Add BFL models to model_prices_and_context_window.json with pricing:
- flux-kontext-pro: $0.04/image
- flux-kontext-max: $0.08/image
- flux-pro-1.0-fill: $0.05/image
- flux-pro-1.0-expand: $0.05/image
Add black_forest_labs_models set to __init__.py for model discovery.
* add explicit caching to litellm proxy for gemini models via injection
* fix: add missing `supports_function_calling` for deepinfra models
All 55 deepinfra models that had `supports_tool_choice: true` were
missing the `supports_function_calling` flag, causing
`litellm.supports_function_calling()` to incorrectly return False.
Fixes#22619
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Managed batches - Address PR bot comments from #22464
* feat(togetherai): add support for TogetherAI Qwen3.5-397B-A17B model
* Agent Tracing - support context_id based trace id propogation + nested llm calls (#22626)
* style(ui/): distinguish agent calls from llm calls on ui
* feat: initial grouping working
* feat: set stable contextid for a2a calls - allows for easily passing to downstream llm/mcp calls
* feat(a2a_endpoints.py): fix tracing to avoid recreating logging objects for the same call
allows stable trace id usage
* fix(guardrail_endpoints): handle string ui_type values in _build_field_dict
_build_field_dict unconditionally called .value on ui_type, which crashes
for guardrail configs that use plain strings (e.g. BlockCodeExecutionGuardrailConfigModel
uses "multiselect" and "percentage"). Now checks with hasattr before calling .value.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: propagate trace/session id from headers in MCP server calls
Cherry-picked mcp_server/server.py fixes from 6feb9bab: adds
get_chain_id_from_headers to extract x-litellm-trace-id /
x-litellm-session-id from raw headers, and uses it in call_tool
and list_tools to keep spend logs and tracing consistent with A2A.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* [Feat] UI - Add Open in New Tab on leftnav Bar (#22731)
* Add minimal dev_config.yaml for proxy development
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* feat(ui): wrap left nav items in <a> tags for open-in-new-tab support
Nav items are now rendered as <a> elements with proper href attributes,
enabling right-click → 'Open in new tab', Ctrl/Cmd+click, and
middle-click to open any sidebar page in a new browser tab.
Normal clicks continue to use SPA navigation (no full page reload).
Applied to both leftnav.tsx (query-param routing) and Sidebar2.tsx
(Next.js file-based routing).
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* [Feat] Add Tool Policies for AI Gateway (#22732)
* fix: fix ui render
* fix: fix minor bugs
* refactor: use prisma functions instead of raw sql (safer)
* fix(add-new-tiles-to-tool-policies): allow developer to see what's available
* feat: ensure tool allowlist runs correctly for tool names + mcp's
* refactor: more ui improvements
* feat: working key tool blocking
* feat(tools): show tool logs
* refactor: backend code improvements
* refactor: improve log viewer for tools
* fix: address PR review feedback for tool access control
- Add missing blocked_tools column to root schema.prisma (schema drift)
- Invalidate ToolPolicyRegistry after policy mutations so changes take effect immediately
- Remove dead code: unused get_effective_policies, get_tool_policies_cached, and helpers
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: race condition in permission resolution and remove duplicate allowlist check
- Use atomic update_many with object_permission_id=None to prevent concurrent
requests from creating orphaned permission rows and losing tool blocks
- Remove duplicate allowed_tools enforcement from guardrail (already enforced
in auth layer via check_tools_allowlist)
- Move inline uuid import to module level
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* update to account for userAgent
* UI - Add ToolDetails
* input/output policy
* LiteLLM_PolicyAttachmentTable
* LiteLLM_PolicyAttachmentTable
* fix: add _enqueue_tool_registry_upsert
* fix: tool mgmt endpoints
* tool mgmt endpoints
* Update tests/test_litellm/proxy/db/test_tool_registry_writer.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update tests/test_litellm/proxy/db/test_tool_registry_writer.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update tests/test_litellm/proxy/db/test_tool_registry_writer.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix: sync root schema.prisma and fix test_tool_registry_writer for input/output policy
- Migrate root schema.prisma LiteLLM_ToolTable from call_policy to
input_policy/output_policy, add missing user_agent and last_used_at columns
(now consistent with litellm/proxy/schema.prisma and litellm-proxy-extras)
- Fix SpendLogToolIndex comment across all three schema files
- Fix all call_policy references in test_tool_registry_writer.py:
swapped update_tool_policy arguments, wrong get_tools_by_names return type
assertions, _mock_tool_row setting call_policy instead of input_policy
Addresses Greptile review feedback on PR #22732.
