fix(anthropic): sanitize tool_use IDs in convert_to_anthropic_tool_invoke#21964
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… deployment tagging (BerriAI#21655) POST /access_group/new and PUT /access_group/{name}/update now accept an optional model_ids list that targets specific deployments by their unique model_id, instead of tagging every deployment that shares a model_name. When model_ids is provided it takes priority over model_names, giving API callers the same single-deployment precision that the UI already has via PATCH /model/{model_id}/update. Backward compatible: model_names continues to work as before. Closes BerriAI#21544
… custom favicon for the litellm proxy UI.\n\n- Add favicon_url field to UIThemeConfig model\n- Add LITELLM_FAVICON_URL env var support\n- Add /get_favicon endpoint to serve custom favicons\n- Update ThemeContext to dynamically set favicon\n- Add favicon URL input to UI theme settings page\n- Add comprehensive tests\n\nCloses BerriAI#8323 (BerriAI#21653)
In create_file for Bedrock, get_complete_file_url is called twice: once in the sync handler (generating UUID-1 for api_base) and once inside transform_create_file_request (generating UUID-2 for the actual S3 upload). The Bedrock provider correctly writes UUID-2 into litellm_params["upload_url"], but the sync handler unconditionally overwrites it with api_base (UUID-1). This causes the returned file_id to point to a non-existent S3 key. Fix: only set upload_url to api_base when transform_create_file_request has not already set it, preserving the Bedrock provider's value. Closes BerriAI#21546
…nt (BerriAI#21649) Add vector_size parameter to QdrantSemanticCache and expose it through the Cache facade as qdrant_semantic_cache_vector_size. This allows users to use embedding models with dimensions other than the default 1536, enabling cheaper/stronger models like Stella (1024d), bge-en-icl (4096d), voyage, cohere, etc. The parameter defaults to QDRANT_VECTOR_SIZE (env var or 1536) for backward compatibility. When creating new collections, the configured vector_size is used instead of the hardcoded constant. Closes BerriAI#9377
…rriAI#21762) Clients like OpenCode's @ai-sdk/openai-compatible send budgetTokens (camelCase) instead of budget_tokens in the thinking parameter, causing validation errors. Add early normalization in completion().
Adds per-alert-type digest mode that aggregates duplicate alerts
within a configurable time window and emits a single summary message
with count, start/end timestamps.
Configuration via general_settings.alert_type_config:
alert_type_config:
llm_requests_hanging:
digest: true
digest_interval: 86400
Digest key: (alert_type, request_model, api_base)
Default interval: 24 hours
Window type: fixed interval
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds GetBlogPosts class that fetches blog posts from GitHub with a 1-hour in-process TTL cache, validates the response, and falls back to the bundled blog_posts_backup.json on any network or validation failure.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…ache duplication Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…out real API calls
Intercepts at httpx transport layer so the full proxy path (auth, routing,
OpenAI SDK, response transformation) is exercised with zero-latency responses.
Activated via `litellm_settings: { network_mock: true }` in proxy config.
