diff --git a/.circleci/config.yml b/.circleci/config.yml index eed94b77b93..3f61ed5fa91 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -1656,7 +1656,7 @@ jobs: - search_coverage.xml - search_coverage # Split litellm_mapped_tests into 3 parallel jobs for 3x faster execution - litellm_mapped_tests_proxy: + litellm_mapped_tests_proxy_part1: docker: - image: cimg/python:3.11 auth: @@ -1667,23 +1667,53 @@ jobs: steps: - setup_litellm_test_deps - run: - name: Run proxy tests + name: Run proxy tests part 1 (high-volume directories) command: | prisma generate - python -m pytest tests/test_litellm/proxy --cov=litellm --cov-report=xml --junitxml=test-results/junit-proxy.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING - no_output_timeout: 120m + export PYTHONUNBUFFERED=1 + python -m pytest tests/test_litellm/proxy/guardrails tests/test_litellm/proxy/management_endpoints tests/test_litellm/proxy/_experimental tests/test_litellm/proxy/client tests/test_litellm/proxy/auth --cov=litellm --cov-report=xml --junitxml=test-results/junit-proxy-part1.xml --durations=10 -n 8 --maxfail=5 --timeout=60 -vv --log-cli-level=WARNING -r A + no_output_timeout: 60m - run: name: Rename the coverage files command: | - mv coverage.xml litellm_proxy_tests_coverage.xml - mv .coverage litellm_proxy_tests_coverage + mv coverage.xml litellm_proxy_tests_part1_coverage.xml + mv .coverage litellm_proxy_tests_part1_coverage - store_test_results: path: test-results - persist_to_workspace: root: . paths: - - litellm_proxy_tests_coverage.xml - - litellm_proxy_tests_coverage + - litellm_proxy_tests_part1_coverage.xml + - litellm_proxy_tests_part1_coverage + litellm_mapped_tests_proxy_part2: + docker: + - image: cimg/python:3.11 + auth: + username: ${DOCKERHUB_USERNAME} + password: ${DOCKERHUB_PASSWORD} + working_directory: ~/project + resource_class: xlarge + steps: + - setup_litellm_test_deps + - run: + name: Run proxy tests part 2 (all other tests) + command: | + prisma generate + export PYTHONUNBUFFERED=1 + python -m pytest tests/test_litellm/proxy --ignore=tests/test_litellm/proxy/guardrails --ignore=tests/test_litellm/proxy/management_endpoints --ignore=tests/test_litellm/proxy/_experimental --ignore=tests/test_litellm/proxy/client --ignore=tests/test_litellm/proxy/auth --cov=litellm --cov-report=xml --junitxml=test-results/junit-proxy-part2.xml --durations=10 -n 8 --maxfail=5 --timeout=60 -vv --log-cli-level=WARNING -r A + no_output_timeout: 60m + - run: + name: Rename the coverage files + command: | + mv coverage.xml litellm_proxy_tests_part2_coverage.xml + mv .coverage litellm_proxy_tests_part2_coverage + - store_test_results: + path: test-results + - persist_to_workspace: + root: . + paths: + - litellm_proxy_tests_part2_coverage.xml + - litellm_proxy_tests_part2_coverage litellm_mapped_tests_llms: docker: - image: cimg/python:3.11 @@ -1724,7 +1754,7 @@ jobs: - run: name: Run core tests command: | - python -m pytest tests/test_litellm --ignore=tests/test_litellm/proxy --ignore=tests/test_litellm/llms --ignore=tests/test_litellm/integrations --ignore=tests/test_litellm/litellm_core_utils --cov=litellm --cov-report=xml --junitxml=test-results/junit-core.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING + python -m pytest tests/test_litellm --ignore=tests/test_litellm/proxy --ignore=tests/test_litellm/llms --ignore=tests/test_litellm/integrations --ignore=tests/test_litellm/litellm_core_utils --ignore=tests/test_litellm/experimental_mcp_client --cov=litellm --cov-report=xml --junitxml=test-results/junit-core.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING no_output_timeout: 120m - run: name: Rename the coverage files @@ -1765,6 +1795,33 @@ jobs: paths: - litellm_core_utils_tests_coverage.xml - litellm_core_utils_tests_coverage + litellm_mapped_tests_mcps: + docker: + - image: cimg/python:3.11 + auth: + username: ${DOCKERHUB_USERNAME} + password: ${DOCKERHUB_PASSWORD} + working_directory: ~/project + resource_class: xlarge + steps: + - setup_litellm_test_deps + - run: + name: Run MCP client tests + command: | + python -m pytest tests/test_litellm/experimental_mcp_client --cov=litellm --cov-report=xml --junitxml=test-results/junit-mcps.xml --durations=10 -n 4 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING + no_output_timeout: 120m + - run: + name: Rename the coverage files + command: | + mv coverage.xml litellm_mcps_tests_coverage.xml + mv .coverage litellm_mcps_tests_coverage + - store_test_results: + path: test-results + - persist_to_workspace: + root: . + paths: + - litellm_mcps_tests_coverage.xml + - litellm_mcps_tests_coverage litellm_mapped_tests_integrations: docker: - image: cimg/python:3.11 @@ -3597,6 +3654,7 @@ jobs: -p 4000:4000 \ -e DATABASE_URL=postgresql://postgres:postgres@host.docker.internal:5432/circle_test \ -e LITELLM_MASTER_KEY="sk-1234" \ + -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \ -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \ -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \ -e AWS_REGION_NAME="us-east-1" \ @@ -3653,7 +3711,7 @@ jobs: python -m venv venv . venv/bin/activate pip install coverage - coverage combine llm_translation_coverage realtime_translation_coverage llm_responses_api_coverage ocr_coverage search_coverage mcp_coverage logging_coverage audio_coverage litellm_router_coverage litellm_router_unit_coverage local_testing_part1_coverage local_testing_part2_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_part1_coverage litellm_proxy_unit_tests_part2_coverage image_gen_coverage pass_through_unit_tests_coverage batches_coverage litellm_security_tests_coverage guardrails_coverage litellm_mapped_tests_coverage + coverage combine llm_translation_coverage realtime_translation_coverage llm_responses_api_coverage ocr_coverage search_coverage mcp_coverage litellm_mcps_tests_coverage logging_coverage audio_coverage litellm_router_coverage litellm_router_unit_coverage local_testing_part1_coverage local_testing_part2_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_part1_coverage litellm_proxy_unit_tests_part2_coverage image_gen_coverage pass_through_unit_tests_coverage batches_coverage litellm_security_tests_coverage guardrails_coverage litellm_mapped_tests_coverage coverage xml - codecov/upload: file: ./coverage.xml @@ -4393,7 +4451,13 @@ workflows: only: - main - /litellm_.*/ - - litellm_mapped_tests_proxy: + - litellm_mapped_tests_proxy_part1: + filters: + branches: + only: + - main + - /litellm_.*/ + - litellm_mapped_tests_proxy_part2: filters: branches: only: @@ -4411,6 +4475,12 @@ workflows: only: - main - /litellm_.*/ + - litellm_mapped_tests_mcps: + filters: + branches: + only: + - main + - /litellm_.*/ - litellm_mapped_tests_integrations: filters: branches: @@ -4470,9 +4540,11 @@ workflows: - llm_responses_api_testing - ocr_testing - search_testing - - litellm_mapped_tests_proxy + - litellm_mapped_tests_proxy_part1 + - litellm_mapped_tests_proxy_part2 - litellm_mapped_tests_llms - litellm_mapped_tests_core + - litellm_mapped_tests_mcps - litellm_mapped_tests_integrations - litellm_mapped_tests_litellm_core_utils - litellm_mapped_enterprise_tests @@ -4549,9 +4621,11 @@ workflows: - llm_responses_api_testing - ocr_testing - search_testing - - litellm_mapped_tests_proxy + - litellm_mapped_tests_proxy_part1 + - litellm_mapped_tests_proxy_part2 - litellm_mapped_tests_llms - litellm_mapped_tests_core + - litellm_mapped_tests_mcps - litellm_mapped_tests_integrations - litellm_mapped_tests_litellm_core_utils - litellm_mapped_enterprise_tests diff --git a/.github/workflows/test-litellm-ui-build.yml b/.github/workflows/test-litellm-ui-build.yml new file mode 100644 index 00000000000..b0a8b648a44 --- /dev/null +++ b/.github/workflows/test-litellm-ui-build.yml @@ -0,0 +1,32 @@ +name: UI Build Check +permissions: + contents: read + +on: + pull_request: + branches: [main] + +jobs: + build-ui: + runs-on: ubuntu-latest + timeout-minutes: 10 + defaults: + run: + working-directory: ui/litellm-dashboard + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: "20" + cache: "npm" + cache-dependency-path: ui/litellm-dashboard/package-lock.json + + - name: Install dependencies + run: npm install + + - name: Build + run: npm run build diff --git a/.gitignore b/.gitignore index ddf5f6279b3..c43df98a9e5 100644 --- a/.gitignore +++ b/.gitignore @@ -2,6 +2,7 @@ .venv .venv_policy_test .env +.claude .newenv newenv/* litellm/proxy/myenv/* diff --git a/docs/my-website/blog/claude_code_beta_headers/index.md b/docs/my-website/blog/claude_code_beta_headers/index.md new file mode 100644 index 00000000000..138a85a60c5 --- /dev/null +++ b/docs/my-website/blog/claude_code_beta_headers/index.md @@ -0,0 +1,274 @@ +--- +slug: claude_code_beta_headers +title: "Claude Code - Managing Anthropic Beta Headers" +date: 2026-02-16T10:00:00 +authors: + - name: Sameer Kankute + title: SWE @ LiteLLM (LLM Translation) + url: https://www.linkedin.com/in/sameer-kankute/ + image_url: https://pbs.twimg.com/profile_images/2001352686994907136/ONgNuSk5_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 + - 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 +description: "How to manage and configure Anthropic beta headers with Claude Code in LiteLLM: filtering, mapping, and dynamic updates across providers." +tags: [anthropic, claude, beta headers, configuration, liteLLM] +hide_table_of_contents: false + +--- +import Image from '@theme/IdealImage'; + +When using Claude Code with LiteLLM and non-Anthropic providers (Bedrock, Azure AI, Vertex AI), you need to ensure that only supported beta headers are sent to each provider. This guide explains how to add support for new beta headers or fix invalid beta header errors. + +## What Are Beta Headers? + +Anthropic uses beta headers to enable experimental features in Claude. When you use Claude Code, it may send beta headers like: + +``` +anthropic-beta: prompt-caching-scope-2026-01-05,advanced-tool-use-2025-11-20 +``` + +However, not all providers support all Anthropic beta features. LiteLLM uses `anthropic_beta_headers_config.json` to manage which beta headers are supported by each provider. + +## Common Error Message + +```bash +Error: The model returned the following errors: invalid beta flag +``` + +## How LiteLLM Handles Beta Headers + +LiteLLM uses a strict validation approach with a configuration file: + +``` +litellm/litellm/anthropic_beta_headers_config.json +``` + +This JSON file contains a **mapping** of beta headers for each provider: +- **Keys**: Input beta header names (from Anthropic) +- **Values**: Provider-specific header names (or `null` if unsupported) +- **Validation**: Only headers present in the mapping with non-null values are forwarded + +This enforces stricter validation than just filtering unsupported headers - headers must be explicitly defined to be allowed. + +## Adding Support for a New Beta Header + +When Anthropic releases a new beta feature, you need to add it to the configuration file for each provider. + +### Step 1: Add the New Beta Header + +Open `anthropic_beta_headers_config.json` and add the new header to each provider's mapping: + +```json title="anthropic_beta_headers_config.json" +{ + "description": "Mapping of Anthropic beta headers for each provider. Keys are input header names, values are provider-specific header names (or null if unsupported). Only headers present in mapping keys with non-null values can be forwarded.", + "anthropic": { + "advanced-tool-use-2025-11-20": "advanced-tool-use-2025-11-20", + "new-feature-2026-03-01": "new-feature-2026-03-01", + ... + }, + "azure_ai": { + "advanced-tool-use-2025-11-20": "advanced-tool-use-2025-11-20", + "new-feature-2026-03-01": "new-feature-2026-03-01", + ... + }, + "bedrock_converse": { + "advanced-tool-use-2025-11-20": "tool-search-tool-2025-10-19", + "new-feature-2026-03-01": null, + ... + }, + "bedrock": { + "advanced-tool-use-2025-11-20": "tool-search-tool-2025-10-19", + "new-feature-2026-03-01": null, + ... + }, + "vertex_ai": { + "advanced-tool-use-2025-11-20": "tool-search-tool-2025-10-19", + "new-feature-2026-03-01": null, + ... + } +} +``` + +**Key Points:** +- **Supported headers**: Set the value to the provider-specific header name (often the same as the key) +- **Unsupported headers**: Set the value to `null` +- **Header transformations**: Some providers use different header names (e.g., Bedrock maps `advanced-tool-use-2025-11-20` to `tool-search-tool-2025-10-19`) +- **Alphabetical order**: Keep headers sorted alphabetically for maintainability + +### Step 2: Reload Configuration (No Restart Required!) + +**Option 1: Dynamic Reload Without Restart** + +Instead of restarting your application, you can dynamically reload the beta headers configuration using environment variables and API endpoints: + +```bash +# Set environment variable to fetch from remote URL (Do this if you want to point it to some other URL) +export LITELLM_ANTHROPIC_BETA_HEADERS_URL="https://raw.githubusercontent.com/BerriAI/litellm/main/litellm/anthropic_beta_headers_config.json" + +# Manually trigger reload via API (no restart needed!) +curl -X POST "https://your-proxy-url/reload/anthropic_beta_headers" \ + -H "Authorization: Bearer YOUR_ADMIN_TOKEN" +``` + +**Option 2: Schedule Automatic Reloads** + +Set up automatic reloading to always stay up-to-date with the latest beta headers: + +```bash +# Reload configuration every 24 hours +curl -X POST "https://your-proxy-url/schedule/anthropic_beta_headers_reload?hours=24" \ + -H "Authorization: Bearer YOUR_ADMIN_TOKEN" +``` + +**Option 3: Traditional Restart** + +If you prefer the traditional approach, restart your LiteLLM proxy or application: + +```bash +# If using LiteLLM proxy +litellm --config config.yaml + +# If using Python SDK +# Just restart your Python application +``` + +:::tip Zero-Downtime Updates +With dynamic reloading, you can fix invalid beta header errors **without restarting your service**! This is especially useful in production environments where downtime is costly. + +See [Auto Sync Anthropic Beta Headers](../proxy/sync_anthropic_beta_headers.md) for complete documentation. +::: + +## Fixing Invalid Beta Header Errors + +If you encounter an "invalid beta flag" error, it means a beta header is being sent that the provider doesn't support. + +### Step 1: Identify the Problematic Header + +Check your logs to see which header is causing the issue: + +```bash +Error: The model returned the following errors: invalid beta flag: new-feature-2026-03-01 +``` + +### Step 2: Update the Config + +Set the header value to `null` for that provider: + +```json title="anthropic_beta_headers_config.json" +{ + "bedrock_converse": { + "new-feature-2026-03-01": null + } +} +``` + +### Step 3: Restart and Test + +Restart your application and verify the header is now filtered out. + +## Contributing a Fix to LiteLLM + +Help the community by contributing your fix! + +### What to Include in Your PR + +1. **Update the config file**: Add the new beta header to `litellm/anthropic_beta_headers_config.json` +2. **Test your changes**: Verify the header is correctly filtered/mapped for each provider +3. **Documentation**: Include provider documentation links showing which headers are supported + +### Example PR Description + +```markdown +## Add support for new-feature-2026-03-01 beta header + +### Changes +- Added `new-feature-2026-03-01` to anthropic_beta_headers_config.json +- Set to `null` for bedrock_converse (unsupported) +- Set to header name for anthropic, azure_ai (supported) + +### Testing +Tested with: +- ✅ Anthropic: Header passed through correctly +- ✅ Azure AI: Header passed through correctly +- ✅ Bedrock Converse: Header filtered out (returns error without fix) + +### References +- Anthropic docs: [link] +- AWS Bedrock docs: [link] +``` + + +## How Beta Header Filtering Works + +When you make a request through LiteLLM: + +```mermaid +sequenceDiagram + participant CC as Claude Code + participant LP as LiteLLM + participant Config as Beta Headers Config + participant Provider as Provider (Bedrock/Azure/etc) + + CC->>LP: Request with beta headers + Note over CC,LP: anthropic-beta: header1,header2,header3 + + LP->>Config: Load header mapping for provider + Config-->>LP: Returns mapping (header→value or null) + + Note over LP: Validate & Transform:
1. Check if header exists in mapping
2. Filter out null values
3. Map to provider-specific names + + LP->>Provider: Request with filtered & mapped headers + Note over LP,Provider: anthropic-beta: mapped-header2
(header1, header3 filtered out) + + Provider-->>LP: Success response + LP-->>CC: Response +``` + +### Filtering Rules + +1. **Header must exist in mapping**: Unknown headers are filtered out +2. **Header must have non-null value**: Headers with `null` values are filtered out +3. **Header transformation**: Headers are mapped to provider-specific names (e.g., `advanced-tool-use-2025-11-20` → `tool-search-tool-2025-10-19` for Bedrock) + +### Example + +Request with headers: +``` +anthropic-beta: advanced-tool-use-2025-11-20,computer-use-2025-01-24,unknown-header +``` + +For Bedrock Converse: +- ✅ `computer-use-2025-01-24` → `computer-use-2025-01-24` (supported, passed through) +- ❌ `advanced-tool-use-2025-11-20` → filtered out (null value in config) +- ❌ `unknown-header` → filtered out (not in config) + +Result sent to Bedrock: +``` +anthropic-beta: computer-use-2025-01-24 +``` + +## Dynamic Configuration Management (No Restart Required!) + +### Environment Variables + +Control how LiteLLM loads the beta headers configuration: + +| Variable | Description | Default | +|----------|-------------|---------| +| `LITELLM_ANTHROPIC_BETA_HEADERS_URL` | URL to fetch config from | GitHub main branch | +| `LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS` | Set to `True` to use local config only | `False` | + +**Example: Use Custom Config URL** +```bash +export LITELLM_ANTHROPIC_BETA_HEADERS_URL="https://your-company.com/custom-beta-headers.json" +``` + +**Example: Use Local Config Only (No Remote Fetching)** +```bash +export LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS=True +``` diff --git a/docs/my-website/blog/claude_opus_4_6/index.md b/docs/my-website/blog/claude_opus_4_6/index.md index 82320472e13..e44420bd570 100644 --- a/docs/my-website/blog/claude_opus_4_6/index.md +++ b/docs/my-website/blog/claude_opus_4_6/index.md @@ -185,7 +185,7 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \ model_list: - model_name: claude-opus-4-6 litellm_params: - model: bedrock/anthropic.claude-opus-4-6-v1:0 + model: bedrock/anthropic.claude-opus-4-6-v1 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: us-east-1 diff --git a/docs/my-website/docs/projects/openai-agents.md b/docs/my-website/docs/projects/openai-agents.md index 95a2191b883..86983e7e510 100644 --- a/docs/my-website/docs/projects/openai-agents.md +++ b/docs/my-website/docs/projects/openai-agents.md @@ -1,22 +1,121 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; # OpenAI Agents SDK -The [OpenAI Agents SDK](https://github.com/openai/openai-agents-python) is a lightweight framework for building multi-agent workflows. -It includes an official LiteLLM extension that lets you use any of the 100+ supported providers (Anthropic, Gemini, Mistral, Bedrock, etc.) +Use OpenAI Agents SDK with any LLM provider through LiteLLM Proxy. + +The [OpenAI Agents SDK](https://github.com/openai/openai-agents-python) is a lightweight framework for building multi-agent workflows. It includes an official LiteLLM extension that lets you use any of the 100+ supported providers. + +## Quick Start + +### 1. Install Dependencies + +```bash +pip install "openai-agents[litellm]" +``` + +### 2. Add Model to Config + +```yaml title="config.yaml" +model_list: + - model_name: gpt-4o + litellm_params: + model: "openai/gpt-4o" + api_key: "os.environ/OPENAI_API_KEY" + + - model_name: claude-sonnet + litellm_params: + model: "anthropic/claude-3-5-sonnet-20241022" + api_key: "os.environ/ANTHROPIC_API_KEY" + + - model_name: gemini-pro + litellm_params: + model: "gemini/gemini-2.0-flash-exp" + api_key: "os.environ/GEMINI_API_KEY" +``` + +### 3. Start LiteLLM Proxy + +```bash +litellm --config config.yaml +``` + +### 4. Use with Proxy + + + ```python from agents import Agent, Runner from agents.extensions.models.litellm_model import LitellmModel +# Point to LiteLLM proxy agent = Agent( name="Assistant", instructions="You are a helpful assistant.", - model=LitellmModel(model="provider/model-name") + model=LitellmModel( + model="claude-sonnet", # Model from config.yaml + api_key="sk-1234", # LiteLLM API key + base_url="http://localhost:4000" + ) ) -result = Runner.run_sync(agent, "your_prompt_here") -print("Result:", result.final_output) +result = await Runner.run(agent, "What is LiteLLM?") +print(result.final_output) ``` -- [GitHub](https://github.com/openai/openai-agents-python) -- [LiteLLM