From e08b4767e925c5c55c62a7881440da4bd6641a7c Mon Sep 17 00:00:00 2001 From: Chesars Date: Thu, 18 Dec 2025 17:25:43 -0300 Subject: [PATCH 01/46] fix: case-insensitive model cost map lookup Users were getting "does not support parameters: ['tools']" errors when using lowercase model names (e.g., "qwen/qwen3-next-80b-a3b-thinking") because the model cost map has mixed-case keys and the lookup was case-sensitive. Added _get_model_cost_key() helper that tries exact match first (O(1)), then falls back to case-insensitive search if not found. --- litellm/utils.py | 96 ++++++++++++++-------- tests/local_testing/test_get_model_info.py | 83 +++++++++++++++++++ 2 files changed, 144 insertions(+), 35 deletions(-) diff --git a/litellm/utils.py b/litellm/utils.py index dfc0df5c9a2..8eb71817111 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -4697,6 +4697,25 @@ def _strip_model_name(model: str, custom_llm_provider: Optional[str]) -> str: return model +def _get_model_cost_key(potential_key: str) -> Optional[str]: + """ + Get the actual key from model_cost, with case-insensitive fallback. + + Returns the key if found (exact match preferred, then case-insensitive), or None if not found. + """ + # Try exact match first (most common case, O(1)) + if potential_key in litellm.model_cost: + return potential_key + + # Fallback to case-insensitive match + potential_key_lower = potential_key.lower() + for key in litellm.model_cost: + if key.lower() == potential_key_lower: + return key + + return None + + def _get_model_info_from_model_cost(key: str) -> dict: return litellm.model_cost[key] @@ -4845,10 +4864,10 @@ def _is_potential_model_name_in_model_cost( potential_model_names: PotentialModelNamesAndCustomLLMProvider, ) -> bool: """ - Check if the potential model name is in the model cost. + Check if the potential model name is in the model cost (case-insensitive). """ return any( - potential_model_name in litellm.model_cost + _get_model_cost_key(potential_model_name) is not None for potential_model_name in potential_model_names.values() ) @@ -4926,44 +4945,51 @@ def _get_model_info_helper( # noqa: PLR0915 _model_info: Optional[Dict[str, Any]] = None key: Optional[str] = None - if combined_model_name in litellm.model_cost: - key = combined_model_name - _model_info = _get_model_info_from_model_cost(key=cast(str, key)) - if not _check_provider_match( - model_info=_model_info, custom_llm_provider=custom_llm_provider - ): - _model_info = None - if _model_info is None and model in litellm.model_cost: - key = model - _model_info = _get_model_info_from_model_cost(key=cast(str, key)) - if not _check_provider_match( - model_info=_model_info, custom_llm_provider=custom_llm_provider - ): - _model_info = None - if ( - _model_info is None - and combined_stripped_model_name in litellm.model_cost - ): - key = combined_stripped_model_name - _model_info = _get_model_info_from_model_cost(key=cast(str, key)) - if not _check_provider_match( - model_info=_model_info, custom_llm_provider=custom_llm_provider - ): - _model_info = None - if _model_info is None and stripped_model_name in litellm.model_cost: - key = stripped_model_name - _model_info = _get_model_info_from_model_cost(key=cast(str, key)) - if not _check_provider_match( - model_info=_model_info, custom_llm_provider=custom_llm_provider - ): - _model_info = None - if _model_info is None and split_model in litellm.model_cost: - key = split_model + # Use case-insensitive lookup for all model name checks + _matched_key = _get_model_cost_key(combined_model_name) + if _matched_key is not None: + key = _matched_key _model_info = _get_model_info_from_model_cost(key=cast(str, key)) if not _check_provider_match( model_info=_model_info, custom_llm_provider=custom_llm_provider ): _model_info = None + if _model_info is None: + _matched_key = _get_model_cost_key(model) + if _matched_key is not None: + key = _matched_key + _model_info = _get_model_info_from_model_cost(key=cast(str, key)) + if not _check_provider_match( + model_info=_model_info, custom_llm_provider=custom_llm_provider + ): + _model_info = None + if _model_info is None: + _matched_key = _get_model_cost_key(combined_stripped_model_name) + if _matched_key is not None: + key = _matched_key + _model_info = _get_model_info_from_model_cost(key=cast(str, key)) + if not _check_provider_match( + model_info=_model_info, custom_llm_provider=custom_llm_provider + ): + _model_info = None + if _model_info is None: + _matched_key = _get_model_cost_key(stripped_model_name) + if _matched_key is not None: + key = _matched_key + _model_info = _get_model_info_from_model_cost(key=cast(str, key)) + if not _check_provider_match( + model_info=_model_info, custom_llm_provider=custom_llm_provider + ): + _model_info = None + if _model_info is None: + _matched_key = _get_model_cost_key(split_model) + if _matched_key is not None: + key = _matched_key + _model_info = _get_model_info_from_model_cost(key=cast(str, key)) + if not _check_provider_match( + model_info=_model_info, custom_llm_provider=custom_llm_provider + ): + _model_info = None if _model_info is None or key is None: raise ValueError( diff --git a/tests/local_testing/test_get_model_info.py b/tests/local_testing/test_get_model_info.py index 823f03185d5..b84fc22af01 100644 --- a/tests/local_testing/test_get_model_info.py +++ b/tests/local_testing/test_get_model_info.py @@ -372,3 +372,86 @@ def test_get_model_info_cost_calculator_bedrock_region_cris_stripped(model, prov print("info", info) assert info["key"] == "us.anthropic.claude-3-haiku-20240307-v1:0" assert info["litellm_provider"] == "bedrock" + + +def test_get_model_info_case_insensitive_lookup(monkeypatch): + """ + Test that model info lookup is case-insensitive. + + This ensures that users can use lowercase model names even when the model cost + map has mixed-case keys (e.g., "Qwen/Qwen3-Next-80B-A3B-Thinking"). + + Related Slack discussion: Users were getting "does not support parameters: ['tools']" + errors when using lowercase model names like "qwen/qwen3-next-80b-a3b-thinking" + because the lookup was case-sensitive. + """ + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + litellm.model_cost = litellm.get_model_cost_map(url="") + + # Register a test model with mixed-case name + litellm.register_model( + { + "together_ai/Qwen/Qwen3-Next-80B-A3B-Thinking": { + "input_cost_per_token": 0.0001, + "output_cost_per_token": 0.0002, + "litellm_provider": "together_ai", + "supports_function_calling": True, + } + } + ) + + # Test 1: Exact case should work + info = litellm.get_model_info( + model="Qwen/Qwen3-Next-80B-A3B-Thinking", custom_llm_provider="together_ai" + ) + assert info is not None + assert info["supports_function_calling"] is True + + # Test 2: Lowercase should also work (case-insensitive lookup) + info_lower = litellm.get_model_info( + model="qwen/qwen3-next-80b-a3b-thinking", custom_llm_provider="together_ai" + ) + assert info_lower is not None + assert info_lower["supports_function_calling"] is True + + # Test 3: Mixed case should also work + info_mixed = litellm.get_model_info( + model="QWEN/qwen3-NEXT-80b-a3b-thinking", custom_llm_provider="together_ai" + ) + assert info_mixed is not None + assert info_mixed["supports_function_calling"] is True + + +def test_get_model_info_case_insensitive_supports_function_calling(monkeypatch): + """ + Test that supports_function_calling check works with case-insensitive model lookup. + """ + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + litellm.model_cost = litellm.get_model_cost_map(url="") + + # Register a model with mixed-case name that supports function calling + litellm.register_model( + { + "test_provider/TestModel-ABC": { + "input_cost_per_token": 0.0001, + "output_cost_per_token": 0.0002, + "litellm_provider": "test_provider", + "supports_function_calling": True, + } + } + ) + + # Test that supports_function_calling works with lowercase model name + from litellm.utils import supports_function_calling + + # Exact case + assert ( + supports_function_calling("TestModel-ABC", custom_llm_provider="test_provider") + is True + ) + + # Lowercase (should now work with case-insensitive lookup) + assert ( + supports_function_calling("testmodel-abc", custom_llm_provider="test_provider") + is True + ) From b84aafbab6c55881718746bfdd9e6488562f73a0 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Tue, 23 Dec 2025 08:31:21 -0500 Subject: [PATCH 02/46] Add end to end integration tests for batches --- BATCH_FIXES_README.md | 365 +++++++++++ .../proxy/hooks/managed_files.py | 41 +- litellm/proxy/_types.py | 2 +- litellm/proxy/batches_endpoints/endpoints.py | 1 + .../openai_files_endpoints/files_endpoints.py | 1 + tests/batches_tests/local-litellm/README.md | 15 + .../local-litellm/docker-compose.dev.yml | 38 ++ .../local-litellm/docker-compose.yml | 109 ++++ .../local-litellm/litellm-config.yaml | 57 ++ .../local-litellm/mock-server/Dockerfile | 18 + .../local-litellm/mock-server/main.py | 47 ++ .../mock-server/mock_azure_batch.py | 582 ++++++++++++++++++ .../local-litellm/mock-server/mock_chat.py | 124 ++++ .../mock-server/mock_embeddings.py | 26 + .../mock-server/mock_responses.py | 92 +++ .../local-litellm/mock-server/pyproject.toml | 20 + .../local-litellm/mock-server/uv.lock | 416 +++++++++++++ .../local-litellm/patches/README.md | 231 +++++++ .../batches_tests/test_managed_files_base.py | 220 +++++++ .../test_managed_files_endtoend.py | 204 ++++++ .../test_managed_files_permissions.py | 436 +++++++++++++ 21 files changed, 3041 insertions(+), 4 deletions(-) create mode 100644 BATCH_FIXES_README.md create mode 100644 tests/batches_tests/local-litellm/README.md create mode 100644 tests/batches_tests/local-litellm/docker-compose.dev.yml create mode 100644 tests/batches_tests/local-litellm/docker-compose.yml create mode 100644 tests/batches_tests/local-litellm/litellm-config.yaml create mode 100644 tests/batches_tests/local-litellm/mock-server/Dockerfile create mode 100644 tests/batches_tests/local-litellm/mock-server/main.py create mode 100644 tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py create mode 100644 tests/batches_tests/local-litellm/mock-server/mock_chat.py create mode 100644 tests/batches_tests/local-litellm/mock-server/mock_embeddings.py create mode 100644 tests/batches_tests/local-litellm/mock-server/mock_responses.py create mode 100644 tests/batches_tests/local-litellm/mock-server/pyproject.toml create mode 100644 tests/batches_tests/local-litellm/mock-server/uv.lock create mode 100644 tests/batches_tests/local-litellm/patches/README.md create mode 100644 tests/batches_tests/test_managed_files_base.py create mode 100644 tests/batches_tests/test_managed_files_endtoend.py create mode 100644 tests/batches_tests/test_managed_files_permissions.py diff --git a/BATCH_FIXES_README.md b/BATCH_FIXES_README.md new file mode 100644 index 00000000000..205ab2d29a1 --- /dev/null +++ b/BATCH_FIXES_README.md @@ -0,0 +1,365 @@ +# LiteLLM Batch API Fixes + +This document describes bugs found in LiteLLM's managed batch/files functionality and the patches applied to fix them. It also provides step-by-step instructions to reproduce the tests from a clean slate. + +## Table of Contents + +1. [Bug 1: File Deletion Fails for Batch Output Files](#bug-1-file-deletion-fails-for-batch-output-files) +2. [Bug 2: File Deletion Returns Wrong Response](#bug-2-file-deletion-returns-wrong-response) +3. [Bug 3: Batch Listing Fails with Duplicate Argument](#bug-3-batch-listing-fails-with-duplicate-argument) +4. [Bug 4: File Retrieve Returns None for Batch Output Files](#bug-4-file-retrieve-returns-none-for-batch-output-files) +5. [Mock Server: Azure-like Credential Validation](#mock-server-azure-like-credential-validation) +6. [Test Setup Instructions](#test-setup-instructions) + +--- + +## Bug 1: File Deletion Fails for Batch Output Files + +### Description + +**Broken Feature:** `DELETE /files/{file_id}` - Deleting batch output files fails with a Pydantic validation error. + +**Error Message:** +``` +openai.InternalServerError: Error code: 500 - { + 'error': { + 'message': '1 validation error for LiteLLM_ManagedFileTable\nfile_object\n Input should be a valid dictionary or instance of OpenAIFileObject [type=model_type, input_value=None, input_type=NoneType]' + } +} +``` + +**Root Cause:** When LiteLLM stores batch output files in `LiteLLM_ManagedFileTable`, it sets `file_object=None`. However, the Pydantic model requires this field to be a valid `OpenAIFileObject`. + +### Patch + +**File:** `litellm/proxy/_types.py`, line ~3759 + +```python +# Before +class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): + file_object: OpenAIFileObject + +# After +class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): + file_object: Optional[OpenAIFileObject] = None # PATCHED +``` + +--- + +## Bug 2: File Deletion Returns Wrong Response + +### Description + +**Broken Feature:** `DELETE /files/{file_id}` - Even after fixing Bug #1, the method returns `None` instead of the delete confirmation. + +**Error Message:** +``` +Exception: LiteLLM Managed File object with id=... not found +``` + +**Root Cause:** `afile_delete` in `managed_files.py` calls `llm_router.afile_delete()` (which deletes the file at the provider) but discards the response. + +### Patch + +**File:** `enterprise/litellm_enterprise/proxy/hooks/managed_files.py`, line ~879 + +```python +# Before +async def afile_delete(self, file_id, ...): + for model_id, model_file_id in mapping.items(): + await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) + # Returns None when stored_file_object is None + +# After +async def afile_delete(self, file_id, ...): + delete_response = None # PATCHED: Capture response + for model_id, model_file_id in mapping.items(): + delete_response = await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) + + stored_file_object = await self.delete_unified_file_id(file_id, ...) + if stored_file_object: + return stored_file_object + elif delete_response: # PATCHED: Return provider response + delete_response.id = file_id # Replace with unified ID + return delete_response + else: + raise Exception(...) +``` + +--- + +## Bug 3: Batch Listing Fails with Duplicate Argument + +### Description + +**Broken Feature:** `GET /batches?target_model_names=...` - Listing batches fails when using `target_model_names` query parameter. + +**Error Message:** +``` +openai.InternalServerError: Error code: 500 - { + 'error': { + 'message': "alist_batches() got multiple values for keyword argument 'model'" + } +} +``` + +**Root Cause:** The code passes `model` explicitly AND includes it in `**data`: +```python +model = target_model_names.split(",")[0] +response = await llm_router.alist_batches( + model=model, # Passed explicitly + **data, # Also contains 'model' and 'target_model_names' keys +) +``` + +### Patch + +**File:** `litellm/proxy/batches_endpoints/endpoints.py`, line ~576-577 + +```python +# Before +model = target_model_names.split(",")[0] +response = await llm_router.alist_batches(model=model, **data) + +# After +model = target_model_names.split(",")[0] +data.pop("model", None) # PATCHED: Remove duplicate +data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream +response = await llm_router.alist_batches(model=model, **data) +``` + +--- + +## Bug 4: File Retrieve Returns None for Batch Output Files + +### Description + +**Broken Feature:** `GET /files/{file_id}` - Retrieving batch output file metadata returns `None`. + +**Error Message:** +``` +AttributeError: 'NoneType' object has no attribute 'id' +``` + +**Root Cause:** `afile_retrieve` returns `stored_file_object.file_object` which is `None` for batch output files. It should fetch the file metadata from the provider instead. + +### Patch (Part A) + +**File:** `enterprise/litellm_enterprise/proxy/hooks/managed_files.py`, line ~839-868 + +Add `import litellm` at the top of the file, then modify `afile_retrieve`: + +```python +# Before +async def afile_retrieve(self, file_id, litellm_parent_otel_span): + stored = await self.get_unified_file_id(file_id, ...) + return stored.file_object # Returns None for batch output files! + +# After +import litellm # Added at top of file + +async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router=None): # PATCHED: Added llm_router + stored = await self.get_unified_file_id(file_id, ...) + if stored: + if stored.file_object: + return stored.file_object + # PATCHED: Fetch from provider when file_object is None + elif stored.model_mappings and llm_router: + for model_id, model_file_id in stored.model_mappings.items(): + deployment = llm_router.get_deployment(model_id=model_id) + if deployment: + credentials = llm_router.get_deployment_credentials(model_id=model_id) or {} + # Extract custom_llm_provider - afile_retrieve needs it as explicit param + custom_llm_provider = credentials.pop("custom_llm_provider", None) + if not custom_llm_provider: + # Infer from model name (e.g., "azure/gpt-5" -> "azure") + model_name = deployment.litellm_params.model or "" + if "/" in model_name: + custom_llm_provider = model_name.split("/")[0] + else: + custom_llm_provider = "openai" + response = await litellm.afile_retrieve( + file_id=model_file_id, + custom_llm_provider=custom_llm_provider, # Explicit param for Azure + **credentials + ) + response.id = file_id # Replace with unified ID + return response +``` + +### Patch (Part B) + +**File:** `litellm/proxy/openai_files_endpoints/files_endpoints.py`, line ~888 + +```python +# Before +response = await managed_files_obj.afile_retrieve( + file_id=file_id, + litellm_parent_otel_span=user_api_key_dict.parent_otel_span, +) + +# After +response = await managed_files_obj.afile_retrieve( + file_id=file_id, + litellm_parent_otel_span=user_api_key_dict.parent_otel_span, + llm_router=llm_router, # PATCHED: Pass router to fetch from provider +) +``` + +--- + +## Test Setup Instructions + +### Prerequisites + +- Python 3.11+ +- Docker and Docker Compose +- Poetry (Python package manager) + +### Step 1: Clone and Setup Environment + +```bash +# Install dependencies +poetry install --extras "proxy extra_proxy" + +# Install enterprise package in editable mode (required for patches to work) +poetry run pip install -e enterprise +``` + +### Step 2: Terminal 1 - Start Database and Mock Server + +```bash +cd tests/batches_tests/local-litellm + +# Build and start PostgreSQL and Mock Azure Server +docker compose -f docker-compose.dev.yml up --build +``` + +Wait until you see both services are healthy: +- `litellm_dev_db` - PostgreSQL database +- `mock-server` - Mock Azure OpenAI server (with credential validation enabled by default) + +**Note:** The mock server now validates credentials like real Azure. Use `--build` to ensure you have the latest mock server with credential validation. + +### Step 3: Terminal 2 - Start LiteLLM Proxy + +```bash +cd /path/to/litellm + +# Set environment variables +export DATABASE_URL="postgresql://llmproxy:dbpassword9090@localhost:5432/litellm" +export LITELLM_MASTER_KEY="sk-1234" +export LITELLM_SALT_KEY="mock-salt-key-12345" + +# For real Azure testing (optional): +# export OPENAI_API_KEY="your-azure-api-key" +# export OPENAI_API_BASE=https://your azure endpoint" + +# Generate Prisma client (first time only) +poetry run python -m prisma generate + +# Start the proxy server +poetry run litellm --config tests/batches_tests/local-litellm/litellm-config.yaml --detailed_debug --port 4000 +``` + +Wait until you see: +``` +INFO: Uvicorn running on http://0.0.0.0:4000 +``` + +### Step 4: Terminal 3 - Run Tests + +```bash +cd /path/to/litellm + +# Run the end-to-end managed files test with mock server +USE_MOCK_SERVER=true poetry run pytest tests/batches_tests/test_managed_files_endtoend.py -s -vvv +``` + +### Expected Output + +The test should pass with output similar to: + +``` +tests/batches_tests/test_managed_files_endtoend.py::TestManagedFilesAPI::test_e2e_managed_batch[gpt] +Creating batch input file... +Created batch input file: bGl0ZWxs... + +Creating batch... +Created batch: bGl0ZWxs... + +Waiting for batch to reach completed state... +Batch status: completed + +Retrieving batch output file metadata... +Output file metadata: ... + +Fetching batch output file content... +Output file content: ... + +Deleting input file... +Deleting output file... + +PASSED +``` + +--- + +## Configuration Files + +### `tests/batches_tests/local-litellm/litellm-config-local.yaml` + +This config file sets up models for local testing: +- Mock OpenAI models pointing to `http://localhost:8090` +- Mock Azure batch model pointing to `http://localhost:8090` +- (Optional) Real Azure batch model with API key from environment + +### `tests/batches_tests/local-litellm/docker-compose.dev.yml` + +Docker Compose file that runs: +- PostgreSQL 16 database on port 5432 +- Mock Azure OpenAI server on port 8090 + +--- + +## Troubleshooting + +### "No module named prisma" + +```bash +poetry run pip install prisma==0.11.0 +poetry run python -m prisma generate +``` + +### Database connection error + +Ensure PostgreSQL is running and the DATABASE_URL is correct: +```bash +docker ps | grep postgres +# Should show litellm_dev_db running on port 5432 +``` + +### Patches not being picked up/ + +1. Clear Python cache: + ```bash + find enterprise -name "__pycache__" -type d -exec rm -rf {} + + find litellm -name "__pycache__" -type d -exec rm -rf {} + + ``` + +2. Verify editable install: + ```bash + poetry run pip show litellm-enterprise | grep "Editable" + # Should show: Editable project location: /path/to/litellm/enterprise + ``` + +3. Restart the proxy server + +### Azure credentials error when testing with real Azure + +Set the environment variable before starting the proxy: +```bash +export OPENAI_API_KEY="your-actual-azure-api-key" +``` + +--- diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index a83d7e224b5..1afaee30c74 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -8,6 +8,7 @@ from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union, cas from fastapi import HTTPException +import litellm from litellm import Router, verbose_logger from litellm._uuid import uuid from litellm.caching.caching import DualCache @@ -836,13 +837,41 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): return response async def afile_retrieve( - self, file_id: str, litellm_parent_otel_span: Optional[Span] + self, file_id: str, litellm_parent_otel_span: Optional[Span], llm_router=None ) -> OpenAIFileObject: stored_file_object = await self.get_unified_file_id( file_id, litellm_parent_otel_span ) if stored_file_object: - return stored_file_object.file_object + # PATCHED: If file_object is None (batch output files), fetch from provider + if stored_file_object.file_object: + return stored_file_object.file_object + elif stored_file_object.model_mappings and llm_router: + for model_id, model_file_id in stored_file_object.model_mappings.items(): + # PATCHED: Get deployment info and credentials from router + deployment = llm_router.get_deployment(model_id=model_id) + if deployment: + credentials = llm_router.get_deployment_credentials(model_id=model_id) or {} + # Extract custom_llm_provider - afile_retrieve needs it as explicit param + custom_llm_provider = credentials.pop("custom_llm_provider", None) + if not custom_llm_provider: + # Infer from model name (e.g., "azure/gpt-5" -> "azure") + model_name = deployment.litellm_params.model or "" + if "/" in model_name: + custom_llm_provider = model_name.split("/")[0] + else: + custom_llm_provider = "openai" + response = await litellm.afile_retrieve( + file_id=model_file_id, + custom_llm_provider=custom_llm_provider, + **credentials + ) + response.id = file_id # Replace with unified ID + return response + else: + raise Exception(f"No deployment found for model_id={model_id}") + else: + raise Exception(f"LiteLLM Managed File object with id={file_id} has no file_object, or no model_mappings/llm_router to fetch from provider") else: raise Exception(f"LiteLLM Managed File object with id={file_id} not found") @@ -868,10 +897,12 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): [file_id], litellm_parent_otel_span ) + # PATCHED: Capture delete response from provider + delete_response = None specific_model_file_id_mapping = model_file_id_mapping.get(file_id) if specific_model_file_id_mapping: for model_id, model_file_id in specific_model_file_id_mapping.items(): - await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) # type: ignore + delete_response = await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) # type: ignore stored_file_object = await self.delete_unified_file_id( file_id, litellm_parent_otel_span @@ -879,6 +910,10 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): if stored_file_object: return stored_file_object + # PATCHED: Return provider response with unified ID when stored_file_object is None + elif delete_response: + delete_response.id = file_id + return delete_response else: raise Exception(f"LiteLLM Managed File object with id={file_id} not found") diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 06067035c18..9767e07bbc8 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -3756,7 +3756,7 @@ class SpendUpdateQueueItem(TypedDict, total=False): class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): unified_file_id: str - file_object: OpenAIFileObject + file_object: Optional[OpenAIFileObject] = None # PATCHED: Allow None for batch output files model_mappings: Dict[str, str] flat_model_file_ids: List[str] created_by: Optional[str] diff --git a/litellm/proxy/batches_endpoints/endpoints.py b/litellm/proxy/batches_endpoints/endpoints.py index 086105042e8..dd68a54f694 100644 --- a/litellm/proxy/batches_endpoints/endpoints.py +++ b/litellm/proxy/batches_endpoints/endpoints.py @@ -574,6 +574,7 @@ async def list_batches( raise ValueError("target_model_names is required for this routing scenario") model = target_model_names.split(",")[0] data.pop("model", None) + data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream response = await llm_router.alist_batches( model=model, after=after, diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index 810f5c62720..586f7840835 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -885,6 +885,7 @@ async def get_file( response = await managed_files_obj.afile_retrieve( file_id=file_id, litellm_parent_otel_span=user_api_key_dict.parent_otel_span, + llm_router=llm_router, # PATCHED: Pass router to fetch from provider if file_object is None ) else: response = await litellm.afile_retrieve( diff --git a/tests/batches_tests/local-litellm/README.md b/tests/batches_tests/local-litellm/README.md new file mode 100644 index 00000000000..b4f5e38fdec --- /dev/null +++ b/tests/batches_tests/local-litellm/README.md @@ -0,0 +1,15 @@ +# Local LiteLLM + +Local LiteLLM proxy with a mock LLM server for testing. + +## Start + +```bash +docker compose up --build +``` + +## Stop + +```bash +docker compose down +``` diff --git a/tests/batches_tests/local-litellm/docker-compose.dev.yml b/tests/batches_tests/local-litellm/docker-compose.dev.yml new file mode 100644 index 00000000000..035b65648e0 --- /dev/null +++ b/tests/batches_tests/local-litellm/docker-compose.dev.yml @@ -0,0 +1,38 @@ +# Docker Compose for local development +# Runs db and mock-server only - proxy runs locally via poetry + +services: + db: + image: postgres:16 + container_name: litellm_dev_db + restart: always + environment: + POSTGRES_DB: litellm + POSTGRES_USER: llmproxy + POSTGRES_PASSWORD: dbpassword9090 + healthcheck: + test: ["CMD-SHELL", "pg_isready -d litellm -U llmproxy"] + interval: 1s + timeout: 5s + retries: 10 + volumes: + - postgres_data_dev:/var/lib/postgresql/data + ports: + - "5432:5432" + + mock-server: + build: + context: ./mock-server + dockerfile: Dockerfile + ports: + - "8090:8090" + healthcheck: + test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:8090/health || exit 1"] + interval: 5s + timeout: 5s + retries: 5 + start_period: 10s + +volumes: + postgres_data_dev: + diff --git a/tests/batches_tests/local-litellm/docker-compose.yml b/tests/batches_tests/local-litellm/docker-compose.yml new file mode 100644 index 00000000000..914d659ac81 --- /dev/null +++ b/tests/batches_tests/local-litellm/docker-compose.yml @@ -0,0 +1,109 @@ +services: + # Default LiteLLM without patches + litellm: + image: ghcr.io/berriai/litellm:main-latest + profiles: ["default", "unpatched"] + ports: + - "4000:4000" + volumes: + - ./litellm-config.yaml:/app/config.yaml + command: + - "--config=/app/config.yaml" + - "--detailed_debug" + environment: + DATABASE_URL: "postgresql://llmproxy:dbpassword9090@db:5432/litellm" + STORE_MODEL_IN_DB: "True" + LITELLM_MASTER_KEY: "sk-1234" + LITELLM_SALT_KEY: "mock-salt-key-12345" + LITELLM_LOG: "DEBUG" + real_azure_api_key: "${real_azure_api_key:-}" + depends_on: + db: + condition: service_healthy + mock-server: + condition: service_healthy + healthcheck: + test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:4000/health/liveliness || exit 1"] + interval: 30s + timeout: 10s + retries: 3 + start_period: 40s + + # LiteLLM with patches enabled + litellm-patched: + image: ghcr.io/berriai/litellm:main-latest + profiles: ["patched"] + ports: + - "4000:4000" + volumes: + - ./litellm-config.yaml:/app/config.yaml + # patch1 + - ./patches/managed_files.py:/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py + - ./patches/managed_files.py:/app/enterprise/litellm_enterprise/proxy/hooks/managed_files.py + # patch2 + - ./patches/_types.py:/usr/lib/python3.13/site-packages/litellm/proxy/_types.py + - ./patches/_types.py:/app/litellm/proxy/_types.py + # patch3 + - ./patches/batches_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py + - ./patches/batches_endpoints.py:/app/litellm/proxy/batches_endpoints/endpoints.py + # patch4 + - ./patches/files_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py + - ./patches/files_endpoints.py:/app/litellm/proxy/openai_files_endpoints/files_endpoints.py + command: + - "--config=/app/config.yaml" + - "--detailed_debug" + environment: + DATABASE_URL: "postgresql://llmproxy:dbpassword9090@db:5432/litellm" + STORE_MODEL_IN_DB: "True" + LITELLM_MASTER_KEY: "sk-1234" + LITELLM_SALT_KEY: "mock-salt-key-12345" + LITELLM_LOG: "DEBUG" + real_azure_api_key: "${real_azure_api_key:-}" + depends_on: + db: + condition: service_healthy + mock-server: + condition: service_healthy + healthcheck: + test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:4000/health/liveliness || exit 1"] + interval: 30s + timeout: 10s + retries: 3 + start_period: 40s + + db: + image: postgres:16 + restart: always + container_name: litellm_local_db + environment: + POSTGRES_DB: litellm + POSTGRES_USER: llmproxy + POSTGRES_PASSWORD: dbpassword9090 + ports: + - "5432:5432" + volumes: + - postgres_data:/var/lib/postgresql/data + healthcheck: + test: ["CMD-SHELL", "pg_isready -d litellm -U llmproxy"] + interval: 1s + timeout: 5s + retries: 10 + + mock-server: + build: + context: ./mock-server + dockerfile: Dockerfile + ports: + - "8090:8090" + environment: + TIME_TO_SLEEP: "0" + healthcheck: + test: ["CMD-SHELL", "curl -f http://localhost:8090/health || exit 1"] + interval: 10s + timeout: 5s + retries: 3 + start_period: 5s + +volumes: + postgres_data: + name: litellm_local_postgres_data diff --git a/tests/batches_tests/local-litellm/litellm-config.yaml b/tests/batches_tests/local-litellm/litellm-config.yaml new file mode 100644 index 00000000000..28721f1081c --- /dev/null +++ b/tests/batches_tests/local-litellm/litellm-config.yaml @@ -0,0 +1,57 @@ +model_list: + - model_name: openai-fake-gpt-3.5-turbo + litellm_params: + model: openai/openai-fake-gpt-3.5-turbo + api_base: http://localhost:8090/v1 + api_key: fake-key + - model_name: openai-fake-gpt-4 + litellm_params: + model: openai/openai-fake-gpt-4 + api_base: http://localhost:8090/v1 + api_key: fake-key + - model_name: openai-fake-gpt-4o + litellm_params: + model: openai/openai-fake-gpt-4o + api_base: http://localhost:8090/v1 + api_key: fake-key + - model_name: fake-text-embedding-3-small + litellm_params: + model: openai/fake-text-embedding-3-small + api_base: http://localhost:8090/v1 + api_key: fake-key + - model_name: o3-mini-batch-2025-01-31 + litellm_params: + model: openai/o3-mini-batch-2025-01-31 + api_base: http://localhost:8090/openai/v1 + api_key: fake-key + model_info: + mode: batch + - model_name: azure-fake-gpt-5-batch-2025-08-07 + litellm_params: + api_base: http://localhost:8090 + api_key: fake-key + api_version: 2025-03-01-preview + base_model: azure/gpt-5 + model: azure/gpt-5-batch-2025-08-07 + custom_llm_provider: azure + model_info: + mode: batch + - model_name: gpt-5-batch-2025-08-07 + litellm_params: + api_base: os.environ/OPENAI_API_BASE + api_key: os.environ/OPENAI_API_KEY + api_version: 2025-03-01-preview + base_model: azure/gpt-5 + model: azure/gpt-5-batch-2025-08-07 + custom_llm_provider: azure + model_info: + mode: batch + +general_settings: + master_key: sk-1234 + database_url: "postgresql://llmproxy:dbpassword9090@localhost:5432/litellm" + +litellm_settings: + drop_params: true + set_verbose: true + json_logs: true diff --git a/tests/batches_tests/local-litellm/mock-server/Dockerfile b/tests/batches_tests/local-litellm/mock-server/Dockerfile new file mode 100644 index 00000000000..dd31250349c --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/Dockerfile @@ -0,0 +1,18 @@ +FROM python:3.11-slim + +RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +COPY pyproject.toml . +COPY main.py . +COPY mock_azure_batch.py . +COPY mock_chat.py . +COPY mock_responses.py . +COPY mock_embeddings.py . + +RUN pip install --no-cache-dir $(python -c "import tomllib; print(' '.join(tomllib.load(open('pyproject.toml', 'rb'))['project']['dependencies']))") + +EXPOSE 8090 + +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8090"] diff --git a/tests/batches_tests/local-litellm/mock-server/main.py b/tests/batches_tests/local-litellm/mock-server/main.py new file mode 100644 index 00000000000..943ab36681f --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/main.py @@ -0,0 +1,47 @@ +from dotenv import load_dotenv +from fastapi import FastAPI, Request +from fastapi.middleware.cors import CORSMiddleware +from slowapi import Limiter, _rate_limit_exceeded_handler +from slowapi.errors import RateLimitExceeded + +from mock_azure_batch import setup_batch_routes +from mock_chat import setup_chat_routes +from mock_embeddings import setup_embeddings_routes +from mock_responses import setup_responses_routes + + +def get_request_url(request: Request): + return str(request.url) + + +limiter = Limiter(key_func=get_request_url) +load_dotenv() + +app = FastAPI() +app.state.limiter = limiter +app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +@app.get("/health") +async def health(): + return {"status": "ok"} + + +setup_chat_routes(app) +setup_responses_routes(app) +setup_embeddings_routes(app) +setup_batch_routes(app) + + +if __name__ == "__main__": + import uvicorn + + uvicorn.run(app, host="0.0.0.0", port=8090) diff --git a/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py b/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py new file mode 100644 index 00000000000..3512c8472d5 --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py @@ -0,0 +1,582 @@ +import asyncio +import io +import json +import logging +import os +import time +import uuid +from typing import Dict, List, Optional + +from fastapi import FastAPI, HTTPException, Query, Request, UploadFile, Depends +from fastapi.responses import StreamingResponse +from fastapi.security import APIKeyHeader +from pydantic import BaseModel + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +# Azure-like credential validation +# Set MOCK_REQUIRE_CREDENTIALS=true to enforce credential checks (like real Azure) +REQUIRE_CREDENTIALS = os.environ.get("MOCK_REQUIRE_CREDENTIALS", "true").lower() == "true" +VALID_API_KEYS = {"fake-key", "sk-1234", "test-key"} # Accept these API keys + +api_key_header = APIKeyHeader(name="api-key", auto_error=False) +auth_header = APIKeyHeader(name="Authorization", auto_error=False) + + +def validate_credentials( + api_key: Optional[str] = Depends(api_key_header), + authorization: Optional[str] = Depends(auth_header), +): + """ + Validate Azure-style credentials. + Azure accepts either: + - api-key header + - Authorization: Bearer header + """ + if not REQUIRE_CREDENTIALS: + return True + + # Check api-key header + if api_key: + if api_key in VALID_API_KEYS: + return True + logger.warning(f"Invalid api-key provided: {api_key[:8]}...") + raise HTTPException( + status_code=401, + detail={ + "error": { + "code": "401", + "message": "Access denied due to invalid subscription key or wrong API endpoint. " + "Make sure to provide a valid key for an active subscription and use a " + "correct regional API endpoint for your resource." + } + } + ) + + # Check Authorization header (Bearer token) + if authorization: + if authorization.startswith("Bearer "): + # Accept any bearer token for mock purposes + return True + logger.warning(f"Invalid Authorization header format") + + # No credentials provided + logger.warning("No credentials provided in request") + raise HTTPException( + status_code=401, + detail={ + "error": { + "code": "401", + "message": "Missing credentials. Please pass one of `api_key`, `azure_ad_token`, " + "`azure_ad_token_provider`, or the `AZURE_OPENAI_API_KEY` or " + "`AZURE_OPENAI_AD_TOKEN` environment variables." + } + } + ) + + +class FileObject(BaseModel): + id: str + object: str = "file" + bytes: int + created_at: int + filename: str + purpose: str + status: str = "processed" + status_details: Optional[str] = None + expires_at: Optional[int] = None + + +class BatchObject(BaseModel): + id: str + object: str = "batch" + endpoint: str + errors: Optional[Dict] = None + input_file_id: str + completion_window: str + status: str + output_file_id: Optional[str] = None + error_file_id: Optional[str] = None + created_at: int + in_progress_at: Optional[int] = None + expires_at: Optional[int] = None + finalizing_at: Optional[int] = None + completed_at: Optional[int] = None + failed_at: Optional[int] = None + expired_at: Optional[int] = None + cancelling_at: Optional[int] = None + cancelled_at: Optional[int] = None + request_counts: Optional[Dict[str, int]] = None + metadata: Optional[Dict] = None + + +class BatchListResponse(BaseModel): + object: str = "list" + data: List[Dict] + first_id: Optional[str] = None + last_id: Optional[str] = None + has_more: bool = False + + +file_storage: Dict[str, Dict] = {} +batch_storage: Dict[str, BatchObject] = {} +batch_results: Dict[str, List[Dict]] = {} + +PROCESSING_DELAY_SECONDS = float(1) +VALIDATING_DELAY_SECONDS = float(3) + + +async def process_batch(batch_id: str): + logger.info(f"Starting batch processing for {batch_id}") + try: + batch = batch_storage[batch_id] + + await asyncio.sleep(VALIDATING_DELAY_SECONDS) + batch.status = "in_progress" + batch.in_progress_at = int(time.time()) + logger.info(f"Batch {batch_id} status: in_progress") + + await process_batch_requests(batch_id) + await asyncio.sleep(PROCESSING_DELAY_SECONDS) + + batch.status = "finalizing" + batch.finalizing_at = int(time.time()) + logger.info(f"Batch {batch_id} status: finalizing") + await asyncio.sleep(PROCESSING_DELAY_SECONDS) + + await create_output_file(batch_id) + + batch.status = "completed" + batch.completed_at = int(time.time()) + logger.info(f"Batch {batch_id} status: completed") + + except Exception as e: + logger.error(f"Batch {batch_id} failed: {e}") + batch = batch_storage[batch_id] + batch.status = "failed" + batch.failed_at = int(time.time()) + batch.errors = { + "object": "list", + "data": [{"code": "processing_error", "message": str(e)}], + } + + +async def process_batch_requests(batch_id: str): + batch = batch_storage[batch_id] + input_file = file_storage[batch.input_file_id] + + requests = [] + for line in input_file["content"].split("\n"): + if line.strip(): + try: + requests.append(json.loads(line)) + except json.JSONDecodeError as e: + logger.warning(f"Invalid JSON line in batch {batch_id}: {e}") + + logger.info(f"Batch {batch_id} has {len(requests)} requests") + + results = [] + failed_count = 0 + for req in requests: + result = await process_single_request(req) + if result.get("error"): + failed_count += 1 + results.append(result) + + batch_results[batch_id] = results + batch.request_counts = { + "total": len(requests), + "completed": len(results) - failed_count, + "failed": failed_count, + } + + +async def process_single_request(request_data: Dict) -> Dict: + custom_id = request_data.get("custom_id") + url = request_data.get("url", "/v1/chat/completions") + body = request_data.get("body", {}) + + if "/chat/completions" in url: + response_body = { + "id": f"chatcmpl-{uuid.uuid4().hex}", + "object": "chat.completion", + "created": int(time.time()), + "model": body.get("model", "gpt-4o"), + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "Mock batch response."}, + "finish_reason": "stop", + }, + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, + } + status_code = 200 + else: + response_body = {"error": {"message": f"Unsupported endpoint: {url}"}} + status_code = 400 + + return { + "id": f"batch_req_{uuid.uuid4().hex[:12]}", + "custom_id": custom_id, + "response": { + "status_code": status_code, + "request_id": f"req_{uuid.uuid4().hex[:12]}", + "body": response_body, + }, + "error": None, + } + + +async def create_output_file(batch_id: str): + results = batch_results.get(batch_id, []) + output_lines = [json.dumps(result) for result in results] + output_content = "\n".join(output_lines) + + output_file_id = f"file-batch-output-{uuid.uuid4().hex[:12]}" + file_storage[output_file_id] = { + "content": output_content, + "filename": f"batch_output_{batch_id}.jsonl", + "purpose": "batch_output", + "bytes": len(output_content.encode()), + "created_at": int(time.time()), + } + + batch = batch_storage[batch_id] + batch.output_file_id = output_file_id + logger.info(f"Created output file {output_file_id} for batch {batch_id}") + + +def validate_batch_input(content: str) -> tuple[bool, str, List[Dict]]: + requests = [] + custom_ids = set() + + lines = content.strip().split("\n") + if not lines or all(not line.strip() for line in lines): + return False, "empty_batch", [] + + for line_num, line in enumerate(lines, 1): + if not line.strip(): + continue + try: + req = json.loads(line) + except json.JSONDecodeError: + return False, "invalid_json_line", [] + + for field in ["custom_id", "method", "url", "body"]: + if field not in req: + return False, "invalid_request", [] + + if req["custom_id"] in custom_ids: + return False, "duplicate_custom_id", [] + custom_ids.add(req["custom_id"]) + + requests.append(req) + + if len(requests) > 100000: + return False, "too_many_tasks", [] + + return True, "", requests + + +def setup_batch_routes(app: FastAPI): + # Files endpoints (OpenAI and Azure paths) + # All endpoints require credentials (like real Azure) + @app.post("/openai/v1/files") + @app.post("/openai/files") + @app.post("/v1/files") + @app.post("/files") + async def create_file(request: Request, _=Depends(validate_credentials)): + form = await request.form() + logger.info(f"File upload form fields: {list(form.keys())}") + + file: UploadFile = form.get("file") + purpose: str = form.get("purpose", "batch") + + if not file: + raise HTTPException(status_code=400, detail="No file provided") + + logger.info(f"Uploading file: {file.filename}, purpose: {purpose}") + + content = await file.read() + content_str = content.decode("utf-8") + + file_id = f"file-{uuid.uuid4().hex[:24]}" + created_at = int(time.time()) + + expires_at = None + expires_after_seconds = form.get("expires_after[seconds]") + if expires_after_seconds: + try: + seconds = int(expires_after_seconds) + logger.info(f"expires_after[seconds] = {seconds}") + if seconds < 259200 or seconds > 2592000: + raise HTTPException( + status_code=400, + detail={ + "error": { + "code": "invalidPayload", + "message": "Value for Seconds must be between 259200 and 2592000.", + }, + }, + ) + expires_at = created_at + seconds + logger.info(f"Calculated expires_at: {expires_at}") + except ValueError as e: + logger.warning(f"Failed to parse expires_after[seconds]: {e}") + + file_storage[file_id] = { + "content": content_str, + "filename": file.filename or "batch_input.jsonl", + "purpose": purpose, + "bytes": len(content), + "created_at": created_at, + "expires_at": expires_at, + } + + logger.info(f"Created file {file_id}, expires_at={expires_at}") + return FileObject( + id=file_id, + bytes=len(content), + created_at=created_at, + filename=file.filename or "batch_input.jsonl", + purpose=purpose, + expires_at=expires_at, + ).model_dump() + + @app.get("/openai/v1/files/{file_id}") + @app.get("/openai/files/{file_id}") + @app.get("/v1/files/{file_id}") + @app.get("/files/{file_id}") + async def get_file(file_id: str, _=Depends(validate_credentials)): + logger.info(f"Getting file: {file_id}") + if file_id not in file_storage: + raise HTTPException(status_code=404, detail="File not found") + + file_data = file_storage[file_id] + return FileObject( + id=file_id, + bytes=file_data["bytes"], + created_at=file_data["created_at"], + filename=file_data["filename"], + purpose=file_data["purpose"], + expires_at=file_data.get("expires_at"), + ).model_dump() + + @app.get("/openai/v1/files/{file_id}/content") + @app.get("/openai/files/{file_id}/content") + @app.get("/v1/files/{file_id}/content") + @app.get("/files/{file_id}/content") + async def get_file_content(file_id: str, _=Depends(validate_credentials)): + logger.info(f"Getting file content: {file_id}") + if file_id not in file_storage: + raise HTTPException(status_code=404, detail="File not found") + + file_data = file_storage[file_id] + content = file_data["content"] + + return StreamingResponse( + io.StringIO(content), + media_type="application/octet-stream", + headers={ + "Content-Disposition": f"attachment; filename={file_data['filename']}", + }, + ) + + @app.delete("/openai/v1/files/{file_id}") + @app.delete("/openai/files/{file_id}") + @app.delete("/v1/files/{file_id}") + @app.delete("/files/{file_id}") + async def delete_file(file_id: str, _=Depends(validate_credentials)): + logger.info(f"Deleting file: {file_id}") + if file_id not in file_storage: + raise HTTPException(status_code=404, detail="File not found") + + del file_storage[file_id] + return {"id": file_id, "object": "file", "deleted": True} + + @app.get("/openai/v1/files") + @app.get("/openai/files") + @app.get("/v1/files") + @app.get("/files") + async def list_files( + purpose: Optional[str] = None, + limit: int = Query(10000, le=10000), + _=Depends(validate_credentials), + ): + logger.info(f"Listing files, purpose: {purpose}, limit: {limit}") + files = [] + for file_id, file_data in file_storage.items(): + if purpose is None or file_data.get("purpose") == purpose: + files.append( + FileObject( + id=file_id, + bytes=file_data["bytes"], + created_at=file_data["created_at"], + filename=file_data["filename"], + purpose=file_data["purpose"], + expires_at=file_data.get("expires_at"), + ).model_dump(), + ) + return {"object": "list", "data": files[:limit]} + + # Batches endpoints (OpenAI and Azure paths) + @app.post("/openai/v1/batches") + @app.post("/openai/batches") + @app.post("/v1/batches") + @app.post("/batches") + async def create_batch(request_data: dict, _=Depends(validate_credentials)): + input_file_id = request_data.get("input_file_id") + endpoint = request_data.get("endpoint", "/v1/chat/completions") + completion_window = request_data.get("completion_window", "24h") + metadata = request_data.get("metadata", {}) + output_expires_after = request_data.get("output_expires_after") + + logger.info( + f"Creating batch with input_file: {input_file_id}, endpoint: {endpoint}, output_expires_after: {output_expires_after}", + ) + + if not input_file_id or input_file_id not in file_storage: + raise HTTPException(status_code=400, detail="Input file not found") + + input_file = file_storage[input_file_id] + is_valid, error_code, _ = validate_batch_input(input_file["content"]) + if not is_valid: + raise HTTPException( + status_code=400, + detail={ + "error": { + "code": error_code, + "message": f"Validation failed: {error_code}", + }, + }, + ) + + batch_id = f"batch_{uuid.uuid4()}" + created_at = int(time.time()) + + if output_expires_after: + seconds = ( + output_expires_after.get("seconds", 0) + if isinstance(output_expires_after, dict) + else 0 + ) + expires_at = created_at + seconds + logger.info( + f"Using output_expires_after: {seconds}s, expires_at: {expires_at}", + ) + elif completion_window == "24h": + expires_at = created_at + (24 * 60 * 60) + else: + expires_at = created_at + (24 * 60 * 60) + + batch = BatchObject( + id=batch_id, + endpoint=endpoint, + input_file_id=input_file_id, + completion_window=completion_window, + status="validating", + created_at=created_at, + expires_at=expires_at, + request_counts={"total": 0, "completed": 0, "failed": 0}, + metadata=metadata, + ) + + batch_storage[batch_id] = batch + logger.info(f"Created batch {batch_id}") + + asyncio.create_task(process_batch(batch_id)) + + return batch.model_dump() + + @app.get("/openai/v1/batches/{batch_id}") + @app.get("/openai/batches/{batch_id}") + @app.get("/v1/batches/{batch_id}") + @app.get("/batches/{batch_id}") + async def get_batch(batch_id: str, _=Depends(validate_credentials)): + logger.info(f"Getting batch: {batch_id}") + if batch_id not in batch_storage: + raise HTTPException(status_code=404, detail="Batch not found") + + return batch_storage[batch_id].model_dump() + + @app.get("/openai/v1/batches") + @app.get("/openai/batches") + @app.get("/v1/batches") + @app.get("/batches") + async def list_batches( + after: Optional[str] = Query(None), + limit: int = Query(20, le=100), + _=Depends(validate_credentials), + ): + logger.info(f"Listing batches, after: {after}, limit: {limit}") + batches = list(batch_storage.values()) + batches.sort(key=lambda x: x.created_at, reverse=True) + + if after: + after_index = next((i for i, b in enumerate(batches) if b.id == after), -1) + if after_index >= 0: + batches = batches[after_index + 1 :] + + batches = batches[:limit] + + return BatchListResponse( + data=[batch.model_dump() for batch in batches], + first_id=batches[0].id if batches else None, + last_id=batches[-1].id if batches else None, + has_more=len(batches) == limit, + ).model_dump() + + @app.post("/openai/v1/batches/{batch_id}/cancel") + @app.post("/openai/batches/{batch_id}/cancel") + @app.post("/v1/batches/{batch_id}/cancel") + @app.post("/batches/{batch_id}/cancel") + async def cancel_batch(batch_id: str, _=Depends(validate_credentials)): + logger.info(f"Cancelling batch: {batch_id}") + if batch_id not in batch_storage: + raise HTTPException(status_code=404, detail="Batch not found") + + batch = batch_storage[batch_id] + if batch.status in ["completed", "failed", "cancelled", "expired"]: + raise HTTPException( + status_code=400, + detail=f"Cannot cancel batch in {batch.status} status", + ) + + batch.status = "cancelled" + batch.cancelled_at = int(time.time()) + logger.info(f"Batch {batch_id} cancelled") + + return batch.model_dump() + + # Debug endpoints + @app.get("/debug/batches") + async def debug_list_batches(): + return { + "batches": { + batch_id: batch.model_dump() + for batch_id, batch in batch_storage.items() + }, + "files": { + file_id: {k: v for k, v in data.items() if k != "content"} + for file_id, data in file_storage.items() + }, + } + + @app.post("/reset") + @app.post("/debug/clear") + async def reset_all(): + file_storage.clear() + batch_storage.clear() + batch_results.clear() + logger.info("All data cleared") + return {"message": "All data cleared"} + + @app.get("/debug/status") + async def debug_status(): + return { + "files_count": len(file_storage), + "batches_count": len(batch_storage), + "batch_statuses": {bid: b.status for bid, b in batch_storage.items()}, + } diff --git a/tests/batches_tests/local-litellm/mock-server/mock_chat.py b/tests/batches_tests/local-litellm/mock-server/mock_chat.py new file mode 100644 index 00000000000..c33523579a5 --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/mock_chat.py @@ -0,0 +1,124 @@ +import json +import time +import uuid +from datetime import datetime + +from fastapi import FastAPI, Request +from fastapi.responses import StreamingResponse + + +def get_request_details(request: Request, body: dict = None) -> str: + details = { + "method": request.method, + "url": str(request.url), + "path": request.url.path, + "headers": dict(request.headers), + "query_params": dict(request.query_params), + } + return json.dumps(details, indent=2) + + +def data_generator(response_details: str, model: str): + response_id = uuid.uuid4().hex + content = response_details + chunk_size = 50 + for i in range(0, len(content), chunk_size): + text_chunk = content[i : i + chunk_size] + chunk = { + "id": f"chatcmpl-{response_id}", + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model, + "choices": [{"index": 0, "delta": {"content": text_chunk}}], + } + yield f"data: {json.dumps(chunk)}\n\n" + final_chunk = { + "id": f"chatcmpl-{response_id}", + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model, + "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], + } + yield f"data: {json.dumps(final_chunk)}\n\n" + yield "data: [DONE]\n\n" + + +def setup_chat_routes(app: FastAPI): + @app.post("/chat/completions") + @app.post("/v1/chat/completions") + @app.post("/openai/deployments/{model:path}/chat/completions") + async def completion(request: Request): + data = await request.json() + model = data.get("model", "unknown") + request_details = get_request_details(request, data) + timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + response_details = f"Request:{request_details}, Canned Response:{timestamp}" + + if data.get("stream"): + return StreamingResponse( + content=data_generator(response_details, model), + media_type="text/event-stream", + ) + else: + response_id = uuid.uuid4().hex + response = { + "id": f"chatcmpl-{response_id}", + "object": "chat.completion", + "created": int(time.time()), + "model": model, + "system_fingerprint": "fp_mock_server", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": response_details, + }, + "logprobs": None, + "finish_reason": "stop", + }, + ], + "usage": { + "prompt_tokens": 9, + "completion_tokens": 12, + "total_tokens": 21, + }, + } + return response + + @app.post("/completions") + @app.post("/v1/completions") + async def text_completion(request: Request): + data = await request.json() + model = data.get("model", "unknown") + request_details = get_request_details(request, data) + timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + response_details = f"Request:{request_details}, Canned Response:{timestamp}" + + if data.get("stream"): + return StreamingResponse( + content=data_generator(response_details, model), + media_type="text/event-stream", + ) + else: + response = { + "id": f"cmpl-{uuid.uuid4().hex}", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": None, + "text": response_details, + }, + ], + "created": int(time.time()), + "model": model, + "object": "text_completion", + "system_fingerprint": None, + "usage": { + "completion_tokens": 16, + "prompt_tokens": 10, + "total_tokens": 26, + }, + } + return response diff --git a/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py b/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py new file mode 100644 index 00000000000..9f7aa46adcd --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py @@ -0,0 +1,26 @@ +from fastapi import FastAPI, Request + + +def setup_embeddings_routes(app: FastAPI): + @app.post("/embeddings") + @app.post("/v1/embeddings") + @app.post("/openai/deployments/{model:path}/embeddings") + async def embeddings(request: Request): + data = await request.json() + model = data.get("model", "unknown") + _small_embedding = [ + -0.006929283495992422, + -0.005336422007530928, + -4.547132266452536e-05, + -0.024047505110502243, + ] + big_embedding = _small_embedding * 100 + return { + "object": "list", + "data": [{"object": "embedding", "index": 0, "embedding": big_embedding}], + "model": model, + "usage": {"prompt_tokens": 5, "total_tokens": 5}, + } + + + diff --git a/tests/batches_tests/local-litellm/mock-server/mock_responses.py b/tests/batches_tests/local-litellm/mock-server/mock_responses.py new file mode 100644 index 00000000000..40e7ae34fbd --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/mock_responses.py @@ -0,0 +1,92 @@ +import json +import time +import uuid +from datetime import datetime + +from fastapi import FastAPI, Request + + +def get_request_details(request: Request, body: dict = None) -> str: + details = { + "method": request.method, + "url": str(request.url), + "path": request.url.path, + "headers": dict(request.headers), + "query_params": dict(request.query_params), + } + return json.dumps(details, indent=2) + + +def setup_responses_routes(app: FastAPI): + @app.post("/responses") + @app.post("/v1/responses") + @app.post("/openai/responses") + async def responses_api(request: Request): + data = await request.json() + model = data.get("model", "unknown") + request_details = get_request_details(request, data) + timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + response_details = f"Request:{request_details}, Canned Response:{timestamp}" + response_id = uuid.uuid4().hex + message_id = f"msg_{uuid.uuid4().hex[:34]}" + return { + "id": f"resp_{response_id}", + "created_at": int(time.time()), + "error": None, + "incomplete_details": None, + "instructions": None, + "metadata": {}, + "model": model, + "object": "response", + "output": [ + { + "id": message_id, + "content": [ + { + "annotations": [], + "text": response_details, + "type": "output_text", + "logprobs": [], + }, + ], + "role": "assistant", + "status": "completed", + "type": "message", + }, + ], + "parallel_tool_calls": True, + "temperature": data.get("temperature", 1.0), + "tool_choice": data.get("tool_choice", "auto"), + "tools": data.get("tools", []), + "top_p": data.get("top_p", 1.0), + "max_output_tokens": data.get("max_output_tokens"), + "previous_response_id": None, + "reasoning": {"effort": None, "summary": None}, + "status": "completed", + "text": {"format": {"type": "text"}, "verbosity": "medium"}, + "truncation": "disabled", + "usage": { + "input_tokens": 11, + "input_tokens_details": { + "audio_tokens": None, + "cached_tokens": 0, + "text_tokens": None, + }, + "output_tokens": 19, + "output_tokens_details": {"reasoning_tokens": 0, "text_tokens": None}, + "total_tokens": 30, + "cost": None, + }, + "user": None, + "store": True, + "background": False, + "content_filters": None, + "max_tool_calls": None, + "prompt_cache_key": None, + "safety_identifier": None, + "service_tier": "default", + "top_logprobs": 0, + } + + + diff --git a/tests/batches_tests/local-litellm/mock-server/pyproject.toml b/tests/batches_tests/local-litellm/mock-server/pyproject.toml new file mode 100644 index 00000000000..ecb462983cc --- /dev/null +++ b/tests/batches_tests/local-litellm/mock-server/pyproject.toml @@ -0,0 +1,20 @@ +[project] +name = "mock-server" +version = "0.1.0" +description = "Mock LLM server for testing LiteLLM" +requires-python = ">=3.11" +dependencies = [ + "fastapi", + "uvicorn", + "slowapi", + "python-dotenv>=0.2.0", + "python-multipart", + "pydantic", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["."] diff --git a/tests/batches_tests/local-litellm/mock-server/uv.lock b/tests/batches_tests/local-litellm/mock-server/uv.lock new file mode 100644 index 00000000000..9f00d16db95 --- /dev/null +++ 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File Deletion Fails for Batch Output Files + +### Broken Feature + +`DELETE /files/{file_id}` - Deleting batch output files fails with a Pydantic validation error. + +### Error Message + +``` +openai.InternalServerError: Error code: 500 - { + 'error': { + 'message': '1 validation error for LiteLLM_ManagedFileTable\nfile_object\n Input should be a valid dictionary or instance of OpenAIFileObject [type=model_type, input_value=None, input_type=NoneType]' + } +} +``` + +### Root Cause + +When LiteLLM stores batch output files in `LiteLLM_ManagedFileTable`, it sets `file_object=None`. However, the Pydantic model requires this field to be a valid `OpenAIFileObject`. + +### Code Change (`_types.py`) + +```python +# Before +class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): + file_object: OpenAIFileObject + +# After +class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): + file_object: Optional[OpenAIFileObject] = None # PATCHED +``` + +--- + +## 2. File Deletion Returns Wrong Response + +### Broken Feature + +`DELETE /files/{file_id}` - Even after fixing patch #1, the method returns `None` instead of the delete confirmation. + +### Error Message + +``` +Exception: LiteLLM Managed File object with id=... not found +``` + +### Root Cause + +`afile_delete` in `managed_files.py` calls `llm_router.afile_delete` (which deletes the file at the provider) but discards the response. + +### Code Change (`managed_files.py`) + +```python +# Before +async def afile_delete(self, file_id, ...): + for model_id, model_file_id in mapping.items(): + await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) + # Returns None + +# After +async def afile_delete(self, file_id, ...): + delete_response = None + for model_id, model_file_id in mapping.items(): + delete_response = await llm_router.afile_delete(...) # PATCHED: Capture response + if delete_response: + delete_response.id = file_id # PATCHED: Replace with unified ID + return delete_response +``` + +--- + +## 3. Batch Listing Fails with Duplicate Argument + +### Broken Feature + +`GET /batches?target_model_names=...` - Listing batches fails when using `target_model_names` query parameter. + +### Error Message + +``` +openai.InternalServerError: Error code: 500 - { + 'error': { + 'message': "alist_batches() got multiple values for keyword argument 'model'" + } +} +``` + +### Root Cause + +The code passes `model` explicitly AND includes it in `**data`: + +```python +model = target_model_names.split(",")[0] +response = await llm_router.alist_batches( + model=model, # Passed explicitly + **data, # Also contains 'model' key +) +``` + +### Code Change (`batches_endpoints.py`) + +```python +# Before +model = target_model_names.split(",")[0] +response = await llm_router.alist_batches(model=model, **data) + +# After +model = target_model_names.split(",")[0] +data.pop("model", None) # PATCHED: Remove duplicate +data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream +response = await llm_router.alist_batches(model=model, **data) +``` + +--- + +## 4. File Retrieve Returns None for Batch Output Files + +### Broken Feature + +`GET /files/{file_id}` - Retrieving batch output file metadata returns `None`. + +### Error Message + +``` +AttributeError: 'NoneType' object has no attribute 'id' +``` + +### Root Cause + +`afile_retrieve` returns `stored_file_object.file_object` which is `None` for batch output files. It should fetch from the provider. + +### Code Change (`managed_files.py` + `files_endpoints.py`) + +```python +# managed_files.py - After +async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router=None): + stored = await self.get_unified_file_id(file_id, ...) + if stored.file_object: + return stored.file_object + # PATCHED: Fetch from provider when file_object is None + for model_id, model_file_id in stored.model_mappings.items(): + response = await llm_router.afile_retrieve(model=model_id, file_id=model_file_id) + response.id = file_id + return response +``` + +```python +# files_endpoints.py - After +response = await managed_files_obj.afile_retrieve( + file_id=file_id, + litellm_parent_otel_span=user_api_key_dict.parent_otel_span, + llm_router=llm_router, # PATCHED: Pass router +) +``` + +--- + +## Known Issues (Not Bugs) + +### Azure Batch Creation Response Missing `endpoint` + +**Behavior:** Azure's batch creation response returns `endpoint=''` (empty string). + +**Expected:** When you call `batches.retrieve()` or `batches.list()`, Azure returns `endpoint='/v1/chat/completions'` correctly. + +**Workaround:** If you need the endpoint immediately after creation, retrieve the batch to get the correct value. + +### Azure Batch Listing Returns Raw IDs + +**Behavior:** `batches.list()` returns raw Azure batch IDs (e.g., `batch_abc123`) instead of LiteLLM unified IDs. + +**Root Cause:** LiteLLM routes `batches.list()` directly to Azure instead of querying its internal managed batches database. + +**Workaround:** Use `batches.retrieve(unified_batch_id)` instead of relying on list. + +### Config Fix: Azure Batch Listing 404 + +**Behavior:** `batches.list()` returns empty results because Azure returns 404. + +**Root Cause:** LiteLLM defaults to OpenAI handler instead of Azure handler for batch operations. + +**Fix (config):** Add `custom_llm_provider: azure` to your model's `litellm_params`: + +```yaml +litellm_params: + model: azure/gpt-5-batch + custom_llm_provider: azure # Required for Azure batch operations +``` + +--- + +## Patch Files + +| Patch File | Container Path | +|------------|----------------| +| `_types.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/_types.py` | +| `managed_files.py` | `/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py` | +| `batches_endpoints.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py` | +| `files_endpoints.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py` | + +--- + +## Usage + +### With Patches + +```bash +./start-patched.sh +``` + +### Without Patches + +```bash +./start-unpatched.sh +``` + +### Docker Compose Volumes + +```yaml +volumes: + - ./patches/_types.py:/usr/lib/python3.13/site-packages/litellm/proxy/_types.py + - ./patches/managed_files.py:/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py + - ./patches/batches_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py + - ./patches/files_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py +``` diff --git a/tests/batches_tests/test_managed_files_base.py b/tests/batches_tests/test_managed_files_base.py new file mode 100644 index 00000000000..9ea6d58355f --- /dev/null +++ b/tests/batches_tests/test_managed_files_base.py @@ -0,0 +1,220 @@ +"""Base class for managed files and batch API tests.""" + +import json +import os +import time +import uuid + +import httpx +import openai +import pytest +from tenacity import Retrying, stop_after_delay, wait_fixed + + +LOCAL_LITELLM_BASE_URL = "http://localhost:4000" +LOCAL_AZURE_BASE_URL = "http://localhost:8090" + +USE_LITELLM = os.environ.get("USE_LITELLM", "true").lower() == "true" +if USE_LITELLM: + base_url = LOCAL_LITELLM_BASE_URL + api_key = "sk-1234" +else: + base_url = LOCAL_AZURE_BASE_URL + api_key = "sk-1234" + +USE_MOCK_SERVER = os.environ.get("USE_MOCK_SERVER", "false").lower() == "true" +if USE_MOCK_SERVER: + model_name = "azure-fake-gpt-5-batch-2025-08-07" + MODEL_NAMES = [ + "azure-fake-gpt-5-batch-2025-08-07", + # "anthropic-fake-claude-sonnet-4-batch-2025-08-07", + # "vertex-fake-gemini-2.5-pro-batch-2025-08-07", + ] +else: + model_name = "gpt-5-batch-2025-08-07" + MODEL_NAMES = [ + "gpt-5-batch-2025-08-07", + # "claude-sonnet-4-batch-2025-08-07", + # "gemini-2.5-pro-batch-2025-08-07", + ] + + +def _extract_model_id(model_name: str) -> str: + if "gpt" in model_name: + return "gpt" + elif "claude" in model_name or "anthropic" in model_name: + return "anthropic" + elif "gemini" in model_name or "vertex" in model_name: + return "gemini" + return model_name.split("-")[0] + + +MODEL_IDS = [_extract_model_id(m) for m in MODEL_NAMES] + +MIN_EXPIRY_SECONDS = 259200 + + +class ManagedFilesBase: + """Base class with shared helpers for managed files and batch tests.""" + + base_url = base_url + api_key = api_key + + @pytest.fixture(autouse=True) + def setup_test(self): + print(f"Base URL: {self.base_url}, Model: {model_name}\n") + self.reset_mock_server() + + @staticmethod + def generate_request_id(): + return f"req-{uuid.uuid4().hex[:8]}" + + def create_openai_client(self, api_key: str) -> openai.OpenAI: + return openai.OpenAI( + base_url=self.base_url, + api_key=api_key, + http_client=httpx.Client(verify=False), + ) + + def create_batch_request_file_on_disk(self, tmpdir, model: str): + request_id = self.generate_request_id() + batch_request = { + "custom_id": request_id, + "method": "POST", + "url": "/v1/chat/completions", + "body": { + "model": model, + "messages": [ + {"role": "user", "content": "What is 2+2?"}, + ], + }, + } + + request_file = os.path.join(tmpdir, f"request-{request_id}.jsonl") + with open(request_file, "w") as f: + f.write(json.dumps(batch_request)) + + return request_file + + def create_batch_input_file( + self, + client: openai.OpenAI, + request_file: str, + expiry_seconds: int = MIN_EXPIRY_SECONDS, + ): + batch_input_file = client.files.create( + file=open(request_file, "rb"), + purpose="batch", + extra_body={ + "target_model_names": model_name, + "expires_after": { + "seconds": expiry_seconds, + "anchor": "created_at", + }, + }, + ) + return batch_input_file + + def create_batch( + self, + client: openai.OpenAI, + input_file_id: str, + expiry_seconds: int = MIN_EXPIRY_SECONDS, + ): + batch = client.batches.create( + input_file_id=input_file_id, + endpoint="/v1/chat/completions", + completion_window="24h", + extra_body={ + "output_expires_after": { + "seconds": expiry_seconds, + "anchor": "created_at", + }, + }, + ) + return batch + + def wait_for_batch_state( + self, + client: openai.OpenAI, + batch_id: str, + expected_status: str, + max_seconds: int = 60, + wait_seconds: int = 5, + ): + for attempt in Retrying( + stop=stop_after_delay(max_seconds), + wait=wait_fixed(wait_seconds), + ): + with attempt: + batch_response = client.batches.retrieve(batch_id=batch_id) + print( + f"[{time.strftime('%H:%M:%S')}] Batch status: {batch_response.status}, expected: {expected_status}", + ) + if batch_response.status == expected_status: + return batch_response + if batch_response.status in ["failed", "expired", "cancelled"]: + raise Exception( + f"Batch failed with status: {batch_response.status}", + ) + raise Exception(f"Batch not in {expected_status} state yet") + return None + + def wait_for_batch_completed( + self, + client: openai.OpenAI, + batch_id: str, + max_seconds: int = 120, + wait_seconds: int = 5, + ): + return self.wait_for_batch_state( + client, + batch_id, + "completed", + max_seconds, + wait_seconds, + ) + + def shorten_id(self, id_str: str) -> str: + if id_str is None: + return "None" + if len(id_str) <= 20: + return id_str + return id_str[:8] + "..." + id_str[-8:] + + def reset_mock_server(self): + if not USE_MOCK_SERVER: + return + print("Resetting mock server state...") + reset_response = httpx.post(f"{LOCAL_AZURE_BASE_URL}/reset") + assert reset_response.status_code == 200, f"Reset failed: {reset_response.text}" + + def print_file_metadata(self, file_obj, label="File"): + print(f"{label} metadata:") + print(f"\tid={self.shorten_id(file_obj.id)}") + print(f"\tobject={file_obj.object}") + print(f"\tbytes={file_obj.bytes}") + print(f"\tfilename={file_obj.filename}") + print(f"\tpurpose={file_obj.purpose}") + print(f"\tstatus={file_obj.status}") + print(f"\tcreated_at={file_obj.created_at}") + print(f"\texpires_at={file_obj.expires_at}") + if file_obj.status_details: + print(f"\tstatus_details={file_obj.status_details}") + + def print_batch_metadata(self, batch): + print("Batch metadata:") + print(f"\tid={self.shorten_id(batch.id)}") + print(f"\tstatus={batch.status}") + print(f"\tendpoint={batch.endpoint}") + print(f"\tcompletion_window={batch.completion_window}") + print(f"\tinput_file_id={self.shorten_id(batch.input_file_id)}") + print(f"\tcreated_at={batch.created_at}") + print(f"\texpires_at={batch.expires_at}") + print(f"\tin_progress_at={batch.in_progress_at}") + print(f"\tcompleted_at={batch.completed_at}") + print(f"\toutput_file_id={self.shorten_id(batch.output_file_id)}") + print(f"\trequest_counts={batch.request_counts}") + + + diff --git a/tests/batches_tests/test_managed_files_endtoend.py b/tests/batches_tests/test_managed_files_endtoend.py new file mode 100644 index 00000000000..828060e9cd5 --- /dev/null +++ b/tests/batches_tests/test_managed_files_endtoend.py @@ -0,0 +1,204 @@ +import warnings + +import openai +import pytest +from tenacity import RetryError, Retrying, stop_after_delay, wait_fixed + +from test_managed_files_base import ( + MODEL_IDS, + MODEL_NAMES, + ManagedFilesBase, + MIN_EXPIRY_SECONDS, +) + + +class TestManagedFilesAPI(ManagedFilesBase): + """Test cases for managed files and batch API. + + Configuration via environment variables: + USE_LITELLM=true - Run against LiteLLM proxy + USE_LITELLM=false - Run against mock server directly (default) + """ + + @classmethod + def setup_class(cls): + cls.openai_client = cls.create_openai_client(cls, cls.api_key) + + def wait_for_batch_list(self, model_name, max_seconds=90, wait_seconds=10): + for attempt in Retrying( + stop=stop_after_delay(max_seconds), + wait=wait_fixed(wait_seconds), + ): + with attempt: + batches_list = self.openai_client.batches.list( + limit=10, + extra_query={"target_model_names": model_name}, + ) + print( + f"Batches in list: {len(batches_list.data)}", + ) + if len(batches_list.data) == 0: + raise Exception("No batches found in list yet") + return batches_list + return None + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_e2e_managed_batch(self, tmp_path, model_name): + print( + f"\n\nStarting test with base_url={self.base_url} and model_name={model_name}\n", + ) + + self.reset_mock_server() + + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + + print("Creating batch input file...") + batch_input_file = self.create_batch_input_file( + self.openai_client, + request_file, + MIN_EXPIRY_SECONDS, + ) + print(f"Created batch input file: {self.shorten_id(batch_input_file.id)}\n") + + print( + f"Retrieving batch input file metadata for file id: {self.shorten_id(batch_input_file.id)}", + ) + input_file_metadata = self.openai_client.files.retrieve(batch_input_file.id) + assert input_file_metadata.id == batch_input_file.id, "File ID mismatch" + assert input_file_metadata.object == "file", "object should be 'file'" + assert input_file_metadata.bytes > 0, "bytes not set" + assert input_file_metadata.filename == "modified_file.jsonl", ( + "filename mismatch" + ) + assert input_file_metadata.purpose == "batch", "purpose mismatch" + assert input_file_metadata.status in ["uploaded", "processed", "error"], ( + "invalid status" + ) + assert input_file_metadata.created_at > 0, "created_at not set" + if not input_file_metadata.expires_at: + warnings.warn("batch input file expires_at not set") + self.print_file_metadata(input_file_metadata, "Input file") + + print("\nCreating batch...") + batch = self.create_batch( + self.openai_client, + batch_input_file.id, + MIN_EXPIRY_SECONDS, + ) + print(f"Created batch: {self.shorten_id(batch.id)}") + assert batch.id, "No batch ID returned" + assert batch.input_file_id == batch_input_file.id, "File ID mismatch" + assert batch.status in [ + "validating", + "in_progress", + "finalizing", + "completed", + ], "Status mismatch" + if not batch.expires_at: + warnings.warn("batch expires_at not set") + else: + assert batch.expires_at > 0, "batch expires_at not set" + + if not batch.endpoint: + warnings.warn( + "batch.endpoint empty in creation response - Azure API quirk, not a bug", + ) + else: + assert batch.endpoint == "/v1/chat/completions", "endpoint mismatch" + assert batch.completion_window == "24h", "completion_window mismatch" + assert batch.created_at > 0, "created_at not set" + + self.print_batch_metadata(batch) + + print("\nListing batches...") + try: + batches_list = self.wait_for_batch_list( + model_name, + max_seconds=30, + wait_seconds=5, + ) + batches = batches_list.data if batches_list else [] + batch_ids = [b.id for b in batches] + if batch.id not in batch_ids: + warnings.warn( + f"Batch {batch.id} not found in list. batches.list returns raw IDs and not the encoded IDs. raw IDs: {batch_ids}", + ) + except RetryError: + warnings.warn( + "batches.list() returned empty list after retries - known LiteLLM issue with managed batches", + ) + except openai.APIError as e: + pytest.fail(f"batches.list() failed: {e}") + + print( + f"\nWaiting for batch {self.shorten_id(batch.id)} to reach completed state...", + ) + try: + batch_response = self.wait_for_batch_state( + self.openai_client, + batch.id, + "completed", + max_seconds=30 * 60, + wait_seconds=5, + ) + except RetryError: + raise TimeoutError("Timed out waiting for batch to be in state: completed") + + print("\nRetrieving batch output file metadata...") + output_file_metadata = self.openai_client.files.retrieve( + batch_response.output_file_id, + ) + assert output_file_metadata.id == batch_response.output_file_id, ( + "Output file ID mismatch" + ) + assert output_file_metadata.object == "file", "object should be 'file'" + assert output_file_metadata.bytes > 0, "bytes not set" + assert output_file_metadata.filename, "filename not set" + assert output_file_metadata.purpose in ["batch_output", "batch"], ( + "purpose should be batch_output" + ) + assert output_file_metadata.created_at > 0, "created_at not set" + self.print_file_metadata(output_file_metadata, "Output file") + + print("\nFetching batch output file content...") + batch_file_content = self.openai_client.files.content( + batch_response.output_file_id, + ) + assert batch_file_content.text, "No batch file content returned" + assert len(batch_file_content.text) > 0, "Batch file content is empty" + print(f"Output file content ({len(batch_file_content.text)} bytes):") + for line in batch_file_content.text.strip().split("\n")[:3]: + print(f"\t{line}") + + print(f"\nDeleting input file: {self.shorten_id(batch_input_file.id)}") + try: + self.openai_client.files.delete(batch_input_file.id) + except openai.APIError as e: + pytest.fail(f"files.delete() failed: {e}") + + print( + f"\nDeleting output file: {self.shorten_id(batch_response.output_file_id)}", + ) + try: + self.openai_client.files.delete(batch_response.output_file_id) + except openai.APIError as e: + pytest.fail(f"files.delete() failed: {e}") + + print("\nVerifying input file is deleted...") + try: + self.openai_client.files.content(batch_input_file.id) + assert False, f"Input file {batch_input_file.id} exists after deletion" + except (openai.NotFoundError, openai.PermissionDeniedError): + print("Input file correctly not accessible after deletion") + + print("\nVerifying output file is deleted...") + try: + self.openai_client.files.content(batch_response.output_file_id) + assert False, ( + f"Output file {batch_response.output_file_id} exists after deletion" + ) + except (openai.NotFoundError, openai.PermissionDeniedError): + print("Output file correctly not accessible after deletion") + + + diff --git a/tests/batches_tests/test_managed_files_permissions.py b/tests/batches_tests/test_managed_files_permissions.py new file mode 100644 index 00000000000..c4b9e8828f4 --- /dev/null +++ b/tests/batches_tests/test_managed_files_permissions.py @@ -0,0 +1,436 @@ +""" +Test cross-user batch access permissions. + +This test verifies that a batch and related files created by one API key +cannot be accessed, modified, or cancelled by a different API key. + +Reference: https://github.com/BerriAI/litellm/pull/17401/files +""" + +import time + +import httpx +import openai +import pytest + +from test_managed_files_base import ( + ManagedFilesBase, + MODEL_NAMES, + MODEL_IDS, +) + + +BATCH_ROUTES = [ + "/v1/files", + "/files", + "/v1/files/*", + "/files/*", + "/v1/batches", + "/batches", + "/v1/batches/*", + "/batches/*", +] + + +class TestManagedFilesPermissions(ManagedFilesBase): + """Test cases for cross-user batch access permissions. + + Verifies that: + - User A can create and access their own batches and files + - User B cannot access, retrieve, cancel, or delete User A's batches/files + """ + + master_api_key = "sk-1234" + + @classmethod + def setup_class(cls): + cls.admin_client = httpx.Client(base_url=cls.base_url, verify=False) + + @classmethod + def teardown_class(cls): + cls.admin_client.close() + + def user_suffix(self) -> str: + return f"{time.strftime('%Y%m%d%H%M%S')}{int(time.time() * 1000) % 1000:03d}" + + def create_user_and_key(self, user_suffix: str) -> tuple[str, str]: + user_email = f"test-user-{user_suffix}-{self.user_suffix()}@test.com" + + user_response = self.admin_client.post( + "/user/new", + json={ + "user_email": user_email, + "user_alias": user_email, + "user_role": "internal_user", + "auto_create_key": "false", + }, + headers={ + "Authorization": f"Bearer {self.master_api_key}", + "Content-Type": "application/json", + }, + timeout=30, + ) + assert user_response.status_code == 200, ( + f"Failed to create user: {user_response.status_code} - {user_response.text}" + ) + user_data = user_response.json() + user_id = user_data.get("user_id") + + key_response = self.admin_client.post( + "/key/generate", + json={ + "user_id": user_id, + "key_alias": user_email, + "allowed_routes": BATCH_ROUTES, + }, + headers={ + "Authorization": f"Bearer {self.master_api_key}", + "Content-Type": "application/json", + }, + timeout=30, + ) + assert key_response.status_code == 200, ( + f"Failed to create key: {key_response.status_code} - {key_response.text}" + ) + key_data = key_response.json() + api_key = key_data.get("key") + + print(f"Created user {user_email} with key {key_data.get('key_alias')}") + return user_id, api_key + + def create_user_key_and_client( + self, + user_suffix: str, + ) -> tuple[str, str, openai.OpenAI]: + user_id, api_key = self.create_user_and_key(user_suffix) + return user_id, api_key, self.create_openai_client(api_key) + + def create_key_and_client(self, user_id: str, key_suffix: str) -> str: + key_alias = f"additional-key-{key_suffix}-{self.user_suffix()}" + key_response = self.admin_client.post( + "/key/generate", + json={ + "user_id": user_id, + "key_alias": key_alias, + "allowed_routes": BATCH_ROUTES, + }, + headers={ + "Authorization": f"Bearer {self.master_api_key}", + "Content-Type": "application/json", + }, + timeout=30, + ) + assert key_response.status_code == 200, ( + f"Failed to create additional key: {key_response.status_code} - {key_response.text}" + ) + api_key = key_response.json().get("key") + print(f"Created additional key {api_key[:20]}... for user {user_id}") + return api_key, self.create_openai_client(api_key) + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_retrieve_user_a_batch(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # User A retrieves their own batch + batch_a = client_A.batches.retrieve(batch_id=batch.id) + assert batch_a.id == batch.id, ( + "User A should be able to retrieve their own batch" + ) + + # User B cannot retrieve User A's batch + try: + client_B.batches.retrieve(batch_id=batch.id) + pytest.fail("User B should NOT be able to retrieve User A's batch") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_cancel_user_a_batch(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # User B cannot cancel User A's batch + try: + client_B.batches.cancel(batch_id=batch.id) + pytest.fail("User B should NOT be able to cancel User A's batch") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_retrieve_user_a_batch_input_file(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + + # User A retrieves their own file + file_a = client_A.files.retrieve(file_id=batch_input_file.id) + assert file_a.id == batch_input_file.id, ( + "User A should be able to retrieve their own file" + ) + + # User B cannot retrieve User A's file + try: + client_B.files.retrieve(file_id=batch_input_file.id) + pytest.fail("User B should NOT be able to retrieve User A's file") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_download_user_a_batch_input_file_content( + self, + tmp_path, + model_name, + ): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + + # User A can download their own file content + content_a = client_A.files.content(file_id=batch_input_file.id) + assert content_a.text, ( + "User A should be able to download their own file content" + ) + + # User B cannot download User A's file content + try: + client_B.files.content(file_id=batch_input_file.id) + pytest.fail("User B should NOT be able to download User A's file content") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_delete_user_a_batch_input_file(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + + # User B cannot delete User A's file + try: + client_B.files.delete(file_id=batch_input_file.id) + pytest.fail("User B should NOT be able to delete User A's file") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + # User A can still retrieve their own file + file_a = client_A.files.retrieve(file_id=batch_input_file.id) + assert file_a.id == batch_input_file.id, "File should still exist" + + # User A can delete their own file + try: + client_A.files.delete(file_id=batch_input_file.id) + except openai.APIError as e: + pytest.fail(f"User A should be able to delete their own file: {e}") + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_retrieve_user_a_batch_output_file( + self, + tmp_path, + model_name, + ): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # Wait for batch to complete + completed_batch = self.wait_for_batch_completed(client_A, batch.id) + assert completed_batch.output_file_id, "Batch should have an output file" + + # User A retrieves their own output file + file_a = client_A.files.retrieve(file_id=completed_batch.output_file_id) + assert file_a.id == completed_batch.output_file_id, ( + "User A should be able to retrieve their own output file" + ) + + # User B cannot retrieve User A's output file + try: + client_B.files.retrieve(file_id=completed_batch.output_file_id) + pytest.fail("User B should NOT be able to retrieve User A's output file") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_download_user_a_batch_output_file_content( + self, + tmp_path, + model_name, + ): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # Wait for batch to complete + completed_batch = self.wait_for_batch_completed(client_A, batch.id) + assert completed_batch.output_file_id, "Batch should have an output file" + + # User A can download their own output file content + content_a = client_A.files.content(file_id=completed_batch.output_file_id) + assert content_a.text, ( + "User A should be able to download their own output file content" + ) + + # User B cannot download User A's output file content + try: + client_B.files.content(file_id=completed_batch.output_file_id) + pytest.fail( + "User B should NOT be able to download User A's output file content", + ) + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_delete_user_a_batch_output_file(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # Wait for batch to complete + completed_batch = self.wait_for_batch_completed(client_A, batch.id) + assert completed_batch.output_file_id, "Batch should have an output file" + + # User B cannot delete User A's output file + try: + client_B.files.delete(file_id=completed_batch.output_file_id) + pytest.fail("User B should NOT be able to delete User A's output file") + except openai.PermissionDeniedError as e: + assert e.status_code == 403 + + # User A can still retrieve their own output file + file_a = client_A.files.retrieve(file_id=completed_batch.output_file_id) + assert file_a.id == completed_batch.output_file_id, ( + "Output file should still exist" + ) + + # User A can delete their own output file + try: + client_A.files.delete(file_id=completed_batch.output_file_id) + except openai.APIError as e: + pytest.fail(f"User A should be able to delete their own output file: {e}") + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_b_cannot_list_user_a_batches(self, tmp_path, model_name): + user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") + user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") + + # User A creates a batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_A, request_file) + batch = self.create_batch(client_A, batch_input_file.id) + + # User A can see their own batch in the list + batches_a = client_A.batches.list( + limit=10, + extra_query={"target_model_names": model_name}, + ) + batch_ids_a = [b.id for b in batches_a.data] + assert batch.id in batch_ids_a, "User A should see their own batch in the list" + + # User B's batch list should NOT contain User A's batch + batches_b = client_B.batches.list( + limit=10, + extra_query={"target_model_names": model_name}, + ) + batch_ids_b = [b.id for b in batches_b.data] + assert batch.id not in batch_ids_b, ( + "User B should NOT see User A's batch in the list" + ) + + @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) + def test_user_api_keys_are_interchangeable(self, tmp_path, model_name): + # Create user with 3 keys + user_id, key1, client_Key1 = self.create_user_key_and_client("a") + key2, client_Key2 = self.create_key_and_client(user_id, "a2") + key3, client_Key3 = self.create_key_and_client(user_id, "a3") + + # Key1: Create batch input file and batch + request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file = self.create_batch_input_file(client_Key1, request_file) + batch = self.create_batch(client_Key1, batch_input_file.id) + + # Key1: Retrieve batch + batch_retrieved = client_Key1.batches.retrieve(batch_id=batch.id) + assert batch_retrieved.id == batch.id, "Key1 should retrieve its own batch" + + # Key2: Wait for batch completion and retrieve output + completed_batch = self.wait_for_batch_completed(client_Key2, batch.id) + assert completed_batch.output_file_id, "Batch should have an output file" + + # Key2: Retrieve output file metadata + output_file = client_Key2.files.retrieve(file_id=completed_batch.output_file_id) + assert output_file.id == completed_batch.output_file_id, ( + "Key2 should retrieve output file" + ) + + # Key2: Download output file content + output_content = client_Key2.files.content( + file_id=completed_batch.output_file_id, + ) + assert output_content.text, "Key2 should download output file content" + + # Key3: List batches and verify batch is visible + batches = client_Key3.batches.list( + limit=10, + extra_query={"target_model_names": model_name}, + ) + batch_ids = [b.id for b in batches.data] + assert batch.id in batch_ids, "Key3 should see batch in list" + + # Key3: Delete input file + try: + client_Key3.files.delete(file_id=batch_input_file.id) + except openai.APIError as e: + pytest.fail(f"Key3 should delete input file: {e}") + + # Key3: Delete output file + try: + client_Key3.files.delete(file_id=completed_batch.output_file_id) + except openai.APIError as e: + pytest.fail(f"Key3 should delete output file: {e}") + + # Key1: Create another batch for cancellation test + request_file2 = self.create_batch_request_file_on_disk(tmp_path, model_name) + batch_input_file2 = self.create_batch_input_file(client_Key1, request_file2) + batch2 = self.create_batch(client_Key1, batch_input_file2.id) + + # Key3: Cancel the batch created by Key1 + try: + cancelled_batch = client_Key3.batches.cancel(batch_id=batch2.id) + assert cancelled_batch.id == batch2.id, ( + "Key3 should cancel batch created by Key1" + ) + except openai.BadRequestError: + pass # Batch may have already completed + + + From 73083a1f5b400f1d9724a84be1e6dbeaa2d56127 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Tue, 23 Dec 2025 11:54:46 -0500 Subject: [PATCH 03/46] Add end to end integration tests for batches --- BATCH_FIXES_README.md | 174 +++--------------- .../proxy/hooks/managed_files.py | 55 +++--- litellm/proxy/batches_endpoints/endpoints.py | 1 - 3 files changed, 48 insertions(+), 182 deletions(-) diff --git a/BATCH_FIXES_README.md b/BATCH_FIXES_README.md index 205ab2d29a1..e04f18b900f 100644 --- a/BATCH_FIXES_README.md +++ b/BATCH_FIXES_README.md @@ -6,9 +6,8 @@ This document describes bugs found in LiteLLM's managed batch/files functionalit 1. [Bug 1: File Deletion Fails for Batch Output Files](#bug-1-file-deletion-fails-for-batch-output-files) 2. [Bug 2: File Deletion Returns Wrong Response](#bug-2-file-deletion-returns-wrong-response) -3. [Bug 3: Batch Listing Fails with Duplicate Argument](#bug-3-batch-listing-fails-with-duplicate-argument) -4. [Bug 4: File Retrieve Returns None for Batch Output Files](#bug-4-file-retrieve-returns-none-for-batch-output-files) -5. [Mock Server: Azure-like Credential Validation](#mock-server-azure-like-credential-validation) +3. [Bug 3: File Retrieve Returns None for Batch Output Files](#bug-3-file-retrieve-returns-none-for-batch-output-files) +4. [Known Limitation: Error Files Not Retrievable](#known-limitation-error-files-not-retrievable) 6. [Test Setup Instructions](#test-setup-instructions) --- @@ -30,20 +29,6 @@ openai.InternalServerError: Error code: 500 - { **Root Cause:** When LiteLLM stores batch output files in `LiteLLM_ManagedFileTable`, it sets `file_object=None`. However, the Pydantic model requires this field to be a valid `OpenAIFileObject`. -### Patch - -**File:** `litellm/proxy/_types.py`, line ~3759 - -```python -# Before -class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): - file_object: OpenAIFileObject - -# After -class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): - file_object: Optional[OpenAIFileObject] = None # PATCHED -``` - --- ## Bug 2: File Deletion Returns Wrong Response @@ -59,78 +44,9 @@ Exception: LiteLLM Managed File object with id=... not found **Root Cause:** `afile_delete` in `managed_files.py` calls `llm_router.afile_delete()` (which deletes the file at the provider) but discards the response. -### Patch - -**File:** `enterprise/litellm_enterprise/proxy/hooks/managed_files.py`, line ~879 - -```python -# Before -async def afile_delete(self, file_id, ...): - for model_id, model_file_id in mapping.items(): - await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) - # Returns None when stored_file_object is None - -# After -async def afile_delete(self, file_id, ...): - delete_response = None # PATCHED: Capture response - for model_id, model_file_id in mapping.items(): - delete_response = await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) - - stored_file_object = await self.delete_unified_file_id(file_id, ...) - if stored_file_object: - return stored_file_object - elif delete_response: # PATCHED: Return provider response - delete_response.id = file_id # Replace with unified ID - return delete_response - else: - raise Exception(...) -``` - --- -## Bug 3: Batch Listing Fails with Duplicate Argument - -### Description - -**Broken Feature:** `GET /batches?target_model_names=...` - Listing batches fails when using `target_model_names` query parameter. - -**Error Message:** -``` -openai.InternalServerError: Error code: 500 - { - 'error': { - 'message': "alist_batches() got multiple values for keyword argument 'model'" - } -} -``` - -**Root Cause:** The code passes `model` explicitly AND includes it in `**data`: -```python -model = target_model_names.split(",")[0] -response = await llm_router.alist_batches( - model=model, # Passed explicitly - **data, # Also contains 'model' and 'target_model_names' keys -) -``` - -### Patch - -**File:** `litellm/proxy/batches_endpoints/endpoints.py`, line ~576-577 - -```python -# Before -model = target_model_names.split(",")[0] -response = await llm_router.alist_batches(model=model, **data) - -# After -model = target_model_names.split(",")[0] -data.pop("model", None) # PATCHED: Remove duplicate -data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream -response = await llm_router.alist_batches(model=model, **data) -``` - ---- - -## Bug 4: File Retrieve Returns None for Batch Output Files +## Bug 3: File Retrieve Returns None for Batch Output Files ### Description @@ -143,71 +59,29 @@ AttributeError: 'NoneType' object has no attribute 'id' **Root Cause:** `afile_retrieve` returns `stored_file_object.file_object` which is `None` for batch output files. It should fetch the file metadata from the provider instead. -### Patch (Part A) - -**File:** `enterprise/litellm_enterprise/proxy/hooks/managed_files.py`, line ~839-868 - -Add `import litellm` at the top of the file, then modify `afile_retrieve`: - -```python -# Before -async def afile_retrieve(self, file_id, litellm_parent_otel_span): - stored = await self.get_unified_file_id(file_id, ...) - return stored.file_object # Returns None for batch output files! - -# After -import litellm # Added at top of file - -async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router=None): # PATCHED: Added llm_router - stored = await self.get_unified_file_id(file_id, ...) - if stored: - if stored.file_object: - return stored.file_object - # PATCHED: Fetch from provider when file_object is None - elif stored.model_mappings and llm_router: - for model_id, model_file_id in stored.model_mappings.items(): - deployment = llm_router.get_deployment(model_id=model_id) - if deployment: - credentials = llm_router.get_deployment_credentials(model_id=model_id) or {} - # Extract custom_llm_provider - afile_retrieve needs it as explicit param - custom_llm_provider = credentials.pop("custom_llm_provider", None) - if not custom_llm_provider: - # Infer from model name (e.g., "azure/gpt-5" -> "azure") - model_name = deployment.litellm_params.model or "" - if "/" in model_name: - custom_llm_provider = model_name.split("/")[0] - else: - custom_llm_provider = "openai" - response = await litellm.afile_retrieve( - file_id=model_file_id, - custom_llm_provider=custom_llm_provider, # Explicit param for Azure - **credentials - ) - response.id = file_id # Replace with unified ID - return response -``` - -### Patch (Part B) - -**File:** `litellm/proxy/openai_files_endpoints/files_endpoints.py`, line ~888 - -```python -# Before -response = await managed_files_obj.afile_retrieve( - file_id=file_id, - litellm_parent_otel_span=user_api_key_dict.parent_otel_span, -) - -# After -response = await managed_files_obj.afile_retrieve( - file_id=file_id, - litellm_parent_otel_span=user_api_key_dict.parent_otel_span, - llm_router=llm_router, # PATCHED: Pass router to fetch from provider -) -``` - --- +## Known Limitation: Error Files Not Retrievable + +### Description + +When a batch fails, the provider returns an `error_file_id` containing details about failed requests. Currently, **error files are NOT retrievable** through the managed files API (`GET /files/{file_id}`). + +### Root Cause + +Only `output_file_id` is stored in `LiteLLM_ManagedFileTable` when a batch completes. The `error_file_id` is encoded in the batch response but never stored in the managed files table. + +**In `async_post_call_success_hook`:** +```python +# Only output_file_id is handled: +if response.output_file_id and model_id: + await self.store_unified_file_id( + file_id=response.output_file_id, + ... + ) +# error_file_id is NOT stored +``` + ## Test Setup Instructions ### Prerequisites diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index 1afaee30c74..37eef176927 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -842,38 +842,31 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): stored_file_object = await self.get_unified_file_id( file_id, litellm_parent_otel_span ) - if stored_file_object: - # PATCHED: If file_object is None (batch output files), fetch from provider - if stored_file_object.file_object: - return stored_file_object.file_object - elif stored_file_object.model_mappings and llm_router: - for model_id, model_file_id in stored_file_object.model_mappings.items(): - # PATCHED: Get deployment info and credentials from router - deployment = llm_router.get_deployment(model_id=model_id) - if deployment: - credentials = llm_router.get_deployment_credentials(model_id=model_id) or {} - # Extract custom_llm_provider - afile_retrieve needs it as explicit param - custom_llm_provider = credentials.pop("custom_llm_provider", None) - if not custom_llm_provider: - # Infer from model name (e.g., "azure/gpt-5" -> "azure") - model_name = deployment.litellm_params.model or "" - if "/" in model_name: - custom_llm_provider = model_name.split("/")[0] - else: - custom_llm_provider = "openai" - response = await litellm.afile_retrieve( - file_id=model_file_id, - custom_llm_provider=custom_llm_provider, - **credentials - ) - response.id = file_id # Replace with unified ID - return response - else: - raise Exception(f"No deployment found for model_id={model_id}") - else: - raise Exception(f"LiteLLM Managed File object with id={file_id} has no file_object, or no model_mappings/llm_router to fetch from provider") - else: + + # Case 1 : This is not a managed file + if not stored_file_object: 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 + if stored_file_object and stored_file_object.file_object: + 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) + # So we fetch the file object from the provider. We deliberately do not store the result to avoid interfering with batch cost tracking code. + if not llm_router: + raise Exception( + f"LiteLLM Managed File object with id={file_id} has no file_object " + f"and llm_router is required to fetch from provider" + ) + + try: + model_id, model_file_id = next(iter(stored_file_object.model_mappings.items())) + credentials = llm_router.get_deployment_credentials_with_provider(model_id) or {} + response = await litellm.afile_retrieve(file_id=model_file_id, **credentials) + response.id = file_id # Replace with unified ID + return response + except Exception as e: + raise Exception(f"Failed to retrieve file {file_id} from provider: {str(e)}") from e async def afile_list( self, diff --git a/litellm/proxy/batches_endpoints/endpoints.py b/litellm/proxy/batches_endpoints/endpoints.py index dd68a54f694..086105042e8 100644 --- a/litellm/proxy/batches_endpoints/endpoints.py +++ b/litellm/proxy/batches_endpoints/endpoints.py @@ -574,7 +574,6 @@ async def list_batches( raise ValueError("target_model_names is required for this routing scenario") model = target_model_names.split(",")[0] data.pop("model", None) - data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream response = await llm_router.alist_batches( model=model, after=after, From 479e40672ecd745e493065020c76ac5aa31819a6 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Tue, 23 Dec 2025 12:55:09 -0500 Subject: [PATCH 04/46] Add end to end integration tests for batches --- .../proxy/hooks/managed_files.py | 2 - litellm/proxy/_types.py | 2 +- .../openai_files_endpoints/files_endpoints.py | 2 +- .../proxy/hooks/test_managed_files.py | 244 ++++++++++++++++++ 4 files changed, 246 insertions(+), 4 deletions(-) diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index 37eef176927..445d2b242b4 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -890,7 +890,6 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): [file_id], litellm_parent_otel_span ) - # PATCHED: Capture delete response from provider delete_response = None specific_model_file_id_mapping = model_file_id_mapping.get(file_id) if specific_model_file_id_mapping: @@ -903,7 +902,6 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): if stored_file_object: return stored_file_object - # PATCHED: Return provider response with unified ID when stored_file_object is None elif delete_response: delete_response.id = file_id return delete_response diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 9767e07bbc8..3865a4c65bc 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -3756,7 +3756,7 @@ class SpendUpdateQueueItem(TypedDict, total=False): class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): unified_file_id: str - file_object: Optional[OpenAIFileObject] = None # PATCHED: Allow None for batch output files + file_object: Optional[OpenAIFileObject] = None model_mappings: Dict[str, str] flat_model_file_ids: List[str] created_by: Optional[str] diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index 586f7840835..7e3f5820814 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -885,7 +885,7 @@ async def get_file( response = await managed_files_obj.afile_retrieve( file_id=file_id, litellm_parent_otel_span=user_api_key_dict.parent_otel_span, - llm_router=llm_router, # PATCHED: Pass router to fetch from provider if file_object is None + llm_router=llm_router, ) else: response = await litellm.afile_retrieve( diff --git a/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py b/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py index 5f66b03aad4..82c6821eb02 100644 --- a/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py +++ b/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py @@ -590,3 +590,247 @@ def test_update_responses_input_with_multiple_file_ids(): assert updated_input[0]["content"][2]["file_id"] == regular_file_id # Verify text content was preserved assert updated_input[0]["content"][1]["text"] == "Compare these files" + + +@pytest.mark.asyncio +async def test_store_unified_file_id_with_none_file_object(): + """ + Test that store_unified_file_id works