…plete-status fix(tests): add INCOMPLETE to interactions status enum expected values
Concurrent requests via run_in_executor + asyncio.gather caused a race condition where more requests slipped through the rate limiter than expected, leading to flaky test failures (e.g. 3 successes instead of 2 with rpm_limit=2). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…erriAI#21948) * feat: Singapore PDPA PII protection guardrail policy template Add Singapore Personal Data Protection Act (PDPA) guardrail support: Regex patterns (patterns.json): - sg_nric: NRIC/FIN detection ([STFGM] + 7 digits + checksum letter) - sg_phone: Singapore phone numbers (+65/0065/65 prefix) - sg_postal_code: 6-digit postal codes (contextual) - passport_singapore: Passport numbers (E/K + 7 digits, contextual) - sg_uen: Unique Entity Numbers (3 formats) - sg_bank_account: Bank account numbers (dash format, contextual) YAML policy templates (5 sub-guardrails): - sg_pdpa_personal_identifiers: s.13 Consent - sg_pdpa_sensitive_data: Advisory Guidelines - sg_pdpa_do_not_call: Part IX DNC Registry - sg_pdpa_data_transfer: s.26 overseas transfers - sg_pdpa_profiling_automated_decisions: Model AI Governance Framework Policy template entry in policy_templates.json with 9 guardrail definitions (4 regex-based + 5 YAML conditional keyword matching). Tests: - test_sg_patterns.py: regex pattern unit tests - test_sg_pdpa_guardrails.py: conditional keyword matching tests (100+ cases) * feat: MAS AI Risk Management Guidelines guardrail policy template Add Monetary Authority of Singapore (MAS) AI Risk Management Guidelines guardrail support for financial institutions: YAML policy templates (5 sub-guardrails): - sg_mas_fairness_bias: Blocks discriminatory financial AI (credit/loans/insurance by protected attributes) - sg_mas_transparency_explainability: Blocks opaque/unexplainable AI for consequential financial decisions - sg_mas_human_oversight: Blocks fully automated financial decisions without human-in-the-loop - sg_mas_data_governance: Blocks unauthorized sharing/mishandling of financial customer data - sg_mas_model_security: Blocks adversarial attacks, model poisoning, inversion on financial AI Policy template entry in policy_templates.json with 5 guardrail definitions. Aligned with MAS FEAT Principles, Project MindForge, and NIST AI RMF. Tests: - test_sg_mas_ai_guardrails.py: conditional keyword matching tests (100+ cases) * fix: address SG pattern review feedback - Update NRIC lowercase test for IGNORECASE runtime behavior - Add keyword context guard to sg_uen pattern to reduce false positives * docs: clarify MAS AIRM timeline references - Explicitly mark MAS AIRM as Nov 2025 consultation draft - Add 2018 qualifier for FEAT principles in MAS policy descriptions - Update MAS guardrail wording to avoid release-year ambiguity * chore: commit resolved MAS policy conflicts * test: * chore:
) * Add OpenAI Agents SDK tutorial to docs * Update OpenAI Agents SDK tutorial to use LiteLLM environment variables * Enhance OpenAI Agents SDK tutorial with built-in LiteLLM extension details and updated configuration steps. Adjust section headings for clarity and improve the flow of information regarding model setup and usage.
fix(tests): make RPM limit test sequential to fix race condition
…section docs: add performance & reliability section to v1.81.14 release notes
…I#21955) openai videos models support the features to download variants. See more details here: https://developers.openai.com/api/docs/guides/video-generation#use-image-references. Plumb variant (e.g. "thumbnail", "spritesheet") through the full video content download chain: avideo_content → video_content → video_content_handler → transform_video_content_request. OpenAI appends ?variant=<value> to the GET URL; other providers accept the parameter in their signature but ignore it.
…te PR workflow Remove the Claude Code-powered duplicate PR detection workflow and revert the duplicate issue checker back to wow-actions/potential-duplicates with text similarity matching.
…e_workflows Revert duplicate issue checker to text-based matching
[Feature] UI - Blog Dropdown in Navbar
Apply _sanitize_anthropic_tool_use_id to tool_use blocks in convert_to_anthropic_tool_invoke, not just tool_result blocks. IDs from external frameworks (e.g. MiniMax) may contain characters like colons that violate Anthropic's ^[a-zA-Z0-9_-]+$ pattern. Adds test for invalid ID sanitization in tool_use blocks.
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Pull request overview
This PR fixes a bug where tool call IDs from non-Anthropic providers (e.g., MiniMax, Composio) containing invalid characters like colons or dots cause invalid_request_error when routing multi-provider conversations to Anthropic. Anthropic requires tool_use IDs to match the pattern ^[a-zA-Z0-9_-]+$.