Extension Docs](https://openai.github.io/openai-agents-python/ref/extensions/litellm/) + + + +```python +from agents import Agent, Runner +from agents.extensions.models.litellm_model import LitellmModel + +# Use any provider directly +agent = Agent( + name="Assistant", + instructions="You are a helpful assistant.", + model=LitellmModel( + model="anthropic/claude-3-5-sonnet-20241022", + api_key="your-anthropic-key" + ) +) + +result = await Runner.run(agent, "What is LiteLLM?") +print(result.final_output) +``` + + + + +## Track Usage + +Enable usage tracking to monitor token consumption: + +```python +from agents import Agent, ModelSettings +from agents.extensions.models.litellm_model import LitellmModel + +agent = Agent( + name="Assistant", + model=LitellmModel(model="claude-sonnet", api_key="sk-1234"), + model_settings=ModelSettings(include_usage=True) +) + +result = await Runner.run(agent, "Hello") +print(result.context_wrapper.usage) # Token counts +``` + +## Environment Variables + +| Variable | Value | Description | +|----------|-------|-------------| +| `LITELLM_BASE_URL` | `http://localhost:4000` | LiteLLM proxy URL | +| `LITELLM_API_KEY` | `sk-1234` | Your LiteLLM API key | + +## Related Resources + +- [OpenAI Agents SDK Documentation](https://openai.github.io/openai-agents-python/) +- [LiteLLM Extension Docs](https://openai.github.io/openai-agents-python/models/litellm/) +- [LiteLLM Proxy Quick Start](../proxy/quick_start) diff --git a/docs/my-website/docs/proxy/access_groups.md b/docs/my-website/docs/proxy/access_groups.md new file mode 100644 index 00000000000..59904575da8 --- /dev/null +++ b/docs/my-website/docs/proxy/access_groups.md @@ -0,0 +1,122 @@ +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Access Groups + +Access Groups simplify how you define and manage resource access across your organization. Instead of configuring models, MCP servers, and agents separately on each key or team, you create one group that bundles the resources you want to grant, then attach that group to your keys or teams. + +## Overview + +**Access Groups** let you define a reusable set of allowed resources—models, MCP servers, and agents—in a single place. One group can grant access to all three resource types. Simply attach the group to a key or team, and they get access to everything defined in that group. + +- **Unified resource control** – One group controls access to models, MCP servers, and agents together +- **Reusable** – Define once, attach to many keys or teams +- **Easy to maintain** – Update the group (add or remove resources) and all attached keys and teams automatically reflect the change +- **Clear visibility** – See exactly which resources each group grants and which keys/teams use it + + + +### How It Works + +**Key concept:** Define resources in a group → Attach group to key or team → Key/team gets access to all resources in the group + +| Resource Type | What the group controls | +| --------------- | -------------------------------------------------------------------- | +| **Models** | Which LLM models keys/teams can use (e.g., `gpt-4`, `claude-3-opus`) | +| **MCP Servers** | Which MCP servers are available for tool calling | +| **Agents** | Which agents can be invoked | + +## How to Create and Use Access Groups in the UI + +### 1. Navigate to Access Groups + +Go to the Admin UI (e.g. `http://localhost:4000/ui` or your `PROXY_BASE_URL/ui`) and click **Access Groups** in the sidebar. + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/d117fdb2-18c8-49e0-91e6-1f830d2d4b85/ascreenshot_f5822a0ddac64e3383124419d0c66298_text_export.jpeg) + +### 2. Create an Access Group + +Click **Create Access Group** and give your group a name. + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/aefb900d-d106-4436-806c-3608ad19659f/ascreenshot_3f6fed1256604fe3b7038a0778ce3342_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/0951bb93-61bd-477e-beaf-f58810f8980b/ascreenshot_f0fb5d552fd74ff8a1080e82758fcdc2_text_export.jpeg) + +### 3. Define Resources in the Group + +Use the tabs to select which models, MCP servers, and agents this group grants access to: + +- **Models tab** – Select the LLM models +- **MCP Servers tab** – Select MCP servers (for tool calling) +- **Agents tab** – Select agents + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/37398e8f-cd50-48c9-85e2-c77b2eeb994b/ascreenshot_440ec7906c8f4199b30ef91c903960b9_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/99d36543-8582-4bb7-a34d-3d5fe0fcf12f/ascreenshot_d9983240955c496892e1f7c38c074045_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/06fc5919-5c71-4fc3-999b-da7a4800af3f/ascreenshot_db93fdf742b249dc90a4b9d5991d6097_text_export.jpeg) + +### 4. Attach the Access Group to a Key + +When creating or editing a virtual key, expand **Optional Settings** and select your Access Group. The key will inherit access to all models, MCP servers, and agents defined in that group. + +1. Go to **Virtual Keys** and click **+ Create New Key** +2. Expand **Optional Settings** +3. In the Access Group field, select the group you created +4. Save the key + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/cdfa76ab-bf38-4ca4-a97d-2cb50fafe50b/ascreenshot_046daecb57554c28ba553cf6c01f5450_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/84f08e9c-e9d0-42aa-8317-f385190b6d7d/ascreenshot_2d239716d30f431d9ad494baf7933d6a_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/41d7b7f9-ac58-4602-b887-c35c9b419dce/ascreenshot_8abd4fef48014dd1b88848411e6d7912_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/e37b01c0-f2d7-4133-8b2f-ccc51f6769e1/ascreenshot_f495df428ad54cac9ec43b46c3dfc1b1_text_export.jpeg) + +![](https://colony-recorder.s3.amazonaws.com/files/2026-02-15/3fe33cad-6b64-46c3-a66e-6e6e073c3d7a/ascreenshot_f2dcc79ae8af47dd86ade2f85165d3c1_text_export.jpeg) + +### 5. Attach the Access Group to a Team + +You can also attach an Access Group to a team when creating or editing the team. All keys associated with that team will then have access to the resources defined in the group. + +## Use Cases + +### Team-based Access + +Create groups like "Engineering", "Data Science", or "Product" with the models, MCP servers, and agents each team needs. Attach the group to the team—no need to configure each resource on every key. + +### Environment Separation + +- **Production group** – Production models, approved MCP servers, and production agents +- **Development group** – Cost-efficient models, experimental MCP tools, and dev agents + +Attach the appropriate group to keys or teams based on environment. + +### Simplified Onboarding + +New developers get a key with an Access Group instead of manually configuring models, MCP servers, and agents. Add them to the right team or give them a key with the correct group. + +### Centralized Updates + +When you add a new model or MCP server to a group, every key and team attached to that group automatically gains access. Remove a resource from the group and it’s revoked everywhere at once. + +## Access Group vs. Model Access Groups + +LiteLLM has two related concepts: + +| Feature | **Access Groups** (this page) | **Model Access Groups** | +| ---------- | ----------------------------------------------------------------------- | ------------------------------------------------------- | +| Definition | Define in the UI; one group can include models, MCP servers, and agents | Defined in config or via API; groups are model-centric | +| Scope | Models + MCP servers + agents | Models only | +| Attach to | Keys, teams | Keys, teams | +| Use when | You want unified control over models, MCP, and agents from the UI | You need config-based or API-based model access control | + +For config-based model access with `access_groups` in `model_info`, see [Model Access Groups](./model_access_groups.md). + +## Related Documentation + +- [Virtual Keys](./virtual_keys.md) – Creating and managing API keys +- [Role-based Access Controls](./access_control.md) – Organizations, teams, and user roles +- [Model Access Groups](./model_access_groups.md) – Config-based model access groups +- [MCP Control](../mcp_control.md) – MCP server setup and access control diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md index d563adcaa74..5e3f56c4206 100644 --- a/docs/my-website/docs/proxy/config_settings.md +++ b/docs/my-website/docs/proxy/config_settings.md @@ -520,6 +520,7 @@ router_settings: | DEBUG_OTEL | Enable debug mode for OpenTelemetry | DEFAULT_ALLOWED_FAILS | Maximum failures allowed before cooling down a model. Default is 3 | DEFAULT_A2A_AGENT_TIMEOUT | Default timeout in seconds for A2A (Agent-to-Agent) protocol requests. Default is 6000 +| DEFAULT_ACCESS_GROUP_CACHE_TTL | Time-to-live in seconds for cached access group information. Default is 600 (10 minutes) | DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS | Default maximum tokens for Anthropic chat completions. Default is 4096 | DEFAULT_BATCH_SIZE | Default batch size for operations. Default is 512 | DEFAULT_CHUNK_OVERLAP | Default chunk overlap for RAG text splitters. Default is 200 @@ -548,6 +549,7 @@ router_settings: | DEFAULT_MCP_SEMANTIC_FILTER_EMBEDDING_MODEL | Default embedding model for MCP semantic tool filtering. Default is "text-embedding-3-small" | DEFAULT_MCP_SEMANTIC_FILTER_SIMILARITY_THRESHOLD | Default similarity threshold for MCP semantic tool filtering. Default is 0.3 | DEFAULT_MCP_SEMANTIC_FILTER_TOP_K | Default number of top results to return for MCP semantic tool filtering. Default is 10 +| MCP_NPM_CACHE_DIR | Directory for npm cache used by STDIO MCP servers. In containers the default (~/.npm) may not exist or be read-only. Default is `/tmp/.npm_mcp_cache` | MCP_OAUTH2_TOKEN_CACHE_DEFAULT_TTL | Default TTL in seconds for MCP OAuth2 token cache. Default is 3600 | MCP_OAUTH2_TOKEN_CACHE_MAX_SIZE | Maximum number of entries in MCP OAuth2 token cache. Default is 200 | MCP_OAUTH2_TOKEN_CACHE_MIN_TTL | Minimum TTL in seconds for MCP OAuth2 token cache. Default is 10 @@ -745,10 +747,12 @@ router_settings: | LITERAL_API_KEY | API key for Literal integration | LITERAL_API_URL | API URL for Literal service | LITERAL_BATCH_SIZE | Batch size for Literal operations +| LITELLM_ANTHROPIC_BETA_HEADERS_URL | Custom URL for fetching Anthropic beta headers configuration. Default is the GitHub main branch URL | LITELLM_ANTHROPIC_DISABLE_URL_SUFFIX | Disable automatic URL suffix appending for Anthropic API base URLs. When set to `true`, prevents LiteLLM from automatically adding `/v1/messages` or `/v1/complete` to custom Anthropic API endpoints | LITELLM_ASSETS_PATH | Path to directory for UI assets and logos. Used when running with read-only filesystem (e.g., Kubernetes). Default is `/var/lib/litellm/assets` in Docker. | LITELLM_CLI_JWT_EXPIRATION_HOURS | Expiration time in hours for CLI-generated JWT tokens. Default is 24 hours | LITELLM_DD_AGENT_HOST | Hostname or IP of DataDog agent for LiteLLM-specific logging. When set, logs are sent to agent instead of direct API +| LITELLM_DEPLOYMENT_ENVIRONMENT | Environment name for the deployment (e.g., "production", "staging"). Used as a fallback when OTEL_ENVIRONMENT_NAME is not set. Sets the `environment` tag in telemetry data | LITELLM_DD_AGENT_PORT | Port of DataDog agent for LiteLLM-specific log intake. Default is 10518 | LITELLM_DD_LLM_OBS_PORT | Port for Datadog LLM Observability agent. Default is 8126 | LITELLM_DONT_SHOW_FEEDBACK_BOX | Flag to hide feedback box in LiteLLM UI @@ -765,7 +769,9 @@ router_settings: | LITELM_ENVIRONMENT | Environment of LiteLLM Instance, used by logging services. Currently only used by DeepEval. | LITELLM_KEY_ROTATION_ENABLED | Enable auto-key rotation for LiteLLM (boolean). Default is false. | LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS | Interval in seconds for how often to run job that auto-rotates keys. Default is 86400 (24 hours). +| LITELLM_KEY_ROTATION_GRACE_PERIOD | Duration to keep old key valid after rotation (e.g. "24h", "2d"). Default is empty (immediate revoke). Used for scheduled rotations and as fallback when not specified in regenerate request. | LITELLM_LICENSE | License key for LiteLLM usage +| LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS | Set to `True` to use the local bundled Anthropic beta headers config only, disabling remote fetching. Default is `False` | LITELLM_LOCAL_MODEL_COST_MAP | Local configuration for model cost mapping in LiteLLM | LITELLM_LOCAL_POLICY_TEMPLATES | When set to "true", uses local backup policy templates instead of fetching from GitHub. Policy templates are fetched from https://raw.githubusercontent.com/BerriAI/litellm/main/policy_templates.json by default, with automatic fallback to local backup on failure | LITELLM_LOG | Enable detailed logging for LiteLLM diff --git a/docs/my-website/docs/proxy/guardrails/policy_templates.md b/docs/my-website/docs/proxy/guardrails/policy_templates.md index 6c2da70560a..f0c93ca44c7 100644 --- a/docs/my-website/docs/proxy/guardrails/policy_templates.md +++ b/docs/my-website/docs/proxy/guardrails/policy_templates.md @@ -16,8 +16,6 @@ Policy templates provide pre-configured guardrail policies that you can use as a 6. Review and customize the pre-filled policy form 7. Click **"Create Policy"** to save -![Policy Templates UI](/img/policy_templates_ui.png) - ### Workflow ``` diff --git a/docs/my-website/docs/proxy/logging.md b/docs/my-website/docs/proxy/logging.md index 56fb420e6cf..1abb127dfda 100644 --- a/docs/my-website/docs/proxy/logging.md +++ b/docs/my-website/docs/proxy/logging.md @@ -1338,6 +1338,7 @@ litellm_settings: s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY # AWS Secret Access Key for S3 s3_path: my-test-path # [OPTIONAL] set path in bucket you want to write logs to s3_endpoint_url: https://s3.amazonaws.com # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 buckets + s3_use_virtual_hosted_style: false # [OPTIONAL] use virtual-hosted-style URLs (bucket.endpoint/key) instead of path-style (endpoint/bucket/key). Useful for S3-compatible services like MinIO s3_strip_base64_files: false # [OPTIONAL] remove base64 files before storing in s3 ``` diff --git a/docs/my-website/docs/proxy/virtual_keys.md b/docs/my-website/docs/proxy/virtual_keys.md index 38ff4ede280..c74aa75ff4a 100644 --- a/docs/my-website/docs/proxy/virtual_keys.md +++ b/docs/my-website/docs/proxy/virtual_keys.md @@ -549,11 +549,14 @@ curl 'http://localhost:4000/key/sk-1234/regenerate' \ "models": [ "gpt-4", "gpt-3.5-turbo" - ] + ], + "grace_period": "48h" }' ``` +**Grace period (optional)**: Set `grace_period` (e.g. `"24h"`, `"2d"`, `"1w"`) to keep the old key valid for a transitional period. Both old and new keys work until the grace period elapses, enabling seamless cutover without production downtime. Omitted or empty = immediate revoke. Can also be set via `LITELLM_KEY_ROTATION_GRACE_PERIOD` env var for scheduled rotations. + **Read More** - [Write rotated keys to secrets manager](https://docs.litellm.ai/docs/secret#aws-secret-manager) @@ -640,11 +643,13 @@ Set these environment variables when starting the proxy: |----------|-------------|---------| | `LITELLM_KEY_ROTATION_ENABLED` | Enable the rotation worker | `false` | | `LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS` | How often to scan for keys to rotate (in seconds) | `86400` (24 hours) | +| `LITELLM_KEY_ROTATION_GRACE_PERIOD` | Duration to keep old key valid after rotation (e.g. `24h`, `2d`) | `""` (immediate revoke) | **Example:** ```bash export LITELLM_KEY_ROTATION_ENABLED=true export LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS=3600 # Check every hour +export LITELLM_KEY_ROTATION_GRACE_PERIOD=48h # Keep old key valid for 48h during cutover litellm --config config.yaml ``` diff --git a/docs/my-website/img/release_notes/guard_actions.png b/docs/my-website/img/release_notes/guard_actions.png new file mode 100644 index 00000000000..ef705828188 Binary files /dev/null and b/docs/my-website/img/release_notes/guard_actions.png differ diff --git a/docs/my-website/img/ui_access_groups.png b/docs/my-website/img/ui_access_groups.png new file mode 100644 index 00000000000..484f6c852fc Binary files /dev/null and b/docs/my-website/img/ui_access_groups.png differ diff --git a/docs/my-website/package-lock.json b/docs/my-website/package-lock.json index 419211cca02..3ba42bc5023 100644 --- a/docs/my-website/package-lock.json +++ b/docs/my-website/package-lock.json @@ -20455,6 +20455,13 @@ "url": "https://opencollective.com/webpack" } }, + "node_modules/search-insights": { + "version": "2.17.3", + "resolved": "https://registry.npmjs.org/search-insights/-/search-insights-2.17.3.tgz", + "integrity": "sha512-RQPdCYTa8A68uM2jwxoY842xDhvx3E5LFL1LxvxCNMev4o5mLuokczhzjAgGwUZBAmOKZknArSxLKmXtIi2AxQ==", + "license": "MIT", + "peer": true + }, "node_modules/section-matter": { "version": "1.0.0", "resolved": "https://registry.npmjs.org/section-matter/-/section-matter-1.0.0.tgz", diff --git a/docs/my-website/release_notes/v1.81.12.md b/docs/my-website/release_notes/v1.81.12.md new file mode 100644 index 00000000000..c68b23488c0 --- /dev/null +++ b/docs/my-website/release_notes/v1.81.12.md @@ -0,0 +1,433 @@ +--- +title: "[Preview] v1.81.12 - Guardrail Policy Templates & Action Builder" +slug: "v1-81-12" +date: 2026-02-14T00:00:00 +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'; + + + + +``` showLineNumbers title="docker run litellm" +docker run \ +-e STORE_MODEL_IN_DB=True \ +-p 4000:4000 \ +ghcr.io/berriai/litellm:main-v1.81.12.rc.1 +``` + + + + +``` showLineNumbers title="pip install litellm" +pip install litellm==1.81.12.rc1 +``` + + + + +## Key Highlights + +- **Policy Templates** - [Pre-configured guardrail policy templates for common safety and compliance use-cases (including NSFW, toxic content, and child safety)](../../docs/proxy/guardrails/policy_templates) +- **Guardrail Action Builder** - [Build and customize guardrail policy flows with the new action-builder UI and conditional execution support](../../docs/proxy/guardrails/policy_templates) +- **MCP OAuth2 M2M + Tracing** - [Add machine-to-machine OAuth2 support for MCP servers and OpenTelemetry tracing for MCP calls through AI Gateway](../../docs/mcp) +- **Responses API `shell` Tool & `context_management` support** - [Server-side context management (compaction) and Shell tool support for the OpenAI Responses API](../../docs/response_api) +- **Access Groups** - [Create access groups to manage model, MCP server, and agent access across teams and keys](../../docs/proxy/access_groups) +- **50+ New Bedrock Regional Model Entries** - DeepSeek V3.2, MiniMax M2.1, Kimi K2.5, Qwen3 Coder Next, and NVIDIA Nemotron Nano across multiple regions +- **Add Semgrep & fix OOMs** - [Static analysis rules and out-of-memory fixes](#add-semgrep--fix-ooms) - [PR #20912](https://github.com/BerriAI/litellm/pull/20912) + +--- + +## Add Semgrep & fix OOMs + +This release fixes out-of-memory (OOM) risks from unbounded `asyncio.Queue()` usage. Log queues (e.g. GCS bucket) and DB spend-update queues were previously unbounded and could grow without limit under load. They now use a configurable max size (`LITELLM_ASYNCIO_QUEUE_MAXSIZE`, default 1000); when full, queues flush immediately to make room instead of growing memory. A Semgrep rule (`.semgrep/rules/python/unbounded-memory.yml`) was added to flag similar unbounded-memory patterns in future code. [PR #20912](https://github.com/BerriAI/litellm/pull/20912) + +--- + +## Guardrail Action Builder + +This release adds a visual action builder for guardrail policies with conditional execution support. You can now chain guardrails into multi-step pipelines — if a simple guardrail fails, route to an advanced one instead of immediately blocking. Each step has configurable ON PASS and ON FAIL actions (Next Step, Block, or Allow), and you can test the full pipeline with a sample message before saving. + +![Guardrail Action Builder](../img/release_notes/guard_actions.png) + +### Access Groups + +Access Groups simplify defining resource access across your organization. One group can grant access to models, MCP servers, and agents—simply attach it to a key or team. Create groups in the Admin UI, define which resources each group includes, then assign the group when creating keys or teams. Updates to a group apply automatically to all attached keys and teams. + + + +## New Providers and Endpoints + +### New Providers (2 new providers) + +| Provider | Supported LiteLLM Endpoints | Description | +| -------- | --------------------------- | ----------- | +| [Scaleway](../../docs/providers/scaleway) | `/chat/completions` | Scaleway Generative APIs for chat completions | +| [Sarvam AI](../../docs/providers/sarvam) | `/chat/completions`, `/audio/transcriptions`, `/audio/speech` | Sarvam AI STT and TTS support for Indian languages | + +--- + +## New Models / Updated Models + +#### New Model Support (19 highlighted models) + +| Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) | +| -------- | ----- | -------------- | ------------------- | -------------------- | +| AWS Bedrock | `deepseek.v3.2` | 164K | $0.62 | $1.85 | +| AWS Bedrock | `minimax.minimax-m2.1` | 196K | $0.30 | $1.20 | +| AWS Bedrock | `moonshotai.kimi-k2.5` | 262K | $0.60 | $3.00 | +| AWS Bedrock | `moonshotai.kimi-k2-thinking` | 262K | $0.73 | $3.03 | +| AWS Bedrock | `qwen.qwen3-coder-next` | 262K | $0.50 | $1.20 | +| AWS Bedrock | `nvidia.nemotron-nano-3-30b` | 262K | $0.06 | $0.24 | +| Azure AI | `azure_ai/kimi-k2.5` | 262K | $0.60 | $3.00 | +| Vertex AI | `vertex_ai/zai-org/glm-5-maas` | 200K | $1.00 | $3.20 | +| MiniMax | `minimax/MiniMax-M2.5` | 1M | $0.30 | $1.20 | +| MiniMax | `minimax/MiniMax-M2.5-lightning` | 1M | $0.30 | $2.40 | +| Dashscope | `dashscope/qwen3-max` | 258K | Tiered pricing | Tiered pricing | +| Perplexity | `perplexity/preset/pro-search` | - | Per-request | Per-request | +| Perplexity | `perplexity/openai/gpt-4o` | - | Per-request | Per-request | +| Perplexity | `perplexity/openai/gpt-5.2` | - | Per-request | Per-request | +| Vercel AI Gateway | `vercel_ai_gateway/anthropic/claude-opus-4.6` | 200K | $5.00 | $25.00 | +| Vercel AI Gateway | `vercel_ai_gateway/anthropic/claude-sonnet-4` | 200K | $3.00 | $15.00 | +| Vercel AI Gateway | `vercel_ai_gateway/anthropic/claude-haiku-4.5` | 200K | $1.00 | $5.00 | +| Sarvam AI | `sarvam/sarvam-m` | 8K | Free tier | Free tier | +| Anthropic | `fast/claude-opus-4-6` | 1M | $30.00 | $150.00 | + +*Note: AWS Bedrock models are available across multiple regions (us-east-1, us-east-2, us-west-2, eu-central-1, eu-north-1, ap-northeast-1, ap-south-1, ap-southeast-3, sa-east-1). 