when file_object is None + (e.g., for batch output files that are stored before file metadata is available). + """ + from litellm.proxy._types import UserAPIKeyAuth + + prisma_client = AsyncMock() + prisma_client.db.litellm_managedfiletable.create = AsyncMock(return_value=MagicMock()) + internal_usage_cache = MagicMock() + internal_usage_cache.async_set_cache = AsyncMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Store with file_object=None (simulating batch output file storage) + await proxy_managed_files.store_unified_file_id( + file_id="test-unified-file-id", + file_object=None, + litellm_parent_otel_span=None, + model_mappings={"model-123": "file-provider-xyz"}, + user_api_key_dict=UserAPIKeyAuth(user_id="test-user"), + ) + + # Verify DB create was called with expected data (without file_object) + prisma_client.db.litellm_managedfiletable.create.assert_called_once() + call_args = prisma_client.db.litellm_managedfiletable.create.call_args + assert call_args.kwargs["data"]["unified_file_id"] == "test-unified-file-id" + assert "file_object" not in call_args.kwargs["data"] + + +@pytest.mark.asyncio +async def test_afile_delete_returns_provider_response_when_stored_file_object_none(): + """ + Test that afile_delete returns the provider's delete response when the + stored file_object is None (e.g., for batch output files). + """ + from litellm.types.llms.openai import OpenAIFileObject + + unified_file_id = "bGl0ZWxsbV9wcm94eTphcHBsaWNhdGlvbi9qc29uO3VuaWZpZWRfaWQsdGVzdC1pZDt0YXJnZXRfbW9kZWxfbmFtZXMsZ3B0LTRvO2xsbV9vdXRwdXRfZmlsZV9pZCxmaWxlLXByb3ZpZGVyLXh5ejtsbG1fb3V0cHV0X2ZpbGVfbW9kZWxfaWQsbW9kZWwtMTIz" + + prisma_client = AsyncMock() + db_record = MagicMock() + db_record.model_mappings = '{"model-123": "file-provider-xyz"}' + prisma_client.db.litellm_managedfiletable.find_first = AsyncMock(return_value=db_record) + prisma_client.db.litellm_managedfiletable.delete = AsyncMock() + + internal_usage_cache = MagicMock() + internal_usage_cache.async_get_cache = AsyncMock(return_value={ + "unified_file_id": unified_file_id, + "model_mappings": {"model-123": "file-provider-xyz"}, + "flat_model_file_ids": ["file-provider-xyz"], + "file_object": None, + "created_by": "test-user", + "updated_by": "test-user", + }) + internal_usage_cache.async_set_cache = AsyncMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Mock the delete_unified_file_id to return None (simulating file_object=None) + proxy_managed_files.delete_unified_file_id = AsyncMock(return_value=None) + + # Mock router response + provider_delete_response = OpenAIFileObject( + id="file-provider-xyz", + object="file", + bytes=1234, + created_at=1234567890, + filename="test.jsonl", + purpose="batch", + ) + + mock_router = MagicMock() + mock_router.afile_delete = AsyncMock(return_value=provider_delete_response) + + result = await proxy_managed_files.afile_delete( + file_id=unified_file_id, + litellm_parent_otel_span=None, + llm_router=mock_router, + ) + + # Should return the provider response with the unified file ID + assert result is not None + assert result.id == unified_file_id + + +@pytest.mark.asyncio +async def test_afile_retrieve_fetches_from_provider_when_file_object_none(): + """ + Test that afile_retrieve fetches from the provider when the stored + file_object is None (e.g., for batch output files). + """ + from litellm.types.llms.openai import OpenAIFileObject + + prisma_client = AsyncMock() + internal_usage_cache = MagicMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Mock get_unified_file_id to return a stored object with file_object=None + stored_file = MagicMock() + stored_file.file_object = None + stored_file.model_mappings = {"model-123": "file-provider-xyz"} + proxy_managed_files.get_unified_file_id = AsyncMock(return_value=stored_file) + + # Mock the router and provider response + provider_file_response = OpenAIFileObject( + id="file-provider-xyz", + object="file", + bytes=5678, + created_at=1234567890, + filename="output.jsonl", + purpose="batch_output", + ) + + mock_router = MagicMock() + mock_router.get_deployment_credentials_with_provider = MagicMock(return_value={ + "api_key": "test-key", + "api_base": "https://api.openai.com", + }) + + with patch("litellm.afile_retrieve", new_callable=AsyncMock) as mock_afile_retrieve: + mock_afile_retrieve.return_value = provider_file_response + + unified_file_id = "test-unified-file-id" + result = await proxy_managed_files.afile_retrieve( + file_id=unified_file_id, + litellm_parent_otel_span=None, + llm_router=mock_router, + ) + + # Should return the provider response with the unified file ID + assert result is not None + assert result.id == unified_file_id + mock_afile_retrieve.assert_called_once() + + +@pytest.mark.asyncio +async def test_afile_retrieve_raises_error_when_no_router_and_file_object_none(): + """ + Test that afile_retrieve raises an appropriate error when file_object is None + and no llm_router is provided to fetch from the provider. + """ + prisma_client = AsyncMock() + internal_usage_cache = MagicMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Mock get_unified_file_id to return a stored object with file_object=None + stored_file = MagicMock() + stored_file.file_object = None + stored_file.model_mappings = {"model-123": "file-provider-xyz"} + proxy_managed_files.get_unified_file_id = AsyncMock(return_value=stored_file) + + unified_file_id = "test-unified-file-id" + + with pytest.raises(Exception) as exc_info: + await proxy_managed_files.afile_retrieve( + file_id=unified_file_id, + litellm_parent_otel_span=None, + llm_router=None, + ) + + assert "llm_router is required" in str(exc_info.value) + + +@pytest.mark.asyncio +async def test_afile_retrieve_returns_stored_file_object_when_exists(): + """ + Test that afile_retrieve returns the stored file_object directly when it exists + (the normal case for user-uploaded files). + """ + from litellm.types.llms.openai import OpenAIFileObject + + prisma_client = AsyncMock() + internal_usage_cache = MagicMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Mock get_unified_file_id to return a stored object WITH file_object + stored_file_object = OpenAIFileObject( + id="test-unified-file-id", + object="file", + bytes=1234, + created_at=1234567890, + filename="input.jsonl", + purpose="batch", + ) + stored_file = MagicMock() + stored_file.file_object = stored_file_object + proxy_managed_files.get_unified_file_id = AsyncMock(return_value=stored_file) + + result = await proxy_managed_files.afile_retrieve( + file_id="test-unified-file-id", + litellm_parent_otel_span=None, + llm_router=None, + ) + + # Should return the stored file object directly + assert result == stored_file_object + + +@pytest.mark.asyncio +async def test_afile_retrieve_raises_error_for_non_managed_file(): + """ + Test that afile_retrieve raises an error when the file_id is not found + in the managed files table. + """ + prisma_client = AsyncMock() + internal_usage_cache = MagicMock() + + proxy_managed_files = _PROXY_LiteLLMManagedFiles( + internal_usage_cache=internal_usage_cache, + prisma_client=prisma_client, + ) + + # Mock get_unified_file_id to return None (file not found) + proxy_managed_files.get_unified_file_id = AsyncMock(return_value=None) + + with pytest.raises(Exception) as exc_info: + await proxy_managed_files.afile_retrieve( + file_id="non-existent-file-id", + litellm_parent_otel_span=None, + ) + + assert "not found" in str(exc_info.value) From 103633c79485acceedf813611bcc0c27c4995579 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Tue, 23 Dec 2025 12:59:22 -0500 Subject: [PATCH 05/46] Fix linter errors: remove unused imports and variables --- .../proxy/hooks/test_managed_files.py | 11 ++--------- 1 file changed, 2 insertions(+), 9 deletions(-) diff --git a/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py b/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py index 82c6821eb02..9a6e153a22b 100644 --- a/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py +++ b/tests/enterprise/litellm_enterprise/proxy/hooks/test_managed_files.py @@ -1,18 +1,14 @@ import json -import os -import sys from unittest.mock import AsyncMock, MagicMock, patch import pytest from fastapi import HTTPException -from fastapi.testclient import TestClient from litellm_enterprise.proxy.hooks.managed_files import _PROXY_LiteLLMManagedFiles from litellm.caching import DualCache from litellm.proxy.openai_files_endpoints.common_utils import ( _is_base64_encoded_unified_file_id, ) -from litellm.types.utils import SpecialEnums def test_get_file_ids_from_messages(): @@ -255,7 +251,7 @@ async def test_can_user_call_unified_file_id(call_type): ) unified_file_id = "bGl0ZWxsbV9wcm94eTphcHBsaWNhdGlvbi9vY3RldC1zdHJlYW07dW5pZmllZF9pZCxmMTNlNDAzZS01YWM3LTRhZjktOGQzNS0wNDgwZDMxOTgyYTg7dGFyZ2V0X21vZGVsX25hbWVzLGdwdC00by1taW5pLW9wZW5haTtsbG1fb3V0cHV0X2ZpbGVfaWQsZmlsZS1Ib3UxZDFXc3c1SDNKcjFMYllpZDJiO2xsbV9vdXRwdXRfZmlsZV9tb2RlbF9pZCxmODBiNWU2NzQ1NzdkNjkyMjM4YmVhNTIxZDdiMGI5ZGYyY2FmMTEwMTU2YmU5YzBjM2NjMmNkNTBjOTM1ZDI0" - with pytest.raises(HTTPException) as e: + with pytest.raises(HTTPException): await proxy_managed_files.async_pre_call_hook( user_api_key_dict=UserAPIKeyAuth( user_id="456", parent_otel_span=MagicMock() @@ -310,7 +306,7 @@ async def test_router_acreate_batch_only_selects_from_file_id_mapping(monkeypatc litellm, "acreate_batch", return_value=AsyncMock() ) as mock_acreate_batch: for _ in range(1000): - response = await router.acreate_batch( + await router.acreate_batch( model="gpt-3.5-turbo", input_file_id=file_id, model_file_id_mapping=model_file_id_mapping, @@ -329,7 +325,6 @@ async def test_output_file_id_for_batch_retrieve(): from openai.types.batch import BatchRequestCounts - from litellm.proxy._types import UserAPIKeyAuth from litellm.types.utils import LiteLLMBatch batch = LiteLLMBatch( @@ -381,8 +376,6 @@ async def test_output_file_id_for_batch_retrieve(): @pytest.mark.asyncio async def test_async_post_call_success_hook_twice_assert_no_unique_violation(): import asyncio - from litellm.proxy.proxy_server import proxy_logging_obj - from litellm.proxy.utils import PrismaClient from litellm.types.utils import LiteLLMBatch from litellm.proxy._types import UserAPIKeyAuth from openai.types.batch import BatchRequestCounts From 07fe9e86048669d475bbed5ed5536add50f0a209 Mon Sep 17 00:00:00 2001 From: Xiaohan Fu Date: Tue, 6 Jan 2026 04:47:05 -0500 Subject: [PATCH 06/46] implement failopen option default to True on grayswan guardrail (#18266) * implement failopen option default to True * introduce a config to set the timeout limit (default to 30) --- .../guardrail_hooks/grayswan/__init__.py | 4 + .../guardrail_hooks/grayswan/grayswan.py | 91 +++++++++++++++---- .../guardrails/guardrail_hooks/grayswan.py | 8 ++ scripts/mock_grayswan_timeout_server.py | 85 +++++++++++++++++ 4 files changed, 170 insertions(+), 18 deletions(-) create mode 100644 scripts/mock_grayswan_timeout_server.py diff --git a/litellm/proxy/guardrails/guardrail_hooks/grayswan/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/grayswan/__init__.py index 99f58f654a7..3aca9078c0a 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/grayswan/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/grayswan/__init__.py @@ -46,6 +46,10 @@ def initialize_guardrail( streaming_sampling_rate=_get_config_value( litellm_params, optional_params, "streaming_sampling_rate" ) or 5, + fail_open=_get_config_value(litellm_params, optional_params, "fail_open"), + guardrail_timeout=_get_config_value( + litellm_params, optional_params, "guardrail_timeout" + ), event_hook=litellm_params.mode, default_on=litellm_params.default_on, ) diff --git a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py index 59e737f7d21..2a852cbda08 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py +++ b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py @@ -1,6 +1,7 @@ """Gray Swan Cygnal guardrail integration.""" import os +import time from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional from fastapi import HTTPException @@ -28,6 +29,10 @@ class GraySwanGuardrailMissingSecrets(Exception): class GraySwanGuardrailAPIError(Exception): """Raised when the Gray Swan API returns an error.""" + def __init__(self, message: str, status_code: Optional[int] = None) -> None: + super().__init__(message) + self.status_code = status_code + class GraySwanGuardrail(CustomGuardrail): """ @@ -63,6 +68,8 @@ class GraySwanGuardrail(CustomGuardrail): policy_id: Optional[str] = None, streaming_end_of_stream_only: bool = False, streaming_sampling_rate: int = 5, + fail_open: Optional[bool] = True, + guardrail_timeout: Optional[float] = 30.0, **kwargs: Any, ) -> None: self.async_handler = get_async_httpx_client( @@ -96,6 +103,8 @@ class GraySwanGuardrail(CustomGuardrail): self.reasoning_mode = self._resolve_reasoning_mode(reasoning_mode) self.categories = categories self.policy_id = policy_id + self.fail_open = True if fail_open is None else bool(fail_open) + self.guardrail_timeout = 30.0 if guardrail_timeout is None else float(guardrail_timeout) # Streaming configuration self.streaming_end_of_stream_only = streaming_end_of_stream_only @@ -202,18 +211,36 @@ class GraySwanGuardrail(CustomGuardrail): if payload is None: return inputs - # Call GraySwan API - response_json = await self._call_grayswan_api(payload) - # Process response - is_output = input_type == "response" - result = self._process_response_internal( - response_json=response_json, - request_data=request_data, - inputs=inputs, - is_output=is_output, - ) - - return result + start_time = time.time() + try: + response_json = await self._call_grayswan_api(payload) + is_output = input_type == "response" + result = self._process_response_internal( + response_json=response_json, + request_data=request_data, + inputs=inputs, + is_output=is_output, + ) + return result + except Exception as exc: + end_time = time.time() + status_code = getattr(exc, "status_code", None) or getattr( + exc, "exception_status_code", None + ) + self._log_guardrail_failure( + exc=exc, + request_data=request_data or {}, + start_time=start_time, + end_time=end_time, + status_code=status_code, + ) + if self.fail_open: + verbose_proxy_logger.warning( + "Gray Swan Guardrail: fail_open=True. Allowing request to proceed despite error: %s", + exc, + ) + return inputs + raise GraySwanGuardrailAPIError(str(exc), status_code=status_code) from exc # ------------------------------------------------------------------ # Legacy Test Interface (for backward compatibility) @@ -348,7 +375,7 @@ class GraySwanGuardrail(CustomGuardrail): url=self.monitor_url, headers=headers, json=payload, - timeout=30.0, + timeout=self.guardrail_timeout, ) response.raise_for_status() result = response.json() @@ -356,13 +383,11 @@ class GraySwanGuardrail(CustomGuardrail): "Gray Swan Guardrail: monitor response %s", safe_dumps(result) ) return result - except HTTPException: - raise except Exception as exc: - verbose_proxy_logger.exception( - "Gray Swan Guardrail: API request failed: %s", exc + status_code = getattr(exc, "status_code", None) or getattr( + exc, "exception_status_code", None ) - raise GraySwanGuardrailAPIError(str(exc)) from exc + raise GraySwanGuardrailAPIError(str(exc), status_code=status_code) from exc def _process_response_internal( self, @@ -579,3 +604,33 @@ class GraySwanGuardrail(CustomGuardrail): if env_val and env_val.lower() in self.SUPPORTED_REASONING_MODES: return env_val.lower() return None + + def _log_guardrail_failure( + self, + exc: Exception, + request_data: dict, + start_time: float, + end_time: float, + status_code: Optional[int] = None, + ) -> None: + """Log guardrail failure and attach standard logging metadata.""" + try: + self.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response=str(exc), + request_data=request_data, + guardrail_status="guardrail_failed_to_respond", + start_time=start_time, + end_time=end_time, + duration=end_time - start_time, + guardrail_provider="grayswan", + ) + except Exception: + verbose_proxy_logger.exception( + "Gray Swan Guardrail: failed to log guardrail failure for error: %s", + exc, + ) + verbose_proxy_logger.error( + "Gray Swan Guardrail: API request failed%s: %s", + f" (status_code={status_code})" if status_code else "", + exc, + ) diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py b/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py index 79239e52621..24d8cd85a0b 100644 --- a/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py +++ b/litellm/types/proxy/guardrails/guardrail_hooks/grayswan.py @@ -32,6 +32,14 @@ class GraySwanGuardrailConfigModelOptionalParams(BaseModel): default=None, description="Default Gray Swan category definitions to send with each request.", ) + fail_open: Optional[bool] = Field( + default=True, + description="If true (default), errors contacting Gray Swan are logged and the request proceeds. If false, errors propagate and block the request.", + ) + guardrail_timeout: Optional[float] = Field( + default=30.0, + description="Timeout in seconds for calling the Gray Swan guardrail service.", + ) class GraySwanGuardrailConfigModel( diff --git a/scripts/mock_grayswan_timeout_server.py b/scripts/mock_grayswan_timeout_server.py new file mode 100644 index 00000000000..bc40e13dfa5 --- /dev/null +++ b/scripts/mock_grayswan_timeout_server.py @@ -0,0 +1,85 @@ +""" +Minimal mock GraySwan monitor server that intentionally responds slowly. + +Usage: + python scripts/mock_grayswan_timeout_server.py --port 8787 --delay 35 + +Point GRAYSWAN_API_BASE at http://127.0.0.1:8787 so the guardrail hits this +endpoint and times out (the guardrail client has a 30s timeout). +""" + +from __future__ import annotations + +import argparse +import json +import logging +import time +from http.server import BaseHTTPRequestHandler, HTTPServer +from typing import Optional + +LOG = logging.getLogger("mock_grayswan") +logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s") + + +class SlowHandler(BaseHTTPRequestHandler): + delay_seconds: float = 35.0 + + def log_message(self, fmt: str, *args) -> None: # noqa: D401 + """Route handler logs through the logging module.""" + LOG.info("%s - %s", self.address_string(), fmt % args) + + def _read_body(self) -> Optional[bytes]: + content_length = self.headers.get("content-length") + if content_length is None: + return None + try: + length = int(content_length) + except ValueError: + return None + return self.rfile.read(length) + + def do_POST(self) -> None: # noqa: N802 + if self.path != "/cygnal/monitor": + self.send_error(404, "Not Found") + return + + body = self._read_body() + LOG.info("Received POST %s body=%s", self.path, body) + + LOG.info("Sleeping for %.1fs to trigger client timeout", self.delay_seconds) + time.sleep(self.delay_seconds) + + response = {"status": "ok", "delayed": self.delay_seconds} + response_bytes = json.dumps(response).encode("utf-8") + + self.send_response(200) + self.send_header("Content-Type", "application/json") + self.send_header("Content-Length", str(len(response_bytes))) + self.end_headers() + self.wfile.write(response_bytes) + + +def main() -> None: + parser = argparse.ArgumentParser(description="Mock GraySwan monitor server") + parser.add_argument("--port", type=int, default=8787, help="Port to listen on") + parser.add_argument( + "--delay", + type=float, + default=35.0, + help="Seconds to delay before responding (must exceed guardrail timeout)", + ) + args = parser.parse_args() + + SlowHandler.delay_seconds = args.delay + server = HTTPServer(("0.0.0.0", args.port), SlowHandler) + LOG.info("Starting mock server on port %d with delay %.1fs", args.port, args.delay) + try: + server.serve_forever() + except KeyboardInterrupt: + LOG.info("Shutting down mock server") + finally: + server.server_close() + + +if __name__ == "__main__": + main() From 1203e8416279a58c8404e9a1af87e4cfda48b4be Mon Sep 17 00:00:00 2001 From: Harshit Jain <48647625+Harshit28j@users.noreply.github.com> Date: Fri, 9 Jan 2026 23:43:44 +0530 Subject: [PATCH 07/46] fix(otel): update semantic conventions to 1.38 (gen_ai attributes) (#18793) --- litellm/integrations/opentelemetry.py | 174 +++++++++---- litellm/proxy/_types.py | 144 +++++++---- .../integrations/test_opentelemetry.py | 234 ++++++++++++++++++ 3 files changed, 452 insertions(+), 100 deletions(-) diff --git a/litellm/integrations/opentelemetry.py b/litellm/integrations/opentelemetry.py index 7e0cfab617b..a223925d59a 100644 --- a/litellm/integrations/opentelemetry.py +++ b/litellm/integrations/opentelemetry.py @@ -594,9 +594,9 @@ class OpenTelemetry(CustomLogger): def _get_dynamic_otel_headers_from_kwargs(self, kwargs) -> Optional[dict]: """Extract dynamic headers from kwargs if available.""" - standard_callback_dynamic_params: Optional[ - StandardCallbackDynamicParams - ] = kwargs.get("standard_callback_dynamic_params") + standard_callback_dynamic_params: Optional[StandardCallbackDynamicParams] = ( + kwargs.get("standard_callback_dynamic_params") + ) if not standard_callback_dynamic_params: return None @@ -797,7 +797,7 @@ class OpenTelemetry(CustomLogger): and self._token_usage_histogram ): in_attrs = {**common_attrs, "gen_ai.token.type": "input"} - out_attrs = {**common_attrs, "gen_ai.token.type": "completion"} + out_attrs = {**common_attrs, "gen_ai.token.type": "output"} self._token_usage_histogram.record( usage.get("prompt_tokens", 0), attributes=in_attrs ) @@ -1488,21 +1488,21 @@ class OpenTelemetry(CustomLogger): if usage: self.safe_set_attribute( span=span, - key=SpanAttributes.LLM_USAGE_TOTAL_TOKENS.value, + key=SpanAttributes.GEN_AI_USAGE_TOTAL_TOKENS.value, value=usage.get("total_tokens"), ) # The number of tokens used in the LLM response (completion). self.safe_set_attribute( span=span, - key=SpanAttributes.LLM_USAGE_COMPLETION_TOKENS.value, + key=SpanAttributes.GEN_AI_USAGE_OUTPUT_TOKENS.value, value=usage.get("completion_tokens"), ) # The number of tokens used in the LLM prompt. self.safe_set_attribute( span=span, - key=SpanAttributes.LLM_USAGE_PROMPT_TOKENS.value, + key=SpanAttributes.GEN_AI_USAGE_INPUT_TOKENS.value, value=usage.get("prompt_tokens"), ) @@ -1520,53 +1520,75 @@ class OpenTelemetry(CustomLogger): self.set_tools_attributes(span, tools) if kwargs.get("messages"): - for idx, prompt in enumerate(kwargs.get("messages")): - if prompt.get("role"): - self.safe_set_attribute( - span=span, - key=f"{SpanAttributes.LLM_PROMPTS.value}.{idx}.role", - value=prompt.get("role"), - ) + transformed_messages = ( + self._transform_messages_to_otel_semantic_conventions( + kwargs.get("messages") + ) + ) + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_INPUT_MESSAGES.value, + value=safe_dumps(transformed_messages), + ) - if prompt.get("content"): - if not isinstance(prompt.get("content"), str): - prompt["content"] = str(prompt.get("content")) - self.safe_set_attribute( - span=span, - key=f"{SpanAttributes.LLM_PROMPTS.value}.{idx}.content", - value=prompt.get("content"), - ) + if kwargs.get("system_instructions"): + transformed_system_instructions = ( + self._transform_messages_to_otel_semantic_conventions( + kwargs.get("system_instructions") + ) + ) + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_SYSTEM_INSTRUCTIONS.value, + value=safe_dumps(transformed_system_instructions), + ) + + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_OPERATION_NAME.value, + value=( + "chat" + if standard_logging_payload.get("call_type") == "completion" + else standard_logging_payload.get("call_type") or "chat" + ), + ) + + if standard_logging_payload.get("request_id"): + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_REQUEST_ID.value, + value=standard_logging_payload.get("request_id"), + ) ############################################# ########## LLM Response Attributes ########## ############################################# if response_obj is not None: if response_obj.get("choices"): + transformed_choices = ( + self._transform_choices_to_otel_semantic_conventions( + response_obj.get("choices") + ) + ) + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_OUTPUT_MESSAGES.value, + value=safe_dumps(transformed_choices), + ) + + finish_reasons = [] + for idx, choice in enumerate(response_obj.get("choices")): + if choice.get("finish_reason"): + finish_reasons.append(choice.get("finish_reason")) + + if finish_reasons: + self.safe_set_attribute( + span=span, + key=SpanAttributes.GEN_AI_RESPONSE_FINISH_REASONS.value, + value=safe_dumps(finish_reasons), + ) + for idx, choice in enumerate(response_obj.get("choices")): if choice.get("finish_reason"): - self.safe_set_attribute( - span=span, - key=f"{SpanAttributes.LLM_COMPLETIONS.value}.{idx}.finish_reason", - value=choice.get("finish_reason"), - ) - if choice.get("message"): - if choice.get("message").get("role"): - self.safe_set_attribute( - span=span, - key=f"{SpanAttributes.LLM_COMPLETIONS.value}.{idx}.role", - value=choice.get("message").get("role"), - ) - if choice.get("message").get("content"): - if not isinstance( - choice.get("message").get("content"), str - ): - choice["message"]["content"] = str( - choice.get("message").get("content") - ) - self.safe_set_attribute( - span=span, - key=f"{SpanAttributes.LLM_COMPLETIONS.value}.{idx}.content", - value=choice.get("message").get("content"), - ) message = choice.get("message") tool_calls = message.get("tool_calls") @@ -1608,6 +1630,66 @@ class OpenTelemetry(CustomLogger): primitive_value = self._cast_as_primitive_value_type(value) span.set_attribute(key, primitive_value) + def _transform_messages_to_otel_semantic_conventions( + self, messages: Union[List[dict], str] + ) -> List[dict]: + """ + Transforms LiteLLM/OpenAI style messages into OTEL GenAI 1.38 compliant format. + OTEL expects a 'parts' array instead of a single 'content' string. + """ + if isinstance(messages, str): + # Handle system_instructions passed as a string + return [ + {"role": "system", "parts": [{"type": "text", "content": messages}]} + ] + + transformed = [] + for msg in messages: + role = msg.get("role", "user") + content = msg.get("content", "") + parts = [] + + if isinstance(content, str): + parts.append({"type": "text", "content": content}) + elif isinstance(content, list): + # Handle multi-modal content if necessary + for part in content: + if isinstance(part, dict): + parts.append(part) + else: + parts.append({"type": "text", "content": str(part)}) + + transformed_msg = {"role": role, "parts": parts} + if "id" in msg: + transformed_msg["id"] = msg["id"] + if "tool_calls" in msg: + transformed_msg["tool_calls"] = msg["tool_calls"] + if "tool_call_id" in msg: + transformed_msg["tool_call_id"] = msg["tool_call_id"] + transformed.append(transformed_msg) + + return transformed + + def _transform_choices_to_otel_semantic_conventions( + self, choices: List[dict] + ) -> List[dict]: + """ + Transforms choices into OTEL GenAI 1.38 compliant format for output.messages. + """ + transformed = [] + for choice in choices: + message = choice.get("message") or {} + finish_reason = choice.get("finish_reason") + + transformed_msg = self._transform_messages_to_otel_semantic_conventions( + [message] + )[0] + if finish_reason: + transformed_msg["finish_reason"] = finish_reason + + transformed.append(transformed_msg) + return transformed + def set_raw_request_attributes(self, span: Span, kwargs, response_obj): try: kwargs.get("optional_params", {}) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index be1e4dbcdc9..fc69836cf75 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -830,9 +830,9 @@ class GenerateRequestBase(LiteLLMPydanticObjectBase): allowed_cache_controls: Optional[list] = [] config: Optional[dict] = {} permissions: Optional[dict] = {} - model_max_budget: Optional[ - dict - ] = {} # {"gpt-4": 5.0, "gpt-3.5-turbo": 5.0}, defaults to {} + model_max_budget: Optional[dict] = ( + {} + ) # {"gpt-4": 5.0, "gpt-3.5-turbo": 5.0}, defaults to {} model_config = ConfigDict(protected_namespaces=()) model_rpm_limit: Optional[dict] = None @@ -1364,12 +1364,12 @@ class NewCustomerRequest(BudgetNewRequest): blocked: bool = False # allow/disallow requests for this end-user budget_id: Optional[str] = None # give either a budget_id or max_budget spend: Optional[float] = None - allowed_model_region: Optional[ - AllowedModelRegion - ] = None # require all user requests to use models in this specific region - default_model: Optional[ - str - ] = None # if no equivalent model in allowed region - default all requests to this model + allowed_model_region: Optional[AllowedModelRegion] = ( + None # require all user requests to use models in this specific region + ) + default_model: Optional[str] = ( + None # if no equivalent model in allowed region - default all requests to this model + ) @model_validator(mode="before") @classmethod @@ -1391,12 +1391,12 @@ class UpdateCustomerRequest(LiteLLMPydanticObjectBase): blocked: bool = False # allow/disallow requests for this end-user max_budget: Optional[float] = None budget_id: Optional[str] = None # give either a budget_id or max_budget - allowed_model_region: Optional[ - AllowedModelRegion - ] = None # require all user requests to use models in this specific region - default_model: Optional[ - str - ] = None # if no equivalent model in allowed region - default all requests to this model + allowed_model_region: Optional[AllowedModelRegion] = ( + None # require all user requests to use models in this specific region + ) + default_model: Optional[str] = ( + None # if no equivalent model in allowed region - default all requests to this model + ) class DeleteCustomerRequest(LiteLLMPydanticObjectBase): @@ -1482,15 +1482,15 @@ class NewTeamRequest(TeamBase): ] = None # raise an error if 'guaranteed_throughput' is set and we're overallocating tpm model_tpm_limit: Optional[Dict[str, int]] = None - team_member_budget: Optional[ - float - ] = None # allow user to set a budget for all team members - team_member_rpm_limit: Optional[ - int - ] = None # allow user to set RPM limit for all team members - team_member_tpm_limit: Optional[ - int - ] = None # allow user to set TPM limit for all team members + team_member_budget: Optional[float] = ( + None # allow user to set a budget for all team members + ) + team_member_rpm_limit: Optional[int] = ( + None # allow user to set RPM limit for all team members + ) + team_member_tpm_limit: Optional[int] = ( + None # allow user to set TPM limit for all team members + ) team_member_key_duration: Optional[str] = None # e.g. "1d", "1w", "1m" allowed_vector_store_indexes: Optional[List[AllowedVectorStoreIndexItem]] = None @@ -1578,9 +1578,9 @@ class BlockKeyRequest(LiteLLMPydanticObjectBase): class AddTeamCallback(LiteLLMPydanticObjectBase): callback_name: str - callback_type: Optional[ - Literal["success", "failure", "success_and_failure"] - ] = "success_and_failure" + callback_type: Optional[Literal["success", "failure", "success_and_failure"]] = ( + "success_and_failure" + ) callback_vars: Dict[str, str] @model_validator(mode="before") @@ -1893,9 +1893,9 @@ class ConfigList(LiteLLMPydanticObjectBase): stored_in_db: Optional[bool] field_default_value: Any premium_field: bool = False - nested_fields: Optional[ - List[FieldDetail] - ] = None # For nested dictionary or Pydantic fields + nested_fields: Optional[List[FieldDetail]] = ( + None # For nested dictionary or Pydantic fields + ) class UserHeaderMapping(LiteLLMPydanticObjectBase): @@ -2289,9 +2289,9 @@ class LiteLLM_OrganizationMembershipTable(LiteLLMPydanticObjectBase): budget_id: Optional[str] = None created_at: datetime updated_at: datetime - user: Optional[ - Any - ] = None # You might want to replace 'Any' with a more specific type if available + user: Optional[Any] = ( + None # You might want to replace 'Any' with a more specific type if available + ) litellm_budget_table: Optional[LiteLLM_BudgetTable] = None model_config = ConfigDict(protected_namespaces=()) @@ -2826,6 +2826,18 @@ class SpanAttributes(str, enum.Enum): LLM_RESPONSE_MODEL = "gen_ai.response.model" LLM_USAGE_COMPLETION_TOKENS = "gen_ai.usage.completion_tokens" LLM_USAGE_PROMPT_TOKENS = "gen_ai.usage.prompt_tokens" + + # OTEL 1.38 attributes + GEN_AI_INPUT_MESSAGES = "gen_ai.input.messages" + GEN_AI_OUTPUT_MESSAGES = "gen_ai.output.messages" + GEN_AI_USAGE_INPUT_TOKENS = "gen_ai.usage.input_tokens" + GEN_AI_USAGE_OUTPUT_TOKENS = "gen_ai.usage.output_tokens" + GEN_AI_USAGE_TOTAL_TOKENS = "gen_ai.usage.total_tokens" + GEN_AI_OPERATION_NAME = "gen_ai.operation.name" + GEN_AI_REQUEST_ID = "gen_ai.request.id" + GEN_AI_SYSTEM_INSTRUCTIONS = "gen_ai.system_instructions" + GEN_AI_RESPONSE_FINISH_REASONS = "gen_ai.response.finish_reasons" + LLM_TOKEN_TYPE = "gen_ai.token.type" # To be added # LLM_RESPONSE_FINISH_REASON = "gen_ai.response.finish_reasons" @@ -3251,9 +3263,9 @@ class TeamModelDeleteRequest(BaseModel): # Organization Member Requests class OrganizationMemberAddRequest(OrgMemberAddRequest): organization_id: str - max_budget_in_organization: Optional[ - float - ] = None # Users max budget within the organization + max_budget_in_organization: Optional[float] = ( + None # Users max budget within the organization + ) class OrganizationMemberDeleteRequest(MemberDeleteRequest): @@ -3468,9 +3480,9 @@ class ProviderBudgetResponse(LiteLLMPydanticObjectBase): Maps provider names to their budget configs. """ - providers: Dict[ - str, ProviderBudgetResponseObject - ] = {} # Dictionary mapping provider names to their budget configurations + providers: Dict[str, ProviderBudgetResponseObject] = ( + {} + ) # Dictionary mapping provider names to their budget configurations class ProxyStateVariables(TypedDict): @@ -3613,9 +3625,9 @@ class LiteLLM_JWTAuth(LiteLLMPydanticObjectBase): enforce_rbac: bool = False roles_jwt_field: Optional[str] = None # v2 on role mappings role_mappings: Optional[List[RoleMapping]] = None - object_id_jwt_field: Optional[ - str - ] = None # can be either user / team, inferred from the role mapping + object_id_jwt_field: Optional[str] = ( + None # can be either user / team, inferred from the role mapping + ) scope_mappings: Optional[List[ScopeMapping]] = None enforce_scope_based_access: bool = False enforce_team_based_model_access: bool = False @@ -3866,20 +3878,44 @@ class CostEstimateResponse(LiteLLMPydanticObjectBase): num_requests_per_day: Optional[int] = None num_requests_per_month: Optional[int] = None # Per-request costs - cost_per_request: float = Field(description="Total cost per request (includes margin)") - input_cost_per_request: float = Field(description="Input token cost per request (before margin)") - output_cost_per_request: float = Field(description="Output token cost per request (before margin)") - margin_cost_per_request: float = Field(default=0.0, description="Margin/fee added per request") + cost_per_request: float = Field( + description="Total cost per request (includes margin)" + ) + input_cost_per_request: float = Field( + description="Input token cost per request (before margin)" + ) + output_cost_per_request: float = Field( + description="Output token cost per request (before margin)" + ) + margin_cost_per_request: float = Field( + default=0.0, description="Margin/fee added per request" + ) # Daily costs (if num_requests_per_day provided) - daily_cost: Optional[float] = Field(default=None, description="Total daily cost (includes margin)") - daily_input_cost: Optional[float] = Field(default=None, description="Daily input token cost") - daily_output_cost: Optional[float] = Field(default=None, description="Daily output token cost") - daily_margin_cost: Optional[float] = Field(default=None, description="Daily margin/fee") + daily_cost: Optional[float] = Field( + default=None, description="Total daily cost (includes margin)" + ) + daily_input_cost: Optional[float] = Field( + default=None, description="Daily input token cost" + ) + daily_output_cost: Optional[float] = Field( + default=None, description="Daily output token cost" + ) + daily_margin_cost: Optional[float] = Field( + default=None, description="Daily margin/fee" + ) # Monthly costs (if num_requests_per_month provided) - monthly_cost: Optional[float] = Field(default=None, description="Total monthly cost (includes margin)") - monthly_input_cost: Optional[float] = Field(default=None, description="Monthly input token cost") - monthly_output_cost: Optional[float] = Field(default=None, description="Monthly output token cost") - monthly_margin_cost: Optional[float] = Field(default=None, description="Monthly margin/fee") + monthly_cost: Optional[float] = Field( + default=None, description="Total monthly cost (includes margin)" + ) + monthly_input_cost: Optional[float] = Field( + default=None, description="Monthly input token cost" + ) + monthly_output_cost: Optional[float] = Field( + default=None, description="Monthly output token cost" + ) + monthly_margin_cost: Optional[float] = Field( + default=None, description="Monthly margin/fee" + ) # Pricing info input_cost_per_token: Optional[float] = None output_cost_per_token: Optional[float] = None diff --git a/tests/test_litellm/integrations/test_opentelemetry.py b/tests/test_litellm/integrations/test_opentelemetry.py index 55b65fbb92a..95fa6ed8f60 100644 --- a/tests/test_litellm/integrations/test_opentelemetry.py +++ b/tests/test_litellm/integrations/test_opentelemetry.py @@ -1869,3 +1869,237 @@ class TestOpenTelemetryExternalSpan(unittest.TestCase): parent_span_finished.attributes, "Parent span should have model attribute from LiteLLM even on failure" ) + + +class TestOpenTelemetrySemanticConventions138(unittest.TestCase): + """ + Test suite for OpenTelemetry 1.38 Semantic Conventions compliance. + + These tests verify that LiteLLM emits span attributes following the + OpenTelemetry GenAI semantic conventions v1.38, including: + - gen_ai.input.messages (JSON string with parts array) + - gen_ai.output.messages (JSON string with parts array) + - gen_ai.usage.input_tokens / output_tokens (new naming) + - gen_ai.response.finish_reasons (JSON array) + + See: https://github.com/BerriAI/litellm/issues/17794 + """ + + def test_input_messages_uses_parts_structure(self): + """ + Test that gen_ai.input.messages uses the OTEL 1.38 parts array structure. + + Expected format: + [{"role": "user", "parts": [{"type": "text", "content": "Hello"}]}] + """ + otel = OpenTelemetry() + mock_span = MagicMock() + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello world"}], + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + "standard_logging_object": { + "id": "test-id", + "call_type": "completion", + "metadata": {}, + }, + } + + response_obj = { + "id": "test-response-id", + "model": "gpt-4", + "choices": [ + { + "finish_reason": "stop", + "message": {"role": "assistant", "content": "Hi there!"}, + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30}, + } + + otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj) + + # Find the call that set gen_ai.input.messages + input_messages_calls = [ + call for call in mock_span.set_attribute.call_args_list + if call[0][0] == "gen_ai.input.messages" + ] + self.assertEqual(len(input_messages_calls), 1, "Should have exactly one gen_ai.input.messages attribute") + + input_messages_value = input_messages_calls[0][0][1] + parsed = json.loads(input_messages_value) + + # Verify structure + self.assertIsInstance(parsed, list) + self.assertEqual(len(parsed), 1) + self.assertEqual(parsed[0]["role"], "user") + self.assertIn("parts", parsed[0]) + self.assertEqual(parsed[0]["parts"][0]["type"], "text") + self.assertEqual(parsed[0]["parts"][0]["content"], "Hello world") + + def test_output_messages_uses_parts_structure(self): + """ + Test that gen_ai.output.messages uses the OTEL 1.38 parts array structure. + + Expected format: + [{"role": "assistant", "parts": [{"type": "text", "content": "Hi!"}], "finish_reason": "stop"}] + """ + otel = OpenTelemetry() + mock_span = MagicMock() + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + "standard_logging_object": { + "id": "test-id", + "call_type": "completion", + "metadata": {}, + }, + } + + response_obj = { + "id": "test-response-id", + "model": "gpt-4", + "choices": [ + { + "finish_reason": "stop", + "message": {"role": "assistant", "content": "Hello back!"}, + } + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30}, + } + + otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj) + + # Find the call that set gen_ai.output.messages + output_messages_calls = [ + call for call in mock_span.set_attribute.call_args_list + if call[0][0] == "gen_ai.output.messages" + ] + self.assertEqual(len(output_messages_calls), 1, "Should have exactly one gen_ai.output.messages attribute") + + output_messages_value = output_messages_calls[0][0][1] + parsed = json.loads(output_messages_value) + + # Verify structure + self.assertIsInstance(parsed, list) + self.assertEqual(len(parsed), 1) + self.assertEqual(parsed[0]["role"], "assistant") + self.assertIn("parts", parsed[0]) + self.assertEqual(parsed[0]["parts"][0]["type"], "text") + self.assertEqual(parsed[0]["parts"][0]["content"], "Hello back!") + self.assertEqual(parsed[0]["finish_reason"], "stop") + + def test_usage_tokens_use_new_naming_convention(self): + """ + Test that token usage uses the OTEL 1.38 naming convention: + - gen_ai.usage.input_tokens (not prompt_tokens) + - gen_ai.usage.output_tokens (not completion_tokens) + """ + otel = OpenTelemetry() + mock_span = MagicMock() + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + "standard_logging_object": { + "id": "test-id", + "call_type": "completion", + "metadata": {}, + }, + } + + response_obj = { + "id": "test-response-id", + "model": "gpt-4", + "choices": [], + "usage": {"prompt_tokens": 100, "completion_tokens": 50, "total_tokens": 150}, + } + + otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj) + + # Verify new naming convention is used + mock_span.set_attribute.assert_any_call("gen_ai.usage.input_tokens", 100) + mock_span.set_attribute.assert_any_call("gen_ai.usage.output_tokens", 50) + mock_span.set_attribute.assert_any_call("gen_ai.usage.total_tokens", 150) + + def test_finish_reasons_is_json_array(self): + """ + Test that gen_ai.response.finish_reasons is a proper JSON array. + + Expected: '["stop"]' (not "['stop']") + """ + otel = OpenTelemetry() + mock_span = MagicMock() + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + "standard_logging_object": { + "id": "test-id", + "call_type": "completion", + "metadata": {}, + }, + } + + response_obj = { + "id": "test-response-id", + "model": "gpt-4", + "choices": [ + {"finish_reason": "stop", "message": {"role": "assistant", "content": "Hi"}}, + ], + "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30}, + } + + otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj) + + # Find the call that set gen_ai.response.finish_reasons + finish_reasons_calls = [ + call for call in mock_span.set_attribute.call_args_list + if call[0][0] == "gen_ai.response.finish_reasons" + ] + self.assertEqual(len(finish_reasons_calls), 1, "Should have exactly one gen_ai.response.finish_reasons attribute") + + finish_reasons_value = finish_reasons_calls[0][0][1] + + # Verify it's valid JSON (not Python repr) + parsed = json.loads(finish_reasons_value) + self.assertEqual(parsed, ["stop"]) + + def test_operation_name_is_chat_for_completion(self): + """ + Test that gen_ai.operation.name is 'chat' for completion calls. + """ + otel = OpenTelemetry() + mock_span = MagicMock() + + kwargs = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "optional_params": {}, + "litellm_params": {"custom_llm_provider": "openai"}, + "standard_logging_object": { + "id": "test-id", + "call_type": "completion", + "metadata": {}, + }, + } + + response_obj = { + "id": "test-response-id", + "model": "gpt-4", + "choices": [], + "usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30}, + } + + otel.set_attributes(span=mock_span, kwargs=kwargs, response_obj=response_obj) + + mock_span.set_attribute.assert_any_call("gen_ai.operation.name", "chat") From 2e6fe80f909cdfd55e22abbeef9938e31c073682 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 14:44:28 -0800 Subject: [PATCH 08/46] optional query params for org list --- .../organization_endpoints.py | 89 +++++++++++-- .../test_organization_endpoints.py | 125 ++++++++++++++++++ 2 files changed, 200 insertions(+), 14 deletions(-) diff --git a/litellm/proxy/management_endpoints/organization_endpoints.py b/litellm/proxy/management_endpoints/organization_endpoints.py index a088f46d67d..94cfa82c0c6 100644 --- a/litellm/proxy/management_endpoints/organization_endpoints.py +++ b/litellm/proxy/management_endpoints/organization_endpoints.py @@ -11,8 +11,9 @@ Endpoints for /organization operations #### ORGANIZATION MANAGEMENT #### -from typing import List, Optional, Tuple +from typing import Any, Dict, List, Optional, Tuple +import fastapi from fastapi import APIRouter, Depends, HTTPException, Request, status from litellm._logging import verbose_proxy_logger @@ -595,11 +596,33 @@ async def delete_organization( response_model=List[LiteLLM_OrganizationTableWithMembers], ) async def list_organization( + org_id: Optional[str] = fastapi.Query( + default=None, description="Filter organizations by exact organization_id match" + ), + org_alias: Optional[str] = fastapi.Query( + default=None, + description="Filter organizations by partial organization_alias match. Supports case-insensitive search.", + ), user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): """ + Get a list of organizations with optional filtering. + + Parameters: + org_id: Optional[str] + Filter organizations by exact organization_id match + org_alias: Optional[str] + Filter organizations by partial organization_alias match (case-insensitive) + + Example: ``` - curl --location --request GET 'http://0.0.0.0:4000/organization/list' \ + curl --location --request GET 'http://0.0.0.0:4000/organization/list?org_alias=my-org' \ + --header 'Authorization: Bearer sk-1234' + ``` + + Example with org_id: + ``` + curl --location --request GET 'http://0.0.0.0:4000/organization/list?org_id=123e4567-e89b-12d3-a456-426614174000' \ --header 'Authorization: Bearer sk-1234' ``` """ @@ -614,28 +637,66 @@ async def list_organization( detail={"error": CommonProxyErrors.db_not_connected_error.value}, ) - # if proxy admin - get all orgs + # Build where conditions based on provided filters + where_conditions: Dict[str, Any] = {} + + if org_id: + where_conditions["organization_id"] = org_id + + if org_alias: + where_conditions["organization_alias"] = { + "contains": org_alias, + "mode": "insensitive", # Case-insensitive search + } + + # if proxy admin - get all orgs (with optional filters) if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN: response = await prisma_client.db.litellm_organizationtable.find_many( - include={"litellm_budget_table": True, "members": True, "teams": True} + where=where_conditions if where_conditions else None, + include={"litellm_budget_table": True, "members": True, "teams": True}, ) - # if internal user - get orgs they are a member of + # if internal user - get orgs they are a member of (with optional filters) else: org_memberships = ( await prisma_client.db.litellm_organizationmembership.find_many( where={"user_id": user_api_key_dict.user_id} ) ) - org_objects = await prisma_client.db.litellm_organizationtable.find_many( - where={ - "organization_id": { - "in": [membership.organization_id for membership in org_memberships] - } - }, - include={"litellm_budget_table": True, "members": True, "teams": True}, - ) + membership_org_ids = [ + membership.organization_id for membership in org_memberships + ] - response = org_objects + # Combine membership filter with provided filters + if membership_org_ids: + if org_id: + # If org_id is provided, ensure user is a member of that org + if org_id not in membership_org_ids: + # User is not a member of the requested org, return empty list + response = [] + else: + where_conditions["organization_id"] = org_id + response = await prisma_client.db.litellm_organizationtable.find_many( + where=where_conditions, + include={ + "litellm_budget_table": True, + "members": True, + "teams": True, + }, + ) + else: + # Filter by membership and any additional filters + where_conditions["organization_id"] = {"in": membership_org_ids} + response = await prisma_client.db.litellm_organizationtable.find_many( + where=where_conditions, + include={ + "litellm_budget_table": True, + "members": True, + "teams": True, + }, + ) + else: + # User is not a member of any orgs + response = [] return response diff --git a/tests/test_litellm/proxy/management_endpoints/test_organization_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_organization_endpoints.py index c02db727bf0..2a2c37d03c2 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_organization_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_organization_endpoints.py @@ -410,3 +410,128 @@ async def test_organization_update_object_permissions_missing_permission_record( # Verify upsert was called to create new record mock_prisma_client.db.litellm_objectpermissiontable.upsert.assert_called_once() + + +@pytest.mark.asyncio +async def test_list_organization_filter_by_org_id(monkeypatch): + """ + Test filtering organizations by org_id query parameter. + + This test verifies that when org_id is provided, only the organization + with that exact organization_id is returned. + """ + from types import SimpleNamespace + + from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth + from litellm.proxy.management_endpoints.organization_endpoints import ( + list_organization, + ) + + # Mock prisma client + mock_prisma_client = AsyncMock() + + # Mock organization data + mock_org1 = SimpleNamespace( + organization_id="org-123", + organization_alias="Test Org 1", + model_dump=lambda: { + "organization_id": "org-123", + "organization_alias": "Test Org 1", + }, + ) + + # Mock find_many to return filtered results + mock_prisma_client.db.litellm_organizationtable.find_many = AsyncMock( + return_value=[mock_org1] + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + # Test as proxy admin + auth = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, user_id="admin-user" + ) + + result = await list_organization(org_id="org-123", org_alias=None, user_api_key_dict=auth) + + # Verify the correct organization was returned + assert len(result) == 1 + assert result[0].organization_id == "org-123" + assert result[0].organization_alias == "Test Org 1" + + # Verify find_many was called with correct where conditions + mock_prisma_client.db.litellm_organizationtable.find_many.assert_called_once() + call_args = mock_prisma_client.db.litellm_organizationtable.find_many.call_args + assert call_args.kwargs["where"] == {"organization_id": "org-123"} + assert call_args.kwargs["include"] == { + "litellm_budget_table": True, + "members": True, + "teams": True, + } + + +@pytest.mark.asyncio +async def test_list_organization_filter_by_org_alias(monkeypatch): + """ + Test filtering organizations by org_alias query parameter with case-insensitive partial matching. + + This test verifies that when org_alias is provided, organizations with matching + organization_alias (case-insensitive partial match) are returned. + """ + from types import SimpleNamespace + + from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth + from litellm.proxy.management_endpoints.organization_endpoints import ( + list_organization, + ) + + # Mock prisma client + mock_prisma_client = AsyncMock() + + # Mock organization data + mock_org1 = SimpleNamespace( + organization_id="org-123", + organization_alias="My Test Organization", + model_dump=lambda: { + "organization_id": "org-123", + "organization_alias": "My Test Organization", + }, + ) + mock_org2 = SimpleNamespace( + organization_id="org-456", + organization_alias="Another Test Org", + model_dump=lambda: { + "organization_id": "org-456", + "organization_alias": "Another Test Org", + }, + ) + + # Mock find_many to return filtered results + mock_prisma_client.db.litellm_organizationtable.find_many = AsyncMock( + return_value=[mock_org1, mock_org2] + ) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) + + # Test as proxy admin with org_alias filter + auth = UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, user_id="admin-user" + ) + + result = await list_organization(org_id=None, org_alias="test", user_api_key_dict=auth) + + # Verify organizations with "test" in alias were returned + assert len(result) == 2 + assert all("test" in org.organization_alias.lower() for org in result) + + # Verify find_many was called with correct where conditions (case-insensitive contains) + mock_prisma_client.db.litellm_organizationtable.find_many.assert_called_once() + call_args = mock_prisma_client.db.litellm_organizationtable.find_many.call_args + assert call_args.kwargs["where"] == { + "organization_alias": {"contains": "test", "mode": "insensitive"} + } + assert call_args.kwargs["include"] == { + "litellm_budget_table": True, + "members": True, + "teams": True, + } From 2b93fd775d2878de0aec300a417d3b7215d0731b Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 15:05:30 -0800 Subject: [PATCH 09/46] temp commit for branch switching --- .../organizations/OrganizationFilters.tsx | 120 ++++++++++++++++++ .../src/components/networking.tsx | 21 ++- .../src/components/organizations.tsx | 67 +++++++++- 3 files changed, 200 insertions(+), 8 deletions(-) create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx diff --git a/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx new file mode 100644 index 00000000000..9b3fa2fc026 --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx @@ -0,0 +1,120 @@ +import React from "react"; + +interface OrganizationFiltersProps { + filters: FilterState; + showFilters: boolean; + onToggleFilters: (toggle: boolean) => void; + onChange: (key: K, value: FilterState[K]) => void; + onReset: () => void; +} + +type FilterState = { + org_id: string; + org_alias: string; + sort_by: string; + sort_order: "asc" | "desc"; +}; + +const OrganizationFilters = ({ + filters, + showFilters, + onToggleFilters, + onChange, + onReset, +}: OrganizationFiltersProps) => { + return ( +