Changes:
- Applied existing
_sanitize_anthropic_tool_use_id()sanitization to tool_use blocks inconvert_to_anthropic_tool_invoke() - Added comprehensive test coverage for ID sanitization with various invalid characters
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| litellm/litellm_core_utils/prompt_templates/factory.py | Applied ID sanitization to regular tool_use blocks, ensuring consistency with tool_result handling |
| tests/llm_translation/test_prompt_factory.py | Added test validating sanitization of invalid characters (colons, dots) in tool IDs and that valid IDs pass through unchanged |
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Greptile SummaryThis PR fixes an
Confidence Score: 5/5
|
| Filename | Overview |
|---|---|
| litellm/litellm_core_utils/prompt_templates/factory.py | Applies existing _sanitize_anthropic_tool_use_id() to regular tool_use blocks in convert_to_anthropic_tool_invoke, matching the pattern already used for tool_result blocks. Minimal 2-line change, no new logic introduced. |
| tests/llm_translation/test_prompt_factory.py | Adds test covering sanitization of invalid tool_use IDs (colons, dots) and verifying valid IDs pass through unchanged. Test is well-structured and covers the key scenarios. |
Sequence Diagram
sequenceDiagram
participant External as Non-Anthropic Provider
participant LiteLLM as LiteLLM Router
participant Sanitizer as _sanitize_anthropic_tool_use_id
participant Anthropic as Anthropic API
External->>LiteLLM: tool_call with id "sessions_history:183"
LiteLLM->>LiteLLM: convert_to_anthropic_tool_invoke()
LiteLLM->>Sanitizer: sanitize tool_use id
Sanitizer-->>LiteLLM: "sessions_history_183"
LiteLLM->>Anthropic: tool_use block with sanitized id
Anthropic-->>LiteLLM: Response
LiteLLM->>LiteLLM: convert_to_anthropic_tool_result()
LiteLLM->>Sanitizer: sanitize tool_result id (already existed)
Sanitizer-->>LiteLLM: "sessions_history_183" (consistent)
LiteLLM->>Anthropic: tool_result with matching id
Last reviewed commit: 02d71bc
dd5b856
into
BerriAI:litellm_oss_staging_02_23_2026
…voke (BerriAI#21964) * auth_with_role_name add region_name arg for cross-account sts * update tests to include case with aws_region_name for _auth_with_aws_role * Only pass region_name to STS client when aws_region_name is set * Add optional aws_sts_endpoint to _auth_with_aws_role * Parametrize ambient-credentials test for no opts, region_name, and aws_sts_endpoint * consistently passing region and endpoint args into explicit credentials irsa * fix env var leakage * fix: bedrock openai-compatible imported-model should also have model arn encoded * feat: show proxy url in ModelHub (BerriAI#21660) * fix(bedrock): correct modelInput format for Converse API batch models (BerriAI#21656) * fix(proxy): add model_ids param to access group endpoints for precise deployment tagging (BerriAI#21655) POST /access_group/new and PUT /access_group/{name}/update now accept an optional model_ids list that targets specific deployments by their unique model_id, instead of tagging every deployment that shares a model_name. When model_ids is provided it takes priority over model_names, giving API callers the same single-deployment precision that the UI already has via PATCH /model/{model_id}/update. Backward compatible: model_names continues to work as before. Closes BerriAI#21544 * feat(proxy): add custom favicon support\n\nAdd ability to configure a custom favicon for the litellm proxy UI.\n\n- Add favicon_url field to UIThemeConfig model\n- Add LITELLM_FAVICON_URL env var support\n- Add /get_favicon endpoint to serve custom favicons\n- Update ThemeContext to dynamically set favicon\n- Add favicon URL input to UI theme settings page\n- Add comprehensive tests\n\nCloses BerriAI#8323 (BerriAI#21653) * fix(bedrock): prevent double UUID in create_file S3 key (BerriAI#21650) In create_file for Bedrock, get_complete_file_url is called twice: once in the sync handler (generating UUID-1 for api_base) and once inside transform_create_file_request (generating UUID-2 for the actual S3 upload). The Bedrock provider correctly writes UUID-2 into litellm_params["upload_url"], but the sync handler unconditionally overwrites it with api_base (UUID-1). This causes the returned file_id to point to a non-existent S3 key. Fix: only set upload_url to api_base when transform_create_file_request has