54 regional model entries were added in total.* + +#### Features + +- **[Anthropic](../../docs/providers/anthropic)** + - Enable non-tool structured outputs on Claude Opus 4.5 and 4.6 using `output_format` param - [PR #20548](https://github.com/BerriAI/litellm/pull/20548) + - Add support for `anthropic_messages` call type in prompt caching - [PR #19233](https://github.com/BerriAI/litellm/pull/19233) + - Managing Anthropic Beta Headers with remote URL fetching - [PR #20935](https://github.com/BerriAI/litellm/pull/20935), [PR #21110](https://github.com/BerriAI/litellm/pull/21110) + - Remove `x-anthropic-billing` block - [PR #20951](https://github.com/BerriAI/litellm/pull/20951) + - Use Authorization Bearer for OAuth tokens instead of x-api-key - [PR #21039](https://github.com/BerriAI/litellm/pull/21039) + - Filter unsupported JSON schema constraints for structured outputs - [PR #20813](https://github.com/BerriAI/litellm/pull/20813) + - New Claude Opus 4.6 features for `/v1/messages` - [PR #20733](https://github.com/BerriAI/litellm/pull/20733) + - Fix `reasoning_effort=None` and `"none"` should return None for Opus 4.6 - [PR #20800](https://github.com/BerriAI/litellm/pull/20800) + +- **[AWS Bedrock](../../docs/providers/bedrock)** + - Extend model support with 4 new beta models - [PR #21035](https://github.com/BerriAI/litellm/pull/21035) + - Add Claude Opus 4.6 to `_supports_tool_search_on_bedrock` - [PR #21017](https://github.com/BerriAI/litellm/pull/21017) + - Correct Bedrock Claude Opus 4.6 model IDs (remove `:0` suffix) - [PR #20564](https://github.com/BerriAI/litellm/pull/20564), [PR #20671](https://github.com/BerriAI/litellm/pull/20671) + - Add `output_config` as supported param - [PR #20748](https://github.com/BerriAI/litellm/pull/20748) + +- **[Vertex AI](../../docs/providers/vertex)** + - Add Vertex GLM-5 model support - [PR #21053](https://github.com/BerriAI/litellm/pull/21053) + - Propagate `extra_headers` anthropic-beta to request body - [PR #20666](https://github.com/BerriAI/litellm/pull/20666) + - Preserve `usageMetadata` in `_hidden_params` - [PR #20559](https://github.com/BerriAI/litellm/pull/20559) + - Map `IMAGE_PROHIBITED_CONTENT` to `content_filter` - [PR #20524](https://github.com/BerriAI/litellm/pull/20524) + - Add RAG ingest for Vertex AI - [PR #21120](https://github.com/BerriAI/litellm/pull/21120) + +- **[OCI / Cohere](../../docs/providers/cohere)** + - OCI Cohere responseFormat/Pydantic support - [PR #20663](https://github.com/BerriAI/litellm/pull/20663) + - Fix OCI Cohere system messages by populating `preambleOverride` - [PR #20958](https://github.com/BerriAI/litellm/pull/20958) + +- **[Perplexity](../../docs/providers/perplexity)** + - Perplexity Research API support with preset search - [PR #20860](https://github.com/BerriAI/litellm/pull/20860) + +- **[MiniMax](../../docs/providers/minimax)** + - Add MiniMax-M2.5 and MiniMax-M2.5-lightning models - [PR #21054](https://github.com/BerriAI/litellm/pull/21054) + +- **[Kimi / Moonshot](../../docs/providers/moonshot)** + - Add Kimi model pricing by region - [PR #20855](https://github.com/BerriAI/litellm/pull/20855) + - Add `moonshotai.kimi-k2.5` - [PR #20863](https://github.com/BerriAI/litellm/pull/20863) + +- **[Dashscope](../../docs/providers/dashscope)** + - Add `dashscope/qwen3-max` model with tiered pricing - [PR #20919](https://github.com/BerriAI/litellm/pull/20919) + +- **[Vercel AI Gateway](../../docs/providers/vercel_ai_gateway)** + - Add new Vercel AI Anthropic models - [PR #20745](https://github.com/BerriAI/litellm/pull/20745) + +- **[Azure AI](../../docs/providers/azure_ai)** + - Add `azure_ai/kimi-k2.5` to Azure model DB - [PR #20896](https://github.com/BerriAI/litellm/pull/20896) + - Support Azure AD token auth for non-Claude azure_ai models - [PR #20981](https://github.com/BerriAI/litellm/pull/20981) + - Fix Azure batches issues - [PR #21092](https://github.com/BerriAI/litellm/pull/21092) + +- **[DeepSeek](../../docs/providers/deepseek)** + - Sync DeepSeek model metadata and add bare-name fallback - [PR #20938](https://github.com/BerriAI/litellm/pull/20938) + +- **[Gemini](../../docs/providers/gemini)** + - Handle image in assistant message for Gemini - [PR #20845](https://github.com/BerriAI/litellm/pull/20845) + - Add missing tpm/rpm for Gemini models - [PR #21175](https://github.com/BerriAI/litellm/pull/21175) + +- **General** + - Add 30 missing models to pricing JSON - [PR #20797](https://github.com/BerriAI/litellm/pull/20797) + - Cleanup 39 deprecated OpenRouter models - [PR #20786](https://github.com/BerriAI/litellm/pull/20786) + - Standardize endpoint `display_name` naming convention - [PR #20791](https://github.com/BerriAI/litellm/pull/20791) + - Fix and stabilize model cost map formatting - [PR #20895](https://github.com/BerriAI/litellm/pull/20895) + - Export `PermissionDeniedError` from `litellm.__init__` - [PR #20960](https://github.com/BerriAI/litellm/pull/20960) + +### Bug Fixes + +- **[Anthropic](../../docs/providers/anthropic)** + - Fix `get_supported_anthropic_messages_params` - [PR #20752](https://github.com/BerriAI/litellm/pull/20752) + - Fix `base_model` name for body and deployment name in URL - [PR #20747](https://github.com/BerriAI/litellm/pull/20747) + +- **[Azure](../../docs/providers/azure/azure)** + - Preserve `content_policy_violation` error details from Azure OpenAI - [PR #20883](https://github.com/BerriAI/litellm/pull/20883) + +- **[Vertex AI](../../docs/providers/vertex)** + - Fix Gemini multi-turn tool calling message formatting (added and reverted) - [PR #20569](https://github.com/BerriAI/litellm/pull/20569), [PR #21051](https://github.com/BerriAI/litellm/pull/21051) + +--- + +## LLM API Endpoints + +#### Features + +- **[Responses API](../../docs/response_api)** + - Add server-side context management (compaction) support - [PR #21058](https://github.com/BerriAI/litellm/pull/21058) + - Add Shell tool support for OpenAI Responses API - [PR #21063](https://github.com/BerriAI/litellm/pull/21063) + - Preserve tool call argument deltas when streaming id is omitted - [PR #20712](https://github.com/BerriAI/litellm/pull/20712) + - Preserve interleaved thinking/redacted_thinking blocks during streaming - [PR #20702](https://github.com/BerriAI/litellm/pull/20702) + +- **[Chat Completions](../../docs/completion/input)** + - Add Web Search support using LiteLLM `/search` (web search interception hook) - [PR #20483](https://github.com/BerriAI/litellm/pull/20483) + - Preserved nullable object fields by carrying schema properties - [PR #19132](https://github.com/BerriAI/litellm/pull/19132) + - Support `prompt_cache_key` for OpenAI and Azure chat completions - [PR #20989](https://github.com/BerriAI/litellm/pull/20989) + +- **[Pass-Through Endpoints](../../docs/pass_through/bedrock)** + - Add support for `langchain_aws` via LiteLLM passthrough - [PR #20843](https://github.com/BerriAI/litellm/pull/20843) + - Add `custom_body` parameter to `endpoint_func` in `create_pass_through_route` - [PR #20849](https://github.com/BerriAI/litellm/pull/20849) + +- **[Vector Stores](../../docs/providers/openai)** + - Add `target_model_names` for vector store endpoints - [PR #21089](https://github.com/BerriAI/litellm/pull/21089) + +- **General** + - Add `output_config` as supported param - [PR #20748](https://github.com/BerriAI/litellm/pull/20748) + - Add managed error file support - [PR #20838](https://github.com/BerriAI/litellm/pull/20838) + +#### Bugs + +- **General** + - Stop leaking Python tracebacks in streaming SSE error responses - [PR #20850](https://github.com/BerriAI/litellm/pull/20850) + - Fix video list pagination cursors not encoded with provider metadata - [PR #20710](https://github.com/BerriAI/litellm/pull/20710) + - Handle `metadata=None` in SDK path retry/error logic - [PR #20873](https://github.com/BerriAI/litellm/pull/20873) + - Fix Spend logs pickle error with Pydantic models and redaction - [PR #20685](https://github.com/BerriAI/litellm/pull/20685) + - Remove duplicate `PerplexityResponsesConfig` from `LLM_CONFIG_NAMES` - [PR #21105](https://github.com/BerriAI/litellm/pull/21105) + +--- + +## Management Endpoints / UI + +#### Features + +- **Access Groups** + - New Access Groups feature for managing model, MCP server, and agent access - [PR #21022](https://github.com/BerriAI/litellm/pull/21022) + - Access Groups table and details page UI - [PR #21165](https://github.com/BerriAI/litellm/pull/21165) + - Refactor `model_ids` to `model_names` for backwards compatibility - [PR #21166](https://github.com/BerriAI/litellm/pull/21166) + +- **Policies** + - Allow connecting Policies to Tags, simulating Policies, viewing key/team counts - [PR #20904](https://github.com/BerriAI/litellm/pull/20904) + - Guardrail pipeline support for conditional sequential execution - [PR #21177](https://github.com/BerriAI/litellm/pull/21177) + - Pipeline flow builder UI for guardrail policies - [PR #21188](https://github.com/BerriAI/litellm/pull/21188) + +- **SSO / Auth** + - New Login With SSO Button - [PR #20908](https://github.com/BerriAI/litellm/pull/20908) + - M2M OAuth2 UI Flow - [PR #20794](https://github.com/BerriAI/litellm/pull/20794) + - Allow Organization and Team Admins to call `/invitation/new` - [PR #20987](https://github.com/BerriAI/litellm/pull/20987) + - Invite User: Email Integration Alert - [PR #20790](https://github.com/BerriAI/litellm/pull/20790) + - Populate identity fields in proxy admin JWT early-return path - [PR #21169](https://github.com/BerriAI/litellm/pull/21169) + +- **Spend Logs** + - Show predefined error codes in filter with user definable fallback - [PR #20773](https://github.com/BerriAI/litellm/pull/20773) + - Paginated searchable model select - [PR #20892](https://github.com/BerriAI/litellm/pull/20892) + - Sorting columns support - [PR #21143](https://github.com/BerriAI/litellm/pull/21143) + - Allow sorting on `/spend/logs/ui` - [PR #20991](https://github.com/BerriAI/litellm/pull/20991) + +- **UI Improvements** + - Navbar: Option to hide Usage Popup - [PR #20910](https://github.com/BerriAI/litellm/pull/20910) + - Model Page: Improve Credentials Messaging - [PR #21076](https://github.com/BerriAI/litellm/pull/21076) + - Fallbacks: Default configurable to 10 models - [PR #21144](https://github.com/BerriAI/litellm/pull/21144) + - Fallback display with arrows and card structure - [PR #20922](https://github.com/BerriAI/litellm/pull/20922) + - Team Info: Migrate to AntD Tabs + Table - [PR #20785](https://github.com/BerriAI/litellm/pull/20785) + - AntD refactoring and 0 cost models fix - [PR #20687](https://github.com/BerriAI/litellm/pull/20687) + - Zscaler AI Guard UI - [PR #21077](https://github.com/BerriAI/litellm/pull/21077) + - Include Config Defined Pass Through Endpoints - [PR #20898](https://github.com/BerriAI/litellm/pull/20898) + - Rename "HTTP" to "Streamable HTTP (Recommended)" in MCP server page - [PR #21000](https://github.com/BerriAI/litellm/pull/21000) + - MCP server discovery UI - [PR #21079](https://github.com/BerriAI/litellm/pull/21079) + +- **Virtual Keys** + - Allow Management keys to access `user/daily/activity` and team - [PR #20124](https://github.com/BerriAI/litellm/pull/20124) + - Skip premium check for empty metadata fields on team/key update - [PR #20598](https://github.com/BerriAI/litellm/pull/20598) + +#### Bugs + +- Logs: Fix Input and Output Copying - [PR #20657](https://github.com/BerriAI/litellm/pull/20657) +- Teams: Fix Available Teams - [PR #20682](https://github.com/BerriAI/litellm/pull/20682) +- Spend Logs: Reset Filters Resets Custom Date Range - [PR #21149](https://github.com/BerriAI/litellm/pull/21149) +- Usage: Request Chart stack variant fix - [PR #20894](https://github.com/BerriAI/litellm/pull/20894) +- Add Auto Router: Description Text Input Focus - [PR #21004](https://github.com/BerriAI/litellm/pull/21004) +- Guardrail Edit: LiteLLM Content Filter Categories - [PR #21002](https://github.com/BerriAI/litellm/pull/21002) +- Add null guard for models in API keys table - [PR #20655](https://github.com/BerriAI/litellm/pull/20655) +- Show error details instead of 'Data Not Available' for failed requests - [PR #20656](https://github.com/BerriAI/litellm/pull/20656) +- Fix Spend Management Tests - [PR #21088](https://github.com/BerriAI/litellm/pull/21088) +- Fix JWT email domain validation error message - [PR #21212](https://github.com/BerriAI/litellm/pull/21212) + +--- + +## AI Integrations + +### Logging + +- **[PostHog](../../docs/observability/posthog_integration)** + - Fix JSON serialization error for non-serializable objects - [PR #20668](https://github.com/BerriAI/litellm/pull/20668) + +- **[Prometheus](../../docs/proxy/logging#prometheus)** + - Sanitize label values to prevent metric scrape failures - [PR #20600](https://github.com/BerriAI/litellm/pull/20600) + +- **[Langfuse](../../docs/proxy/logging#langfuse)** + - Prevent empty proxy request spans from being sent to Langfuse - [PR #19935](https://github.com/BerriAI/litellm/pull/19935) + +- **[OpenTelemetry](../../docs/proxy/logging#otel)** + - Auto-infer `otlp_http` exporter when endpoint is configured - [PR #20438](https://github.com/BerriAI/litellm/pull/20438) + +- **[CloudZero](../../docs/proxy/logging)** + - Update CBF field mappings per LIT-1907 - [PR #20906](https://github.com/BerriAI/litellm/pull/20906) + +- **General** + - Allow `MAX_CALLBACKS` override via env var - [PR #20781](https://github.com/BerriAI/litellm/pull/20781) + - Add `standard_logging_payload_excluded_fields` config option - [PR #20831](https://github.com/BerriAI/litellm/pull/20831) + - Enable `verbose_logger` when `LITELLM_LOG=DEBUG` - [PR #20496](https://github.com/BerriAI/litellm/pull/20496) + - Guard against None `litellm_metadata` in batch logging path - [PR #20832](https://github.com/BerriAI/litellm/pull/20832) + - Propagate model-level tags from config to SpendLogs - [PR #20769](https://github.com/BerriAI/litellm/pull/20769) + +### Guardrails + +- **Policy Templates** + - New Policy Templates: pre-configured guardrail combinations for specific use-cases - [PR #21025](https://github.com/BerriAI/litellm/pull/21025) + - Add NSFW policy template, toxic keywords in multiple languages, child safety content filter, JSON content viewer - [PR #21205](https://github.com/BerriAI/litellm/pull/21205) + - Add toxic/abusive content filter guardrails - [PR #20934](https://github.com/BerriAI/litellm/pull/20934) + +- **Pipeline Execution** + - Add guardrail pipeline support for conditional sequential execution - [PR #21177](https://github.com/BerriAI/litellm/pull/21177) + - Agent Guardrails on streaming output - [PR #21206](https://github.com/BerriAI/litellm/pull/21206) + - Pipeline flow builder UI - [PR #21188](https://github.com/BerriAI/litellm/pull/21188) + +- **[Zscaler AI Guard](../../docs/apply_guardrail)** + - Zscaler AI Guard bug fixes and support during post-call - [PR #20801](https://github.com/BerriAI/litellm/pull/20801) + - Zscaler AI Guard UI - [PR #21077](https://github.com/BerriAI/litellm/pull/21077) + +- **[ZGuard](../../docs/apply_guardrail)** + - Add team policy mapping for ZGuard - [PR #20608](https://github.com/BerriAI/litellm/pull/20608) + +- **General** + - Add logging to all unified guardrails + link to custom code guardrail templates - [PR #20900](https://github.com/BerriAI/litellm/pull/20900) + - Forward request headers + `litellm_version` to generic guardrails - [PR #20729](https://github.com/BerriAI/litellm/pull/20729) + - Empty `guardrails`/`policies` arrays should not trigger enterprise license check - [PR #20567](https://github.com/BerriAI/litellm/pull/20567) + - Fix OpenAI moderation guardrails - [PR #20718](https://github.com/BerriAI/litellm/pull/20718) + - Fix `/v2/guardrails/list` returning sensitive values - [PR #20796](https://github.com/BerriAI/litellm/pull/20796) + - Fix guardrail status error - [PR #20972](https://github.com/BerriAI/litellm/pull/20972) + - Reuse `get_instance_fn` in `initialize_custom_guardrail` - [PR #20917](https://github.com/BerriAI/litellm/pull/20917) + +--- + +## Spend Tracking, Budgets and Rate Limiting + +- **Prevent shared backend model key from being polluted** by per-deployment custom pricing - [PR #20679](https://github.com/BerriAI/litellm/pull/20679) +- **Avoid in-place mutation** in SpendUpdateQueue aggregation - [PR #20876](https://github.com/BerriAI/litellm/pull/20876) + +--- + +## MCP Gateway (12 updates) + +- **MCP M2M OAuth2 Support** - Add support for machine-to-machine OAuth2 for MCP servers - [PR #20788](https://github.com/BerriAI/litellm/pull/20788) +- **MCP Server Discovery UI** - Browse and discover available MCP servers from the UI - [PR #21079](https://github.com/BerriAI/litellm/pull/21079) +- **MCP Tracing** - Add OpenTelemetry tracing for MCP calls running through AI Gateway - [PR #21018](https://github.com/BerriAI/litellm/pull/21018) +- **MCP OAuth2 Debug Headers** - Client-side debug headers for OAuth2 troubleshooting - [PR #21151](https://github.com/BerriAI/litellm/pull/21151) +- **Fix MCP "Session not found" errors** - Resolve session persistence issues - [PR #21040](https://github.com/BerriAI/litellm/pull/21040) +- **Fix MCP OAuth2 root endpoints** returning "MCP server not found" - [PR #20784](https://github.com/BerriAI/litellm/pull/20784) +- **Fix MCP OAuth2 query param merging** when `authorization_url` already contains params - [PR #20968](https://github.com/BerriAI/litellm/pull/20968) +- **Fix MCP SCOPES on Atlassian** issue - [PR #21150](https://github.com/BerriAI/litellm/pull/21150) +- **Fix MCP StreamableHTTP backend** - Use `anyio.fail_after` instead of `asyncio.wait_for` - [PR #20891](https://github.com/BerriAI/litellm/pull/20891) +- **Inject `NPM_CONFIG_CACHE`** into STDIO MCP subprocess env - [PR #21069](https://github.com/BerriAI/litellm/pull/21069) +- **Block spaces and hyphens** in MCP server names and aliases - [PR #21074](https://github.com/BerriAI/litellm/pull/21074) + +--- + +## Performance / Loadbalancing / Reliability improvements (8 improvements) + +- **Remove orphan entries from queue** - Fix memory leak in scheduler queue - [PR #20866](https://github.com/BerriAI/litellm/pull/20866) +- **Remove repeated provider parsing** in budget limiter hot path - [PR #21043](https://github.com/BerriAI/litellm/pull/21043) +- **Use current retry exception** for retry backoff instead of stale exception - [PR #20725](https://github.com/BerriAI/litellm/pull/20725) +- **Add Semgrep & fix OOMs** - Static analysis rules and out-of-memory fixes - [PR #20912](https://github.com/BerriAI/litellm/pull/20912) +- **Add Pyroscope** for continuous profiling and observability - [PR #21167](https://github.com/BerriAI/litellm/pull/21167) +- **Respect `ssl_verify`** with shared aiohttp sessions - [PR #20349](https://github.com/BerriAI/litellm/pull/20349) +- **Fix shared health check serialization** - [PR #21119](https://github.com/BerriAI/litellm/pull/21119) +- **Change model mismatch logs** from WARNING to DEBUG - [PR #20994](https://github.com/BerriAI/litellm/pull/20994) + +--- + +## Database Changes + +### Schema Updates + +| Table | Change Type | Description | PR | Migration | +| ----- | ----------- | ----------- | -- | --------- | +| `LiteLLM_VerificationToken` | New Indexes | Added indexes on `user_id`+`team_id`, `team_id`, and `budget_reset_at`+`expires` | [PR #20736](https://github.com/BerriAI/litellm/pull/20736) | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260209085821_add_verificationtoken_indexes/migration.sql) | +| `LiteLLM_PolicyAttachmentTable` | New Column | Added `tags` text array for policy-to-tag connections | [PR #21061](https://github.com/BerriAI/litellm/pull/21061) | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260212103349_adjust_tags_policy_table/migration.sql) | +| `LiteLLM_AccessGroupTable` | New Table | Access groups for managing model, MCP server, and agent access | [PR #21022](https://github.com/BerriAI/litellm/pull/21022) | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260212143306_add_access_group_table/migration.sql) | +| `LiteLLM_AccessGroupTable` | Column Change | Renamed `access_model_ids` to `access_model_names` | [PR #21166](https://github.com/BerriAI/litellm/pull/21166) | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260213170952_access_group_change_to_model_name/migration.sql) | +| `LiteLLM_ManagedVectorStoreTable` | New Table | Managed vector store tracking with model mappings | - | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260213105436_add_managed_vector_store_table/migration.sql) | +| `LiteLLM_TeamTable`, `LiteLLM_VerificationToken` | New Column | Added `access_group_ids` text array | [PR #21022](https://github.com/BerriAI/litellm/pull/21022) | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260212143306_add_access_group_table/migration.sql) | +| `LiteLLM_GuardrailsTable` | New Column | Added `team_id` text column | - | [Migration](https://github.com/BerriAI/litellm/blob/main/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214094754_schema_sync/migration.sql) | + +--- + +## Documentation Updates (14 updates) + +- LiteLLM Observatory section added to v1.81.9 release notes - [PR #20675](https://github.com/BerriAI/litellm/pull/20675) +- Callback registration optimization added to release notes - [PR #20681](https://github.com/BerriAI/litellm/pull/20681) +- Middleware performance blog post - [PR #20677](https://github.com/BerriAI/litellm/pull/20677) +- UI Team Soft Budget documentation - [PR #20669](https://github.com/BerriAI/litellm/pull/20669) +- UI Contributing and Troubleshooting guide - [PR #20674](https://github.com/BerriAI/litellm/pull/20674) +- Reorganize Admin UI subsection - [PR #20676](https://github.com/BerriAI/litellm/pull/20676) +- SDK proxy authentication (OAuth2/JWT auto-refresh) - [PR #20680](https://github.com/BerriAI/litellm/pull/20680) +- Forward client headers to LLM API documentation fix - [PR #20768](https://github.com/BerriAI/litellm/pull/20768) +- Add docs guide for using policies - [PR #20914](https://github.com/BerriAI/litellm/pull/20914) +- Add native thinking param examples for Claude Opus 4.6 - [PR #20799](https://github.com/BerriAI/litellm/pull/20799) +- Fix Claude Code MCP tutorial - [PR #21145](https://github.com/BerriAI/litellm/pull/21145) +- Add API base URLs for Dashscope (International and China/Beijing) - [PR #21083](https://github.com/BerriAI/litellm/pull/21083) +- Fix `DEFAULT_NUM_WORKERS_LITELLM_PROXY` default (1, not 4) - [PR #21127](https://github.com/BerriAI/litellm/pull/21127) +- Correct ElevenLabs support status in README - [PR #20643](https://github.com/BerriAI/litellm/pull/20643) + +--- + +## New Contributors +* @iver56 made their first contribution in [PR #20643](https://github.com/BerriAI/litellm/pull/20643) +* @eliasaronson made their first contribution in [PR #20666](https://github.com/BerriAI/litellm/pull/20666) +* @NirantK made their first contribution in [PR #19656](https://github.com/BerriAI/litellm/pull/19656) +* @looksgood made their first contribution in [PR #20919](https://github.com/BerriAI/litellm/pull/20919) +* @kelvin-tran made their first contribution in [PR #20548](https://github.com/BerriAI/litellm/pull/20548) +* @bluet made their first contribution in [PR #20873](https://github.com/BerriAI/litellm/pull/20873) +* @itayov made their first contribution in [PR #20729](https://github.com/BerriAI/litellm/pull/20729) +* @CSteigstra made their first contribution in [PR #20960](https://github.com/BerriAI/litellm/pull/20960) +* @rahulrd25 made their first contribution in [PR #20569](https://github.com/BerriAI/litellm/pull/20569) +* @muraliavarma made their first contribution in [PR #20598](https://github.com/BerriAI/litellm/pull/20598) +* @joaokopernico made their first contribution in [PR #21039](https://github.com/BerriAI/litellm/pull/21039) +* @datzscaler made their first contribution in [PR #21077](https://github.com/BerriAI/litellm/pull/21077) +* @atapia27 made their first contribution in [PR #20922](https://github.com/BerriAI/litellm/pull/20922) +* @fpagny made their first contribution in [PR #21121](https://github.com/BerriAI/litellm/pull/21121) +* @aidankovacic-8451 made their first contribution in [PR #21119](https://github.com/BerriAI/litellm/pull/21119) +* @luisgallego-aily made their first contribution in [PR #19935](https://github.com/BerriAI/litellm/pull/19935) + +--- + +## Full Changelog +[v1.81.9.rc.1...v1.81.12.rc.1](https://github.com/BerriAI/litellm/compare/v1.81.9.rc.1...v1.81.12.rc.1) diff --git a/docs/my-website/release_notes/v1.81.6.md b/docs/my-website/release_notes/v1.81.6.md index d349afa65f9..1e948aa37b7 100644 --- a/docs/my-website/release_notes/v1.81.6.md +++ b/docs/my-website/release_notes/v1.81.6.md @@ -14,6 +14,14 @@ authors: hide_table_of_contents: false --- +:::danger Known Issue - CPU Usage + +This release had known issues with CPU usage. This has been fixed in [v1.81.9-stable](./v1-81-9). + +**We recommend using v1.81.9-stable instead.** + +::: + ## Deploy this version import Tabs from '@theme/Tabs'; diff --git a/docs/my-website/release_notes/v1.81.9.md b/docs/my-website/release_notes/v1.81.9.md index c34d3056cae..c7659442c4c 100644 --- a/docs/my-website/release_notes/v1.81.9.md +++ b/docs/my-website/release_notes/v1.81.9.md @@ -1,5 +1,5 @@ --- -title: "[Preview] v1.81.9 - Control which MCP Servers are exposed on the Internet" +title: "v1.81.9 - Control which MCP Servers are exposed on the Internet" slug: "v1-81-9" date: 2026-02-07T00:00:00 authors: @@ -14,6 +14,16 @@ authors: hide_table_of_contents: false --- +:::info Stable Release Branch + +For each stable release, we now maintain a dedicated branch with the format `litellm_stable_release_branch_x_xx_xx` for the version. + +This allows easier patching for day 0 model launches. + +**Branch for v1.81.9:** [litellm_stable_release_branch_1_81_9](https://github.com/BerriAI/litellm/tree/litellm_stable_release_branch_1_81_9) + +::: + ## Deploy this version import Tabs from '@theme/Tabs'; @@ -27,7 +37,7 @@ import Image from '@theme/IdealImage'; docker run \ -e STORE_MODEL_IN_DB=True \ -p 4000:4000 \ -ghcr.io/berriai/litellm:main-v1.81.9.rc.1 +ghcr.io/berriai/litellm:main-v1.81.9-stable ``` diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js index 9b3581cce32..42996d1a3e9 100644 --- a/docs/my-website/sidebars.js +++ b/docs/my-website/sidebars.js @@ -176,6 +176,7 @@ const sidebars = { "tutorials/copilotkit_sdk", "tutorials/google_adk", "tutorials/livekit_xai_realtime", + "projects/openai-agents" ] }, @@ -467,6 +468,7 @@ const sidebars = { "proxy/model_access_guide", "proxy/model_access", "proxy/model_access_groups", + "proxy/access_groups", "proxy/team_model_add" ] }, diff --git a/enterprise/dist/litellm_enterprise-0.1.32-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.32-py3-none-any.whl new file mode 100644 index 00000000000..0c87c72c989 Binary files /dev/null and b/enterprise/dist/litellm_enterprise-0.1.32-py3-none-any.whl differ diff --git a/enterprise/dist/litellm_enterprise-0.1.32.tar.gz b/enterprise/dist/litellm_enterprise-0.1.32.tar.gz new file mode 100644 index 00000000000..4f0ac1a9b20 Binary files /dev/null and b/enterprise/dist/litellm_enterprise-0.1.32.tar.gz differ diff --git a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py index bb25e4f0626..b28b4497e7c 100644 --- a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py +++ b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py @@ -4,7 +4,7 @@ Polls LiteLLM_ManagedObjectTable to check if the batch job is complete, and if t from litellm._uuid import uuid from datetime import datetime -from typing import TYPE_CHECKING, Optional, cast +from typing import TYPE_CHECKING, Optional from litellm._logging import verbose_proxy_logger @@ -35,14 +35,11 @@ class CheckBatchCost: - if not, return False - if so, return True """ - from litellm_enterprise.proxy.hooks.managed_files import ( - _PROXY_LiteLLMManagedFiles, - ) - from litellm.batches.batch_utils import ( _get_file_content_as_dictionary, calculate_batch_cost_and_usage, ) + from litellm.files.main import afile_content from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.proxy.openai_files_endpoints.common_utils import ( @@ -102,27 +99,29 @@ class CheckBatchCost: continue ## RETRIEVE THE BATCH JOB OUTPUT FILE - managed_files_obj = cast( - Optional[_PROXY_LiteLLMManagedFiles], - self.proxy_logging_obj.get_proxy_hook("managed_files"), - ) if ( response.status == "completed" and response.output_file_id is not None - and managed_files_obj is not None ): verbose_proxy_logger.info( f"Batch ID: {batch_id} is complete, tracking cost and usage" ) - # track cost - model_file_id_mapping = { - response.output_file_id: {model_id: response.output_file_id} - } - _file_content = await managed_files_obj.afile_content( - file_id=response.output_file_id, - litellm_parent_otel_span=None, - llm_router=self.llm_router, - model_file_id_mapping=model_file_id_mapping, + + # This background job runs as default_user_id, so going through the HTTP endpoint + # would trigger check_managed_file_id_access and get 403. Instead, extract the raw + # provider file ID and call afile_content directly with deployment credentials. + raw_output_file_id = response.output_file_id + decoded = _is_base64_encoded_unified_file_id(raw_output_file_id) + if decoded: + try: + raw_output_file_id = decoded.split("llm_output_file_id,")[1].split(";")[0] + except (IndexError, AttributeError): + pass + + credentials = self.llm_router.get_deployment_credentials_with_provider(model_id) or {} + _file_content = await afile_content( + file_id=raw_output_file_id, + **credentials, ) file_content_as_dict = _get_file_content_as_dictionary( @@ -143,11 +142,15 @@ class CheckBatchCost: custom_llm_provider=custom_llm_provider, ) + # Pass deployment model_info so custom batch pricing + # (input_cost_per_token_batches etc.) is used for cost calc + deployment_model_info = deployment_info.model_info.model_dump() if deployment_info.model_info else {} batch_cost, batch_usage, batch_models = ( await calculate_batch_cost_and_usage( file_content_dictionary=file_content_as_dict, custom_llm_provider=llm_provider, # type: ignore model_name=model_name, + model_info=deployment_model_info, ) ) logging_obj = LiteLLMLogging( diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index a41b3f3bf6f..f341a1e9634 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -230,12 +230,14 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): if managed_file: return managed_file.created_by == user_id - return False + raise HTTPException( + status_code=404, + detail=f"File not found: {unified_file_id}", + ) async def can_user_call_unified_object_id( self, unified_object_id: str, user_api_key_dict: UserAPIKeyAuth ) -> bool: - ## check if the user has access to the unified object id ## check if the user has access to the unified object id user_id = user_api_key_dict.user_id managed_object = ( @@ -246,7 +248,10 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): if managed_object: return managed_object.created_by == user_id - return True # don't raise error if managed object is not found + raise HTTPException( + status_code=404, + detail=f"Object not found: {unified_object_id}", + ) async def list_user_batches( self, @@ -911,15 +916,22 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): ) setattr(response, file_attr, unified_file_id) - # Fetch the actual file object from the provider + # Use llm_router credentials when available. Without credentials, + # Azure and other auth-required providers return 500/401. file_object = None try: - # Use litellm to retrieve the file object from the provider - from litellm import afile_retrieve - file_object = await afile_retrieve( - custom_llm_provider=model_name.split("/")[0] if model_name and "/" in model_name else "openai", - file_id=original_file_id - ) + from litellm.proxy.proxy_server import llm_router as _llm_router + if _llm_router is not None and model_id: + _creds = _llm_router.get_deployment_credentials_with_provider(model_id) or {} + file_object = await litellm.afile_retrieve( + file_id=original_file_id, + **_creds, + ) + else: + file_object = await litellm.afile_retrieve( + custom_llm_provider=model_name.split("/")[0] if model_name and "/" in model_name else "openai", + file_id=original_file_id, + ) verbose_logger.debug( f"Successfully retrieved file object for {file_attr}={original_file_id}" ) @@ -1004,7 +1016,10 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): raise Exception(f"LiteLLM Managed File object with id={file_id} not found") # Case 2: Managed file and the file object exists in the database + # The stored file_object has the raw provider ID. Replace with the unified ID + # so callers see a consistent ID (matching Case 3 which does response.id = file_id). if stored_file_object and stored_file_object.file_object: + stored_file_object.file_object.id = file_id return stored_file_object.file_object # Case 3: Managed file exists in the database but not the file object (for. e.g the batch task might not have run) diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml index eca5cdb97df..55720934f09 100644 --- a/enterprise/pyproject.toml +++ b/enterprise/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-enterprise" -version = "0.1.31" +version = "0.1.32" 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 = "0.1.31" +version = "0.1.32" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-enterprise==", diff --git a/litellm-proxy-extras/build_and_publish.md b/litellm-proxy-extras/build_and_publish.md new file mode 100644 index 00000000000..6bf16b99466 --- /dev/null +++ b/litellm-proxy-extras/build_and_publish.md @@ -0,0 +1,127 @@ +# Build & Publish `litellm-proxy-extras` + +This runbook covers building and publishing a new version of the `litellm-proxy-extras` PyPI package. For use by litellm engineers only. + +## Prerequisites + +- All `schema.prisma` files are in sync (see [migration_runbook.md](./migration_runbook.md) Step 0) +- Migration has been generated and committed +- You are in the `litellm-proxy-extras/` directory + +## Step 1: Bump the Version + +### Option A: Automatic Version Bump (Recommended) + +Use commitizen to automatically bump the version across all files: + +```bash +cd litellm-proxy-extras +cz bump --increment patch +``` + +This will automatically: +- Bump the version in `pyproject.toml` (both `[tool.poetry].version` and `[tool.commitizen].version`) +- Update the version in `../requirements.txt` +- Update the version in `../pyproject.toml` (root) +- Create a git commit with the version bump + +Then skip to Step 3 (Install Build Dependencies). + +### Option B: Manual Version Bump + +Update the version in `pyproject.toml`: + +```bash +cd litellm-proxy-extras + +# Check current version +grep 'version' pyproject.toml +``` + +Edit `pyproject.toml` and bump the version (both `[tool.poetry].version` and `[tool.commitizen].version`). + +#### Step 2: Update Version in Root Package Files (Manual Only) + +After bumping the version in `litellm-proxy-extras/pyproject.toml`, you **must** also update the version reference in the root-level files: + +| File | Line to update | +|------|---------------| +| `requirements.txt` | `litellm-proxy-extras==X.Y.Z` | +| `pyproject.toml` (root) | `litellm-proxy-extras = {version = "X.Y.Z", optional = true}` | + +```bash +# From the repo root — replace OLD with NEW version +sed -i '' 's/litellm-proxy-extras==OLD/litellm-proxy-extras==NEW/' requirements.txt +sed -i '' 's/litellm-proxy-extras = {version = "OLD"/litellm-proxy-extras = {version = "NEW"/' pyproject.toml +``` + +> **Do NOT skip this step.** The main `litellm` package pins the extras version — if you don't update these, users will install the old version. + +## Step 3: Install Build Dependencies + +```bash +pip install build twine +``` + +## Step 4: Clean Old Artifacts + +```bash +rm -rf dist/ build/ *.egg-info +``` + +## Step 5: Build the Package + +```bash +python3 -m build +``` + +This creates `.tar.gz` and `.whl` files in the `dist/` directory. + +Verify the build output: + +```bash +ls -la dist/ +``` + +## Step 6: Upload to PyPI + +```bash +twine upload dist/* +``` + +You will be prompted for your PyPI API token: + +``` +Enter your API token: pypi-... +``` + +> Use `__token__` as the username and your PyPI API token as the password. + +## Quick Reference (Copy-Paste) + +```bash +cd litellm-proxy-extras +rm -rf dist/ build/ *.egg-info +python3 -m build +twine upload dist/* +``` + +--- + +## Do you want to build and publish a new `litellm-proxy-extras` package? (y/n) + +If **yes**, run the following commands in order: + +```bash +cd litellm-proxy-extras +pip install build twine +rm -rf dist/ build/ *.egg-info +python3 -m build +twine upload dist/* +``` + +When `twine upload` runs, enter your PyPI credentials: +- **Username:** `__token__` +- **Password:** *(paste your PyPI API key)* + +If **no**, you're done — no package publish needed. diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40-py3-none-any.whl new file mode 100644 index 00000000000..9f2ad8fd317 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40-py3-none-any.whl differ diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40.tar.gz new file mode 100644 index 00000000000..fdab43c01a3 Binary files /dev/null and b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.40.tar.gz differ diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260203120000_add_deprecated_verification_token_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260203120000_add_deprecated_verification_token_table/migration.sql new file mode 100644 index 00000000000..51d88444191 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260203120000_add_deprecated_verification_token_table/migration.sql @@ -0,0 +1,19 @@ +-- CreateTable +CREATE TABLE "LiteLLM_DeprecatedVerificationToken" ( + "id" TEXT NOT NULL, + "token" TEXT NOT NULL, + "active_token_id" TEXT NOT NULL, + "revoke_at" TIMESTAMP(3) NOT NULL, + "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + + CONSTRAINT "LiteLLM_DeprecatedVerificationToken_pkey" PRIMARY KEY ("id") +); + +-- CreateIndex +CREATE UNIQUE INDEX "LiteLLM_DeprecatedVerificationToken_token_key" ON "LiteLLM_DeprecatedVerificationToken"("token"); + +-- CreateIndex +CREATE INDEX "LiteLLM_DeprecatedVerificationToken_token_revoke_at_idx" ON "LiteLLM_DeprecatedVerificationToken"("token", "revoke_at"); + +-- CreateIndex +CREATE INDEX "LiteLLM_DeprecatedVerificationToken_revoke_at_idx" ON "LiteLLM_DeprecatedVerificationToken"("revoke_at"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214094754_schema_sync/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214094754_schema_sync/migration.sql new file mode 100644 index 00000000000..b5d5b978580 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214094754_schema_sync/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_GuardrailsTable" ADD COLUMN "team_id" TEXT; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214124140_baseline_diff/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214124140_baseline_diff/migration.sql new file mode 100644 index 00000000000..2f725d83806 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214124140_baseline_diff/migration.sql @@ -0,0 +1,2 @@ +-- This is an empty migration. + diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214163027_add_pipeline_to_policy_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214163027_add_pipeline_to_policy_table/migration.sql new file mode 100644 index 00000000000..e57b9ef29c5 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260214163027_add_pipeline_to_policy_table/migration.sql @@ -0,0 +1,3 @@ +-- AlterTable +ALTER TABLE "LiteLLM_PolicyTable" ADD COLUMN "pipeline" JSONB; + diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index 39359a34547..441c2cdf70d 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -325,6 +325,19 @@ model LiteLLM_VerificationToken { @@index([budget_reset_at, expires]) } +// Deprecated keys during grace period - allows old key to work until revoke_at +model LiteLLM_DeprecatedVerificationToken { + id String @id @default(uuid()) + token String // Hashed old key + active_token_id String // Current token hash in LiteLLM_VerificationToken + revoke_at DateTime // When the old key stops working + created_at DateTime @default(now()) @map("created_at") + + @@unique([token]) + @@index([token, revoke_at]) + @@index([revoke_at]) +} + // Audit table for deleted keys - preserves spend and key information for historical tracking model LiteLLM_DeletedVerificationToken { id String @id @default(uuid()) @@ -920,6 +933,7 @@ model LiteLLM_PolicyTable { guardrails_add String[] @default([]) guardrails_remove String[] @default([]) condition Json? @default("{}") // Policy conditions (e.g., model matching) + pipeline Json? // Optional guardrail pipeline (mode + steps[]) created_at DateTime @default(now()) created_by String? updated_at DateTime @default(now()) @updatedAt diff --git a/litellm-proxy-extras/migration_runbook.md b/litellm-proxy-extras/migration_runbook.md index 93948f24b13..3310b1626a8 100644 --- a/litellm-proxy-extras/migration_runbook.md +++ b/litellm-proxy-extras/migration_runbook.md @@ -2,7 +2,35 @@ This is a runbook for creating and running database migrations for the LiteLLM proxy. For use for litellm engineers only. -## Quick Start +## Step 0: Sync All `schema.prisma` Files + +Before doing anything else, make sure all `schema.prisma` files in the repo are in sync. There are multiple copies that must match: + +| File | Purpose | +|------|---------| +| `schema.prisma` (repo root) | Source of truth | +| `litellm/proxy/schema.prisma` | Used by the proxy server | +| `litellm-proxy-extras/litellm_proxy_extras/schema.prisma` | Used for migration generation | + +**Sync process:** + +```bash +# 1. Diff all schema files against the root source of truth +diff schema.prisma litellm/proxy/schema.prisma +diff schema.prisma litellm-proxy-extras/litellm_proxy_extras/schema.prisma + +# 2. If there are differences, copy the root schema to all locations +cp schema.prisma litellm/proxy/schema.prisma +cp schema.prisma litellm-proxy-extras/litellm_proxy_extras/schema.prisma + +# 3. Verify all files are now identical +diff schema.prisma litellm/proxy/schema.prisma && echo "proxy schema in sync" || echo "MISMATCH" +diff schema.prisma litellm-proxy-extras/litellm_proxy_extras/schema.prisma && echo "extras schema in sync" || echo "MISMATCH" +``` + +> **Do NOT proceed to migration generation until all schema files are identical.