block)
@@ -983,7 +967,7 @@ class AmazonConverseConfig(BaseConfig):
SystemContentBlock(text=m["text"])
)
cache_block = self._get_cache_point_block(
- m, block_type="system"
+ m, block_type="system", model=model
)
if cache_block:
system_content_blocks.append(cache_block)
@@ -1112,7 +1096,28 @@ class AmazonConverseConfig(BaseConfig):
# Add computer use tools and anthropic_beta if needed (only when computer use tools are present)
if computer_use_tools:
- anthropic_beta_list.append("computer-use-2024-10-22")
+ # Determine the correct computer-use beta header based on model
+ # "computer-use-2025-11-24" for Claude Opus 4.6, Claude Opus 4.5
+ # "computer-use-2025-01-24" for Claude Sonnet 4.5, Haiku 4.5, Opus 4.1, Sonnet 4, Opus 4, and Sonnet 3.7
+ # "computer-use-2024-10-22" for older models
+ model_lower = model.lower()
+ if "opus-4.6" in model_lower or "opus_4.6" in model_lower or "opus-4-6" in model_lower or "opus_4_6" in model_lower:
+ computer_use_header = "computer-use-2025-11-24"
+ elif "opus-4.5" in model_lower or "opus_4.5" in model_lower or "opus-4-5" in model_lower or "opus_4_5" in model_lower:
+ computer_use_header = "computer-use-2025-11-24"
+ elif any(pattern in model_lower for pattern in [
+ "sonnet-4.5", "sonnet_4.5", "sonnet-4-5", "sonnet_4_5",
+ "haiku-4.5", "haiku_4.5", "haiku-4-5", "haiku_4_5",
+ "opus-4.1", "opus_4.1", "opus-4-1", "opus_4_1",
+ "sonnet-4", "sonnet_4",
+ "opus-4", "opus_4",
+ "sonnet-3.7", "sonnet_3.7", "sonnet-3-7", "sonnet_3_7"
+ ]):
+ computer_use_header = "computer-use-2025-01-24"
+ else:
+ computer_use_header = "computer-use-2024-10-22"
+
+ anthropic_beta_list.append(computer_use_header)
# Transform computer use tools to proper Bedrock format
transformed_computer_tools = self._transform_computer_use_tools(
computer_use_tools
@@ -1137,14 +1142,14 @@ class AmazonConverseConfig(BaseConfig):
if beta not in seen:
unique_betas.append(beta)
seen.add(beta)
-
- # Filter out unsupported beta headers for Bedrock Converse API
- filtered_betas = self._filter_unsupported_beta_headers_for_bedrock(
- model=model,
- beta_list=unique_betas,
+
+ filtered_betas = filter_and_transform_beta_headers(
+ beta_headers=unique_betas,
+ provider="bedrock_converse",
)
- additional_request_params["anthropic_beta"] = filtered_betas
+ if filtered_betas:
+ additional_request_params["anthropic_beta"] = filtered_betas
return bedrock_tools, anthropic_beta_list
@@ -1196,9 +1201,11 @@ class AmazonConverseConfig(BaseConfig):
)
# Prepare and separate parameters
- inference_params, additional_request_params, request_metadata = self._prepare_request_params(
- optional_params, model
- )
+ (
+ inference_params,
+ additional_request_params,
+ request_metadata,
+ ) = self._prepare_request_params(optional_params, model)
original_tools = inference_params.pop("tools", [])
@@ -1250,7 +1257,9 @@ class AmazonConverseConfig(BaseConfig):
litellm_params: dict,
headers: Optional[dict] = None,
) -> RequestObject:
- messages, system_content_blocks = self._transform_system_message(messages)
+ messages, system_content_blocks = self._transform_system_message(
+ messages, model=model
+ )
# Convert last user message to guarded_text if guardrailConfig is present
messages = self._convert_consecutive_user_messages_to_guarded_text(
@@ -1306,7 +1315,9 @@ class AmazonConverseConfig(BaseConfig):
litellm_params: dict,
headers: Optional[dict] = None,
) -> RequestObject:
- messages, system_content_blocks = self._transform_system_message(messages)
+ messages, system_content_blocks = self._transform_system_message(
+ messages, model=model
+ )
# Convert last user message to guarded_text if guardrailConfig is present
messages = self._convert_consecutive_user_messages_to_guarded_text(
@@ -1484,7 +1495,9 @@ class AmazonConverseConfig(BaseConfig):
return message, returned_finish_reason
- def _translate_message_content(self, content_blocks: List[ContentBlock]) -> Tuple[
+ def _translate_message_content(
+ self, content_blocks: List[ContentBlock]
+ ) -> Tuple[
str,
List[ChatCompletionToolCallChunk],
Optional[List[BedrockConverseReasoningContentBlock]],
@@ -1501,9 +1514,9 @@ class AmazonConverseConfig(BaseConfig):
"""
content_str = ""
tools: List[ChatCompletionToolCallChunk] = []
- reasoningContentBlocks: Optional[List[BedrockConverseReasoningContentBlock]] = (
- None
- )
+ reasoningContentBlocks: Optional[
+ List[BedrockConverseReasoningContentBlock]
+ ] = None
citationsContentBlocks: Optional[List[CitationsContentBlock]] = None
for idx, content in enumerate(content_blocks):
"""
@@ -1557,7 +1570,7 @@ class AmazonConverseConfig(BaseConfig):
return content_str, tools, reasoningContentBlocks, citationsContentBlocks
- def _transform_response( # noqa: PLR0915
+ def _transform_response( # noqa: PLR0915
self,
model: str,
response: httpx.Response,
@@ -1630,9 +1643,9 @@ class AmazonConverseConfig(BaseConfig):
chat_completion_message: ChatCompletionResponseMessage = {"role": "assistant"}
content_str = ""
tools: List[ChatCompletionToolCallChunk] = []
- reasoningContentBlocks: Optional[List[BedrockConverseReasoningContentBlock]] = (
- None
- )
+ reasoningContentBlocks: Optional[
+ List[BedrockConverseReasoningContentBlock]
+ ] = None
citationsContentBlocks: Optional[List[CitationsContentBlock]] = None
if message is not None:
@@ -1651,15 +1664,17 @@ class AmazonConverseConfig(BaseConfig):
provider_specific_fields["citationsContent"] = citationsContentBlocks
if provider_specific_fields:
- chat_completion_message["provider_specific_fields"] = provider_specific_fields
+ chat_completion_message[
+ "provider_specific_fields"
+ ] = provider_specific_fields
if reasoningContentBlocks is not None:
- chat_completion_message["reasoning_content"] = (
- self._transform_reasoning_content(reasoningContentBlocks)
- )
- chat_completion_message["thinking_blocks"] = (
- self._transform_thinking_blocks(reasoningContentBlocks)
- )
+ chat_completion_message[
+ "reasoning_content"
+ ] = self._transform_reasoning_content(reasoningContentBlocks)
+ chat_completion_message[
+ "thinking_blocks"
+ ] = self._transform_thinking_blocks(reasoningContentBlocks)
chat_completion_message["content"] = content_str
if (
json_mode is True
diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py
index 65d237bdbdf..4c87f6fa994 100644
--- a/litellm/llms/bedrock/common_utils.py
+++ b/litellm/llms/bedrock/common_utils.py
@@ -446,6 +446,29 @@ def get_bedrock_base_model(model: str) -> str:
return model
+def is_claude_4_5_on_bedrock(model: str) -> bool:
+ """
+ Check if the model is a Claude 4.5 model on Bedrock.
+ Claude 4.5 models support prompt caching with '5m' and '1h' TTL on Bedrock.
+ """
+ model_lower = model.lower()
+ claude_4_5_patterns = [
+ "sonnet-4.5",
+ "sonnet_4.5",
+ "sonnet-4-5",
+ "sonnet_4_5",
+ "haiku-4.5",
+ "haiku_4.5",
+ "haiku-4-5",
+ "haiku_4_5",
+ "opus-4.5",
+ "opus_4.5",
+ "opus-4-5",
+ "opus_4_5",
+ ]
+ return any(pattern in model_lower for pattern in claude_4_5_patterns)
+
+
# Import after standalone functions to avoid circular imports
from litellm.llms.bedrock.count_tokens.bedrock_token_counter import BedrockTokenCounter
@@ -815,21 +838,23 @@ def get_anthropic_beta_from_headers(headers: dict) -> List[str]:
# If it's already a list, return it
if isinstance(anthropic_beta_header, list):
return anthropic_beta_header
-
+
# Try to parse as JSON array first (e.g., '["interleaved-thinking-2025-05-14", "claude-code-20250219"]')
if isinstance(anthropic_beta_header, str):
anthropic_beta_header = anthropic_beta_header.strip()
- if anthropic_beta_header.startswith("[") and anthropic_beta_header.endswith("]"):
+ if anthropic_beta_header.startswith("[") and anthropic_beta_header.endswith(
+ "]"
+ ):
try:
parsed = json.loads(anthropic_beta_header)
if isinstance(parsed, list):
return [str(beta).strip() for beta in parsed]
except json.JSONDecodeError:
pass # Fall through to comma-separated parsing
-
+
# Fall back to comma-separated values
return [beta.strip() for beta in anthropic_beta_header.split(",")]
-
+
return []
diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
index b1c45ea83a2..19fe7d8c140 100644
--- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
@@ -12,6 +12,9 @@ from typing import (
import httpx
+from litellm.anthropic_beta_headers_manager import (
+ filter_and_transform_beta_headers,
+)
from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
AnthropicMessagesConfig,
@@ -23,7 +26,10 @@ from litellm.llms.bedrock.chat.invoke_handler import AWSEventStreamDecoder
from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation import (
AmazonInvokeConfig,
)
-from litellm.llms.bedrock.common_utils import get_anthropic_beta_from_headers
+from litellm.llms.bedrock.common_utils import (
+ get_anthropic_beta_from_headers,
+ is_claude_4_5_on_bedrock,
+)
from litellm.types.llms.anthropic import ANTHROPIC_TOOL_SEARCH_BETA_HEADER
from litellm.types.llms.openai import AllMessageValues
from litellm.types.router import GenericLiteLLMParams
@@ -52,10 +58,6 @@ class AmazonAnthropicClaudeMessagesConfig(
# Beta header patterns that are not supported by Bedrock Invoke API
# These will be filtered out to prevent 400 "invalid beta flag" errors
- UNSUPPORTED_BEDROCK_INVOKE_BETA_PATTERNS = [
- "advanced-tool-use", # Bedrock Invoke doesn't support advanced-tool-use beta headers
- "prompt-caching-scope"
- ]
def __init__(self, **kwargs):
BaseAnthropicMessagesConfig.__init__(self, **kwargs)
@@ -116,15 +118,22 @@ class AmazonAnthropicClaudeMessagesConfig(
)
def _remove_ttl_from_cache_control(
- self, anthropic_messages_request: Dict
+ self, anthropic_messages_request: Dict, model: Optional[str] = None
) -> None:
"""
Remove `ttl` field from cache_control in messages.
Bedrock doesn't support the ttl field in cache_control.
+ Update: Bedock supports `5m` and `1h` for Claude 4.5 models.
+
Args:
anthropic_messages_request: The request dictionary to modify in-place
+ model: The model name to check if it supports ttl
"""
+ is_claude_4_5 = False
+ if model:
+ is_claude_4_5 = self._is_claude_4_5_on_bedrock(model)
+
if "messages" in anthropic_messages_request:
for message in anthropic_messages_request["messages"]:
if isinstance(message, dict) and "content" in message:
@@ -133,7 +142,14 @@ class AmazonAnthropicClaudeMessagesConfig(
for item in content:
if isinstance(item, dict) and "cache_control" in item:
cache_control = item["cache_control"]
- if isinstance(cache_control, dict) and "ttl" in cache_control:
+ if (
+ isinstance(cache_control, dict)
+ and "ttl" in cache_control
+ ):
+ ttl = cache_control["ttl"]
+ if is_claude_4_5 and ttl in ["5m", "1h"]:
+ continue
+
cache_control.pop("ttl", None)
def _supports_extended_thinking_on_bedrock(self, model: str) -> bool:
@@ -155,10 +171,18 @@ class AmazonAnthropicClaudeMessagesConfig(
# Supported models on Bedrock for extended thinking
supported_patterns = [
- "opus-4.5", "opus_4.5", "opus-4-5", "opus_4_5", # Opus 4.5
- "opus-4.1", "opus_4.1", "opus-4-1", "opus_4_1", # Opus 4.1
- "opus-4", "opus_4", # Opus 4
- "sonnet-4", "sonnet_4", # Sonnet 4
+ "opus-4.5",
+ "opus_4.5",
+ "opus-4-5",
+ "opus_4_5", # Opus 4.5
+ "opus-4.1",
+ "opus_4.1",
+ "opus-4-1",
+ "opus_4_1", # Opus 4.1
+ "opus-4",
+ "opus_4", # Opus 4
+ "sonnet-4",
+ "sonnet_4", # Sonnet 4
]
return any(pattern in model_lower for pattern in supported_patterns)
@@ -175,10 +199,27 @@ class AmazonAnthropicClaudeMessagesConfig(
"""
model_lower = model.lower()
opus_4_5_patterns = [
- "opus-4.5", "opus_4.5", "opus-4-5", "opus_4_5",
+ "opus-4.5",
+ "opus_4.5",
+ "opus-4-5",
+ "opus_4_5",
]
return any(pattern in model_lower for pattern in opus_4_5_patterns)
+ def _is_claude_4_5_on_bedrock(self, model: str) -> bool:
+ """
+ Check if the model is Claude 4.5 on Bedrock.
+
+ Claude Sonnet 4.5, Haiku 4.5, and Opus 4.5 support 1-hour prompt caching.
+
+ Args:
+ model: The model name
+
+ Returns:
+ True if the model is Claude 4.5
+ """
+ return is_claude_4_5_on_bedrock(model)
+
def _supports_tool_search_on_bedrock(self, model: str) -> bool:
"""
Check if the model supports tool search on Bedrock.
@@ -199,9 +240,15 @@ class AmazonAnthropicClaudeMessagesConfig(
# Supported models for tool search on Bedrock
supported_patterns = [
# Opus 4.5
- "opus-4.5", "opus_4.5", "opus-4-5", "opus_4_5",
+ "opus-4.5",
+ "opus_4.5",
+ "opus-4-5",
+ "opus_4_5",
# Sonnet 4.5
- "sonnet-4.5", "sonnet_4.5", "sonnet-4-5", "sonnet_4_5",
+ "sonnet-4.5",
+ "sonnet_4.5",
+ "sonnet-4-5",
+ "sonnet_4_5",
]
return any(pattern in model_lower for pattern in supported_patterns)
@@ -228,41 +275,48 @@ class AmazonAnthropicClaudeMessagesConfig(
model: The model name
beta_set: The set of beta headers to filter in-place
"""
- beta_headers_to_remove = set()
- has_advanced_tool_use = False
-
- # 1. Filter out beta headers that are universally unsupported on Bedrock Invoke and track if advanced-tool-use header is present
- for beta in beta_set:
- for unsupported_pattern in self.UNSUPPORTED_BEDROCK_INVOKE_BETA_PATTERNS:
- if unsupported_pattern in beta.lower():
- beta_headers_to_remove.add(beta)
- has_advanced_tool_use = True
- break
-
+ # 1. Handle header transformations BEFORE filtering
+ # (advanced-tool-use -> tool-search-tool)
+ # This must happen before filtering because advanced-tool-use is in the unsupported list
+ has_advanced_tool_use = "advanced-tool-use-2025-11-20" in beta_set
+ if has_advanced_tool_use and self._supports_tool_search_on_bedrock(model):
+ beta_set.discard("advanced-tool-use-2025-11-20")
+ beta_set.add("tool-search-tool-2025-10-19")
+ beta_set.add("tool-examples-2025-10-29")
- # 2. Filter out extended thinking headers for models that don't support them
+ # 2. Apply provider-level filtering using centralized JSON config
+ beta_list = list(beta_set)
+ filtered_list = filter_and_transform_beta_headers(
+ beta_headers=beta_list,
+ provider="bedrock",
+ )
+
+ # Update the set with filtered headers
+ beta_set.clear()
+ beta_set.update(filtered_list)
+
+ # 2.1. Handle model-specific exceptions: structured-outputs is only supported on Opus 4.6
+ # Re-add structured-outputs if it was in the original set and model is Opus 4.6
+ model_lower = model.lower()
+ is_opus_4_6 = any(pattern in model_lower for pattern in ["opus-4.6", "opus_4.6", "opus-4-6", "opus_4_6"])
+ if is_opus_4_6 and "structured-outputs-2025-11-13" in beta_list:
+ beta_set.add("structured-outputs-2025-11-13")
+
+ # 3. Filter out extended thinking headers for models that don't support them
extended_thinking_patterns = [
"extended-thinking",
"interleaved-thinking",
]
if not self._supports_extended_thinking_on_bedrock(model):
+ beta_headers_to_remove = set()
for beta in beta_set:
for pattern in extended_thinking_patterns:
if pattern in beta.lower():
beta_headers_to_remove.add(beta)
break
-
- # Remove all filtered headers
- for beta in beta_headers_to_remove:
- beta_set.discard(beta)
-
- # 3. Translate advanced-tool-use to Bedrock-specific headers for models that support tool search
- # Ref: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages-request-response.html
- # Ref: https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-search-tool
- if has_advanced_tool_use and self._supports_tool_search_on_bedrock(model):
- beta_set.add("tool-search-tool-2025-10-19")
- beta_set.add("tool-examples-2025-10-29")
-
+
+ for beta in beta_headers_to_remove:
+ beta_set.discard(beta)
def _get_tool_search_beta_header_for_bedrock(
self,
@@ -290,7 +344,9 @@ class AmazonAnthropicClaudeMessagesConfig(
input_examples_used: Whether input examples are used
beta_set: The set of beta headers to modify in-place
"""
- if tool_search_used and not (programmatic_tool_calling_used or input_examples_used):
+ if tool_search_used and not (
+ programmatic_tool_calling_used or input_examples_used
+ ):
beta_set.discard(ANTHROPIC_TOOL_SEARCH_BETA_HEADER)
if "opus-4" in model.lower() or "opus_4" in model.lower():
beta_set.add("tool-search-tool-2025-10-19")
@@ -302,13 +358,13 @@ class AmazonAnthropicClaudeMessagesConfig(
) -> None:
"""
Convert Anthropic output_format to inline schema in message content.
-
+
Bedrock Invoke doesn't support the output_format parameter, so we embed
the schema directly into the user message content as text instructions.
-
+
This approach adds the schema to the last user message, instructing the model
to respond in the specified JSON format.
-
+
Args:
output_format: The output_format dict with 'type' and 'schema'
anthropic_messages_request: The request dict to modify in-place
@@ -321,35 +377,32 @@ class AmazonAnthropicClaudeMessagesConfig(
schema = output_format.get("schema")
if not schema:
return
-
+
# Get messages from the request
messages = anthropic_messages_request.get("messages", [])
if not messages:
return
-
+
# Find the last user message
last_user_message_idx = None
for idx in range(len(messages) - 1, -1, -1):
if messages[idx].get("role") == "user":
last_user_message_idx = idx
break
-
+
if last_user_message_idx is None:
return
-
+
last_user_message = messages[last_user_message_idx]
content = last_user_message.get("content", [])
-
+
# Ensure content is a list
if isinstance(content, str):
content = [{"type": "text", "text": content}]
last_user_message["content"] = content
-
+
# Add schema as text content to the message
- schema_text = {
- "type": "text",
- "text": json.dumps(schema)
- }
+ schema_text = {"type": "text", "text": json.dumps(schema)}
content.append(schema_text)
def transform_anthropic_messages_request(
@@ -374,9 +427,9 @@ class AmazonAnthropicClaudeMessagesConfig(
# 1. anthropic_version is required for all claude models
if "anthropic_version" not in anthropic_messages_request:
- anthropic_messages_request["anthropic_version"] = (
- self.DEFAULT_BEDROCK_ANTHROPIC_API_VERSION
- )
+ anthropic_messages_request[
+ "anthropic_version"
+ ] = self.DEFAULT_BEDROCK_ANTHROPIC_API_VERSION
# 2. `stream` is not allowed in request body for bedrock invoke
if "stream" in anthropic_messages_request:
@@ -386,8 +439,10 @@ class AmazonAnthropicClaudeMessagesConfig(
if "model" in anthropic_messages_request:
anthropic_messages_request.pop("model", None)
- # 4. Remove `ttl` field from cache_control in messages (Bedrock doesn't support it)
- self._remove_ttl_from_cache_control(anthropic_messages_request)
+ # 4. Remove `ttl` field from cache_control in messages (Bedrock doesn't support it for older models)
+ self._remove_ttl_from_cache_control(
+ anthropic_messages_request=anthropic_messages_request, model=model
+ )
# 5. Convert `output_format` to inline schema (Bedrock invoke doesn't support output_format)
output_format = anthropic_messages_request.pop("output_format", None)
@@ -396,14 +451,14 @@ class AmazonAnthropicClaudeMessagesConfig(
output_format=output_format,
anthropic_messages_request=anthropic_messages_request,
)
-
+
# 6. AUTO-INJECT beta headers based on features used
anthropic_model_info = AnthropicModelInfo()
tools = anthropic_messages_optional_request_params.get("tools")
messages_typed = cast(List[AllMessageValues], messages)
tool_search_used = anthropic_model_info.is_tool_search_used(tools)
- programmatic_tool_calling_used = anthropic_model_info.is_programmatic_tool_calling_used(
- tools
+ programmatic_tool_calling_used = (
+ anthropic_model_info.is_programmatic_tool_calling_used(tools)
)
input_examples_used = anthropic_model_info.is_input_examples_used(tools)
@@ -436,8 +491,7 @@ class AmazonAnthropicClaudeMessagesConfig(
if beta_set:
anthropic_messages_request["anthropic_beta"] = list(beta_set)
-
-
+
return anthropic_messages_request
def get_async_streaming_response_iterator(
@@ -455,7 +509,7 @@ class AmazonAnthropicClaudeMessagesConfig(
)
# Convert decoded Bedrock events to Server-Sent Events expected by Anthropic clients.
return self.bedrock_sse_wrapper(
- completion_stream=completion_stream,
+ completion_stream=completion_stream,
litellm_logging_obj=litellm_logging_obj,
request_body=request_body,
)
@@ -474,14 +528,14 @@ class AmazonAnthropicClaudeMessagesConfig(
from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
BaseAnthropicMessagesStreamingIterator,
)
+
handler = BaseAnthropicMessagesStreamingIterator(
litellm_logging_obj=litellm_logging_obj,
request_body=request_body,
)
-
+
async for chunk in handler.async_sse_wrapper(completion_stream):
yield chunk
-
class AmazonAnthropicClaudeMessagesStreamDecoder(AWSEventStreamDecoder):
diff --git a/litellm/llms/databricks/chat/transformation.py b/litellm/llms/databricks/chat/transformation.py
index 2b7f5dd5995..e9ae94307d4 100644
--- a/litellm/llms/databricks/chat/transformation.py
+++ b/litellm/llms/databricks/chat/transformation.py
@@ -298,7 +298,8 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig):
if "reasoning_effort" in non_default_params and "claude" in model:
optional_params["thinking"] = AnthropicConfig._map_reasoning_effort(
- non_default_params.get("reasoning_effort")
+ reasoning_effort=non_default_params.get("reasoning_effort"),
+ model=model
)
optional_params.pop("reasoning_effort", None)
## handle thinking tokens
diff --git a/litellm/llms/deprecated_providers/palm.py b/litellm/llms/deprecated_providers/palm.py
index 3039222c0e2..657a6fdb229 100644
--- a/litellm/llms/deprecated_providers/palm.py
+++ b/litellm/llms/deprecated_providers/palm.py
@@ -139,7 +139,7 @@ def completion(
)
## COMPLETION CALL
try:
- response = palm.generate_text(prompt=prompt, **inference_params)
+ response = palm.generate_text(prompt=prompt, **inference_params) # type: ignore[attr-defined]
except Exception as e:
raise PalmError(
message=str(e),
diff --git a/litellm/llms/gigachat/chat/transformation.py b/litellm/llms/gigachat/chat/transformation.py
index ba14de1f65d..f546f356e11 100644
--- a/litellm/llms/gigachat/chat/transformation.py
+++ b/litellm/llms/gigachat/chat/transformation.py
@@ -386,33 +386,7 @@ class GigaChatConfig(BaseConfig):
transformed.append(message)
- # Collapse consecutive user messages
- return self._collapse_user_messages(transformed)
-
- def _collapse_user_messages(self, messages: List[dict]) -> List[dict]:
- """Collapse consecutive user messages into one."""