not already set it, preserving the Bedrock provider's value. Closes BerriAI#21546 * feat(semantic-cache): support configurable vector dimensions for Qdrant (BerriAI#21649) Add vector_size parameter to QdrantSemanticCache and expose it through the Cache facade as qdrant_semantic_cache_vector_size. This allows users to use embedding models with dimensions other than the default 1536, enabling cheaper/stronger models like Stella (1024d), bge-en-icl (4096d), voyage, cohere, etc. The parameter defaults to QDRANT_VECTOR_SIZE (env var or 1536) for backward compatibility. When creating new collections, the configured vector_size is used instead of the hardcoded constant. Closes BerriAI#9377 * fix(utils): normalize camelCase thinking param keys to snake_case (BerriAI#21762) Clients like OpenCode's @ai-sdk/openai-compatible send budgetTokens (camelCase) instead of budget_tokens in the thinking parameter, causing validation errors. Add early normalization in completion(). * feat: add optional digest mode for Slack alert types (BerriAI#21683) Adds per-alert-type digest mode that aggregates duplicate alerts within a configurable time window and emits a single summary message with count, start/end timestamps. Configuration via general_settings.alert_type_config: alert_type_config: llm_requests_hanging: digest: true digest_interval: 86400 Digest key: (alert_type, request_model, api_base) Default interval: 24 hours Window type: fixed interval Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add blog_posts.json and local backup * feat: add GetBlogPosts utility with GitHub fetch and local fallback Adds GetBlogPosts class that fetches blog posts from GitHub with a 1-hour in-process TTL cache, validates the response, and falls back to the bundled blog_posts_backup.json on any network or validation failure. * test: add cache reset fixture and LITELLM_LOCAL_BLOG_POSTS test Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat: add GET /public/litellm_blog_posts endpoint Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: log fallback warning in blog posts endpoint and tighten test * feat: add disable_show_blog to UISettings Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat: add useUISettings and useDisableShowBlog hooks * fix: rename useUISettings to useUISettingsFlags to avoid naming collision * fix: use existing useUISettings hook in useDisableShowBlog to avoid cache duplication Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat: add BlogDropdown component with react-query and error/retry state Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: enforce 5-post limit in BlogDropdown and add cap test * fix: add retry, stable post key, enabled guard in BlogDropdown Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat: add BlogDropdown to navbar after Docs link * feat: add network_mock transport for benchmarking proxy overhead without real API calls Intercepts at httpx transport layer so the full proxy path (auth, routing, OpenAI SDK, response transformation) is exercised with zero-latency responses. Activated via `litellm_settings: { network_mock: true }` in proxy config. * Litellm dev 02 19 2026 p2 (BerriAI#21871) * feat(ui/): new guardrails monitor 'demo mock representation of what guardrails monitor looks like * fix: ui updates * style(ui/): fix styling * feat: enable running ai monitor on individual guardrails * feat: add backend logic for guardrail monitoring * fix(guardrails/usage_endpoints.py): fix usage dashboard * fix(budget): fix timezone config lookup and replace hardcoded timezone map with ZoneInfo (BerriAI#21754) * fix(budget): fix timezone config lookup and replace hardcoded timezone map with ZoneInfo * fix(budget): update stale docstring on get_budget_reset_time * fix: add missing return type annotations to iterator protocol methods in streaming_handler (BerriAI#21750) * fix: add return type annotations to iterator protocol methods in streaming_handler Add missing return type annotations to __iter__, __aiter__, __next__, and __anext__ methods in CustomStreamWrapper and related classes. - __iter__(self) -> Iterator["ModelResponseStream"] - __aiter__(self) -> AsyncIterator["ModelResponseStream"] - __next__(self) -> "ModelResponseStream" - __anext__(self) -> "ModelResponseStream" Also adds AsyncIterator and Iterator to typing imports. Fixes issue with PLR0915 noqa comments and