** + +## Step 1: Quick Start — Generate Migration ```bash # Install deps (one time) @@ -43,8 +71,13 @@ rm -rf litellm-proxy-extras/litellm_proxy_extras/migrations/[empty_dir] ## Rules -- Update `schema.prisma` first +- Sync all `schema.prisma` files first (Step 0) +- Update `schema.prisma` at the repo root first, then sync copies - Review generated SQL before committing - Use descriptive migration names - Never edit existing migration files - Commit schema + migration together + +--- + +**Done with migration?** See [build_and_publish.md](./build_and_publish.md) to publish a new `litellm-proxy-extras` package. diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml index 909c5e7e6cd..7ef0409b6b8 100644 --- a/litellm-proxy-extras/pyproject.toml +++ b/litellm-proxy-extras/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm-proxy-extras" -version = "0.4.37" +version = "0.4.40" 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 = "0.4.37" +version = "0.4.40" version_files = [ "pyproject.toml:version", "../requirements.txt:litellm-proxy-extras==", diff --git a/litellm/_service_logger.py b/litellm/_service_logger.py index b67d0d86063..8f9a3c5083f 100644 --- a/litellm/_service_logger.py +++ b/litellm/_service_logger.py @@ -312,10 +312,12 @@ class ServiceLogging(CustomLogger): _duration, type(_duration) ) ) # invalid _duration value + # Batch polling callbacks (check_batch_cost) don't include call_type in kwargs. + # Use .get() to avoid KeyError. await self.async_service_success_hook( service=ServiceTypes.LITELLM, duration=_duration, - call_type=kwargs["call_type"], + call_type=kwargs.get("call_type", "unknown") ) except Exception as e: raise e diff --git a/litellm/batches/batch_utils.py b/litellm/batches/batch_utils.py index 16a467e00cb..29bd99c2a60 100644 --- a/litellm/batches/batch_utils.py +++ b/litellm/batches/batch_utils.py @@ -8,7 +8,7 @@ import litellm from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.types.llms.openai import Batch -from litellm.types.utils import CallTypes, ModelResponse, Usage +from litellm.types.utils import CallTypes, ModelInfo, ModelResponse, Usage from litellm.utils import token_counter @@ -16,14 +16,22 @@ async def calculate_batch_cost_and_usage( file_content_dictionary: List[dict], custom_llm_provider: Literal["openai", "azure", "vertex_ai", "hosted_vllm", "anthropic"], model_name: Optional[str] = None, + model_info: Optional[ModelInfo] = None, ) -> Tuple[float, Usage, List[str]]: """ - Calculate the cost and usage of a batch + Calculate the cost and usage of a batch. + + Args: + model_info: Optional deployment-level model info with custom batch + pricing. Threaded through to batch_cost_calculator so that + deployment-specific pricing (e.g. input_cost_per_token_batches) + is used instead of the global cost map. """ batch_cost = _batch_cost_calculator( custom_llm_provider=custom_llm_provider, file_content_dictionary=file_content_dictionary, model_name=model_name, + model_info=model_info, ) batch_usage = _get_batch_job_total_usage_from_file_content( file_content_dictionary=file_content_dictionary, @@ -94,6 +102,7 @@ def _batch_cost_calculator( file_content_dictionary: List[dict], custom_llm_provider: Literal["openai", "azure", "vertex_ai", "hosted_vllm", "anthropic"] = "openai", model_name: Optional[str] = None, + model_info: Optional[ModelInfo] = None, ) -> float: """ Calculate the cost of a batch based on the output file id @@ -108,6 +117,7 @@ def _batch_cost_calculator( total_cost = _get_batch_job_cost_from_file_content( file_content_dictionary=file_content_dictionary, custom_llm_provider=custom_llm_provider, + model_info=model_info, ) verbose_logger.debug("total_cost=%s", total_cost) return total_cost @@ -290,10 +300,13 @@ def _get_file_content_as_dictionary(file_content: bytes) -> List[dict]: def _get_batch_job_cost_from_file_content( file_content_dictionary: List[dict], custom_llm_provider: Literal["openai", "azure", "vertex_ai", "hosted_vllm", "anthropic"] = "openai", + model_info: Optional[ModelInfo] = None, ) -> float: """ Get the cost of a batch job from the file content """ + from litellm.cost_calculator import batch_cost_calculator + try: total_cost: float = 0.0 # parse the file content as json @@ -303,11 +316,22 @@ def _get_batch_job_cost_from_file_content( for _item in file_content_dictionary: if _batch_response_was_successful(_item): _response_body = _get_response_from_batch_job_output_file(_item) - total_cost += litellm.completion_cost( - completion_response=_response_body, - custom_llm_provider=custom_llm_provider, - call_type=CallTypes.aretrieve_batch.value, - ) + if model_info is not None: + usage = _get_batch_job_usage_from_response_body(_response_body) + model = _response_body.get("model", "") + prompt_cost, completion_cost = batch_cost_calculator( + usage=usage, + model=model, + custom_llm_provider=custom_llm_provider, + model_info=model_info, + ) + total_cost += prompt_cost + completion_cost + else: + total_cost += litellm.completion_cost( + completion_response=_response_body, + custom_llm_provider=custom_llm_provider, + call_type=CallTypes.aretrieve_batch.value, + ) verbose_logger.debug("total_cost=%s", total_cost) return total_cost except Exception as e: diff --git a/litellm/constants.py b/litellm/constants.py index addd659be73..a4a0e7882ea 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -106,9 +106,7 @@ MCP_OAUTH2_TOKEN_CACHE_DEFAULT_TTL = int( # npm/npx needs a writable cache dir; in containers the default (~/.npm) # may not exist or be read-only. /tmp is always writable. MCP_NPM_CACHE_DIR = os.getenv("MCP_NPM_CACHE_DIR", "/tmp/.npm_mcp_cache") -MCP_OAUTH2_TOKEN_CACHE_MIN_TTL = int( - os.getenv("MCP_OAUTH2_TOKEN_CACHE_MIN_TTL", "10") -) +MCP_OAUTH2_TOKEN_CACHE_MIN_TTL = int(os.getenv("MCP_OAUTH2_TOKEN_CACHE_MIN_TTL", "10")) LITELLM_UI_ALLOW_HEADERS = [ "x-litellm-semantic-filter", @@ -131,7 +129,7 @@ DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET_GEMINI_2_5_FLASH_LITE = int( # Maximum number of callbacks that can be registered # This prevents callbacks from exponentially growing and consuming CPU resources # Override with LITELLM_MAX_CALLBACKS env var for large deployments (e.g., many teams with guardrails) -MAX_CALLBACKS = get_env_int("LITELLM_MAX_CALLBACKS", 30) +MAX_CALLBACKS = get_env_int("LITELLM_MAX_CALLBACKS", 100) # Generic fallback for unknown models DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET = int( @@ -167,15 +165,19 @@ _DEFAULT_TTL_FOR_HTTPX_CLIENTS = 3600 # 1 hour, re-use the same httpx client fo # Aiohttp connection pooling - prevents memory leaks from unbounded connection growth # Set to 0 for unlimited (not recommended for production) AIOHTTP_CONNECTOR_LIMIT = int(os.getenv("AIOHTTP_CONNECTOR_LIMIT", 300)) -AIOHTTP_CONNECTOR_LIMIT_PER_HOST = int(os.getenv("AIOHTTP_CONNECTOR_LIMIT_PER_HOST", 50)) +AIOHTTP_CONNECTOR_LIMIT_PER_HOST = int( + os.getenv("AIOHTTP_CONNECTOR_LIMIT_PER_HOST", 50) +) AIOHTTP_KEEPALIVE_TIMEOUT = int(os.getenv("AIOHTTP_KEEPALIVE_TIMEOUT", 120)) AIOHTTP_TTL_DNS_CACHE = int(os.getenv("AIOHTTP_TTL_DNS_CACHE", 300)) # enable_cleanup_closed is only needed for Python versions with the SSL leak bug # Fixed in Python 3.12.7+ and 3.13.1+ (see https://github.com/python/cpython/pull/118960) # Reference: https://github.com/aio-libs/aiohttp/blob/master/aiohttp/connector.py#L74-L78 -AIOHTTP_NEEDS_CLEANUP_CLOSED = ( - (3, 13, 0) <= sys.version_info < (3, 13, 1) or sys.version_info < (3, 12, 7) -) +AIOHTTP_NEEDS_CLEANUP_CLOSED = (3, 13, 0) <= sys.version_info < ( + 3, + 13, + 1, +) or sys.version_info < (3, 12, 7) # WebSocket constants # Default to None (unlimited) to match OpenAI's official agents SDK behavior @@ -213,15 +215,15 @@ REDIS_UPDATE_BUFFER_KEY = "litellm_spend_update_buffer" REDIS_DAILY_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_spend_update_buffer" REDIS_DAILY_TEAM_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_team_spend_update_buffer" REDIS_DAILY_ORG_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_org_spend_update_buffer" -REDIS_DAILY_END_USER_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_end_user_spend_update_buffer" +REDIS_DAILY_END_USER_SPEND_UPDATE_BUFFER_KEY = ( + "litellm_daily_end_user_spend_update_buffer" +) REDIS_DAILY_AGENT_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_agent_spend_update_buffer" REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_tag_spend_update_buffer" MAX_REDIS_BUFFER_DEQUEUE_COUNT = int(os.getenv("MAX_REDIS_BUFFER_DEQUEUE_COUNT", 100)) MAX_SIZE_IN_MEMORY_QUEUE = int(os.getenv("MAX_SIZE_IN_MEMORY_QUEUE", 2000)) # Bounds asyncio.Queue() instances (log queues, spend update queues, etc.) to prevent unbounded memory growth -LITELLM_ASYNCIO_QUEUE_MAXSIZE = int( - os.getenv("LITELLM_ASYNCIO_QUEUE_MAXSIZE", 1000) -) +LITELLM_ASYNCIO_QUEUE_MAXSIZE = int(os.getenv("LITELLM_ASYNCIO_QUEUE_MAXSIZE", 1000)) MAX_IN_MEMORY_QUEUE_FLUSH_COUNT = int( os.getenv("MAX_IN_MEMORY_QUEUE_FLUSH_COUNT", 1000) ) @@ -317,6 +319,9 @@ NON_LLM_CONNECTION_TIMEOUT = int( MAX_EXCEPTION_MESSAGE_LENGTH = int(os.getenv("MAX_EXCEPTION_MESSAGE_LENGTH", 2000)) MAX_STRING_LENGTH_PROMPT_IN_DB = int(os.getenv("MAX_STRING_LENGTH_PROMPT_IN_DB", 2048)) BEDROCK_MAX_POLICY_SIZE = int(os.getenv("BEDROCK_MAX_POLICY_SIZE", 75)) +BEDROCK_MIN_THINKING_BUDGET_TOKENS = int( + os.getenv("BEDROCK_MIN_THINKING_BUDGET_TOKENS", 1024) +) REPLICATE_POLLING_DELAY_SECONDS = float( os.getenv("REPLICATE_POLLING_DELAY_SECONDS", 0.5) ) @@ -343,7 +348,9 @@ MAX_SIZE_PER_ITEM_IN_MEMORY_CACHE_IN_KB = int( DEFAULT_MAX_TOKENS_FOR_TRITON = int(os.getenv("DEFAULT_MAX_TOKENS_FOR_TRITON", 2000)) #### 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 +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. @@ -395,8 +402,12 @@ DD_TRACER_STREAMING_CHUNK_YIELD_RESOURCE = os.getenv( "DD_TRACER_STREAMING_CHUNK_YIELD_RESOURCE", "streaming.chunk.yield" ) -EMAIL_BUDGET_ALERT_TTL = int(os.getenv("EMAIL_BUDGET_ALERT_TTL", 24 * 60 * 60)) # 24 hours in seconds -EMAIL_BUDGET_ALERT_MAX_SPEND_ALERT_PERCENTAGE = float(os.getenv("EMAIL_BUDGET_ALERT_MAX_SPEND_ALERT_PERCENTAGE", 0.8)) # 80% of max budget +EMAIL_BUDGET_ALERT_TTL = int( + os.getenv("EMAIL_BUDGET_ALERT_TTL", 24 * 60 * 60) +) # 24 hours in seconds +EMAIL_BUDGET_ALERT_MAX_SPEND_ALERT_PERCENTAGE = float( + os.getenv("EMAIL_BUDGET_ALERT_MAX_SPEND_ALERT_PERCENTAGE", 0.8) +) # 80% of max budget ############### LLM Provider Constants ############### ### ANTHROPIC CONSTANTS ### ANTHROPIC_TOKEN_COUNTING_BETA_VERSION = os.getenv( @@ -1150,7 +1161,17 @@ known_tokenizer_config = { } -OPENAI_FINISH_REASONS = ["stop", "length", "function_call", "content_filter", "null", "finish_reason_unspecified", "malformed_function_call", "guardrail_intervened", "eos"] +OPENAI_FINISH_REASONS = [ + "stop", + "length", + "function_call", + "content_filter", + "null", + "finish_reason_unspecified", + "malformed_function_call", + "guardrail_intervened", + "eos", +] HUMANLOOP_PROMPT_CACHE_TTL_SECONDS = int( os.getenv("HUMANLOOP_PROMPT_CACHE_TTL_SECONDS", 60) ) # 1 minute @@ -1240,6 +1261,9 @@ LITELLM_KEY_ROTATION_ENABLED = os.getenv("LITELLM_KEY_ROTATION_ENABLED", "false" LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS = int( os.getenv("LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS", 86400) ) # 24 hours default +LITELLM_KEY_ROTATION_GRACE_PERIOD: str = os.getenv( + "LITELLM_KEY_ROTATION_GRACE_PERIOD", "" +) # Duration to keep old key valid after rotation (e.g. "24h", "2d"); empty = immediate revoke (default) UI_SESSION_TOKEN_TEAM_ID = "litellm-dashboard" LITELLM_PROXY_ADMIN_NAME = "default_user_id" @@ -1250,8 +1274,8 @@ CLI_SSO_SESSION_CACHE_KEY_PREFIX = "cli_sso_session" CLI_JWT_TOKEN_NAME = "cli-jwt-token" # Support both CLI_JWT_EXPIRATION_HOURS and LITELLM_CLI_JWT_EXPIRATION_HOURS for backwards compatibility CLI_JWT_EXPIRATION_HOURS = int( - os.getenv("CLI_JWT_EXPIRATION_HOURS") - or os.getenv("LITELLM_CLI_JWT_EXPIRATION_HOURS") + os.getenv("CLI_JWT_EXPIRATION_HOURS") + or os.getenv("LITELLM_CLI_JWT_EXPIRATION_HOURS") or 24 ) @@ -1342,6 +1366,9 @@ SPECIAL_LITELLM_AUTH_TOKEN = ["ui-token"] DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL = int( os.getenv("DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL", 60) ) +DEFAULT_ACCESS_GROUP_CACHE_TTL = int( + os.getenv("DEFAULT_ACCESS_GROUP_CACHE_TTL", 600) +) # Sentry Scrubbing Configuration SENTRY_DENYLIST = [ @@ -1432,9 +1459,7 @@ MICROSOFT_USER_EMAIL_ATTRIBUTE = str( MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE = str( os.getenv("MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE", "displayName") ) -MICROSOFT_USER_ID_ATTRIBUTE = str( - os.getenv("MICROSOFT_USER_ID_ATTRIBUTE", "id") -) +MICROSOFT_USER_ID_ATTRIBUTE = str(os.getenv("MICROSOFT_USER_ID_ATTRIBUTE", "id")) MICROSOFT_USER_FIRST_NAME_ATTRIBUTE = str( os.getenv("MICROSOFT_USER_FIRST_NAME_ATTRIBUTE", "givenName") ) diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 4ea22dbd90f..dae0bb1c2c0 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -74,6 +74,7 @@ from litellm.llms.vertex_ai.cost_calculator import ( from litellm.llms.vertex_ai.cost_calculator import cost_router as google_cost_router from litellm.llms.xai.cost_calculator import cost_per_token as xai_cost_per_token from litellm.responses.utils import ResponseAPILoggingUtils +from litellm.types.agents import LiteLLMSendMessageResponse from litellm.types.llms.openai import ( HttpxBinaryResponseContent, ImageGenerationRequestQuality, @@ -150,32 +151,33 @@ def _get_additional_costs( ) -> Optional[dict]: """ Calculate additional costs beyond standard token costs. - + This function delegates to provider-specific config classes to calculate any additional costs like routing fees, infrastructure costs, etc. - + Args: model: The model name custom_llm_provider: The provider name (optional) prompt_tokens: Number of prompt tokens completion_tokens: Number of completion tokens - + Returns: Optional dictionary with cost names and amounts, or None if no additional costs """ if not custom_llm_provider: return None - + try: config_class = None if custom_llm_provider == "azure_ai": from litellm.llms.azure_ai.common_utils import AzureFoundryModelInfo + config_class = AzureFoundryModelInfo.get_azure_ai_config_for_model(model) # Add more providers here as needed # elif custom_llm_provider == "other_provider": # config_class = get_other_provider_config(model) - - if config_class and hasattr(config_class, 'calculate_additional_costs'): + + if config_class and hasattr(config_class, "calculate_additional_costs"): return config_class.calculate_additional_costs( model=model, prompt_tokens=prompt_tokens, @@ -183,7 +185,7 @@ def _get_additional_costs( ) except Exception as e: verbose_logger.debug(f"Error calculating additional costs: {e}") - + return None @@ -748,6 +750,8 @@ def _infer_call_type( return "image_generation" elif isinstance(completion_response, TextCompletionResponse): return "text_completion" + elif isinstance(completion_response, LiteLLMSendMessageResponse): + return "send_message" return call_type @@ -1037,9 +1041,9 @@ def completion_cost( # noqa: PLR0915 or isinstance(completion_response, dict) ): # tts returns a custom class if isinstance(completion_response, dict): - usage_obj: Optional[ - Union[dict, Usage] - ] = completion_response.get("usage", {}) + usage_obj: Optional[Union[dict, Usage]] = ( + completion_response.get("usage", {}) + ) else: usage_obj = getattr(completion_response, "usage", {}) if isinstance(usage_obj, BaseModel) and not _is_known_usage_objects( @@ -1393,7 +1397,7 @@ def completion_cost( # noqa: PLR0915 service_tier=service_tier, response=completion_response, ) - + # Get additional costs from provider (e.g., routing fees, infrastructure costs) additional_costs = _get_additional_costs( model=model, @@ -1401,7 +1405,7 @@ def completion_cost( # noqa: PLR0915 prompt_tokens=prompt_tokens, completion_tokens=completion_tokens, ) - + _final_cost = ( prompt_tokens_cost_usd_dollar + completion_tokens_cost_usd_dollar ) @@ -1892,9 +1896,16 @@ def batch_cost_calculator( usage: Usage, model: str, custom_llm_provider: Optional[str] = None, + model_info: Optional[ModelInfo] = None, ) -> Tuple[float, float]: """ - Calculate the cost of a batch job + Calculate the cost of a batch job. + + Args: + model_info: Optional deployment-level model info containing custom + batch pricing (e.g. input_cost_per_token_batches). When provided, + skips the global litellm.get_model_info() lookup so that + deployment-specific pricing is used. """ _, custom_llm_provider, _, _ = litellm.get_llm_provider( @@ -1907,12 +1918,13 @@ def batch_cost_calculator( custom_llm_provider, ) - try: - model_info: Optional[ModelInfo] = litellm.get_model_info( - model=model, custom_llm_provider=custom_llm_provider - ) - except Exception: - model_info = None + if model_info is None: + try: + model_info = litellm.get_model_info( + model=model, custom_llm_provider=custom_llm_provider + ) + except Exception: + model_info = None if not model_info: return 0.0, 0.0 diff --git a/litellm/integrations/langfuse/langfuse_otel.py b/litellm/integrations/langfuse/langfuse_otel.py index 8955d3619f7..b96ec72b04e 100644 --- a/litellm/integrations/langfuse/langfuse_otel.py +++ b/litellm/integrations/langfuse/langfuse_otel.py @@ -1,6 +1,7 @@ import base64 import json # <--- NEW import os +from datetime import datetime from typing import TYPE_CHECKING, Any, Optional, Union from litellm._logging import verbose_logger @@ -392,6 +393,22 @@ class LangfuseOtelLogger(OpenTelemetry): return dynamic_headers + def create_litellm_proxy_request_started_span( + self, + start_time: datetime, + headers: dict, + ) -> Optional[Span]: + """ + Override to prevent creating empty proxy request spans. + + Langfuse should only receive spans for actual LLM calls, not for + internal proxy operations (auth, postgres, proxy_pre_call, etc.). + + By returning None, we prevent the parent span from being created, + which in turn prevents empty traces from being sent to Langfuse. + """ + return None + async def async_service_success_hook(self, *args, **kwargs): """ Langfuse should not receive service success logs. diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index b847180174a..35362a71ccd 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -1051,23 +1051,15 @@ class OpenTelemetry(CustomLogger): # See: https://github.com/open-telemetry/opentelemetry-python/pull/4676 # TODO: Refactor to use the proper OTEL Logs API instead of directly creating SDK LogRecords - from opentelemetry._logs import ( - SeverityNumber, - get_logger, - ) - - # MyPy evaluates both branches of try/except imports and can fail when - # newer OTEL stubs remove/relocate symbols. Gate the typing import so - # only the canonical location is type-checked. - if TYPE_CHECKING: - from opentelemetry.sdk._logs._internal import LogRecord as SdkLogRecord - else: - try: - from opentelemetry.sdk._logs import ( - LogRecord as SdkLogRecord, # type: ignore[attr-defined] - ) - except ImportError: - from opentelemetry.sdk._logs._internal import LogRecord as SdkLogRecord + from opentelemetry._logs import SeverityNumber, get_logger + try: + from opentelemetry.sdk._logs import ( # type: ignore[attr-defined] # OTEL < 1.39.0 + LogRecord as SdkLogRecord, + ) + except ImportError: + from opentelemetry.sdk._logs._internal import ( + LogRecord as SdkLogRecord, # type: ignore[attr-defined] # OTEL >= 1.39.0 + ) otel_logger = get_logger(LITELLM_LOGGER_NAME) diff --git a/litellm/integrations/s3_v2.py b/litellm/integrations/s3_v2.py index 534b85e4752..eddc80dbc1f 100644 --- a/litellm/integrations/s3_v2.py +++ b/litellm/integrations/s3_v2.py @@ -51,6 +51,7 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): s3_use_team_prefix: bool = False, s3_strip_base64_files: bool = False, s3_use_key_prefix: bool = False, + s3_use_virtual_hosted_style: bool = False, **kwargs, ): try: @@ -78,7 +79,8 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): s3_path=s3_path, s3_use_team_prefix=s3_use_team_prefix, s3_strip_base64_files=s3_strip_base64_files, - s3_use_key_prefix=s3_use_key_prefix + s3_use_key_prefix=s3_use_key_prefix, + s3_use_virtual_hosted_style=s3_use_virtual_hosted_style ) verbose_logger.debug(f"s3 logger using endpoint url {s3_endpoint_url}") @@ -135,6 +137,7 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): s3_use_team_prefix: bool = False, s3_strip_base64_files: bool = False, s3_use_key_prefix: bool = False, + s3_use_virtual_hosted_style: bool = False, ): """ Initialize the s3 params for this logging callback @@ -217,6 +220,11 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): or s3_strip_base64_files ) + self.s3_use_virtual_hosted_style = ( + bool(litellm.s3_callback_params.get("s3_use_virtual_hosted_style", False)) + or s3_use_virtual_hosted_style + ) + return async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): @@ -247,8 +255,14 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): standard_logging_payload=kwargs.get("standard_logging_object", None), ) + # afile_delete and other non-model call types never produce a standard_logging_object, + # so s3_batch_logging_element is None. Skip gracefully instead of raising ValueError. if s3_batch_logging_element is None: - raise ValueError("s3_batch_logging_element is None") + verbose_logger.debug( + "s3 Logging - skipping event, no standard_logging_object for call_type=%s", + kwargs.get("call_type", "unknown"), + ) + return verbose_logger.debug( "\ns3 Logger - Logging payload = %s", s3_batch_logging_element @@ -302,13 +316,20 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): url = f"https://{self.s3_bucket_name}.s3.{self.s3_region_name}.amazonaws.com/{batch_logging_element.s3_object_key}" if self.s3_endpoint_url and self.s3_bucket_name: - url = ( - self.s3_endpoint_url - + "/" - + self.s3_bucket_name - + "/" - + batch_logging_element.s3_object_key - ) + if self.s3_use_virtual_hosted_style: + # Virtual-hosted-style: bucket.endpoint/key + endpoint_host = self.s3_endpoint_url.replace("https://", "").replace("http://", "") + protocol = "https://" if self.s3_endpoint_url.startswith("https://") else "http://" + url = f"{protocol}{self.s3_bucket_name}.{endpoint_host}/{batch_logging_element.s3_object_key}" + else: + # Path-style: endpoint/bucket/key + url = ( + self.s3_endpoint_url + + "/" + + self.s3_bucket_name + + "/" + + batch_logging_element.s3_object_key + ) # Convert JSON to string json_string = safe_dumps(batch_logging_element.payload) @@ -456,13 +477,20 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): url = f"https://{self.s3_bucket_name}.s3.{self.s3_region_name}.amazonaws.com/{batch_logging_element.s3_object_key}" if self.s3_endpoint_url and self.s3_bucket_name: - url = ( - self.s3_endpoint_url - + "/" - + self.s3_bucket_name - + "/" - + batch_logging_element.s3_object_key - ) + if self.s3_use_virtual_hosted_style: + # Virtual-hosted-style: bucket.endpoint/key + endpoint_host = self.s3_endpoint_url.replace("https://", "").replace("http://", "") + protocol = "https://" if self.s3_endpoint_url.startswith("https://") else "http://" + url = f"{protocol}{self.s3_bucket_name}.{endpoint_host}/{batch_logging_element.s3_object_key}" + else: + # Path-style: endpoint/bucket/key + url = ( + self.s3_endpoint_url + + "/" + + self.s3_bucket_name + + "/" + + batch_logging_element.s3_object_key + ) # Convert JSON to string json_string = safe_dumps(batch_logging_element.payload) @@ -550,13 +578,20 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): url = f"https://{self.s3_bucket_name}.s3.{self.s3_region_name}.amazonaws.com/{s3_object_key}" if self.s3_endpoint_url and self.s3_bucket_name: - url = ( - self.s3_endpoint_url - + "/" - + self.s3_bucket_name - + "/" - + s3_object_key - ) + if self.s3_use_virtual_hosted_style: + # Virtual-hosted-style: bucket.endpoint/key + endpoint_host = self.s3_endpoint_url.replace("https://", "").replace("http://", "") + protocol = "https://" if self.s3_endpoint_url.startswith("https://") else "http://" + url = f"{protocol}{self.s3_bucket_name}.{endpoint_host}/{s3_object_key}" + else: + # Path-style: endpoint/bucket/key + url = ( + self.s3_endpoint_url + + "/" + + self.s3_bucket_name + + "/" + + s3_object_key + ) # Prepare the request for GET operation # For GET requests, we need x-amz-content-sha256 with hash of empty string @@ -618,4 +653,4 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM): verbose_logger.exception( f"Error retrieving object {object_key} from cold storage: {str(e)}" ) - return None + return None \ No newline at end of file diff --git a/litellm/litellm_core_utils/api_route_to_call_types.py b/litellm/litellm_core_utils/api_route_to_call_types.py index 4146ff6d6a6..2ae9986ce94 100644 --- a/litellm/litellm_core_utils/api_route_to_call_types.py +++ b/litellm/litellm_core_utils/api_route_to_call_types.py @@ -3,6 +3,9 @@ Dictionary mapping API routes to their corresponding CallTypes in LiteLLM. This dictionary maps each API endpoint to the CallTypes that can be used for that route. Each route can have both async (prefixed with 'a') and sync call types. + +Route patterns may contain placeholders like {agent_id}, {model}, {batch_id}; these +match a single path segment when resolving call types for a concrete path. """ from typing import List, Optional @@ -10,17 +13,43 @@ from typing import List, Optional from litellm.types.utils import API_ROUTE_TO_CALL_TYPES, CallTypes +def _route_matches_pattern(route: str, pattern: str) -> bool: + """ + Return True if the concrete route matches the pattern. + Pattern segments like {param} match any single path segment. + """ + route_parts = route.strip("/").split("/") + pattern_parts = pattern.strip("/").split("/") + if len(route_parts) != len(pattern_parts): + return False + for r, p in zip(route_parts, pattern_parts): + if p.startswith("{") and p.endswith("}"): + continue + if r != p: + return False + return True + + def get_call_types_for_route(route: str) -> Optional[List[CallTypes]]: """ Get the list of CallTypes for a given API route. + Supports both exact keys and dynamic patterns (e.g. /a2a/my-agent/message/send + matches /a2a/{agent_id}/message/send). + Args: - route: API route path (e.g., "/chat/completions") + route: API route path (e.g., "/chat/completions" or "/a2a/my-pydantic-agent/message/send") Returns: List of CallTypes for that route, or None if route not found """ - return API_ROUTE_TO_CALL_TYPES.get(route, None) + exact = API_ROUTE_TO_CALL_TYPES.get(route, None) + if exact is not None: + return exact + for pattern, call_types in API_ROUTE_TO_CALL_TYPES.items(): + if _route_matches_pattern(route, pattern): + return call_types + return None def get_routes_for_call_type(call_type: CallTypes) -> list: diff --git a/litellm/llms/a2a/chat/guardrail_translation/handler.py b/litellm/llms/a2a/chat/guardrail_translation/handler.py index 770453f2def..fbd1da749c2 100644 --- a/litellm/llms/a2a/chat/guardrail_translation/handler.py +++ b/litellm/llms/a2a/chat/guardrail_translation/handler.py @@ -10,6 +10,7 @@ A2A Protocol Format: - Output: JSON-RPC 2.0 with result containing message/artifact parts """ +import json from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union from litellm._logging import verbose_proxy_logger @@ -206,6 +207,118 @@ class A2AGuardrailHandler(BaseTranslation): response["result"] = result return response + async def process_output_streaming_response( + self, + responses_so_far: List[Any], + guardrail_to_apply: "CustomGuardrail", + litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None, + user_api_key_dict: Optional["UserAPIKeyAuth"] = None, + ) -> List[Any]: + """ + Process A2A streaming output by applying guardrails to accumulated text. + + responses_so_far can be a list of JSON-RPC 2.0 objects (dict or NDJSON str), e.g.: + - task with history, status-update, artifact-update (with result.artifact.parts), + - then status-update (final). Text is extracted from result.artifact.parts, + result.message.parts, result.parts, etc., concatenated in order, guardrailed once, + then the combined guardrailed text is written into the first chunk that had text + and all other text parts in other chunks are cleared (in-place). + """ + from litellm.llms.a2a.common_utils import extract_text_from_a2a_response + + # Parse each item; keep alignment with responses_so_far (None where unparseable) + parsed: List[Optional[Dict[str, Any]]] = [None] * len(responses_so_far) + for i, item in enumerate(responses_so_far): + if isinstance(item, dict): + obj = item + elif isinstance(item, str): + try: + obj = json.loads(item.strip()) + except (json.JSONDecodeError, TypeError): + continue + else: + continue + if isinstance(obj.get("result"), dict): + parsed[i] = obj + + valid_parsed = [(i, obj) for i, obj in enumerate(parsed) if obj is not None] + if not valid_parsed: + return responses_so_far + + # Collect text from each chunk in order (by original index in responses_so_far) + text_parts: List[str] = [] + chunk_indices_with_text: List[int] = [] # indices into valid_parsed + for idx, (orig_i, obj) in enumerate(valid_parsed): + t = extract_text_from_a2a_response(obj) + if t: + text_parts.append(t) + chunk_indices_with_text.append(orig_i) + + combined_text = "".join(text_parts) + if not combined_text: + return responses_so_far + + request_data: dict = {"responses_so_far": responses_so_far} + 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=[combined_text]) + 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", []) + if not guardrailed_texts: + return responses_so_far + guardrailed_text = guardrailed_texts[0] + + # Find first chunk (by original index) that has text; put full guardrailed text there and clear rest + first_chunk_with_text: Optional[int] = ( + chunk_indices_with_text[0] if chunk_indices_with_text else None + ) + + for orig_i, obj in valid_parsed: + result = obj.get("result", {}) + if not isinstance(result, dict): + continue + texts_in_chunk: List[str] = [] + mappings: List[Tuple[Tuple[str, ...], int]] = [] + self._extract_texts_from_result( + result=result, + texts_to_check=texts_in_chunk, + task_mappings=mappings, + ) + if not mappings: + continue + if orig_i == first_chunk_with_text: + # Put full guardrailed text in first text part; clear others + for task_idx, (path, part_idx) in enumerate(mappings): + text = guardrailed_text if task_idx == 0 else "" + self._apply_text_to_path( + result=result, + path=path, + part_idx=part_idx, + text=text, + ) + else: + for path, part_idx in mappings: + self._apply_text_to_path( + result=result, + path=path, + part_idx=part_idx, + text="", + ) + + # Write back to responses_so_far where we had NDJSON strings + for i, item in enumerate(responses_so_far): + if isinstance(item, str) and parsed[i] is not None: + responses_so_far[i] = json.dumps(parsed[i]) + "\n" + + return responses_so_far + def _extract_texts_from_result( self, result: Dict[str, Any], diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py index c2cfff80685..85a4790a9b9 100644 --- a/litellm/llms/anthropic/chat/transformation.py +++ b/litellm/llms/anthropic/chat/transformation.py @@ -1282,9 +1282,13 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): output_config = optional_params.get("output_config") if output_config and isinstance(output_config, dict): effort = output_config.get("effort") - if effort and effort not in ["high", "medium", "low"]: + if effort and effort not in ["high", "medium", "low", "max"]: raise ValueError( - f"Invalid effort value: {effort}. Must be one of: 'high', 'medium', 'low'" + f"Invalid effort value: {effort}. Must be one of: 'high', 'medium', 'low', 'max'" + ) + if effort == "max" and not self._is_claude_opus_4_6(model): + raise ValueError( + f"effort='max' is only supported by Claude Opus 4.6. Got model: {model}" ) data["output_config"] = output_config diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/handler.py b/litellm/llms/anthropic/experimental_pass_through/adapters/handler.py index c6caaddf98b..73e74c228ba 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/handler.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/handler.py @@ -19,6 +19,7 @@ from litellm.types.llms.anthropic_messages.anthropic_response import ( AnthropicMessagesResponse, ) from litellm.types.utils import ModelResponse +from litellm.utils import get_model_info if TYPE_CHECKING: pass @@ -63,6 +64,14 @@ class LiteLLMMessagesToCompletionTransformationHandler: return model = completion_kwargs.get("model") + try: + model_info = get_model_info(model=cast(str, model), custom_llm_provider=custom_llm_provider) + if model_info and model_info.get("supports_reasoning") is False: + # Model doesn't support reasoning/responses API, don't route + return + except Exception: + pass + if isinstance(model, str) and model and not model.startswith("responses/"): # Prefix model with "responses/" to route to OpenAI Responses API completion_kwargs["model"] = f"responses/{model}" diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py index a86820f82e8..de634ff9ecf 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py @@ -239,8 +239,13 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): merged_chunk["delta"] = {} # Add usage to the held chunk + uncached_input_tokens = chunk.usage.prompt_tokens or 0 + if hasattr(chunk.usage, "prompt_tokens_details") and chunk.usage.prompt_tokens_details: + cached_tokens = getattr(chunk.usage.prompt_tokens_details, "cached_tokens", 0) or 0 + uncached_input_tokens -= cached_tokens + usage_dict: UsageDelta = { - "input_tokens": chunk.usage.prompt_tokens or 0, + "input_tokens": uncached_input_tokens, "output_tokens": chunk.usage.completion_tokens or 0, } # Add cache tokens if available (for prompt caching support) @@ -412,6 +417,7 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): if block_type == "tool_use": # Type narrowing: content_block_start is ToolUseBlock when block_type is "tool_use" from typing import cast + from litellm.types.llms.anthropic import ToolUseBlock tool_block = cast(ToolUseBlock, content_block_start) @@ -430,6 +436,7 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): # if we get a function name since it signals a new tool call if block_type == "tool_use": from typing import cast + from litellm.types.llms.anthropic import ToolUseBlock tool_block = cast(ToolUseBlock, content_block_start) diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py index 169b138a5f7..efbac13735c 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py @@ -1070,8 +1070,13 @@ class LiteLLMAnthropicMessagesAdapter: ) # extract usage usage: Usage = getattr(response, "usage") + uncached_input_tokens = usage.prompt_tokens or 0 + if hasattr(usage, "prompt_tokens_details") and usage.prompt_tokens_details: + cached_tokens = getattr(usage.prompt_tokens_details, "cached_tokens", 0) or 0 + uncached_input_tokens -= cached_tokens + anthropic_usage = AnthropicUsage( - input_tokens=usage.prompt_tokens or 0, + input_tokens=uncached_input_tokens, output_tokens=usage.completion_tokens or 0, ) # Add cache tokens if available (for prompt caching support) @@ -1230,8 +1235,13 @@ class LiteLLMAnthropicMessagesAdapter: else: litellm_usage_chunk = None if litellm_usage_chunk is not None: + uncached_input_tokens = litellm_usage_chunk.prompt_tokens or 0 + if hasattr(litellm_usage_chunk, "prompt_tokens_details") and litellm_usage_chunk.prompt_tokens_details: + cached_tokens = getattr(litellm_usage_chunk.prompt_tokens_details, "cached_tokens", 0) or 0 + uncached_input_tokens -= cached_tokens + usage_delta = UsageDelta( - input_tokens=litellm_usage_chunk.prompt_tokens or 0, + input_tokens=uncached_input_tokens, output_tokens=litellm_usage_chunk.completion_tokens or 0, ) # Add cache tokens if available (for prompt caching support) diff --git a/litellm/llms/azure/responses/transformation.py b/litellm/llms/azure/responses/transformation.py index 44ce368fd49..78631d38005 100644 --- a/litellm/llms/azure/responses/transformation.py +++ b/litellm/llms/azure/responses/transformation.py @@ -1,5 +1,5 @@ -from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Tuple, Union from copy import deepcopy +from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Tuple, Union import httpx from openai.types.responses import ResponseReasoningItem @@ -21,10 +21,25 @@ else: class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): + + # Parameters not supported by Azure Responses API + AZURE_UNSUPPORTED_PARAMS = ["context_management"] + @property def custom_llm_provider(self) -> LlmProviders: return LlmProviders.AZURE + def get_supported_openai_params(self, model: str) -> list: + """ + Azure Responses API does not support context_management (compaction). + """ + base_supported_params = super().get_supported_openai_params(model) + return [ + param + for param in base_supported_params + if param not in self.AZURE_UNSUPPORTED_PARAMS + ] + def validate_environment( self, headers: dict, model: str, litellm_params: Optional[GenericLiteLLMParams] ) -> dict: diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py index 2c82e39d76b..cf2f9c9f774 100644 --- a/litellm/llms/bedrock/chat/converse_transformation.py +++ b/litellm/llms/bedrock/chat/converse_transformation.py @@ -12,7 +12,10 @@ import httpx import litellm from litellm._logging import verbose_logger -from litellm.constants import RESPONSE_FORMAT_TOOL_NAME +from litellm.constants import ( + BEDROCK_MIN_THINKING_BUDGET_TOKENS, + RESPONSE_FORMAT_TOOL_NAME, +) from litellm.litellm_core_utils.core_helpers import ( filter_exceptions_from_params, filter_internal_params, @@ -463,6 +466,25 @@ class AmazonConverseConfig(BaseConfig): reasoning_effort=reasoning_effort, model=model ) + @staticmethod + def _clamp_thinking_budget_tokens(optional_params: dict) -> None: + """ + Clamp thinking.budget_tokens to the Bedrock minimum (1024). + + Bedrock returns a 400 error if budget_tokens < 1024. + """ + thinking = optional_params.get("thinking") + if isinstance(thinking, dict): + budget = thinking.get("budget_tokens") + if isinstance(budget, int) and budget < BEDROCK_MIN_THINKING_BUDGET_TOKENS: + verbose_logger.debug( + "Bedrock requires thinking.budget_tokens >= %d, got %d. " + "Clamping to minimum.", + BEDROCK_MIN_THINKING_BUDGET_TOKENS, + budget, + ) + thinking["budget_tokens"] = BEDROCK_MIN_THINKING_BUDGET_TOKENS + def get_supported_openai_params(self, model: str) -> List[str]: from litellm.utils import supports_function_calling @@ -1002,9 +1024,14 @@ class AmazonConverseConfig(BaseConfig): Checks 'non_default_params' for 'thinking' and 'max_tokens' if 'thinking' is enabled and 'max_tokens' is not specified, set 'max_tokens' to the thinking token budget + DEFAULT_MAX_TOKENS + + Also clamps thinking.budget_tokens to the Bedrock minimum (1024) to + prevent 400 errors from the Bedrock API. """ from litellm.constants import DEFAULT_MAX_TOKENS + self._clamp_thinking_budget_tokens(optional_params) + is_thinking_enabled = self.is_thinking_enabled(optional_params) is_max_tokens_in_request = self.is_max_tokens_in_request(non_default_params) if is_thinking_enabled and not is_max_tokens_in_request: diff --git a/litellm/llms/chatgpt/responses/transformation.py b/litellm/llms/chatgpt/responses/transformation.py index 0ce24f63a89..bcb6edd39f9 100644 --- a/litellm/llms/chatgpt/responses/transformation.py +++ b/litellm/llms/chatgpt/responses/transformation.py @@ -73,10 +73,6 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): litellm_params, headers, ) - request.pop("max_output_tokens", None) - request.pop("max_tokens", None) - request.pop("max_completion_tokens", None) - request.pop("metadata", None) base_instructions = get_chatgpt_default_instructions() existing_instructions = request.get("instructions") if existing_instructions: @@ -92,7 +88,22 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): if "reasoning.encrypted_content" not in include: include.append("reasoning.encrypted_content") request["include"] = include - return request + + allowed_keys = { + "model", + "input", + "instructions", + "stream", + "store", + "include", + "tools", + "tool_choice", + "reasoning", + "previous_response_id", + "truncation", + } + + return {k: v for k, v in request.items() if k in allowed_keys} def transform_response_api_response( self, diff --git a/litellm/llms/custom_httpx/aiohttp_transport.py b/litellm/llms/custom_httpx/aiohttp_transport.py index fb98006c7e4..6cec1f4fe16 100644 --- a/litellm/llms/custom_httpx/aiohttp_transport.py +++ b/litellm/llms/custom_httpx/aiohttp_transport.py @@ -119,8 +119,13 @@ class AiohttpResponseStream(httpx.AsyncByteStream): class AiohttpTransport(httpx.AsyncBaseTransport): - def __init__(self, client: Union[ClientSession, Callable[[], ClientSession]]) -> None: + def __init__( + self, + client: Union[ClientSession, Callable[[], ClientSession]], + owns_session: bool = True, + ) -> None: self.client = client + self._owns_session = owns_session ######################################################### # Class variables for proxy settings @@ -128,7 +133,7 @@ class AiohttpTransport(httpx.AsyncBaseTransport): self.proxy_cache: Dict[str, Optional[str]] = {} async def aclose(self) -> None: - if isinstance(self.client, ClientSession): + if self._owns_session and isinstance(self.client, ClientSession): await self.client.close() @@ -144,10 +149,11 @@ class LiteLLMAiohttpTransport(AiohttpTransport): self, client: Union[ClientSession, Callable[[], ClientSession]], ssl_verify: Optional[Union[bool, ssl.SSLContext]] = None, + owns_session: bool = True, ): self.client = client self._ssl_verify = ssl_verify # Store for per-request SSL override - super().