- collapsed: List[dict] = []
- prev_user_msg: Optional[dict] = None
- content_parts: List[str] = []
-
- for msg in messages:
- if msg.get("role") == "user" and prev_user_msg is not None:
- content_parts.append(msg.get("content", ""))
- else:
- if content_parts and prev_user_msg:
- prev_user_msg["content"] = "\n".join(
- [prev_user_msg.get("content", "")] + content_parts
- )
- content_parts = []
- collapsed.append(msg)
- prev_user_msg = msg if msg.get("role") == "user" else None
-
- if content_parts and prev_user_msg:
- prev_user_msg["content"] = "\n".join(
- [prev_user_msg.get("content", "")] + content_parts
- )
-
- return collapsed
+ return transformed
def transform_response(
self,
diff --git a/litellm/llms/github_copilot/chat/transformation.py b/litellm/llms/github_copilot/chat/transformation.py
index d613c82402d..be8ad7d0877 100644
--- a/litellm/llms/github_copilot/chat/transformation.py
+++ b/litellm/llms/github_copilot/chat/transformation.py
@@ -1,5 +1,6 @@
from typing import List, Optional, Tuple
+
from litellm.exceptions import AuthenticationError
from litellm.llms.openai.openai import OpenAIConfig
from litellm.types.llms.openai import AllMessageValues
@@ -29,9 +30,7 @@ class GithubCopilotConfig(OpenAIConfig):
api_key: Optional[str],
custom_llm_provider: str,
) -> Tuple[Optional[str], Optional[str], str]:
- dynamic_api_base = (
- self.authenticator.get_api_base() or GITHUB_COPILOT_API_BASE
- )
+ dynamic_api_base = self.authenticator.get_api_base() or GITHUB_COPILOT_API_BASE
try:
dynamic_api_key = self.authenticator.get_api_key()
except GetAPIKeyError as e:
@@ -140,7 +139,7 @@ class GithubCopilotConfig(OpenAIConfig):
"""
Check if any message contains vision content (images).
Returns True if any message has content with vision-related types, otherwise False.
-
+
Checks for:
- image_url content type (OpenAI format)
- Content items with type 'image_url'
diff --git a/litellm/llms/openai/embeddings/guardrail_translation/__init__.py b/litellm/llms/openai/embeddings/guardrail_translation/__init__.py
new file mode 100644
index 00000000000..a60662282ca
--- /dev/null
+++ b/litellm/llms/openai/embeddings/guardrail_translation/__init__.py
@@ -0,0 +1,13 @@
+"""OpenAI Embeddings handler for Unified Guardrails."""
+
+from litellm.llms.openai.embeddings.guardrail_translation.handler import (
+ OpenAIEmbeddingsHandler,
+)
+from litellm.types.utils import CallTypes
+
+guardrail_translation_mappings = {
+ CallTypes.embedding: OpenAIEmbeddingsHandler,
+ CallTypes.aembedding: OpenAIEmbeddingsHandler,
+}
+
+__all__ = ["guardrail_translation_mappings", "OpenAIEmbeddingsHandler"]
diff --git a/litellm/llms/openai/embeddings/guardrail_translation/handler.py b/litellm/llms/openai/embeddings/guardrail_translation/handler.py
new file mode 100644
index 00000000000..7458020e109
--- /dev/null
+++ b/litellm/llms/openai/embeddings/guardrail_translation/handler.py
@@ -0,0 +1,179 @@
+"""
+OpenAI Embeddings Handler for Unified Guardrails
+
+This module provides guardrail translation support for OpenAI's embeddings endpoint.
+The handler processes the 'input' parameter for guardrails.
+"""
+
+from typing import TYPE_CHECKING, Any, List, Optional, Union
+
+from litellm._logging import verbose_proxy_logger
+from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.types.utils import GenericGuardrailAPIInputs
+
+if TYPE_CHECKING:
+ from litellm.integrations.custom_guardrail import CustomGuardrail
+ from litellm.types.utils import EmbeddingResponse
+
+
+class OpenAIEmbeddingsHandler(BaseTranslation):
+ """
+ Handler for processing OpenAI embeddings requests with guardrails.
+
+ This class provides methods to:
+ 1. Process input text (pre-call hook)
+ 2. Process output response (post-call hook) - embeddings don't typically need output guardrails
+
+ The handler specifically processes the 'input' parameter which can be:
+ - A single string
+ - A list of strings (for batch embeddings)
+ - A list of integers (token IDs - not processed by guardrails)
+ - A list of lists of integers (batch token IDs - not processed by guardrails)
+ """
+
+ async def process_input_messages(
+ self,
+ data: dict,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional[Any] = None,
+ ) -> Any:
+ """
+ Process input text by applying guardrails to text content.
+
+ Args:
+ data: Request data dictionary containing 'input' parameter
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+
+ Returns:
+ Modified data with guardrails applied to input
+ """
+ input_data = data.get("input")
+ if input_data is None:
+ verbose_proxy_logger.debug(
+ "OpenAI Embeddings: No input found in request data"
+ )
+ return data
+
+ if isinstance(input_data, str):
+ data = await self._process_string_input(
+ data, input_data, guardrail_to_apply, litellm_logging_obj
+ )
+ elif isinstance(input_data, list):
+ data = await self._process_list_input(
+ data, input_data, guardrail_to_apply, litellm_logging_obj
+ )
+ else:
+ verbose_proxy_logger.warning(
+ "OpenAI Embeddings: Unexpected input type: %s. Expected string or list.",
+ type(input_data),
+ )
+
+ return data
+
+ async def _process_string_input(
+ self,
+ data: dict,
+ input_data: str,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional[Any],
+ ) -> dict:
+ """Process a single string input through the guardrail."""
+ inputs = GenericGuardrailAPIInputs(texts=[input_data])
+ if model := data.get("model"):
+ inputs["model"] = model
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=data,
+ input_type="request",
+ logging_obj=litellm_logging_obj,
+ )
+
+ if guardrailed_texts := guardrailed_inputs.get("texts"):
+ data["input"] = guardrailed_texts[0]
+ verbose_proxy_logger.debug(
+ "OpenAI Embeddings: Applied guardrail to string input. "
+ "Original length: %d, New length: %d",
+ len(input_data),
+ len(data["input"]),
+ )
+
+ return data
+
+ async def _process_list_input(
+ self,
+ data: dict,
+ input_data: List[Union[str, int, List[int]]],
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional[Any],
+ ) -> dict:
+ """Process a list input through the guardrail (if it contains strings)."""
+ if len(input_data) == 0:
+ return data
+
+ first_item = input_data[0]
+
+ # Skip non-text inputs (token IDs)
+ if isinstance(first_item, (int, list)):
+ verbose_proxy_logger.debug(
+ "OpenAI Embeddings: Input is token IDs, skipping guardrail processing"
+ )
+ return data
+
+ if not isinstance(first_item, str):
+ verbose_proxy_logger.warning(
+ "OpenAI Embeddings: Unexpected input list item type: %s",
+ type(first_item),
+ )
+ return data
+
+ # List of strings - apply guardrail
+ inputs = GenericGuardrailAPIInputs(texts=input_data) # type: ignore
+ if model := data.get("model"):
+ inputs["model"] = model
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=data,
+ input_type="request",
+ logging_obj=litellm_logging_obj,
+ )
+
+ if guardrailed_texts := guardrailed_inputs.get("texts"):
+ data["input"] = guardrailed_texts
+ verbose_proxy_logger.debug(
+ "OpenAI Embeddings: Applied guardrail to %d inputs",
+ len(guardrailed_texts),
+ )
+
+ return data
+
+ async def process_output_response(
+ self,
+ response: "EmbeddingResponse",
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional[Any] = None,
+ user_api_key_dict: Optional[Any] = None,
+ ) -> Any:
+ """
+ Process output response - embeddings responses contain vectors, not text.
+
+ For embeddings, the output is numerical vectors, so there's typically
+ no text content to apply guardrails to. This method is a no-op but
+ is included for interface consistency.
+
+ Args:
+ response: Embedding response object
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+ user_api_key_dict: User API key metadata
+
+ Returns:
+ Unmodified response (embeddings don't have text output to guard)
+ """
+ verbose_proxy_logger.debug(
+ "OpenAI Embeddings: Output response processing skipped - "
+ "embeddings contain vectors, not text"
+ )
+ return response
diff --git a/litellm/llms/vertex_ai/files/transformation.py b/litellm/llms/vertex_ai/files/transformation.py
index b3612113ec2..2470c59bbac 100644
--- a/litellm/llms/vertex_ai/files/transformation.py
+++ b/litellm/llms/vertex_ai/files/transformation.py
@@ -165,7 +165,7 @@ class VertexAIFilesConfig(VertexBase, BaseFilesConfig):
"""
Get the complete url for the request
"""
- bucket_name = litellm_params.get("bucket_name") or os.getenv("GCS_BUCKET_NAME")
+ bucket_name = litellm_params.get("bucket_name") or litellm_params.get("litellm_metadata", {}).pop("gcs_bucket_name", None) or os.getenv("GCS_BUCKET_NAME")
if not bucket_name:
raise ValueError("GCS bucket_name is required")
file_data = data.get("file")
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 b5a6949f272..04ae4b6beb8 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
@@ -1732,6 +1732,52 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
else:
return "stop"
+ @staticmethod
+ def _check_prompt_level_content_filter(
+ processed_chunk: GenerateContentResponseBody,
+ response_id: Optional[str],
+ ) -> Optional["ModelResponseStream"]:
+ """
+ Check if prompt is blocked due to content filtering at the prompt level.
+
+ This handles the case where Vertex AI blocks the prompt before generation begins,
+ indicated by promptFeedback.blockReason being present.
+
+ Args:
+ processed_chunk: The parsed response chunk from Vertex AI
+ response_id: The response ID from the chunk
+
+ Returns:
+ ModelResponseStream with content_filter finish_reason if blocked, None otherwise.
+
+ Note:
+ This is consistent with non-streaming _handle_blocked_response() behavior.
+ Candidate-level content filtering (SAFETY, RECITATION, etc.) is handled
+ separately via _process_candidates() → _check_finish_reason().
+ """
+ from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+ # Check if prompt is blocked due to content filtering
+ prompt_feedback = processed_chunk.get("promptFeedback")
+ if prompt_feedback and "blockReason" in prompt_feedback:
+ verbose_logger.debug(
+ f"Prompt blocked due to: {prompt_feedback.get('blockReason')} - {prompt_feedback.get('blockReasonMessage')}"
+ )
+
+ # Create a content_filter response (consistent with non-streaming _handle_blocked_response)
+ choice = StreamingChoices(
+ finish_reason="content_filter",
+ index=0,
+ delta=Delta(content=None, role="assistant"),
+ logprobs=None,
+ enhancements=None,
+ )
+
+ model_response = ModelResponseStream(choices=[choice], id=response_id)
+ return model_response
+
+ return None
+
@staticmethod
def _calculate_web_search_requests(grounding_metadata: List[dict]) -> Optional[int]:
web_search_requests: Optional[int] = None
@@ -2813,6 +2859,15 @@ class ModelResponseIterator:
processed_chunk = GenerateContentResponseBody(**chunk) # type: ignore
response_id = processed_chunk.get("responseId")
model_response = ModelResponseStream(choices=[], id=response_id)
+
+ # Check if prompt is blocked due to content filtering
+ blocked_response = VertexGeminiConfig._check_prompt_level_content_filter(
+ processed_chunk=processed_chunk,
+ response_id=response_id,
+ )
+ if blocked_response is not None:
+ model_response = blocked_response
+
usage: Optional[Usage] = None
_candidates: Optional[List[Candidates]] = processed_chunk.get("candidates")
grounding_metadata: List[dict] = []
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 9b8ff3ecc2d..918b8ecc225 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -1,5 +1,8 @@
from typing import Any, Dict, List, Optional, Tuple
+from litellm.anthropic_beta_headers_manager import (
+ update_headers_with_filtered_beta,
+)
from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
AnthropicMessagesConfig,
@@ -7,7 +10,6 @@ from litellm.llms.anthropic.experimental_pass_through.messages.transformation im
from litellm.types.llms.anthropic import (
ANTHROPIC_BETA_HEADER_VALUES,
ANTHROPIC_HOSTED_TOOLS,
- ANTHROPIC_PROMPT_CACHING_SCOPE_BETA_HEADER,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.llms.vertex_ai import VertexPartnerProvider
@@ -65,10 +67,6 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
existing_beta = headers.get("anthropic-beta")
if existing_beta:
beta_values.update(b.strip() for b in existing_beta.split(","))
-
- # Use the helper to remove unsupported beta headers
- self.remove_unsupported_beta(headers)
- beta_values.discard(ANTHROPIC_PROMPT_CACHING_SCOPE_BETA_HEADER)
# Check for web search tool
for tool in tools:
@@ -84,6 +82,12 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
if beta_values:
headers["anthropic-beta"] = ",".join(beta_values)
+ # Filter out unsupported beta headers for Vertex AI
+ headers = update_headers_with_filtered_beta(
+ headers=headers,
+ provider="vertex_ai",
+ )
+
return headers, api_base
def get_complete_url(
@@ -128,23 +132,3 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
) # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet
return anthropic_messages_request
-
- def remove_unsupported_beta(self, headers: dict) -> None:
- """
- Helper method to remove unsupported beta headers from the beta headers.
- Modifies headers in place.
- """
- unsupported_beta_headers = [
- ANTHROPIC_PROMPT_CACHING_SCOPE_BETA_HEADER
- ]
- existing_beta = headers.get("anthropic-beta")
- if existing_beta:
- filtered_beta = [
- b.strip()
- for b in existing_beta.split(",")
- if b.strip() not in unsupported_beta_headers
- ]
- if filtered_beta:
- headers["anthropic-beta"] = ",".join(filtered_beta)
- elif "anthropic-beta" in headers:
- del headers["anthropic-beta"]
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
index 1df07f405e6..0b728d88e76 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
@@ -51,6 +51,40 @@ class VertexAIAnthropicConfig(AnthropicConfig):
def custom_llm_provider(self) -> Optional[str]:
return "vertex_ai"
+ def _add_context_management_beta_headers(
+ self, beta_set: set, context_management: dict
+ ) -> None:
+ """
+ Add context_management beta headers to the beta_set.
+
+ - If any edit has type "compact_20260112", add compact-2026-01-12 header
+ - For all other edits, add context-management-2025-06-27 header
+
+ Args:
+ beta_set: Set of beta headers to modify in-place
+ context_management: The context_management dict from optional_params
+ """
+ from litellm.types.llms.anthropic import ANTHROPIC_BETA_HEADER_VALUES
+
+ edits = context_management.get("edits", [])
+ has_compact = False
+ has_other = False
+
+ for edit in edits:
+ edit_type = edit.get("type", "")
+ if edit_type == "compact_20260112":
+ has_compact = True
+ else:
+ has_other = True
+
+ # Add compact header if any compact edits exist
+ if has_compact:
+ beta_set.add(ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value)
+
+ # Add context management header if any other edits exist
+ if has_other:
+ beta_set.add(ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value)
+
def transform_request(
self,
model: str,
@@ -86,6 +120,11 @@ class VertexAIAnthropicConfig(AnthropicConfig):
beta_set = set(auto_betas)
if tool_search_used:
beta_set.add("tool-search-tool-2025-10-19") # Vertex requires this header for tool search
+
+ # Add context_management beta headers (compact and/or context-management)
+ context_management = optional_params.get("context_management")
+ if context_management:
+ self._add_context_management_beta_headers(beta_set, context_management)
if beta_set:
data["anthropic_beta"] = list(beta_set)
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index d3038d13a1e..5cad0db241f 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -963,6 +963,276 @@
"supports_vision": true,
"tool_use_system_prompt_tokens": 159
},
+ "anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "global.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "global.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "us.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "eu.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "eu.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "apac.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "apac.anthropic.claude-opus-4-6-v1": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
"anthropic.claude-sonnet-4-20250514-v1:0": {
"cache_creation_input_token_cost": 3.75e-06,
"cache_read_input_token_cost": 3e-07,
@@ -1444,6 +1714,33 @@
"supports_tool_choice": true,
"supports_vision": true
},
+ "azure_ai/claude-opus-4-6": {
+ "input_cost_per_token": 5e-06,
+ "output_cost_per_token": 2.5e-05,
+ "litellm_provider": "azure_ai",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_1hr": 1e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 159
+ },
"azure_ai/claude-opus-4-1": {
"cache_creation_input_token_cost": 1.875e-05,
"cache_creation_input_token_cost_above_1hr": 3e-05,
@@ -7455,6 +7752,130 @@
"supports_vision": true,
"tool_use_system_prompt_tokens": 159
},
+ "claude-opus-4-6": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_creation_input_token_cost_above_1hr": 1e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "anthropic",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "us/claude-opus-4-6": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_creation_input_token_cost_above_1hr": 1.1e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "anthropic",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "claude-opus-4-6-20260205": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_creation_input_token_cost_above_1hr": 1e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "anthropic",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
+ "us/claude-opus-4-6-20260205": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_creation_input_token_cost_above_1hr": 1.1e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "anthropic",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
"claude-sonnet-4-20250514": {
"deprecation_date": "2026-05-14",
"cache_creation_input_token_cost": 3.75e-06,
@@ -10575,6 +10996,32 @@
"/v1/audio/transcriptions"
]
},
+ "elevenlabs/eleven_v3": {
+ "input_cost_per_character": 0.00018,
+ "litellm_provider": "elevenlabs",
+ "metadata": {
+ "calculation": "$0.18/1000 characters (Scale plan pricing, 1 credit per character)",
+ "notes": "ElevenLabs Eleven v3 - most expressive TTS model with 70+ languages and audio tags support"
+ },
+ "mode": "audio_speech",
+ "source": "https://elevenlabs.io/pricing",
+ "supported_endpoints": [
+ "/v1/audio/speech"
+ ]
+ },
+ "elevenlabs/eleven_multilingual_v2": {
+ "input_cost_per_character": 0.00018,
+ "litellm_provider": "elevenlabs",
+ "metadata": {
+ "calculation": "$0.18/1000 characters (Scale plan pricing, 1 credit per character)",
+ "notes": "ElevenLabs Eleven Multilingual v2 - default TTS model with 29 languages support"
+ },
+ "mode": "audio_speech",
+ "source": "https://elevenlabs.io/pricing",
+ "supported_endpoints": [
+ "/v1/audio/speech"
+ ]
+ },
"embed-english-light-v2.0": {
"input_cost_per_token": 1e-07,
"litellm_provider": "cohere",
@@ -29291,6 +29738,36 @@
"tool_use_system_prompt_tokens": 159,
"supports_native_streaming": true
},
+ "vertex_ai/claude-opus-4-6": {
+ "cache_creation_input_token_cost": 6.25e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.25e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1e-06,
+ "input_cost_per_token": 5e-06,
+ "input_cost_per_token_above_200k_tokens": 1e-05,
+ "litellm_provider": "vertex_ai-anthropic_models",
+ "max_input_tokens": 1000000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-05,
+ "output_cost_per_token_above_200k_tokens": 3.75e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
"vertex_ai/claude-sonnet-4-5": {
"cache_creation_input_token_cost": 3.75e-06,
"cache_read_input_token_cost": 3e-07,
diff --git a/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py b/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
index 081d83dd1c8..75b75d3ba44 100644
--- a/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
+++ b/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
@@ -27,6 +27,7 @@ class MCPAuthenticatedUser(AuthenticatedUser):
oauth2_headers: Optional[Dict[str, str]] = None,
mcp_protocol_version: Optional[str] = None,
raw_headers: Optional[Dict[str, str]] = None,
+ client_ip: Optional[str] = None,
):
self.user_api_key_auth = user_api_key_auth
self.mcp_auth_header = mcp_auth_header
@@ -35,3 +36,4 @@ class MCPAuthenticatedUser(AuthenticatedUser):
self.mcp_protocol_version = mcp_protocol_version
self.oauth2_headers = oauth2_headers
self.raw_headers = raw_headers
+ self.client_ip = client_ip
diff --git a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
index 7e70b5baae4..786cfbfb008 100644
--- a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
+++ b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
@@ -1,11 +1,12 @@
from typing import Dict, List, Optional, Set, Tuple
+from fastapi import HTTPException
from starlette.datastructures import Headers
from starlette.requests import Request
from starlette.types import Scope
from litellm._logging import verbose_logger
-from litellm.proxy._types import LiteLLM_TeamTable, SpecialHeaders, UserAPIKeyAuth
+from litellm.proxy._types import LiteLLM_TeamTable, ProxyException, SpecialHeaders, UserAPIKeyAuth
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
@@ -63,6 +64,13 @@ class MCPRequestHandler:
HTTPException: If headers are invalid or missing required headers
"""
headers = MCPRequestHandler._safe_get_headers_from_scope(scope)
+
+ # Check if there is an explicit LiteLLM API key (primary header)
+ has_explicit_litellm_key = (
+ headers.get(MCPRequestHandler.LITELLM_API_KEY_HEADER_NAME_PRIMARY)
+ is not None
+ )
+
litellm_api_key = (
MCPRequestHandler.get_litellm_api_key_from_headers(headers) or ""
)
@@ -106,16 +114,38 @@ class MCPRequestHandler:
request.body = mock_body # type: ignore
if ".well-known" in str(request.url): # public routes
validated_user_api_key_auth = UserAPIKeyAuth()
- # elif litellm_api_key == "":
- # from fastapi import HTTPException
-
- # raise HTTPException(
- # status_code=401,
- # detail="LiteLLM API key is missing. Please add it or use OAuth authentication.",
- # headers={
- # "WWW-Authenticate": f'Bearer resource_metadata=f"{request.base_url}/.well-known/oauth-protected-resource"',
- # },
- # )
+ elif has_explicit_litellm_key:
+ # Explicit x-litellm-api-key provided - always validate normally
+ validated_user_api_key_auth = await user_api_key_auth(
+ api_key=litellm_api_key, request=request
+ )
+ elif oauth2_headers:
+ # No x-litellm-api-key, but Authorization header present.