+ {/* Search and Filter Controls */} +
+ {/* Organization Alias Search */} +
+ onChange("org_alias", e.target.value)} + /> + + + +
+ + {/* Filter Button */} + + + {/* Reset Filters Button */} + +
+ + {/* Additional Filters */} + {showFilters && ( +
+ {/* Organization ID Search */} +
+ onChange("org_id", e.target.value)} + /> + + + +
+
+ )} +
+ ); +}; + +export default OrganizationFilters; +export type { FilterState }; diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx index 6fd828dfc25..0a378eba3b2 100644 --- a/ui/litellm-dashboard/src/components/networking.tsx +++ b/ui/litellm-dashboard/src/components/networking.tsx @@ -1411,12 +1411,31 @@ export const availableTeamListCall = async (accessToken: string) => { } }; -export const organizationListCall = async (accessToken: string) => { +export const organizationListCall = async ( + accessToken: string, + org_id: string | null = null, + org_alias: string | null = null, +) => { /** * Get all organizations on proxy */ try { let url = proxyBaseUrl ? `${proxyBaseUrl}/organization/list` : `/organization/list`; + const queryParams = new URLSearchParams(); + + if (org_id) { + queryParams.append("org_id", org_id.toString()); + } + + if (org_alias) { + queryParams.append("org_alias", org_alias.toString()); + } + + const queryString = queryParams.toString(); + if (queryString) { + url += `?${queryString}`; + } + const response = await fetch(url, { method: "GET", headers: { diff --git a/ui/litellm-dashboard/src/components/organizations.tsx b/ui/litellm-dashboard/src/components/organizations.tsx index 32ba210161b..d75f3c84a3d 100644 --- a/ui/litellm-dashboard/src/components/organizations.tsx +++ b/ui/litellm-dashboard/src/components/organizations.tsx @@ -34,6 +34,7 @@ import { formatNumberWithCommas } from "../utils/dataUtils"; import NotificationsManager from "./molecules/notifications_manager"; import DeleteResourceModal from "./common_components/DeleteResourceModal"; import TableIconActionButton from "./common_components/IconActionButton/TableIconActionButtons/TableIconActionButton"; +import OrganizationFilters, { FilterState } from "@/app/(dashboard)/organizations/OrganizationFilters"; interface OrganizationsTableProps { organizations: Organization[]; @@ -51,8 +52,10 @@ interface OrganizationsTableProps { export const fetchOrganizations = async ( accessToken: string, setOrganizations: (organizations: Organization[]) => void, + org_id: string | null = null, + org_alias: string | null = null, ) => { - const organizations = await organizationListCall(accessToken); + const organizations = await organizationListCall(accessToken, org_id, org_alias); setOrganizations(organizations); }; @@ -76,12 +79,51 @@ const OrganizationsTable: React.FC = ({ const [isOrgModalVisible, setIsOrgModalVisible] = useState(false); const [form] = Form.useForm(); const [expandedAccordions, setExpandedAccordions] = useState>({}); + const [showFilters, setShowFilters] = useState(false); + const [filters, setFilters] = useState({ + org_id: "", + org_alias: "", + sort_by: "created_at", + sort_order: "desc", + }); - useEffect(() => { + const handleFilterChange = (key: keyof FilterState, value: string) => { + const newFilters = { ...filters, [key]: value }; + setFilters(newFilters); + // Call organizationListCall with the new filters if (accessToken) { - fetchOrganizations(accessToken, setOrganizations); + organizationListCall(accessToken, newFilters.org_id || null, newFilters.org_alias || null) + .then((response) => { + if (response) { + setOrganizations(response); + } + }) + .catch((error) => { + console.error("Error fetching organizations:", error); + }); } - }, [accessToken]); + }; + + const handleFilterReset = () => { + setFilters({ + org_id: "", + org_alias: "", + sort_by: "created_at", + sort_order: "desc", + }); + // Reset organizations list + if (accessToken) { + organizationListCall(accessToken, null, null) + .then((response) => { + if (response) { + setOrganizations(response); + } + }) + .catch((error) => { + console.error("Error fetching organizations:", error); + }); + } + }; const handleDelete = (orgId: string | null) => { if (!orgId) return; @@ -101,7 +143,7 @@ const OrganizationsTable: React.FC = ({ setIsDeleteModalOpen(false); setOrgToDelete(null); // Refresh organizations list - await fetchOrganizations(accessToken, setOrganizations); + await fetchOrganizations(accessToken, setOrganizations, filters.org_id || null, filters.org_alias || null); } catch (error) { console.error("Error deleting organization:", error); } finally { @@ -148,7 +190,7 @@ const OrganizationsTable: React.FC = ({ setIsOrgModalVisible(false); form.resetFields(); // Refresh organizations list - fetchOrganizations(accessToken, setOrganizations); + fetchOrganizations(accessToken, setOrganizations, filters.org_id || null, filters.org_alias || null); } catch (error) { console.error("Error creating organization:", error); } @@ -217,7 +259,18 @@ const OrganizationsTable: React.FC = ({ Click on “Organization ID” to view organization details. - + +
+
+ +
+
From e783a66f2ab4b4eaf3dd22fe7155eeead5d87ccf Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 17:06:00 -0800 Subject: [PATCH 10/46] Organization Filters UI --- .../OrganizationFilters.test.tsx | 125 ++++++++++++++++++ .../organizations/OrganizationFilters.tsx | 102 ++++---------- .../Filters/FilterInput.test.tsx | 59 +++++++++ .../common_components/Filters/FilterInput.tsx | 51 +++++++ .../Filters/FiltersButton.test.tsx | 37 ++++++ .../Filters/FiltersButton.tsx | 25 ++++ .../Filters/ResetFiltersButton.test.tsx | 29 ++++ .../Filters/ResetFiltersButton.tsx | 16 +++ 8 files changed, 367 insertions(+), 77 deletions(-) create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.test.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.test.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.test.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.test.tsx create mode 100644 ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.tsx diff --git a/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.test.tsx new file mode 100644 index 00000000000..814625ff6be --- /dev/null +++ b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.test.tsx @@ -0,0 +1,125 @@ +import { render, screen, waitFor } from "@testing-library/react"; +import userEvent from "@testing-library/user-event"; +import { describe, expect, it, vi } from "vitest"; +import OrganizationFilters, { FilterState } from "./OrganizationFilters"; + +describe("OrganizationFilters", () => { + const defaultFilters: FilterState = { + org_id: "", + org_alias: "", + sort_by: "", + sort_order: "asc", + }; + + it("should render", () => { + const onToggleFilters = vi.fn(); + const onChange = vi.fn(); + const onReset = vi.fn(); + + render( + , + ); + + expect(screen.getByPlaceholderText("Search by Organization Name")).toBeInTheDocument(); + expect(screen.getByRole("button", { name: /^filters$/i })).toBeInTheDocument(); + expect(screen.getByRole("button", { name: /reset filters/i })).toBeInTheDocument(); + }); + + it("should show additional filters when showFilters is true", () => { + const onToggleFilters = vi.fn(); + const onChange = vi.fn(); + const onReset = vi.fn(); + + render( + , + ); + + expect(screen.getByPlaceholderText("Search by Organization ID")).toBeInTheDocument(); + }); + + it("should call onChange when organization name input changes", async () => { + const user = userEvent.setup(); + const onToggleFilters = vi.fn(); + const onChange = vi.fn(); + const onReset = vi.fn(); + + render( + , + ); + + const input = screen.getByPlaceholderText("Search by Organization Name"); + await user.type(input, "test"); + + await waitFor( + () => { + expect(onChange).toHaveBeenCalledWith("org_alias", expect.any(String)); + }, + { timeout: 500 }, + ); + }); + + it("should call onReset when reset button is clicked", async () => { + const user = userEvent.setup(); + const onToggleFilters = vi.fn(); + const onChange = vi.fn(); + const onReset = vi.fn(); + + render( + , + ); + + const resetButton = screen.getByRole("button", { name: /reset filters/i }); + await user.click(resetButton); + + expect(onReset).toHaveBeenCalledTimes(1); + }); + + it("should show badge on filters button when filters are active", () => { + const onToggleFilters = vi.fn(); + const onChange = vi.fn(); + const onReset = vi.fn(); + + const filtersWithActive: FilterState = { + ...defaultFilters, + org_alias: "test org", + }; + + render( + , + ); + + const filtersButton = screen.getByRole("button", { name: /^filters$/i }); + const badgeWrapper = filtersButton.closest(".ant-badge"); + expect(badgeWrapper).toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx index 9b3fa2fc026..5643a4bc51a 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/organizations/OrganizationFilters.tsx @@ -1,4 +1,7 @@ -import React from "react"; +import { FilterInput } from "@/components/common_components/Filters/FilterInput"; +import { FiltersButton } from "@/components/common_components/Filters/FiltersButton"; +import { ResetFiltersButton } from "@/components/common_components/Filters/ResetFiltersButton"; +import { Search, User } from "lucide-react"; interface OrganizationFiltersProps { filters: FilterState; @@ -22,94 +25,39 @@ const OrganizationFilters = ({ onChange, onReset, }: OrganizationFiltersProps) => { + const hasActiveFilters = !!(filters.org_id || filters.org_alias); + return (
{/* Search and Filter Controls */}
- {/* Organization Alias Search */} -
- onChange("org_alias", e.target.value)} - /> - - - -
+ onChange("org_alias", value)} + icon={Search} + className="w-64" + /> - {/* Filter Button */} - + active={showFilters} + hasActiveFilters={hasActiveFilters} + /> - {/* Reset Filters Button */} - +
{/* Additional Filters */} {showFilters && (
- {/* Organization ID Search */} -
- onChange("org_id", e.target.value)} - /> - - - -
+ onChange("org_id", value)} + icon={User} + className="w-64" + />
)}
diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.test.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.test.tsx new file mode 100644 index 00000000000..e96936e179a --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.test.tsx @@ -0,0 +1,59 @@ +import { act, fireEvent, render, screen } from "@testing-library/react"; +import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"; +import { FilterInput } from "./FilterInput"; + +describe("FilterInput", () => { + beforeEach(() => { + vi.useFakeTimers(); + }); + + afterEach(() => { + vi.runOnlyPendingTimers(); + vi.useRealTimers(); + }); + + it("should render", () => { + const onChange = vi.fn(); + render(); + expect(screen.getByPlaceholderText("Search...")).toBeInTheDocument(); + }); + + it("should call onChange with debounced value", async () => { + const onChange = vi.fn(); + render(); + + const input = screen.getByPlaceholderText("Search..."); + + act(() => { + fireEvent.change(input, { target: { value: "test" } }); + }); + + expect(onChange).not.toHaveBeenCalled(); + + act(() => { + vi.advanceTimersByTime(300); + }); + + expect(onChange).toHaveBeenCalledWith("test"); + }); + + it("should display the value prop", () => { + const onChange = vi.fn(); + render(); + const input = screen.getByPlaceholderText("Search...") as HTMLInputElement; + expect(input.value).toBe("initial value"); + }); + + it("should update local value immediately when typing", async () => { + const onChange = vi.fn(); + render(); + + const input = screen.getByPlaceholderText("Search...") as HTMLInputElement; + + act(() => { + fireEvent.change(input, { target: { value: "a" } }); + }); + + expect(input.value).toBe("a"); + }); +}); diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.tsx new file mode 100644 index 00000000000..3590619ba25 --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/FilterInput.tsx @@ -0,0 +1,51 @@ +import { cx } from "@/lib/cva.config"; +import { Input } from "antd"; +import debounce from "lodash/debounce"; +import { LucideIcon } from "lucide-react"; +import React, { useCallback, useEffect, useMemo, useState } from "react"; + +interface FilterInputProps { + placeholder?: string; + value: string; + onChange: (value: string) => void; + icon?: LucideIcon; + className?: string; + style?: React.CSSProperties; +} + +const DEBOUNCE_DELAY = 300; + +export const FilterInput: React.FC = ({ placeholder, value, onChange, icon: Icon, className }) => { + const [localValue, setLocalValue] = useState(value); + + useEffect(() => { + setLocalValue(value); + }, [value]); + + const debouncedOnChange = useMemo(() => debounce((val: string) => onChange(val), DEBOUNCE_DELAY), [onChange]); + + useEffect(() => { + return () => { + debouncedOnChange.cancel(); + }; + }, [debouncedOnChange]); + + const handleChange = useCallback( + (e: React.ChangeEvent) => { + const newValue = e.target.value; + setLocalValue(newValue); + debouncedOnChange(newValue); + }, + [debouncedOnChange], + ); + + return ( + : undefined} + className={cx("w-64", className)} + /> + ); +}; diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.test.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.test.tsx new file mode 100644 index 00000000000..ccb2c5d9e53 --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.test.tsx @@ -0,0 +1,37 @@ +import { render, screen } from "@testing-library/react"; +import userEvent from "@testing-library/user-event"; +import { describe, expect, it, vi } from "vitest"; +import { FiltersButton } from "./FiltersButton"; + +describe("FiltersButton", () => { + it("should render", () => { + const onClick = vi.fn(); + render(); + expect(screen.getByRole("button", { name: /filters/i })).toBeInTheDocument(); + }); + + it("should call onClick when clicked", async () => { + const user = userEvent.setup(); + const onClick = vi.fn(); + render(); + + const button = screen.getByRole("button", { name: /filters/i }); + await user.click(button); + + expect(onClick).toHaveBeenCalledTimes(1); + }); + + it("should show badge when hasActiveFilters is true", () => { + const onClick = vi.fn(); + const { container } = render(); + const button = screen.getByRole("button", { name: /filters/i }); + const badgeWrapper = button.closest(".ant-badge"); + expect(badgeWrapper).toBeInTheDocument(); + }); + + it("should render custom label when provided", () => { + const onClick = vi.fn(); + render(); + expect(screen.getByRole("button", { name: /advanced filters/i })).toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.tsx new file mode 100644 index 00000000000..09782dd4469 --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/FiltersButton.tsx @@ -0,0 +1,25 @@ +import { Badge, Button } from "antd"; +import { Filter } from "lucide-react"; +import React from "react"; + +interface FiltersButtonProps { + onClick: () => void; + active: boolean; + hasActiveFilters: boolean; + label?: string; +} + +export const FiltersButton: React.FC = ({ + onClick, + active, + hasActiveFilters, + label = "Filters", +}) => { + return ( + + + + ); +}; diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.test.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.test.tsx new file mode 100644 index 00000000000..da37ee1b269 --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.test.tsx @@ -0,0 +1,29 @@ +import { render, screen } from "@testing-library/react"; +import userEvent from "@testing-library/user-event"; +import { describe, expect, it, vi } from "vitest"; +import { ResetFiltersButton } from "./ResetFiltersButton"; + +describe("ResetFiltersButton", () => { + it("should render", () => { + const onClick = vi.fn(); + render(); + expect(screen.getByRole("button", { name: /reset filters/i })).toBeInTheDocument(); + }); + + it("should call onClick when clicked", async () => { + const user = userEvent.setup(); + const onClick = vi.fn(); + render(); + + const button = screen.getByRole("button", { name: /reset filters/i }); + await user.click(button); + + expect(onClick).toHaveBeenCalledTimes(1); + }); + + it("should render custom label when provided", () => { + const onClick = vi.fn(); + render(); + expect(screen.getByRole("button", { name: /clear all/i })).toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.tsx b/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.tsx new file mode 100644 index 00000000000..113d03ddc0b --- /dev/null +++ b/ui/litellm-dashboard/src/components/common_components/Filters/ResetFiltersButton.tsx @@ -0,0 +1,16 @@ +import { Button } from "antd"; +import { RotateCcw } from "lucide-react"; +import React from "react"; + +interface ResetFiltersButtonProps { + onClick: () => void; + label?: string; +} + +export const ResetFiltersButton: React.FC = ({ onClick, label = "Reset Filters" }) => { + return ( + + ); +}; From 0cc935325b9c2c65220097409f0c0688b0af64cb Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Sat, 10 Jan 2026 17:08:00 -0800 Subject: [PATCH 11/46] Fixing build --- .../src/components/organizations.tsx | 51 +++++++++---------- 1 file changed, 25 insertions(+), 26 deletions(-) diff --git a/ui/litellm-dashboard/src/components/organizations.tsx b/ui/litellm-dashboard/src/components/organizations.tsx index d75f3c84a3d..991bf247a41 100644 --- a/ui/litellm-dashboard/src/components/organizations.tsx +++ b/ui/litellm-dashboard/src/components/organizations.tsx @@ -1,40 +1,39 @@ -import React, { useState, useEffect } from "react"; +import OrganizationFilters, { FilterState } from "@/app/(dashboard)/organizations/OrganizationFilters"; +import { InfoCircleOutlined } from "@ant-design/icons"; +import { ChevronDownIcon, ChevronRightIcon, RefreshIcon } from "@heroicons/react/outline"; import { + Badge, + Button, + Card, + Col, + Grid, + Icon, + Tab, + TabGroup, Table, + TableBody, + TableCell, TableHead, TableHeaderCell, - TableBody, TableRow, - TableCell, - Card, - Text, - Badge, - Icon, - Grid, - Col, - Button, - TabGroup, TabList, - Tab, - TabPanels, TabPanel, + TabPanels, + Text, + TextInput, } from "@tremor/react"; -import NumericalInput from "./shared/numerical_input"; -import { Input } from "antd"; -import { Modal, Form, Tooltip, Select as Select2 } from "antd"; -import { InfoCircleOutlined } from "@ant-design/icons"; -import { RefreshIcon, ChevronDownIcon, ChevronRightIcon } from "@heroicons/react/outline"; -import { TextInput } from "@tremor/react"; -import { getModelDisplayName } from "./key_team_helpers/fetch_available_models_team_key"; -import OrganizationInfoView from "./organization/organization_view"; -import { Organization, organizationListCall, organizationCreateCall, organizationDeleteCall } from "./networking"; -import VectorStoreSelector from "./vector_store_management/VectorStoreSelector"; -import MCPServerSelector from "./mcp_server_management/MCPServerSelector"; +import { Form, Input, Modal, Select as Select2, Tooltip } from "antd"; +import React, { useState } from "react"; import { formatNumberWithCommas } from "../utils/dataUtils"; -import NotificationsManager from "./molecules/notifications_manager"; import DeleteResourceModal from "./common_components/DeleteResourceModal"; import TableIconActionButton from "./common_components/IconActionButton/TableIconActionButtons/TableIconActionButton"; -import OrganizationFilters, { FilterState } from "@/app/(dashboard)/organizations/OrganizationFilters"; +import { getModelDisplayName } from "./key_team_helpers/fetch_available_models_team_key"; +import MCPServerSelector from "./mcp_server_management/MCPServerSelector"; +import NotificationsManager from "./molecules/notifications_manager"; +import { Organization, organizationCreateCall, organizationDeleteCall, organizationListCall } from "./networking"; +import OrganizationInfoView from "./organization/organization_view"; +import NumericalInput from "./shared/numerical_input"; +import VectorStoreSelector from "./vector_store_management/VectorStoreSelector"; interface OrganizationsTableProps { organizations: Organization[]; From 1aa63842495eca7fc65e146a8140e0e2c5fc60ea Mon Sep 17 00:00:00 2001 From: Chesars Date: Mon, 12 Jan 2026 09:46:06 -0300 Subject: [PATCH 12/46] fix: resolve mypy type error in _is_potential_model_name_in_model_cost Add explicit str() conversion when calling _get_model_cost_key to satisfy mypy type checking. TypedDict.values() returns object type, not str. --- litellm/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/litellm/utils.py b/litellm/utils.py index 8eb71817111..a75130a31eb 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -4867,7 +4867,7 @@ def _is_potential_model_name_in_model_cost( Check if the potential model name is in the model cost (case-insensitive). """ return any( - _get_model_cost_key(potential_model_name) is not None + _get_model_cost_key(str(potential_model_name)) is not None for potential_model_name in potential_model_names.values() ) From 935c249c4582934d84db443024468fa202a9e7a1 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Mon, 12 Jan 2026 09:53:54 -0500 Subject: [PATCH 13/46] Add end to end integration tests for batches --- tests/batches_tests/local-litellm/README.md | 15 - .../local-litellm/docker-compose.dev.yml | 38 -- .../local-litellm/docker-compose.yml | 109 ---- .../local-litellm/litellm-config.yaml | 57 -- .../local-litellm/mock-server/Dockerfile | 18 - .../local-litellm/mock-server/main.py | 47 -- .../mock-server/mock_azure_batch.py | 582 ------------------ .../local-litellm/mock-server/mock_chat.py | 124 ---- .../mock-server/mock_embeddings.py | 26 - .../mock-server/mock_responses.py | 92 --- .../local-litellm/mock-server/pyproject.toml | 20 - .../local-litellm/mock-server/uv.lock | 416 ------------- .../local-litellm/patches/README.md | 231 ------- .../batches_tests/test_managed_files_base.py | 1 + .../test_managed_files_endtoend.py | 1 + .../test_managed_files_permissions.py | 1 + 16 files changed, 3 insertions(+), 1775 deletions(-) delete mode 100644 tests/batches_tests/local-litellm/README.md delete mode 100644 tests/batches_tests/local-litellm/docker-compose.dev.yml delete mode 100644 tests/batches_tests/local-litellm/docker-compose.yml delete mode 100644 tests/batches_tests/local-litellm/litellm-config.yaml delete mode 100644 tests/batches_tests/local-litellm/mock-server/Dockerfile delete mode 100644 tests/batches_tests/local-litellm/mock-server/main.py delete mode 100644 tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py delete mode 100644 tests/batches_tests/local-litellm/mock-server/mock_chat.py delete mode 100644 tests/batches_tests/local-litellm/mock-server/mock_embeddings.py delete mode 100644 tests/batches_tests/local-litellm/mock-server/mock_responses.py delete mode 100644 tests/batches_tests/local-litellm/mock-server/pyproject.toml delete mode 100644 tests/batches_tests/local-litellm/mock-server/uv.lock delete mode 100644 tests/batches_tests/local-litellm/patches/README.md diff --git a/tests/batches_tests/local-litellm/README.md b/tests/batches_tests/local-litellm/README.md deleted file mode 100644 index b4f5e38fdec..00000000000 --- a/tests/batches_tests/local-litellm/README.md +++ /dev/null @@ -1,15 +0,0 @@ -# Local LiteLLM - -Local LiteLLM proxy with a mock LLM server for testing. - -## Start - -```bash -docker compose up --build -``` - -## Stop - -```bash -docker compose down -``` diff --git a/tests/batches_tests/local-litellm/docker-compose.dev.yml b/tests/batches_tests/local-litellm/docker-compose.dev.yml deleted file mode 100644 index 035b65648e0..00000000000 --- a/tests/batches_tests/local-litellm/docker-compose.dev.yml +++ /dev/null @@ -1,38 +0,0 @@ -# Docker Compose for local development -# Runs db and mock-server only - proxy runs locally via poetry - -services: - db: - image: postgres:16 - container_name: litellm_dev_db - restart: always - environment: - POSTGRES_DB: litellm - POSTGRES_USER: llmproxy - POSTGRES_PASSWORD: dbpassword9090 - healthcheck: - test: ["CMD-SHELL", "pg_isready -d litellm -U llmproxy"] - interval: 1s - timeout: 5s - retries: 10 - volumes: - - postgres_data_dev:/var/lib/postgresql/data - ports: - - "5432:5432" - - mock-server: - build: - context: ./mock-server - dockerfile: Dockerfile - ports: - - "8090:8090" - healthcheck: - test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:8090/health || exit 1"] - interval: 5s - timeout: 5s - retries: 5 - start_period: 10s - -volumes: - postgres_data_dev: - diff --git a/tests/batches_tests/local-litellm/docker-compose.yml b/tests/batches_tests/local-litellm/docker-compose.yml deleted file mode 100644 index 914d659ac81..00000000000 --- a/tests/batches_tests/local-litellm/docker-compose.yml +++ /dev/null @@ -1,109 +0,0 @@ -services: - # Default LiteLLM without patches - litellm: - image: ghcr.io/berriai/litellm:main-latest - profiles: ["default", "unpatched"] - ports: - - "4000:4000" - volumes: - - ./litellm-config.yaml:/app/config.yaml - command: - - "--config=/app/config.yaml" - - "--detailed_debug" - environment: - DATABASE_URL: "postgresql://llmproxy:dbpassword9090@db:5432/litellm" - STORE_MODEL_IN_DB: "True" - LITELLM_MASTER_KEY: "sk-1234" - LITELLM_SALT_KEY: "mock-salt-key-12345" - LITELLM_LOG: "DEBUG" - real_azure_api_key: "${real_azure_api_key:-}" - depends_on: - db: - condition: service_healthy - mock-server: - condition: service_healthy - healthcheck: - test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:4000/health/liveliness || exit 1"] - interval: 30s - timeout: 10s - retries: 3 - start_period: 40s - - # LiteLLM with patches enabled - litellm-patched: - image: ghcr.io/berriai/litellm:main-latest - profiles: ["patched"] - ports: - - "4000:4000" - volumes: - - ./litellm-config.yaml:/app/config.yaml - # patch1 - - ./patches/managed_files.py:/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py - - ./patches/managed_files.py:/app/enterprise/litellm_enterprise/proxy/hooks/managed_files.py - # patch2 - - ./patches/_types.py:/usr/lib/python3.13/site-packages/litellm/proxy/_types.py - - ./patches/_types.py:/app/litellm/proxy/_types.py - # patch3 - - ./patches/batches_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py - - ./patches/batches_endpoints.py:/app/litellm/proxy/batches_endpoints/endpoints.py - # patch4 - - ./patches/files_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py - - ./patches/files_endpoints.py:/app/litellm/proxy/openai_files_endpoints/files_endpoints.py - command: - - "--config=/app/config.yaml" - - "--detailed_debug" - environment: - DATABASE_URL: "postgresql://llmproxy:dbpassword9090@db:5432/litellm" - STORE_MODEL_IN_DB: "True" - LITELLM_MASTER_KEY: "sk-1234" - LITELLM_SALT_KEY: "mock-salt-key-12345" - LITELLM_LOG: "DEBUG" - real_azure_api_key: "${real_azure_api_key:-}" - depends_on: - db: - condition: service_healthy - mock-server: - condition: service_healthy - healthcheck: - test: ["CMD-SHELL", "wget --no-verbose --tries=1 http://localhost:4000/health/liveliness || exit 1"] - interval: 30s - timeout: 10s - retries: 3 - start_period: 40s - - db: - image: postgres:16 - restart: always - container_name: litellm_local_db - environment: - POSTGRES_DB: litellm - POSTGRES_USER: llmproxy - POSTGRES_PASSWORD: dbpassword9090 - ports: - - "5432:5432" - volumes: - - postgres_data:/var/lib/postgresql/data - healthcheck: - test: ["CMD-SHELL", "pg_isready -d litellm -U llmproxy"] - interval: 1s - timeout: 5s - retries: 10 - - mock-server: - build: - context: ./mock-server - dockerfile: Dockerfile - ports: - - "8090:8090" - environment: - TIME_TO_SLEEP: "0" - healthcheck: - test: ["CMD-SHELL", "curl -f http://localhost:8090/health || exit 1"] - interval: 10s - timeout: 5s - retries: 3 - start_period: 5s - -volumes: - postgres_data: - name: litellm_local_postgres_data diff --git a/tests/batches_tests/local-litellm/litellm-config.yaml b/tests/batches_tests/local-litellm/litellm-config.yaml deleted file mode 100644 index 28721f1081c..00000000000 --- a/tests/batches_tests/local-litellm/litellm-config.yaml +++ /dev/null @@ -1,57 +0,0 @@ -model_list: - - model_name: openai-fake-gpt-3.5-turbo - litellm_params: - model: openai/openai-fake-gpt-3.5-turbo - api_base: http://localhost:8090/v1 - api_key: fake-key - - model_name: openai-fake-gpt-4 - litellm_params: - model: openai/openai-fake-gpt-4 - api_base: http://localhost:8090/v1 - api_key: fake-key - - model_name: openai-fake-gpt-4o - litellm_params: - model: openai/openai-fake-gpt-4o - api_base: http://localhost:8090/v1 - api_key: fake-key - - model_name: fake-text-embedding-3-small - litellm_params: - model: openai/fake-text-embedding-3-small - api_base: http://localhost:8090/v1 - api_key: fake-key - - model_name: o3-mini-batch-2025-01-31 - litellm_params: - model: openai/o3-mini-batch-2025-01-31 - api_base: http://localhost:8090/openai/v1 - api_key: fake-key - model_info: - mode: batch - - model_name: azure-fake-gpt-5-batch-2025-08-07 - litellm_params: - api_base: http://localhost:8090 - api_key: fake-key - api_version: 2025-03-01-preview - base_model: azure/gpt-5 - model: azure/gpt-5-batch-2025-08-07 - custom_llm_provider: azure - model_info: - mode: batch - - model_name: gpt-5-batch-2025-08-07 - litellm_params: - api_base: os.environ/OPENAI_API_BASE - api_key: os.environ/OPENAI_API_KEY - api_version: 2025-03-01-preview - base_model: azure/gpt-5 - model: azure/gpt-5-batch-2025-08-07 - custom_llm_provider: azure - model_info: - mode: batch - -general_settings: - master_key: sk-1234 - database_url: "postgresql://llmproxy:dbpassword9090@localhost:5432/litellm" - -litellm_settings: - drop_params: true - set_verbose: true - json_logs: true diff --git a/tests/batches_tests/local-litellm/mock-server/Dockerfile b/tests/batches_tests/local-litellm/mock-server/Dockerfile deleted file mode 100644 index dd31250349c..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/Dockerfile +++ /dev/null @@ -1,18 +0,0 @@ -FROM python:3.11-slim - -RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/* - -WORKDIR /app - -COPY pyproject.toml . -COPY main.py . -COPY mock_azure_batch.py . -COPY mock_chat.py . -COPY mock_responses.py . -COPY mock_embeddings.py . - -RUN pip install --no-cache-dir $(python -c "import tomllib; print(' '.join(tomllib.load(open('pyproject.toml', 'rb'))['project']['dependencies']))") - -EXPOSE 8090 - -CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8090"] diff --git a/tests/batches_tests/local-litellm/mock-server/main.py b/tests/batches_tests/local-litellm/mock-server/main.py deleted file mode 100644 index 943ab36681f..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/main.py +++ /dev/null @@ -1,47 +0,0 @@ -from dotenv import load_dotenv -from fastapi import FastAPI, Request -from fastapi.middleware.cors import CORSMiddleware -from slowapi import Limiter, _rate_limit_exceeded_handler -from slowapi.errors import RateLimitExceeded - -from mock_azure_batch import setup_batch_routes -from mock_chat import setup_chat_routes -from mock_embeddings import setup_embeddings_routes -from mock_responses import setup_responses_routes - - -def get_request_url(request: Request): - return str(request.url) - - -limiter = Limiter(key_func=get_request_url) -load_dotenv() - -app = FastAPI() -app.state.limiter = limiter -app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) - -app.add_middleware( - CORSMiddleware, - allow_origins=["*"], - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], -) - - -@app.get("/health") -async def health(): - return {"status": "ok"} - - -setup_chat_routes(app) -setup_responses_routes(app) -setup_embeddings_routes(app) -setup_batch_routes(app) - - -if __name__ == "__main__": - import uvicorn - - uvicorn.run(app, host="0.0.0.0", port=8090) diff --git a/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py b/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py deleted file mode 100644 index 3512c8472d5..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/mock_azure_batch.py +++ /dev/null @@ -1,582 +0,0 @@ -import asyncio -import io -import json -import logging -import os -import time -import uuid -from typing import Dict, List, Optional - -from fastapi import FastAPI, HTTPException, Query, Request, UploadFile, Depends -from fastapi.responses import StreamingResponse -from fastapi.security import APIKeyHeader -from pydantic import BaseModel - -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - -# Azure-like credential validation -# Set MOCK_REQUIRE_CREDENTIALS=true to enforce credential checks (like real Azure) -REQUIRE_CREDENTIALS = os.environ.get("MOCK_REQUIRE_CREDENTIALS", "true").lower() == "true" -VALID_API_KEYS = {"fake-key", "sk-1234", "test-key"} # Accept these API keys - -api_key_header = APIKeyHeader(name="api-key", auto_error=False) -auth_header = APIKeyHeader(name="Authorization", auto_error=False) - - -def validate_credentials( - api_key: Optional[str] = Depends(api_key_header), - authorization: Optional[str] = Depends(auth_header), -): - """ - Validate Azure-style credentials. - Azure accepts either: - - api-key header - - Authorization: Bearer header - """ - if not REQUIRE_CREDENTIALS: - return True - - # Check api-key header - if api_key: - if api_key in VALID_API_KEYS: - return True - logger.warning(f"Invalid api-key provided: {api_key[:8]}...") - raise HTTPException( - status_code=401, - detail={ - "error": { - "code": "401", - "message": "Access denied due to invalid subscription key or wrong API endpoint. " - "Make sure to provide a valid key for an active subscription and use a " - "correct regional API endpoint for your resource." - } - } - ) - - # Check Authorization header (Bearer token) - if authorization: - if authorization.startswith("Bearer "): - # Accept any bearer token for mock purposes - return True - logger.warning(f"Invalid Authorization header format") - - # No credentials provided - logger.warning("No credentials provided in request") - raise HTTPException( - status_code=401, - detail={ - "error": { - "code": "401", - "message": "Missing credentials. Please pass one of `api_key`, `azure_ad_token`, " - "`azure_ad_token_provider`, or the `AZURE_OPENAI_API_KEY` or " - "`AZURE_OPENAI_AD_TOKEN` environment variables." - } - } - ) - - -class FileObject(BaseModel): - id: str - object: str = "file" - bytes: int - created_at: int - filename: str - purpose: str - status: str = "processed" - status_details: Optional[str] = None - expires_at: Optional[int] = None - - -class BatchObject(BaseModel): - id: str - object: str = "batch" - endpoint: str - errors: Optional[Dict] = None - input_file_id: str - completion_window: str - status: str - output_file_id: Optional[str] = None - error_file_id: Optional[str] = None - created_at: int - in_progress_at: Optional[int] = None - expires_at: Optional[int] = None - finalizing_at: Optional[int] = None - completed_at: Optional[int] = None - failed_at: Optional[int] = None - expired_at: Optional[int] = None - cancelling_at: Optional[int] = None - cancelled_at: Optional[int] = None - request_counts: Optional[Dict[str, int]] = None - metadata: Optional[Dict] = None - - -class BatchListResponse(BaseModel): - object: str = "list" - data: List[Dict] - first_id: Optional[str] = None - last_id: Optional[str] = None - has_more: bool = False - - -file_storage: Dict[str, Dict] = {} -batch_storage: Dict[str, BatchObject] = {} -batch_results: Dict[str, List[Dict]] = {} - -PROCESSING_DELAY_SECONDS = float(1) -VALIDATING_DELAY_SECONDS = float(3) - - -async def process_batch(batch_id: str): - logger.info(f"Starting batch processing for {batch_id}") - try: - batch = batch_storage[batch_id] - - await asyncio.sleep(VALIDATING_DELAY_SECONDS) - batch.status = "in_progress" - batch.in_progress_at = int(time.time()) - logger.info(f"Batch {batch_id} status: in_progress") - - await process_batch_requests(batch_id) - await asyncio.sleep(PROCESSING_DELAY_SECONDS) - - batch.status = "finalizing" - batch.finalizing_at = int(time.time()) - logger.info(f"Batch {batch_id} status: finalizing") - await asyncio.sleep(PROCESSING_DELAY_SECONDS) - - await create_output_file(batch_id) - - batch.status = "completed" - batch.completed_at = int(time.time()) - logger.info(f"Batch {batch_id} status: completed") - - except Exception as e: - logger.error(f"Batch {batch_id} failed: {e}") - batch = batch_storage[batch_id] - batch.status = "failed" - batch.failed_at = int(time.time()) - batch.errors = { - "object": "list", - "data": [{"code": "processing_error", "message": str(e)}], - } - - -async def process_batch_requests(batch_id: str): - batch = batch_storage[batch_id] - input_file = file_storage[batch.input_file_id] - - requests = [] - for line in input_file["content"].split("\n"): - if line.strip(): - try: - requests.append(json.loads(line)) - except json.JSONDecodeError as e: - logger.warning(f"Invalid JSON line in batch {batch_id}: {e}") - - logger.info(f"Batch {batch_id} has {len(requests)} requests") - - results = [] - failed_count = 0 - for req in requests: - result = await process_single_request(req) - if result.get("error"): - failed_count += 1 - results.append(result) - - batch_results[batch_id] = results - batch.request_counts = { - "total": len(requests), - "completed": len(results) - failed_count, - "failed": failed_count, - } - - -async def process_single_request(request_data: Dict) -> Dict: - custom_id = request_data.get("custom_id") - url = request_data.get("url", "/v1/chat/completions") - body = request_data.get("body", {}) - - if "/chat/completions" in url: - response_body = { - "id": f"chatcmpl-{uuid.uuid4().hex}", - "object": "chat.completion", - "created": int(time.time()), - "model": body.get("model", "gpt-4o"), - "choices": [ - { - "index": 0, - "message": {"role": "assistant", "content": "Mock batch response."}, - "finish_reason": "stop", - }, - ], - "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}, - } - status_code = 200 - else: - response_body = {"error": {"message": f"Unsupported endpoint: {url}"}} - status_code = 400 - - return { - "id": f"batch_req_{uuid.uuid4().hex[:12]}", - "custom_id": custom_id, - "response": { - "status_code": status_code, - "request_id": f"req_{uuid.uuid4().hex[:12]}", - "body": response_body, - }, - "error": None, - } - - -async def create_output_file(batch_id: str): - results = batch_results.get(batch_id, []) - output_lines = [json.dumps(result) for result in results] - output_content = "\n".join(output_lines) - - output_file_id = f"file-batch-output-{uuid.uuid4().hex[:12]}" - file_storage[output_file_id] = { - "content": output_content, - "filename": f"batch_output_{batch_id}.jsonl", - "purpose": "batch_output", - "bytes": len(output_content.encode()), - "created_at": int(time.time()), - } - - batch = batch_storage[batch_id] - batch.output_file_id = output_file_id - logger.info(f"Created output file {output_file_id} for batch {batch_id}") - - -def validate_batch_input(content: str) -> tuple[bool, str, List[Dict]]: - requests = [] - custom_ids = set() - - lines = content.strip().split("\n") - if not lines or all(not line.strip() for line in lines): - return False, "empty_batch", [] - - for line_num, line in enumerate(lines, 1): - if not line.strip(): - continue - try: - req = json.loads(line) - except json.JSONDecodeError: - return False, "invalid_json_line", [] - - for field in ["custom_id", "method", "url", "body"]: - if field not in req: - return False, "invalid_request", [] - - if req["custom_id"] in custom_ids: - return False, "duplicate_custom_id", [] - custom_ids.add(req["custom_id"]) - - requests.append(req) - - if len(requests) > 100000: - return False, "too_many_tasks", [] - - return True, "", requests - - -def setup_batch_routes(app: FastAPI): - # Files endpoints (OpenAI and Azure paths) - # All endpoints require credentials (like real Azure) - @app.post("/openai/v1/files") - @app.post("/openai/files") - @app.post("/v1/files") - @app.post("/files") - async def create_file(request: Request, _=Depends(validate_credentials)): - form = await request.form() - logger.info(f"File upload form fields: {list(form.keys())}") - - file: UploadFile = form.get("file") - purpose: str = form.get("purpose", "batch") - - if not file: - raise HTTPException(status_code=400, detail="No file provided") - - logger.info(f"Uploading file: {file.filename}, purpose: {purpose}") - - content = await file.read() - content_str = content.decode("utf-8") - - file_id = f"file-{uuid.uuid4().hex[:24]}" - created_at = int(time.time()) - - expires_at = None - expires_after_seconds = form.get("expires_after[seconds]") - if expires_after_seconds: - try: - seconds = int(expires_after_seconds) - logger.info(f"expires_after[seconds] = {seconds}") - if seconds < 259200 or seconds > 2592000: - raise HTTPException( - status_code=400, - detail={ - "error": { - "code": "invalidPayload", - "message": "Value for Seconds must be between 259200 and 2592000.", - }, - }, - ) - expires_at = created_at + seconds - logger.info(f"Calculated expires_at: {expires_at}") - except ValueError as e: - logger.warning(f"Failed to parse expires_after[seconds]: {e}") - - file_storage[file_id] = { - "content": content_str, - "filename": file.filename or "batch_input.jsonl", - "purpose": purpose, - "bytes": len(content), - "created_at": created_at, - "expires_at": expires_at, - } - - logger.info(f"Created file {file_id}, expires_at={expires_at}") - return FileObject( - id=file_id, - bytes=len(content), - created_at=created_at, - filename=file.filename or "batch_input.jsonl", - purpose=purpose, - expires_at=expires_at, - ).model_dump() - - @app.get("/openai/v1/files/{file_id}") - @app.get("/openai/files/{file_id}") - @app.get("/v1/files/{file_id}") - @app.get("/files/{file_id}") - async def get_file(file_id: str, _=Depends(validate_credentials)): - logger.info(f"Getting file: {file_id}") - if file_id not in file_storage: - raise HTTPException(status_code=404, detail="File not found") - - file_data = file_storage[file_id] - return FileObject( - id=file_id, - bytes=file_data["bytes"], - created_at=file_data["created_at"], - filename=file_data["filename"], - purpose=file_data["purpose"], - expires_at=file_data.get("expires_at"), - ).model_dump() - - @app.get("/openai/v1/files/{file_id}/content") - @app.get("/openai/files/{file_id}/content") - @app.get("/v1/files/{file_id}/content") - @app.get("/files/{file_id}/content") - async def get_file_content(file_id: str, _=Depends(validate_credentials)): - logger.info(f"Getting file content: {file_id}") - if file_id not in file_storage: - raise HTTPException(status_code=404, detail="File not found") - - file_data = file_storage[file_id] - content = file_data["content"] - - return StreamingResponse( - io.StringIO(content), - media_type="application/octet-stream", - headers={ - "Content-Disposition": f"attachment; filename={file_data['filename']}", - }, - ) - - @app.delete("/openai/v1/files/{file_id}") - @app.delete("/openai/files/{file_id}") - @app.delete("/v1/files/{file_id}") - @app.delete("/files/{file_id}") - async def delete_file(file_id: str, _=Depends(validate_credentials)): - logger.info(f"Deleting file: {file_id}") - if file_id not in file_storage: - raise HTTPException(status_code=404, detail="File not found") - - del file_storage[file_id] - return {"id": file_id, "object": "file", "deleted": True} - - @app.get("/openai/v1/files") - @app.get("/openai/files") - @app.get("/v1/files") - @app.get("/files") - async def list_files( - purpose: Optional[str] = None, - limit: int = Query(10000, le=10000), - _=Depends(validate_credentials), - ): - logger.info(f"Listing files, purpose: {purpose}, limit: {limit}") - files = [] - for file_id, file_data in file_storage.items(): - if purpose is None or file_data.get("purpose") == purpose: - files.append( - FileObject( - id=file_id, - bytes=file_data["bytes"], - created_at=file_data["created_at"], - filename=file_data["filename"], - purpose=file_data["purpose"], - expires_at=file_data.get("expires_at"), - ).model_dump(), - ) - return {"object": "list", "data": files[:limit]} - - # Batches endpoints (OpenAI and Azure paths) - @app.post("/openai/v1/batches") - @app.post("/openai/batches") - @app.post("/v1/batches") - @app.post("/batches") - async def create_batch(request_data: dict, _=Depends(validate_credentials)): - input_file_id = request_data.get("input_file_id") - endpoint = request_data.get("endpoint", "/v1/chat/completions") - completion_window = request_data.get("completion_window", "24h") - metadata = request_data.get("metadata", {}) - output_expires_after = request_data.get("output_expires_after") - - logger.info( - f"Creating batch with input_file: {input_file_id}, endpoint: {endpoint}, output_expires_after: {output_expires_after}", - ) - - if not input_file_id or input_file_id not in file_storage: - raise HTTPException(status_code=400, detail="Input file not found") - - input_file = file_storage[input_file_id] - is_valid, error_code, _ = validate_batch_input(input_file["content"]) - if not is_valid: - raise HTTPException( - status_code=400, - detail={ - "error": { - "code": error_code, - "message": f"Validation failed: {error_code}", - }, - }, - ) - - batch_id = f"batch_{uuid.uuid4()}" - created_at = int(time.time()) - - if output_expires_after: - seconds = ( - output_expires_after.get("seconds", 0) - if isinstance(output_expires_after, dict) - else 0 - ) - expires_at = created_at + seconds - logger.info( - f"Using output_expires_after: {seconds}s, expires_at: {expires_at}", - ) - elif completion_window == "24h": - expires_at = created_at + (24 * 60 * 60) - else: - expires_at = created_at + (24 * 60 * 60) - - batch = BatchObject( - id=batch_id, - endpoint=endpoint, - input_file_id=input_file_id, - completion_window=completion_window, - status="validating", - created_at=created_at, - expires_at=expires_at, - request_counts={"total": 0, "completed": 0, "failed": 0}, - metadata=metadata, - ) - - batch_storage[batch_id] = batch - logger.info(f"Created batch {batch_id}") - - asyncio.create_task(process_batch(batch_id)) - - return batch.model_dump() - - @app.get("/openai/v1/batches/{batch_id}") - @app.get("/openai/batches/{batch_id}") - @app.get("/v1/batches/{batch_id}") - @app.get("/batches/{batch_id}") - async def get_batch(batch_id: str, _=Depends(validate_credentials)): - logger.info(f"Getting batch: {batch_id}") - if batch_id not in batch_storage: - raise HTTPException(status_code=404, detail="Batch not found") - - return batch_storage[batch_id].model_dump() - - @app.get("/openai/v1/batches") - @app.get("/openai/batches") - @app.get("/v1/batches") - @app.get("/batches") - async def list_batches( - after: Optional[str] = Query(None), - limit: int = Query(20, le=100), - _=Depends(validate_credentials), - ): - logger.info(f"Listing batches, after: {after}, limit: {limit}") - batches = list(batch_storage.values()) - batches.sort(key=lambda x: x.created_at, reverse=True) - - if after: - after_index = next((i for i, b in enumerate(batches) if b.id == after), -1) - if after_index >= 0: - batches = batches[after_index + 1 :] - - batches = batches[:limit] - - return BatchListResponse( - data=[batch.model_dump() for batch in batches], - first_id=batches[0].id if batches else None, - last_id=batches[-1].id if batches else None, - has_more=len(batches) == limit, - ).model_dump() - - @app.post("/openai/v1/batches/{batch_id}/cancel") - @app.post("/openai/batches/{batch_id}/cancel") - @app.post("/v1/batches/{batch_id}/cancel") - @app.post("/batches/{batch_id}/cancel") - async def cancel_batch(batch_id: str, _=Depends(validate_credentials)): - logger.info(f"Cancelling batch: {batch_id}") - if batch_id not in batch_storage: - raise HTTPException(status_code=404, detail="Batch not found") - - batch = batch_storage[batch_id] - if batch.status in ["completed", "failed", "cancelled", "expired"]: - raise HTTPException( - status_code=400, - detail=f"Cannot cancel batch in {batch.status} status", - ) - - batch.status = "cancelled" - batch.cancelled_at = int(time.time()) - logger.info(f"Batch {batch_id} cancelled") - - return batch.model_dump() - - # Debug endpoints - @app.get("/debug/batches") - async def debug_list_batches(): - return { - "batches": { - batch_id: batch.model_dump() - for batch_id, batch in batch_storage.items() - }, - "files": { - file_id: {k: v for k, v in data.items() if k != "content"} - for file_id, data in file_storage.items() - }, - } - - @app.post("/reset") - @app.post("/debug/clear") - async def reset_all(): - file_storage.clear() - batch_storage.clear() - batch_results.clear() - logger.info("All data cleared") - return {"message": "All data cleared"} - - @app.get("/debug/status") - async def debug_status(): - return { - "files_count": len(file_storage), - "batches_count": len(batch_storage), - "batch_statuses": {bid: b.status for bid, b in batch_storage.items()}, - } diff --git a/tests/batches_tests/local-litellm/mock-server/mock_chat.py b/tests/batches_tests/local-litellm/mock-server/mock_chat.py deleted file mode 100644 index c33523579a5..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/mock_chat.py +++ /dev/null @@ -1,124 +0,0 @@ -import json -import time -import uuid -from datetime import datetime - -from fastapi import FastAPI, Request -from fastapi.responses import StreamingResponse - - -def get_request_details(request: Request, body: dict = None) -> str: - details = { - "method": request.method, - "url": str(request.url), - "path": request.url.path, - "headers": dict(request.headers), - "query_params": dict(request.query_params), - } - return json.dumps(details, indent=2) - - -def data_generator(response_details: str, model: str): - response_id = uuid.uuid4().hex - content = response_details - chunk_size = 50 - for i in range(0, len(content), chunk_size): - text_chunk = content[i : i + chunk_size] - chunk = { - "id": f"chatcmpl-{response_id}", - "object": "chat.completion.chunk", - "created": int(time.time()), - "model": model, - "choices": [{"index": 0, "delta": {"content": text_chunk}}], - } - yield f"data: {json.dumps(chunk)}\n\n" - final_chunk = { - "id": f"chatcmpl-{response_id}", - "object": "chat.completion.chunk", - "created": int(time.time()), - "model": model, - "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}], - } - yield f"data: {json.dumps(final_chunk)}\n\n" - yield "data: [DONE]\n\n" - - -def setup_chat_routes(app: FastAPI): - @app.post("/chat/completions") - @app.post("/v1/chat/completions") - @app.post("/openai/deployments/{model:path}/chat/completions") - async def completion(request: Request): - data = await request.json() - model = data.get("model", "unknown") - request_details = get_request_details(request, data) - timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - response_details = f"Request:{request_details}, Canned Response:{timestamp}" - - if data.get("stream"): - return StreamingResponse( - content=data_generator(response_details, model), - media_type="text/event-stream", - ) - else: - response_id = uuid.uuid4().hex - response = { - "id": f"chatcmpl-{response_id}", - "object": "chat.completion", - "created": int(time.time()), - "model": model, - "system_fingerprint": "fp_mock_server", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": response_details, - }, - "logprobs": None, - "finish_reason": "stop", - }, - ], - "usage": { - "prompt_tokens": 9, - "completion_tokens": 12, - "total_tokens": 21, - }, - } - return response - - @app.post("/completions") - @app.post("/v1/completions") - async def text_completion(request: Request): - data = await request.json() - model = data.get("model", "unknown") - request_details = get_request_details(request, data) - timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - response_details = f"Request:{request_details}, Canned Response:{timestamp}" - - if data.get("stream"): - return StreamingResponse( - content=data_generator(response_details, model), - media_type="text/event-stream", - ) - else: - response = { - "id": f"cmpl-{uuid.uuid4().hex}", - "choices": [ - { - "finish_reason": "stop", - "index": 0, - "logprobs": None, - "text": response_details, - }, - ], - "created": int(time.time()), - "model": model, - "object": "text_completion", - "system_fingerprint": None, - "usage": { - "completion_tokens": 16, - "prompt_tokens": 10, - "total_tokens": 26, - }, - } - return response diff --git a/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py b/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py deleted file mode 100644 index 9f7aa46adcd..