ensures proper type checking support. Related to: BerriAI#8304 * fix: add ruff PLR0915 noqa for files with too many statements * Add gollem Go agent framework cookbook example (BerriAI#21747) Show how to use gollem, a production Go agent framework, with LiteLLM proxy for multi-provider LLM access including tool use and streaming. * fix: avoid mutating caller-owned dicts in SpendUpdateQueue aggregation (BerriAI#21742) * fix(vertex_ai): enable context-1m-2025-08-07 beta header (BerriAI#21870) * server root path regression doc * fixing syntax * fix: replace Zapier webhook with Google Form for survey submission (BerriAI#21621) * Replace Zapier webhook with Google Form for survey submission * Add back error logging for survey submission debugging --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> * Revert "Merge pull request BerriAI#21140 from BerriAI/litellm_perf_user_api_key_auth" This reverts commit 0e1db3f, reversing changes made to 7e2d6f2. * test_vertex_ai_gemini_2_5_pro_streaming * UI new build * fix rendering * ui new build * docs fix * docs fix * docs fix * docs fix * docs fix * docs fix * docs fix * docs fix * release note docs * docs * adding image * fix(vertex_ai): enable context-1m-2025-08-07 beta header The `context-1m-2025-08-07` Anthropic beta header was set to `null` for vertex_ai, causing it to be filtered out when users set `extra_headers: {anthropic-beta: context-1m-2025-08-07}`. This prevented using Claude's 1M context window feature via Vertex AI, resulting in `prompt is too long: 460500 tokens > 200000 maximum` errors. Fixes BerriAI#21861 --------- Co-authored-by: yuneng-jiang <yuneng.jiang@gmail.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> * Revert "fix(vertex_ai): enable context-1m-2025-08-07 beta header (BerriAI#21870)" (BerriAI#21876) This reverts commit bce078a. * docs(ui): add pre-PR checklist to UI contributing guide Add testing and build verification steps per maintainer feedback from @yjiang-litellm. Contributors should run their related tests per-file and ensure npm run build passes before opening PRs. * Fix entries with fast and us/ * Add tests for fast and us * Add support for Priority PayGo for vertex ai and gemini * Add model pricing * fix: ensure arrival_time is set before calculating queue time * Fix: Anthropic model wildcard access issue * Add incident report * Add ability to see which model cost map is getting used * Fix name of title * Readd tpm limit * State management fixes for CheckBatchCost * Fix PR review comments * State management fixes for CheckBatchCost - Address greptile comments * fix mypy issues: * Add Noma guardrails v2 based on custom guardrails (BerriAI#21400) * Fix code qa issues * Fix mypy issues * Fix mypy issues * Fix test_aaamodel_prices_and_context_window_json_is_valid * fix: update calendly on repo * fix(tests): use counter-based mock for time.time in prisma self-heal test The test used a fixed side_effect list for time.time(), but the number of calls varies by Python version, causing StopIteration on 3.12 and AssertionError on 3.14. Replace with an infinite counter-based callable and assert the timestamp was updated rather than checking for an exact value. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(tests): use absolute path for model_prices JSON in validation test The test used a relative path 'litellm/model_prices_and_context_window.json' which only works when pytest runs from a specific working directory. Use os.path based on __file__ to resolve the path reliably. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Update tests/test_litellm/test_utils.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * fix(tests): use os.path instead of Path to avoid NameError Path is not imported at module level. Use os.path.join which is already available. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * clean up mock transport: remove streaming, add defensive parsing * docs: add Google GenAI SDK tutorial (JS & Python) (BerriAI#21885) * docs: add Google GenAI SDK tutorial for JS and Python Add tutorial for using Google's official GenAI SDK (@google/genai for JS, google-genai for Python) with LiteLLM proxy. Covers pass-through and native router endpoints, streaming, multi-turn chat, and multi-provider routing via model_group_alias. Also updates pass-through docs to use the new SDK replacing the deprecated @google/generative-ai. * fix(docs): correct Python SDK env var name in GenAI tutorial GOOGLE_GENAI_API_KEY does not exist in the google-genai SDK. The correct env var is GEMINI_API_KEY (or GOOGLE_API_KEY). Also note that the Python SDK has no base URL env var. * fix(docs): replace non-existent GOOGLE_GENAI_BASE_URL env var in interactions.md The Python google-genai SDK does not read GOOGLE_GENAI_BASE_URL. Use http_options={"base_url": "..."