Made-with: Cursor
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* feat(proxy): add key_alias, key_hash, requested_model DD APM span tags (#22710)
* feat(proxy): add key_alias, key_hash, requested_model tags to DD APM spans
* refactor(proxy): consolidate DD APM tag helpers into DDSpanTagger class
* refactor(proxy): move DDSpanTagger to its own file litellm/proxy/dd_span_tagger.py
---------
Co-authored-by: liweiguang <codingpunk@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Ephrim Stanley <ephrim.stanley@point72.com>
Co-authored-by: Varad Khonde <varadkhonde@gmail.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Fixes#22646
Adds pricing for DashScope models that were missing from the cost map,
causing $0 spend tracking in the proxy dashboard:
- dashscope/qwen3-max-2026-01-23 (tiered, same as qwen3-max)
- dashscope/qwen3-next-80b-a3b-instruct ($0.15/$1.20 per 1M)
- dashscope/qwen3-next-80b-a3b-thinking ($0.15/$1.20 per 1M)
- dashscope/qwen3-vl-235b-a22b-instruct ($0.40/$1.60 per 1M)
- dashscope/qwen3-vl-235b-a22b-thinking ($0.40/$4.00 per 1M)
- dashscope/qwen3-vl-32b-instruct ($0.16/$0.64 per 1M)
- dashscope/qwen3-vl-32b-thinking ($0.16/$2.87 per 1M)
Fixes#22609
Adds pricing for OpenRouter models that were routing correctly but
returning $0 for spend tracking due to missing cost map entries:
- openrouter/anthropic/claude-sonnet-4.6 ($3.00/$15.00 per 1M tokens)
- openrouter/google/gemini-3.1-pro-preview ($2.00/$12.00 per 1M tokens)
- openrouter/openai/gpt-5.1-codex-max ($1.25/$10.00 per 1M tokens)
- openrouter/qwen/qwen3-coder-plus ($1.00/$5.00 per 1M tokens)
- openrouter/z-ai/glm-5 ($0.80/$2.56 per 1M tokens)
All 55 deepinfra models that had `supports_tool_choice: true` were
missing the `supports_function_calling` flag, causing
`litellm.supports_function_calling()` to incorrectly return False.
Fixes#22619
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
mistral-small-latest now points to Small 3.2 (since June 2025).
Updated pricing from $0.10/$0.30 to $0.06/$0.18 per 1M tokens,
context from 32k to 131k, and added vision support to match
mistral-small-3-2-2506.
Add 9 new Mistral models (mistral-large-2512, mistral-medium-3-1-2508,
mistral-small-3-2-2506, ministral-3-3b/8b/14b-2512, saba-2502,
magistral-medium/small-1-2-2509) and update mistral-large-latest,
mistral-large-3, and mistral-medium-latest with correct pricing and
context windows.
Fixes#22585
Fixes#22591 - These models were missing from the pricing JSON, causing
$0 cost tracking when routed via the dashscope/* wildcard.
Pricing sourced from official Alibaba Cloud Model Studio docs (international tier).
Bedrock Claude models were missing cache_read_input_token_cost and
cache_creation_input_token_cost fields, causing cache tokens to be
billed at the full input rate instead of the discounted cache rate.
Added pricing using Bedrock's documented multipliers (0.1x for cache
read, 1.25x for cache write) consistent with all existing entries.
The `gemini/gemini-2.5-flash-image` entry had `litellm_provider` set to
`vertex_ai-language-models` instead of `gemini`. This causes a provider
mismatch in `_check_provider_match()` when the model is used via the
Gemini API provider (`custom_llm_provider="gemini"`), resulting in a
noisy error log on every request:
"This model isn't mapped yet. model=gemini/gemini-2.5-flash-image,
custom_llm_provider=gemini"
The `vertex_ai/gemini-2.5-flash-image` entry already exists with the
correct `vertex_ai-language-models` provider, and the sibling
`gemini/gemini-2.5-flash-image-preview` entry correctly uses `gemini`.
Resolve conflict in model_prices_and_context_window.json by keeping both
the new minimax-m2.5 model from upstream and the OpenRouter native models
from this branch.
Remove /v1/chat/completions and /v1/responses from supported_endpoints
and revert the audio model detection change since gpt-realtime-1.5 does
not go through Chat Completions.
New OpenAI realtime model released 2026-02-23. Adds pricing and capability
metadata for gpt-realtime-1.5 (32K context, 4K output, audio/image/text I/O).
Unlike gpt-realtime, this model also supports Chat Completions and Responses
endpoints (not just WebSocket).
Closes#22266
- add gemini-3.1-flash-image-preview + vertex_ai alias entries\n- set pricing to Gemini 3.1 Flash Image Preview rates\n- mirror updates in packaged backup model map\n- update llm cost calc regression test to cover new model
* Adjust input and output cost per token for mistral-small-2503
Cost per million for mistral-small-2503 is not correct.
In Azure Documentation:
Pay-as-you-go (per 1,000 tokens)
$0.0001
Model input
$0.0003
Model output
* Update input and output cost per token for model