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/mock_embeddings.py +++ /dev/null @@ -1,26 +0,0 @@ -from fastapi import FastAPI, Request - - -def setup_embeddings_routes(app: FastAPI): - @app.post("/embeddings") - @app.post("/v1/embeddings") - @app.post("/openai/deployments/{model:path}/embeddings") - async def embeddings(request: Request): - data = await request.json() - model = data.get("model", "unknown") - _small_embedding = [ - -0.006929283495992422, - -0.005336422007530928, - -4.547132266452536e-05, - -0.024047505110502243, - ] - big_embedding = _small_embedding * 100 - return { - "object": "list", - "data": [{"object": "embedding", "index": 0, "embedding": big_embedding}], - "model": model, - "usage": {"prompt_tokens": 5, "total_tokens": 5}, - } - - - diff --git a/tests/batches_tests/local-litellm/mock-server/mock_responses.py b/tests/batches_tests/local-litellm/mock-server/mock_responses.py deleted file mode 100644 index 40e7ae34fbd..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/mock_responses.py +++ /dev/null @@ -1,92 +0,0 @@ -import json -import time -import uuid -from datetime import datetime - -from fastapi import FastAPI, Request - - -def get_request_details(request: Request, body: dict = None) -> str: - details = { - "method": request.method, - "url": str(request.url), - "path": request.url.path, - "headers": dict(request.headers), - "query_params": dict(request.query_params), - } - return json.dumps(details, indent=2) - - -def setup_responses_routes(app: FastAPI): - @app.post("/responses") - @app.post("/v1/responses") - @app.post("/openai/responses") - async def responses_api(request: Request): - data = await request.json() - model = data.get("model", "unknown") - request_details = get_request_details(request, data) - timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - response_details = f"Request:{request_details}, Canned Response:{timestamp}" - response_id = uuid.uuid4().hex - message_id = f"msg_{uuid.uuid4().hex[:34]}" - return { - "id": f"resp_{response_id}", - "created_at": int(time.time()), - "error": None, - "incomplete_details": None, - "instructions": None, - "metadata": {}, - "model": model, - "object": "response", - "output": [ - { - "id": message_id, - "content": [ - { - "annotations": [], - "text": response_details, - "type": "output_text", - "logprobs": [], - }, - ], - "role": "assistant", - "status": "completed", - "type": "message", - }, - ], - "parallel_tool_calls": True, - "temperature": data.get("temperature", 1.0), - "tool_choice": data.get("tool_choice", "auto"), - "tools": data.get("tools", []), - "top_p": data.get("top_p", 1.0), - "max_output_tokens": data.get("max_output_tokens"), - "previous_response_id": None, - "reasoning": {"effort": None, "summary": None}, - "status": "completed", - "text": {"format": {"type": "text"}, "verbosity": "medium"}, - "truncation": "disabled", - "usage": { - "input_tokens": 11, - "input_tokens_details": { - "audio_tokens": None, - "cached_tokens": 0, - "text_tokens": None, - }, - "output_tokens": 19, - "output_tokens_details": {"reasoning_tokens": 0, "text_tokens": None}, - "total_tokens": 30, - 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File Deletion Fails for Batch Output Files - -### Broken Feature - -`DELETE /files/{file_id}` - Deleting batch output files fails with a Pydantic validation error. - -### Error Message - -``` -openai.InternalServerError: Error code: 500 - { - 'error': { - 'message': '1 validation error for LiteLLM_ManagedFileTable\nfile_object\n Input should be a valid dictionary or instance of OpenAIFileObject [type=model_type, input_value=None, input_type=NoneType]' - } -} -``` - -### Root Cause - -When LiteLLM stores batch output files in `LiteLLM_ManagedFileTable`, it sets `file_object=None`. However, the Pydantic model requires this field to be a valid `OpenAIFileObject`. - -### Code Change (`_types.py`) - -```python -# Before -class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): - file_object: OpenAIFileObject - -# After -class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): - file_object: Optional[OpenAIFileObject] = None # PATCHED -``` - ---- - -## 2. File Deletion Returns Wrong Response - -### Broken Feature - -`DELETE /files/{file_id}` - Even after fixing patch #1, the method returns `None` instead of the delete confirmation. - -### Error Message - -``` -Exception: LiteLLM Managed File object with id=... not found -``` - -### Root Cause - -`afile_delete` in `managed_files.py` calls `llm_router.afile_delete` (which deletes the file at the provider) but discards the response. - -### Code Change (`managed_files.py`) - -```python -# Before -async def afile_delete(self, file_id, ...): - for model_id, model_file_id in mapping.items(): - await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) - # Returns None - -# After -async def afile_delete(self, file_id, ...): - delete_response = None - for model_id, model_file_id in mapping.items(): - delete_response = await llm_router.afile_delete(...) # PATCHED: Capture response - if delete_response: - delete_response.id = file_id # PATCHED: Replace with unified ID - return delete_response -``` - ---- - -## 3. Batch Listing Fails with Duplicate Argument - -### Broken Feature - -`GET /batches?target_model_names=...` - Listing batches fails when using `target_model_names` query parameter. - -### Error Message - -``` -openai.InternalServerError: Error code: 500 - { - 'error': { - 'message': "alist_batches() got multiple values for keyword argument 'model'" - } -} -``` - -### Root Cause - -The code passes `model` explicitly AND includes it in `**data`: - -```python -model = target_model_names.split(",")[0] -response = await llm_router.alist_batches( - model=model, # Passed explicitly - **data, # Also contains 'model' key -) -``` - -### Code Change (`batches_endpoints.py`) - -```python -# Before -model = target_model_names.split(",")[0] -response = await llm_router.alist_batches(model=model, **data) - -# After -model = target_model_names.split(",")[0] -data.pop("model", None) # PATCHED: Remove duplicate -data.pop("target_model_names", None) # PATCHED: Remove to avoid passing to downstream -response = await llm_router.alist_batches(model=model, **data) -``` - ---- - -## 4. File Retrieve Returns None for Batch Output Files - -### Broken Feature - -`GET /files/{file_id}` - Retrieving batch output file metadata returns `None`. - -### Error Message - -``` -AttributeError: 'NoneType' object has no attribute 'id' -``` - -### Root Cause - -`afile_retrieve` returns `stored_file_object.file_object` which is `None` for batch output files. It should fetch from the provider. - -### Code Change (`managed_files.py` + `files_endpoints.py`) - -```python -# managed_files.py - After -async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router=None): - stored = await self.get_unified_file_id(file_id, ...) - if stored.file_object: - return stored.file_object - # PATCHED: Fetch from provider when file_object is None - for model_id, model_file_id in stored.model_mappings.items(): - response = await llm_router.afile_retrieve(model=model_id, file_id=model_file_id) - response.id = file_id - return response -``` - -```python -# files_endpoints.py - After -response = await managed_files_obj.afile_retrieve( - file_id=file_id, - litellm_parent_otel_span=user_api_key_dict.parent_otel_span, - llm_router=llm_router, # PATCHED: Pass router -) -``` - ---- - -## Known Issues (Not Bugs) - -### Azure Batch Creation Response Missing `endpoint` - -**Behavior:** Azure's batch creation response returns `endpoint=''` (empty string). - -**Expected:** When you call `batches.retrieve()` or `batches.list()`, Azure returns `endpoint='/v1/chat/completions'` correctly. - -**Workaround:** If you need the endpoint immediately after creation, retrieve the batch to get the correct value. - -### Azure Batch Listing Returns Raw IDs - -**Behavior:** `batches.list()` returns raw Azure batch IDs (e.g., `batch_abc123`) instead of LiteLLM unified IDs. - -**Root Cause:** LiteLLM routes `batches.list()` directly to Azure instead of querying its internal managed batches database. - -**Workaround:** Use `batches.retrieve(unified_batch_id)` instead of relying on list. - -### Config Fix: Azure Batch Listing 404 - -**Behavior:** `batches.list()` returns empty results because Azure returns 404. - -**Root Cause:** LiteLLM defaults to OpenAI handler instead of Azure handler for batch operations. - -**Fix (config):** Add `custom_llm_provider: azure` to your model's `litellm_params`: - -```yaml -litellm_params: - model: azure/gpt-5-batch - custom_llm_provider: azure # Required for Azure batch operations -``` - ---- - -## Patch Files - -| Patch File | Container Path | -|------------|----------------| -| `_types.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/_types.py` | -| `managed_files.py` | `/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py` | -| `batches_endpoints.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py` | -| `files_endpoints.py` | `/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py` | - ---- - -## Usage - -### With Patches - -```bash -./start-patched.sh -``` - -### Without Patches - -```bash -./start-unpatched.sh -``` - -### Docker Compose Volumes - -```yaml -volumes: - - ./patches/_types.py:/usr/lib/python3.13/site-packages/litellm/proxy/_types.py - - ./patches/managed_files.py:/usr/lib/python3.13/site-packages/litellm_enterprise/proxy/hooks/managed_files.py - - ./patches/batches_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/batches_endpoints/endpoints.py - - ./patches/files_endpoints.py:/usr/lib/python3.13/site-packages/litellm/proxy/openai_files_endpoints/files_endpoints.py -``` diff --git a/tests/batches_tests/test_managed_files_base.py b/tests/batches_tests/test_managed_files_base.py index 9ea6d58355f..4b5d2463014 100644 --- a/tests/batches_tests/test_managed_files_base.py +++ b/tests/batches_tests/test_managed_files_base.py @@ -218,3 +218,4 @@ class ManagedFilesBase: + diff --git a/tests/batches_tests/test_managed_files_endtoend.py b/tests/batches_tests/test_managed_files_endtoend.py index 828060e9cd5..21de9717dc4 100644 --- a/tests/batches_tests/test_managed_files_endtoend.py +++ b/tests/batches_tests/test_managed_files_endtoend.py @@ -202,3 +202,4 @@ class TestManagedFilesAPI(ManagedFilesBase): + diff --git a/tests/batches_tests/test_managed_files_permissions.py b/tests/batches_tests/test_managed_files_permissions.py index c4b9e8828f4..e23eb9198a9 100644 --- a/tests/batches_tests/test_managed_files_permissions.py +++ b/tests/batches_tests/test_managed_files_permissions.py @@ -434,3 +434,4 @@ class TestManagedFilesPermissions(ManagedFilesBase): + From 3256eb21a02c79f9824ab0a918e40ebc6d7ad34b Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Mon, 12 Jan 2026 10:43:09 -0500 Subject: [PATCH 14/46] Add end to end integration tests for batches --- litellm/llms/base_llm/files/transformation.py | 1 + .../test_files_endpoint.py | 24 +++++++++---------- 2 files changed, 13 insertions(+), 12 deletions(-) diff --git a/litellm/llms/base_llm/files/transformation.py b/litellm/llms/base_llm/files/transformation.py index 35b76479cdc..9b3f3a58c11 100644 --- a/litellm/llms/base_llm/files/transformation.py +++ b/litellm/llms/base_llm/files/transformation.py @@ -136,6 +136,7 @@ class BaseFileEndpoints(ABC): self, file_id: str, litellm_parent_otel_span: Optional[Span], + llm_router: Optional[Router] = None, ) -> OpenAIFileObject: pass diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py index 36f0ab5097d..4651bf59b40 100644 --- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py +++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py @@ -158,16 +158,16 @@ def test_mock_create_audio_file(mocker: MockerFixture, monkeypatch, llm_router: status="uploaded", ) - async def afile_retrieve(self, file_id, litellm_parent_otel_span): + async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router): raise NotImplementedError("Not implemented for test") async def afile_list(self, purpose, litellm_parent_otel_span): raise NotImplementedError("Not implemented for test") - async def afile_delete(self, file_id, litellm_parent_otel_span): + async def afile_delete(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") - async def afile_content(self, file_id, litellm_parent_otel_span): + async def afile_content(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") # Manually add the hook to the proxy_hook_mapping @@ -607,16 +607,16 @@ def test_create_file_with_expires_after(mocker: MockerFixture, monkeypatch, llm_ status="uploaded", ) - async def afile_retrieve(self, file_id, litellm_parent_otel_span): + async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router): raise NotImplementedError("Not implemented for test") async def afile_list(self, purpose, litellm_parent_otel_span): raise NotImplementedError("Not implemented for test") - async def afile_delete(self, file_id, litellm_parent_otel_span): + async def afile_delete(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") - async def afile_content(self, file_id, litellm_parent_otel_span): + async def afile_content(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") proxy_logging_obj.proxy_hook_mapping["managed_files"] = DummyManagedFiles() @@ -747,16 +747,16 @@ def test_create_file_with_expires_after_valid_values(mocker: MockerFixture, monk status="uploaded", ) - async def afile_retrieve(self, file_id, litellm_parent_otel_span): + async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router): raise NotImplementedError("Not implemented for test") async def afile_list(self, purpose, litellm_parent_otel_span): raise NotImplementedError("Not implemented for test") - async def afile_delete(self, file_id, litellm_parent_otel_span): + async def afile_delete(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") - async def afile_content(self, file_id, litellm_parent_otel_span): + async def afile_content(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") proxy_logging_obj.proxy_hook_mapping["managed_files"] = DummyManagedFiles() @@ -820,16 +820,16 @@ def test_create_file_without_expires_after(mocker: MockerFixture, monkeypatch, l status="uploaded", ) - async def afile_retrieve(self, file_id, litellm_parent_otel_span): + async def afile_retrieve(self, file_id, litellm_parent_otel_span, llm_router): raise NotImplementedError("Not implemented for test") async def afile_list(self, purpose, litellm_parent_otel_span): raise NotImplementedError("Not implemented for test") - async def afile_delete(self, file_id, litellm_parent_otel_span): + async def afile_delete(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") - async def afile_content(self, file_id, litellm_parent_otel_span): + async def afile_content(self, file_id, litellm_parent_otel_span, llm_router, **data): raise NotImplementedError("Not implemented for test") proxy_logging_obj.proxy_hook_mapping["managed_files"] = DummyManagedFiles() From 2763b919600cfb173abfb9c7df2d01426ea53cec Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Mon, 12 Jan 2026 13:55:27 -0500 Subject: [PATCH 15/46] Add end to end integration tests for batches --- BATCH_FIXES_README.md | 239 ------------------------------------------ 1 file changed, 239 deletions(-) delete mode 100644 BATCH_FIXES_README.md diff --git a/BATCH_FIXES_README.md b/BATCH_FIXES_README.md deleted file mode 100644 index e04f18b900f..00000000000 --- a/BATCH_FIXES_README.md +++ /dev/null @@ -1,239 +0,0 @@ -# LiteLLM Batch API Fixes - -This document describes bugs found in LiteLLM's managed batch/files functionality and the patches applied to fix them. It also provides step-by-step instructions to reproduce the tests from a clean slate. - -## Table of Contents - -1. [Bug 1: File Deletion Fails for Batch Output Files](#bug-1-file-deletion-fails-for-batch-output-files) -2. [Bug 2: File Deletion Returns Wrong Response](#bug-2-file-deletion-returns-wrong-response) -3. [Bug 3: File Retrieve Returns None for Batch Output Files](#bug-3-file-retrieve-returns-none-for-batch-output-files) -4. [Known Limitation: Error Files Not Retrievable](#known-limitation-error-files-not-retrievable) -6. [Test Setup Instructions](#test-setup-instructions) - ---- - -## Bug 1: File Deletion Fails for Batch Output Files - -### Description - -**Broken Feature:** `DELETE /files/{file_id}` - Deleting batch output files fails with a Pydantic validation error. - -**Error Message:** -``` -openai.InternalServerError: Error code: 500 - { - 'error': { - 'message': '1 validation error for LiteLLM_ManagedFileTable\nfile_object\n Input should be a valid dictionary or instance of OpenAIFileObject [type=model_type, input_value=None, input_type=NoneType]' - } -} -``` - -**Root Cause:** When LiteLLM stores batch output files in `LiteLLM_ManagedFileTable`, it sets `file_object=None`. However, the Pydantic model requires this field to be a valid `OpenAIFileObject`. - ---- - -## Bug 2: File Deletion Returns Wrong Response - -### Description - -**Broken Feature:** `DELETE /files/{file_id}` - Even after fixing Bug #1, the method returns `None` instead of the delete confirmation. - -**Error Message:** -``` -Exception: LiteLLM Managed File object with id=... not found -``` - -**Root Cause:** `afile_delete` in `managed_files.py` calls `llm_router.afile_delete()` (which deletes the file at the provider) but discards the response. - ---- - -## Bug 3: File Retrieve Returns None for Batch Output Files - -### Description - -**Broken Feature:** `GET /files/{file_id}` - Retrieving batch output file metadata returns `None`. - -**Error Message:** -``` -AttributeError: 'NoneType' object has no attribute 'id' -``` - -**Root Cause:** `afile_retrieve` returns `stored_file_object.file_object` which is `None` for batch output files. It should fetch the file metadata from the provider instead. - ---- - -## Known Limitation: Error Files Not Retrievable - -### Description - -When a batch fails, the provider returns an `error_file_id` containing details about failed requests. Currently, **error files are NOT retrievable** through the managed files API (`GET /files/{file_id}`). - -### Root Cause - -Only `output_file_id` is stored in `LiteLLM_ManagedFileTable` when a batch completes. The `error_file_id` is encoded in the batch response but never stored in the managed files table. - -**In `async_post_call_success_hook`:** -```python -# Only output_file_id is handled: -if response.output_file_id and model_id: - await self.store_unified_file_id( - file_id=response.output_file_id, - ... - ) -# error_file_id is NOT stored -``` - -## Test Setup Instructions - -### Prerequisites - -- Python 3.11+ -- Docker and Docker Compose -- Poetry (Python package manager) - -### Step 1: Clone and Setup Environment - -```bash -# Install dependencies -poetry install --extras "proxy extra_proxy" - -# Install enterprise package in editable mode (required for patches to work) -poetry run pip install -e enterprise -``` - -### Step 2: Terminal 1 - Start Database and Mock Server - -```bash -cd tests/batches_tests/local-litellm - -# Build and start PostgreSQL and Mock Azure Server -docker compose -f docker-compose.dev.yml up --build -``` - -Wait until you see both services are healthy: -- `litellm_dev_db` - PostgreSQL database -- `mock-server` - Mock Azure OpenAI server (with credential validation enabled by default) - -**Note:** The mock server now validates credentials like real Azure. Use `--build` to ensure you have the latest mock server with credential validation. - -### Step 3: Terminal 2 - Start LiteLLM Proxy - -```bash -cd /path/to/litellm - -# Set environment variables -export DATABASE_URL="postgresql://llmproxy:dbpassword9090@localhost:5432/litellm" -export LITELLM_MASTER_KEY="sk-1234" -export LITELLM_SALT_KEY="mock-salt-key-12345" - -# For real Azure testing (optional): -# export OPENAI_API_KEY="your-azure-api-key" -# export OPENAI_API_BASE=https://your azure endpoint" - -# Generate Prisma client (first time only) -poetry run python -m prisma generate - -# Start the proxy server -poetry run litellm --config tests/batches_tests/local-litellm/litellm-config.yaml --detailed_debug --port 4000 -``` - -Wait until you see: -``` -INFO: Uvicorn running on http://0.0.0.0:4000 -``` - -### Step 4: Terminal 3 - Run Tests - -```bash -cd /path/to/litellm - -# Run the end-to-end managed files test with mock server -USE_MOCK_SERVER=true poetry run pytest tests/batches_tests/test_managed_files_endtoend.py -s -vvv -``` - -### Expected Output - -The test should pass with output similar to: - -``` -tests/batches_tests/test_managed_files_endtoend.py::TestManagedFilesAPI::test_e2e_managed_batch[gpt] -Creating batch input file... -Created batch input file: bGl0ZWxs... - -Creating batch... -Created batch: bGl0ZWxs... - -Waiting for batch to reach completed state... -Batch status: completed - -Retrieving batch output file metadata... -Output file metadata: ... - -Fetching batch output file content... -Output file content: ... - -Deleting input file... -Deleting output file... - -PASSED -``` - ---- - -## Configuration Files - -### `tests/batches_tests/local-litellm/litellm-config-local.yaml` - -This config file sets up models for local testing: -- Mock OpenAI models pointing to `http://localhost:8090` -- Mock Azure batch model pointing to `http://localhost:8090` -- (Optional) Real Azure batch model with API key from environment - -### `tests/batches_tests/local-litellm/docker-compose.dev.yml` - -Docker Compose file that runs: -- PostgreSQL 16 database on port 5432 -- Mock Azure OpenAI server on port 8090 - ---- - -## Troubleshooting - -### "No module named prisma" - -```bash -poetry run pip install prisma==0.11.0 -poetry run python -m prisma generate -``` - -### Database connection error - -Ensure PostgreSQL is running and the DATABASE_URL is correct: -```bash -docker ps | grep postgres -# Should show litellm_dev_db running on port 5432 -``` - -### Patches not being picked up/ - -1. Clear Python cache: - ```bash - find enterprise -name "__pycache__" -type d -exec rm -rf {} + - find litellm -name "__pycache__" -type d -exec rm -rf {} + - ``` - -2. Verify editable install: - ```bash - poetry run pip show litellm-enterprise | grep "Editable" - # Should show: Editable project location: /path/to/litellm/enterprise - ``` - -3. Restart the proxy server - -### Azure credentials error when testing with real Azure - -Set the environment variable before starting the proxy: -```bash -export OPENAI_API_KEY="your-actual-azure-api-key" -``` - ---- From 99cb59c2d202a2fa60a1a9fec11a9ff2d5d0a44e Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Mon, 12 Jan 2026 13:58:47 -0500 Subject: [PATCH 16/46] Add end to end integration tests for batches --- .../batches_tests/test_managed_files_base.py | 221 --------- .../test_managed_files_endtoend.py | 205 -------- .../test_managed_files_permissions.py | 437 ------------------ 3 files changed, 863 deletions(-) delete mode 100644 tests/batches_tests/test_managed_files_base.py delete mode 100644 tests/batches_tests/test_managed_files_endtoend.py delete mode 100644 tests/batches_tests/test_managed_files_permissions.py diff --git a/tests/batches_tests/test_managed_files_base.py b/tests/batches_tests/test_managed_files_base.py deleted file mode 100644 index 4b5d2463014..00000000000 --- a/tests/batches_tests/test_managed_files_base.py +++ /dev/null @@ -1,221 +0,0 @@ -"""Base class for managed files and batch API tests.""" - -import json -import os -import time -import uuid - -import httpx -import openai -import pytest -from tenacity import Retrying, stop_after_delay, wait_fixed - - -LOCAL_LITELLM_BASE_URL = "http://localhost:4000" -LOCAL_AZURE_BASE_URL = "http://localhost:8090" - -USE_LITELLM = os.environ.get("USE_LITELLM", "true").lower() == "true" -if USE_LITELLM: - base_url = LOCAL_LITELLM_BASE_URL - api_key = "sk-1234" -else: - base_url = LOCAL_AZURE_BASE_URL - api_key = "sk-1234" - -USE_MOCK_SERVER = os.environ.get("USE_MOCK_SERVER", "false").lower() == "true" -if USE_MOCK_SERVER: - model_name = "azure-fake-gpt-5-batch-2025-08-07" - MODEL_NAMES = [ - "azure-fake-gpt-5-batch-2025-08-07", - # "anthropic-fake-claude-sonnet-4-batch-2025-08-07", - # "vertex-fake-gemini-2.5-pro-batch-2025-08-07", - ] -else: - model_name = "gpt-5-batch-2025-08-07" - MODEL_NAMES = [ - "gpt-5-batch-2025-08-07", - # "claude-sonnet-4-batch-2025-08-07", - # "gemini-2.5-pro-batch-2025-08-07", - ] - - -def _extract_model_id(model_name: str) -> str: - if "gpt" in model_name: - return "gpt" - elif "claude" in model_name or "anthropic" in model_name: - return "anthropic" - elif "gemini" in model_name or "vertex" in model_name: - return "gemini" - return model_name.split("-")[0] - - -MODEL_IDS = [_extract_model_id(m) for m in MODEL_NAMES] - -MIN_EXPIRY_SECONDS = 259200 - - -class ManagedFilesBase: - """Base class with shared helpers for managed files and batch tests.""" - - base_url = base_url - api_key = api_key - - @pytest.fixture(autouse=True) - def setup_test(self): - print(f"Base URL: {self.base_url}, Model: {model_name}\n") - self.reset_mock_server() - - @staticmethod - def generate_request_id(): - return f"req-{uuid.uuid4().hex[:8]}" - - def create_openai_client(self, api_key: str) -> openai.OpenAI: - return openai.OpenAI( - base_url=self.base_url, - api_key=api_key, - http_client=httpx.Client(verify=False), - ) - - def create_batch_request_file_on_disk(self, tmpdir, model: str): - request_id = self.generate_request_id() - batch_request = { - "custom_id": request_id, - "method": "POST", - "url": "/v1/chat/completions", - "body": { - "model": model, - "messages": [ - {"role": "user", "content": "What is 2+2?"}, - ], - }, - } - - request_file = os.path.join(tmpdir, f"request-{request_id}.jsonl") - with open(request_file, "w") as f: - f.write(json.dumps(batch_request)) - - return request_file - - def create_batch_input_file( - self, - client: openai.OpenAI, - request_file: str, - expiry_seconds: int = MIN_EXPIRY_SECONDS, - ): - batch_input_file = client.files.create( - file=open(request_file, "rb"), - purpose="batch", - extra_body={ - "target_model_names": model_name, - "expires_after": { - "seconds": expiry_seconds, - "anchor": "created_at", - }, - }, - ) - return batch_input_file - - def create_batch( - self, - client: openai.OpenAI, - input_file_id: str, - expiry_seconds: int = MIN_EXPIRY_SECONDS, - ): - batch = client.batches.create( - input_file_id=input_file_id, - endpoint="/v1/chat/completions", - completion_window="24h", - extra_body={ - "output_expires_after": { - "seconds": expiry_seconds, - "anchor": "created_at", - }, - }, - ) - return batch - - def wait_for_batch_state( - self, - client: openai.OpenAI, - batch_id: str, - expected_status: str, - max_seconds: int = 60, - wait_seconds: int = 5, - ): - for attempt in Retrying( - stop=stop_after_delay(max_seconds), - wait=wait_fixed(wait_seconds), - ): - with attempt: - batch_response = client.batches.retrieve(batch_id=batch_id) - print( - f"[{time.strftime('%H:%M:%S')}] Batch status: {batch_response.status}, expected: {expected_status}", - ) - if batch_response.status == expected_status: - return batch_response - if batch_response.status in ["failed", "expired", "cancelled"]: - raise Exception( - f"Batch failed with status: {batch_response.status}", - ) - raise Exception(f"Batch not in {expected_status} state yet") - return None - - def wait_for_batch_completed( - self, - client: openai.OpenAI, - batch_id: str, - max_seconds: int = 120, - wait_seconds: int = 5, - ): - return self.wait_for_batch_state( - client, - batch_id, - "completed", - max_seconds, - wait_seconds, - ) - - def shorten_id(self, id_str: str) -> str: - if id_str is None: - return "None" - if len(id_str) <= 20: - return id_str - return id_str[:8] + "..." + id_str[-8:] - - def reset_mock_server(self): - if not USE_MOCK_SERVER: - return - print("Resetting mock server state...") - reset_response = httpx.post(f"{LOCAL_AZURE_BASE_URL}/reset") - assert reset_response.status_code == 200, f"Reset failed: {reset_response.text}" - - def print_file_metadata(self, file_obj, label="File"): - print(f"{label} metadata:") - print(f"\tid={self.shorten_id(file_obj.id)}") - print(f"\tobject={file_obj.object}") - print(f"\tbytes={file_obj.bytes}") - print(f"\tfilename={file_obj.filename}") - print(f"\tpurpose={file_obj.purpose}") - print(f"\tstatus={file_obj.status}") - print(f"\tcreated_at={file_obj.created_at}") - print(f"\texpires_at={file_obj.expires_at}") - if file_obj.status_details: - print(f"\tstatus_details={file_obj.status_details}") - - def print_batch_metadata(self, batch): - print("Batch metadata:") - print(f"\tid={self.shorten_id(batch.id)}") - print(f"\tstatus={batch.status}") - print(f"\tendpoint={batch.endpoint}") - print(f"\tcompletion_window={batch.completion_window}") - print(f"\tinput_file_id={self.shorten_id(batch.input_file_id)}") - print(f"\tcreated_at={batch.created_at}") - print(f"\texpires_at={batch.expires_at}") - print(f"\tin_progress_at={batch.in_progress_at}") - print(f"\tcompleted_at={batch.completed_at}") - print(f"\toutput_file_id={self.shorten_id(batch.output_file_id)}") - print(f"\trequest_counts={batch.request_counts}") - - - - diff --git a/tests/batches_tests/test_managed_files_endtoend.py b/tests/batches_tests/test_managed_files_endtoend.py deleted file mode 100644 index 21de9717dc4..00000000000 --- a/tests/batches_tests/test_managed_files_endtoend.py +++ /dev/null @@ -1,205 +0,0 @@ -import warnings - -import openai -import pytest -from tenacity import RetryError, Retrying, stop_after_delay, wait_fixed - -from test_managed_files_base import ( - MODEL_IDS, - MODEL_NAMES, - ManagedFilesBase, - MIN_EXPIRY_SECONDS, -) - - -class TestManagedFilesAPI(ManagedFilesBase): - """Test cases for managed files and batch API. - - Configuration via environment variables: - USE_LITELLM=true - Run against LiteLLM proxy - USE_LITELLM=false - Run against mock server directly (default) - """ - - @classmethod - def setup_class(cls): - cls.openai_client = cls.create_openai_client(cls, cls.api_key) - - def wait_for_batch_list(self, model_name, max_seconds=90, wait_seconds=10): - for attempt in Retrying( - stop=stop_after_delay(max_seconds), - wait=wait_fixed(wait_seconds), - ): - with attempt: - batches_list = self.openai_client.batches.list( - limit=10, - extra_query={"target_model_names": model_name}, - ) - print( - f"Batches in list: {len(batches_list.data)}", - ) - if len(batches_list.data) == 0: - raise Exception("No batches found in list yet") - return batches_list - return None - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_e2e_managed_batch(self, tmp_path, model_name): - print( - f"\n\nStarting test with base_url={self.base_url} and model_name={model_name}\n", - ) - - self.reset_mock_server() - - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - - print("Creating batch input file...") - batch_input_file = self.create_batch_input_file( - self.openai_client, - request_file, - MIN_EXPIRY_SECONDS, - ) - print(f"Created batch input file: {self.shorten_id(batch_input_file.id)}\n") - - print( - f"Retrieving batch input file metadata for file id: {self.shorten_id(batch_input_file.id)}", - ) - input_file_metadata = self.openai_client.files.retrieve(batch_input_file.id) - assert input_file_metadata.id == batch_input_file.id, "File ID mismatch" - assert input_file_metadata.object == "file", "object should be 'file'" - assert input_file_metadata.bytes > 0, "bytes not set" - assert input_file_metadata.filename == "modified_file.jsonl", ( - "filename mismatch" - ) - assert input_file_metadata.purpose == "batch", "purpose mismatch" - assert input_file_metadata.status in ["uploaded", "processed", "error"], ( - "invalid status" - ) - assert input_file_metadata.created_at > 0, "created_at not set" - if not input_file_metadata.expires_at: - warnings.warn("batch input file expires_at not set") - self.print_file_metadata(input_file_metadata, "Input file") - - print("\nCreating batch...") - batch = self.create_batch( - self.openai_client, - batch_input_file.id, - MIN_EXPIRY_SECONDS, - ) - print(f"Created batch: {self.shorten_id(batch.id)}") - assert batch.id, "No batch ID returned" - assert batch.input_file_id == batch_input_file.id, "File ID mismatch" - assert batch.status in [ - "validating", - "in_progress", - "finalizing", - "completed", - ], "Status mismatch" - if not batch.expires_at: - warnings.warn("batch expires_at not set") - else: - assert batch.expires_at > 0, "batch expires_at not set" - - if not batch.endpoint: - warnings.warn( - "batch.endpoint empty in creation response - Azure API quirk, not a bug", - ) - else: - assert batch.endpoint == "/v1/chat/completions", "endpoint mismatch" - assert batch.completion_window == "24h", "completion_window mismatch" - assert batch.created_at > 0, "created_at not set" - - self.print_batch_metadata(batch) - - print("\nListing batches...") - try: - batches_list = self.wait_for_batch_list( - model_name, - max_seconds=30, - wait_seconds=5, - ) - batches = batches_list.data if batches_list else [] - batch_ids = [b.id for b in batches] - if batch.id not in batch_ids: - warnings.warn( - f"Batch {batch.id} not found in list. batches.list returns raw IDs and not the encoded IDs. raw IDs: {batch_ids}", - ) - except RetryError: - warnings.warn( - "batches.list() returned empty list after retries - known LiteLLM issue with managed batches", - ) - except openai.APIError as e: - pytest.fail(f"batches.list() failed: {e}") - - print( - f"\nWaiting for batch {self.shorten_id(batch.id)} to reach completed state...", - ) - try: - batch_response = self.wait_for_batch_state( - self.openai_client, - batch.id, - "completed", - max_seconds=30 * 60, - wait_seconds=5, - ) - except RetryError: - raise TimeoutError("Timed out waiting for batch to be in state: completed") - - print("\nRetrieving batch output file metadata...") - output_file_metadata = self.openai_client.files.retrieve( - batch_response.output_file_id, - ) - assert output_file_metadata.id == batch_response.output_file_id, ( - "Output file ID mismatch" - ) - assert output_file_metadata.object == "file", "object should be 'file'" - assert output_file_metadata.bytes > 0, "bytes not set" - assert output_file_metadata.filename, "filename not set" - assert output_file_metadata.purpose in ["batch_output", "batch"], ( - "purpose should be batch_output" - ) - assert output_file_metadata.created_at > 0, "created_at not set" - self.print_file_metadata(output_file_metadata, "Output file") - - print("\nFetching batch output file content...") - batch_file_content = self.openai_client.files.content( - batch_response.output_file_id, - ) - assert batch_file_content.text, "No batch file content returned" - assert len(batch_file_content.text) > 0, "Batch file content is empty" - print(f"Output file content ({len(batch_file_content.text)} bytes):") - for line in batch_file_content.text.strip().split("\n")[:3]: - print(f"\t{line}") - - print(f"\nDeleting input file: {self.shorten_id(batch_input_file.id)}") - try: - self.openai_client.files.delete(batch_input_file.id) - except openai.APIError as e: - pytest.fail(f"files.delete() failed: {e}") - - print( - f"\nDeleting output file: {self.shorten_id(batch_response.output_file_id)}", - ) - try: - self.openai_client.files.delete(batch_response.output_file_id) - except openai.APIError as e: - pytest.fail(f"files.delete() failed: {e}") - - print("\nVerifying input file is deleted...") - try: - self.openai_client.files.content(batch_input_file.id) - assert False, f"Input file {batch_input_file.id} exists after deletion" - except (openai.NotFoundError, openai.PermissionDeniedError): - print("Input file correctly not accessible after deletion") - - print("\nVerifying output file is deleted...") - try: - self.openai_client.files.content(batch_response.output_file_id) - assert False, ( - f"Output file {batch_response.output_file_id} exists after deletion" - ) - except (openai.NotFoundError, openai.PermissionDeniedError): - print("Output file correctly not accessible after deletion") - - - - diff --git a/tests/batches_tests/test_managed_files_permissions.py b/tests/batches_tests/test_managed_files_permissions.py deleted file mode 100644 index e23eb9198a9..00000000000 --- a/tests/batches_tests/test_managed_files_permissions.py +++ /dev/null @@ -1,437 +0,0 @@ -""" -Test cross-user batch access permissions. - -This test verifies that a batch and related files created by one API key -cannot be accessed, modified, or cancelled by a different API key. - -Reference: https://github.com/BerriAI/litellm/pull/17401/files -""" - -import time - -import httpx -import openai -import pytest - -from test_managed_files_base import ( - ManagedFilesBase, - MODEL_NAMES, - MODEL_IDS, -) - - -BATCH_ROUTES = [ - "/v1/files", - "/files", - "/v1/files/*", - "/files/*", - "/v1/batches", - "/batches", - "/v1/batches/*", - "/batches/*", -] - - -class TestManagedFilesPermissions(ManagedFilesBase): - """Test cases for cross-user batch access permissions. - - Verifies that: - - User A can create and access their own batches and files - - User B cannot access, retrieve, cancel, or delete User A's batches/files - """ - - master_api_key = "sk-1234" - - @classmethod - def setup_class(cls): - cls.admin_client = httpx.Client(base_url=cls.base_url, verify=False) - - @classmethod - def teardown_class(cls): - cls.admin_client.close() - - def user_suffix(self) -> str: - return f"{time.strftime('%Y%m%d%H%M%S')}{int(time.time() * 1000) % 1000:03d}" - - def create_user_and_key(self, user_suffix: str) -> tuple[str, str]: - user_email = f"test-user-{user_suffix}-{self.user_suffix()}@test.com" - - user_response = self.admin_client.post( - "/user/new", - json={ - "user_email": user_email, - "user_alias": user_email, - "user_role": "internal_user", - "auto_create_key": "false", - }, - headers={ - "Authorization": f"Bearer {self.master_api_key}", - "Content-Type": "application/json", - }, - timeout=30, - ) - assert user_response.status_code == 200, ( - f"Failed to create user: {user_response.status_code} - {user_response.text}" - ) - user_data = user_response.json() - user_id = user_data.get("user_id") - - key_response = self.admin_client.post( - "/key/generate", - json={ - "user_id": user_id, - "key_alias": user_email, - "allowed_routes": BATCH_ROUTES, - }, - headers={ - "Authorization": f"Bearer {self.master_api_key}", - "Content-Type": "application/json", - }, - timeout=30, - ) - assert key_response.status_code == 200, ( - f"Failed to create key: {key_response.status_code} - {key_response.text}" - ) - key_data = key_response.json() - api_key = key_data.get("key") - - print(f"Created user {user_email} with key {key_data.get('key_alias')}") - return user_id, api_key - - def create_user_key_and_client( - self, - user_suffix: str, - ) -> tuple[str, str, openai.OpenAI]: - user_id, api_key = self.create_user_and_key(user_suffix) - return user_id, api_key, self.create_openai_client(api_key) - - def create_key_and_client(self, user_id: str, key_suffix: str) -> str: - key_alias = f"additional-key-{key_suffix}-{self.user_suffix()}" - key_response = self.admin_client.post( - "/key/generate", - json={ - "user_id": user_id, - "key_alias": key_alias, - "allowed_routes": BATCH_ROUTES, - }, - headers={ - "Authorization": f"Bearer {self.master_api_key}", - "Content-Type": "application/json", - }, - timeout=30, - ) - assert key_response.status_code == 200, ( - f"Failed to create additional key: {key_response.status_code} - {key_response.text}" - ) - api_key = key_response.json().get("key") - print(f"Created additional key {api_key[:20]}... for user {user_id}") - return api_key, self.create_openai_client(api_key) - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_retrieve_user_a_batch(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # User A retrieves their own batch - batch_a = client_A.batches.retrieve(batch_id=batch.id) - assert batch_a.id == batch.id, ( - "User A should be able to retrieve their own batch" - ) - - # User B cannot retrieve User A's batch - try: - client_B.batches.retrieve(batch_id=batch.id) - pytest.fail("User B should NOT be able to retrieve User A's batch") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_cancel_user_a_batch(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # User B cannot cancel User A's batch - try: - client_B.batches.cancel(batch_id=batch.id) - pytest.fail("User B should NOT be able to cancel User A's batch") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_retrieve_user_a_batch_input_file(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - - # User A retrieves their own file - file_a = client_A.files.retrieve(file_id=batch_input_file.id) - assert file_a.id == batch_input_file.id, ( - "User A should be able to retrieve their own file" - ) - - # User B cannot retrieve User A's file - try: - client_B.files.retrieve(file_id=batch_input_file.id) - pytest.fail("User B should NOT be able to retrieve User A's file") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_download_user_a_batch_input_file_content( - self, - tmp_path, - model_name, - ): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - - # User A can download their own file content - content_a = client_A.files.content(file_id=batch_input_file.id) - assert content_a.text, ( - "User A should be able to download their own file content" - ) - - # User B cannot download User A's file content - try: - client_B.files.content(file_id=batch_input_file.id) - pytest.fail("User B should NOT be able to download User A's file content") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_delete_user_a_batch_input_file(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - - # User B cannot delete User A's file - try: - client_B.files.delete(file_id=batch_input_file.id) - pytest.fail("User B should NOT be able to delete User A's file") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - # User A can still retrieve their own file - file_a = client_A.files.retrieve(file_id=batch_input_file.id) - assert file_a.id == batch_input_file.id, "File should still exist" - - # User A can delete their own file - try: - client_A.files.delete(file_id=batch_input_file.id) - except openai.APIError as e: - pytest.fail(f"User A should be able to delete their own file: {e}") - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_retrieve_user_a_batch_output_file( - self, - tmp_path, - model_name, - ): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # Wait for batch to complete - completed_batch = self.wait_for_batch_completed(client_A, batch.id) - assert completed_batch.output_file_id, "Batch should have an output file" - - # User A retrieves their own output file - file_a = client_A.files.retrieve(file_id=completed_batch.output_file_id) - assert file_a.id == completed_batch.output_file_id, ( - "User A should be able to retrieve their own output file" - ) - - # User B cannot retrieve User A's output file - try: - client_B.files.retrieve(file_id=completed_batch.output_file_id) - pytest.fail("User B should NOT be able to retrieve User A's output file") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_download_user_a_batch_output_file_content( - self, - tmp_path, - model_name, - ): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # Wait for batch to complete - completed_batch = self.wait_for_batch_completed(client_A, batch.id) - assert completed_batch.output_file_id, "Batch should have an output file" - - # User A can download their own output file content - content_a = client_A.files.content(file_id=completed_batch.output_file_id) - assert content_a.text, ( - "User A should be able to download their own output file content" - ) - - # User B cannot download User A's output file content - try: - client_B.files.content(file_id=completed_batch.output_file_id) - pytest.fail( - "User B should NOT be able to download User A's output file content", - ) - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_delete_user_a_batch_output_file(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # Wait for batch to complete - completed_batch = self.wait_for_batch_completed(client_A, batch.id) - assert completed_batch.output_file_id, "Batch should have an output file" - - # User B cannot delete User A's output file - try: - client_B.files.delete(file_id=completed_batch.output_file_id) - pytest.fail("User B should NOT be able to delete User A's output file") - except openai.PermissionDeniedError as e: - assert e.status_code == 403 - - # User A can still retrieve their own output file - file_a = client_A.files.retrieve(file_id=completed_batch.output_file_id) - assert file_a.id == completed_batch.output_file_id, ( - "Output file should still exist" - ) - - # User A can delete their own output file - try: - client_A.files.delete(file_id=completed_batch.output_file_id) - except openai.APIError as e: - pytest.fail(f"User A should be able to delete their own output file: {e}") - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_b_cannot_list_user_a_batches(self, tmp_path, model_name): - user_a_id, user_a_key, client_A = self.create_user_key_and_client("a") - user_b_id, user_b_key, client_B = self.create_user_key_and_client("b") - - # User A creates a batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_A, request_file) - batch = self.create_batch(client_A, batch_input_file.id) - - # User A can see their own batch in the list - batches_a = client_A.batches.list( - limit=10, - extra_query={"target_model_names": model_name}, - ) - batch_ids_a = [b.id for b in batches_a.data] - assert batch.id in batch_ids_a, "User A should see their own batch in the list" - - # User B's batch list should NOT contain User A's batch - batches_b = client_B.batches.list( - limit=10, - extra_query={"target_model_names": model_name}, - ) - batch_ids_b = [b.id for b in batches_b.data] - assert batch.id not in batch_ids_b, ( - "User B should NOT see User A's batch in the list" - ) - - @pytest.mark.parametrize("model_name", MODEL_NAMES, ids=MODEL_IDS) - def test_user_api_keys_are_interchangeable(self, tmp_path, model_name): - # Create user with 3 keys - user_id, key1, client_Key1 = self.create_user_key_and_client("a") - key2, client_Key2 = self.create_key_and_client(user_id, "a2") - key3, client_Key3 = self.create_key_and_client(user_id, "a3") - - # Key1: Create batch input file and batch - request_file = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file = self.create_batch_input_file(client_Key1, request_file) - batch = self.create_batch(client_Key1, batch_input_file.id) - - # Key1: Retrieve batch - batch_retrieved = client_Key1.batches.retrieve(batch_id=batch.id) - assert batch_retrieved.id == batch.id, "Key1 should retrieve its own batch" - - # Key2: Wait for batch completion and retrieve output - completed_batch = self.wait_for_batch_completed(client_Key2, batch.id) - assert completed_batch.output_file_id, "Batch should have an output file" - - # Key2: Retrieve output file metadata - output_file = client_Key2.files.retrieve(file_id=completed_batch.output_file_id) - assert output_file.id == completed_batch.output_file_id, ( - "Key2 should retrieve output file" - ) - - # Key2: Download output file content - output_content = client_Key2.files.content( - file_id=completed_batch.output_file_id, - ) - assert output_content.text, "Key2 should download output file content" - - # Key3: List batches and verify batch is visible - batches = client_Key3.batches.list( - limit=10, - extra_query={"target_model_names": model_name}, - ) - batch_ids = [b.id for b in batches.data] - assert batch.id in batch_ids, "Key3 should see batch in list" - - # Key3: Delete input file - try: - client_Key3.files.delete(file_id=batch_input_file.id) - except openai.APIError as e: - pytest.fail(f"Key3 should delete input file: {e}") - - # Key3: Delete output file - try: - client_Key3.files.delete(file_id=completed_batch.output_file_id) - except openai.APIError as e: - pytest.fail(f"Key3 should delete output file: {e}") - - # Key1: Create another batch for cancellation test - request_file2 = self.create_batch_request_file_on_disk(tmp_path, model_name) - batch_input_file2 = self.create_batch_input_file(client_Key1, request_file2) - batch2 = self.create_batch(client_Key1, batch_input_file2.id) - - # Key3: Cancel the batch created by Key1 - try: - cancelled_batch = client_Key3.batches.cancel(batch_id=batch2.id) - assert cancelled_batch.id == batch2.id, ( - "Key3 should cancel batch created by Key1" - ) - except openai.BadRequestError: - pass # Batch may have already completed - - - - From 685437c9cce56b0db687a914bb329ff88b656c48 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Mon, 12 Jan 2026 13:51:09 -0800 Subject: [PATCH 17/46] Adding help scripts for neon --- ui/litellm-dashboard/package-lock.json | 175 ++++++++---------- ui/litellm-dashboard/package.json | 2 + .../scripts/e2e_tests/neonHelperScripts.ts | 47 +++++ 3 files changed, 123 insertions(+), 101 deletions(-) create mode 100644 ui/litellm-dashboard/scripts/e2e_tests/neonHelperScripts.ts diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index 0e9675f40a1..7f53d1e1956 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -39,6 +39,7 @@ "uuid": "^11.1.0" }, "devDependencies": { + "@neondatabase/api-client": "^2.6.0", "@playwright/test": "^1.57.0", "@tailwindcss/forms": "^0.5.7", "@testing-library/dom": "^10.4.1", @@ -57,6 +58,7 @@ "@vitest/coverage-v8": "^3.2.4", "@vitest/ui": "^3.2.4", "autoprefixer": "^10.4.17", + "dotenv": "^17.2.3", "eslint": "^8", "eslint-config-next": "14.2.32", "eslint-config-prettier": "^10.1.8", @@ -92,6 +94,7 @@ "version": "5.2.0", "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==", + "dev": true, "license": "MIT", "engines": { "node": ">=10" @@ -325,7 +328,6 @@ "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.28.5.tgz", "integrity": "sha512-e7jT4DxYvIDLk1ZHmU/m/mB19rex9sv0c2ftBtjSBv+kVM/902eh0fINUzD7UwLLNR+jU585GxUJ8/EBfAM5fw==", "license": "MIT", - "peer": true, "dependencies": { "@babel/code-frame": "^7.27.1", "@babel/generator": "^7.28.5", @@ -2187,7 +2189,6 @@ } ], "license": "MIT", - "peer": true, "engines": { "node": ">=18" }, @@ -2230,7 +2231,6 @@ } ], "license": "MIT", - "peer": true, "engines": { "node": ">=18" } @@ -2340,7 +2340,6 @@ "resolved": "https://registry.npmjs.org/postcss-selector-parser/-/postcss-selector-parser-7.1.0.tgz", "integrity": "sha512-8sLjZwK0R+JlxlYcTuVnyT2v+htpdrjDOKuMcOVdYjt52Lh8hWRYpxBPoKx/Zg+bcjc3wx6fmQevMmUztS/ccA==", "license": "MIT", - "peer": true, "dependencies": { "cssesc": "^3.0.0", "util-deprecate": "^1.0.2" @@ -2762,7 +2761,6 @@ "resolved": "https://registry.npmjs.org/postcss-selector-parser/-/postcss-selector-parser-7.1.0.tgz", "integrity": "sha512-8sLjZwK0R+JlxlYcTuVnyT2v+htpdrjDOKuMcOVdYjt52Lh8hWRYpxBPoKx/Zg+bcjc3wx6fmQevMmUztS/ccA==", "license": "MIT", - "peer": true, "dependencies": { "cssesc": "^3.0.0", "util-deprecate": "^1.0.2" @@ -3546,40 +3544,6 @@ "react-dom": "*" } }, - "node_modules/@docusaurus/plugin-content-docs": { - "version": "3.9.2", - "resolved": "https://registry.npmjs.org/@docusaurus/plugin-content-docs/-/plugin-content-docs-3.9.2.tgz", - "integrity": "sha512-C5wZsGuKTY8jEYsqdxhhFOe1ZDjH0uIYJ9T/jebHwkyxqnr4wW0jTkB72OMqNjsoQRcb0JN3PcSeTwFlVgzCZg==", - "license": "MIT", - "peer": true, - "dependencies": { - "@docusaurus/core": "3.9.2", - "@docusaurus/logger": "3.9.2", - "@docusaurus/mdx-loader": "3.9.2", - "@docusaurus/module-type-aliases": "3.9.2", - "@docusaurus/theme-common": "3.9.2", - "@docusaurus/types": "3.9.2", - "@docusaurus/utils": "3.9.2", - "@docusaurus/utils-common": "3.9.2", - "@docusaurus/utils-validation": "3.9.2", - "@types/react-router-config": "^5.0.7", - "combine-promises": "^1.1.0", - "fs-extra": "^11.1.1", - "js-yaml": "^4.1.0", - "lodash": "^4.17.21", - "schema-dts": "^1.1.2", - "tslib": "^2.6.0", - "utility-types": "^3.10.0", - "webpack": "^5.88.1" - }, - "engines": { - "node": ">=20.0" - }, - "peerDependencies": { - "react": "^18.0.0 || ^19.0.0", - "react-dom": "^18.0.0 || ^19.0.0" - } - }, "node_modules/@docusaurus/theme-common": { "version": "3.9.2", "resolved": "https://registry.npmjs.org/@docusaurus/theme-common/-/theme-common-3.9.2.tgz", @@ -4739,24 +4703,6 @@ "url": "https://opencollective.com/unified" } }, - "node_modules/@mdx-js/react": { - "version": "3.1.1", - "resolved": "https://registry.npmjs.org/@mdx-js/react/-/react-3.1.1.tgz", - "integrity": "sha512-f++rKLQgUVYDAtECQ6fn/is15GkEH9+nZPM3MS0RcxVqoTfawHvDlSCH7JbMhAM6uJ32v3eXLvLmLvjGu7PTQw==", - "license": "MIT", - "peer": true, - "dependencies": { - "@types/mdx": "^2.0.0" - }, - "funding": { - "type": "opencollective", - "url": "https://opencollective.com/unified" - }, - "peerDependencies": { - "@types/react": ">=16", - "react": ">=16" - } - }, "node_modules/@mermaid-js/parser": { "version": "0.6.3", "resolved": "https://registry.npmjs.org/@mermaid-js/parser/-/parser-0.6.3.tgz", @@ -4779,6 +4725,16 @@ "@tybys/wasm-util": "^0.10.0" } }, + "node_modules/@neondatabase/api-client": { + "version": "2.6.0", + "resolved": "https://registry.npmjs.org/@neondatabase/api-client/-/api-client-2.6.0.tgz", + "integrity": "sha512-NxKE+EFcVwxXU3jj8I/WgueXSyzrXV85AV0nb2SeoKtOa3dlEcTylsdOsMsMeZZeFfQXLyiCOm2nAduGZn9olA==", + "dev": true, + "license": "MIT", + "dependencies": { + "axios": "^1.9.0" + } + }, "node_modules/@next/env": { "version": "14.2.35", "resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.35.tgz", @@ -4988,9 +4944,8 @@ "version": "1.57.0", "resolved": "https://registry.npmjs.org/@playwright/test/-/test-1.57.0.tgz", "integrity": "sha512-6TyEnHgd6SArQO8UO2OMTxshln3QMWBtPGrOCgs3wVEmQmwyuNtB10IZMfmYDE0riwNR1cu4q+pPcxMVtaG3TA==", - "devOptional": true, + "dev": true, "license": "Apache-2.0", - "peer": true, "dependencies": { "playwright": "1.57.0" }, @@ -5847,7 +5802,6 @@ "integrity": "sha512-o4PXJQidqJl82ckFaXUeoAW+XysPLauYI43Abki5hABd853iMhitooc6znOnczgbTYmEP6U6/y1ZyKAIsvMKGg==", "dev": true, "license": "MIT", - "peer": true, "dependencies": { "@babel/code-frame": "^7.10.4", "@babel/runtime": "^7.12.5", @@ -6641,7 +6595,6 @@ "resolved": "https://registry.npmjs.org/@types/react/-/react-18.2.48.tgz", "integrity": "sha512-qboRCl6Ie70DQQG9hhNREz81jqC1cs9EVNcjQ1AU+jH6NFfSAhVVbrrY/+nSF+Bsk4AOwm9Qa61InvMCyV+H3w==", "license": "MIT", - "peer": true, "dependencies": { "@types/prop-types": "*", "@types/scheduler": "*", @@ -6664,7 +6617,6 @@ "integrity": "sha512-MEe3UeoENYVFXzoXEWsvcpg6ZvlrFNlOQ7EOsvhI3CfAXwzPfO8Qwuxd40nepsYKqyyVQnTdEfv68q91yLcKrQ==", "dev": true, "license": "MIT", - "peer": true, "peerDependencies": { "@types/react": "^18.0.0" } @@ -6861,7 +6813,6 @@ "integrity": "sha512-lJi3PfxVmo0AkEY93ecfN+r8SofEqZNGByvHAI3GBLrvt1Cw6H5k1IM02nSzu0RfUafr2EvFSw0wAsZgubNplQ==", "dev": true, "license": "MIT", - 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"peer": true, "dependencies": { "@alloc/quick-lru": "^5.2.0", "arg": "^5.0.2", @@ -24456,6 +24429,7 @@ "version": "6.0.2", "resolved": "https://registry.npmjs.org/glob-parent/-/glob-parent-6.0.2.tgz", "integrity": "sha512-XxwI8EOhVQgWp6iDL+3b0r86f4d6AX6zSU55HfB4ydCEuXLXc5FcYeOu+nnGftS4TEju/11rt4KJPTMgbfmv4A==", + "dev": true, "license": "ISC", "dependencies": { "is-glob": "^4.0.3" @@ -24616,6 +24590,7 @@ "version": "3.3.1", "resolved": "https://registry.npmjs.org/thenify/-/thenify-3.3.1.tgz", "integrity": "sha512-RVZSIV5IG10Hk3enotrhvz0T9em6cyHBLkH/YAZuKqd8hRkKhSfCGIcP2KUY0EPxndzANBmNllzWPwak+bheSw==", + "dev": true, "license": "MIT", "dependencies": { "any-promise": "^1.0.0" @@ -24625,6 +24600,7 @@ "version": "1.6.0", "resolved": "https://registry.npmjs.org/thenify-all/-/thenify-all-1.6.0.tgz", "integrity": "sha512-RNxQH/qI8/t3thXJDwcstUO4zeqo64+Uy/+sNVRBx4Xn2OX+OZ9oP+iJnNFqplFra2ZUVeKCSa2oVWi3T4uVmA==", + "dev": true, "license": "MIT", "dependencies": { "thenify": ">= 3.1.0 < 4" @@ -24696,6 +24672,7 @@ "version": "0.2.15", "resolved": "https://registry.npmjs.org/tinyglobby/-/tinyglobby-0.2.15.tgz", "integrity": "sha512-j2Zq4NyQYG5XMST4cbs02Ak8iJUdxRM0XI5QyxXuZOzKOINmWurp3smXu3y5wDcJrptwpSjgXHzIQxR0omXljQ==", + "dev": true, "license": "MIT", "dependencies": { "fdir": "^6.5.0", @@ -24712,6 +24689,7 @@ "version": "6.5.0", "resolved": "https://registry.npmjs.org/fdir/-/fdir-6.5.0.tgz", "integrity": "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg==", + "dev": true, "license": "MIT", "engines": { "node": ">=12.0.0" @@ -24729,8 +24707,8 @@ "version": "4.0.3", "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-4.0.3.tgz", "integrity": "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==", + "dev": true, "license": "MIT", - "peer": true, "engines": { "node": ">=12" }, @@ -24911,6 +24889,7 @@ "version": "0.1.13", "resolved": "https://registry.npmjs.org/ts-interface-checker/-/ts-interface-checker-0.1.13.tgz", "integrity": "sha512-Y/arvbn+rrz3JCKl9C4kVNfTfSm2/mEp5FSz5EsZSANGPSlQrpRI5M4PKF+mJnE52jOO90PnPSc3Ur3bTQw0gA==", + "dev": true, "license": "Apache-2.0" }, "node_modules/tsconfig-paths": { @@ -24943,8 +24922,7 @@ "version": "2.8.1", "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz", "integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==", - "license": "0BSD", - "peer": true + "license": "0BSD" }, "node_modules/type-check": { "version": "0.4.0", @@ -25075,9 +25053,8 @@ "version": "5.3.3", "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.3.3.tgz", "integrity": "sha512-pXWcraxM0uxAS+tN0AG/BF2TyqmHO014Z070UsJ+pFvYuRSq8KH8DmWpnbXe0pEPDHXZV3FcAbJkijJ5oNEnWw==", - "devOptional": true, + "dev": true, "license": "Apache-2.0", - "peer": true, "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" @@ -25620,7 +25597,6 @@ "integrity": "sha512-NL8jTlbo0Tn4dUEXEsUg8KeyG/Lkmc4Fnzb8JXN/Ykm9G4HNImjtABMJgkQoVjOBN/j2WAwDTRytdqJbZsah7w==", "dev": true, "license": "MIT", - "peer": true, "dependencies": { "esbuild": "^0.25.0", "fdir": "^6.5.0", @@ -25737,7 +25713,6 @@ "integrity": "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==", "dev": true, "license": "MIT", - "peer": true, "engines": { "node": ">=12" }, @@ -25751,7 +25726,6 @@ "integrity": "sha512-LUCP5ev3GURDysTWiP47wRRUpLKMOfPh+yKTx3kVIEiu5KOMeqzpnYNsKyOoVrULivR8tLcks4+lga33Whn90A==", "dev": true, "license": "MIT", - "peer": true, "dependencies": { "@types/chai": "^5.2.2", "@vitest/expect": "3.2.4", @@ -25957,7 +25931,6 @@ "resolved": "https://registry.npmjs.org/webpack/-/webpack-5.103.0.tgz", "integrity": "sha512-HU1JOuV1OavsZ+mfigY0j8d1TgQgbZ6M+J75zDkpEAwYeXjWSqrGJtgnPblJjd/mAyTNQ7ygw0MiKOn6etz8yw==", "license": "MIT", - "peer": true, "dependencies": { "@types/eslint-scope": "^3.7.7", "@types/estree": "^1.0.8", diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index 0ecba62140f..58ac0ab0451 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -47,6 +47,7 @@ "uuid": "^11.1.0" }, "devDependencies": { + "@neondatabase/api-client": "^2.6.0", "@playwright/test": "^1.57.0", "@tailwindcss/forms": "^0.5.7", "@testing-library/dom": "^10.4.1", @@ -65,6 +66,7 @@ "@vitest/coverage-v8": "^3.2.4", "@vitest/ui": "^3.2.4", "autoprefixer": "^10.4.17", + "dotenv": "^17.2.3", "eslint": "^8", "eslint-config-next": "14.2.32", "eslint-config-prettier": "^10.1.8", diff --git a/ui/litellm-dashboard/scripts/e2e_tests/neonHelperScripts.ts b/ui/litellm-dashboard/scripts/e2e_tests/neonHelperScripts.ts new file mode 100644 index 00000000000..3078a0d90d2 --- /dev/null +++ b/ui/litellm-dashboard/scripts/e2e_tests/neonHelperScripts.ts @@ -0,0 +1,47 @@ +import { createApiClient } from "@neondatabase/api-client"; +import { config } from "dotenv"; +import { resolve } from "path"; + +const envPaths = [ + resolve(process.cwd(), "../../.env"), // project root +]; + +for (const envPath of envPaths) { + config({ path: envPath }); +} + +const NEON_API_KEY = process.env.NEON_API_KEY!; +const PROJECT_ID = process.env.NEON_PROJECT_ID!; +const PARENT_BRANCH = process.env.NEON_PARENT_BRANCH_ID!; +const NEON_E2E_UI_TEST_DB_NAME = process.env.NEON_E2E_UI_TEST_DB_NAME!; + +const apiClient = createApiClient({ + apiKey: NEON_API_KEY, +}); + +export async function createNeonE2ETestingBranch(projectId: string, parentBranchId?: string, expireAt?: string) { + try { + const response = await apiClient.createProjectBranch(projectId, { + branch: { + name: `e2e-local-${crypto.randomUUID()}`, + parent_id: parentBranchId, + expires_at: expireAt ?? new Date(Date.now() + 1000 * 60 * 30).toISOString(), + }, + }); + return response; + } catch (error) { + throw error; + } +} + +export async function getNeonE2ETestingBranchConnectionString() { + await createNeonE2ETestingBranch(PROJECT_ID, PARENT_BRANCH); + + const response = await apiClient.getConnectionUri({ + database_name: NEON_E2E_UI_TEST_DB_NAME, + role_name: "neondb_owner", + projectId: PROJECT_ID, + }); + console.log("connection string:", response.data.uri); + return response.data.uri; +} From f5fc38dcf93fc1635a423a96e3a5ea95889e6c99 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Mon, 12 Jan 2026 13:55:47 -0800 Subject: [PATCH 18/46] docs litellm cloud --- docs/my-website/docs/data_retention.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/my-website/docs/data_retention.md b/docs/my-website/docs/data_retention.md index 04d4675199e..3cfdd247258 100644 --- a/docs/my-website/docs/data_retention.md +++ b/docs/my-website/docs/data_retention.md @@ -10,7 +10,7 @@ This policy outlines the requirements and controls/procedures LiteLLM Cloud has For Customers 1. Active Accounts -- Customer data is retained for as long as the customer’s account is in active status. This includes data such as prompts, generated content, logs, and usage metrics. +- Customer data is retained for as long as the customer’s account is in active status. This includes data such as prompts, generated content, logs, and usage metrics. By default, we do not store the message / response content of your API requests or responses. Cloud users need to explicitly opt in to store the message / response content of your API requests or responses. 2. Voluntary Account Closure From a0e0026df0758dfa4ff8d53b1ba60509a72c925f Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 10:09:23 +0900 Subject: [PATCH 19/46] chore: document temporary grype ignore for CVE-2019-1010022 --- ci_cd/.grype.yaml | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 ci_cd/.grype.yaml diff --git a/ci_cd/.grype.yaml b/ci_cd/.grype.yaml new file mode 100644 index 00000000000..e1068de8e34 --- /dev/null +++ b/ci_cd/.grype.yaml @@ -0,0 +1,3 @@ +ignore: + - vulnerability: CVE-2019-1010022 + reason: no fixed glibc package is available yet in the Wolfi repositories, so this is ignored temporarily until an upstream release exists From 54b21cabf7ab95189027bbe8ff23590c381d6f90 Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 10:19:12 +0900 Subject: [PATCH 20/46] chore: add config option --- ci_cd/security_scans.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ci_cd/security_scans.sh b/ci_cd/security_scans.sh index be9167adda2..eeaaddd3e1e 100755 --- a/ci_cd/security_scans.sh +++ b/ci_cd/security_scans.sh @@ -101,12 +101,12 @@ run_grype_scans() { # Build and scan Dockerfile.database echo "Building and scanning Dockerfile.database..." docker build --no-cache -t litellm-database:latest -f ./docker/Dockerfile.database . - grype litellm-database:latest --fail-on critical + grype litellm-database:latest --config ci_cd/.grype.yaml --fail-on critical # Build and scan main Dockerfile echo "Building and scanning main Dockerfile..." docker build --no-cache -t litellm:latest . - grype litellm:latest --fail-on critical + grype litellm:latest --config ci_cd/.grype.yaml --fail-on critical # Restore original .dockerignore echo "Restoring original .dockerignore..." From 4daac9e3328a73135691b8fe6c454f588fe347e7 Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 10:30:34 +0900 Subject: [PATCH 21/46] chore: add ALLOWED_CVES --- ci_cd/security_scans.sh | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/ci_cd/security_scans.sh b/ci_cd/security_scans.sh index eeaaddd3e1e..17cf4c1817d 100755 --- a/ci_cd/security_scans.sh +++ b/ci_cd/security_scans.sh @@ -129,6 +129,11 @@ run_grype_scans() { "CVE-2025-13836" # Python 3.13 HTTP response reading OOM/DoS - no fix available in base image "CVE-2025-12084" # Python 3.13 xml.dom.minidom quadratic algorithm - no fix available in base image "CVE-2025-60876" # BusyBox wget HTTP request splitting - no fix available in Chainguard Wolfi base image + "CVE-2010-4756" # glibc glob DoS - awaiting patched Wolfi glibc build + "CVE-2019-1010022" # glibc stack guard bypass - awaiting patched Wolfi glibc build + "CVE-2019-1010023" # glibc ldd remap issue - awaiting patched Wolfi glibc build + "CVE-2019-1010024" # glibc ASLR mitigation bypass - awaiting patched Wolfi glibc build + "CVE-2019-1010025" # glibc pthread heap address leak - awaiting patched Wolfi glibc build ) # Build JSON array of allowlisted CVE IDs for jq From 7d468bc9e3fa4fac7b3c2dd7c72419e5d38e021d Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Mon, 12 Jan 2026 17:31:37 -0800 Subject: [PATCH 22/46] refetch after key create --- .../src/app/(dashboard)/hooks/keys/useKeys.ts | 2 +- .../src/components/organisms/create_key_button.test.tsx | 4 ++-- .../src/components/organisms/create_key_button.tsx | 8 ++++++++ 3 files changed, 11 insertions(+), 3 deletions(-) diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts index 8ae4d76ff5d..cd3df1a3820 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/keys/useKeys.ts @@ -4,7 +4,7 @@ import { keyListCall } from "@/components/networking"; import { KeyResponse } from "@/components/key_team_helpers/key_list"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; -const keyKeys = createQueryKeys("keys"); +export const keyKeys = createQueryKeys("keys"); export interface KeysResponse { keys: KeyResponse[]; diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.test.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.test.tsx index 08c05f5fadf..bd5e0ee1cbc 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.test.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.test.tsx @@ -1,5 +1,5 @@ -import { render, screen } from "@testing-library/react"; import { beforeEach, describe, expect, it, vi } from "vitest"; +import { renderWithProviders, screen } from "../../../tests/test-utils"; import CreateKey from "./create_key_button"; const mockKeyCreateCall = vi.fn().mockResolvedValue({ @@ -58,7 +58,7 @@ describe("CreateKey", () => { }); it("should render the CreateKey component", () => { - render(); + renderWithProviders(); expect(screen.getByRole("button", { name: /create new key/i })).toBeInTheDocument(); }); }); diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx index 3cd8a04e067..8ad1555dd84 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx @@ -7,6 +7,8 @@ import { Button as Button2, Form, Input, Modal, Radio, Select, Switch, Tooltip } import debounce from "lodash/debounce"; import React, { useCallback, useEffect, useState } from "react"; import { CopyToClipboard } from "react-copy-to-clipboard"; +import { useQueryClient } from "@tanstack/react-query"; +import { createQueryKeys } from "@/app/(dashboard)/hooks/common/queryKeysFactory"; import { rolesWithWriteAccess } from "../../utils/roles"; import AgentSelector from "../agent_management/AgentSelector"; import { mapDisplayToInternalNames } from "../callback_info_helpers"; @@ -36,6 +38,7 @@ import { } from "../networking"; import NumericalInput from "../shared/numerical_input"; import VectorStoreSelector from "../vector_store_management/VectorStoreSelector"; +import { keyKeys } from "@/app/(dashboard)/hooks/keys/useKeys"; const { Option } = Select; @@ -136,6 +139,7 @@ export const fetchUserModels = async ( */ const CreateKey: React.FC = ({ team, teams, data, addKey }) => { const { accessToken, userId: userID, userRole, premiumUser } = useAuthorized(); + const queryClient = useQueryClient(); const [form] = Form.useForm(); const [isModalVisible, setIsModalVisible] = useState(false); const [apiKey, setApiKey] = useState(null); @@ -392,6 +396,10 @@ const CreateKey: React.FC = ({ team, teams, data, addKey }) => { // Also directly update the keys list in VirtualKeysTable without an API call addKey(response); + // Invalidate and refetch all keys list queries to update the table + // This will trigger a refetch of all key list queries regardless of pagination + queryClient.invalidateQueries({ queryKey: keyKeys.lists() }); + setApiKey(response["key"]); setSoftBudget(response["soft_budget"]); NotificationsManager.success("Virtual Key Created"); From a57f1e2e08bf6e70dd251f542ba69e1ef74bae5b Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 10:34:01 +0900 Subject: [PATCH 23/46] test: remove flaky azure oidc embedding test --- tests/local_testing/test_embedding.py | 28 --------------------------- 1 file changed, 28 deletions(-) diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py index 4855932ca9f..d46def7f3ae 100644 --- a/tests/local_testing/test_embedding.py +++ b/tests/local_testing/test_embedding.py @@ -317,34 +317,6 @@ def test_openai_azure_embedding(): pytest.fail(f"Error occurred: {e}") -@pytest.mark.skipif( - os.environ.get("CIRCLE_OIDC_TOKEN") is None, - reason="Cannot run without being in CircleCI Runner", -) -def test_aaaaaa_openai_azure_embedding_with_oidc_and_cf(): - # TODO: Switch to our own Azure account, currently using ai.moda's account - os.environ["AZURE_TENANT_ID"] = "17c0a27a-1246-4aa1-a3b6-d294e80e783c" - os.environ["AZURE_CLIENT_ID"] = "4faf5422-b2bd-45e8-a6d7-46543a38acd0" - - old_key = os.environ["AZURE_API_KEY"] - os.environ.pop("AZURE_API_KEY", None) - - try: - response = embedding( - model="azure/text-embedding-ada-002", - input=["Hello"], - azure_ad_token="oidc/circleci/", - api_base="https://eastus2-litellm.openai.azure.com/", - api_version="2024-06-01", - ) - print(response) - - except Exception as e: - pytest.fail(f"Error occurred: {e}") - finally: - os.environ["AZURE_API_KEY"] = old_key - - from openai.types.embedding import Embedding From b610dad3b8b37b2cc8e0ce151aef65b67fe432ff Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Mon, 12 Jan 2026 17:34:47 -0800 Subject: [PATCH 24/46] fixing build --- .../src/components/organisms/create_key_button.tsx | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx index 8ad1555dd84..f05f1c4183e 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx @@ -1,14 +1,14 @@ "use client"; +import { keyKeys } from "@/app/(dashboard)/hooks/keys/useKeys"; import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized"; import { formatNumberWithCommas } from "@/utils/dataUtils"; import { InfoCircleOutlined } from "@ant-design/icons"; +import { useQueryClient } from "@tanstack/react-query"; import { Accordion, AccordionBody, AccordionHeader, Button, Col, Grid, Text, TextInput, Title } from "@tremor/react"; import { Button as Button2, Form, Input, Modal, Radio, Select, Switch, Tooltip } from "antd"; import debounce from "lodash/debounce"; import React, { useCallback, useEffect, useState } from "react"; import { CopyToClipboard } from "react-copy-to-clipboard"; -import { useQueryClient } from "@tanstack/react-query"; -import { createQueryKeys } from "@/app/(dashboard)/hooks/common/queryKeysFactory"; import { rolesWithWriteAccess } from "../../utils/roles"; import AgentSelector from "../agent_management/AgentSelector"; import { mapDisplayToInternalNames } from "../callback_info_helpers"; @@ -38,7 +38,6 @@ import { } from "../networking"; import NumericalInput from "../shared/numerical_input"; import VectorStoreSelector from "../vector_store_management/VectorStoreSelector"; -import { keyKeys } from "@/app/(dashboard)/hooks/keys/useKeys"; const { Option } = Select; From f14949149831134e125b5f138cc873737d393f4c Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 11:21:57 +0900 Subject: [PATCH 25/46] =?UTF-8?q?bump:=20version=201.80.15=20=E2=86=92=201?= =?UTF-8?q?.80.16?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 36305ad0ed3..aa8e6fd97be 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm" -version = "1.80.15" +version = "1.80.16" description = "Library to easily interface with LLM API providers" authors = ["BerriAI"] license = "MIT" @@ -167,7 +167,7 @@ requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.80.15" +version = "1.80.16" version_files = [ "pyproject.toml:^version" ] From 21d611554b9f1f25326dc13b564d778ed68b4f37 Mon Sep 17 00:00:00 2001 From: Ishaan Jaff Date: Mon, 12 Jan 2026 18:26:53 -0800 Subject: [PATCH 26/46] [Fix] MSFT SSO - allow setting custom MSFT Base URLs (#18977) * fix TestCustomMicrosoftSSO * init CustomMicrosoftSSO * use CustomMicrosoftSSO * docs fix * docs fix --- docs/my-website/docs/proxy/admin_ui_sso.md | 15 ++- docs/my-website/docs/proxy/config_settings.md | 5 +- .../management_endpoints/sso/__init__.py | 12 ++ .../sso/custom_microsoft_sso.py | 91 +++++++++++++ litellm/proxy/management_endpoints/ui_sso.py | 11 +- .../proxy/management_endpoints/test_ui_sso.py | 124 ++++++++++++++++++ 6 files changed, 249 insertions(+), 9 deletions(-) create mode 100644 litellm/proxy/management_endpoints/sso/__init__.py create mode 100644 litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py diff --git a/docs/my-website/docs/proxy/admin_ui_sso.md b/docs/my-website/docs/proxy/admin_ui_sso.md index dba563a327b..4984cac2d0d 100644 --- a/docs/my-website/docs/proxy/admin_ui_sso.md +++ b/docs/my-website/docs/proxy/admin_ui_sso.md @@ -73,8 +73,21 @@ GOOGLE_CLIENT_SECRET= ```shell MICROSOFT_CLIENT_ID="84583a4d-" MICROSOFT_CLIENT_SECRET="nbk8Q~" -MICROSOFT_TENANT="5a39737 +MICROSOFT_TENANT="5a39737" ``` + +**Optional: Custom Microsoft SSO Endpoints** + +If you need to use custom Microsoft SSO endpoints (e.g., for a custom identity provider, sovereign cloud, or proxy), you can override the default endpoints: + +```shell +MICROSOFT_AUTHORIZATION_ENDPOINT="https://your-custom-url.com/oauth2/v2.0/authorize" +MICROSOFT_TOKEN_ENDPOINT="https://your-custom-url.com/oauth2/v2.0/token" +MICROSOFT_USERINFO_ENDPOINT="https://your-custom-graph-api.com/v1.0/me" +``` + +If these are not set, the default Microsoft endpoints are used based on your tenant. + - Set Redirect URI on your App Registration on https://portal.azure.com/ - Set a redirect url = `/sso/callback` ```shell diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md index 42494c1e5f5..e9f9fb37a25 100644 --- a/docs/my-website/docs/proxy/config_settings.md +++ b/docs/my-website/docs/proxy/config_settings.md @@ -771,10 +771,13 @@ router_settings: | MINIMUM_PROMPT_CACHE_TOKEN_COUNT | Minimum token count for caching a prompt. Default is 1024 | MISTRAL_API_BASE | Base URL for Mistral API. Default is https://api.mistral.ai | MISTRAL_API_KEY | API key for Mistral API +| MICROSOFT_AUTHORIZATION_ENDPOINT | Custom authorization endpoint URL for Microsoft SSO (overrides default Microsoft OAuth authorization endpoint) | MICROSOFT_CLIENT_ID | Client ID for Microsoft services | MICROSOFT_CLIENT_SECRET | Client secret for Microsoft services -| MICROSOFT_TENANT | Tenant ID for Microsoft Azure | MICROSOFT_SERVICE_PRINCIPAL_ID | Service Principal ID for Microsoft Enterprise Application. (This is an advanced feature if you want litellm to auto-assign members to Litellm Teams based on their Microsoft Entra ID Groups) +| MICROSOFT_TENANT | Tenant ID for Microsoft Azure +| MICROSOFT_TOKEN_ENDPOINT | Custom token endpoint URL for Microsoft SSO (overrides default Microsoft OAuth token endpoint) +| MICROSOFT_USERINFO_ENDPOINT | Custom userinfo endpoint URL for Microsoft SSO (overrides default Microsoft Graph userinfo endpoint) | NO_DOCS | Flag to disable Swagger UI documentation | NO_REDOC | Flag to disable Redoc documentation | NO_PROXY | List of addresses to bypass proxy diff --git a/litellm/proxy/management_endpoints/sso/__init__.py b/litellm/proxy/management_endpoints/sso/__init__.py new file mode 100644 index 00000000000..8144e7c53ff --- /dev/null +++ b/litellm/proxy/management_endpoints/sso/__init__.py @@ -0,0 +1,12 @@ +""" +SSO (Single Sign-On) related modules for LiteLLM Proxy. + +This package contains custom SSO implementations and utilities. +""" + +from litellm.proxy.management_endpoints.sso.custom_microsoft_sso import ( + CustomMicrosoftSSO, +) + +__all__ = ["CustomMicrosoftSSO"] + diff --git a/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py b/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py new file mode 100644 index 00000000000..61b3a8231ac --- /dev/null +++ b/litellm/proxy/management_endpoints/sso/custom_microsoft_sso.py @@ -0,0 +1,91 @@ +""" +Custom Microsoft SSO class that allows overriding default Microsoft endpoints. + +This module provides a subclass of fastapi_sso's MicrosoftSSO that allows +custom authorization, token, and userinfo endpoints to be specified via environment +variables. + +Environment Variables: +- MICROSOFT_AUTHORIZATION_ENDPOINT: Custom authorization endpoint URL +- MICROSOFT_TOKEN_ENDPOINT: Custom token endpoint URL +- MICROSOFT_USERINFO_ENDPOINT: Custom userinfo endpoint URL + +If these are not set, the default Microsoft endpoints are used. +""" + +import os +from typing import List, Optional, Union + +import pydantic +from fastapi_sso.sso.base import DiscoveryDocument +from fastapi_sso.sso.microsoft import MicrosoftSSO + +from litellm._logging import verbose_proxy_logger + + +class CustomMicrosoftSSO(MicrosoftSSO): + """ + Microsoft SSO subclass that allows overriding default endpoints via environment variables. + + Supports: + - MICROSOFT_AUTHORIZATION_ENDPOINT + - MICROSOFT_TOKEN_ENDPOINT + - MICROSOFT_USERINFO_ENDPOINT + """ + + def __init__( + self, + client_id: str, + client_secret: str, + redirect_uri: Optional[Union[pydantic.AnyHttpUrl, str]] = None, + allow_insecure_http: bool = False, + scope: Optional[List[str]] = None, + tenant: Optional[str] = None, + ): + super().__init__( + client_id=client_id, + client_secret=client_secret, + redirect_uri=redirect_uri, + allow_insecure_http=allow_insecure_http, + scope=scope, + tenant=tenant, + ) + + async def get_discovery_document(self) -> DiscoveryDocument: + """ + Override to support custom endpoints via environment variables. + Falls back to default Microsoft endpoints if not set. + """ + custom_authorization_endpoint = os.getenv( + "MICROSOFT_AUTHORIZATION_ENDPOINT", None + ) + custom_token_endpoint = os.getenv("MICROSOFT_TOKEN_ENDPOINT", None) + custom_userinfo_endpoint = os.getenv("MICROSOFT_USERINFO_ENDPOINT", None) + + # Use custom endpoints if set, otherwise use defaults + authorization_endpoint = ( + custom_authorization_endpoint + or f"https://login.microsoftonline.com/{self.tenant}/oauth2/v2.0/authorize" + ) + token_endpoint = ( + custom_token_endpoint + or f"https://login.microsoftonline.com/{self.tenant}/oauth2/v2.0/token" + ) + userinfo_endpoint = ( + custom_userinfo_endpoint or f"https://graph.microsoft.com/{self.version}/me" + ) + + if custom_authorization_endpoint or custom_token_endpoint or custom_userinfo_endpoint: + verbose_proxy_logger.debug( + f"Using custom Microsoft SSO endpoints - " + f"authorization: {authorization_endpoint}, " + f"token: {token_endpoint}, " + f"userinfo: {userinfo_endpoint}" + ) + + return DiscoveryDocument( + authorization_endpoint=authorization_endpoint, + token_endpoint=token_endpoint, + userinfo_endpoint=userinfo_endpoint, + ) + diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py index dc976e1ce64..5b3ebbf1c27 100644 --- a/litellm/proxy/management_endpoints/ui_sso.py +++ b/litellm/proxy/management_endpoints/ui_sso.py @@ -57,6 +57,7 @@ from litellm.proxy.common_utils.html_forms.jwt_display_template import ( ) from litellm.proxy.common_utils.html_forms.ui_login import html_form from litellm.proxy.management_endpoints.internal_user_endpoints import new_user +from litellm.proxy.management_endpoints.sso import CustomMicrosoftSSO from litellm.proxy.management_endpoints.sso_helper_utils import ( check_is_admin_only_access, has_admin_ui_access, @@ -341,7 +342,7 @@ def generic_response_convertor( if role_mappings is not None and role_mappings.provider.lower() in ["generic", "okta"]: # Use role_mappings to determine role from groups group_claim = role_mappings.group_claim - user_groups_raw = get_nested_value(response, group_claim) + user_groups_raw: Any = get_nested_value(response, group_claim) # Handle different formats: could be a list, string (comma-separated), or single value user_groups: List[str] = [] @@ -1450,8 +1451,6 @@ class SSOAuthenticationHandler: return await google_sso.get_login_redirect(state=state) # Microsoft SSO Auth elif microsoft_client_id is not None: - from fastapi_sso.sso.microsoft import MicrosoftSSO - microsoft_client_secret = os.getenv("MICROSOFT_CLIENT_SECRET", None) microsoft_tenant = os.getenv("MICROSOFT_TENANT", None) if microsoft_client_secret is None: @@ -1461,7 +1460,7 @@ class SSOAuthenticationHandler: param="MICROSOFT_CLIENT_SECRET", code=status.HTTP_500_INTERNAL_SERVER_ERROR, ) - microsoft_sso = MicrosoftSSO( + microsoft_sso = CustomMicrosoftSSO( client_id=microsoft_client_id, client_secret=microsoft_client_secret, tenant=microsoft_tenant, @@ -2277,8 +2276,6 @@ class MicrosoftSSOHandler: Args: return_raw_sso_response: If True, return the raw SSO response """ - from fastapi_sso.sso.microsoft import MicrosoftSSO - microsoft_client_secret = os.getenv("MICROSOFT_CLIENT_SECRET", None) microsoft_tenant = os.getenv("MICROSOFT_TENANT", None) if microsoft_client_secret is None: @@ -2295,7 +2292,7 @@ class MicrosoftSSOHandler: param="MICROSOFT_TENANT", code=status.HTTP_500_INTERNAL_SERVER_ERROR, ) - microsoft_sso = MicrosoftSSO( + microsoft_sso = CustomMicrosoftSSO( client_id=microsoft_client_id, client_secret=microsoft_client_secret, tenant=microsoft_tenant, diff --git a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py index 829e76108c4..be9d193e3f1 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py +++ b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py @@ -18,6 +18,7 @@ sys.path.insert( import litellm from litellm.proxy._types import LiteLLM_UserTable, NewTeamRequest, NewUserResponse from litellm.proxy.auth.handle_jwt import JWTHandler +from litellm.proxy.management_endpoints.sso import CustomMicrosoftSSO from litellm.proxy.management_endpoints.types import CustomOpenID from litellm.proxy.management_endpoints.ui_sso import ( GoogleSSOHandler, @@ -3386,3 +3387,126 @@ class TestSSOReadinessEndpoint: ) finally: app.dependency_overrides.clear() + + +class TestCustomMicrosoftSSO: + """Tests for CustomMicrosoftSSO class.""" + + @pytest.mark.asyncio + async def test_custom_microsoft_sso_uses_default_endpoints_when_no_env_vars(self): + """ + Test that CustomMicrosoftSSO uses default Microsoft endpoints + when no custom environment variables are set. + """ + # Ensure no custom endpoints are set + for key in [ + "MICROSOFT_AUTHORIZATION_ENDPOINT", + "MICROSOFT_TOKEN_ENDPOINT", + "MICROSOFT_USERINFO_ENDPOINT", + ]: + os.environ.pop(key, None) + + sso = CustomMicrosoftSSO( + client_id="test-client-id", + client_secret="test-client-secret", + tenant="test-tenant", + redirect_uri="http://localhost:4000/sso/callback", + ) + + discovery = await sso.get_discovery_document() + + assert discovery["authorization_endpoint"] == "https://login.microsoftonline.com/test-tenant/oauth2/v2.0/authorize" + assert discovery["token_endpoint"] == "https://login.microsoftonline.com/test-tenant/oauth2/v2.0/token" + assert discovery["userinfo_endpoint"] == "https://graph.microsoft.com/v1.0/me" + + @pytest.mark.asyncio + async def test_custom_microsoft_sso_uses_custom_endpoints_when_env_vars_set(self): + """ + Test that CustomMicrosoftSSO uses custom endpoints + when environment variables are set. + """ + custom_auth_endpoint = "https://custom.example.com/oauth2/v2.0/authorize" + custom_token_endpoint = "https://custom.example.com/oauth2/v2.0/token" + custom_userinfo_endpoint = "https://custom.example.com/v1.0/me" + + with patch.dict( + os.environ, + { + "MICROSOFT_AUTHORIZATION_ENDPOINT": custom_auth_endpoint, + "MICROSOFT_TOKEN_ENDPOINT": custom_token_endpoint, + "MICROSOFT_USERINFO_ENDPOINT": custom_userinfo_endpoint, + }, + ): + sso = CustomMicrosoftSSO( + client_id="test-client-id", + client_secret="test-client-secret", + tenant="test-tenant", + redirect_uri="http://localhost:4000/sso/callback", + ) + + discovery = await sso.get_discovery_document() + + assert discovery["authorization_endpoint"] == custom_auth_endpoint + assert discovery["token_endpoint"] == custom_token_endpoint + assert discovery["userinfo_endpoint"] == custom_userinfo_endpoint + + @pytest.mark.asyncio + async def test_custom_microsoft_sso_uses_partial_custom_endpoints(self): + """ + Test that CustomMicrosoftSSO uses custom endpoints for those set, + and defaults for others. + """ + custom_auth_endpoint = "https://custom.example.com/oauth2/v2.0/authorize" + + # Clear other env vars first + os.environ.pop("MICROSOFT_TOKEN_ENDPOINT", None) + os.environ.pop("MICROSOFT_USERINFO_ENDPOINT", None) + + with patch.dict( + os.environ, + { + "MICROSOFT_AUTHORIZATION_ENDPOINT": custom_auth_endpoint, + }, + ): + sso = CustomMicrosoftSSO( + client_id="test-client-id", + client_secret="test-client-secret", + tenant="test-tenant", + redirect_uri="http://localhost:4000/sso/callback", + ) + + discovery = await sso.get_discovery_document() + + # Custom auth endpoint + assert discovery["authorization_endpoint"] == custom_auth_endpoint + # Default token and userinfo endpoints + assert discovery["token_endpoint"] == "https://login.microsoftonline.com/test-tenant/oauth2/v2.0/token" + assert discovery["userinfo_endpoint"] == "https://graph.microsoft.com/v1.0/me" + + def test_custom_microsoft_sso_uses_common_tenant_when_none(self): + """ + Test that CustomMicrosoftSSO uses 'common' tenant when tenant is None. + """ + sso = CustomMicrosoftSSO( + client_id="test-client-id", + client_secret="test-client-secret", + tenant=None, + redirect_uri="http://localhost:4000/sso/callback", + ) + + assert sso.tenant == "common" + + def test_custom_microsoft_sso_is_subclass_of_microsoft_sso(self): + """ + Test that CustomMicrosoftSSO is a subclass of MicrosoftSSO. + """ + from fastapi_sso.sso.microsoft import MicrosoftSSO + + sso = CustomMicrosoftSSO( + client_id="test-client-id", + client_secret="test-client-secret", + tenant="test-tenant", + redirect_uri="http://localhost:4000/sso/callback", + ) + + assert isinstance(sso, MicrosoftSSO) From 0dbeb5634649b4d35fdeb1eaa3cd49d237a49536 Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Mon, 12 Jan 2026 18:28:29 -0800 Subject: [PATCH 27/46] Simplify Key Generate Permission Error --- .../organisms/create_key_button.tsx | 4 +- .../src/components/organisms/utils.test.ts | 146 ++++++++++++++++++ .../src/components/organisms/utils.ts | 56 +++++++ 3 files changed, 205 insertions(+), 1 deletion(-) create mode 100644 ui/litellm-dashboard/src/components/organisms/utils.test.ts create mode 100644 ui/litellm-dashboard/src/components/organisms/utils.ts diff --git a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx index f05f1c4183e..90ed9a62cc0 100644 --- a/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx +++ b/ui/litellm-dashboard/src/components/organisms/create_key_button.tsx @@ -38,6 +38,7 @@ import { } from "../networking"; import NumericalInput from "../shared/numerical_input"; import VectorStoreSelector from "../vector_store_management/VectorStoreSelector"; +import { simplifyKeyGenerateError } from "./utils"; const { Option } = Select; @@ -406,7 +407,8 @@ const CreateKey: React.FC = ({ team, teams, data, addKey }) => { localStorage.removeItem("userData" + userID); } catch (error) { console.log("error in create key:", error); - NotificationsManager.fromBackend(`Error creating the key: ${error}`); + const simplifiedError = simplifyKeyGenerateError(error); + NotificationsManager.fromBackend(simplifiedError); } }; diff --git a/ui/litellm-dashboard/src/components/organisms/utils.test.ts b/ui/litellm-dashboard/src/components/organisms/utils.test.ts new file mode 100644 index 00000000000..df653003a9a --- /dev/null +++ b/ui/litellm-dashboard/src/components/organisms/utils.test.ts @@ -0,0 +1,146 @@ +import { describe, expect, it } from "vitest"; +import { simplifyKeyGenerateError } from "./utils"; + +describe("simplifyKeyGenerateError", () => { + const expectedSimplifiedMessage = + "Team member does not have permission to generate key for this team. Ask your proxy admin to configure the team member permission settings."; + + describe("when error is NOT related to /key/generate", () => { + it("should return the original error message for generic errors", () => { + const error = "Some random error"; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: Some random error"); + }); + + it("should return the original error message for other endpoint errors", () => { + const error = "Error: Failed to fetch /key/list"; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: Error: Failed to fetch /key/list"); + }); + + it("should handle Error objects for non-/key/generate errors", () => { + const error = new Error("Database connection failed"); + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: Error: Database connection failed"); + }); + }); + + describe("when error is related to /key/generate team member permission error", () => { + it("should simplify JSON error with team_member_permission_error", () => { + const error = JSON.stringify({ + error: { + message: + "Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE. You only have access to the following endpoints: ['/key/info', '/key/health'] for team 60f6c0db-3ed9-4112-a2ef-8d838b2c8679. To create keys for this team, please ask your proxy admin to check the team member permission settings and update the settings to allow team member users to create keys.", + type: "team_member_permission_error", + param: "/key/generate", + code: "401", + }, + }); + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should simplify error string containing /key/generate and team_member_permission_error", () => { + const error = + 'Error creating the key: {"error":{"message":"Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE. You only have access to the following endpoints: [\'/key/info\', \'/key/health\'] for team 60f6c0db-3ed9-4112-a2ef-8d838b2c8679. To create keys for this team, please ask your proxy admin to check the team member permission settings and update the settings to allow team member users to create keys.","type":"team_member_permission_error","param":"/key/generate","code":"401"}}'; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should simplify error with KeyManagementRoutes.KEY_GENERATE in message", () => { + const error = + "Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE. Ask your proxy admin to check the team member permission settings."; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should handle nested error object structure", () => { + const error = { + error: { + message: + "Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE. You only have access to the following endpoints: ['/key/info', '/key/health'].", + type: "team_member_permission_error", + }, + }; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should handle error with team_member_permission_error type in string", () => { + const error = + 'Some prefix {"error":{"type":"team_member_permission_error","message":"Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE"}} some suffix'; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + }); + + describe("when error is related to /key/generate but NOT a permission error", () => { + it("should return original error message for /key/generate validation errors", () => { + const error = "Invalid request to /key/generate: missing required field"; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: Invalid request to /key/generate: missing required field"); + }); + + it("should return original error message for /key/generate server errors", () => { + const error = JSON.stringify({ + error: { + message: "Internal server error occurred while processing /key/generate", + type: "server_error", + code: "500", + }, + }); + const result = simplifyKeyGenerateError(error); + expect(result).toBe(`Error creating the key: ${error}`); + }); + }); + + describe("edge cases", () => { + it("should handle malformed JSON gracefully", () => { + const error = + '{"error":{"message":"Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE", invalid json'; + const result = simplifyKeyGenerateError(error); + // Should still detect the permission error from the string content + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should handle empty string", () => { + const error = ""; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: "); + }); + + it("should handle null", () => { + const error = null; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: null"); + }); + + it("should handle undefined", () => { + const error = undefined; + const result = simplifyKeyGenerateError(error); + expect(result).toBe("Error creating the key: undefined"); + }); + + it("should handle Error object with /key/generate permission error", () => { + const error = new Error( + '{"error":{"message":"Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE","type":"team_member_permission_error"}}', + ); + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should handle error with multiple JSON objects", () => { + const error = + 'Prefix {"error":{"message":"Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE","type":"team_member_permission_error"}} suffix {"other":"data"}'; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + + it("should handle error message without explicit team_member_permission_error type but with permission text", () => { + const error = + "Team member does not have permissions for endpoint: KeyManagementRoutes.KEY_GENERATE. Please contact admin."; + const result = simplifyKeyGenerateError(error); + expect(result).toBe(expectedSimplifiedMessage); + }); + }); +}); diff --git a/ui/litellm-dashboard/src/components/organisms/utils.ts b/ui/litellm-dashboard/src/components/organisms/utils.ts new file mode 100644 index 00000000000..c08fb10e8ae --- /dev/null +++ b/ui/litellm-dashboard/src/components/organisms/utils.ts @@ -0,0 +1,56 @@ +/** + * Helper function to simplify /key/generate permission errors + * Extracts a user-friendly error message from team member permission errors + * @param error - The error object or message + * @returns A simplified error message string + */ +export const simplifyKeyGenerateError = (error: any): string => { + // Handle plain objects by stringifying them first + let errorString: string; + if (error && typeof error === "object" && !(error instanceof Error)) { + errorString = JSON.stringify(error); + } else { + errorString = String(error); + } + + // Check if this is a /key/generate team member permission error + if (!errorString.includes("/key/generate") && !errorString.includes("KeyManagementRoutes.KEY_GENERATE")) { + return `Error creating the key: ${error}`; + } + + // Try to parse JSON if the message contains JSON or extract from object + let errorMessage = errorString; + try { + // If error is already an object, extract message directly + if (error && typeof error === "object" && !(error instanceof Error)) { + const errorObj = error?.error || error; + if (errorObj?.message) { + errorMessage = errorObj.message; + } + } else { + // Try to parse JSON from string + const jsonMatch = errorString.match(/\{[\s\S]*\}/); + if (jsonMatch) { + const parsedError = JSON.parse(jsonMatch[0]); + const errorObj = parsedError?.error || parsedError; + if (errorObj?.message) { + errorMessage = errorObj.message; + } + } + } + } catch (e) { + // If parsing fails, use the original message + } + + // Check if this is a team member permission error + if ( + errorString.includes("team_member_permission_error") || + errorMessage.includes("Team member does not have permissions") + ) { + // Return the simplified message + return "Team member does not have permission to generate key for this team. Ask your proxy admin to configure the team member permission settings."; + } + + // If it's not a permission error, return the original error message + return `Error creating the key: ${error}`; +}; From c4e6ae4d9e92ef84f4f00b0b82fdb13d6705a2d5 Mon Sep 17 00:00:00 2001 From: Ishaan Jaff Date: Mon, 12 Jan 2026 18:48:17 -0800 Subject: [PATCH 28/46] [Feat] UI Feedback Form - why LiteLLM (#18999) * init survey prompt * init survey modal * init Survey Modal * POST feedback hook * survey Modal * add other * in product survey fixes * fix survey prompt * fix survey --- ui/litellm-dashboard/src/app/page.tsx | 46 +++ .../src/components/survey/SurveyModal.tsx | 385 ++++++++++++++++++ .../src/components/survey/SurveyPrompt.tsx | 77 ++++ .../src/components/survey/index.tsx | 3 + 4 files changed, 511 insertions(+) create mode 100644 ui/litellm-dashboard/src/components/survey/SurveyModal.tsx create mode 100644 ui/litellm-dashboard/src/components/survey/SurveyPrompt.tsx create mode 100644 ui/litellm-dashboard/src/components/survey/index.tsx diff --git a/ui/litellm-dashboard/src/app/page.tsx b/ui/litellm-dashboard/src/app/page.tsx index 598266df9a2..ac019a7a8c5 100644 --- a/ui/litellm-dashboard/src/app/page.tsx +++ b/ui/litellm-dashboard/src/app/page.tsx @@ -27,6 +27,7 @@ import PromptsPanel from "@/components/prompts"; import PublicModelHub from "@/components/public_model_hub"; import { SearchTools } from "@/components/search_tools"; import Settings from "@/components/settings"; +import { SurveyPrompt, SurveyModal } from "@/components/survey"; import TagManagement from "@/components/tag_management"; import TransformRequestPanel from "@/components/transform_request"; import UIThemeSettings from "@/components/ui_theme_settings"; @@ -119,6 +120,10 @@ export default function CreateKeyPage() { const [authLoading, setAuthLoading] = useState(true); const [userID, setUserID] = useState(null); + // Survey state - always show by default + const [showSurveyPrompt, setShowSurveyPrompt] = useState(true); + const [showSurveyModal, setShowSurveyModal] = useState(false); + const invitation_id = searchParams.get("invitation_id"); // Get page from URL, default to 'api-keys' if not present @@ -262,6 +267,35 @@ export default function CreateKeyPage() { } }, [accessToken, userID, userRole]); + // Auto-dismiss survey prompt after 15 seconds + useEffect(() => { + if (showSurveyPrompt && !showSurveyModal) { + const timer = setTimeout(() => { + setShowSurveyPrompt(false); + }, 15000); + return () => clearTimeout(timer); + } + }, [showSurveyPrompt, showSurveyModal]); + + const handleOpenSurvey = () => { + setShowSurveyPrompt(false); + setShowSurveyModal(true); + }; + + const handleDismissSurveyPrompt = () => { + setShowSurveyPrompt(false); + }; + + const handleSurveyComplete = () => { + setShowSurveyModal(false); + }; + + const handleSurveyModalClose = () => { + // If they close the modal without completing, show the prompt again + setShowSurveyModal(false); + setShowSurveyPrompt(true); + }; + if (authLoading || redirectToLogin) { return ; } @@ -457,6 +491,18 @@ export default function CreateKeyPage() { /> )} + + {/* Survey Components */} + + )} diff --git a/ui/litellm-dashboard/src/components/survey/SurveyModal.tsx b/ui/litellm-dashboard/src/components/survey/SurveyModal.tsx new file mode 100644 index 00000000000..3a1dc68f198 --- /dev/null +++ b/ui/litellm-dashboard/src/components/survey/SurveyModal.tsx @@ -0,0 +1,385 @@ +import React, { useState } from "react"; +import { X, MessageSquare, ArrowRight, ArrowLeft } from "lucide-react"; +import { Button, Input, Radio, Space, Progress, Checkbox } from "antd"; + +interface SurveyModalProps { + isOpen: boolean; + onClose: () => void; + onComplete: () => void; +} + +const REASONS_OPTIONS = [ + { + id: "oss_adoption", + label: "OSS Adoption", + description: "Stars, contributors, forks, community support", + }, + { + id: "ai_integration", + label: "AI Integration", + description: "LiteLLM had the logging/guardrail integration we needed - Langfuse, OTEL, S3 logging, Azure Content Safety guardrails", + }, + { + id: "unified_api", + label: "Unified API", + description: "LiteLLM had the best OpenAI-compatible API across providers - OpenAI, Anthropic, Gemini, etc.", + }, + { + id: "breadth_of_models", + label: "Breadth of Models/Providers", + description: "LiteLLM had the provider + endpoint combinations we needed - /ocr endpoint with Mistral OCR, /batches endppint with Bedrock API, etc.", + }, + { + id: "other", + label: "Other", + description: "Something else not listed above", + }, +]; + +type SurveyData = { + usingAtCompany: boolean | null; + companyName: string; + startDate: string; + reasons: string[]; + otherReason: string; + email: string; +}; + +export function SurveyModal({ isOpen, onClose, onComplete }: SurveyModalProps) { + const [step, setStep] = useState(1); + const [data, setData] = useState({ + usingAtCompany: null, + companyName: "", + startDate: "", + reasons: [], + otherReason: "", + email: "", + }); + const [isSubmitting, setIsSubmitting] = useState(false); + + // Steps: 1=company?, 2=company name (conditional), 3=when, 4=why, 5=email + // If not at company: skip step 2, so total is 4 + // If at company: total is 5 + const totalSteps = data.usingAtCompany === true ? 5 : 4; + + if (!isOpen) return null; + + const handleNext = () => { + // Skip company name step if not using at company + if (step === 1 && data.usingAtCompany === false) { + setStep(3); // Skip to "when did you start" + } else if (step < 5) { + setStep(step + 1); + } else { + handleSubmit(); + } + }; + + const handleBack = () => { + if (step === 3 && data.usingAtCompany === false) { + setStep(1); // Go back to first question if we skipped company name + } else { + setStep(step - 1); + } + }; + + const handleSubmit = async () => { + setIsSubmitting(true); + try { + // Map reason IDs to readable labels + const reasonLabels: Record = { + oss_adoption: "OSS Adoption (stars, contributors, forks)", + ai_integration: "AI Integration (Langfuse, OTEL, S3, Azure Content Safety)", + unified_api: "Unified API (OpenAI-compatible)", + breadth_of_models: "Breadth of Models/Providers (/ocr, /batches, Bedrock, Azure OCR)", + }; + + const readableReasons = data.reasons.map((r) => { + if (r === "other" && data.otherReason) { + return `Other: ${data.otherReason}`; + } + return reasonLabels[r] || r; + }); + + await fetch("https://hooks.zapier.com/hooks/catch/16331268/ugms6w0/", { + method: "POST", + mode: "no-cors", + headers: { + "Content-Type": "application/json", + }, + body: JSON.stringify({ + usingAtCompany: data.usingAtCompany ? "Yes" : "No", + companyName: data.companyName || null, + startDate: data.startDate, + reasons: readableReasons.join(", "), + otherReason: data.otherReason || null, + email: data.email || null, + submittedAt: new Date().toISOString(), + }), + }); + } catch (error) { + // Silently fail - don't block the user experience + console.error("Failed to submit survey:", error); + } + setIsSubmitting(false); + onComplete(); + }; + + const updateData = (key: keyof SurveyData, value: boolean | string | string[] | null) => { + setData((prev) => ({ + ...prev, + [key]: value, + })); + }; + + const toggleReason = (reasonId: string) => { + setData((prev) => ({ + ...prev, + reasons: prev.reasons.includes(reasonId) + ? prev.reasons.filter((r) => r !== reasonId) + : [...prev.reasons, reasonId], + })); + }; + + const isStepValid = () => { + if (step === 1) return data.usingAtCompany !== null; + if (step === 2) return data.companyName.trim().length > 0; + if (step === 3) return data.startDate !== ""; + if (step === 4) { + // If "other" is selected, require the text field + if (data.reasons.includes("other")) { + return data.reasons.length > 0 && data.otherReason.trim().length > 0; + } + return data.reasons.length > 0; + } + if (step === 5) return true; // Email is optional + return false; + }; + + const getStepNumber = () => { + if (data.usingAtCompany === false) { + // When not at company: skip step 2, so steps 3,4,5 become 2,3,4 + if (step === 1) return 1; + if (step === 3) return 2; + if (step === 4) return 3; + if (step === 5) return 4; + } + return step; + }; + + const renderStepContent = () => { + // Step 1: Using at company? + if (step === 1) { + return ( +
+