__init__(client=client) + super().__init__(client=client, owns_session=owns_session) # Store the client factory for recreating sessions when needed if callable(client): self._client_factory = client diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 5cf6efe5ba2..328097639e5 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -866,6 +866,7 @@ class AsyncHTTPHandler: return LiteLLMAiohttpTransport( client=shared_session, ssl_verify=ssl_for_transport, + owns_session=False, ) # Create new session only if none provided or existing one is invalid diff --git a/litellm/llms/openai_like/dynamic_config.py b/litellm/llms/openai_like/dynamic_config.py index 1e7866bebbe..a2ce6b9a531 100644 --- a/litellm/llms/openai_like/dynamic_config.py +++ b/litellm/llms/openai_like/dynamic_config.py @@ -4,6 +4,7 @@ Dynamic configuration class generator for JSON-based providers. from typing import Any, Coroutine, List, Literal, Optional, Tuple, Union, overload +from litellm._logging import verbose_logger from litellm.litellm_core_utils.prompt_templates.common_utils import ( handle_messages_with_content_list_to_str_conversion, ) @@ -96,8 +97,27 @@ def create_config_class(provider: SimpleProviderConfig): return api_base def get_supported_openai_params(self, model: str) -> list: - """Get supported OpenAI params from base class""" - return super().get_supported_openai_params(model=model) + """Get supported OpenAI params, excluding tool-related params for models + that don't support function calling.""" + from litellm.utils import supports_function_calling + + supported_params = super().get_supported_openai_params(model=model) + + _supports_fc = supports_function_calling( + model=model, custom_llm_provider=provider.slug + ) + + if not _supports_fc: + tool_params = ["tools", "tool_choice", "function_call", "functions", "parallel_tool_calls"] + for param in tool_params: + if param in supported_params: + supported_params.remove(param) + verbose_logger.debug( + f"Model {model} on provider {provider.slug} does not support " + f"function calling — removed tool-related params from supported params." + ) + + return supported_params def map_openai_params( self, diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/llama3/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/llama3/transformation.py index a70e16000b6..51310e4fa85 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/llama3/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/llama3/transformation.py @@ -9,7 +9,13 @@ from litellm.llms.openai.chat.gpt_transformation import ( OpenAIGPTConfig, ) from litellm.types.llms.openai import AllMessageValues, OpenAIChatCompletionResponse -from litellm.types.utils import ModelResponse, ModelResponseStream, Usage +from litellm.types.utils import ( + Delta, + ModelResponse, + ModelResponseStream, + StreamingChoices, + Usage, +) from ...common_utils import VertexAIError @@ -145,17 +151,74 @@ class VertexAILlama3StreamingHandler(OpenAIChatCompletionStreamingHandler): """ Vertex AI Llama models may not include role in streaming chunk deltas. This handler ensures the first chunk always has role="assistant". + + When Vertex AI returns a single chunk with both role and finish_reason (empty response), + this handler splits it into two chunks: + 1. First chunk: role="assistant", content="", finish_reason=None + 2. Second chunk: role=None, content=None, finish_reason="stop" + + This matches OpenAI's streaming format where the first chunk has role and + the final chunk has finish_reason but no role. """ def __init__(self, **kwargs): super().__init__(**kwargs) self.sent_role = False + self._pending_chunk: Optional[ModelResponseStream] = None def chunk_parser(self, chunk: dict) -> ModelResponseStream: result = super().chunk_parser(chunk) if not self.sent_role and result.choices: delta = result.choices[0].delta - if delta.role is None: + finish_reason = result.choices[0].finish_reason + + # If this is both the first chunk AND the final chunk (has finish_reason), + # we need to split it into two chunks to match OpenAI format + if finish_reason is not None: + # Create a pending final chunk with finish_reason but no role + self._pending_chunk = ModelResponseStream( + id=result.id, + object="chat.completion.chunk", + created=result.created, + model=result.model, + choices=[ + StreamingChoices( + index=0, + delta=Delta(content=None, role=None), + finish_reason=finish_reason, + ) + ], + ) + # Modify current chunk to be the first chunk with role but no finish_reason + result.choices[0].finish_reason = None delta.role = "assistant" + # Ensure content is empty string for first chunk, not None + if delta.content is None: + delta.content = "" + # Prevent downstream stream wrapper from dropping this chunk + # (it drops empty-content chunks unless special fields are present) + if delta.provider_specific_fields is None: + delta.provider_specific_fields = {} + elif delta.role is None: + delta.role = "assistant" + # If the first chunk has empty content, ensure it's still emitted + if (delta.content == "" or delta.content is None) and delta.provider_specific_fields is None: + delta.provider_specific_fields = {} self.sent_role = True return result + + def __next__(self): + # First return any pending chunk from a previous split + if self._pending_chunk is not None: + chunk = self._pending_chunk + self._pending_chunk = None + return chunk + return super().__next__() + + async def __anext__(self): + # First return any pending chunk from a previous split + if self._pending_chunk is not None: + chunk = self._pending_chunk + self._pending_chunk = None + return chunk + return await super().__anext__() diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 64eceae3297..2b6d2800124 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -12456,6 +12456,19 @@ "supports_tool_choice": true, "supports_web_search": true }, + "fireworks_ai/accounts/fireworks/models/kimi-k2p5": { + "input_cost_per_token": 6e-07, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "max_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 3e-06, + "source": "https://fireworks.ai/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, "fireworks_ai/accounts/fireworks/models/llama-v3p1-405b-instruct": { "input_cost_per_token": 3e-06, "litellm_provider": "fireworks_ai", @@ -23204,7 +23217,7 @@ "mode": "chat", "output_cost_per_token": 6e-05, "supports_function_calling": true, - "supports_parallel_function_calling": true, + "supports_parallel_function_calling": false, "supports_pdf_input": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -23759,7 +23772,7 @@ "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", - "output_cost_per_token": 1.5e-07, + "output_cost_per_token": 1.5e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, "supports_response_schema": false @@ -23807,7 +23820,7 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", - "output_cost_per_token": 1.5e-07, + "output_cost_per_token": 1.5e-05, "source": "https://www.oracle.com/artificial-intelligence/generative-ai/generative-ai-service/pricing", "supports_function_calling": true, "supports_response_schema": false diff --git a/litellm/policy_templates_backup.json b/litellm/policy_templates_backup.json index 6541839611b..a0ffd6acd30 100644 --- a/litellm/policy_templates_backup.json +++ b/litellm/policy_templates_backup.json @@ -2,7 +2,7 @@ { "id": "advanced-au-pii-protection", "title": "Advanced PII Protection (Australia)", - "description": "Comprehensive PII detection and masking for Australia. Protects Australian-specific identifiers, international employee data, financial information, credentials, protected class information, and industry-specific sensitive data.", + "description": "Protects Australian-specific identifiers, international employee data, financial information, credentials, protected class information, and industry-specific sensitive data.", "icon": "ShieldCheckIcon", "iconColor": "text-purple-500", "iconBg": "bg-purple-50", @@ -274,5 +274,405 @@ ], "guardrails_remove": [] } + }, + { + "id": "nsfw-content-filter-australia", + "title": "NSFW Content Filter (Australia)", + "description": "Blocks profanity, sexual content, NSFW requests, self-harm content, and child safety violations using English and Australian-specific slang. Protects against inappropriate content including sexual solicitation, explicit content, Australian profanity, self-harm, and content involving minors.", + "icon": "ShieldExclamationIcon", + "iconColor": "text-red-500", + "iconBg": "bg-red-50", + "guardrails": [ + "nsfw-content-filter-english", + "nsfw-content-filter-australian", + "nsfw-self-harm-filter", + "nsfw-child-safety-filter", + "nsfw-racial-bias-filter" + ], + "complexity": "Medium", + "guardrailDefinitions": [ + { + "guardrail_name": "nsfw-content-filter-english", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks profanity, sexual content, slurs, and NSFW terms in English" + } + }, + { + "guardrail_name": "nsfw-content-filter-australian", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse_au", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks Australian-specific slang and profanity (root, perv, bogan, wanker, etc.)" + } + }, + { + "guardrail_name": "nsfw-self-harm-filter", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_self_harm", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks content related to self-harm, suicide, and eating disorders" + } + }, + { + "guardrail_name": "nsfw-child-safety-filter", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_child_safety", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks inappropriate content involving minors using identifier + block word combinations" + } + }, + { + "guardrail_name": "nsfw-racial-bias-filter", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "bias_racial", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks racial and ethnic discrimination, hate speech, and supremacist content" + } + } + ], + "templateData": { + "policy_name": "nsfw-content-filter-australia", + "description": "NSFW content filter for Australia. Blocks profanity, sexual content, inappropriate requests, self-harm content, child safety violations, and racial bias in English and Australian slang.", + "guardrails_add": [ + "nsfw-content-filter-english", + "nsfw-content-filter-australian", + "nsfw-self-harm-filter", + "nsfw-child-safety-filter", + "nsfw-racial-bias-filter" + ], + "guardrails_remove": [] + } + }, + { + "id": "nsfw-content-filter-basic", + "title": "NSFW Content Filter (Basic)", + "description": "Basic NSFW content filtering for English only. Blocks profanity, sexual content, slurs, solicitation, explicit requests, self-harm content, and child safety violations. Suitable for most applications requiring content moderation.", + "icon": "ShieldExclamationIcon", + "iconColor": "text-orange-500", + "iconBg": "bg-orange-50", + "guardrails": [ + "nsfw-content-filter-english-only", + "nsfw-self-harm-filter-basic", + "nsfw-child-safety-filter-basic", + "nsfw-racial-bias-filter-basic" + ], + "complexity": "Low", + "guardrailDefinitions": [ + { + "guardrail_name": "nsfw-content-filter-english-only", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks profanity, sexual content, slurs, and NSFW terms. Includes 485+ keywords covering explicit content, solicitation, sexual behavior, and exploitation." + } + }, + { + "guardrail_name": "nsfw-self-harm-filter-basic", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_self_harm", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks content related to self-harm, suicide, and eating disorders" + } + }, + { + "guardrail_name": "nsfw-child-safety-filter-basic", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_child_safety", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks inappropriate content involving minors using identifier + block word combinations" + } + }, + { + "guardrail_name": "nsfw-racial-bias-filter-basic", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "bias_racial", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks racial and ethnic discrimination, hate speech, and supremacist content" + } + } + ], + "templateData": { + "policy_name": "nsfw-content-filter-basic", + "description": "Basic NSFW content filter. Blocks profanity, sexual content, inappropriate requests, self-harm content, child safety violations, and racial bias in English.", + "guardrails_add": [ + "nsfw-content-filter-english-only", + "nsfw-self-harm-filter-basic", + "nsfw-child-safety-filter-basic", + "nsfw-racial-bias-filter-basic" + ], + "guardrails_remove": [] + } + }, + { + "id": "nsfw-content-filter-all-regions", + "title": "NSFW Content Filter (All Regions)", + "description": "Comprehensive multi-language NSFW content filtering. Blocks profanity, sexual content, inappropriate requests, self-harm content, and child safety violations in English, Spanish, French, German, and Australian. Best for global applications.", + "icon": "ShieldExclamationIcon", + "iconColor": "text-purple-500", + "iconBg": "bg-purple-50", + "guardrails": [ + "nsfw-filter-english", + "nsfw-filter-spanish", + "nsfw-filter-french", + "nsfw-filter-german", + "nsfw-filter-australian", + "nsfw-self-harm-filter-global", + "nsfw-child-safety-filter-global", + "nsfw-racial-bias-filter-global" + ], + "complexity": "High", + "guardrailDefinitions": [ + { + "guardrail_name": "nsfw-filter-english", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "English profanity, sexual content, slurs, and NSFW terms (485+ keywords)" + } + }, + { + "guardrail_name": "nsfw-filter-spanish", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse_es", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Spanish profanity and offensive terms (68 keywords)" + } + }, + { + "guardrail_name": "nsfw-filter-french", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse_fr", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "French profanity and offensive terms (91 keywords)" + } + }, + { + "guardrail_name": "nsfw-filter-german", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse_de", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "German profanity and offensive terms (65 keywords)" + } + }, + { + "guardrail_name": "nsfw-filter-australian", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harm_toxic_abuse_au", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Australian slang and profanity (32 keywords: root, perv, bogan, wanker, etc.)" + } + }, + { + "guardrail_name": "nsfw-self-harm-filter-global", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_self_harm", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks content related to self-harm, suicide, and eating disorders" + } + }, + { + "guardrail_name": "nsfw-child-safety-filter-global", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "harmful_child_safety", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks inappropriate content involving minors using identifier + block word combinations" + } + }, + { + "guardrail_name": "nsfw-racial-bias-filter-global", + "litellm_params": { + "guardrail": "litellm_content_filter", + "mode": "pre_call", + "categories": [ + { + "category": "bias_racial", + "enabled": true, + "action": "BLOCK", + "severity_threshold": "medium" + } + ] + }, + "guardrail_info": { + "description": "Blocks racial and ethnic discrimination, hate speech, and supremacist content" + } + } + ], + "templateData": { + "policy_name": "nsfw-content-filter-all-regions", + "description": "Comprehensive multi-language NSFW content filter. Blocks profanity, inappropriate content, self-harm, child safety violations, and racial bias in English, Spanish, French, German, and Australian. Total coverage: 741+ keywords across all languages plus self-harm, child safety, and racial bias protection.", + "guardrails_add": [ + "nsfw-filter-english", + "nsfw-filter-spanish", + "nsfw-filter-french", + "nsfw-filter-german", + "nsfw-filter-australian", + "nsfw-self-harm-filter-global", + "nsfw-child-safety-filter-global", + "nsfw-racial-bias-filter-global" + ], + "guardrails_remove": [] + } } ] diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index ba107a9dd10..31836a27509 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -149,7 +149,7 @@ if MCP_AVAILABLE: app=server, event_store=None, json_response=False, # enables SSE streaming - stateless=False, # enables session state + stateless=True, ) # Create SSE session manager diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html index 788e9379f62..c73aba563bc 100644 --- a/litellm/proxy/_experimental/out/404.html +++ b/litellm/proxy/_experimental/out/404.html @@ -1 +1 @@ -404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

\ No newline at end of file +404: This page could not be found.LiteLLM Dashboard

404