+ # Could be a LiteLLM key (backward compat) OR an OAuth2 token
+ # from an upstream MCP provider (e.g. Atlassian).
+ # Try LiteLLM auth first; on auth failure, treat as OAuth2 passthrough.
+ try:
+ validated_user_api_key_auth = await user_api_key_auth(
+ api_key=litellm_api_key, request=request
+ )
+ except HTTPException as e:
+ if e.status_code in (401, 403):
+ verbose_logger.debug(
+ "MCP OAuth2: Authorization header is not a valid LiteLLM key, "
+ "treating as OAuth2 token passthrough"
+ )
+ validated_user_api_key_auth = UserAPIKeyAuth()
+ else:
+ raise
+ except ProxyException as e:
+ if str(e.code) in ("401", "403"):
+ verbose_logger.debug(
+ "MCP OAuth2: Authorization header is not a valid LiteLLM key, "
+ "treating as OAuth2 token passthrough"
+ )
+ validated_user_api_key_auth = UserAPIKeyAuth()
+ else:
+ raise
else:
validated_user_api_key_auth = await user_api_key_auth(
api_key=litellm_api_key, request=request
diff --git a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
index 56feff548ad..8b052dd0da1 100644
--- a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
@@ -9,13 +9,14 @@ from litellm.llms.custom_httpx.http_handler import (
get_async_httpx_client,
httpxSpecialProvider,
)
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.common_utils.encrypt_decrypt_utils import (
decrypt_value_helper,
encrypt_value_helper,
)
from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
-from litellm.types.mcp_server.mcp_server_manager import MCPServer
from litellm.proxy.utils import get_server_root_path
+from litellm.types.mcp_server.mcp_server_manager import MCPServer
router = APIRouter(
tags=["mcp"],
@@ -300,7 +301,10 @@ async def authorize(
)
lookup_name = mcp_server_name or client_id
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(lookup_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ lookup_name, client_ip=client_ip
+ )
if mcp_server is None:
raise HTTPException(status_code=404, detail="MCP server not found")
return await authorize_with_server(
@@ -342,7 +346,10 @@ async def token_endpoint(
)
lookup_name = mcp_server_name or client_id
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(lookup_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ lookup_name, client_ip=client_ip
+ )
if mcp_server is None:
raise HTTPException(status_code=404, detail="MCP server not found")
return await exchange_token_with_server(
@@ -425,7 +432,10 @@ def _build_oauth_protected_resource_response(
request_base_url = get_request_base_url(request)
mcp_server: Optional[MCPServer] = None
if mcp_server_name:
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
# Build resource URL based on the pattern
if mcp_server_name:
@@ -538,7 +548,10 @@ def _build_oauth_authorization_server_response(
mcp_server: Optional[MCPServer] = None
if mcp_server_name:
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
return {
"issuer": request_base_url, # point to your proxy
@@ -629,7 +642,10 @@ async def register_client(request: Request, mcp_server_name: Optional[str] = Non
if not mcp_server_name:
return dummy_return
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
if mcp_server is None:
return dummy_return
return await register_client_with_server(
diff --git a/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py b/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
index 4d53ae7059d..14bbb82808d 100644
--- a/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
+++ b/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
@@ -1,26 +1,37 @@
"""
MCP Guardrail Handler for Unified Guardrails.
-This handler works with the synthetic "messages" payload generated by
-`ProxyLogging._convert_mcp_to_llm_format`, which always produces a single user
-message whose `content` string encodes the MCP tool name and arguments. The
-handler simply feeds that text through the configured guardrail and writes the
-result back onto the message.
+Converts an MCP call_tool (name + arguments) into a single OpenAI-compatible
+tool_call and passes it to apply_guardrail. Works with the synthetic payload
+from ProxyLogging._convert_mcp_to_llm_format.
+
+Note: For MCP tool definitions (schema) -> OpenAI tools=[], see
+litellm.experimental_mcp_client.tools.transform_mcp_tool_to_openai_tool
+when you have a full MCP Tool from list_tools. Here we only have the call
+payload (name + arguments) so we just build the tool_call.
"""
from typing import TYPE_CHECKING, Any, Dict, Optional
+from mcp.types import Tool as MCPTool
+
from litellm._logging import verbose_proxy_logger
+from litellm.experimental_mcp_client.tools import transform_mcp_tool_to_openai_tool
from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.types.llms.openai import (
+ ChatCompletionToolParam,
+ ChatCompletionToolParamFunctionChunk,
+)
from litellm.types.utils import GenericGuardrailAPIInputs
if TYPE_CHECKING:
- from litellm.integrations.custom_guardrail import CustomGuardrail
from mcp.types import CallToolResult
+ from litellm.integrations.custom_guardrail import CustomGuardrail
+
class MCPGuardrailTranslationHandler(BaseTranslation):
- """Guardrail translation handler for MCP tool calls."""
+ """Guardrail translation handler for MCP tool calls (passes a single tool_call to guardrail)."""
async def process_input_messages(
self,
@@ -28,56 +39,51 @@ class MCPGuardrailTranslationHandler(BaseTranslation):
guardrail_to_apply: "CustomGuardrail",
litellm_logging_obj: Optional[Any] = None,
) -> Dict[str, Any]:
- messages = data.get("messages")
- if not isinstance(messages, list) or not messages:
- verbose_proxy_logger.debug("MCP Guardrail: No messages to process")
+ mcp_tool_name = data.get("mcp_tool_name") or data.get("name")
+ mcp_arguments = data.get("mcp_arguments") or data.get("arguments")
+ mcp_tool_description = data.get("mcp_tool_description") or data.get(
+ "description"
+ )
+ if mcp_arguments is None or not isinstance(mcp_arguments, dict):
+ mcp_arguments = {}
+
+ if not mcp_tool_name:
+ verbose_proxy_logger.debug("MCP Guardrail: mcp_tool_name missing")
return data
- first_message = messages[0]
- content: Optional[str] = None
- if isinstance(first_message, dict):
- content = first_message.get("content")
- else:
- content = getattr(first_message, "content", None)
+ # Convert MCP input via transform_mcp_tool_to_openai_tool, then map to litellm
+ # ChatCompletionToolParam (openai SDK type has incompatible strict/cache_control).
+ mcp_tool = MCPTool(
+ name=mcp_tool_name,
+ description=mcp_tool_description or "",
+ inputSchema={}, # Call payload has no schema; guardrail gets args from request_data
+ )
+ openai_tool = transform_mcp_tool_to_openai_tool(mcp_tool)
+ fn = openai_tool["function"]
+ tool_def: ChatCompletionToolParam = {
+ "type": "function",
+ "function": ChatCompletionToolParamFunctionChunk(
+ name=fn["name"],
+ description=fn.get("description") or "",
+ parameters=fn.get("parameters")
+ or {
+ "type": "object",
+ "properties": {},
+ "additionalProperties": False,
+ },
+ strict=fn.get("strict", False) or False, # Default to False if None
+ ),
+ }
+ inputs: GenericGuardrailAPIInputs = GenericGuardrailAPIInputs(
+ tools=[tool_def],
+ )
- if not isinstance(content, str):
- verbose_proxy_logger.debug(
- "MCP Guardrail: Message content missing or not a string",
- )
- return data
-
- inputs = GenericGuardrailAPIInputs(texts=[content])
- # Include model information if available
- model = data.get("model")
- if model:
- inputs["model"] = model
- guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ await guardrail_to_apply.apply_guardrail(
inputs=inputs,
request_data=data,
input_type="request",
logging_obj=litellm_logging_obj,
)
- guardrailed_texts = (
- guardrailed_inputs.get("texts", []) if guardrailed_inputs else []
- )
-
- if guardrailed_texts:
- new_content = guardrailed_texts[0]
- if isinstance(first_message, dict):
- first_message["content"] = new_content
- else:
- setattr(first_message, "content", new_content)
-
- verbose_proxy_logger.debug(
- "MCP Guardrail: Updated content for tool %s",
- data.get("mcp_tool_name"),
- )
- else:
- verbose_proxy_logger.debug(
- "MCP Guardrail: Guardrail returned no text updates for tool %s",
- data.get("mcp_tool_name"),
- )
-
return data
async def process_output_response(
@@ -87,7 +93,6 @@ class MCPGuardrailTranslationHandler(BaseTranslation):
litellm_logging_obj: Optional[Any] = None,
user_api_key_dict: Optional[Any] = None,
) -> Any:
- # Not implemented: MCP guardrail translation never calls this path today.
verbose_proxy_logger.debug(
"MCP Guardrail: Output processing not implemented for MCP tools",
)
diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
index 4c17a2ff3e0..e7174f943b2 100644
--- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
+++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
@@ -53,6 +53,7 @@ from litellm.proxy._types import (
MCPTransportType,
UserAPIKeyAuth,
)
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper
from litellm.proxy.utils import ProxyLogging
from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -65,20 +66,23 @@ from litellm.types.mcp_server.mcp_server_manager import (
from litellm.types.utils import CallTypes
try:
- from mcp.shared.tool_name_validation import ( # type: ignore
+ from mcp.shared.tool_name_validation import (
+ validate_tool_name, # pyright: ignore[reportAssignmentType]
+ )
+ from mcp.shared.tool_name_validation import (
SEP_986_URL,
- validate_tool_name,
)
except ImportError:
from pydantic import BaseModel
+
SEP_986_URL = "https://github.com/modelcontextprotocol/protocol/blob/main/proposals/0001-tool-name-validation.md"
- class ToolNameValidationResult(BaseModel):
+ class _ToolNameValidationResult(BaseModel):
is_valid: bool = True
warnings: list = []
- def validate_tool_name(name: str) -> ToolNameValidationResult: # type: ignore[misc]
- return ToolNameValidationResult()
+ def validate_tool_name(name: str) -> _ToolNameValidationResult: # type: ignore[misc]
+ return _ToolNameValidationResult()
# Probe includes characters on both sides of the separator to mimic real prefixed tool names.
@@ -324,6 +328,9 @@ class MCPServerManager:
access_groups=server_config.get("access_groups", None),
static_headers=server_config.get("static_headers", None),
allow_all_keys=bool(server_config.get("allow_all_keys", False)),
+ available_on_public_internet=bool(
+ server_config.get("available_on_public_internet", False)
+ ),
)
self.config_mcp_servers[server_id] = new_server
@@ -469,12 +476,12 @@ class MCPServerManager:
)
# Update tool name to server name mapping (for both prefixed and base names)
- self.tool_name_to_mcp_server_name_mapping[
- base_tool_name
- ] = server_prefix
- self.tool_name_to_mcp_server_name_mapping[
- prefixed_tool_name
- ] = server_prefix
+ self.tool_name_to_mcp_server_name_mapping[base_tool_name] = (
+ server_prefix
+ )
+ self.tool_name_to_mcp_server_name_mapping[prefixed_tool_name] = (
+ server_prefix
+ )
registered_count += 1
verbose_logger.debug(
@@ -622,6 +629,9 @@ class MCPServerManager:
allowed_tools=getattr(mcp_server, "allowed_tools", None),
disallowed_tools=getattr(mcp_server, "disallowed_tools", None),
allow_all_keys=mcp_server.allow_all_keys,
+ available_on_public_internet=bool(
+ getattr(mcp_server, "available_on_public_internet", False)
+ ),
updated_at=getattr(mcp_server, "updated_at", None),
)
return new_server
@@ -696,6 +706,23 @@ class MCPServerManager:
verbose_logger.warning(f"Failed to get allowed MCP servers: {str(e)}.")
return allow_all_server_ids
+ def filter_server_ids_by_ip(
+ self, server_ids: List[str], client_ip: Optional[str]
+ ) -> List[str]:
+ """
+ Filter server IDs by client IP — external callers only see public servers.
+
+ Returns server_ids unchanged when client_ip is None (no filtering).
+ """
+ if client_ip is None:
+ return server_ids
+ return [
+ sid
+ for sid in server_ids
+ if (s := self.get_mcp_server_by_id(sid)) is not None
+ and self._is_server_accessible_from_ip(s, client_ip)
+ ]
+
async def get_tools_for_server(self, server_id: str) -> List[MCPTool]:
"""
Get the tools for a given server
@@ -1929,7 +1956,9 @@ class MCPServerManager:
)
async def _call_tool_via_client(client, params):
- return await client.call_tool(params, host_progress_callback=host_progress_callback)
+ return await client.call_tool(
+ params, host_progress_callback=host_progress_callback
+ )
tasks.append(
asyncio.create_task(_call_tool_via_client(client, call_tool_params))
@@ -1967,7 +1996,6 @@ class MCPServerManager:
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
host_progress_callback: Optional[Callable] = None,
-
) -> CallToolResult:
"""
Call a tool with the given name and arguments
@@ -2200,6 +2228,42 @@ class MCPServerManager:
servers.append(server)
return servers
+ def _get_general_settings(self) -> Dict[str, Any]:
+ """Get general_settings, importing lazily to avoid circular imports."""
+ try:
+ from litellm.proxy.proxy_server import (
+ general_settings as proxy_general_settings,
+ )
+ return proxy_general_settings
+ except ImportError:
+ # Fallback if proxy_server not available
+ return {}
+
+ def _is_server_accessible_from_ip(
+ self, server: MCPServer, client_ip: Optional[str]
+ ) -> bool:
+ """
+ Check if a server is accessible from the given client IP.
+
+ - If client_ip is None, no IP filtering is applied (internal callers).
+ - If the server has available_on_public_internet=True, it's always accessible.
+ - Otherwise, only internal/private IPs can access it.
+ """
+ if client_ip is None:
+ return True
+ if server.available_on_public_internet:
+ return True
+ # Check backwards compat: litellm.public_mcp_servers
+ public_ids = set(litellm.public_mcp_servers or [])
+ if server.server_id in public_ids:
+ return True
+ # Non-public server: only accessible from internal IPs
+ general_settings = self._get_general_settings()
+ internal_networks = IPAddressUtils.parse_internal_networks(
+ general_settings.get("mcp_internal_ip_ranges")
+ )
+ return IPAddressUtils.is_internal_ip(client_ip, internal_networks)
+
def get_mcp_server_by_id(self, server_id: str) -> Optional[MCPServer]:
"""
Get the MCP Server from the server id
@@ -2212,27 +2276,72 @@ class MCPServerManager:
def get_public_mcp_servers(self) -> List[MCPServer]:
"""
- Get the public MCP servers
+ Get the public MCP servers (available_on_public_internet=True flag on server).
+ Also includes servers from litellm.public_mcp_servers for backwards compat.
"""
servers: List[MCPServer] = []
- if litellm.public_mcp_servers is None:
- return servers
- for server_id in litellm.public_mcp_servers:
- server = self.get_mcp_server_by_id(server_id)
- if server:
+ public_ids = set(litellm.public_mcp_servers or [])
+ for server in self.get_registry().values():
+ if server.available_on_public_internet or server.server_id in public_ids:
servers.append(server)
return servers
- def get_mcp_server_by_name(self, server_name: str) -> Optional[MCPServer]:
+ def get_mcp_server_by_name(
+ self, server_name: str, client_ip: Optional[str] = None
+ ) -> Optional[MCPServer]:
"""
- Get the MCP Server from the server name
+ Get the MCP Server from the server name.
+
+ Uses priority-based matching to avoid collisions:
+ 1. First pass: exact alias match (highest priority)
+ 2. Second pass: exact server_name match
+ 3. Third pass: exact name match (lowest priority)
+
+ Args:
+ server_name: The server name to look up.
+ client_ip: Optional client IP for access control. When provided,
+ non-public servers are hidden from external IPs.
"""
registry = self.get_registry()
+ # Pass 1: Match by alias (highest priority)
+ for server in registry.values():
+ if server.alias == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
+ return server
+ # Pass 2: Match by server_name
for server in registry.values():
if server.server_name == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
+ return server
+ # Pass 3: Match by name (lowest priority)
+ for server in registry.values():
+ if server.name == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
return server
return None
+ def get_filtered_registry(
+ self, client_ip: Optional[str] = None
+ ) -> Dict[str, MCPServer]:
+ """
+ Get registry filtered by client IP access control.
+
+ Args:
+ client_ip: Optional client IP. When provided, non-public servers
+ are hidden from external IPs. When None, returns all servers.
+ """
+ registry = self.get_registry()
+ if client_ip is None:
+ return registry
+ return {
+ k: v
+ for k, v in registry.items()
+ if self._is_server_accessible_from_ip(v, client_ip)
+ }
+
def _generate_stable_server_id(
self,
server_name: str,
@@ -2462,6 +2571,7 @@ class MCPServerManager:
token_url=server.token_url,
registration_url=server.registration_url,
allow_all_keys=server.allow_all_keys,
+ available_on_public_internet=server.available_on_public_internet,
)
async def get_all_mcp_servers_unfiltered(self) -> List[LiteLLM_MCPServerTable]:
diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index d93f852f22d..2fe40bb197e 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -10,8 +10,10 @@ from litellm.proxy._experimental.mcp_server.ui_session_utils import (
)
from litellm.proxy._experimental.mcp_server.utils import merge_mcp_headers
from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
from litellm.types.mcp import MCPAuth
+from litellm.types.utils import CallTypes
MCP_AVAILABLE: bool = True
try:
@@ -28,6 +30,7 @@ router = APIRouter(
if MCP_AVAILABLE:
from mcp.types import Tool as MCPTool
+
from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
global_mcp_server_manager,
)
@@ -76,6 +79,82 @@ if MCP_AVAILABLE:
for tool in tools
]
+ def _extract_mcp_headers_from_request(
+ request: Request,
+ mcp_request_handler_cls,
+ ) -> tuple:
+ """
+ Extract MCP auth headers from HTTP request.
+
+ Returns:
+ Tuple of (mcp_auth_header, mcp_server_auth_headers, raw_headers)
+ """
+ headers = request.headers
+ raw_headers = dict(headers)
+ mcp_auth_header = mcp_request_handler_cls._get_mcp_auth_header_from_headers(
+ headers
+ )
+ mcp_server_auth_headers = (
+ mcp_request_handler_cls._get_mcp_server_auth_headers_from_headers(headers)
+ )
+ return mcp_auth_header, mcp_server_auth_headers, raw_headers
+
+ async def _resolve_allowed_mcp_servers_with_ip_filter(
+ request: Request,
+ user_api_key_dict: UserAPIKeyAuth,
+ server_id: str,
+ ) -> List[MCPServer]:
+ """
+ Resolve allowed MCP servers for a tool call with IP filtering.
+
+ Args:
+ request: The HTTP request object
+ user_api_key_dict: The user's API key auth object
+ server_id: The server ID to validate access for
+
+ Returns:
+ List of allowed MCPServer objects
+
+ Raises:
+ HTTPException: If the server_id is not allowed
+ """
+ # Get all auth contexts
+ auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
+
+ # Collect allowed server IDs from all contexts, then apply IP filtering
+ _rest_client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ allowed_server_ids_set = set()
+ for auth_context in auth_contexts:
+ servers = await global_mcp_server_manager.get_allowed_mcp_servers(
+ user_api_key_auth=auth_context,
+ )
+ allowed_server_ids_set.update(servers)
+
+ allowed_server_ids_set = set(
+ global_mcp_server_manager.filter_server_ids_by_ip(
+ list(allowed_server_ids_set), _rest_client_ip
+ )
+ )
+
+ # Check if the specified server_id is allowed
+ if server_id not in allowed_server_ids_set:
+ raise HTTPException(
+ status_code=403,
+ detail={
+ "error": "access_denied",
+ "message": f"The key is not allowed to access server {server_id}",
+ },
+ )
+
+ # Build allowed_mcp_servers list (only include allowed servers)
+ allowed_mcp_servers: List[MCPServer] = []
+ for allowed_server_id in allowed_server_ids_set:
+ server = global_mcp_server_manager.get_mcp_server_by_id(allowed_server_id)
+ if server is not None:
+ allowed_mcp_servers.append(server)
+
+ return allowed_mcp_servers
+
async def _get_tools_for_single_server(
server,
server_auth_header,
@@ -96,6 +175,35 @@ if MCP_AVAILABLE:
return _create_tool_response_objects(tools, server.mcp_info)
+ async def _resolve_allowed_mcp_servers_for_tool_call(
+ user_api_key_dict: UserAPIKeyAuth,
+ server_id: str,
+ ) -> List[MCPServer]:
+ """Resolve allowed MCP servers for the given user and validate server_id access."""
+ auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
+ allowed_server_ids_set = set()
+ for auth_context in auth_contexts:
+ servers = await global_mcp_server_manager.get_allowed_mcp_servers(
+ user_api_key_auth=auth_context
+ )
+ allowed_server_ids_set.update(servers)
+ if server_id not in allowed_server_ids_set:
+ raise HTTPException(
+ status_code=403,
+ detail={
+ "error": "access_denied",
+ "message": f"The key is not allowed to access server {server_id}",
+ },
+ )
+ allowed_mcp_servers: List[MCPServer] = []
+ for allowed_server_id in allowed_server_ids_set:
+ server = global_mcp_server_manager.get_mcp_server_by_id(
+ allowed_server_id
+ )
+ if server is not None:
+ allowed_mcp_servers.append(server)
+ return allowed_mcp_servers
+
########################################################
@router.get("/tools/list", dependencies=[Depends(user_api_key_auth)])
async def list_tool_rest_api(
@@ -142,21 +250,25 @@ if MCP_AVAILABLE:
auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
+ _rest_client_ip = IPAddressUtils.get_mcp_client_ip(request)
+
allowed_server_ids_set = set()
for auth_context in auth_contexts:
servers = await global_mcp_server_manager.get_allowed_mcp_servers(
- user_api_key_auth=auth_context
+ user_api_key_auth=auth_context,
)
allowed_server_ids_set.update(servers)
- allowed_server_ids = list(allowed_server_ids_set)
+ allowed_server_ids = global_mcp_server_manager.filter_server_ids_by_ip(
+ list(allowed_server_ids_set), _rest_client_ip
+ )
list_tools_result = []
error_message = None
# If server_id is specified, only query that specific server
if server_id:
- if server_id not in allowed_server_ids_set:
+ if server_id not in allowed_server_ids:
raise HTTPException(
status_code=403,
detail={
@@ -164,7 +276,9 @@ if MCP_AVAILABLE:
"message": f"The key is not allowed to access server {server_id}",
},
)
- server = global_mcp_server_manager.get_mcp_server_by_id(server_id)
+ server = global_mcp_server_manager.get_mcp_server_by_id(
+ server_id
+ )
if server is None:
return {
"tools": [],
@@ -261,7 +375,14 @@ if MCP_AVAILABLE:
from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import (
MCPRequestHandler,
)
- from litellm.proxy.proxy_server import add_litellm_data_to_request, proxy_config
+ from litellm.proxy.common_request_processing import (
+ ProxyBaseLLMRequestProcessing,
+ )
+ from litellm.proxy.proxy_server import (
+ general_settings,
+ proxy_config,
+ proxy_logging_obj,
+ )
try:
data = await request.json()
@@ -289,28 +410,22 @@ if MCP_AVAILABLE:
tool_arguments = data.get("arguments")
- data = await add_litellm_data_to_request(
- data=data,
- request=request,
- user_api_key_dict=user_api_key_dict,
- proxy_config=proxy_config,
+ proxy_base_llm_response_processor = ProxyBaseLLMRequestProcessing(data=data)
+ data, logging_obj = (
+ await proxy_base_llm_response_processor.common_processing_pre_call_logic(
+ request=request,
+ user_api_key_dict=user_api_key_dict,
+ proxy_config=proxy_config,
+ route_type=CallTypes.call_mcp_tool.value,
+ proxy_logging_obj=proxy_logging_obj,
+ general_settings=general_settings,
+ )
)
- # FIX: Extract MCP auth headers from request
- # The UI sends bearer token in x-mcp-auth header and server-specific headers,
- # but they weren't being extracted and passed to call_mcp_tool.
- # This fix ensures auth headers are properly extracted from the HTTP request
- # and passed through to the MCP server for authentication.
- headers = request.headers
- raw_headers_from_request = dict(headers)
- mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(
- headers
+ # Extract MCP auth headers from request and add to data dict
+ mcp_auth_header, mcp_server_auth_headers, raw_headers_from_request = (
+ _extract_mcp_headers_from_request(request, MCPRequestHandler)
)
- mcp_server_auth_headers = (
- MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers)
- )
-
- # Add extracted headers to data dict to pass to call_mcp_tool
if mcp_auth_header:
data["mcp_auth_header"] = mcp_auth_header
if mcp_server_auth_headers:
@@ -322,35 +437,10 @@ if MCP_AVAILABLE:
if "metadata" in data and "user_api_key_auth" in data["metadata"]:
data["user_api_key_auth"] = data["metadata"]["user_api_key_auth"]
- # Get all auth contexts
- auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
-
- # Collect allowed server IDs from all contexts
- allowed_server_ids_set = set()
- for auth_context in auth_contexts:
- servers = await global_mcp_server_manager.get_allowed_mcp_servers(
- user_api_key_auth=auth_context
- )
- allowed_server_ids_set.update(servers)
-
- # Check if the specified server_id is allowed
- if server_id not in allowed_server_ids_set:
- raise HTTPException(
- status_code=403,
- detail={
- "error": "access_denied",
- "message": f"The key is not allowed to access server {server_id}",
- },
- )
-
- # Build allowed_mcp_servers list (only include allowed servers)
- allowed_mcp_servers: List[MCPServer] = []
- for allowed_server_id in allowed_server_ids_set:
- server = global_mcp_server_manager.get_mcp_server_by_id(
- allowed_server_id
- )
- if server is not None:
- allowed_mcp_servers.append(server)
+ # Resolve allowed MCP servers with IP filtering
+ allowed_mcp_servers = await _resolve_allowed_mcp_servers_with_ip_filter(
+ request, user_api_key_dict, server_id
+ )
# Call execute_mcp_tool directly (permission checks already done)
result = await execute_mcp_tool(
diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py
index 79cd88227a9..890c4ae8fb2 100644
--- a/litellm/proxy/_experimental/mcp_server/server.py
+++ b/litellm/proxy/_experimental/mcp_server/server.py
@@ -5,12 +5,24 @@ LiteLLM MCP Server Routes
import asyncio
import contextlib
-from datetime import datetime
import traceback
import uuid
-from typing import Any, AsyncIterator, Dict, List, Optional, Tuple, Union, cast, Callable
+from datetime import datetime
+from typing import (
+ Any,
+ AsyncIterator,
+ Callable,
+ Dict,
+ List,
+ Optional,
+ Tuple,
+ Union,
+ cast,
+)
+
from fastapi import FastAPI, HTTPException
from pydantic import AnyUrl, ConfigDict
+from starlette.requests import Request as StarletteRequest
from starlette.types import Receive, Scope, Send
from litellm._logging import verbose_logger
@@ -25,6 +37,7 @@ from litellm.proxy._experimental.mcp_server.utils import (
LITELLM_MCP_SERVER_VERSION,
)
from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.types.mcp import MCPAuth
from litellm.types.mcp_server.mcp_server_manager import MCPInfo, MCPServer
from litellm.types.utils import CallTypes, StandardLoggingMCPToolCall
@@ -213,6 +226,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_tools - User API Key Auth from context: {user_api_key_auth}"
@@ -276,6 +290,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
@@ -288,7 +303,7 @@ if MCP_AVAILABLE:
host_token = getattr(host_ctx.meta, 'progressToken', None)
if host_token and hasattr(host_ctx, 'session') and host_ctx.session:
host_session = host_ctx.session
-
+
async def forward_progress(progress: float, total: float | None):
"""Forward progress notifications from external MCP to Host"""
try:
@@ -300,7 +315,7 @@ if MCP_AVAILABLE:
verbose_logger.debug(f"Forwarded progress {progress}/{total} to Host")
except Exception as e:
verbose_logger.error(f"Failed to forward progress to Host: {e}")
-
+
host_progress_callback = forward_progress
verbose_logger.debug(f"Host progressToken captured: {host_token[:8]}...")
except Exception as e:
@@ -387,6 +402,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_prompts - User API Key Auth from context: {user_api_key_auth}"
@@ -440,6 +456,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
@@ -467,6 +484,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_resources - User API Key Auth from context: {user_api_key_auth}"
@@ -505,6 +523,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_resource_templates - User API Key Auth from context: {user_api_key_auth}"
@@ -544,6 +563,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
read_resource_result = await mcp_read_resource(
@@ -702,13 +722,57 @@ if MCP_AVAILABLE:
return tools_to_return
+ def _get_client_ip_from_context() -> Optional[str]:
+ """
+ Extract client_ip from auth context.
+ Returns None if context not set (caller should handle this as "no IP filtering").
+ """
+ try:
+ auth_user = auth_context_var.get()
+ if auth_user and isinstance(auth_user, MCPAuthenticatedUser):
+ return auth_user.client_ip
+ except Exception:
+ pass
+ return None
+
async def _get_allowed_mcp_servers(
user_api_key_auth: Optional[UserAPIKeyAuth],
mcp_servers: Optional[List[str]],
+ client_ip: Optional[str] = None,
) -> List[MCPServer]:
- """Return allowed MCP servers for a request after applying filters."""
+ """Return allowed MCP servers for a request after applying filters.
+
+ Args:
+ user_api_key_auth: The authenticated user's API key info.
+ mcp_servers: Optional list of server names to filter to.
+ client_ip: Client IP for IP-based access control. If None, falls back to
+ auth context. Pass explicitly from request handlers for safety.
+ Note: If client_ip is None and auth context is not set, IP filtering is skipped.
+ This is intentional for internal callers but may indicate a bug if called
+ from a request handler without proper context setup.
+ """
+ # Use explicit client_ip if provided, otherwise try auth context
+ if client_ip is None:
+ client_ip = _get_client_ip_from_context()
+ if client_ip is None:
+ verbose_logger.debug(
+ "MCP _get_allowed_mcp_servers called without client_ip and no auth context. "
+ "IP filtering will be skipped. This is expected for internal calls."
+ )
+
allowed_mcp_server_ids = (
- await global_mcp_server_manager.get_allowed_mcp_servers(user_api_key_auth)
+ await global_mcp_server_manager.get_allowed_mcp_servers(
+ user_api_key_auth
+ )
+ )
+ allowed_mcp_server_ids = (
+ global_mcp_server_manager.filter_server_ids_by_ip(
+ allowed_mcp_server_ids, client_ip
+ )
+ )
+ verbose_logger.debug(
+ "MCP IP filter: client_ip=%s, allowed_server_ids=%s",
+ client_ip, allowed_mcp_server_ids,
)
allowed_mcp_servers: List[MCPServer] = []
for allowed_mcp_server_id in allowed_mcp_server_ids:
@@ -1715,7 +1779,7 @@ if MCP_AVAILABLE:
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
litellm_logging_obj: Optional[Any] = None,
- host_progress_callback: Optional[Callable] = None,
+ host_progress_callback: Optional[Callable] = None,
) -> CallToolResult:
"""Handle tool execution for managed server tools"""
# Import here to avoid circular import
@@ -1891,6 +1955,10 @@ if MCP_AVAILABLE:
oauth2_headers,
raw_headers,
) = await extract_mcp_auth_context(scope, path)
+
+ # Extract client IP for MCP access control
+ _client_ip = IPAddressUtils.get_mcp_client_ip(StarletteRequest(scope))
+
verbose_logger.debug(
f"MCP request mcp_servers (header/path): {mcp_servers}"
)
@@ -1899,11 +1967,11 @@ if MCP_AVAILABLE:
)
# https://datatracker.ietf.org/doc/html/rfc9728#name-www-authenticate-response
for server_name in mcp_servers or []:
- server = global_mcp_server_manager.get_mcp_server_by_name(server_name)
+ server = global_mcp_server_manager.get_mcp_server_by_name(
+ server_name, client_ip=_client_ip
+ )
if server and server.auth_type == MCPAuth.oauth2 and not oauth2_headers:
- from starlette.requests import Request
-
- request = Request(scope)
+ request = StarletteRequest(scope)
base_url = str(request.base_url).rstrip("/")
authorization_uri = (
@@ -1925,6 +1993,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=_client_ip,
)
# Ensure session managers are initialized
@@ -1936,12 +2005,13 @@ if MCP_AVAILABLE:
_strip_stale_mcp_session_header(scope, session_manager)
await session_manager.handle_request(scope, receive, send)
+ except HTTPException:
+ # Re-raise HTTP exceptions to preserve status codes and details
+ raise
except Exception as e:
- raise e
verbose_logger.exception(f"Error handling MCP request: {e}")
- # Instead of re-raising, try to send a graceful error response
+ # Try to send a graceful error response for non-HTTP exceptions
try:
- # Send a proper HTTP error response instead of letting the exception bubble up
from starlette.responses import JSONResponse
from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR
@@ -1969,6 +2039,10 @@ if MCP_AVAILABLE:
oauth2_headers,
raw_headers,
) = await extract_mcp_auth_context(scope, path)
+
+ # Extract client IP for MCP access control
+ _sse_client_ip = IPAddressUtils.get_mcp_client_ip(StarletteRequest(scope))
+
verbose_logger.debug(
f"MCP request mcp_servers (header/path): {mcp_servers}"
)
@@ -1982,6 +2056,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=_sse_client_ip,
)
if not _SESSION_MANAGERS_INITIALIZED:
@@ -2045,6 +2120,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
+ client_ip: Optional[str] = None,
) -> None:
"""
Set the UserAPIKeyAuth in the auth context variable.
@@ -2054,6 +2130,7 @@ if MCP_AVAILABLE:
mcp_auth_header: MCP auth header to be passed to the MCP server (deprecated)
mcp_servers: Optional list of server names and access groups to filter by
mcp_server_auth_headers: Optional dict of server-specific auth headers {server_alias: auth_value}
+ client_ip: Client IP address for MCP access control
"""
auth_user = MCPAuthenticatedUser(
user_api_key_auth=user_api_key_auth,
@@ -2062,6 +2139,7 @@ if MCP_AVAILABLE:
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=client_ip,
)
auth_context_var.set(auth_user)
@@ -2073,14 +2151,15 @@ if MCP_AVAILABLE:
Optional[Dict[str, Dict[str, str]]],
Optional[Dict[str, str]],
Optional[Dict[str, str]],
+ Optional[str],
]
):
"""
Get the UserAPIKeyAuth from the auth context variable.
Returns:
- Tuple[Optional[UserAPIKeyAuth], Optional[str], Optional[List[str]], Optional[Dict[str, str]]]:
- UserAPIKeyAuth object, MCP auth header (deprecated), MCP servers (can include access groups), and server-specific auth headers
+ Tuple containing: UserAPIKeyAuth, MCP auth header (deprecated),
+ MCP servers, server-specific auth headers, OAuth2 headers, raw headers, client IP
"""
auth_user = auth_context_var.get()
if auth_user and isinstance(auth_user, MCPAuthenticatedUser):
@@ -2091,8 +2170,9 @@ if MCP_AVAILABLE:
auth_user.mcp_server_auth_headers,
auth_user.oauth2_headers,
auth_user.raw_headers,
+ auth_user.client_ip,
)
- return None, None, None, None, None, None
+ return None, None, None, None, None, None, None
########################################################
############ End of Auth Context Functions #############
diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html
new file mode 100644
index 00000000000..63f46b9c025
--- /dev/null
+++ b/litellm/proxy/_experimental/out/404.html
@@ -0,0 +1 @@
+404: This page could not be found. LiteLLM Dashboard
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/404/index.html b/litellm/proxy/_experimental/out/404/index.html
deleted file mode 100644
index a8bd30680ab..00000000000
--- a/litellm/proxy/_experimental/out/404/index.html
+++ /dev/null
@@ -1 +0,0 @@
-404: This page could not be found. LiteLLM Dashboard
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/__next.__PAGE__.txt b/litellm/proxy/_experimental/out/__next.__PAGE__.txt
new file mode 100644
index 00000000000..797e7a44c06
--- /dev/null
+++ b/litellm/proxy/_experimental/out/__next.__PAGE__.txt
@@ -0,0 +1,30 @@
+1:"$Sreact.fragment"
+2:I[347257,["/litellm-asset-prefix/_next/static/chunks/d96012bcfc98706a.js","/litellm-asset-prefix/_next/static/chunks/dbca964212122d58.js"],"ClientPageRoot"]
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+ > ${t}-submenu > ${t}-submenu-title`]:{height:o,lineHeight:(0,O.unit)(o)},[`${t}-item-group-list ${t}-submenu-title,
+ ${t}-submenu-title`]:{paddingInlineEnd:c}}},M=e=>{let{componentCls:t,motionDurationSlow:o,motionDurationMid:n,motionEaseInOut:i,motionEaseOut:r,iconCls:l,iconSize:a,iconMarginInlineEnd:d}=e;return{[`${t}-item, ${t}-submenu-title`]:{position:"relative",display:"block",margin:0,whiteSpace:"nowrap",cursor:"pointer",transition:`border-color ${o},background ${o},padding calc(${o} + 0.1s) ${i}`,[`${t}-item-icon, ${l}`]:{minWidth:a,fontSize:a,transition:`font-size ${n} ${r},margin ${o} ${i},color ${o}`,"+ span":{marginInlineStart:d,opacity:1,transition:`opacity ${o} ${i},margin ${o},color ${o}`}},[`${t}-item-icon`]:Object.assign({},(0,k.resetIcon)()),[`&${t}-item-only-child`]:{[`> ${l}, > ${t}-item-icon`]:{marginInlineEnd:0}}},[`${t}-item-disabled, ${t}-submenu-disabled`]:{background:"none !important",cursor:"not-allowed","&::after":{borderColor:"transparent !important"},a:{color:"inherit !important",cursor:"not-allowed",pointerEvents:"none"},[`> ${t}-submenu-title`]:{color:"inherit !important",cursor:"not-allowed"}}}},A=e=>{let{componentCls:t,motionDurationSlow:o,motionEaseInOut:n,borderRadius:i,menuArrowSize:r,menuArrowOffset:l}=e;return{[`${t}-submenu`]:{"&-expand-icon, &-arrow":{position:"absolute",top:"50%",insetInlineEnd:e.margin,width:r,color:"currentcolor",transform:"translateY(-50%)",transition:`transform ${o} ${n}, opacity ${o}`},"&-arrow":{"&::before, &::after":{position:"absolute",width:e.calc(r).mul(.6).equal(),height:e.calc(r).mul(.15).equal(),backgroundColor:"currentcolor",borderRadius:i,transition:`background ${o} ${n},transform ${o} ${n},top ${o} ${n},color ${o} ${n}`,content:'""'},"&::before":{transform:`rotate(45deg) translateY(${(0,O.unit)(e.calc(l).mul(-1).equal())})`},"&::after":{transform:`rotate(-45deg) translateY(${(0,O.unit)(l)})`}}}}},D=e=>{var t,o,n;let{colorPrimary:i,colorError:r,colorTextDisabled:l,colorErrorBg:a,colorText:d,colorTextDescription:s,colorBgContainer:c,colorFillAlter:u,colorFillContent:m,lineWidth:p,lineWidthBold:g,controlItemBgActive:b,colorBgTextHover:$,controlHeightLG:f,lineHeight:v,colorBgElevated:h,marginXXS:y,padding:x,fontSize:C,controlHeightSM:I,fontSizeLG:S,colorTextLightSolid:w,colorErrorHover:O}=e,k=null!=(t=e.activeBarWidth)?t:0,E=null!=(o=e.activeBarBorderWidth)?o:p,z=null!=(n=e.itemMarginInline)?n:e.marginXXS,j=new B.FastColor(w).setA(.65).toRgbString();return{dropdownWidth:160,zIndexPopup:e.zIndexPopupBase+50,radiusItem:e.borderRadiusLG,itemBorderRadius:e.borderRadiusLG,radiusSubMenuItem:e.borderRadiusSM,subMenuItemBorderRadius:e.borderRadiusSM,colorItemText:d,itemColor:d,colorItemTextHover:d,itemHoverColor:d,colorItemTextHoverHorizontal:i,horizontalItemHoverColor:i,colorGroupTitle:s,groupTitleColor:s,colorItemTextSelected:i,itemSelectedColor:i,subMenuItemSelectedColor:i,colorItemTextSelectedHorizontal:i,horizontalItemSelectedColor:i,colorItemBg:c,itemBg:c,colorItemBgHover:$,itemHoverBg:$,colorItemBgActive:m,itemActiveBg:b,colorSubItemBg:u,subMenuItemBg:u,colorItemBgSelected:b,itemSelectedBg:b,colorItemBgSelectedHorizontal:"transparent",horizontalItemSelectedBg:"transparent",colorActiveBarWidth:0,activeBarWidth:k,colorActiveBarHeight:g,activeBarHeight:g,colorActiveBarBorderSize:p,activeBarBorderWidth:E,colorItemTextDisabled:l,itemDisabledColor:l,colorDangerItemText:r,dangerItemColor:r,colorDangerItemTextHover:r,dangerItemHoverColor:r,colorDangerItemTextSelected:r,dangerItemSelectedColor:r,colorDangerItemBgActive:a,dangerItemActiveBg:a,colorDangerItemBgSelected:a,dangerItemSelectedBg:a,itemMarginInline:z,horizontalItemBorderRadius:0,horizontalItemHoverBg:"transparent",itemHeight:f,groupTitleLineHeight:v,collapsedWidth:2*f,popupBg:h,itemMarginBlock:y,itemPaddingInline:x,horizontalLineHeight:`${1.15*f}px`,iconSize:C,iconMarginInlineEnd:I-C,collapsedIconSize:S,groupTitleFontSize:C,darkItemDisabledColor:new B.FastColor(w).setA(.25).toRgbString(),darkItemColor:j,darkDangerItemColor:r,darkItemBg:"#001529",darkPopupBg:"#001529",darkSubMenuItemBg:"#000c17",darkItemSelectedColor:w,darkItemSelectedBg:i,darkDangerItemSelectedBg:r,darkItemHoverBg:"transparent",darkGroupTitleColor:j,darkItemHoverColor:w,darkDangerItemHoverColor:O,darkDangerItemSelectedColor:w,darkDangerItemActiveBg:r,itemWidth:k?`calc(100% + ${E}px)`:`calc(100% - ${2*z}px)`}};var L=e.i(905054),L=L,W=e.i(465394),G=e.i(122767);let q=e=>{var o;let n,{popupClassName:i,icon:r,title:a,theme:s}=e,u=t.useContext(p),{prefixCls:m,inlineCollapsed:g,theme:b}=u,$=(0,W.useFullPath)();if(r){let e=t.isValidElement(a)&&"span"===a.type;n=t.createElement(t.Fragment,null,(0,c.cloneElement)(r,{className:(0,l.default)(t.isValidElement(r)?null==(o=r.props)?void 0:o.className:void 0,`${m}-item-icon`)}),e?a:t.createElement("span",{className:`${m}-title-content`},a))}else n=g&&!