Are you using LiteLLM at your company?

+

Help us understand how our product is being used in professional environments.

+
+ + +
+
+ ); + } + + // Step 2: Company name (only if using at company) + if (step === 2 && data.usingAtCompany === true) { + return ( +
+

What company are you using LiteLLM at?

+

This helps us understand our user base better.

+ updateData("companyName", e.target.value)} + autoFocus + /> +
+ ); + } + + // Step 3: When did you start? + if (step === 3) { + return ( +
+

When did you start using LiteLLM?

+ updateData("startDate", e.target.value)} + className="w-full" + > + + {["Less than a month ago", "1-3 months ago", "3-6 months ago", "More than 6 months ago"].map((option) => ( + + ))} + + +
+ ); + } + + // Step 4: Why did you pick LiteLLM? + if (step === 4) { + return ( +
+

Why did you pick LiteLLM over other AI Gateways?

+

Select all that apply.

+
+ {REASONS_OPTIONS.map((option) => { + const isSelected = data.reasons.includes(option.id); + return ( +
+
toggleReason(option.id)} + onKeyDown={(e) => { + if (e.key === "Enter" || e.key === " ") { + e.preventDefault(); + toggleReason(option.id); + } + }} + className={`flex items-start p-4 rounded-lg border cursor-pointer transition-all ${ + isSelected + ? "border-blue-600 bg-blue-50 ring-1 ring-blue-600" + : "border-gray-200 hover:bg-gray-50" + }`} + > + +
+ {option.label} + {option.description} +
+
+ {/* Show text input if "Other" is selected */} + {option.id === "other" && isSelected && ( + updateData("otherReason", e.target.value)} + onClick={(e) => e.stopPropagation()} + autoFocus + /> + )} +
+ ); + })} +
+
+ ); + } + + // Step 5: Email (optional) + if (step === 5) { + return ( +
+

Want to share more?

+

+ Leave your email and we may reach out to learn more about your experience. This is completely optional. +

+ updateData("email", e.target.value)} + autoFocus + /> +

+ We will only use this to follow up on your feedback. No spam, ever. +

+
+ ); + } + + return null; + }; + + const isLastStep = step === 5; + + return ( +
+ {/* Backdrop */} +
+ + {/* Modal */} +
+ {/* Header */} +
+
+ + Quick Feedback +
+ +
+ + {/* Progress Bar */} + + + {/* Content */} +
{renderStepContent()}
+ + {/* Footer */} +
+
+ Step {getStepNumber()} of {totalSteps} +
+
+ {step > 1 && ( + + )} + +
+
+
+
+ ); +} + diff --git a/ui/litellm-dashboard/src/components/survey/SurveyPrompt.tsx b/ui/litellm-dashboard/src/components/survey/SurveyPrompt.tsx new file mode 100644 index 00000000000..69a886bddeb --- /dev/null +++ b/ui/litellm-dashboard/src/components/survey/SurveyPrompt.tsx @@ -0,0 +1,77 @@ +import React, { useEffect, useState } from "react"; +import { MessageSquare, X } from "lucide-react"; +import { Button } from "antd"; + +interface SurveyPromptProps { + onOpen: () => void; + onDismiss: () => void; + isVisible: boolean; +} + +const DISMISS_DURATION = 15000; // 15 seconds + +export function SurveyPrompt({ onOpen, onDismiss, isVisible }: SurveyPromptProps) { + const [progress, setProgress] = useState(100); + + useEffect(() => { + if (!isVisible) { + setProgress(100); + return; + } + + const startTime = Date.now(); + const interval = setInterval(() => { + const elapsed = Date.now() - startTime; + const remaining = Math.max(0, 100 - (elapsed / DISMISS_DURATION) * 100); + setProgress(remaining); + + if (remaining <= 0) { + clearInterval(interval); + } + }, 50); + + return () => clearInterval(interval); + }, [isVisible]); + + if (!isVisible) return null; + + return ( +
+ {/* Progress bar at top showing time remaining */} +
+
+
+ +
+
+
+ + Quick feedback +
+ +
+ +