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this.done(),rF(this,ea,"m",el).call(this)}async finalFunctionCall(){return await this.done(),rF(this,ea,"m",eu).call(this)}async finalFunctionCallResult(){return await this.done(),rF(this,ea,"m",ec).call(this)}async totalUsage(){return await this.done(),rF(this,ea,"m",eh).call(this)}allChatCompletions(){return[...this._chatCompletions]}_emitFinal(){let e=this._chatCompletions[this._chatCompletions.length-1];e&&this._emit("finalChatCompletion",e);let t=rF(this,ea,"m",el).call(this);t&&this._emit("finalMessage",t);let r=rF(this,ea,"m",eo).call(this);r&&this._emit("finalContent",r);let s=rF(this,ea,"m",eu).call(this);s&&this._emit("finalFunctionCall",s);let n=rF(this,ea,"m",ec).call(this);null!=n&&this._emit("finalFunctionCallResult",n),this._chatCompletions.some(e=>e.usage)&&this._emit("totalUsage",rF(this,ea,"m",eh).call(this))}async _createChatCompletion(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort())),rF(this,ea,"m",ef).call(this,t);let n=await e.chat.completions.create({...t,stream:!1},{...r,signal:this.controller.signal});return this._connected(),this._addChatCompletion(rU(n,t))}async _runChatCompletion(e,t,r){for(let e of t.messages)this._addMessage(e,!1);return await this._createChatCompletion(e,t,r)}async _runFunctions(e,t,r){let s="function",{function_call:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.name,{maxChatCompletions:l=10}=r||{},u={};for(let e of t.functions)u[e.name||e.function.name]=e;let c=t.functions.map(e=>({name:e.name||e.function.name,parameters:e.parameters,description:e.description}));for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e.name)).join(", ")}. Please try again`;this._addMessage({role:s,name:h,content:e});continue}try{t=rO(d)?await d.parse(f):f}catch(e){this._addMessage({role:s,name:h,content:e instanceof Error?e.message:String(e)});continue}let p=await d.function(t,this),m=rF(this,ea,"m",ed).call(this,p);if(this._addMessage({role:s,name:h,content:m}),o)return}}async _runTools(e,t,r){let s="tool",{tool_choice:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.function?.name,{maxChatCompletions:l=10}=r||{},u=t.tools.map(e=>{if(rL(e)){if(!e.$callback)throw new O("Tool given to `.runTools()` that does not have an associated function");return{type:"function",function:{function:e.$callback,name:e.function.name,description:e.function.description||"",parameters:e.function.parameters,parse:e.$parseRaw,strict:!0}}}return e}),c={};for(let e of u)"function"===e.type&&(c[e.function.name||e.function.function.name]=e.function);let h="tools"in t?u.map(e=>"function"===e.type?{type:"function",function:{name:e.function.name||e.function.function.name,parameters:e.function.parameters,description:e.function.description,strict:e.function.strict}}:e):void 0;for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e)).join(", ")}. Please try again`;this._addMessage({role:s,tool_call_id:r,content:e});continue}try{t=rO(a)?await a.parse(i):i}catch(t){let e=t instanceof Error?t.message:String(t);this._addMessage({role:s,tool_call_id:r,content:e});continue}let l=await a.function(t,this),u=rF(this,ea,"m",ed).call(this,l);if(this._addMessage({role:s,tool_call_id:r,content:u}),o)return}}}}ea=new WeakSet,eo=function(){return rF(this,ea,"m",el).call(this).content??null},el=function(){let e=this.messages.length;for(;e-- >0;){let t=this.messages[e];if(rC(t)){let{function_call:e,...r}=t,s={...r,content:t.content??null,refusal:t.refusal??null};return e&&(s.function_call=e),s}}throw new O("stream ended without producing a ChatCompletionMessage with role=assistant")},eu=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rC(t)&&t?.function_call)return t.function_call;if(rC(t)&&t?.tool_calls?.length)return t.tool_calls.at(-1)?.function}},ec=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rk(t)&&null!=t.content||rT(t)&&null!=t.content&&"string"==typeof t.content&&this.messages.some(e=>"assistant"===e.role&&e.tool_calls?.some(e=>"function"===e.type&&e.id===t.tool_call_id)))return t.content}},eh=function(){let e={completion_tokens:0,prompt_tokens:0,total_tokens:0};for(let{usage:t}of this._chatCompletions)t&&(e.completion_tokens+=t.completion_tokens,e.prompt_tokens+=t.prompt_tokens,e.total_tokens+=t.total_tokens);return e},ef=function(e){if(null!=e.n&&e.n>1)throw new O("ChatCompletion convenience helpers only support n=1 at this time. 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write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r},rY=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)};class rQ extends rW{constructor(e){super(),ep.add(this),em.set(this,void 0),eg.set(this,void 0),ey.set(this,void 0),rz(this,em,e,"f"),rz(this,eg,[],"f")}get currentChatCompletionSnapshot(){return rY(this,ey,"f")}static fromReadableStream(e){let t=new rQ(null);return t._run(()=>t._fromReadableStream(e)),t}static createChatCompletion(e,t,r){let s=new rQ(t);return s._run(()=>s._runChatCompletion(e,{...t,stream:!0},{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}async _createChatCompletion(e,t,r){super._createChatCompletion;let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort())),rY(this,ep,"m",ew).call(this);let n=await e.chat.completions.create({...t,stream:!0},{...r,signal:this.controller.signal});for await(let e of(this._connected(),n))rY(this,ep,"m",e_).call(this,e);if(n.controller.signal?.aborted)throw new k;return this._addChatCompletion(rY(this,ep,"m",eA).call(this))}async _fromReadableStream(e,t){let r;let s=t?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort())),rY(this,ep,"m",ew).call(this),this._connected();let n=e3.fromReadableStream(e,this.controller);for await(let e of n)r&&r!==e.id&&this._addChatCompletion(rY(this,ep,"m",eA).call(this)),rY(this,ep,"m",e_).call(this,e),r=e.id;if(n.controller.signal?.aborted)throw new k;return this._addChatCompletion(rY(this,ep,"m",eA).call(this))}[(em=new WeakMap,eg=new WeakMap,ey=new WeakMap,ep=new WeakSet,ew=function(){this.ended||rz(this,ey,void 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e=t.choices[r.index];null!=r.delta.content&&e.message?.role==="assistant"&&e.message?.content&&(this._emit("content",r.delta.content,e.message.content),this._emit("content.delta",{delta:r.delta.content,snapshot:e.message.content,parsed:e.message.parsed})),null!=r.delta.refusal&&e.message?.role==="assistant"&&e.message?.refusal&&this._emit("refusal.delta",{delta:r.delta.refusal,snapshot:e.message.refusal}),r.logprobs?.content!=null&&e.message?.role==="assistant"&&this._emit("logprobs.content.delta",{content:r.logprobs?.content,snapshot:e.logprobs?.content??[]}),r.logprobs?.refusal!=null&&e.message?.role==="assistant"&&this._emit("logprobs.refusal.delta",{refusal:r.logprobs?.refusal,snapshot:e.logprobs?.refusal??[]});let s=rY(this,ep,"m",eb).call(this,e);for(let t of(e.finish_reason&&(rY(this,ep,"m",ex).call(this,e),null!=s.current_tool_call_index&&rY(this,ep,"m",ev).call(this,e,s.current_tool_call_index)),r.delta.tool_calls??[]))s.current_tool_call_index!==t.index&&(rY(this,ep,"m",ex).call(this,e),null!=s.current_tool_call_index&&rY(this,ep,"m",ev).call(this,e,s.current_tool_call_index)),s.current_tool_call_index=t.index;for(let t of r.delta.tool_calls??[]){let r=e.message.tool_calls?.[t.index];r?.type&&(r?.type==="function"?this._emit("tool_calls.function.arguments.delta",{name:r.function?.name,index:t.index,arguments:r.function.arguments,parsed_arguments:r.function.parsed_arguments,arguments_delta:t.function?.arguments??""}):r?.type)}}},ev=function(e,t){if(rY(this,ep,"m",eb).call(this,e).done_tool_calls.has(t))return;let r=e.message.tool_calls?.[t];if(!r)throw Error("no tool call snapshot");if(!r.type)throw Error("tool call snapshot missing `type`");if("function"===r.type){let 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X}if(Object.assign(e,h),!a)continue;let{content:o,refusal:f,function_call:d,role:p,tool_calls:m,...g}=a;if(Object.assign(e.message,g),f&&(e.message.refusal=(e.message.refusal||"")+f),p&&(e.message.role=p),d&&(e.message.function_call?(d.name&&(e.message.function_call.name=d.name),d.arguments&&((s=e.message.function_call).arguments??(s.arguments=""),e.message.function_call.arguments+=d.arguments)):e.message.function_call=d),o&&(e.message.content=(e.message.content||"")+o,!e.message.refusal&&rY(this,ep,"m",eS).call(this)&&(e.message.parsed=rK(e.message.content))),m)for(let{index:t,id:r,type:s,function:i,...a}of(e.message.tool_calls||(e.message.tool_calls=[]),m)){let o=(n=e.message.tool_calls)[t]??(n[t]={});Object.assign(o,a),r&&(o.id=r),s&&(o.type=s),i&&(o.function??(o.function={name:i.name??"",arguments:""})),i?.name&&(o.function.name=i.name),i?.arguments&&(o.function.arguments+=i.arguments,function(e,t){if(!e)return!1;let r=e.tools?.find(e=>e.function?.name===t.function.name);return rL(r)||r?.function.strict||!1}(rY(this,em,"f"),o)&&(o.function.parsed_arguments=rK(o.function.arguments)))}}return i},Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("chunk",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rG(e){return JSON.stringify(e)}class rZ extends rQ{static fromReadableStream(e){let t=new rZ(null);return t._run(()=>t._fromReadableStream(e)),t}static runFunctions(e,t,r){let s=new rZ(null),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runFunctions"}};return s._run(()=>s._runFunctions(e,t,n)),s}static runTools(e,t,r){let s=new rZ(t),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runTools"}};return s._run(()=>s._runTools(e,t,n)),s}}class r0 extends tY{parse(e,t){return!function(e){for(let t of e??[]){if("function"!==t.type)throw new O(`Currently only \`function\` tool types support auto-parsing; Received \`${t.type}\``);if(!0!==t.function.strict)throw new O(`The \`${t.function.name}\` tool is not marked with \`strict: true\`. Only strict function tools can be auto-parsed`)}}(e.tools),this._client.chat.completions.create(e,{...t,headers:{...t?.headers,"X-Stainless-Helper-Method":"beta.chat.completions.parse"}})._thenUnwrap(t=>rU(t,e))}runFunctions(e,t){return e.stream?rZ.runFunctions(this._client,e,t):rq.runFunctions(this._client,e,t)}runTools(e,t){return e.stream?rZ.runTools(this._client,e,t):rq.runTools(this._client,e,t)}stream(e,t){return rQ.createChatCompletion(this._client,e,t)}}class r1 extends tY{constructor(){super(...arguments),this.completions=new r0(this._client)}}(r1||(r1={})).Completions=r0;class r2 extends tY{create(e,t){return this._client.post("/realtime/sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class r6 extends tY{create(e,t){return this._client.post("/realtime/transcription_sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class r8 extends tY{constructor(){super(...arguments),this.sessions=new r2(this._client),this.transcriptionSessions=new r6(this._client)}}r8.Sessions=r2,r8.TranscriptionSessions=r6;var r5=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)},r4=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r};class r3 extends rN{constructor(){super(...arguments),eI.add(this),eR.set(this,[]),eP.set(this,{}),e$.set(this,{}),eO.set(this,void 0),eC.set(this,void 0),ek.set(this,void 0),eT.set(this,void 0),eB.set(this,void 0),eM.set(this,void 0),eN.set(this,void 0),ej.set(this,void 0),eL.set(this,void 0)}[(eR=new WeakMap,eP=new WeakMap,e$=new WeakMap,eO=new WeakMap,eC=new WeakMap,ek=new WeakMap,eT=new WeakMap,eB=new WeakMap,eM=new WeakMap,eN=new WeakMap,ej=new WeakMap,eL=new WeakMap,eI=new WeakSet,Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("event",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}static fromReadableStream(e){let t=new r3;return t._run(()=>t._fromReadableStream(e)),t}async _fromReadableStream(e,t){let r=t?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),this._connected();let s=e3.fromReadableStream(e,this.controller);for await(let e of s)r5(this,eI,"m",eU).call(this,e);if(s.controller.signal?.aborted)throw new k;return this._addRun(r5(this,eI,"m",eD).call(this))}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}static createToolAssistantStream(e,t,r,s,n){let i=new r3;return i._run(()=>i._runToolAssistantStream(e,t,r,s,{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),i}async _createToolAssistantStream(e,t,r,s,n){let i=n?.signal;i&&(i.aborted&&this.controller.abort(),i.addEventListener("abort",()=>this.controller.abort()));let a={...s,stream:!0},o=await e.submitToolOutputs(t,r,a,{...n,signal:this.controller.signal});for await(let e of(this._connected(),o))r5(this,eI,"m",eU).call(this,e);if(o.controller.signal?.aborted)throw new k;return this._addRun(r5(this,eI,"m",eD).call(this))}static createThreadAssistantStream(e,t,r){let s=new r3;return s._run(()=>s._threadAssistantStream(e,t,{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}static createAssistantStream(e,t,r,s){let n=new r3;return n._run(()=>n._runAssistantStream(e,t,r,{...s,headers:{...s?.headers,"X-Stainless-Helper-Method":"stream"}})),n}currentEvent(){return r5(this,eN,"f")}currentRun(){return r5(this,ej,"f")}currentMessageSnapshot(){return r5(this,eO,"f")}currentRunStepSnapshot(){return r5(this,eL,"f")}async finalRunSteps(){return await this.done(),Object.values(r5(this,eP,"f"))}async finalMessages(){return await this.done(),Object.values(r5(this,e$,"f"))}async finalRun(){if(await this.done(),!r5(this,eC,"f"))throw Error("Final run was not received.");return r5(this,eC,"f")}async _createThreadAssistantStream(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort()));let n={...t,stream:!0},i=await e.createAndRun(n,{...r,signal:this.controller.signal});for await(let e of(this._connected(),i))r5(this,eI,"m",eU).call(this,e);if(i.controller.signal?.aborted)throw new k;return this._addRun(r5(this,eI,"m",eD).call(this))}async _createAssistantStream(e,t,r,s){let n=s?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort()));let i={...r,stream:!0},a=await e.create(t,i,{...s,signal:this.controller.signal});for await(let e of(this._connected(),a))r5(this,eI,"m",eU).call(this,e);if(a.controller.signal?.aborted)throw new k;return this._addRun(r5(this,eI,"m",eD).call(this))}static accumulateDelta(e,t){for(let[r,s]of Object.entries(t)){if(!e.hasOwnProperty(r)){e[r]=s;continue}let t=e[r];if(null==t||"index"===r||"type"===r){e[r]=s;continue}if("string"==typeof t&&"string"==typeof s)t+=s;else if("number"==typeof t&&"number"==typeof s)t+=s;else if(tz(t)&&tz(s))t=this.accumulateDelta(t,s);else if(Array.isArray(t)&&Array.isArray(s)){if(t.every(e=>"string"==typeof e||"number"==typeof e)){t.push(...s);continue}for(let e of s){if(!tz(e))throw Error(`Expected array delta entry to be an object but got: ${e}`);let r=e.index;if(null==r)throw console.error(e),Error("Expected array delta entry to have an `index` property");if("number"!=typeof r)throw Error(`Expected array delta entry \`index\` property to be a number but got ${r}`);let s=t[r];null==s?t.push(e):t[r]=this.accumulateDelta(s,e)}continue}else throw Error(`Unhandled record type: ${r}, deltaValue: ${s}, accValue: ${t}`);e[r]=t}return e}_addRun(e){return e}async _threadAssistantStream(e,t,r){return await this._createThreadAssistantStream(t,e,r)}async _runAssistantStream(e,t,r,s){return await this._createAssistantStream(t,e,r,s)}async _runToolAssistantStream(e,t,r,s,n){return await this._createToolAssistantStream(r,e,t,s,n)}}eU=function(e){if(!this.ended)switch(r4(this,eN,e,"f"),r5(this,eI,"m",eq).call(this,e),e.event){case"thread.created":break;case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":case"thread.run.requires_action":case"thread.run.completed":case"thread.run.incomplete":case"thread.run.failed":case"thread.run.cancelling":case"thread.run.cancelled":case"thread.run.expired":r5(this,eI,"m",eV).call(this,e);break;case"thread.run.step.created":case"thread.run.step.in_progress":case"thread.run.step.delta":case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":r5(this,eI,"m",eW).call(this,e);break;case"thread.message.created":case"thread.message.in_progress":case"thread.message.delta":case"thread.message.completed":case"thread.message.incomplete":r5(this,eI,"m",eF).call(this,e);break;case"error":throw Error("Encountered an error event in event processing - errors should be processed earlier")}},eD=function(){if(this.ended)throw new O("stream has ended, this shouldn't happen");if(!r5(this,eC,"f"))throw Error("Final run has not been received");return r5(this,eC,"f")},eF=function(e){let[t,r]=r5(this,eI,"m",eJ).call(this,e,r5(this,eO,"f"));for(let e of(r4(this,eO,t,"f"),r5(this,e$,"f")[t.id]=t,r)){let r=t.content[e.index];r?.type=="text"&&this._emit("textCreated",r.text)}switch(e.event){case"thread.message.created":this._emit("messageCreated",e.data);break;case"thread.message.in_progress":break;case"thread.message.delta":if(this._emit("messageDelta",e.data.delta,t),e.data.delta.content)for(let r of e.data.delta.content){if("text"==r.type&&r.text){let e=r.text,s=t.content[r.index];if(s&&"text"==s.type)this._emit("textDelta",e,s.text);else throw Error("The snapshot associated with this text delta is not text or missing")}if(r.index!=r5(this,ek,"f")){if(r5(this,eT,"f"))switch(r5(this,eT,"f").type){case"text":this._emit("textDone",r5(this,eT,"f").text,r5(this,eO,"f"));break;case"image_file":this._emit("imageFileDone",r5(this,eT,"f").image_file,r5(this,eO,"f"))}r4(this,ek,r.index,"f")}r4(this,eT,t.content[r.index],"f")}break;case"thread.message.completed":case"thread.message.incomplete":if(void 0!==r5(this,ek,"f")){let t=e.data.content[r5(this,ek,"f")];if(t)switch(t.type){case"image_file":this._emit("imageFileDone",t.image_file,r5(this,eO,"f"));break;case"text":this._emit("textDone",t.text,r5(this,eO,"f"))}}r5(this,eO,"f")&&this._emit("messageDone",e.data),r4(this,eO,void 0,"f")}},eW=function(e){let t=r5(this,eI,"m",eX).call(this,e);switch(r4(this,eL,t,"f"),e.event){case"thread.run.step.created":this._emit("runStepCreated",e.data);break;case"thread.run.step.delta":let r=e.data.delta;if(r.step_details&&"tool_calls"==r.step_details.type&&r.step_details.tool_calls&&"tool_calls"==t.step_details.type)for(let e of r.step_details.tool_calls)e.index==r5(this,eB,"f")?this._emit("toolCallDelta",e,t.step_details.tool_calls[e.index]):(r5(this,eM,"f")&&this._emit("toolCallDone",r5(this,eM,"f")),r4(this,eB,e.index,"f"),r4(this,eM,t.step_details.tool_calls[e.index],"f"),r5(this,eM,"f")&&this._emit("toolCallCreated",r5(this,eM,"f")));this._emit("runStepDelta",e.data.delta,t);break;case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":r4(this,eL,void 0,"f"),"tool_calls"==e.data.step_details.type&&r5(this,eM,"f")&&(this._emit("toolCallDone",r5(this,eM,"f")),r4(this,eM,void 0,"f")),this._emit("runStepDone",e.data,t)}},eq=function(e){r5(this,eR,"f").push(e),this._emit("event",e)},eX=function(e){switch(e.event){case"thread.run.step.created":return r5(this,eP,"f")[e.data.id]=e.data,e.data;case"thread.run.step.delta":let t=r5(this,eP,"f")[e.data.id];if(!t)throw Error("Received a RunStepDelta before creation of a snapshot");let r=e.data;if(r.delta){let s=r3.accumulateDelta(t,r.delta);r5(this,eP,"f")[e.data.id]=s}return r5(this,eP,"f")[e.data.id];case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":case"thread.run.step.in_progress":r5(this,eP,"f")[e.data.id]=e.data}if(r5(this,eP,"f")[e.data.id])return r5(this,eP,"f")[e.data.id];throw Error("No snapshot available")},eJ=function(e,t){let r=[];switch(e.event){case"thread.message.created":return[e.data,r];case"thread.message.delta":if(!t)throw Error("Received a delta with no existing snapshot (there should be one from message creation)");let s=e.data;if(s.delta.content)for(let e of s.delta.content)if(e.index in t.content){let r=t.content[e.index];t.content[e.index]=r5(this,eI,"m",eH).call(this,e,r)}else t.content[e.index]=e,r.push(e);return[t,r];case"thread.message.in_progress":case"thread.message.completed":case"thread.message.incomplete":if(t)return[t,r];throw Error("Received thread message event with no existing snapshot")}throw Error("Tried to accumulate a non-message event")},eH=function(e,t){return r3.accumulateDelta(t,e)},eV=function(e){switch(r4(this,ej,e.data,"f"),e.event){case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":break;case"thread.run.requires_action":case"thread.run.cancelled":case"thread.run.failed":case"thread.run.completed":case"thread.run.expired":r4(this,eC,e.data,"f"),r5(this,eM,"f")&&(this._emit("toolCallDone",r5(this,eM,"f")),r4(this,eM,void 0,"f"))}};class r9 extends tY{create(e,t,r){return this._client.post(`/threads/${e}/messages`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}retrieve(e,t,r){return this._client.get(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/messages/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tR(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/messages`,r7,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t,r){return this._client.delete(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class r7 extends t0{}r9.MessagesPage=r7;class se extends tY{retrieve(e,t,r,s={},n){return tR(s)?this.retrieve(e,t,r,{},s):this._client.get(`/threads/${e}/runs/${t}/steps/${r}`,{query:s,...n,headers:{"OpenAI-Beta":"assistants=v2",...n?.headers}})}list(e,t,r={},s){return tR(r)?this.list(e,t,{},r):this._client.getAPIList(`/threads/${e}/runs/${t}/steps`,st,{query:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}}class st extends t0{}se.RunStepsPage=st;class sr extends tY{constructor(){super(...arguments),this.steps=new se(this._client)}create(e,t,r){let{include:s,...n}=t;return this._client.post(`/threads/${e}/runs`,{query:{include:s},body:n,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers},stream:t.stream??!1})}retrieve(e,t,r){return this._client.get(`/threads/${e}/runs/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tR(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/runs`,ss,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}cancel(e,t,r){return this._client.post(`/threads/${e}/runs/${t}/cancel`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}createAndStream(e,t,r){return r3.createAssistantStream(e,this._client.beta.threads.runs,t,r)}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:{...r?.headers,...s}}).withResponse();switch(n.status){case"queued":case"in_progress":case"cancelling":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tM(a);break;case"requires_action":case"incomplete":case"cancelled":case"completed":case"failed":case"expired":return n}}}stream(e,t,r){return r3.createAssistantStream(e,this._client.beta.threads.runs,t,r)}submitToolOutputs(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}/submit_tool_outputs`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers},stream:r.stream??!1})}async submitToolOutputsAndPoll(e,t,r,s){let n=await 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