$.length&&a&&"string"==typeof a?t.createElement("div",{className:`${m}-inline-collapsed-noicon`},a.charAt(0)):t.createElement("span",{className:`${m}-title-content`},a);let f=t.useMemo(()=>Object.assign(Object.assign({},u),{firstLevel:!1}),[u]),[v]=(0,G.useZIndex)("Menu");return t.createElement(p.Provider,{value:f},t.createElement(L.default,Object.assign({},(0,d.default)(e,["icon"]),{title:n,popupClassName:(0,l.default)(m,i,`${m}-${s||b}`),popupStyle:Object.assign({zIndex:v},e.popupStyle)})))};var X=function(e,t){var o={};for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&0>t.indexOf(n)&&(o[n]=e[n]);if(null!=e&&"function"==typeof Object.getOwnPropertySymbols)for(var i=0,n=Object.getOwnPropertySymbols(e);it.indexOf(n[i])&&Object.prototype.propertyIsEnumerable.call(e,n[i])&&(o[n[i]]=e[n[i]]);return o};function F(e){return null===e||!1===e}let Y={item:y,submenu:q,divider:$},_=(0,t.forwardRef)((e,n)=>{var i;let g=t.useContext(S),b=g||{},{getPrefixCls:$,getPopupContainer:f,direction:v,menu:h}=t.useContext(u.ConfigContext),y=$(),{prefixCls:x,className:C,style:I,theme:w="light",expandIcon:B,_internalDisableMenuItemTitleTooltip:T,inlineCollapsed:L,siderCollapsed:W,rootClassName:G,mode:q,selectable:_,onClick:V,overflowedIndicatorPopupClassName:U}=e,Z=X(e,["prefixCls","className","style","theme","expandIcon","_internalDisableMenuItemTitleTooltip","inlineCollapsed","siderCollapsed","rootClassName","mode","selectable","onClick","overflowedIndicatorPopupClassName"]),K=(0,d.default)(Z,["collapsedWidth"]);null==(i=b.validator)||i.call(b,{mode:q});let Q=(0,a.default)((...e)=>{var t;null==V||V.apply(void 0,e),null==(t=b.onClick)||t.call(b)}),J=b.mode||q,ee=null!=_?_:b.selectable,et=null!=L?L:W,eo={horizontal:{motionName:`${y}-slide-up`},inline:(0,s.default)(y),other:{motionName:`${y}-zoom-big`}},en=$("menu",x||b.prefixCls),ei=(0,m.default)(en),[er,el,ea]=((e,t=e,o=!0)=>(0,H.genStyleHooks)("Menu",e=>{let{colorBgElevated:t,controlHeightLG:o,fontSize:n,darkItemColor:i,darkDangerItemColor:r,darkItemBg:l,darkSubMenuItemBg:a,darkItemSelectedColor:d,darkItemSelectedBg:s,darkDangerItemSelectedBg:c,darkItemHoverBg:u,darkGroupTitleColor:m,darkItemHoverColor:p,darkItemDisabledColor:g,darkDangerItemHoverColor:b,darkDangerItemSelectedColor:$,darkDangerItemActiveBg:f,popupBg:v,darkPopupBg:h}=e,y=e.calc(n).div(7).mul(5).equal(),x=(0,N.mergeToken)(e,{menuArrowSize:y,menuHorizontalHeight:e.calc(o).mul(1.15).equal(),menuArrowOffset:e.calc(y).mul(.25).equal(),menuSubMenuBg:t,calc:e.calc,popupBg:v}),C=(0,N.mergeToken)(x,{itemColor:i,itemHoverColor:p,groupTitleColor:m,itemSelectedColor:d,subMenuItemSelectedColor:d,itemBg:l,popupBg:h,subMenuItemBg:a,itemActiveBg:"transparent",itemSelectedBg:s,activeBarHeight:0,activeBarBorderWidth:0,itemHoverBg:u,itemDisabledColor:g,dangerItemColor:r,dangerItemHoverColor:b,dangerItemSelectedColor:$,dangerItemActiveBg:f,dangerItemSelectedBg:c,menuSubMenuBg:a,horizontalItemSelectedColor:d,horizontalItemSelectedBg:s});return[(e=>{let{antCls:t,componentCls:o,fontSize:n,motionDurationSlow:i,motionDurationMid:r,motionEaseInOut:l,paddingXS:a,padding:d,colorSplit:s,lineWidth:c,zIndexPopup:u,borderRadiusLG:m,subMenuItemBorderRadius:p,menuArrowSize:g,menuArrowOffset:b,lineType:$,groupTitleLineHeight:f,groupTitleFontSize:v}=e;return[{"":{[o]:Object.assign(Object.assign({},(0,k.clearFix)()),{"&-hidden":{display:"none"}})},[`${o}-submenu-hidden`]:{display:"none"}},{[o]:Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},(0,k.resetComponent)(e)),(0,k.clearFix)()),{marginBottom:0,paddingInlineStart:0,fontSize:n,lineHeight:0,listStyle:"none",outline:"none",transition:`width ${i} cubic-bezier(0.2, 0, 0, 1) 0s`,"ul, ol":{margin:0,padding:0,listStyle:"none"},"&-overflow":{display:"flex",[`${o}-item`]:{flex:"none"}},[`${o}-item, ${o}-submenu, ${o}-submenu-title`]:{borderRadius:e.itemBorderRadius},[`${o}-item-group-title`]:{padding:`${(0,O.unit)(a)} ${(0,O.unit)(d)}`,fontSize:v,lineHeight:f,transition:`all ${i}`},[`&-horizontal ${o}-submenu`]:{transition:`border-color ${i} ${l},background ${i} ${l}`},[`${o}-submenu, ${o}-submenu-inline`]:{transition:`border-color ${i} ${l},background ${i} ${l},padding ${r} ${l}`},[`${o}-submenu ${o}-sub`]:{cursor:"initial",transition:`background ${i} ${l},padding ${i} ${l}`},[`${o}-title-content`]:{transition:`color ${i}`,"&-with-extra":{display:"inline-flex",alignItems:"center",width:"100%"},[`> ${t}-typography-ellipsis-single-line`]:{display:"inline",verticalAlign:"unset"},[`${o}-item-extra`]:{marginInlineStart:"auto",paddingInlineStart:e.padding}},[`${o}-item a`]:{"&::before":{position:"absolute",inset:0,backgroundColor:"transparent",content:'""'}},[`${o}-item-divider`]:{overflow:"hidden",lineHeight:0,borderColor:s,borderStyle:$,borderWidth:0,borderTopWidth:c,marginBlock:c,padding:0,"&-dashed":{borderStyle:"dashed"}}}),M(e)),{[`${o}-item-group`]:{[`${o}-item-group-list`]:{margin:0,padding:0,[`${o}-item, ${o}-submenu-title`]:{paddingInline:`${(0,O.unit)(e.calc(n).mul(2).equal())} ${(0,O.unit)(d)}`}}},"&-submenu":{"&-popup":{position:"absolute",zIndex:u,borderRadius:m,boxShadow:"none",transformOrigin:"0 0",[`&${o}-submenu`]:{background:"transparent"},"&::before":{position:"absolute",inset:0,zIndex:-1,width:"100%",height:"100%",opacity:0,content:'""'},[`> ${o}`]:Object.assign(Object.assign(Object.assign({borderRadius:m},M(e)),A(e)),{[`${o}-item, ${o}-submenu > ${o}-submenu-title`]:{borderRadius:p},[`${o}-submenu-title::after`]:{transition:`transform ${i} ${l}`}})},[`
+ &-placement-leftTop,
+ &-placement-bottomRight,
+ `]:{transformOrigin:"100% 0"},[`
+ &-placement-leftBottom,
+ &-placement-topRight,
+ `]:{transformOrigin:"100% 100%"},[`
+ &-placement-rightBottom,
+ &-placement-topLeft,
+ `]:{transformOrigin:"0 100%"},[`
+ &-placement-bottomLeft,
+ &-placement-rightTop,
+ `]:{transformOrigin:"0 0"},[`
+ &-placement-leftTop,
+ &-placement-leftBottom
+ `]:{paddingInlineEnd:e.paddingXS},[`
+ &-placement-rightTop,
+ &-placement-rightBottom
+ `]:{paddingInlineStart:e.paddingXS},[`
+ &-placement-topRight,
+ &-placement-topLeft
+ `]:{paddingBottom:e.paddingXS},[`
+ &-placement-bottomRight,
+ &-placement-bottomLeft
+ `]:{paddingTop:e.paddingXS}}}),A(e)),{[`&-inline-collapsed ${o}-submenu-arrow,
+ &-inline ${o}-submenu-arrow`]:{"&::before":{transform:`rotate(-45deg) translateX(${(0,O.unit)(b)})`},"&::after":{transform:`rotate(45deg) translateX(${(0,O.unit)(e.calc(b).mul(-1).equal())})`}},[`${o}-submenu-open${o}-submenu-inline > ${o}-submenu-title > ${o}-submenu-arrow`]:{transform:`translateY(${(0,O.unit)(e.calc(g).mul(.2).mul(-1).equal())})`,"&::after":{transform:`rotate(-45deg) translateX(${(0,O.unit)(e.calc(b).mul(-1).equal())})`},"&::before":{transform:`rotate(45deg) translateX(${(0,O.unit)(b)})`}}})},{[`${t}-layout-header`]:{[o]:{lineHeight:"inherit"}}}]})(x),(e=>{let{componentCls:t,motionDurationSlow:o,horizontalLineHeight:n,colorSplit:i,lineWidth:r,lineType:l,itemPaddingInline:a}=e;return{[`${t}-horizontal`]:{lineHeight:n,border:0,borderBottom:`${(0,O.unit)(r)} ${l} ${i}`,boxShadow:"none","&::after":{display:"block",clear:"both",height:0,content:'"\\20"'},[`${t}-item, ${t}-submenu`]:{position:"relative",display:"inline-block",verticalAlign:"bottom",paddingInline:a},[`> ${t}-item:hover,
+ > ${t}-item-active,
+ > ${t}-submenu ${t}-submenu-title:hover`]:{backgroundColor:"transparent"},[`${t}-item, ${t}-submenu-title`]:{transition:`border-color ${o},background ${o}`},[`${t}-submenu-arrow`]:{display:"none"}}}})(x),(e=>{let{componentCls:t,iconCls:o,itemHeight:n,colorTextLightSolid:i,dropdownWidth:r,controlHeightLG:l,motionEaseOut:a,paddingXL:d,itemMarginInline:s,fontSizeLG:c,motionDurationFast:u,motionDurationSlow:m,paddingXS:p,boxShadowSecondary:g,collapsedWidth:b,collapsedIconSize:$}=e,f={height:n,lineHeight:(0,O.unit)(n),listStylePosition:"inside",listStyleType:"disc"};return[{[t]:{"&-inline, &-vertical":Object.assign({[`&${t}-root`]:{boxShadow:"none"}},P(e))},[`${t}-submenu-popup`]:{[`${t}-vertical`]:Object.assign(Object.assign({},P(e)),{boxShadow:g})}},{[`${t}-submenu-popup ${t}-vertical${t}-sub`]:{minWidth:r,maxHeight:`calc(100vh - ${(0,O.unit)(e.calc(l).mul(2.5).equal())})`,padding:"0",overflow:"hidden",borderInlineEnd:0,"&:not([class*='-active'])":{overflowX:"hidden",overflowY:"auto"}}},{[`${t}-inline`]:{width:"100%",[`&${t}-root`]:{[`${t}-item, ${t}-submenu-title`]:{display:"flex",alignItems:"center",transition:`border-color ${m},background ${m},padding ${u} ${a}`,[`> ${t}-title-content`]:{flex:"auto",minWidth:0,overflow:"hidden",textOverflow:"ellipsis"},"> *":{flex:"none"}}},[`${t}-sub${t}-inline`]:{padding:0,border:0,borderRadius:0,boxShadow:"none",[`& > ${t}-submenu > ${t}-submenu-title`]:f,[`& ${t}-item-group-title`]:{paddingInlineStart:d}},[`${t}-item`]:f}},{[`${t}-inline-collapsed`]:{width:b,[`&${t}-root`]:{[`${t}-item, ${t}-submenu ${t}-submenu-title`]:{[`> ${t}-inline-collapsed-noicon`]:{fontSize:c,textAlign:"center"}}},[`> ${t}-item,
+ > ${t}-item-group > ${t}-item-group-list > ${t}-item,
+ > ${t}-item-group > ${t}-item-group-list > ${t}-submenu > ${t}-submenu-title,
+ > ${t}-submenu > ${t}-submenu-title`]:{insetInlineStart:0,paddingInline:`calc(50% - ${(0,O.unit)(e.calc($).div(2).equal())} - ${(0,O.unit)(s)})`,textOverflow:"clip",[`
+ ${t}-submenu-arrow,
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new file mode 100644
index 00000000000..ef84e7aadbe
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new file mode 100644
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/023ea71d56024e51.js b/litellm/proxy/_experimental/out/_next/static/chunks/023ea71d56024e51.js
new file mode 100644
index 00000000000..6545cebed4c
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+++ b/litellm/proxy/_experimental/out/_next/static/chunks/023ea71d56024e51.js
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new file mode 100644
index 00000000000..5b79d13c9bc
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/06aaedbe7d27898c.js
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diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0930068a29eb5657.js b/litellm/proxy/_experimental/out/_next/static/chunks/0930068a29eb5657.js
new file mode 100644
index 00000000000..b09a8f5fc18
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/0930068a29eb5657.js
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new file mode 100644
index 00000000000..b3e15e69622
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+ "guardrail_version": "your_guardrail_version"
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+ # request_data: {model, user_id, team_id, end_user_id, metadata}
+ # input_type: "request" or "response"
+ return allow()`},blockSSN:{name:"Block SSN",code:`def apply_guardrail(inputs, request_data, input_type):
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+ return block("SSN detected")
+ return allow()`},redactEmail:{name:"Redact Emails",code:`def apply_guardrail(inputs, request_data, input_type):
+ pattern = r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}"
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+ for text in inputs["texts"]:
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+ for text in inputs["texts"]:
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+ return block("SQL code not allowed")
+ return allow()`},validateJSON:{name:"Validate JSON",code:`def apply_guardrail(inputs, request_data, input_type):
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+ return allow()
+
+ schema = {"type": "object", "required": ["name", "value"]}
+
+ for text in inputs["texts"]:
+ obj = json_parse(text)
+ if obj is None:
+ return block("Invalid JSON response")
+ if not json_schema_valid(obj, schema):
+ return block("Response missing required fields")
+ return allow()`},externalAPI:{name:"External API Check (async)",code:`async def apply_guardrail(inputs, request_data, input_type):
+ # Call an external moderation API (async for non-blocking)
+ for text in inputs["texts"]:
+ response = await http_post(
+ "https://api.example.com/moderate",
+ body={"text": text, "user_id": request_data["user_id"]},
+ headers={"Authorization": "Bearer YOUR_API_KEY"},
+ timeout=10
+ )
+
+ if not response["success"]:
+ # API call failed, allow by default or block
+ return allow()
+
+ if response["body"].get("flagged"):
+ return block(response["body"].get("reason", "Content flagged"))
+
+ return allow()`}},tw={"Return Values":[{name:"allow()",desc:"Let request/response through"},{name:"block(reason)",desc:"Reject with message"},{name:"modify(texts=[], images=[], tool_calls=[])",desc:"Transform content"}],"HTTP Requests (async)":[{name:"await http_request(url, method, headers, body)",desc:"Make async HTTP request"},{name:"await http_get(url, headers)",desc:"Async GET request"},{name:"await http_post(url, body, headers)",desc:"Async POST request"}],"Regex Functions":[{name:"regex_match(text, pattern)",desc:"Returns True if pattern found"},{name:"regex_replace(text, pattern, replacement)",desc:"Replace all matches"},{name:"regex_find_all(text, pattern)",desc:"Return list of matches"}],"JSON Functions":[{name:"json_parse(text)",desc:"Parse JSON string, returns None on error"},{name:"json_stringify(obj)",desc:"Convert to JSON string"},{name:"json_schema_valid(obj, schema)",desc:"Validate against JSON schema"}],"URL Functions":[{name:"extract_urls(text)",desc:"Extract all 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+curl -X POST --location '/end_user/new' \\
+
+-H 'Authorization: Bearer ' \\
+
+-H 'Content-Type: application/json' \\
+
+-d '{"user_id": "my-customer-id', "budget_id": ""}' # 👈 KEY CHANGE
+
+`,O=`
+curl -X POST --location '/chat/completions' \\
+
+-H 'Authorization: Bearer ' \\
+
+-H 'Content-Type: application/json' \\
+
+-d '{
+ "model": "gpt-3.5-turbo',
+ "messages":[{"role": "user", "content": "Hey, how's it going?"}],
+ "user": "my-customer-id"
+}' # 👈 KEY CHANGE
+
+`,F=`from openai import OpenAI
+client = OpenAI(
+ base_url="",
+ api_key=""
+)
+
+completion = client.chat.completions.create(
+ model="gpt-3.5-turbo",
+ messages=[
+ {"role": "system", "content": "You are a helpful assistant."},
+ {"role": "user", "content": "Hello!"}
+ ],
+ user="my-customer-id"
+)
+
+print(completion.choices[0].message)`;e.s(["default",0,({accessToken:e})=>{let[y,T]=(0,p.useState)(!1),[v,w]=(0,p.useState)(!1),[I,N]=(0,p.useState)(null),[B,_]=(0,p.useState)([]),[P,S]=(0,p.useState)(!1),[D,R]=(0,p.useState)(!1);(0,p.useEffect)(()=>{e&&(0,k.getBudgetList)(e).then(e=>{_(e)})},[e]);let H=async r=>{null!=e&&(N(r),w(!0))},L=async()=>{if(I&&null!=e){S(!0);try{await (0,k.budgetDeleteCall)(e,I.budget_id),C.default.success("Budget deleted."),await U()}catch(e){console.error("Error deleting budget:",e),"function"==typeof C.default.fromBackend?C.default.fromBackend("Failed to delete budget"):C.default.info("Failed to delete budget")}finally{S(!1),R(!1),N(null)}}},U=async()=>{null!=e&&(0,k.getBudgetList)(e).then(e=>{_(e)})};return(0,r.jsxs)("div",{className:"w-full mx-auto flex-auto overflow-y-auto m-8 p-2",children:[(0,r.jsx)(t.Button,{size:"sm",variant:"primary",className:"mb-2",onClick:()=>T(!0),children:"+ Create Budget"}),(0,r.jsxs)(o.TabGroup,{children:[(0,r.jsxs)(m.TabList,{children:[(0,r.jsx)(a.Tab,{children:"Budgets"}),(0,r.jsx)(a.Tab,{children:"Examples"})]}),(0,r.jsxs)(h.TabPanels,{children:[(0,r.jsx)(g.TabPanel,{children:(0,r.jsxs)("div",{className:"mt-6",children:[(0,r.jsx)(A,{accessToken:e,isModalVisible:y,setIsModalVisible:T,setBudgetList:_}),I&&(0,r.jsx)(E,{accessToken:e,isModalVisible:v,setIsModalVisible:w,setBudgetList:_,existingBudget:I,handleUpdateCall:U}),(0,r.jsxs)(l.Card,{children:[(0,r.jsx)(b.Text,{children:"Create a budget to assign to customers."}),(0,r.jsxs)(i.Table,{children:[(0,r.jsx)(d.TableHead,{children:(0,r.jsxs)(u.TableRow,{children:[(0,r.jsx)(c.TableHeaderCell,{children:"Budget ID"}),(0,r.jsx)(c.TableHeaderCell,{children:"Max Budget"}),(0,r.jsx)(c.TableHeaderCell,{children:"TPM"}),(0,r.jsx)(c.TableHeaderCell,{children:"RPM"})]})}),(0,r.jsx)(n.TableBody,{children:B.slice().sort((e,r)=>new Date(r.updated_at).getTime()-new Date(e.updated_at).getTime()).map((e,t)=>(0,r.jsxs)(u.TableRow,{children:[(0,r.jsx)(s.TableCell,{children:e.budget_id}),(0,r.jsx)(s.TableCell,{children:e.max_budget?e.max_budget:"n/a"}),(0,r.jsx)(s.TableCell,{children:e.tpm_limit?e.tpm_limit:"n/a"}),(0,r.jsx)(s.TableCell,{children:e.rpm_limit?e.rpm_limit:"n/a"}),(0,r.jsx)(j.default,{variant:"Edit",tooltipText:"Edit budget",onClick:()=>H(e),dataTestId:"edit-budget-button"}),(0,r.jsx)(j.default,{variant:"Delete",tooltipText:"Delete budget",onClick:()=>{N(e),R(!0)},dataTestId:"delete-budget-button"})]},t))})]})]}),(0,r.jsx)(f.default,{isOpen:D,title:"Delete Budget?",message:"Are you sure you want to delete this budget? This action cannot be undone.",resourceInformationTitle:"Budget Information",resourceInformation:[{label:"Budget ID",value:I?.budget_id,code:!0},{label:"Max Budget",value:I?.max_budget},{label:"TPM",value:I?.tpm_limit},{label:"RPM",value:I?.rpm_limit}],onCancel:()=>{R(!1)},onOk:L,confirmLoading:P})]})}),(0,r.jsx)(g.TabPanel,{children:(0,r.jsxs)("div",{className:"mt-6",children:[(0,r.jsx)(b.Text,{className:"text-base",children:"How to use budget id"}),(0,r.jsxs)(o.TabGroup,{children:[(0,r.jsxs)(m.TabList,{children:[(0,r.jsx)(a.Tab,{children:"Assign Budget to Customer"}),(0,r.jsx)(a.Tab,{children:"Test it (Curl)"}),(0,r.jsx)(a.Tab,{children:"Test it (OpenAI SDK)"})]}),(0,r.jsxs)(h.TabPanels,{children:[(0,r.jsx)(g.TabPanel,{children:(0,r.jsx)(x.Prism,{language:"bash",children:M})}),(0,r.jsx)(g.TabPanel,{children:(0,r.jsx)(x.Prism,{language:"bash",children:O})}),(0,r.jsx)(g.TabPanel,{children:(0,r.jsx)(x.Prism,{language:"python",children:F})})]})]})]})})]})]})]})}],646050)},267167,e=>{"use strict";var r=e.i(843476),t=e.i(646050),l=e.i(135214);e.s(["default",0,()=>{let{accessToken:e}=(0,l.default)();return(0,r.jsx)(t.default,{accessToken:e})}])}]);
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0d2b7ad3109bd883.js b/litellm/proxy/_experimental/out/_next/static/chunks/0d2b7ad3109bd883.js
new file mode 100644
index 00000000000..acb1d237ecc
--- /dev/null
+++ b/litellm/proxy/_experimental/out/_next/static/chunks/0d2b7ad3109bd883.js
@@ -0,0 +1,14 @@
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deleted file mode 100644
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+ {dots.map((dot) => (
+
+ {i > 0 &&
+ ))}
+
+ );
+
+ const formatNum = (n: number) => n.toLocaleString();
+
+ return (
+ 0.85 ? (1 - dot.progress) * 6 : 0.8,
+ }}
+ />
+ ))}
+
+ {layers.map((layer, i) => (
+ ↓
}
+
+ {layer.label}
+ {layer.warning && ← overhead}
+
+
+
+ );
+}
diff --git a/docs/my-website/src/components/MiddlewareDiagrams/PureASGIAnimation.tsx b/docs/my-website/src/components/MiddlewareDiagrams/PureASGIAnimation.tsx
new file mode 100644
index 00000000000..c936519a651
--- /dev/null
+++ b/docs/my-website/src/components/MiddlewareDiagrams/PureASGIAnimation.tsx
@@ -0,0 +1,67 @@
+import React, { useState, useEffect, useRef, useCallback } from 'react';
+import styles from './styles.module.css';
+
+interface Stage {
+ label: string;
+ subtitle: string;
+}
+
+const STAGES: Stage[] = [
+ { label: 'Scope Check', subtitle: 'scope["type"] != "http"' },
+ { label: 'Direct Call', subtitle: 'await self.app(scope, receive, send)' },
+];
+
+const INTERVAL_MS = 1200;
+const PAUSE_MS = 600;
+
+export default function PureASGIAnimation() {
+ const [activeStage, setActiveStage] = useState(0);
+ const timerRef = useRef
+ 50,000 requests · 1,000 concurrent · 1 worker
+
+
+
+ {/* Before column */}
+
+
+ {/* Summary stats */}
+
+
+
+ {/* After column */}
+
+ Before (1 ASGI + 1 BaseHTTP)
+ {beforeDone && (
+ done
+ )}
+
+ {renderFlowStack(BEFORE_LAYERS, beforeDots, true)}
+
+
+
+
+ {formatNum(beforeCurrentRPS)}
+ RPS
+
+
+ {formatNum(beforeCompleted)}
+ Completed
+
+
+ {BEFORE_P50}ms
+ P50
+
+
+
+
+
+
+ After (2x Pure ASGI)
+ {afterDone && (
+ done
+ )}
+
+ {renderFlowStack(AFTER_LAYERS, afterDots, false)}
+
+
+
+
+ {formatNum(afterCurrentRPS)}
+ RPS
+
+
+ {formatNum(afterCompleted)}
+ Completed
+
+
+ {AFTER_P50}ms
+ P50
+
+
+
+
+
+
+ {/* Collapsible per-run data */}
+
+
+ +74%
+ Throughput (RPS)
+
+
+ -38%
+ Median Latency (P50)
+
+
+
+
+
+
+
+
+
+ | Config | +Run | +RPS | +P50 (ms) | +
|---|---|---|---|
| {row.config} | +{row.run} | +{formatNum(row.rps)} | +{row.p50} | +
+
+ );
+}