} in code instead. * docs: add network mock benchmarking section * docs: tweak benchmarks wording * fix: add auth headers and empty latencies guard to benchmark script * refactor: use method-level import for MockOpenAITransport * fix: guard print_aggregate against empty latencies * fix: add INCOMPLETE status to Interactions API enum and test Google added INCOMPLETE to the Interactions API OpenAPI spec status enum. Update both the Status3 enum in the SDK types and the test's expected values to match. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Guardrail Monitor - measure guardrail reliability in prod (BerriAI#21944) * fix: fix log viewer for guardrail monitoring * feat(ui/): fix rendering logs per guardrail * fix: fix viewing logs on overview tab of guardrail * fix: log viewer * fix: fix naming to align with metric * docs: add performance & reliability section to v1.81.14 release notes * fix(tests): make RPM limit test sequential to avoid race condition Concurrent requests via run_in_executor + asyncio.gather caused a race condition where more requests slipped through the rate limiter than expected, leading to flaky test failures (e.g. 3 successes instead of 2 with rpm_limit=2). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: Singapore guardrail policies (PDPA + MAS AI Risk Management) (BerriAI#21948) * feat: Singapore PDPA PII protection guardrail policy template Add Singapore Personal Data Protection Act (PDPA) guardrail support: Regex patterns (patterns.json): - sg_nric: NRIC/FIN detection ([STFGM] + 7 digits + checksum letter) - sg_phone: Singapore phone numbers (+65/0065/65 prefix) - sg_postal_code: 6-digit postal codes (contextual) - passport_singapore: Passport numbers (E/K + 7 digits, contextual) - sg_uen: Unique Entity Numbers (3 formats) - sg_bank_account: Bank account numbers (dash format, contextual) YAML policy templates (5 sub-guardrails): - sg_pdpa_personal_identifiers: s.13 Consent - sg_pdpa_sensitive_data: Advisory Guidelines - sg_pdpa_do_not_call: Part IX DNC Registry - sg_pdpa_data_transfer: s.26 overseas transfers - sg_pdpa_profiling_automated_decisions: Model AI Governance Framework Policy template entry in policy_templates.json with 9 guardrail definitions (4 regex-based + 5 YAML conditional keyword matching). Tests: - test_sg_patterns.py: regex pattern unit tests - test_sg_pdpa_guardrails.py: conditional keyword matching tests (100+ cases) * feat: MAS AI Risk Management Guidelines guardrail policy template Add Monetary Authority of Singapore (MAS) AI Risk Management Guidelines guardrail support for financial institutions: YAML policy templates (5 sub-guardrails): - sg_mas_fairness_bias: Blocks discriminatory financial AI (credit/loans/insurance by protected attributes) - sg_mas_transparency_explainability: Blocks opaque/unexplainable AI for consequential financial decisions - sg_mas_human_oversight: Blocks fully automated financial decisions without human-in-the-loop - sg_mas_data_governance: Blocks unauthorized sharing/mishandling of financial customer data - sg_mas_model_security: Blocks adversarial attacks, model poisoning, inversion on financial AI Policy template entry in policy_templates.json with 5 guardrail definitions. Aligned with MAS FEAT Principles, Project MindForge, and NIST AI RMF. Tests: - test_sg_mas_ai_guardrails.py: conditional keyword matching tests (100+ cases) * fix: address SG pattern review feedback - Update NRIC lowercase test for IGNORECASE runtime behavior - Add keyword context guard to sg_uen pattern to reduce false positives * docs: clarify MAS AIRM timeline references - Explicitly mark MAS AIRM as Nov 2025 consultation draft - Add 2018 qualifier for FEAT principles in MAS policy descriptions - Update MAS guardrail wording to avoid release-year ambiguity * chore: commit resolved MAS policy conflicts * test: * chore: * Add OpenAI Agents SDK tutorial with LiteLLM Proxy to docs (BerriAI#21221) * Add OpenAI Agents SDK tutorial to docs * Update OpenAI Agents SDK tutorial to use LiteLLM environment variables * Enhance OpenAI Agents SDK tutorial with built-in LiteLLM extension details and updated configuration steps. Adjust section headings for clarity and improve the flow of information regarding model setup and usage. * adjust blog posts to fetch from github first * feat(videos): add variant parameter to video content download (BerriAI#21955) openai videos models support the features to download variants. See more details here: https://developers.openai.com/api/docs/guides/video-generation#use-image-references. Plumb variant (e.g. "thumbnail", "spritesheet") through the full video content download chain: avideo_content → video_content → video_content_handler → transform_video_content_request. OpenAI appends ?variant=<value> to the GET URL; other providers accept the parameter in their signature but ignore it. * fixing path * adjust blog post path * Revert duplicate issue checker to text-based matching, remove duplicate PR workflow Remove the Claude Code-powered duplicate PR detection workflow and revert the duplicate issue checker back to wow-actions/potential-duplicates with text similarity matching. * ui changes * adding tests * fix(anthropic): sanitize tool_use IDs in assistant messages Apply _sanitize_anthropic_tool_use_id to tool_use blocks in convert_to_anthropic_tool_invoke, not just tool_result blocks. IDs from external frameworks (e.g. MiniMax) may contain characters like colons that violate Anthropic's ^[a-zA-Z0-9_-]+$ pattern. Adds test for invalid ID sanitization in tool_use blocks. --------- Co-authored-by: An Tang <ta@stripe.com> Co-authored-by: janfrederickk <75388864+janfrederickk@users.noreply.github.com> Co-authored-by: Zhenting Huang <3061613175@qq.com> Co-authored-by: Cesar Garcia <128240629+Chesars@users.noreply.github.com> Co-authored-by: Darien Kindlund <darien@kindlund.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: yuneng-jiang <yuneng.jiang@gmail.com> Co-authored-by: Ryan Crabbe <rcrabbe@berkeley.edu> Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com> Co-authored-by: LeeJuOh <56071126+LeeJuOh@users.noreply.github.com> Co-authored-by: Monesh Ram <31161039+WhoisMonesh@users.noreply.github.com> Co-authored-by: Trevor Prater <trevor.prater@gmail.com> Co-authored-by: The Mavik <179817126+themavik@users.noreply.github.com> Co-authored-by: Edwin Isac <33712823+edwiniac@users.noreply.github.com> Co-authored-by: milan-berri <milan@berri.ai> Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Chesars <cesarponce19544@gmail.com> Co-authored-by: Sameer Kankute <sameer@berri.ai> Co-authored-by: Harshit Jain <harshitjain0562@gmail.com> Co-authored-by: Harshit Jain <48647625+Harshit28j@users.noreply.github.com> Co-authored-by: Ephrim Stanley <ephrim.stanley@point72.com> Co-authored-by: TomAlon <tom@noma.security> Co-authored-by: Julio Quinteros Pro <jquinter@gmail.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: ryan-crabbe <128659760+ryan-crabbe@users.noreply.github.com> Co-authored-by: Ron Zhong <ron-zhong@hotmail.com> Co-authored-by: Arindam Majumder <109217591+Arindam200@users.noreply.github.com> Co-authored-by: Lei Nie <lenie@quora.com>
Relevant issues
Encountered
invalid_request_errorfrom Anthropic when routing multi-provider conversations — tool call IDs generated by other providers (MiniMax, Composio, etc.) can contain characters like:or.that break Anthropic's^[a-zA-Z0-9_-]+$validation ontool_use.id.Pre-Submission checklist
tests/llm_translation/test_prompt_factory.pyType
🐛 Bug Fix
Changes
_sanitize_anthropic_tool_use_id()already exists and is correctly applied to tool_result blocks inconvert_to_anthropic_tool_result(lines 1714, 1728). However, it's missing from tool_use blocks inconvert_to_anthropic_tool_invoke— thetool_idis passed raw.This means when a conversation history contains tool calls from a non-Anthropic provider (e.g. MiniMax generating IDs like
sessions_history:183), and the conversation is then sent to an Anthropic model, the request fails with:The fix applies the same
_sanitize_anthropic_tool_use_id()to regular tool_use IDs — 2 lines changed. Both tool_use and tool_result now go through the same sanitizer, so ID matching stays consistent.Added a test covering colons, dots, and valid IDs passing through unchanged.