diff --git a/docs/my-website/src/components/MiddlewareDiagrams/index.tsx b/docs/my-website/src/components/MiddlewareDiagrams/index.tsx
new file mode 100644
index 00000000000..ad20d62adfd
--- /dev/null
+++ b/docs/my-website/src/components/MiddlewareDiagrams/index.tsx
@@ -0,0 +1,3 @@
+export { default as BaseHTTPMiddlewareAnimation } from './BaseHTTPMiddlewareAnimation';
+export { default as PureASGIAnimation } from './PureASGIAnimation';
+export { default as BenchmarkVisualization } from './BenchmarkVisualization';
diff --git a/docs/my-website/src/components/MiddlewareDiagrams/styles.module.css b/docs/my-website/src/components/MiddlewareDiagrams/styles.module.css
new file mode 100644
index 00000000000..a9b9249f97a
--- /dev/null
+++ b/docs/my-website/src/components/MiddlewareDiagrams/styles.module.css
@@ -0,0 +1,494 @@
+/* ── Shared custom properties ── */
+:root {
+ --mw-stage-bg: #f8f9fa;
+ --mw-stage-border: #dee2e6;
+ --mw-stage-active-bg: #e8f4fd;
+ --mw-stage-active-border: #3b82f6;
+ --mw-stage-green-active-bg: #ecfdf5;
+ --mw-stage-green-active-border: #10b981;
+ --mw-dot-color: #3b82f6;
+ --mw-warning-accent: #ef4444;
+ --mw-success-accent: #10b981;
+ --mw-text-primary: #1a1a2e;
+ --mw-text-secondary: #6b7280;
+ --mw-code-bg: #f1f5f9;
+ --mw-panel-bg: #ffffff;
+ --mw-panel-border: #e5e7eb;
+ --mw-bar-bg: #e5e7eb;
+ --mw-arrow-color: #9ca3af;
+ --mw-column-bg: #fafafa;
+ --mw-column-border: #e5e7eb;
+ --mw-layer-bg: #f3f4f6;
+ --mw-layer-border: #d1d5db;
+ --mw-layer-warning-bg: #fef2f2;
+ --mw-layer-warning-border: #fca5a5;
+ --mw-progress-bg: #e5e7eb;
+}
+
+[data-theme='dark'] {
+ --mw-stage-bg: #1e1e2e;
+ --mw-stage-border: #374151;
+ --mw-stage-active-bg: #1e3a5f;
+ --mw-stage-active-border: #60a5fa;
+ --mw-stage-green-active-bg: #064e3b;
+ --mw-stage-green-active-border: #34d399;
+ --mw-dot-color: #60a5fa;
+ --mw-warning-accent: #f87171;
+ --mw-success-accent: #34d399;
+ --mw-text-primary: #e5e7eb;
+ --mw-text-secondary: #9ca3af;
+ --mw-code-bg: #1e293b;
+ --mw-panel-bg: #111827;
+ --mw-panel-border: #374151;
+ --mw-bar-bg: #374151;
+ --mw-arrow-color: #6b7280;
+ --mw-column-bg: #111827;
+ --mw-column-border: #374151;
+ --mw-layer-bg: #1f2937;
+ --mw-layer-border: #4b5563;
+ --mw-layer-warning-bg: #451a1a;
+ --mw-layer-warning-border: #b91c1c;
+ --mw-progress-bg: #374151;
+}
+
+/* ── Pipeline (shared between BaseHTTP and PureASGI) ── */
+.pipelineWrapper {
+ margin: 1.5rem 0;
+}
+
+.pipelineLabel {
+ text-align: center;
+ font-size: 0.85rem;
+ font-weight: 600;
+ color: var(--mw-text-secondary);
+ margin-bottom: 0.75rem;
+ text-transform: uppercase;
+ letter-spacing: 0.05em;
+}
+
+.pipeline {
+ display: flex;
+ flex-wrap: wrap;
+ justify-content: center;
+ align-items: stretch;
+ gap: 0.75rem;
+ padding: 0.5rem 0;
+}
+
+.pipelineTwoCol {
+ max-width: 480px;
+ margin: 0 auto;
+}
+
+.stageWrapper {
+ display: flex;
+ align-items: center;
+ width: 160px;
+ flex-shrink: 0;
+}
+
+.pipelineTwoCol .stageWrapper {
+ width: 200px;
+}
+
+.arrow {
+ display: none;
+}
+
+.stage {
+ flex: 1;
+ padding: 0.85rem 0.75rem;
+ min-height: 100px;
+ display: flex;
+ flex-direction: column;
+ justify-content: center;
+ background: var(--mw-stage-bg);
+ border: 2px solid var(--mw-stage-border);
+ border-radius: 8px;
+ text-align: center;
+ cursor: pointer;
+ transition: background 0.4s ease, border-color 0.4s ease, box-shadow 0.4s ease;
+ user-select: none;
+}
+
+.stage:hover {
+ border-color: var(--mw-stage-active-border);
+}
+
+.stageActive {
+ background: var(--mw-stage-active-bg);
+ border-color: var(--mw-stage-active-border);
+ box-shadow: 0 0 0 3px rgba(59, 130, 246, 0.15);
+}
+
+.stageActiveGreen {
+ background: var(--mw-stage-green-active-bg);
+ border-color: var(--mw-stage-green-active-border);
+ box-shadow: 0 0 0 3px rgba(16, 185, 129, 0.15);
+}
+
+.stageNoClick {
+ cursor: default;
+}
+
+.stageNumber {
+ font-size: 0.7rem;
+ font-weight: 700;
+ color: var(--mw-text-secondary);
+ margin-bottom: 0.3rem;
+}
+
+.stageLabel {
+ font-size: 0.85rem;
+ font-weight: 600;
+ color: var(--mw-text-primary);
+ margin-bottom: 0.25rem;
+ line-height: 1.3;
+}
+
+.stageSubtitle {
+ font-size: 0.72rem;
+ color: var(--mw-text-secondary);
+ font-family: 'SFMono-Regular', Consolas, 'Liberation Mono', Menlo, monospace;
+ word-break: break-word;
+ line-height: 1.3;
+}
+
+/* ── Code panel (accordion) ── */
+.codePanel {
+ max-height: 0;
+ overflow: hidden;
+ transition: max-height 0.35s ease, padding 0.35s ease;
+ background: var(--mw-code-bg);
+ border-radius: 0 0 8px 8px;
+ margin-top: 0.5rem;
+}
+
+.codePanelOpen {
+ max-height: 120px;
+ padding: 0.75rem 1rem;
+}
+
+.codePanelCode {
+ font-family: 'SFMono-Regular', Consolas, 'Liberation Mono', Menlo, monospace;
+ font-size: 0.8rem;
+ color: var(--mw-text-primary);
+ white-space: pre;
+ margin: 0;
+ line-height: 1.5;
+}
+
+/* ── Benchmark Visualization ── */
+.benchmarkWrapper {
+ margin: 1.5rem 0;
+}
+
+.benchmarkConfig {
+ text-align: center;
+ font-size: 0.85rem;
+ color: var(--mw-text-secondary);
+ margin-bottom: 1rem;
+ font-weight: 500;
+}
+
+.benchmarkColumns {
+ display: flex;
+ gap: 1.5rem;
+}
+
+.benchmarkColumn {
+ flex: 1;
+ background: var(--mw-column-bg);
+ border: 1px solid var(--mw-column-border);
+ border-radius: 12px;
+ padding: 1.25rem;
+ position: relative;
+ overflow: hidden;
+}
+
+.columnTitle {
+ font-size: 0.9rem;
+ font-weight: 700;
+ color: var(--mw-text-primary);
+ text-align: center;
+ margin-bottom: 1rem;
+}
+
+.columnTitleBefore {
+ color: var(--mw-warning-accent);
+}
+
+.columnTitleAfter {
+ color: var(--mw-success-accent);
+}
+
+/* ── Request flow stack ── */
+.flowStack {
+ display: flex;
+ flex-direction: column;
+ align-items: center;
+ gap: 0;
+ position: relative;
+ min-height: 280px;
+}
+
+.flowLayer {
+ width: 100%;
+ max-width: 260px;
+ padding: 0.6rem 0.75rem;
+ background: var(--mw-layer-bg);
+ border: 1px solid var(--mw-layer-border);
+ border-radius: 6px;
+ text-align: center;
+ font-size: 0.78rem;
+ font-weight: 500;
+ color: var(--mw-text-primary);
+ position: relative;
+ z-index: 1;
+}
+
+.flowLayerWarning {
+ background: var(--mw-layer-warning-bg);
+ border-color: var(--mw-layer-warning-border);
+ font-weight: 700;
+}
+
+.flowArrow {
+ display: flex;
+ justify-content: center;
+ color: var(--mw-arrow-color);
+ font-size: 0.9rem;
+ padding: 0.15rem 0;
+ position: relative;
+ z-index: 0;
+ min-height: 20px;
+}
+
+.overheadTag {
+ font-size: 0.65rem;
+ color: var(--mw-warning-accent);
+ margin-left: 0.4rem;
+}
+
+/* ── Dots layer (canvas for flowing dots) ── */
+.dotsCanvas {
+ position: absolute;
+ top: 0;
+ left: 0;
+ width: 100%;
+ height: 100%;
+ pointer-events: none;
+ z-index: 2;
+}
+
+.dot {
+ position: absolute;
+ width: 6px;
+ height: 6px;
+ border-radius: 50%;
+ background: var(--mw-dot-color);
+ opacity: 0.8;
+}
+
+.dotSlow {
+ background: var(--mw-warning-accent);
+}
+
+.dotFast {
+ background: var(--mw-success-accent);
+}
+
+/* ── Stats & progress ── */
+.statsRow {
+ display: flex;
+ justify-content: space-around;
+ margin-top: 1rem;
+ padding-top: 0.75rem;
+ border-top: 1px solid var(--mw-panel-border);
+}
+
+.stat {
+ text-align: center;
+}
+
+.statValue {
+ font-size: 1.1rem;
+ font-weight: 700;
+ color: var(--mw-text-primary);
+ font-variant-numeric: tabular-nums;
+}
+
+.statLabel {
+ font-size: 0.7rem;
+ color: var(--mw-text-secondary);
+ text-transform: uppercase;
+ letter-spacing: 0.04em;
+}
+
+.progressBar {
+ width: 100%;
+ height: 6px;
+ background: var(--mw-progress-bg);
+ border-radius: 3px;
+ margin-top: 0.75rem;
+ overflow: hidden;
+}
+
+.progressFill {
+ height: 100%;
+ border-radius: 3px;
+ transition: width 0.1s linear;
+}
+
+.progressFillBefore {
+ background: var(--mw-warning-accent);
+}
+
+.progressFillAfter {
+ background: var(--mw-success-accent);
+}
+
+/* ── Summary stats below simulation ── */
+.summaryStats {
+ display: flex;
+ justify-content: center;
+ gap: 2rem;
+ margin-top: 1.5rem;
+ flex-wrap: wrap;
+}
+
+.summaryItem {
+ text-align: center;
+ padding: 0.75rem 1.25rem;
+ background: var(--mw-stage-bg);
+ border-radius: 8px;
+ border: 1px solid var(--mw-panel-border);
+}
+
+.summaryValue {
+ font-size: 1.5rem;
+ font-weight: 800;
+ color: var(--mw-success-accent);
+}
+
+.summaryLabel {
+ font-size: 0.8rem;
+ color: var(--mw-text-secondary);
+ margin-top: 0.2rem;
+}
+
+/* ── Collapsible table ── */
+.collapsible {
+ margin-top: 1.5rem;
+}
+
+.collapsibleToggle {
+ background: none;
+ border: 1px solid var(--mw-panel-border);
+ border-radius: 6px;
+ padding: 0.5rem 1rem;
+ cursor: pointer;
+ font-size: 0.85rem;
+ color: var(--mw-text-primary);
+ width: 100%;
+ text-align: left;
+ display: flex;
+ align-items: center;
+ gap: 0.5rem;
+ transition: background 0.2s;
+}
+
+.collapsibleToggle:hover {
+ background: var(--mw-stage-bg);
+}
+
+.collapsibleChevron {
+ transition: transform 0.3s ease;
+ font-size: 0.7rem;
+}
+
+.collapsibleChevronOpen {
+ transform: rotate(90deg);
+}
+
+.collapsibleContent {
+ max-height: 0;
+ overflow: hidden;
+ transition: max-height 0.35s ease;
+}
+
+.collapsibleContentOpen {
+ max-height: 600px;
+}
+
+.dataTable {
+ width: 100%;
+ border-collapse: collapse;
+ margin-top: 0.75rem;
+ font-size: 0.85rem;
+}
+
+.dataTable th,
+.dataTable td {
+ padding: 0.5rem 0.75rem;
+ text-align: left;
+ border-bottom: 1px solid var(--mw-panel-border);
+}
+
+.dataTable th {
+ font-weight: 600;
+ color: var(--mw-text-secondary);
+ font-size: 0.75rem;
+ text-transform: uppercase;
+ letter-spacing: 0.04em;
+}
+
+.dataTable td {
+ color: var(--mw-text-primary);
+ font-variant-numeric: tabular-nums;
+}
+
+/* ── Reproduce section ── */
+.reproduceSection {
+ margin-top: 1rem;
+}
+
+/* ── Done badge ── */
+.doneBadge {
+ display: inline-block;
+ font-size: 0.75rem;
+ font-weight: 600;
+ padding: 0.2rem 0.6rem;
+ border-radius: 4px;
+ margin-left: 0.5rem;
+}
+
+.doneBadgeBefore {
+ color: var(--mw-warning-accent);
+ background: var(--mw-layer-warning-bg);
+}
+
+.doneBadgeAfter {
+ color: var(--mw-success-accent);
+ background: var(--mw-stage-green-active-bg);
+}
+
+/* ── Responsive ── */
+@media (max-width: 768px) {
+ .stageWrapper {
+ width: 140px;
+ }
+
+ .pipelineTwoCol .stageWrapper {
+ width: 160px;
+ }
+
+ .benchmarkColumns {
+ flex-direction: column;
+ }
+
+ .summaryStats {
+ flex-direction: column;
+ align-items: center;
+ }
+}
diff --git a/enterprise/dist/litellm_enterprise-0.1.30-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.30-py3-none-any.whl
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new file mode 100644
index 00000000000..2bb7510e5d3
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diff --git a/enterprise/dist/litellm_enterprise-0.1.31-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.31-py3-none-any.whl
new file mode 100644
index 00000000000..03cadbd9023
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diff --git a/enterprise/dist/litellm_enterprise-0.1.31.tar.gz b/enterprise/dist/litellm_enterprise-0.1.31.tar.gz
new file mode 100644
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Binary files /dev/null and b/enterprise/dist/litellm_enterprise-0.1.31.tar.gz differ
diff --git a/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py b/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py
index 61e0745bab1..d3e04769300 100644
--- a/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py
+++ b/enterprise/litellm_enterprise/enterprise_callbacks/send_emails/base_email.py
@@ -30,8 +30,15 @@ from litellm.integrations.email_templates.user_invitation_email import (
from litellm.integrations.email_templates.templates import (
MAX_BUDGET_ALERT_EMAIL_TEMPLATE,
SOFT_BUDGET_ALERT_EMAIL_TEMPLATE,
+ TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE,
+)
+from litellm.proxy._types import (
+ CallInfo,
+ InvitationNew,
+ Litellm_EntityType,
+ UserAPIKeyAuth,
+ WebhookEvent,
)
-from litellm.proxy._types import CallInfo, InvitationNew, UserAPIKeyAuth, WebhookEvent
from litellm.secret_managers.main import get_secret_bool
from litellm.types.integrations.slack_alerting import LITELLM_LOGO_URL
from litellm.constants import (
@@ -217,6 +224,78 @@ class BaseEmailLogger(CustomLogger):
)
pass
+ async def send_team_soft_budget_alert_email(self, event: WebhookEvent):
+ """
+ Send email to team members when team soft budget is crossed
+ Supports multiple recipients via alert_emails field from team metadata
+ """
+ # Collect all recipient emails
+ recipient_emails: List[str] = []
+
+ # Add additional alert emails from team metadata.soft_budget_alert_emails
+ if hasattr(event, "alert_emails") and event.alert_emails:
+ for email in event.alert_emails:
+ if email and email not in recipient_emails: # Avoid duplicates
+ recipient_emails.append(email)
+
+ # If no recipients found, skip sending
+ if not recipient_emails:
+ verbose_proxy_logger.warning(
+ f"No recipient emails found for team soft budget alert. event={event.model_dump(exclude_none=True)}"
+ )
+ return
+
+ # Validate that we have at least one valid email address
+ first_recipient_email = recipient_emails[0]
+ if not first_recipient_email or not first_recipient_email.strip():
+ verbose_proxy_logger.warning(
+ f"Invalid recipient email found for team soft budget alert. event={event.model_dump(exclude_none=True)}"
+ )
+ return
+
+ verbose_proxy_logger.debug(
+ f"send_team_soft_budget_alert_email_event: {json.dumps(event.model_dump(exclude_none=True), indent=4, default=str)}"
+ )
+
+ # Get email params using the first recipient email (for template formatting)
+ # For team alerts with alert_emails, we don't need user_id lookup since we already have email addresses
+ # Pass user_id=None to prevent _get_email_params from trying to look up email from a potentially None user_id
+ email_params = await self._get_email_params(
+ email_event=EmailEvent.soft_budget_crossed,
+ user_id=None, # Team alerts don't require user_id when alert_emails are provided
+ user_email=first_recipient_email,
+ event_message=event.event_message,
+ )
+
+ # Format budget values
+ soft_budget_str = f"${event.soft_budget}" if event.soft_budget is not None else "N/A"
+ spend_str = f"${event.spend}" if event.spend is not None else "$0.00"
+ max_budget_info = ""
+ if event.max_budget is not None:
+ max_budget_info = f"Maximum Budget: ${event.max_budget} 2 steps per request
+
+ {STAGES.map((stage, i) => (
+
+
+
+ ))}
+
+
+ {i + 1}
+ {stage.label}
+ {stage.subtitle}
+ " + + # Use team alias or generic greeting + team_alias = event.team_alias or "Team" + + email_html_content = TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE.format( + email_logo_url=email_params.logo_url, + team_alias=team_alias, + soft_budget=soft_budget_str, + spend=spend_str, + max_budget_info=max_budget_info, + base_url=email_params.base_url, + email_support_contact=email_params.support_contact, + ) + + # Send email to all recipients + await self.send_email( + from_email=self.DEFAULT_LITELLM_EMAIL, + to_email=recipient_emails, + subject=email_params.subject, + html_body=email_html_content, + ) + pass + async def send_max_budget_alert_email(self, event: WebhookEvent): """ Send email to user when max budget alert threshold is reached @@ -285,15 +364,36 @@ class BaseEmailLogger(CustomLogger): # - Don't re-alert, if alert already sent _cache: DualCache = self.internal_usage_cache - # percent of max_budget left to spend - if user_info.max_budget is None and user_info.soft_budget is None: - return - # For soft_budget alerts, check if we've already sent an alert if type == "soft_budget": + # For team soft budget alerts, we only need team soft_budget to be set + # For other entity types, we need either max_budget or soft_budget + if user_info.event_group == Litellm_EntityType.TEAM: + if user_info.soft_budget is None: + return + # For team soft budget alerts, require alert_emails to be configured + # Team soft budget alerts are sent via metadata.soft_budget_alerting_emails + if user_info.alert_emails is None or len(user_info.alert_emails) == 0: + verbose_proxy_logger.debug( + "Skipping team soft budget email alert: no alert_emails configured", + ) + return + else: + # For non-team alerts, require either max_budget or soft_budget + if user_info.max_budget is None and user_info.soft_budget is None: + return if user_info.soft_budget is not None and user_info.spend >= user_info.soft_budget: # Generate cache key based on event type and identifier - _id = user_info.token or user_info.user_id or "default_id" + # Use appropriate ID based on event_group to ensure unique cache keys per entity type + if user_info.event_group == Litellm_EntityType.TEAM: + _id = user_info.team_id or "default_id" + elif user_info.event_group == Litellm_EntityType.ORGANIZATION: + _id = user_info.organization_id or "default_id" + elif user_info.event_group == Litellm_EntityType.USER: + _id = user_info.user_id or "default_id" + else: + # For KEY and other types, use token or user_id + _id = user_info.token or user_info.user_id or "default_id" _cache_key = f"email_budget_alerts:soft_budget_crossed:{_id}" # Check if we've already sent this alert @@ -318,10 +418,15 @@ class BaseEmailLogger(CustomLogger): projected_exceeded_date=user_info.projected_exceeded_date, projected_spend=user_info.projected_spend, event_group=user_info.event_group, + alert_emails=user_info.alert_emails, ) try: - await self.send_soft_budget_alert_email(webhook_event) + # Use team-specific function for team alerts, otherwise use standard function + if user_info.event_group == Litellm_EntityType.TEAM: + await self.send_team_soft_budget_alert_email(webhook_event) + else: + await self.send_soft_budget_alert_email(webhook_event) # Cache the alert to prevent duplicate sends await _cache.async_set_cache( diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index c5aaa0a3407..eca5cdb97df 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-enterprise" -version = "0.1.29" +version = "0.1.31" description = "Package for LiteLLM Enterprise features" authors = ["BerriAI"] readme = "README.md" @@ -22,7 +22,7 @@ requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "0.1.29" +version = "0.1.31" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-enterprise==", diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl new file mode 100644 index 00000000000..90b36bd78ac Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz new file mode 100644 index 00000000000..64607235479 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.31.tar.gz differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl new file mode 100644 index 00000000000..deb9653aa78 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz new file mode 100644 index 00000000000..212194e31e2 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.32.tar.gz differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl new file mode 100644 index 00000000000..a4872243ae6 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz new file mode 100644 index 00000000000..643be22aa42 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.33.tar.gz differ diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql new file mode 100644 index 00000000000..a64f1de342f --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260205144610_add_soft_budget_to_team_table/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_TeamTable" ADD COLUMN "soft_budget" DOUBLE PRECISION; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql new file mode 100644 index 00000000000..1efde3dbe0f --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207093506_add_available_on_public_internet_to_mcp_servers/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_MCPServerTable" ADD COLUMN "available_on_public_internet" BOOLEAN NOT NULL DEFAULT false; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql new file mode 100644 index 00000000000..abfb153061b --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260207110613_add_soft_budget_to_deleted_teams_table/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_DeletedTeamTable" ADD COLUMN "soft_budget" DOUBLE PRECISION; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql new file mode 100644 index 00000000000..572eea9b529 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql @@ -0,0 +1,8 @@ +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_user_id_team_id_idx" ON "LiteLLM_VerificationToken"("user_id", "team_id"); + +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_team_id_idx" ON "LiteLLM_VerificationToken"("team_id"); + +-- CreateIndex +CREATE INDEX "LiteLLM_VerificationToken_budget_reset_at_expires_idx" ON "LiteLLM_VerificationToken"("budget_reset_at", "expires"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index dc49036cb15..b1ca1f71c9e 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -113,6 +113,7 @@ model LiteLLM_TeamTable { members_with_roles Json @default("{}") metadata Json @default("{}") max_budget Float? + soft_budget Float? spend Float @default(0.0) models String[] max_parallel_requests Int? @@ -147,6 +148,7 @@ model LiteLLM_DeletedTeamTable { members_with_roles Json @default("{}") metadata Json @default("{}") max_budget Float? + soft_budget Float? spend Float @default(0.0) models String[] max_parallel_requests Int? @@ -262,6 +264,7 @@ model LiteLLM_MCPServerTable { token_url String? registration_url String? allow_all_keys Boolean @default(false) + available_on_public_internet Boolean @default(false) } // Generate Tokens for Proxy @@ -307,6 +310,16 @@ model LiteLLM_VerificationToken { litellm_budget_table LiteLLM_BudgetTable? @relation(fields: [budget_id], references: [budget_id]) litellm_organization_table LiteLLM_OrganizationTable? @relation(fields: [organization_id], references: [organization_id]) object_permission LiteLLM_ObjectPermissionTable? @relation(fields: [object_permission_id], references: [object_permission_id]) + + // SELECT COUNT(*) FROM (SELECT "public"."LiteLLM_VerificationToken"."token" FROM "public"."LiteLLM_VerificationToken" WHERE ("public"."LiteLLM_VerificationToken"."user_id" = $1 AND ("public"."LiteLLM_VerificationToken"."team_id" IS NULL OR "public"."LiteLLM_VerificationToken"."team_id" <> $2)) OFFSET $3 ) AS "sub" + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE "public"."LiteLLM_VerificationToken"."user_id" = $1 OFFSET $2 + @@index([user_id, team_id]) + + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE "public"."LiteLLM_VerificationToken"."team_id" = $1 OFFSET $2 + @@index([team_id]) + + // SELECT ... FROM "public"."LiteLLM_VerificationToken" WHERE (("public"."LiteLLM_VerificationToken"."expires" IS NULL OR "public"."LiteLLM_VerificationToken"."expires" > $1) AND "public"."LiteLLM_VerificationToken"."budget_reset_at" < $2) OFFSET $3 + @@index([budget_reset_at, expires]) } // Audit table for deleted keys - preserves spend and key information for historical tracking diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index d43b591686c..8937858bbd9 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-proxy-extras" -version = "0.4.30" +version = "0.4.33" 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 = "0.4.30" +version = "0.4.33" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-proxy-extras==", diff --git a/litellm/a2a_protocol/__init__.py b/litellm/a2a_protocol/__init__.py index d8d349bb98a..85c03687e25 100644 --- a/litellm/a2a_protocol/__init__.py +++ b/litellm/a2a_protocol/__init__.py @@ -39,6 +39,12 @@ Example usage (class-based): """ from litellm.a2a_protocol.client import A2AClient +from litellm.a2a_protocol.exceptions import ( + A2AAgentCardError, + A2AConnectionError, + A2AError, + A2ALocalhostURLError, +) from litellm.a2a_protocol.main import ( aget_agent_card, asend_message, @@ -49,11 +55,19 @@ from litellm.a2a_protocol.main import ( from litellm.types.agents import LiteLLMSendMessageResponse __all__ = [ + # Client "A2AClient", + # Functions "asend_message", "send_message", "asend_message_streaming", "aget_agent_card", "create_a2a_client", + # Response types "LiteLLMSendMessageResponse", + # Exceptions + "A2AError", + "A2AConnectionError", + "A2AAgentCardError", + "A2ALocalhostURLError", ] diff --git a/litellm/a2a_protocol/card_resolver.py b/litellm/a2a_protocol/card_resolver.py index 7c4c5af149d..4c5dd3e3ba6 100644 --- a/litellm/a2a_protocol/card_resolver.py +++ b/litellm/a2a_protocol/card_resolver.py @@ -7,6 +7,7 @@ Extends the A2A SDK's card resolver to support multiple well-known paths. from typing import TYPE_CHECKING, Any, Dict, Optional from litellm._logging import verbose_logger +from litellm.constants import LOCALHOST_URL_PATTERNS if TYPE_CHECKING: from a2a.types import AgentCard @@ -26,15 +27,61 @@ except ImportError: pass +def is_localhost_or_internal_url(url: Optional[str]) -> bool: + """ + Check if a URL is a localhost or internal URL. + + This detects common development URLs that are accidentally left in + agent cards when deploying to production. + + Args: + url: The URL to check + + Returns: + True if the URL is localhost/internal + """ + if not url: + return False + + url_lower = url.lower() + + return any(pattern in url_lower for pattern in LOCALHOST_URL_PATTERNS) + + +def fix_agent_card_url(agent_card: "AgentCard", base_url: str) -> "AgentCard": + """ + Fix the agent card URL if it contains a localhost/internal address. + + Many A2A agents are deployed with agent cards that contain internal URLs + like "http://0.0.0.0:8001/" or "http://localhost:8000/". This function + replaces such URLs with the provided base_url. + + Args: + agent_card: The agent card to fix + base_url: The base URL to use as replacement + + Returns: + The agent card with the URL fixed if necessary + """ + card_url = getattr(agent_card, "url", None) + + if card_url and is_localhost_or_internal_url(card_url): + # Normalize base_url to ensure it ends with / + fixed_url = base_url.rstrip("/") + "/" + agent_card.url = fixed_url + + return agent_card + + class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] """ Custom A2A card resolver that supports multiple well-known paths. - + Extends the base A2ACardResolver to try both: - /.well-known/agent-card.json (standard) - /.well-known/agent.json (previous/alternative) """ - + async def get_agent_card( self, relative_card_path: Optional[str] = None, @@ -42,17 +89,17 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] ) -> "AgentCard": """ Fetch the agent card, trying multiple well-known paths. - + First tries the standard path, then falls back to the previous path. - + Args: relative_card_path: Optional path to the agent card endpoint. If None, tries both well-known paths. http_kwargs: Optional dictionary of keyword arguments to pass to httpx.get - + Returns: AgentCard from the A2A agent - + Raises: A2AClientHTTPError or A2AClientJSONError if both paths fail """ @@ -62,13 +109,13 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] relative_card_path=relative_card_path, http_kwargs=http_kwargs, ) - + # Try both well-known paths paths = [ AGENT_CARD_WELL_KNOWN_PATH, PREV_AGENT_CARD_WELL_KNOWN_PATH, ] - + last_error = None for path in paths: try: @@ -85,11 +132,11 @@ class LiteLLMA2ACardResolver(_A2ACardResolver): # type: ignore[misc] ) last_error = e continue - + # If we get here, all paths failed - re-raise the last error if last_error is not None: raise last_error - + # This shouldn't happen, but just in case raise Exception( f"Failed to fetch agent card from {self.base_url}. " diff --git a/litellm/a2a_protocol/exception_mapping_utils.py b/litellm/a2a_protocol/exception_mapping_utils.py new file mode 100644 index 00000000000..49dbb22b158 --- /dev/null +++ b/litellm/a2a_protocol/exception_mapping_utils.py @@ -0,0 +1,203 @@ +""" +A2A Protocol Exception Mapping Utils. + +Maps A2A SDK exceptions to LiteLLM A2A exception types. +""" + +from typing import TYPE_CHECKING, Any, Optional + +from litellm._logging import verbose_logger +from litellm.a2a_protocol.card_resolver import ( + fix_agent_card_url, + is_localhost_or_internal_url, +) +from litellm.a2a_protocol.exceptions import ( + A2AAgentCardError, + A2AConnectionError, + A2AError, + A2ALocalhostURLError, +) +from litellm.constants import CONNECTION_ERROR_PATTERNS + +if TYPE_CHECKING: + from a2a.client import A2AClient as A2AClientType + + +# Runtime import +A2A_SDK_AVAILABLE = False +try: + from a2a.client import A2AClient as _A2AClient # type: ignore[no-redef] + + A2A_SDK_AVAILABLE = True +except ImportError: + _A2AClient = None # type: ignore[assignment, misc] + + +class A2AExceptionCheckers: + """ + Helper class for checking various A2A error conditions. + """ + + @staticmethod + def is_connection_error(error_str: str) -> bool: + """ + Check if an error string indicates a connection error. + + Args: + error_str: The error string to check + + Returns: + True if the error indicates a connection issue + """ + if not isinstance(error_str, str): + return False + + error_str_lower = error_str.lower() + return any(pattern in error_str_lower for pattern in CONNECTION_ERROR_PATTERNS) + + @staticmethod + def is_localhost_url(url: Optional[str]) -> bool: + """ + Check if a URL is a localhost/internal URL. + + Args: + url: The URL to check + + Returns: + True if the URL is localhost/internal + """ + return is_localhost_or_internal_url(url) + + @staticmethod + def is_agent_card_error(error_str: str) -> bool: + """ + Check if an error string indicates an agent card error. + + Args: + error_str: The error string to check + + Returns: + True if the error is related to agent card fetching/parsing + """ + if not isinstance(error_str, str): + return False + + error_str_lower = error_str.lower() + agent_card_patterns = [ + "agent card", + "agent-card", + ".well-known", + "card not found", + "invalid agent", + ] + return any(pattern in error_str_lower for pattern in agent_card_patterns) + + +def map_a2a_exception( + original_exception: Exception, + card_url: Optional[str] = None, + api_base: Optional[str] = None, + model: Optional[str] = None, +) -> Exception: + """ + Map an A2A SDK exception to a LiteLLM A2A exception type. + + Args: + original_exception: The original exception from the A2A SDK + card_url: The URL from the agent card (if available) + api_base: The original API base URL + model: The model/agent name + + Returns: + A mapped LiteLLM A2A exception + + Raises: + A2ALocalhostURLError: If the error is a connection error to a localhost URL + A2AConnectionError: If the error is a general connection error + A2AAgentCardError: If the error is related to agent card issues + A2AError: For other A2A-related errors + """ + error_str = str(original_exception) + + # Check for localhost URL connection error (special case - retryable) + if ( + card_url + and api_base + and A2AExceptionCheckers.is_localhost_url(card_url) + and A2AExceptionCheckers.is_connection_error(error_str) + ): + raise A2ALocalhostURLError( + localhost_url=card_url, + base_url=api_base, + original_error=original_exception, + model=model, + ) + + # Check for agent card errors + if A2AExceptionCheckers.is_agent_card_error(error_str): + raise A2AAgentCardError( + message=error_str, + url=api_base, + model=model, + ) + + # Check for general connection errors + if A2AExceptionCheckers.is_connection_error(error_str): + raise A2AConnectionError( + message=error_str, + url=card_url or api_base, + model=model, + ) + + # Default: wrap in generic A2AError + raise A2AError( + message=error_str, + model=model, + ) + + +def handle_a2a_localhost_retry( + error: A2ALocalhostURLError, + agent_card: Any, + a2a_client: "A2AClientType", + is_streaming: bool = False, +) -> "A2AClientType": + """ + Handle A2ALocalhostURLError by fixing the URL and creating a new client. + + This is called when we catch an A2ALocalhostURLError and want to retry + with the corrected URL. + + Args: + error: The localhost URL error + agent_card: The agent card object to fix + a2a_client: The current A2A client + is_streaming: Whether this is a streaming request (for logging) + + Returns: + A new A2A client with the fixed URL + + Raises: + ImportError: If the A2A SDK is not installed + """ + if not A2A_SDK_AVAILABLE or _A2AClient is None: + raise ImportError( + "A2A SDK is required for localhost retry handling. " + "Install it with: pip install a2a" + ) + + request_type = "streaming " if is_streaming else "" + verbose_logger.warning( + f"A2A {request_type}request to '{error.localhost_url}' failed: {error.original_error}. " + f"Agent card contains localhost/internal URL. " + f"Retrying with base_url '{error.base_url}'." + ) + + # Fix the agent card URL + fix_agent_card_url(agent_card, error.base_url) + + # Create a new client with the fixed agent card (transport caches URL) + return _A2AClient( + httpx_client=a2a_client._transport.httpx_client, # type: ignore[union-attr] + agent_card=agent_card, + ) diff --git a/litellm/a2a_protocol/exceptions.py b/litellm/a2a_protocol/exceptions.py new file mode 100644 index 00000000000..546b23105be --- /dev/null +++ b/litellm/a2a_protocol/exceptions.py @@ -0,0 +1,150 @@ +""" +A2A Protocol Exceptions. + +Custom exception types for A2A protocol operations, following LiteLLM's exception pattern. +""" + +from typing import Optional + +import httpx + + +class A2AError(Exception): + """ + Base exception for A2A protocol errors. + + Follows the same pattern as LiteLLM's main exceptions. + """ + + def __init__( + self, + message: str, + status_code: int = 500, + llm_provider: str = "a2a_agent", + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + max_retries: Optional[int] = None, + num_retries: Optional[int] = None, + ): + self.status_code = status_code + self.message = f"litellm.A2AError: {message}" + self.llm_provider = llm_provider + self.model = model + self.litellm_debug_info = litellm_debug_info + self.max_retries = max_retries + self.num_retries = num_retries + self.response = response or httpx.Response( + status_code=self.status_code, + request=httpx.Request(method="POST", url="https://litellm.ai"), + ) + super().__init__(self.message) + + def __str__(self) -> str: + _message = self.message + if self.num_retries: + _message += f" LiteLLM Retried: {self.num_retries} times" + if self.max_retries: + _message += f", LiteLLM Max Retries: {self.max_retries}" + return _message + + def __repr__(self) -> str: + return self.__str__() + + +class A2AConnectionError(A2AError): + """ + Raised when connection to an A2A agent fails. + + This typically occurs when: + - The agent is unreachable + - The agent card contains a localhost/internal URL + - Network issues prevent connection + """ + + def __init__( + self, + message: str, + url: Optional[str] = None, + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + max_retries: Optional[int] = None, + num_retries: Optional[int] = None, + ): + self.url = url + super().__init__( + message=message, + status_code=503, + llm_provider="a2a_agent", + model=model, + response=response, + litellm_debug_info=litellm_debug_info, + max_retries=max_retries, + num_retries=num_retries, + ) + + +class A2AAgentCardError(A2AError): + """ + Raised when there's an issue with the agent card. + + This includes: + - Failed to fetch agent card + - Invalid agent card format + - Missing required fields + """ + + def __init__( + self, + message: str, + url: Optional[str] = None, + model: Optional[str] = None, + response: Optional[httpx.Response] = None, + litellm_debug_info: Optional[str] = None, + ): + self.url = url + super().__init__( + message=message, + status_code=404, + llm_provider="a2a_agent", + model=model, + response=response, + litellm_debug_info=litellm_debug_info, + ) + + +class A2ALocalhostURLError(A2AConnectionError): + """ + Raised when an agent card contains a localhost/internal URL. + + Many A2A agents are deployed with agent cards that contain internal URLs + like "http://0.0.0.0:8001/" or "http://localhost:8000/". This error + indicates that the URL needs to be corrected and the request should be retried. + + Attributes: + localhost_url: The localhost/internal URL found in the agent card + base_url: The public base URL that should be used instead + original_error: The original connection error that was raised + """ + + def __init__( + self, + localhost_url: str, + base_url: str, + original_error: Optional[Exception] = None, + model: Optional[str] = None, + ): + self.localhost_url = localhost_url + self.base_url = base_url + self.original_error = original_error + + message = ( + f"Agent card contains localhost/internal URL '{localhost_url}'. " + f"Retrying with base URL '{base_url}'." + ) + super().__init__( + message=message, + url=localhost_url, + model=model, + ) diff --git a/litellm/a2a_protocol/main.py b/litellm/a2a_protocol/main.py index b326f9e7ed5..642dfaf023c 100644 --- a/litellm/a2a_protocol/main.py +++ b/litellm/a2a_protocol/main.py @@ -44,6 +44,11 @@ except ImportError: # Import our custom card resolver that supports multiple well-known paths from litellm.a2a_protocol.card_resolver import LiteLLMA2ACardResolver +from litellm.a2a_protocol.exception_mapping_utils import ( + handle_a2a_localhost_retry, + map_a2a_exception, +) +from litellm.a2a_protocol.exceptions import A2ALocalhostURLError # Use our custom resolver instead of the default A2A SDK resolver A2ACardResolver = LiteLLMA2ACardResolver @@ -244,10 +249,50 @@ async def asend_message( verbose_logger.info(f"A2A send_message request_id={request.id}, agent={agent_name}") - a2a_response = await a2a_client.send_message(request) + # Get agent card URL for localhost retry logic + agent_card = getattr(a2a_client, "_litellm_agent_card", None) or getattr( + a2a_client, "agent_card", None + ) + card_url = getattr(agent_card, "url", None) if agent_card else None + + # Retry loop: if connection fails due to localhost URL in agent card, retry with fixed URL + a2a_response = None + for _ in range(2): # max 2 attempts: original + 1 retry + try: + a2a_response = await a2a_client.send_message(request) + break # success, exit retry loop + except A2ALocalhostURLError as e: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=e, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=False, + ) + card_url = agent_card.url if agent_card else None + except Exception as e: + # Map exception - will raise A2ALocalhostURLError if applicable + try: + map_a2a_exception(e, card_url, api_base, model=agent_name) + except A2ALocalhostURLError as localhost_err: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=localhost_err, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=False, + ) + card_url = agent_card.url if agent_card else None + continue + except Exception: + # Re-raise the mapped exception + raise verbose_logger.info(f"A2A send_message completed, request_id={request.id}") + # a2a_response is guaranteed to be set if we reach here (loop breaks on success or raises) + assert a2a_response is not None + # Wrap in LiteLLM response type for _hidden_params support response = LiteLLMSendMessageResponse.from_a2a_response(a2a_response) @@ -307,6 +352,48 @@ def send_message( ) +def _build_streaming_logging_obj( + request: "SendStreamingMessageRequest", + agent_name: str, + agent_id: Optional[str], + litellm_params: Optional[Dict[str, Any]], + metadata: Optional[Dict[str, Any]], + proxy_server_request: Optional[Dict[str, Any]], +) -> Logging: + """Build logging object for streaming A2A requests.""" + start_time = datetime.datetime.now() + model = f"a2a_agent/{agent_name}" + + logging_obj = Logging( + model=model, + messages=[{"role": "user", "content": "streaming-request"}], + stream=False, + call_type="asend_message_streaming", + start_time=start_time, + litellm_call_id=str(request.id), + function_id=str(request.id), + ) + logging_obj.model = model + logging_obj.custom_llm_provider = "a2a_agent" + logging_obj.model_call_details["model"] = model + logging_obj.model_call_details["custom_llm_provider"] = "a2a_agent" + if agent_id: + logging_obj.model_call_details["agent_id"] = agent_id + + _litellm_params = litellm_params.copy() if litellm_params else {} + if metadata: + _litellm_params["metadata"] = metadata + if proxy_server_request: + _litellm_params["proxy_server_request"] = proxy_server_request + + logging_obj.litellm_params = _litellm_params + logging_obj.optional_params = _litellm_params + logging_obj.model_call_details["litellm_params"] = _litellm_params + logging_obj.model_call_details["metadata"] = metadata or {} + + return logging_obj + + async def asend_message_streaming( a2a_client: Optional["A2AClientType"] = None, request: Optional["SendStreamingMessageRequest"] = None, @@ -403,55 +490,72 @@ async def asend_message_streaming( verbose_logger.info(f"A2A send_message_streaming request_id={request.id}") - # Track for logging - start_time = datetime.datetime.now() - stream = a2a_client.send_message_streaming(request) - # Build logging object for streaming completion callbacks agent_card = getattr(a2a_client, "_litellm_agent_card", None) or getattr( a2a_client, "agent_card", None ) + card_url = getattr(agent_card, "url", None) if agent_card else None agent_name = getattr(agent_card, "name", "unknown") if agent_card else "unknown" - model = f"a2a_agent/{agent_name}" - logging_obj = Logging( - model=model, - messages=[{"role": "user", "content": "streaming-request"}], - stream=False, # complete response logging after stream ends - call_type="asend_message_streaming", - start_time=start_time, - litellm_call_id=str(request.id), - function_id=str(request.id), - ) - logging_obj.model = model - logging_obj.custom_llm_provider = "a2a_agent" - logging_obj.model_call_details["model"] = model - logging_obj.model_call_details["custom_llm_provider"] = "a2a_agent" - if agent_id: - logging_obj.model_call_details["agent_id"] = agent_id - - # Propagate litellm_params for spend logging (includes cost_per_query, etc.) - _litellm_params = litellm_params.copy() if litellm_params else {} - # Merge metadata into litellm_params.metadata (required for proxy cost tracking) - if metadata: - _litellm_params["metadata"] = metadata - if proxy_server_request: - _litellm_params["proxy_server_request"] = proxy_server_request - - logging_obj.litellm_params = _litellm_params - logging_obj.optional_params = _litellm_params # used by cost calc - logging_obj.model_call_details["litellm_params"] = _litellm_params - logging_obj.model_call_details["metadata"] = metadata or {} - - iterator = A2AStreamingIterator( - stream=stream, + logging_obj = _build_streaming_logging_obj( request=request, - logging_obj=logging_obj, agent_name=agent_name, + agent_id=agent_id, + litellm_params=litellm_params, + metadata=metadata, + proxy_server_request=proxy_server_request, ) - async for chunk in iterator: - yield chunk + # Retry loop: if connection fails due to localhost URL in agent card, retry with fixed URL + # Connection errors in streaming typically occur on first chunk iteration + first_chunk = True + for attempt in range(2): # max 2 attempts: original + 1 retry + stream = a2a_client.send_message_streaming(request) + iterator = A2AStreamingIterator( + stream=stream, + request=request, + logging_obj=logging_obj, + agent_name=agent_name, + ) + + try: + first_chunk = True + async for chunk in iterator: + if first_chunk: + first_chunk = False # connection succeeded + yield chunk + return # stream completed successfully + except A2ALocalhostURLError as e: + # Only retry on first chunk, not mid-stream + if first_chunk and attempt == 0: + a2a_client = handle_a2a_localhost_retry( + error=e, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=True, + ) + card_url = agent_card.url if agent_card else None + else: + raise + except Exception as e: + # Only map exception on first chunk + if first_chunk and attempt == 0: + try: + map_a2a_exception(e, card_url, api_base, model=agent_name) + except A2ALocalhostURLError as localhost_err: + # Localhost URL error - fix and retry + a2a_client = handle_a2a_localhost_retry( + error=localhost_err, + agent_card=agent_card, + a2a_client=a2a_client, + is_streaming=True, + ) + card_url = agent_card.url if agent_card else None + continue + except Exception: + # Re-raise the mapped exception + raise + raise async def create_a2a_client( diff --git a/litellm/anthropic_beta_headers_config.json b/litellm/anthropic_beta_headers_config.json new file mode 100644 index 00000000000..193091c0176 --- /dev/null +++ b/litellm/anthropic_beta_headers_config.json @@ -0,0 +1,30 @@ +{ + "description": "Unsupported Anthropic beta headers for each provider. Headers listed here will be dropped. Headers not listed are passed through as-is.", + "anthropic": [], + "azure_ai": [], + "bedrock_converse": [ + "prompt-caching-scope-2026-01-05", + "bash_20250124", + "bash_20241022", + "text_editor_20250124", + "text_editor_20241022", + "compact-2026-01-12", + "advanced-tool-use-2025-11-20", + "web-fetch-2025-09-10", + "code-execution-2025-08-25", + "skills-2025-10-02", + "files-api-2025-04-14" + ], + "bedrock": [ + "advanced-tool-use-2025-11-20", + "prompt-caching-scope-2026-01-05", + "structured-outputs-2025-11-13", + "web-fetch-2025-09-10", + "code-execution-2025-08-25", + "skills-2025-10-02", + "files-api-2025-04-14" + ], + "vertex_ai": [ + "prompt-caching-scope-2026-01-05" + ] +} diff --git a/litellm/anthropic_beta_headers_manager.py b/litellm/anthropic_beta_headers_manager.py new file mode 100644 index 00000000000..2643f4c03fa --- /dev/null +++ b/litellm/anthropic_beta_headers_manager.py @@ -0,0 +1,221 @@ +""" +Centralized manager for Anthropic beta headers across different providers. + +This module provides utilities to: +1. Load beta header configuration from JSON (lists unsupported headers per provider) +2. Filter out unsupported beta headers +3. Handle provider-specific header name mappings (e.g., advanced-tool-use -> tool-search-tool) + +Design: +- JSON config lists UNSUPPORTED headers for each provider +- Headers not in the unsupported list are passed through +- Header mappings allow renaming headers for specific providers +""" + +import json +import os +from typing import Dict, List, Optional, Set + +from litellm.litellm_core_utils.litellm_logging import verbose_logger + +# Cache for the loaded configuration +_BETA_HEADERS_CONFIG: Optional[Dict] = None + + +def _load_beta_headers_config() -> Dict: + """ + Load the beta headers configuration from JSON file. + Uses caching to avoid repeated file reads. + + Returns: + Dict containing the beta headers configuration + """ + global _BETA_HEADERS_CONFIG + + if _BETA_HEADERS_CONFIG is not None: + return _BETA_HEADERS_CONFIG + + config_path = os.path.join( + os.path.dirname(__file__), + "anthropic_beta_headers_config.json" + ) + + try: + with open(config_path, "r") as f: + _BETA_HEADERS_CONFIG = json.load(f) + verbose_logger.debug(f"Loaded beta headers config from {config_path}") + return _BETA_HEADERS_CONFIG + except Exception as e: + verbose_logger.error(f"Failed to load beta headers config: {e}") + # Return empty config as fallback + return { + "anthropic": [], + "azure_ai": [], + "bedrock": [], + "bedrock_converse": [], + "vertex_ai": [] + } + + +def get_provider_name(provider: str) -> str: + """ + Resolve provider aliases to canonical provider names. + + Args: + provider: Provider name (may be an alias) + + Returns: + Canonical provider name + """ + config = _load_beta_headers_config() + aliases = config.get("provider_aliases", {}) + return aliases.get(provider, provider) + + +def filter_and_transform_beta_headers( + beta_headers: List[str], + provider: str, +) -> List[str]: + """ + Filter beta headers based on provider's unsupported list. + + This function: + 1. Removes headers that are in the provider's unsupported list + 2. Passes through all other headers as-is + + Note: Header transformations/mappings (e.g., advanced-tool-use -> tool-search-tool) + are handled in each provider's transformation code, not here. + + Args: + beta_headers: List of Anthropic beta header values + provider: Provider name (e.g., "anthropic", "bedrock", "vertex_ai") + + Returns: + List of filtered beta headers for the provider + """ + if not beta_headers: + return [] + + config = _load_beta_headers_config() + provider = get_provider_name(provider) + + # Get unsupported headers for this provider + unsupported_headers = set(config.get(provider, [])) + + filtered_headers: Set[str] = set() + + for header in beta_headers: + header = header.strip() + + # Skip if header is unsupported + if header in unsupported_headers: + verbose_logger.debug( + f"Dropping unsupported beta header '{header}' for provider '{provider}'" + ) + continue + + # Pass through as-is + filtered_headers.add(header) + + return sorted(list(filtered_headers)) + + +def is_beta_header_supported( + beta_header: str, + provider: str, +) -> bool: + """ + Check if a specific beta header is supported by a provider. + + Args: + beta_header: The Anthropic beta header value + provider: Provider name + + Returns: + True if the header is supported (not in unsupported list), False otherwise + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + unsupported_headers = set(config.get(provider, [])) + return beta_header not in unsupported_headers + + +def get_provider_beta_header( + anthropic_beta_header: str, + provider: str, +) -> Optional[str]: + """ + Check if a beta header is supported by a provider. + + Note: This does NOT handle header transformations/mappings. + Those are handled in each provider's transformation code. + + Args: + anthropic_beta_header: The Anthropic beta header value + provider: Provider name + + Returns: + The original header if supported, or None if unsupported + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + + # Check if unsupported + unsupported_headers = set(config.get(provider, [])) + if anthropic_beta_header in unsupported_headers: + return None + + return anthropic_beta_header + + +def update_headers_with_filtered_beta( + headers: dict, + provider: str, +) -> dict: + """ + Update headers dict by filtering and transforming anthropic-beta header values. + Modifies the headers dict in place and returns it. + + Args: + headers: Request headers dict (will be modified in place) + provider: Provider name + + Returns: + Updated headers dict + """ + existing_beta = headers.get("anthropic-beta") + if not existing_beta: + return headers + + # Parse existing beta headers + beta_values = [b.strip() for b in existing_beta.split(",") if b.strip()] + + # Filter and transform based on provider + filtered_beta_values = filter_and_transform_beta_headers( + beta_headers=beta_values, + provider=provider, + ) + + # Update or remove the header + if filtered_beta_values: + headers["anthropic-beta"] = ",".join(filtered_beta_values) + else: + # Remove the header if no values remain + headers.pop("anthropic-beta", None) + + return headers + + +def get_unsupported_headers(provider: str) -> List[str]: + """ + Get all beta headers that are unsupported by a provider. + + Args: + provider: Provider name + + Returns: + List of unsupported Anthropic beta header names + """ + config = _load_beta_headers_config() + provider = get_provider_name(provider) + return config.get(provider, []) diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py index ea7e3f5a979..03d09ecc041 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -1123,7 +1123,7 @@ class RedisCache(BaseCache): redis_client = redis_async.Redis(**self.redis_kwargs) # Test the connection - ping_result = await redis_client.ping() + ping_result = await redis_client.ping() # type: ignore[misc] # Close the connection await redis_client.aclose() # type: ignore[attr-defined] diff --git a/litellm/caching/redis_cluster_cache.py b/litellm/caching/redis_cluster_cache.py index 91fcf1d7288..664578c8700 100644 --- a/litellm/caching/redis_cluster_cache.py +++ b/litellm/caching/redis_cluster_cache.py @@ -83,7 +83,7 @@ class RedisClusterCache(RedisCache): ) # Test the connection - ping_result = await redis_client.ping() # type: ignore[attr-defined] + ping_result = await redis_client.ping() # type: ignore[attr-defined, misc] # Close the connection await redis_client.aclose() # type: ignore[attr-defined] diff --git a/litellm/constants.py b/litellm/constants.py index 872ad899f84..3c618723d64 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -306,6 +306,22 @@ DEFAULT_MAX_TOKENS_FOR_TRITON = int(os.getenv("DEFAULT_MAX_TOKENS_FOR_TRITON", 2 #### Networking settings #### request_timeout: float = float(os.getenv("REQUEST_TIMEOUT", 6000)) # time in seconds DEFAULT_A2A_AGENT_TIMEOUT: float = float(os.getenv("DEFAULT_A2A_AGENT_TIMEOUT", 6000)) # 10 minutes +# Patterns that indicate a localhost/internal URL in A2A agent cards that should be +# replaced with the original base_url. This is a common misconfiguration where +# developers deploy agents with development URLs in their agent cards. +LOCALHOST_URL_PATTERNS: List[str] = [ + "localhost", + "127.0.0.1", + "0.0.0.0", + "[::1]", # IPv6 localhost +] +# Patterns in error messages that indicate a connection failure +CONNECTION_ERROR_PATTERNS: List[str] = [ + "connect", + "connection", + "network", + "refused", +] STREAM_SSE_DONE_STRING: str = "[DONE]" STREAM_SSE_DATA_PREFIX: str = "data: " ### SPEND TRACKING ### @@ -970,6 +986,8 @@ BEDROCK_CONVERSE_MODELS = [ "openai.gpt-oss-120b-1:0", "anthropic.claude-haiku-4-5-20251001-v1:0", "anthropic.claude-sonnet-4-5-20250929-v1:0", + "anthropic.claude-opus-4-6-v1:0", + "anthropic.claude-opus-4-6-v1", "anthropic.claude-opus-4-1-20250805-v1:0", "anthropic.claude-opus-4-20250514-v1:0", "anthropic.claude-sonnet-4-20250514-v1:0", diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index bef4d52ce49..4ea22dbd90f 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -1,5 +1,6 @@ # What is this? ## File for 'response_cost' calculation in Logging +import logging import time from functools import lru_cache from typing import TYPE_CHECKING, Any, List, Literal, Optional, Tuple, Union, cast @@ -774,10 +775,11 @@ def _apply_cost_discount( discount_amount = original_cost * discount_percent final_cost = original_cost - discount_amount - verbose_logger.debug( - f"Applied {discount_percent*100}% discount to {custom_llm_provider}: " - f"${original_cost:.6f} -> ${final_cost:.6f} (saved ${discount_amount:.6f})" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Applied {discount_percent*100}% discount to {custom_llm_provider}: " + f"${original_cost:.6f} -> ${final_cost:.6f} (saved ${discount_amount:.6f})" + ) return final_cost, discount_percent, discount_amount @@ -807,17 +809,20 @@ def _apply_cost_margin( margin_config = None if custom_llm_provider and custom_llm_provider in litellm.cost_margin_config: margin_config = litellm.cost_margin_config[custom_llm_provider] - verbose_logger.debug( - f"Found provider-specific margin config for {custom_llm_provider}: {margin_config}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Found provider-specific margin config for {custom_llm_provider}: {margin_config}" + ) elif "global" in litellm.cost_margin_config: margin_config = litellm.cost_margin_config["global"] - verbose_logger.debug(f"Using global margin config: {margin_config}") + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug(f"Using global margin config: {margin_config}") else: - verbose_logger.debug( - f"No margin config found. Provider: {custom_llm_provider}, " - f"Available configs: {list(litellm.cost_margin_config.keys())}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"No margin config found. Provider: {custom_llm_provider}, " + f"Available configs: {list(litellm.cost_margin_config.keys())}" + ) if margin_config is not None: # Handle different margin config formats @@ -836,11 +841,12 @@ def _apply_cost_margin( final_cost = original_cost + margin_total_amount - verbose_logger.debug( - f"Applied margin to {custom_llm_provider or 'global'}: " - f"${original_cost:.6f} -> ${final_cost:.6f} " - f"(margin: {margin_percent*100 if margin_percent > 0 else 0}% + ${margin_fixed_amount:.6f} = ${margin_total_amount:.6f})" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"Applied margin to {custom_llm_provider or 'global'}: " + f"${original_cost:.6f} -> ${final_cost:.6f} " + f"(margin: {margin_percent*100 if margin_percent > 0 else 0}% + ${margin_fixed_amount:.6f} = ${margin_total_amount:.6f})" + ) return final_cost, margin_percent, margin_fixed_amount, margin_total_amount @@ -1021,9 +1027,10 @@ def completion_cost( # noqa: PLR0915 for idx, model in enumerate(potential_model_names): try: - verbose_logger.debug( - f"selected model name for cost calculation: {model}" - ) + if verbose_logger.isEnabledFor(logging.DEBUG): + verbose_logger.debug( + f"selected model name for cost calculation: {model}" + ) if completion_response is not None and ( isinstance(completion_response, BaseModel) @@ -1411,37 +1418,47 @@ def completion_cost( # noqa: PLR0915 # Apply discount from module-level config if configured original_cost = _final_cost - _final_cost, discount_percent, discount_amount = _apply_cost_discount( - base_cost=_final_cost, - custom_llm_provider=custom_llm_provider, - ) + if litellm.cost_discount_config: + _final_cost, discount_percent, discount_amount = _apply_cost_discount( + base_cost=_final_cost, + custom_llm_provider=custom_llm_provider, + ) + else: + discount_percent = 0.0 + discount_amount = 0.0 # Apply margin from module-level config if configured - ( - _final_cost, - margin_percent, - margin_fixed_amount, - margin_total_amount, - ) = _apply_cost_margin( - base_cost=_final_cost, - custom_llm_provider=custom_llm_provider, - ) + if litellm.cost_margin_config: + ( + _final_cost, + margin_percent, + margin_fixed_amount, + margin_total_amount, + ) = _apply_cost_margin( + base_cost=_final_cost, + custom_llm_provider=custom_llm_provider, + ) + else: + margin_percent = 0.0 + margin_fixed_amount = 0.0 + margin_total_amount = 0.0 # Store cost breakdown in logging object if available - _store_cost_breakdown_in_logging_obj( - litellm_logging_obj=litellm_logging_obj, - prompt_tokens_cost_usd_dollar=prompt_tokens_cost_usd_dollar, - completion_tokens_cost_usd_dollar=completion_tokens_cost_usd_dollar, - cost_for_built_in_tools_cost_usd_dollar=cost_for_built_in_tools, - total_cost_usd_dollar=_final_cost, - additional_costs=additional_costs, - original_cost=original_cost, - discount_percent=discount_percent, - discount_amount=discount_amount, - margin_percent=margin_percent, - margin_fixed_amount=margin_fixed_amount, - margin_total_amount=margin_total_amount, - ) + if litellm_logging_obj is not None: + _store_cost_breakdown_in_logging_obj( + litellm_logging_obj=litellm_logging_obj, + prompt_tokens_cost_usd_dollar=prompt_tokens_cost_usd_dollar, + completion_tokens_cost_usd_dollar=completion_tokens_cost_usd_dollar, + cost_for_built_in_tools_cost_usd_dollar=cost_for_built_in_tools, + total_cost_usd_dollar=_final_cost, + original_cost=original_cost, + additional_costs=additional_costs, + discount_percent=discount_percent, + discount_amount=discount_amount, + margin_percent=margin_percent, + margin_fixed_amount=margin_fixed_amount, + margin_total_amount=margin_total_amount, + ) return _final_cost except Exception as e: @@ -2116,3 +2133,5 @@ def handle_realtime_stream_cost_calculation( total_cost = input_cost_per_token + output_cost_per_token return total_cost + + diff --git a/litellm/experimental_mcp_client/client.py b/litellm/experimental_mcp_client/client.py index 3e8f9bc337b..5e21ff9754f 100644 --- a/litellm/experimental_mcp_client/client.py +++ b/litellm/experimental_mcp_client/client.py @@ -209,6 +209,8 @@ class MCPClient: headers["X-API-Key"] = self._mcp_auth_value elif self.auth_type == MCPAuth.authorization: headers["Authorization"] = self._mcp_auth_value + elif self.auth_type == MCPAuth.oauth2: + headers["Authorization"] = f"Bearer {self._mcp_auth_value}" elif isinstance(self._mcp_auth_value, dict): headers.update(self._mcp_auth_value) diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index 1652ec2aa0c..bbd55a59bce 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -268,6 +268,7 @@ class CustomGuardrail(CustomLogger): """ Returns the guardrail(s) to be run from the metadata or root """ + if "guardrails" in data: return data["guardrails"] metadata = data.get("litellm_metadata") or data.get("metadata", {}) diff --git a/litellm/integrations/email_templates/templates.py b/litellm/integrations/email_templates/templates.py index 5de23db0f24..091351df2bb 100644 --- a/litellm/integrations/email_templates/templates.py +++ b/litellm/integrations/email_templates/templates.py @@ -85,6 +85,30 @@ SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ The LiteLLM team
""" +TEAM_SOFT_BUDGET_ALERT_EMAIL_TEMPLATE = """ +
Hi {team_alias} team member,
+
+ Your LiteLLM team has crossed its soft budget limit of {soft_budget}.
+
+ Current Spend: {spend}
+ Soft Budget: {soft_budget}
+ {max_budget_info}
+
+
+ ⚠️ Note: Your API requests will continue to work, but you should monitor your usage closely. + If you reach your maximum budget, requests will be rejected. +
+ + You can view your usage and manage your budget in the LiteLLM Dashboard.+ + If you have any questions, please send an email to {email_support_contact}
+ + Best,
+ The LiteLLM team
+""" + MAX_BUDGET_ALERT_EMAIL_TEMPLATE = """