+ Help us improve LiteLLM! Share your experience in 5 quick questions. +

+ + +
+
+ ); +} + diff --git a/ui/litellm-dashboard/src/components/survey/index.tsx b/ui/litellm-dashboard/src/components/survey/index.tsx new file mode 100644 index 00000000000..7c36419980c --- /dev/null +++ b/ui/litellm-dashboard/src/components/survey/index.tsx @@ -0,0 +1,3 @@ +export { SurveyPrompt } from "./SurveyPrompt"; +export { SurveyModal } from "./SurveyModal"; + From dd959790bb048df6f81515ae2cb6bb49dbe04a42 Mon Sep 17 00:00:00 2001 From: Ishaan Jaffer Date: Mon, 12 Jan 2026 18:53:42 -0800 Subject: [PATCH 29/46] fix build --- ui/litellm-dashboard/tsconfig.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ui/litellm-dashboard/tsconfig.json b/ui/litellm-dashboard/tsconfig.json index 7b285893049..ff13d355267 100644 --- a/ui/litellm-dashboard/tsconfig.json +++ b/ui/litellm-dashboard/tsconfig.json @@ -22,5 +22,5 @@ } }, "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"], - "exclude": ["node_modules"] + "exclude": ["node_modules", "e2e_tests"] } 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this._client.delete(tp`/v1/messages/batches/${e}?beta=true`,{...n,headers:th([{"anthropic-beta":[...r??[],"message-batches-2024-09-24"].toString()},n?.headers])})}cancel(e,t={},n){let{betas:r}=t??{};return this._client.post(tp`/v1/messages/batches/${e}/cancel?beta=true`,{...n,headers:th([{"anthropic-beta":[...r??[],"message-batches-2024-09-24"].toString()},n?.headers])})}async results(e,t={},n){let r=await this.retrieve(e);if(!r.results_url)throw new ei(`No batch \`results_url\`; Has it finished processing? ${r.processing_status} - ${r.id}`);let{betas:a}=t??{};return this._client.get(r.results_url,{...n,headers:th([{"anthropic-beta":[...a??[],"message-batches-2024-09-24"].toString(),Accept:"application/binary"},n?.headers]),stream:!0,__binaryResponse:!0})._thenUnwrap((e,t)=>tb.fromResponse(t.response,t.controller))}}let ty=e=>{let t=0,n=[];for(;t{if(0===e.length)return e;let t=e[e.length-1];switch(t.type){case"separator":return tw(e=e.slice(0,e.length-1));case"number":let 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0),u.set(this,()=>{}),d.set(this,()=>{}),h.set(this,void 0),f.set(this,()=>{}),p.set(this,()=>{}),g.set(this,{}),m.set(this,!1),b.set(this,!1),v.set(this,!1),y.set(this,!1),w.set(this,void 0),_.set(this,void 0),x.set(this,e=>{if(et(this,b,!0,"f"),ea(e)&&(e=new el),e instanceof el)return et(this,v,!0,"f"),this._emit("abort",e);if(e instanceof ei)return this._emit("error",e);if(e instanceof Error){let t=new ei(e.message);return t.cause=e,this._emit("error",t)}return this._emit("error",new ei(String(e)))}),et(this,c,new Promise((e,t)=>{et(this,u,e,"f"),et(this,d,t,"f")}),"f"),et(this,h,new Promise((e,t)=>{et(this,f,e,"f"),et(this,p,t,"f")}),"f"),en(this,c,"f").catch(()=>{}),en(this,h,"f").catch(()=>{})}get response(){return en(this,w,"f")}get request_id(){return en(this,_,"f")}async withResponse(){let e=await en(this,c,"f");if(!e)throw Error("Could not resolve a `Response` object");return{data:this,response:e,request_id:e.headers.get("request-id")}}static fromReadableStream(e){let t=new tE;return t._run(()=>t._fromReadableStream(e)),t}static createMessage(e,t,n){let r=new tE;for(let e of t.messages)r._addMessageParam(e);return r._run(()=>r._createMessage(e,{...t,stream:!0},{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),r}_run(e){e().then(()=>{this._emitFinal(),this._emit("end")},en(this,x,"f"))}_addMessageParam(e){this.messages.push(e)}_addMessage(e,t=!0){this.receivedMessages.push(e),t&&this._emit("message",e)}async _createMessage(e,t,n){let r=n?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),en(this,o,"m",M).call(this);let{response:a,data:s}=await e.create({...t,stream:!0},{...n,signal:this.controller.signal}).withResponse();for await(let e of(this._connected(a),s))en(this,o,"m",E).call(this,e);if(s.controller.signal?.aborted)throw new el;en(this,o,"m",C).call(this)}_connected(e){this.ended||(et(this,w,e,"f"),et(this,_,e?.headers.get("request-id"),"f"),en(this,u,"f").call(this,e),this._emit("connect"))}get ended(){return en(this,m,"f")}get errored(){return en(this,b,"f")}get aborted(){return en(this,v,"f")}abort(){this.controller.abort()}on(e,t){return(en(this,g,"f")[e]||(en(this,g,"f")[e]=[])).push({listener:t}),this}off(e,t){let n=en(this,g,"f")[e];if(!n)return this;let r=n.findIndex(e=>e.listener===t);return r>=0&&n.splice(r,1),this}once(e,t){return(en(this,g,"f")[e]||(en(this,g,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,n)=>{et(this,y,!0,"f"),"error"!==e&&this.once("error",n),this.once(e,t)})}async done(){et(this,y,!0,"f"),await en(this,h,"f")}get currentMessage(){return en(this,l,"f")}async finalMessage(){return await this.done(),en(this,o,"m",k).call(this)}async finalText(){return await this.done(),en(this,o,"m",S).call(this)}_emit(e,...t){if(en(this,m,"f"))return;"end"===e&&(et(this,m,!0,"f"),en(this,f,"f").call(this));let n=en(this,g,"f")[e];if(n&&(en(this,g,"f")[e]=n.filter(e=>!e.once),n.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];en(this,y,"f")||n?.length||Promise.reject(e),en(this,d,"f").call(this,e),en(this,p,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];en(this,y,"f")||n?.length||Promise.reject(e),en(this,d,"f").call(this,e),en(this,p,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",en(this,o,"m",k).call(this))}async _fromReadableStream(e,t){let n=t?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort())),en(this,o,"m",M).call(this),this._connected(null);let r=eV.fromReadableStream(e,this.controller);for await(let e of r)en(this,o,"m",E).call(this,e);if(r.controller.signal?.aborted)throw new el;en(this,o,"m",C).call(this)}[(l=new WeakMap,c=new WeakMap,u=new WeakMap,d=new WeakMap,h=new WeakMap,f=new WeakMap,p=new WeakMap,g=new WeakMap,m=new WeakMap,b=new WeakMap,v=new WeakMap,y=new WeakMap,w=new WeakMap,_=new WeakMap,x=new WeakMap,o=new WeakSet,k=function(){if(0===this.receivedMessages.length)throw new ei("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},S=function(){if(0===this.receivedMessages.length)throw new ei("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new ei("stream ended without producing a content block with type=text");return e.join(" ")},M=function(){this.ended||et(this,l,void 0,"f")},E=function(e){if(this.ended)return;let t=en(this,o,"m",R).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let n=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===n.type&&this._emit("text",e.delta.text,n.text||"");break;case"citations_delta":"text"===n.type&&this._emit("citation",e.delta.citation,n.citations??[]);break;case"input_json_delta":tM(n)&&n.input&&this._emit("inputJson",e.delta.partial_json,n.input);break;case"thinking_delta":"thinking"===n.type&&this._emit("thinking",e.delta.thinking,n.thinking);break;case"signature_delta":"thinking"===n.type&&this._emit("signature",n.signature);break;default:e.delta}break}case"message_stop":this._addMessageParam(t),this._addMessage(t,!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":et(this,l,t,"f")}},C=function(){if(this.ended)throw new ei("stream has ended, this shouldn't happen");let e=en(this,l,"f");if(!e)throw new ei("request ended without sending any chunks");return et(this,l,void 0,"f"),e},R=function(e){let t=en(this,l,"f");if("message_start"===e.type){if(t)throw new ei(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new ei(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.container=e.delta.container,t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push(e.content_block),t;case"content_block_delta":{let n=t.content.at(e.index);switch(e.delta.type){case"text_delta":n?.type==="text"&&(n.text+=e.delta.text);break;case"citations_delta":n?.type==="text"&&(n.citations??(n.citations=[]),n.citations.push(e.delta.citation));break;case"input_json_delta":if(n&&tM(n)){let t=n[tx]||"";if(Object.defineProperty(n,tx,{value:t+=e.delta.partial_json,enumerable:!1,writable:!0}),t)try{n.input=tS(t)}catch(n){let e=new ei(`Unable to parse tool parameter JSON from model. Please retry your request or adjust your prompt. Error: ${n}. JSON: ${t}`);en(this,x,"f").call(this,e)}}break;case"thinking_delta":n?.type==="thinking"&&(n.thinking+=e.delta.thinking);break;case"signature_delta":n?.type==="thinking"&&(n.signature=e.delta.signature);break;default:e.delta}return t}}},Symbol.asyncIterator)](){let e=[],t=[],n=!1;return this.on("streamEvent",n=>{let r=t.shift();r?r.resolve(n):e.push(n)}),this.on("end",()=>{for(let e of(n=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(n=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(n=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:n?{value:void 0,done:!0}:new Promise((e,n)=>t.push({resolve:e,reject:n})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new eV(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}let tC={"claude-opus-4-20250514":8192,"claude-opus-4-0":8192,"claude-4-opus-20250514":8192,"anthropic.claude-opus-4-20250514-v1:0":8192,"claude-opus-4@20250514":8192},tR={"claude-1.3":"November 6th, 2024","claude-1.3-100k":"November 6th, 2024","claude-instant-1.1":"November 6th, 2024","claude-instant-1.1-100k":"November 6th, 2024","claude-instant-1.2":"November 6th, 2024","claude-3-sonnet-20240229":"July 21st, 2025","claude-2.1":"July 21st, 2025","claude-2.0":"July 21st, 2025"};class tP extends tc{constructor(){super(...arguments),this.batches=new tv(this._client)}create(e,t){let{betas:n,...r}=e;r.model in tR&&console.warn(`The model '${r.model}' is deprecated and will reach end-of-life on ${tR[r.model]} +Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.`);let a=this._client._options.timeout;if(!r.stream&&null==a){let e=tC[r.model]??void 0;a=this._client.calculateNonstreamingTimeout(r.max_tokens,e)}return this._client.post("/v1/messages?beta=true",{body:r,timeout:a??6e5,...t,headers:th([{...n?.toString()!=null?{"anthropic-beta":n?.toString()}:void 0},t?.headers]),stream:e.stream??!1})}stream(e,t){return tE.createMessage(this,e,t)}countTokens(e,t){let{betas:n,...r}=e;return this._client.post("/v1/messages/count_tokens?beta=true",{body:r,...t,headers:th([{"anthropic-beta":[...n??[],"token-counting-2024-11-01"].toString()},t?.headers])})}}tP.Batches=tv;class tO extends tc{constructor(){super(...arguments),this.models=new tm(this._client),this.messages=new tP(this._client),this.files=new tg(this._client)}}tO.Models=tm,tO.Messages=tP,tO.Files=tg;class tj extends tc{create(e,t){let{betas:n,...r}=e;return this._client.post("/v1/complete",{body:r,timeout:this._client._options.timeout??6e5,...t,headers:th([{...n?.toString()!=null?{"anthropic-beta":n?.toString()}:void 0},t?.headers]),stream:e.stream??!1})}}let tI="__json_buf";function tA(e){return"tool_use"===e.type||"server_tool_use"===e.type}class tL{constructor(){P.add(this),this.messages=[],this.receivedMessages=[],O.set(this,void 0),this.controller=new AbortController,j.set(this,void 0),I.set(this,()=>{}),A.set(this,()=>{}),L.set(this,void 0),Z.set(this,()=>{}),T.set(this,()=>{}),N.set(this,{}),z.set(this,!1),$.set(this,!1),q.set(this,!1),D.set(this,!1),B.set(this,void 0),H.set(this,void 0),F.set(this,e=>{if(et(this,$,!0,"f"),ea(e)&&(e=new el),e instanceof el)return et(this,q,!0,"f"),this._emit("abort",e);if(e instanceof ei)return this._emit("error",e);if(e instanceof Error){let t=new ei(e.message);return t.cause=e,this._emit("error",t)}return this._emit("error",new ei(String(e)))}),et(this,j,new Promise((e,t)=>{et(this,I,e,"f"),et(this,A,t,"f")}),"f"),et(this,L,new Promise((e,t)=>{et(this,Z,e,"f"),et(this,T,t,"f")}),"f"),en(this,j,"f").catch(()=>{}),en(this,L,"f").catch(()=>{})}get response(){return en(this,B,"f")}get request_id(){return en(this,H,"f")}async withResponse(){let e=await en(this,j,"f");if(!e)throw Error("Could not resolve a `Response` object");return{data:this,response:e,request_id:e.headers.get("request-id")}}static fromReadableStream(e){let t=new tL;return t._run(()=>t._fromReadableStream(e)),t}static createMessage(e,t,n){let r=new tL;for(let e of t.messages)r._addMessageParam(e);return r._run(()=>r._createMessage(e,{...t,stream:!0},{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),r}_run(e){e().then(()=>{this._emitFinal(),this._emit("end")},en(this,F,"f"))}_addMessageParam(e){this.messages.push(e)}_addMessage(e,t=!0){this.receivedMessages.push(e),t&&this._emit("message",e)}async _createMessage(e,t,n){let r=n?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),en(this,P,"m",V).call(this);let{response:a,data:s}=await e.create({...t,stream:!0},{...n,signal:this.controller.signal}).withResponse();for await(let e of(this._connected(a),s))en(this,P,"m",X).call(this,e);if(s.controller.signal?.aborted)throw new el;en(this,P,"m",J).call(this)}_connected(e){this.ended||(et(this,B,e,"f"),et(this,H,e?.headers.get("request-id"),"f"),en(this,I,"f").call(this,e),this._emit("connect"))}get ended(){return en(this,z,"f")}get errored(){return en(this,$,"f")}get aborted(){return en(this,q,"f")}abort(){this.controller.abort()}on(e,t){return(en(this,N,"f")[e]||(en(this,N,"f")[e]=[])).push({listener:t}),this}off(e,t){let n=en(this,N,"f")[e];if(!n)return this;let r=n.findIndex(e=>e.listener===t);return r>=0&&n.splice(r,1),this}once(e,t){return(en(this,N,"f")[e]||(en(this,N,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,n)=>{et(this,D,!0,"f"),"error"!==e&&this.once("error",n),this.once(e,t)})}async done(){et(this,D,!0,"f"),await en(this,L,"f")}get currentMessage(){return en(this,O,"f")}async finalMessage(){return await this.done(),en(this,P,"m",U).call(this)}async finalText(){return await this.done(),en(this,P,"m",W).call(this)}_emit(e,...t){if(en(this,z,"f"))return;"end"===e&&(et(this,z,!0,"f"),en(this,Z,"f").call(this));let n=en(this,N,"f")[e];if(n&&(en(this,N,"f")[e]=n.filter(e=>!e.once),n.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];en(this,D,"f")||n?.length||Promise.reject(e),en(this,A,"f").call(this,e),en(this,T,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];en(this,D,"f")||n?.length||Promise.reject(e),en(this,A,"f").call(this,e),en(this,T,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",en(this,P,"m",U).call(this))}async _fromReadableStream(e,t){let n=t?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort())),en(this,P,"m",V).call(this),this._connected(null);let r=eV.fromReadableStream(e,this.controller);for await(let e of r)en(this,P,"m",X).call(this,e);if(r.controller.signal?.aborted)throw new el;en(this,P,"m",J).call(this)}[(O=new WeakMap,j=new WeakMap,I=new WeakMap,A=new WeakMap,L=new WeakMap,Z=new WeakMap,T=new WeakMap,N=new WeakMap,z=new WeakMap,$=new WeakMap,q=new WeakMap,D=new WeakMap,B=new WeakMap,H=new WeakMap,F=new WeakMap,P=new WeakSet,U=function(){if(0===this.receivedMessages.length)throw new ei("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},W=function(){if(0===this.receivedMessages.length)throw new ei("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new ei("stream ended without producing a content block with type=text");return e.join(" ")},V=function(){this.ended||et(this,O,void 0,"f")},X=function(e){if(this.ended)return;let t=en(this,P,"m",G).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let n=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===n.type&&this._emit("text",e.delta.text,n.text||"");break;case"citations_delta":"text"===n.type&&this._emit("citation",e.delta.citation,n.citations??[]);break;case"input_json_delta":tA(n)&&n.input&&this._emit("inputJson",e.delta.partial_json,n.input);break;case"thinking_delta":"thinking"===n.type&&this._emit("thinking",e.delta.thinking,n.thinking);break;case"signature_delta":"thinking"===n.type&&this._emit("signature",n.signature);break;default:e.delta}break}case"message_stop":this._addMessageParam(t),this._addMessage(t,!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":et(this,O,t,"f")}},J=function(){if(this.ended)throw new ei("stream has ended, this shouldn't happen");let e=en(this,O,"f");if(!e)throw new ei("request ended without sending any chunks");return et(this,O,void 0,"f"),e},G=function(e){let t=en(this,O,"f");if("message_start"===e.type){if(t)throw new ei(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new ei(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push(e.content_block),t;case"content_block_delta":{let n=t.content.at(e.index);switch(e.delta.type){case"text_delta":n?.type==="text"&&(n.text+=e.delta.text);break;case"citations_delta":n?.type==="text"&&(n.citations??(n.citations=[]),n.citations.push(e.delta.citation));break;case"input_json_delta":if(n&&tA(n)){let t=n[tI]||"";Object.defineProperty(n,tI,{value:t+=e.delta.partial_json,enumerable:!1,writable:!0}),t&&(n.input=tS(t))}break;case"thinking_delta":n?.type==="thinking"&&(n.thinking+=e.delta.thinking);break;case"signature_delta":n?.type==="thinking"&&(n.signature=e.delta.signature);break;default:e.delta}return t}}},Symbol.asyncIterator)](){let e=[],t=[],n=!1;return this.on("streamEvent",n=>{let r=t.shift();r?r.resolve(n):e.push(n)}),this.on("end",()=>{for(let e of(n=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(n=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(n=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:n?{value:void 0,done:!0}:new Promise((e,n)=>t.push({resolve:e,reject:n})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new eV(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}class tZ extends 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++++++++++++++++ docs/my-website/docs/proxy/config_settings.md | 5 +++ litellm/constants.py | 17 ++++++++ litellm/proxy/management_endpoints/ui_sso.py | 19 ++++++--- .../proxy/management_endpoints/test_ui_sso.py | 41 +++++++++++++++++++ 5 files changed, 112 insertions(+), 6 deletions(-) diff --git a/docs/my-website/docs/proxy/admin_ui_sso.md b/docs/my-website/docs/proxy/admin_ui_sso.md index 4984cac2d0d..7b299429db7 100644 --- a/docs/my-website/docs/proxy/admin_ui_sso.md +++ b/docs/my-website/docs/proxy/admin_ui_sso.md @@ -111,6 +111,42 @@ To set up app roles: 4. Assign users to these roles in your Enterprise Application 5. When users sign in via SSO, LiteLLM will automatically assign them the corresponding role +**Advanced: Custom User Attribute Mapping** + +For certain Microsoft Entra ID configurations, you may need to override the default user attribute field names. This is useful when your organization uses custom claims or non-standard attribute names in the SSO response. + +**Step 1: Debug SSO Response** + +First, inspect the JWT fields returned by your Microsoft SSO provider using the [SSO Debug Route](#debugging-sso-jwt-fields). + +1. Add `/sso/debug/callback` as a redirect URL in your Azure App Registration +2. Navigate to `https:///sso/debug/login` +3. Complete the SSO flow to see the returned user attributes + +**Step 2: Identify Field Attribute Names** + +From the debug response, identify the field names used for email, display name, user ID, first name, and last name. + +**Step 3: Set Environment Variables** + +Override the default attribute names by setting these environment variables: + +| Environment Variable | Description | Default Value | +|---------------------|-------------|---------------| +| `MICROSOFT_USER_EMAIL_ATTRIBUTE` | Field name for user email | `userPrincipalName` | +| `MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE` | Field name for display name | `displayName` | +| `MICROSOFT_USER_ID_ATTRIBUTE` | Field name for user ID | `id` | +| `MICROSOFT_USER_FIRST_NAME_ATTRIBUTE` | Field name for first name | `givenName` | +| `MICROSOFT_USER_LAST_NAME_ATTRIBUTE` | Field name for last name | `surname` | + +**Step 4: Restart the Proxy** + +After setting the environment variables, restart the proxy: + +```bash +litellm --config /path/to/config.yaml +``` + diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md index e9f9fb37a25..6c5c45dc90c 100644 --- a/docs/my-website/docs/proxy/config_settings.md +++ b/docs/my-website/docs/proxy/config_settings.md @@ -777,6 +777,11 @@ router_settings: | MICROSOFT_SERVICE_PRINCIPAL_ID | Service Principal ID for Microsoft Enterprise Application. (This is an advanced feature if you want litellm to auto-assign members to Litellm Teams based on their Microsoft Entra ID Groups) | MICROSOFT_TENANT | Tenant ID for Microsoft Azure | MICROSOFT_TOKEN_ENDPOINT | Custom token endpoint URL for Microsoft SSO (overrides default Microsoft OAuth token endpoint) +| MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE | Field name for user display name in Microsoft SSO response. Default is `displayName` +| MICROSOFT_USER_EMAIL_ATTRIBUTE | Field name for user email in Microsoft SSO response. Default is `userPrincipalName` +| MICROSOFT_USER_FIRST_NAME_ATTRIBUTE | Field name for user first name in Microsoft SSO response. Default is `givenName` +| MICROSOFT_USER_ID_ATTRIBUTE | Field name for user ID in Microsoft SSO response. Default is `id` +| MICROSOFT_USER_LAST_NAME_ATTRIBUTE | Field name for user last name in Microsoft SSO response. Default is `surname` | MICROSOFT_USERINFO_ENDPOINT | Custom userinfo endpoint URL for Microsoft SSO (overrides default Microsoft Graph userinfo endpoint) | NO_DOCS | Flag to disable Swagger UI documentation | NO_REDOC | Flag to disable Redoc documentation diff --git a/litellm/constants.py b/litellm/constants.py index e24186d567e..4ea0be247b3 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -1285,3 +1285,20 @@ COROUTINE_CHECKER_MAX_SIZE_IN_MEMORY = int( ########################### RAG Text Splitter Constants ########################### DEFAULT_CHUNK_SIZE = int(os.getenv("DEFAULT_CHUNK_SIZE", 1000)) DEFAULT_CHUNK_OVERLAP = int(os.getenv("DEFAULT_CHUNK_OVERLAP", 200)) + +########################### Microsoft SSO Constants ########################### +MICROSOFT_USER_EMAIL_ATTRIBUTE = str( + os.getenv("MICROSOFT_USER_EMAIL_ATTRIBUTE", "userPrincipalName") +) +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_FIRST_NAME_ATTRIBUTE = str( + os.getenv("MICROSOFT_USER_FIRST_NAME_ATTRIBUTE", "givenName") +) +MICROSOFT_USER_LAST_NAME_ATTRIBUTE = str( + os.getenv("MICROSOFT_USER_LAST_NAME_ATTRIBUTE", "surname") +) diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py index 5b3ebbf1c27..3075792f9f2 100644 --- a/litellm/proxy/management_endpoints/ui_sso.py +++ b/litellm/proxy/management_endpoints/ui_sso.py @@ -23,7 +23,14 @@ import litellm from litellm._logging import verbose_proxy_logger from litellm._uuid import uuid from litellm.caching import DualCache -from litellm.constants import MAX_SPENDLOG_ROWS_TO_QUERY +from litellm.constants import ( + MAX_SPENDLOG_ROWS_TO_QUERY, + MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE, + MICROSOFT_USER_EMAIL_ATTRIBUTE, + MICROSOFT_USER_FIRST_NAME_ATTRIBUTE, + MICROSOFT_USER_ID_ATTRIBUTE, + MICROSOFT_USER_LAST_NAME_ATTRIBUTE, +) from litellm.litellm_core_utils.dot_notation_indexing import get_nested_value from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, @@ -2358,12 +2365,12 @@ class MicrosoftSSOHandler: response = response or {} verbose_proxy_logger.debug(f"Microsoft SSO Callback Response: {response}") openid_response = CustomOpenID( - email=response.get("userPrincipalName") or response.get("mail"), - display_name=response.get("displayName"), + email=response.get(MICROSOFT_USER_EMAIL_ATTRIBUTE) or response.get("mail"), + display_name=response.get(MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE), provider="microsoft", - id=response.get("id"), - first_name=response.get("givenName"), - last_name=response.get("surname"), + id=response.get(MICROSOFT_USER_ID_ATTRIBUTE), + first_name=response.get(MICROSOFT_USER_FIRST_NAME_ATTRIBUTE), + last_name=response.get(MICROSOFT_USER_LAST_NAME_ATTRIBUTE), team_ids=team_ids, user_role=user_role, ) diff --git a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py index be9d193e3f1..f0cf5459ad2 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py +++ b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py @@ -115,6 +115,47 @@ def test_microsoft_sso_handler_with_empty_response(): assert result.team_ids == [] +def test_microsoft_sso_handler_openid_from_response_with_custom_attributes(): + """ + Test that MicrosoftSSOHandler.openid_from_response uses custom attribute names + from constants when environment variables are set. + """ + # Arrange + mock_response = { + "custom_email_field": "custom@example.com", + "custom_display_name": "Custom Display Name", + "custom_id_field": "custom_user_123", + "custom_first_name": "CustomFirst", + "custom_last_name": "CustomLast", + } + expected_team_ids = ["team1"] + + # Act + with patch("litellm.constants.MICROSOFT_USER_EMAIL_ATTRIBUTE", "custom_email_field"), \ + patch("litellm.constants.MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE", "custom_display_name"), \ + patch("litellm.constants.MICROSOFT_USER_ID_ATTRIBUTE", "custom_id_field"), \ + patch("litellm.constants.MICROSOFT_USER_FIRST_NAME_ATTRIBUTE", "custom_first_name"), \ + patch("litellm.constants.MICROSOFT_USER_LAST_NAME_ATTRIBUTE", "custom_last_name"), \ + patch("litellm.proxy.management_endpoints.ui_sso.MICROSOFT_USER_EMAIL_ATTRIBUTE", "custom_email_field"), \ + patch("litellm.proxy.management_endpoints.ui_sso.MICROSOFT_USER_DISPLAY_NAME_ATTRIBUTE", "custom_display_name"), \ + patch("litellm.proxy.management_endpoints.ui_sso.MICROSOFT_USER_ID_ATTRIBUTE", "custom_id_field"), \ + patch("litellm.proxy.management_endpoints.ui_sso.MICROSOFT_USER_FIRST_NAME_ATTRIBUTE", "custom_first_name"), \ + patch("litellm.proxy.management_endpoints.ui_sso.MICROSOFT_USER_LAST_NAME_ATTRIBUTE", "custom_last_name"): + result = MicrosoftSSOHandler.openid_from_response( + response=mock_response, team_ids=expected_team_ids, user_role=None + ) + + # Assert + assert isinstance(result, CustomOpenID) + assert result.email == "custom@example.com" + assert result.display_name == "Custom Display Name" + assert result.provider == "microsoft" + assert result.id == "custom_user_123" + assert result.first_name == "CustomFirst" + assert result.last_name == "CustomLast" + assert result.team_ids == expected_team_ids + + def test_get_microsoft_callback_response(): # Arrange mock_request = MagicMock(spec=Request) From 5a51b746587fc4b426202d8667cadc377895886c Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 09:15:05 +0530 Subject: [PATCH 32/46] Add pricing of azure_ai/claude-opus-4-5 --- ...model_prices_and_context_window_backup.json | 18 ++++++++++++++++++ model_prices_and_context_window.json | 18 ++++++++++++++++++ 2 files changed, 36 insertions(+) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index ed218d50af7..f818a2c82e2 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1329,6 +1329,24 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure_ai/claude-opus-4-5": { + "input_cost_per_token": 5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 2.5e-05, + "supports_assistant_prefill": true, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure_ai/claude-opus-4-1": { "input_cost_per_token": 1.5e-05, "litellm_provider": "azure_ai", diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index ed218d50af7..f818a2c82e2 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1329,6 +1329,24 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure_ai/claude-opus-4-5": { + "input_cost_per_token": 5e-06, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 2.5e-05, + "supports_assistant_prefill": true, + "supports_computer_use": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "azure_ai/claude-opus-4-1": { "input_cost_per_token": 1.5e-05, "litellm_provider": "azure_ai", From 7c61933bc52dabf9e0e7be293551d856b71b894b Mon Sep 17 00:00:00 2001 From: Dima-Mediator Date: Mon, 12 Jan 2026 22:54:24 -0500 Subject: [PATCH 33/46] Fix image tokens spend logging for /images/generations --- litellm/responses/utils.py | 4 +- .../test_standard_logging_payload.py | 47 ++++++++++ .../responses/test_responses_utils.py | 87 +++++++++++++++++++ 3 files changed, 137 insertions(+), 1 deletion(-) diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index 49b8e123fe2..469eeb3da06 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -472,7 +472,9 @@ class ResponseAPILoggingUtils: output_tokens_details = getattr(response_api_usage, "output_tokens_details", None) if output_tokens_details: completion_tokens_details = CompletionTokensDetailsWrapper( - reasoning_tokens=getattr(output_tokens_details, "reasoning_tokens", None) + reasoning_tokens=getattr(output_tokens_details, "reasoning_tokens", None), + image_tokens=getattr(output_tokens_details, "image_tokens", None), + text_tokens=getattr(output_tokens_details, "text_tokens", None), ) chat_usage = Usage( diff --git a/tests/logging_callback_tests/test_standard_logging_payload.py b/tests/logging_callback_tests/test_standard_logging_payload.py index 1c01ab91938..4ead642c462 100644 --- a/tests/logging_callback_tests/test_standard_logging_payload.py +++ b/tests/logging_callback_tests/test_standard_logging_payload.py @@ -80,6 +80,53 @@ def test_get_usage(response_obj, expected_values): assert usage.total_tokens == expected_values[2] +def test_get_usage_from_image_generation_response(): + """ + Test that image generation usage (with input_tokens/output_tokens format) + is correctly transformed to standard usage format with image_tokens preserved. + + Note: get_usage_from_response_obj() is used by multiple endpoints including + /images/generations and Response API (/responses), both of which use the + input_tokens/output_tokens format instead of prompt_tokens/completion_tokens. + + This tests the fix for the bug where image_tokens were being lost during + spend log creation for /images/generations endpoint. + """ + # Simulating image generation response usage from OpenAI + response_obj = { + "usage": { + "input_tokens": 13, + "output_tokens": 372, + "total_tokens": 385, + "input_tokens_details": { + "image_tokens": 0, + "text_tokens": 13, + }, + "output_tokens_details": { + "image_tokens": 272, + "text_tokens": 100, + }, + } + } + + usage = StandardLoggingPayloadSetup.get_usage_from_response_obj(response_obj) + + # Check basic token counts are mapped correctly + assert usage.prompt_tokens == 13 + assert usage.completion_tokens == 372 + assert usage.total_tokens == 385 + + # Check that prompt_tokens_details contains image_tokens and text_tokens + assert usage.prompt_tokens_details is not None + assert usage.prompt_tokens_details.image_tokens == 0 + assert usage.prompt_tokens_details.text_tokens == 13 + + # Check that completion_tokens_details contains image_tokens and text_tokens + assert usage.completion_tokens_details is not None + assert usage.completion_tokens_details.image_tokens == 272 + assert usage.completion_tokens_details.text_tokens == 100 + + def test_get_additional_headers(): additional_headers = { "x-ratelimit-limit-requests": "2000", diff --git a/tests/test_litellm/responses/test_responses_utils.py b/tests/test_litellm/responses/test_responses_utils.py index 09628cd4a76..3eb9c63e1be 100644 --- a/tests/test_litellm/responses/test_responses_utils.py +++ b/tests/test_litellm/responses/test_responses_utils.py @@ -222,3 +222,90 @@ class TestResponseAPILoggingUtils: assert result.prompt_tokens == 15 assert result.completion_tokens == 25 assert result.total_tokens == 40 # 15 + 25 + + def test_transform_response_api_usage_with_image_tokens(self): + """Test transformation handles image_tokens from image generation responses. + + Note: _transform_response_api_usage_to_chat_usage() is used by multiple + endpoints including /images/generations and Response API (/responses), + both of which use the input_tokens/output_tokens format. + + This tests the fix for image generation responses that include image_tokens + in both input_tokens_details and output_tokens_details. + + Example from gpt-image-1.5: + - input: text prompt with 13 tokens + - output: generated image with 272 image tokens + 100 text tokens + """ + # Setup - simulating image generation usage from OpenAI + usage = { + "input_tokens": 13, + "output_tokens": 372, + "total_tokens": 385, + "input_tokens_details": { + "image_tokens": 0, + "text_tokens": 13, + }, + "output_tokens_details": { + "image_tokens": 272, + "text_tokens": 100, + }, + } + + # Execute + result = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage( + usage + ) + + # Assert - verify basic token counts + assert isinstance(result, Usage) + assert result.prompt_tokens == 13 + assert result.completion_tokens == 372 + assert result.total_tokens == 385 + + # Assert - verify prompt_tokens_details includes image_tokens and text_tokens + assert result.prompt_tokens_details is not None + assert result.prompt_tokens_details.image_tokens == 0 + assert result.prompt_tokens_details.text_tokens == 13 + + # Assert - verify completion_tokens_details includes image_tokens and text_tokens + assert result.completion_tokens_details is not None + assert result.completion_tokens_details.image_tokens == 272 + assert result.completion_tokens_details.text_tokens == 100 + + def test_transform_response_api_usage_mixed_details(self): + """Test transformation handles mixed token details (cached + image + audio).""" + # Setup - hypothetical usage with mixed token types + usage = { + "input_tokens": 100, + "output_tokens": 200, + "total_tokens": 300, + "input_tokens_details": { + "cached_tokens": 50, + "audio_tokens": 10, + "image_tokens": 20, + "text_tokens": 20, + }, + "output_tokens_details": { + "reasoning_tokens": 30, + "image_tokens": 100, + "text_tokens": 70, + }, + } + + # Execute + result = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage( + usage + ) + + # Assert - all token detail types should be preserved + assert result.prompt_tokens_details is not None + assert result.prompt_tokens_details.cached_tokens == 50 + assert result.prompt_tokens_details.audio_tokens == 10 + assert result.prompt_tokens_details.image_tokens == 20 + assert result.prompt_tokens_details.text_tokens == 20 + + assert result.completion_tokens_details is not None + assert result.completion_tokens_details.reasoning_tokens == 30 + assert result.completion_tokens_details.image_tokens == 100 + assert result.completion_tokens_details.text_tokens == 70 From 005541075b2ae8c3d0e6c62690680ed7c5a04db1 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 09:45:14 +0530 Subject: [PATCH 34/46] Fix: Header forwarding in bedrock passthrough --- .../llm_passthrough_endpoints.py | 1 + .../test_llm_pass_through_endpoints.py | 292 +++++++++++++++++- 2 files changed, 291 insertions(+), 2 deletions(-) diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index d9798dae690..5299b30b52f 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -1037,6 +1037,7 @@ async def bedrock_proxy_route( target=str(prepped.url), custom_headers=prepped.headers, # type: ignore is_streaming_request=is_streaming_request, + _forward_headers=True ) # dynamically construct pass-through endpoint based on incoming path received_value = await endpoint_func( request, diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py index 0bb9924af82..368e2103590 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py @@ -1188,11 +1188,11 @@ class TestBedrockLLMProxyRoute: This test verifies the fix for the bug where passthrough endpoints were using environment variables instead of model-specific credentials from config.yaml. """ + from litellm import Router + from litellm.litellm_core_utils.get_litellm_params import get_litellm_params from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( handle_bedrock_passthrough_router_model, ) - from litellm import Router - from litellm.litellm_core_utils.get_litellm_params import get_litellm_params # Model-specific credentials (different from env vars) model_access_key = "MODEL_SPECIFIC_ACCESS_KEY" @@ -1453,6 +1453,294 @@ class TestVLLMProxyRoute: mock_factory_route.assert_awaited_once() +class TestForwardHeaders: + """ + Test cases for _forward_headers parameter in passthrough endpoints + """ + + @pytest.mark.asyncio + async def test_pass_through_request_with_forward_headers_true(self): + """ + Test that when forward_headers=True, user headers from the main request + are forwarded to the target endpoint (except content-length and host) + """ + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + pass_through_request, + ) + + # Create a mock request with custom headers + mock_request = MagicMock(spec=Request) + mock_request.method = "POST" + mock_request.url = MagicMock() + mock_request.url.path = "/test/endpoint" + + # User headers that should be forwarded + user_headers = { + "x-custom-header": "custom-value", + "x-api-key": "user-api-key", + "authorization": "Bearer user-token", + "user-agent": "test-client/1.0", + "content-type": "application/json", + # These should NOT be forwarded + "content-length": "123", + "host": "original-host.com", + } + mock_request.headers = user_headers + mock_request.query_params = {} + + # Mock the request body + mock_request_body = {"test": "data"} + + mock_user_api_key_dict = MagicMock() + + # Custom headers that should be merged with user headers + custom_headers = { + "x-litellm-header": "litellm-value", + } + + target_url = "https://api.example.com/v1/test" + + # Mock the httpx client and response + mock_httpx_response = MagicMock() + mock_httpx_response.status_code = 200 + mock_httpx_response.headers = {"content-type": "application/json"} + mock_httpx_response.aiter_bytes = AsyncMock(return_value=[b'{"result": "success"}']) + mock_httpx_response.aread = AsyncMock(return_value=b'{"result": "success"}') + + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints._read_request_body", + return_value=mock_request_body, + ), patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_async_httpx_client" + ) as mock_get_client, patch( + "litellm.proxy.proxy_server.proxy_logging_obj" + ) as mock_logging_obj: + # Setup mock httpx client + mock_client = MagicMock() + mock_client.request = AsyncMock(return_value=mock_httpx_response) + mock_client_obj = MagicMock() + mock_client_obj.client = mock_client + mock_get_client.return_value = mock_client_obj + + # Setup mock logging object + mock_logging_obj.pre_call_hook = AsyncMock(return_value=mock_request_body) + mock_logging_obj.post_call_success_hook = AsyncMock() + mock_logging_obj.post_call_failure_hook = AsyncMock() + + # Call pass_through_request with forward_headers=True + result = await pass_through_request( + request=mock_request, + target=target_url, + custom_headers=custom_headers, + user_api_key_dict=mock_user_api_key_dict, + forward_headers=True, # Enable header forwarding + stream=False, + ) + + # Verify the httpx client was called + assert mock_client.request.called + + # Get the headers that were sent to the target + call_args = mock_client.request.call_args + sent_headers = call_args[1]["headers"] + + # Verify user headers were forwarded (except content-length and host) + assert sent_headers["x-custom-header"] == "custom-value" + assert sent_headers["x-api-key"] == "user-api-key" + assert sent_headers["authorization"] == "Bearer user-token" + assert sent_headers["user-agent"] == "test-client/1.0" + assert sent_headers["content-type"] == "application/json" + + # Verify custom headers were included + assert sent_headers["x-litellm-header"] == "litellm-value" + + # Verify content-length and host were NOT forwarded + assert "content-length" not in sent_headers + assert "host" not in sent_headers + + @pytest.mark.asyncio + async def test_pass_through_request_with_forward_headers_false(self): + """ + Test that when forward_headers=False (default), user headers are NOT forwarded, + only custom_headers are sent + """ + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + pass_through_request, + ) + + # Create a mock request with custom headers + mock_request = MagicMock(spec=Request) + mock_request.method = "POST" + mock_request.url = MagicMock() + mock_request.url.path = "/test/endpoint" + + # User headers that should NOT be forwarded + user_headers = { + "x-custom-header": "custom-value", + "x-api-key": "user-api-key", + "authorization": "Bearer user-token", + } + mock_request.headers = user_headers + mock_request.query_params = {} + + mock_request_body = {"test": "data"} + mock_user_api_key_dict = MagicMock() + + # Only these custom headers should be sent + custom_headers = { + "x-litellm-header": "litellm-value", + "authorization": "Bearer litellm-token", + } + + target_url = "https://api.example.com/v1/test" + + # Mock the httpx client and response + mock_httpx_response = MagicMock() + mock_httpx_response.status_code = 200 + mock_httpx_response.headers = {"content-type": "application/json"} + mock_httpx_response.aiter_bytes = AsyncMock(return_value=[b'{"result": "success"}']) + mock_httpx_response.aread = AsyncMock(return_value=b'{"result": "success"}') + + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints._read_request_body", + return_value=mock_request_body, + ), patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_async_httpx_client" + ) as mock_get_client, patch( + "litellm.proxy.proxy_server.proxy_logging_obj" + ) as mock_logging_obj: + # Setup mock httpx client + mock_client = MagicMock() + mock_client.request = AsyncMock(return_value=mock_httpx_response) + mock_client_obj = MagicMock() + mock_client_obj.client = mock_client + mock_get_client.return_value = mock_client_obj + + # Setup mock logging object + mock_logging_obj.pre_call_hook = AsyncMock(return_value=mock_request_body) + mock_logging_obj.post_call_success_hook = AsyncMock() + mock_logging_obj.post_call_failure_hook = AsyncMock() + + # Call pass_through_request with forward_headers=False (default) + result = await pass_through_request( + request=mock_request, + target=target_url, + custom_headers=custom_headers, + user_api_key_dict=mock_user_api_key_dict, + forward_headers=False, # Explicitly set to False + stream=False, + ) + + # Verify the httpx client was called + assert mock_client.request.called + + # Get the headers that were sent to the target + call_args = mock_client.request.call_args + sent_headers = call_args[1]["headers"] + + # Verify only custom headers were sent + assert sent_headers["x-litellm-header"] == "litellm-value" + assert sent_headers["authorization"] == "Bearer litellm-token" + + # Verify user headers were NOT forwarded + assert "x-custom-header" not in sent_headers + assert "x-api-key" not in sent_headers + # Authorization is present but should be from custom_headers, not user headers + assert sent_headers["authorization"] == "Bearer litellm-token" + + @pytest.mark.asyncio + async def test_llm_passthrough_factory_with_forward_headers(self): + """ + Test that _forward_headers works correctly in llm_passthrough_factory_proxy_route + which is used in the code snippet provided by the user + """ + from litellm.types.utils import LlmProviders + + mock_request = MagicMock(spec=Request) + mock_request.method = "POST" + mock_request.url = MagicMock() + mock_request.url.path = "/openai/chat/completions" + + # User headers to be forwarded + user_headers = { + "x-custom-tracking-id": "tracking-123", + "x-request-id": "req-456", + "user-agent": "my-app/2.0", + } + mock_request.headers = user_headers + mock_request.json = AsyncMock(return_value={"stream": False}) + + mock_fastapi_response = MagicMock(spec=Response) + mock_user_api_key_dict = MagicMock() + + # Mock the httpx response + mock_httpx_response = MagicMock() + mock_httpx_response.status_code = 200 + mock_httpx_response.headers = {"content-type": "application/json"} + mock_httpx_response.aiter_bytes = AsyncMock(return_value=[b'{"result": "success"}']) + mock_httpx_response.aread = AsyncMock(return_value=b'{"result": "success"}') + + with patch( + "litellm.utils.ProviderConfigManager.get_provider_model_info" + ) as mock_get_provider, patch( + "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.passthrough_endpoint_router.get_credentials" + ) as mock_get_creds, patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints._read_request_body", + return_value={"messages": [{"role": "user", "content": "test"}]}, + ), patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.get_async_httpx_client" + ) as mock_get_client, patch( + "litellm.proxy.proxy_server.proxy_logging_obj" + ) as mock_logging_obj: + # Setup provider config + mock_provider_config = MagicMock() + mock_provider_config.get_api_base.return_value = "https://api.openai.com/v1" + mock_provider_config.validate_environment.return_value = { + "authorization": "Bearer sk-test" + } + mock_get_provider.return_value = mock_provider_config + mock_get_creds.return_value = "sk-test" + + # Setup mock httpx client + mock_client = MagicMock() + mock_client.request = AsyncMock(return_value=mock_httpx_response) + mock_client_obj = MagicMock() + mock_client_obj.client = mock_client + mock_get_client.return_value = mock_client_obj + + # Setup mock logging object + mock_logging_obj.pre_call_hook = AsyncMock( + return_value={"messages": [{"role": "user", "content": "test"}]} + ) + mock_logging_obj.post_call_success_hook = AsyncMock() + + # This is the key part - when create_pass_through_route is called with _forward_headers=True + # it should forward the user headers + with patch( + "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.create_pass_through_route" + ) as mock_create_route: + mock_endpoint_func = AsyncMock(return_value="success") + mock_create_route.return_value = mock_endpoint_func + + result = await llm_passthrough_factory_proxy_route( + custom_llm_provider=LlmProviders.OPENAI, + endpoint="/chat/completions", + request=mock_request, + fastapi_response=mock_fastapi_response, + user_api_key_dict=mock_user_api_key_dict, + ) + + # Verify create_pass_through_route was called + mock_create_route.assert_called_once() + + # Get the call arguments to verify _forward_headers parameter + call_kwargs = mock_create_route.call_args[1] + + # Note: The current implementation doesn't explicitly pass _forward_headers + # This test documents the current behavior. If _forward_headers should be + # configurable in llm_passthrough_factory_proxy_route, it would need to be added + + class TestMilvusProxyRoute: """ Test cases for Milvus passthrough endpoint From da902c5c55917ed91de2707e09e98d88b0a81f7b Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Mon, 12 Jan 2026 21:04:16 -0800 Subject: [PATCH 35/46] Migrate User and Team filters to use reusable components --- .../src/components/OldTeams.tsx | 95 ++++----------- .../src/components/view_users/table.tsx | 113 +++++------------- 2 files changed, 50 insertions(+), 158 deletions(-) diff --git a/ui/litellm-dashboard/src/components/OldTeams.tsx b/ui/litellm-dashboard/src/components/OldTeams.tsx index 10a38f0285c..5679788d30d 100644 --- a/ui/litellm-dashboard/src/components/OldTeams.tsx +++ b/ui/litellm-dashboard/src/components/OldTeams.tsx @@ -5,6 +5,10 @@ import TeamSSOSettings from "@/components/TeamSSOSettings"; import { isProxyAdminRole } from "@/utils/roles"; import { InfoCircleOutlined } from "@ant-design/icons"; import { ChevronDownIcon, ChevronRightIcon, RefreshIcon } from "@heroicons/react/outline"; +import { FilterInput } from "@/components/common_components/Filters/FilterInput"; +import { FiltersButton } from "@/components/common_components/Filters/FiltersButton"; +import { ResetFiltersButton } from "@/components/common_components/Filters/ResetFiltersButton"; +import { Search, User } from "lucide-react"; import { Accordion, AccordionBody, @@ -681,91 +685,34 @@ const Teams: React.FC = ({ {/* Search and Filter Controls */}
{/* Team Alias Search */} -
- handleFilterChange("team_alias", e.target.value)} - /> - - - -
+ handleFilterChange("team_alias", value)} + icon={Search} + /> {/* Filter Button */} - + active={showFilters} + hasActiveFilters={!!(filters.team_id || filters.team_alias || filters.organization_id)} + /> {/* Reset Filters Button */} - +
{/* Additional Filters */} {showFilters && (
{/* Team ID Search */} -
- handleFilterChange("team_id", e.target.value)} - /> - - - -
+ handleFilterChange("team_id", value)} + icon={User} + /> {/* Organization Dropdown */}
diff --git a/ui/litellm-dashboard/src/components/view_users/table.tsx b/ui/litellm-dashboard/src/components/view_users/table.tsx index 4f8dfa58091..9ae31014882 100644 --- a/ui/litellm-dashboard/src/components/view_users/table.tsx +++ b/ui/litellm-dashboard/src/components/view_users/table.tsx @@ -6,6 +6,10 @@ import { Skeleton } from "antd"; import { UserInfo } from "./types"; import UserInfoView from "./user_info_view"; import { columns as createColumns } from "./columns"; +import { FilterInput } from "@/components/common_components/Filters/FilterInput"; +import { FiltersButton } from "@/components/common_components/Filters/FiltersButton"; +import { ResetFiltersButton } from "@/components/common_components/Filters/ResetFiltersButton"; +import { Search, User, CircleUserRound } from "lucide-react"; interface FilterState { email: string; @@ -215,93 +219,45 @@ export function UserDataTable({ {/* Search and Filter Controls */}
{/* Email Search */} -
- updateFilters({ email: e.target.value })} - /> - - - -
+ updateFilters({ email: value })} + icon={Search} + /> {/* Filter Button */} - + active={showFilters} + hasActiveFilters={!!(filters.user_id || filters.user_role || filters.team)} + /> {/* Reset Filters Button */} - + />
{/* Additional Filters */} {showFilters && (
{/* User ID Search */} -
- updateFilters({ user_id: e.target.value })} - /> - - - -
+ updateFilters({ user_id: value })} + icon={User} + /> + + updateFilters({ sso_user_id: value })} + icon={CircleUserRound} + /> {/* Role Dropdown */}
@@ -333,17 +289,6 @@ export function UserDataTable({ ))}
- - {/* SSO ID Search */} -
- updateFilters({ sso_user_id: e.target.value })} - /> -
)} From dfece51f8c4b51af404bb6d5134db70658d14f2b Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 11:44:48 +0530 Subject: [PATCH 36/46] Fix: Model matching priority in configuration --- .../pass_through_endpoints.py | 16 ++-- litellm/proxy/route_llm_request.py | 12 +-- .../test_router_pattern_matching.py | 76 +++++++++++++++++++ 3 files changed, 91 insertions(+), 13 deletions(-) diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index b2eda5a8d38..75d8253a904 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -226,12 +226,6 @@ async def chat_completion_pass_through_endpoint( # noqa: PLR0915 and data["model"] in llm_router.model_group_alias ): # model set in model_group_alias llm_response = asyncio.create_task(llm_router.aadapter_completion(**data)) - elif ( - llm_router is not None and data["model"] in llm_router.deployment_names - ): # model in router deployments, calling a specific deployment on the router - llm_response = asyncio.create_task( - llm_router.aadapter_completion(**data, specific_deployment=True) - ) elif llm_router is not None and llm_router.has_model_id( data["model"] ): # model in router model list @@ -239,9 +233,15 @@ async def chat_completion_pass_through_endpoint( # noqa: PLR0915 elif ( llm_router is not None and data["model"] not in router_model_names - and llm_router.default_deployment is not None - ): # model in router deployments, calling a specific deployment on the router + and (llm_router.default_deployment is not None or len(llm_router.pattern_router.patterns) > 0) + ): # check for wildcard routes or default deployment before checking deployment_names llm_response = asyncio.create_task(llm_router.aadapter_completion(**data)) + elif ( + llm_router is not None and data["model"] in llm_router.deployment_names + ): # model in router deployments, calling a specific deployment on the router (lowest priority) + llm_response = asyncio.create_task( + llm_router.aadapter_completion(**data, specific_deployment=True) + ) elif user_model is not None: # `litellm --model ` llm_response = asyncio.create_task(litellm.aadapter_completion(**data)) else: diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index 4b3a65737d4..0e061a839d9 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -260,12 +260,9 @@ async def route_request( ): return getattr(llm_router, f"{route_type}")(**data) - elif data["model"] in llm_router.deployment_names: - return getattr(llm_router, f"{route_type}")( - **data, specific_deployment=True - ) - elif data["model"] not in router_model_names: + # Check wildcards before checking deployment_names + # Priority: 1. Exact model_name match, 2. Wildcard match, 3. deployment_names match if llm_router.router_general_settings.pass_through_all_models: return getattr(litellm, f"{route_type}")(**data) elif ( @@ -273,6 +270,11 @@ async def route_request( or len(llm_router.pattern_router.patterns) > 0 ): return getattr(llm_router, f"{route_type}")(**data) + elif data["model"] in llm_router.deployment_names: + # Only match deployment_names if no wildcard matched + return getattr(llm_router, f"{route_type}")( + **data, specific_deployment=True + ) elif route_type in [ "amoderation", "aget_responses", diff --git a/tests/local_testing/test_router_pattern_matching.py b/tests/local_testing/test_router_pattern_matching.py index 5695034c7a5..7f38d14c480 100644 --- a/tests/local_testing/test_router_pattern_matching.py +++ b/tests/local_testing/test_router_pattern_matching.py @@ -314,3 +314,79 @@ def test_calculate_pattern_specificity(): assert PatternUtils.calculate_pattern_specificity("llmengine/*") == (11, 1) assert PatternUtils.calculate_pattern_specificity("*") == (1, 1) + + +def test_wildcard_priority_over_deployment_names(): + """ + Test that wildcard routes take priority over deployment_names (litellm_params.model) matching. + + Scenario: + - deployment 1: model_name="zapier-multi-provider-text-embedding-3-small", model="openai/text-embedding-3-small" + - deployment 2: model_name="*", model="openai/*" + - deployment 3: model_name="openai/*", model="openai/*" + + When calling "openai/text-embedding-3-small", it should match deployment 3 (wildcard), + NOT deployment 1 (even though deployment 1's litellm_params.model matches). + + Priority order should be: + 1. Exact model_name match + 2. Wildcard model_name match + 3. deployment_names (litellm_params.model) match + """ + router = Router( + model_list=[ + { + "model_name": "zapier-multi-provider-text-embedding-3-small", + "litellm_params": { + "model": "openai/text-embedding-3-small", + "api_base": "http://localhost:8080/openai", + "api_key": "test-key-1" + }, + "model_info": { + "id": "zapier-multi-provider-text-embedding-3-small-openai" + } + }, + { + "model_name": "*", + "litellm_params": { + "model": "openai/*", + "api_base": "http://localhost:8081/openai", + "api_key": "test-key-2" + } + }, + { + "model_name": "openai/*", + "litellm_params": { + "model": "openai/*", + "api_base": "http://localhost:8082/openai", + "api_key": "test-key-3" + } + } + ] + ) + + # Test 1: Request "openai/text-embedding-3-small" should match wildcard "openai/*", not deployment_names + deployments = router.get_model_list(model_name="openai/text-embedding-3-small") + + assert deployments is not None, "No deployments found" + assert len(deployments) == 1, f"Expected 1 deployment, got {len(deployments)}" + + # Should match the "openai/*" wildcard deployment (api_base ending in 8082) + assert deployments[0]['litellm_params']['api_base'] == "http://localhost:8082/openai", \ + f"Expected wildcard deployment (8082), got {deployments[0]['litellm_params']['api_base']}" + + # Test 2: Request exact model_name should still work + deployments = router.get_model_list(model_name="zapier-multi-provider-text-embedding-3-small") + + assert deployments is not None, "No deployments found" + assert len(deployments) == 1, f"Expected 1 deployment, got {len(deployments)}" + assert deployments[0]['litellm_params']['api_base'] == "http://localhost:8080/openai", \ + f"Expected exact match deployment (8080), got {deployments[0]['litellm_params']['api_base']}" + + # Test 3: Request with "*" wildcard should match the "*" deployment + deployments = router.get_model_list(model_name="some-random-model") + + assert deployments is not None, "No deployments found" + assert len(deployments) == 1, f"Expected 1 deployment, got {len(deployments)}" + assert deployments[0]['litellm_params']['api_base'] == "http://localhost:8081/openai", \ + f"Expected '*' wildcard deployment (8081), got {deployments[0]['litellm_params']['api_base']}" From 2c8ac2c3f1b36da5ae5303296888a81fc0f6f86d Mon Sep 17 00:00:00 2001 From: Yuta Saito Date: Tue, 13 Jan 2026 15:51:37 +0900 Subject: [PATCH 37/46] test: temporarily disable flaky responses_id_security tests --- tests/test_litellm/test_responses_id_security.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/test_litellm/test_responses_id_security.py b/tests/test_litellm/test_responses_id_security.py index 2addf504f7c..56822882bfa 100644 --- a/tests/test_litellm/test_responses_id_security.py +++ b/tests/test_litellm/test_responses_id_security.py @@ -115,6 +115,7 @@ class TestDecryptResponseId: class TestEncryptResponseId: """Test _encrypt_response_id function""" + @pytest.mark.skip(reason="Flaky on CI; disabling temporarily until responses_id_security is fixed") def test_encrypt_response_id_success( self, responses_id_security, mock_user_api_key_dict ): @@ -139,6 +140,7 @@ class TestEncryptResponseId: assert result.id.startswith("resp_") mock_encrypt.assert_called_once() + @pytest.mark.skip(reason="Flaky on CI; disabling temporarily until responses_id_security is fixed") def test_encrypt_response_id_maintains_prefix( self, responses_id_security, mock_user_api_key_dict ): From 762a3ef090df2fcce7130a6454403c04598d1f80 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 16:39:57 +0530 Subject: [PATCH 38/46] Add support for 0 cost models --- litellm/proxy/auth/auth_checks.py | 179 ++++-- litellm/proxy/auth/user_api_key_auth.py | 100 ++- .../test_zero_cost_model_budget_bypass.py | 590 ++++++++++++++++++ 3 files changed, 782 insertions(+), 87 deletions(-) create mode 100644 tests/proxy_unit_tests/test_zero_cost_model_budget_bypass.py diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index a741869e5fc..1879b306253 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -74,6 +74,75 @@ db_cache_expiry = DEFAULT_IN_MEMORY_TTL # refresh every 5s all_routes = LiteLLMRoutes.openai_routes.value + LiteLLMRoutes.management_routes.value +def _is_model_cost_zero( + model: Optional[Union[str, List[str]]], llm_router: Optional[Router] +) -> bool: + """ + Check if a model has zero cost (no configured pricing). + + Uses the router's get_model_group_info method to get pricing information. + + Args: + model: The model name or list of model names + llm_router: The LiteLLM router instance + + Returns: + bool: True if all costs for the model are zero, False otherwise + """ + if model is None or llm_router is None: + return False + + # Handle list of models + model_list = [model] if isinstance(model, str) else model + + for model_name in model_list: + try: + # Use router's get_model_group_info method directly for better reliability + model_group_info = llm_router.get_model_group_info(model_group=model_name) + + if model_group_info is None: + # Model not found or no pricing info available + # Conservative approach: assume it has cost + verbose_proxy_logger.debug( + f"No model group info found for {model_name}, assuming it has cost" + ) + return False + + # Check costs for this model + # Only allow bypass if BOTH costs are explicitly set to 0 (not None) + input_cost = model_group_info.input_cost_per_token + output_cost = model_group_info.output_cost_per_token + + # If costs are not explicitly configured (None), assume it has cost + if input_cost is None or output_cost is None: + verbose_proxy_logger.debug( + f"Model {model_name} has undefined cost (input: {input_cost}, output: {output_cost}), assuming it has cost" + ) + return False + + # If either cost is non-zero, return False + if input_cost > 0 or output_cost > 0: + verbose_proxy_logger.debug( + f"Model {model_name} has non-zero cost (input: {input_cost}, output: {output_cost})" + ) + return False + + # This model has zero cost explicitly configured + verbose_proxy_logger.debug( + f"Model {model_name} has zero cost explicitly configured (input: {input_cost}, output: {output_cost})" + ) + + except Exception as e: + # If we can't determine the cost, assume it has cost (conservative approach) + verbose_proxy_logger.debug( + f"Error checking cost for model {model_name}: {str(e)}, assuming it has cost" + ) + return False + + # All models checked have zero cost + return True + + async def common_checks( request_body: dict, team_object: Optional[LiteLLM_TeamTable], @@ -86,6 +155,7 @@ async def common_checks( proxy_logging_obj: ProxyLogging, valid_token: Optional[UserAPIKeyAuth], request: Request, + skip_budget_checks: bool = False, ) -> bool: """ Common checks across jwt + key-based auth. @@ -137,64 +207,66 @@ async def common_checks( user_object=user_object, ) - # 3. If team is in budget - await _team_max_budget_check( - team_object=team_object, - proxy_logging_obj=proxy_logging_obj, - valid_token=valid_token, - ) + # If this is a free model, skip all budget checks + if not skip_budget_checks: + # 3. If team is in budget + await _team_max_budget_check( + team_object=team_object, + proxy_logging_obj=proxy_logging_obj, + valid_token=valid_token, + ) - # 3.1. If organization is in budget - await _organization_max_budget_check( - valid_token=valid_token, - team_object=team_object, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) + # 3.1. If organization is in budget + await _organization_max_budget_check( + valid_token=valid_token, + team_object=team_object, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) - await _tag_max_budget_check( - request_body=request_body, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - valid_token=valid_token, - ) + await _tag_max_budget_check( + request_body=request_body, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + valid_token=valid_token, + ) - # 4. If user is in budget - ## 4.1 check personal budget, if personal key - if ( - (team_object is None or team_object.team_id is None) - and user_object is not None - and user_object.max_budget is not None - ): - user_budget = user_object.max_budget - if user_budget < user_object.spend: - raise litellm.BudgetExceededError( - current_cost=user_object.spend, - max_budget=user_budget, - message=f"ExceededBudget: User={user_object.user_id} over budget. Spend={user_object.spend}, Budget={user_budget}", - ) + # 4. If user is in budget + ## 4.1 check personal budget, if personal key + if ( + (team_object is None or team_object.team_id is None) + and user_object is not None + and user_object.max_budget is not None + ): + user_budget = user_object.max_budget + if user_budget < user_object.spend: + raise litellm.BudgetExceededError( + current_cost=user_object.spend, + max_budget=user_budget, + message=f"ExceededBudget: User={user_object.user_id} over budget. Spend={user_object.spend}, Budget={user_budget}", + ) - ## 4.2 check team member budget, if team key - await _check_team_member_budget( - team_object=team_object, - user_object=user_object, - valid_token=valid_token, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) + ## 4.2 check team member budget, if team key + await _check_team_member_budget( + team_object=team_object, + user_object=user_object, + valid_token=valid_token, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) - # 5. If end_user ('user' passed to /chat/completions, /embeddings endpoint) is in budget - if end_user_object is not None and end_user_object.litellm_budget_table is not None: - end_user_budget = end_user_object.litellm_budget_table.max_budget - if end_user_budget is not None and end_user_object.spend > end_user_budget: - raise litellm.BudgetExceededError( - current_cost=end_user_object.spend, - max_budget=end_user_budget, - message=f"ExceededBudget: End User={end_user_object.user_id} over budget. Spend={end_user_object.spend}, Budget={end_user_budget}", - ) + # 5. If end_user ('user' passed to /chat/completions, /embeddings endpoint) is in budget + if end_user_object is not None and end_user_object.litellm_budget_table is not None: + end_user_budget = end_user_object.litellm_budget_table.max_budget + if end_user_budget is not None and end_user_object.spend > end_user_budget: + raise litellm.BudgetExceededError( + current_cost=end_user_object.spend, + max_budget=end_user_budget, + message=f"ExceededBudget: End User={end_user_object.user_id} over budget. Spend={end_user_object.spend}, Budget={end_user_budget}", + ) # 6. [OPTIONAL] If 'enforce_user_param' enabled - did developer pass in 'user' param for openai endpoints if ( @@ -237,6 +309,7 @@ async def common_checks( # 7. [OPTIONAL] If 'litellm.max_budget' is set (>0), is proxy under budget if ( litellm.max_budget > 0 + and not skip_budget_checks and global_proxy_spend is not None # only run global budget checks for OpenAI routes # Reason - the Admin UI should continue working if the proxy crosses it's global budget diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 401aa7fd443..efac74219d5 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -586,6 +586,21 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 if team_object is not None else None, ) + + # Check if model has zero cost - if so, skip all budget checks + model = get_model_from_request(request_data, route) + skip_budget_checks = False + if model is not None and llm_router is not None: + from litellm.proxy.auth.auth_checks import _is_model_cost_zero + + skip_budget_checks = _is_model_cost_zero( + model=model, llm_router=llm_router + ) + if skip_budget_checks: + verbose_proxy_logger.info( + f"Skipping all budget checks for zero-cost model: {model}" + ) + # run through common checks _ = await common_checks( request=request, @@ -599,6 +614,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 llm_router=llm_router, proxy_logging_obj=proxy_logging_obj, valid_token=valid_token, + skip_budget_checks=skip_budget_checks, ) # return UserAPIKeyAuth object @@ -990,8 +1006,22 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 ) user_obj = None + # Check 2a. Check if model has zero cost - if so, skip all budget checks + model = get_model_from_request(request_data, route) + skip_budget_checks = False + if model is not None and llm_router is not None: + from litellm.proxy.auth.auth_checks import _is_model_cost_zero + + skip_budget_checks = _is_model_cost_zero( + model=model, llm_router=llm_router + ) + if skip_budget_checks: + verbose_proxy_logger.info( + f"Skipping all budget checks for zero-cost model: {model}" + ) + # Check 3. Check if user is in their team budget - if valid_token.team_member_spend is not None: + if not skip_budget_checks and valid_token.team_member_spend is not None: if prisma_client is not None: _cache_key = f"{valid_token.team_id}_{valid_token.user_id}" @@ -1055,46 +1085,47 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 param=abbreviate_api_key(api_key=api_key), ) - # Check 4. Token Spend is under budget - if RouteChecks.is_llm_api_route(route=route): - await _virtual_key_max_budget_check( + if not skip_budget_checks: + # Check 4. Token Spend is under budget + if RouteChecks.is_llm_api_route(route=route): + await _virtual_key_max_budget_check( + valid_token=valid_token, + proxy_logging_obj=proxy_logging_obj, + user_obj=user_obj, + ) + + # Check 5. Max Budget Alert Check + await _virtual_key_max_budget_alert_check( valid_token=valid_token, proxy_logging_obj=proxy_logging_obj, user_obj=user_obj, ) - # Check 5. Max Budget Alert Check - await _virtual_key_max_budget_alert_check( - valid_token=valid_token, - proxy_logging_obj=proxy_logging_obj, - user_obj=user_obj, - ) - - # Check 6. Soft Budget Check - await _virtual_key_soft_budget_check( - valid_token=valid_token, - proxy_logging_obj=proxy_logging_obj, - user_obj=user_obj, - ) - - # Check 5. Token Model Spend is under Model budget - max_budget_per_model = valid_token.model_max_budget - current_model = request_data.get("model", None) - - if ( - max_budget_per_model is not None - and isinstance(max_budget_per_model, dict) - and len(max_budget_per_model) > 0 - and prisma_client is not None - and current_model is not None - and valid_token.token is not None - ): - ## GET THE SPEND FOR THIS MODEL - await model_max_budget_limiter.is_key_within_model_budget( - user_api_key_dict=valid_token, - model=current_model, + # Check 6. Soft Budget Check + await _virtual_key_soft_budget_check( + valid_token=valid_token, + proxy_logging_obj=proxy_logging_obj, + user_obj=user_obj, ) + # Check 5. Token Model Spend is under Model budget + max_budget_per_model = valid_token.model_max_budget + current_model = request_data.get("model", None) + + if ( + max_budget_per_model is not None + and isinstance(max_budget_per_model, dict) + and len(max_budget_per_model) > 0 + and prisma_client is not None + and current_model is not None + and valid_token.token is not None + ): + ## GET THE SPEND FOR THIS MODEL + await model_max_budget_limiter.is_key_within_model_budget( + user_api_key_dict=valid_token, + model=current_model, + ) + # Check 6: Additional Common Checks across jwt + key auth if valid_token.team_id is not None: _team_obj: Optional[LiteLLM_TeamTable] = LiteLLM_TeamTable( @@ -1162,6 +1193,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 llm_router=llm_router, proxy_logging_obj=proxy_logging_obj, valid_token=valid_token, + skip_budget_checks=skip_budget_checks, ) # Token passed all checks if valid_token is None: diff --git a/tests/proxy_unit_tests/test_zero_cost_model_budget_bypass.py b/tests/proxy_unit_tests/test_zero_cost_model_budget_bypass.py new file mode 100644 index 00000000000..bc818fc0dca --- /dev/null +++ b/tests/proxy_unit_tests/test_zero_cost_model_budget_bypass.py @@ -0,0 +1,590 @@ +""" +Tests for zero-cost model budget bypass functionality. + +When a user exceeds their budget, the system should still allow requests +to models with zero cost (e.g., on-premises models). +""" + +import asyncio +from typing import Optional +from unittest.mock import MagicMock, patch + +import pytest + +import litellm +from litellm.caching.caching import DualCache +from litellm.proxy._types import ( + LiteLLM_BudgetTable, + LiteLLM_EndUserTable, + LiteLLM_TeamMembership, + LiteLLM_TeamTable, + LiteLLM_UserTable, + UserAPIKeyAuth, +) +from litellm.proxy.auth.auth_checks import ( + _check_team_member_budget, + _is_model_cost_zero, + _team_max_budget_check, + common_checks, +) +from litellm.proxy.utils import ProxyLogging +from litellm.router import Router +from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + +@pytest.fixture +def mock_router_with_zero_cost_model(): + """Create a mock router with a zero-cost model.""" + router = Router( + model_list=[ + { + "model_name": "on-prem-model", + "litellm_params": { + "model": "ollama/llama2", + "api_base": "http://localhost:11434", + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + }, + "model_info": { + "id": "on-prem-model-id", + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + }, + }, + { + "model_name": "cloud-model", + "litellm_params": { + "model": "gpt-3.5-turbo", + "api_key": "sk-test", + }, + "model_info": { + "id": "cloud-model-id", + }, + }, + ] + ) + return router + + +@pytest.fixture +def mock_router_with_paid_model(): + """Create a mock router with only paid models.""" + router = Router( + model_list=[ + { + "model_name": "cloud-model", + "litellm_params": { + "model": "gpt-3.5-turbo", + "api_key": "sk-test", + }, + "model_info": { + "id": "cloud-model-id", + }, + } + ] + ) + return router + + +@pytest.fixture +def mock_proxy_logging(): + """Create a mock ProxyLogging instance.""" + proxy_logging = ProxyLogging(user_api_key_cache=None) + + async def mock_budget_alerts(*args, **kwargs): + pass + + proxy_logging.budget_alerts = mock_budget_alerts + return proxy_logging + + +class TestIsModelCostZero: + """Tests for _is_model_cost_zero helper function.""" + + def test_zero_cost_model_in_router(self, mock_router_with_zero_cost_model): + """Test that a zero-cost model in router is correctly identified.""" + result = _is_model_cost_zero( + model="on-prem-model", llm_router=mock_router_with_zero_cost_model + ) + assert result is True + + def test_paid_model_in_router(self, mock_router_with_zero_cost_model): + """Test that a paid model is correctly identified as non-zero cost.""" + with patch("litellm.get_model_info") as mock_get_model_info: + # Mock the return value for gpt-3.5-turbo + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + result = _is_model_cost_zero( + model="cloud-model", llm_router=mock_router_with_zero_cost_model + ) + assert result is False + + def test_none_model(self, mock_router_with_zero_cost_model): + """Test that None model returns False.""" + result = _is_model_cost_zero( + model=None, llm_router=mock_router_with_zero_cost_model + ) + assert result is False + + def test_none_router(self): + """Test that None router returns False.""" + result = _is_model_cost_zero(model="some-model", llm_router=None) + assert result is False + + def test_list_of_zero_cost_models(self, mock_router_with_zero_cost_model): + """Test that a list of zero-cost models returns True.""" + result = _is_model_cost_zero( + model=["on-prem-model"], llm_router=mock_router_with_zero_cost_model + ) + assert result is True + + def test_mixed_cost_models(self, mock_router_with_zero_cost_model): + """Test that a list with mixed cost models returns False.""" + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + result = _is_model_cost_zero( + model=["on-prem-model", "cloud-model"], + llm_router=mock_router_with_zero_cost_model, + ) + assert result is False + + +class TestUserBudgetBypass: + """Tests for user budget bypass with zero-cost models.""" + + @pytest.mark.asyncio + async def test_user_over_budget_with_zero_cost_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that user over budget can still use zero-cost models.""" + user_object = LiteLLM_UserTable( + user_id="test-user", + spend=100.0, + max_budget=50.0, + ) + + request_body = {"model": "on-prem-model"} + + # Should not raise BudgetExceededError + result = await common_checks( + request_body=request_body, + team_object=None, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + user_id="test-user", + ), + request=MagicMock(), + skip_budget_checks=True, # This is set by user_api_key_auth for zero-cost models + ) + assert result is True + + @pytest.mark.asyncio + async def test_user_over_budget_with_paid_model_blocked( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that user over budget cannot use paid models.""" + user_object = LiteLLM_UserTable( + user_id="test-user", + spend=100.0, + max_budget=50.0, + ) + + request_body = {"model": "cloud-model"} + + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + with pytest.raises(litellm.BudgetExceededError) as exc_info: + await common_checks( + request_body=request_body, + team_object=None, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + user_id="test-user", + ), + request=MagicMock(), + ) + + assert exc_info.value.current_cost == 100.0 + assert exc_info.value.max_budget == 50.0 + assert "test-user" in str(exc_info.value) + + +class TestEndUserBudgetBypass: + """Tests for end user budget bypass with zero-cost models.""" + + @pytest.mark.asyncio + async def test_end_user_over_budget_with_zero_cost_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that end user over budget can still use zero-cost models.""" + end_user_budget = LiteLLM_BudgetTable(max_budget=20.0) + end_user_object = LiteLLM_EndUserTable( + user_id="end-user-123", + spend=50.0, + litellm_budget_table=end_user_budget, + blocked=False, + ) + + request_body = {"model": "on-prem-model", "user": "end-user-123"} + + # In the real flow, skip_budget_checks would be set to True for zero-cost models + result = await common_checks( + request_body=request_body, + team_object=None, + user_object=None, + end_user_object=end_user_object, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + ), + request=MagicMock(), + skip_budget_checks=True, # This is set by user_api_key_auth for zero-cost models + ) + assert result is True + + @pytest.mark.asyncio + async def test_end_user_over_budget_with_paid_model_blocked( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that end user over budget cannot use paid models.""" + end_user_budget = LiteLLM_BudgetTable(max_budget=20.0) + end_user_object = LiteLLM_EndUserTable( + user_id="end-user-123", + spend=50.0, + litellm_budget_table=end_user_budget, + blocked=False, + ) + + request_body = {"model": "cloud-model", "user": "end-user-123"} + + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + with pytest.raises(litellm.BudgetExceededError) as exc_info: + await common_checks( + request_body=request_body, + team_object=None, + user_object=None, + end_user_object=end_user_object, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + ), + request=MagicMock(), + ) + + assert exc_info.value.current_cost == 50.0 + assert exc_info.value.max_budget == 20.0 + assert "end-user-123" in str(exc_info.value) + + +class TestTeamBudgetBypass: + """Tests for team budget bypass with zero-cost models.""" + + @pytest.mark.asyncio + async def test_team_over_budget_with_zero_cost_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that team over budget can still use zero-cost models.""" + team_object = LiteLLM_TeamTable( + team_id="test-team", + spend=150.0, + max_budget=100.0, + ) + + valid_token = UserAPIKeyAuth( + token="test-token", + team_id="test-team", + ) + + request_body = {"model": "on-prem-model"} + + # In the real flow, skip_budget_checks would be set to True for zero-cost models + result = await common_checks( + request_body=request_body, + team_object=team_object, + user_object=None, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=valid_token, + request=MagicMock(), + skip_budget_checks=True, # This is set by user_api_key_auth for zero-cost models + ) + assert result is True + + @pytest.mark.asyncio + async def test_team_over_budget_with_paid_model_blocked( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that team over budget cannot use paid models.""" + team_object = LiteLLM_TeamTable( + team_id="test-team", + spend=150.0, + max_budget=100.0, + ) + + valid_token = UserAPIKeyAuth( + token="test-token", + team_id="test-team", + ) + + request_body = {"model": "cloud-model"} + + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + with pytest.raises(litellm.BudgetExceededError) as exc_info: + await common_checks( + request_body=request_body, + team_object=team_object, + user_object=None, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=valid_token, + request=MagicMock(), + ) + + assert exc_info.value.current_cost == 150.0 + assert exc_info.value.max_budget == 100.0 + assert "test-team" in str(exc_info.value) + + +class TestTeamMemberBudgetBypass: + """Tests for team member budget bypass with zero-cost models.""" + + @pytest.mark.asyncio + async def test_team_member_over_budget_with_zero_cost_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that team member over budget can still use zero-cost models.""" + team_object = LiteLLM_TeamTable( + team_id="test-team", + ) + + user_object = LiteLLM_UserTable( + user_id="test-user", + ) + + valid_token = UserAPIKeyAuth( + token="test-token", + user_id="test-user", + team_id="test-team", + ) + + member_budget = LiteLLM_BudgetTable(max_budget=30.0) + team_membership = LiteLLM_TeamMembership( + user_id="test-user", + team_id="test-team", + spend=60.0, + litellm_budget_table=member_budget, + ) + + request_body = {"model": "on-prem-model"} + + # Mock get_team_membership + with patch( + "litellm.proxy.auth.auth_checks.get_team_membership" + ) as mock_get_membership: + mock_get_membership.return_value = team_membership + + # In the real flow, skip_budget_checks would be set to True for zero-cost models + result = await common_checks( + request_body=request_body, + team_object=team_object, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=valid_token, + request=MagicMock(), + skip_budget_checks=True, # This is set by user_api_key_auth for zero-cost models + ) + assert result is True + + @pytest.mark.asyncio + async def test_team_member_over_budget_with_paid_model_blocked( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that team member over budget cannot use paid models.""" + team_object = LiteLLM_TeamTable( + team_id="test-team", + ) + + user_object = LiteLLM_UserTable( + user_id="test-user", + ) + + valid_token = UserAPIKeyAuth( + token="test-token", + user_id="test-user", + team_id="test-team", + ) + + member_budget = LiteLLM_BudgetTable(max_budget=30.0) + team_membership = LiteLLM_TeamMembership( + user_id="test-user", + team_id="test-team", + spend=60.0, + litellm_budget_table=member_budget, + ) + + request_body = {"model": "cloud-model"} + + with patch( + "litellm.proxy.auth.auth_checks.get_team_membership" + ) as mock_get_membership: + mock_get_membership.return_value = team_membership + + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + with pytest.raises(litellm.BudgetExceededError) as exc_info: + await common_checks( + request_body=request_body, + team_object=team_object, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=valid_token, + request=MagicMock(), + ) + + assert exc_info.value.current_cost == 60.0 + assert exc_info.value.max_budget == 30.0 + assert "test-user" in str(exc_info.value) + assert "test-team" in str(exc_info.value) + + +class TestEdgeCases: + """Tests for edge cases and error handling.""" + + def test_model_not_in_router(self, mock_router_with_zero_cost_model): + """Test behavior when model is not found in router.""" + with patch("litellm.get_model_info") as mock_get_model_info: + # Simulate model not found + mock_get_model_info.side_effect = Exception("Model not found") + result = _is_model_cost_zero( + model="nonexistent-model", llm_router=mock_router_with_zero_cost_model + ) + # Should return False (conservative approach) + assert result is False + + @pytest.mark.asyncio + async def test_user_under_budget_with_paid_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that user under budget can use paid models normally.""" + user_object = LiteLLM_UserTable( + user_id="test-user", + spend=30.0, + max_budget=100.0, + ) + + request_body = {"model": "cloud-model"} + + with patch("litellm.get_model_info") as mock_get_model_info: + mock_get_model_info.return_value = { + "input_cost_per_token": 0.0000015, + "output_cost_per_token": 0.000002, + } + # Should not raise BudgetExceededError + result = await common_checks( + request_body=request_body, + team_object=None, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + user_id="test-user", + ), + request=MagicMock(), + ) + assert result is True + + @pytest.mark.asyncio + async def test_user_under_budget_with_zero_cost_model_allowed( + self, mock_router_with_zero_cost_model, mock_proxy_logging + ): + """Test that user under budget can use zero-cost models normally.""" + user_object = LiteLLM_UserTable( + user_id="test-user", + spend=30.0, + max_budget=100.0, + ) + + request_body = {"model": "on-prem-model"} + + # Should not raise BudgetExceededError + result = await common_checks( + request_body=request_body, + team_object=None, + user_object=user_object, + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/v1/chat/completions", + llm_router=mock_router_with_zero_cost_model, + proxy_logging_obj=mock_proxy_logging, + valid_token=UserAPIKeyAuth( + token="test-token", + user_id="test-user", + ), + request=MagicMock(), + ) + assert result is True From 1932d03aedf5a15cfbc3e3e0ab304160e581e327 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 16:44:02 +0530 Subject: [PATCH 39/46] Add docs on Zero-Cost Models --- docs/my-website/docs/proxy/custom_pricing.md | 46 ++++++++++++++++++++ 1 file changed, 46 insertions(+) diff --git a/docs/my-website/docs/proxy/custom_pricing.md b/docs/my-website/docs/proxy/custom_pricing.md index f6762f5e45c..b5fbd0b6c2e 100644 --- a/docs/my-website/docs/proxy/custom_pricing.md +++ b/docs/my-website/docs/proxy/custom_pricing.md @@ -9,6 +9,7 @@ LiteLLM provides flexible cost tracking and pricing customization for all LLM pr - **Custom Pricing** - Override default model costs or set pricing for custom models - **Cost Per Token** - Track costs based on input/output tokens (most common) - **Cost Per Second** - Track costs based on runtime (e.g., Sagemaker) +- **Zero-Cost Models** - Bypass budget checks for free/on-premises models by setting costs to 0 - **[Provider Discounts](./provider_discounts.md)** - Apply percentage-based discounts to specific providers - **[Provider Margins](./provider_margins.md)** - Add fees/margins to LLM costs for internal billing - **Base Model Mapping** - Ensure accurate cost tracking for Azure deployments @@ -106,6 +107,51 @@ There are other keys you can use to specify costs for different scenarios and mo These keys evolve based on how new models handle multimodality. The latest version can be found at [https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json). +## Zero-Cost Models (Bypass Budget Checks) + +**Use Case**: You have on-premises or free models that should be accessible even when users exceed their budget limits. + +**Solution** ✅: Set both `input_cost_per_token` and `output_cost_per_token` to `0` (explicitly) to bypass all budget checks for that model. + +:::info + +When a model is configured with zero cost, LiteLLM will automatically skip ALL budget checks (user, team, team member, end-user, organization, and global proxy budget) for requests to that model. + +**Important**: Both costs must be **explicitly set to 0**. If costs are `null` or undefined, the model will be treated as having cost and budget checks will apply. + +::: + +### Configuration Example + +```yaml +model_list: + # On-premises model - free to use + - model_name: on-prem-llama + litellm_params: + model: ollama/llama3 + api_base: http://localhost:11434 + model_info: + input_cost_per_token: 0 # 👈 Explicitly set to 0 + output_cost_per_token: 0 # 👈 Explicitly set to 0 + + # Paid cloud model - budget checks apply + - model_name: gpt-4 + litellm_params: + model: gpt-4 + api_key: os.environ/OPENAI_API_KEY + # No model_info - uses default pricing from cost map +``` + +### Behavior + +With the above configuration: + +- **User over budget** → Can still use `on-prem-llama` ✅, but blocked from `gpt-4` ❌ +- **Team over budget** → Can still use `on-prem-llama` ✅, but blocked from `gpt-4` ❌ +- **End-user over budget** → Can still use `on-prem-llama` ✅, but blocked from `gpt-4` ❌ + +This ensures your free/on-premises models remain accessible regardless of budget constraints, while paid models are still properly governed. + ## Set 'base_model' for Cost Tracking (e.g. Azure deployments) **Problem**: Azure returns `gpt-4` in the response when `azure/gpt-4-1106-preview` is used. This leads to inaccurate cost tracking From de6330b6b6b892cccc45a288f1fdfce0761a3976 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Tue, 13 Jan 2026 16:59:17 +0530 Subject: [PATCH 40/46] Fix test_async_otel_callback[False] --- .../test_otel_logging.py | 21 +++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/tests/logging_callback_tests/test_otel_logging.py b/tests/logging_callback_tests/test_otel_logging.py index 3350c6c2dbd..b53be44fe0f 100644 --- a/tests/logging_callback_tests/test_otel_logging.py +++ b/tests/logging_callback_tests/test_otel_logging.py @@ -27,6 +27,9 @@ exporter = InMemorySpanExporter() @pytest.mark.parametrize("streaming", [True, False]) async def test_async_otel_callback(streaming): litellm.set_verbose = True + + # Clear exporter at the start to ensure clean state + exporter.clear() litellm.callbacks = [OpenTelemetry(config=OpenTelemetryConfig(exporter=exporter))] @@ -83,9 +86,9 @@ def validate_litellm_request(span): "llm.user", "gen_ai.response.id", "gen_ai.response.model", - "llm.usage.total_tokens", - "gen_ai.usage.completion_tokens", - "gen_ai.usage.prompt_tokens", + "gen_ai.usage.total_tokens", + "gen_ai.usage.output_tokens", + "gen_ai.usage.input_tokens", ] # get the str of all the span attributes @@ -149,6 +152,10 @@ async def test_awesome_otel_with_message_logging_off(streaming, global_redact): tests when OpenTelemetry(message_logging=False) is set """ litellm.set_verbose = True + + # Clear exporter at the start to ensure clean state + exporter.clear() + litellm.callbacks = [OpenTelemetry(config=OpenTelemetryConfig(exporter=exporter))] if global_redact is False: otel_logger = OpenTelemetry( @@ -201,9 +208,9 @@ def validate_redacted_message_span_attributes(span): "llm.request.type", "gen_ai.response.id", "gen_ai.response.model", - "llm.usage.total_tokens", - "gen_ai.usage.completion_tokens", - "gen_ai.usage.prompt_tokens", + "gen_ai.usage.total_tokens", + "gen_ai.usage.output_tokens", + "gen_ai.usage.input_tokens", ] _all_attributes = set( @@ -230,6 +237,8 @@ def validate_redacted_message_span_attributes(span): attr.startswith("metadata.") or attr.startswith("hidden_params") or attr.startswith("gen_ai.cost.") + or attr.startswith("gen_ai.operation.") + or attr.startswith("gen_ai.request.") ), f"Non-metadata attribute found: {attr}" pass From b7c5662273975708a497de15c375d97b0ab5c8d3 Mon Sep 17 00:00:00 2001 From: Robin Date: Wed, 14 Jan 2026 06:00:19 +0800 Subject: [PATCH 41/46] Fix: update novita models prices (#19005) * feat: ci * feat: fix novita models prices --- model_prices_and_context_window.json | 444 ++++++++++++++------------- 1 file changed, 239 insertions(+), 205 deletions(-) diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index f818a2c82e2..0b97d8761fc 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -32552,8 +32552,8 @@ "novita/deepseek/deepseek-v3.2": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.69e-03, - "output_cost_per_token": 4e-03, + "input_cost_per_token": 2.69e-7, + "output_cost_per_token": 4e-7, "max_input_tokens": 163840, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32562,15 +32562,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 1.345e-03, - "input_cost_per_token_cache_hit": 1.345e-03, + "cache_read_input_token_cost": 1.345e-7, + "input_cost_per_token_cache_hit": 1.345e-7, "supports_reasoning": true }, "novita/minimax/minimax-m2.1": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3e-03, - "output_cost_per_token": 1.2e-02, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 1.2e-06, "max_input_tokens": 204800, "max_output_tokens": 131072, "max_tokens": 131072, @@ -32579,15 +32579,14 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 3e-04, - "input_cost_per_token_cache_hit": 3e-04, - "supports_reasoning": true + "cache_read_input_token_cost": 3e-8, + "input_cost_per_token_cache_hit": 3e-8 }, "novita/zai-org/glm-4.7": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 6e-03, - "output_cost_per_token": 2.2e-02, + "input_cost_per_token": 6e-7, + "output_cost_per_token": 2.2e-06, "max_input_tokens": 204800, "max_output_tokens": 131072, "max_tokens": 131072, @@ -32596,15 +32595,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 1.1e-03, - "input_cost_per_token_cache_hit": 1.1e-03, + "cache_read_input_token_cost": 1.1e-7, + "input_cost_per_token_cache_hit": 1.1e-7, "supports_reasoning": true }, "novita/xiaomimimo/mimo-v2-flash": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1e-03, - "output_cost_per_token": 3e-03, + "input_cost_per_token": 1e-7, + "output_cost_per_token": 3e-7, "max_input_tokens": 262144, "max_output_tokens": 32000, "max_tokens": 32000, @@ -32613,15 +32612,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 2e-04, - "input_cost_per_token_cache_hit": 2e-04, + "cache_read_input_token_cost": 2e-8, + "input_cost_per_token_cache_hit": 2e-8, "supports_reasoning": true }, "novita/zai-org/autoglm-phone-9b-multilingual": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.5e-04, - "output_cost_per_token": 1.38e-03, + "input_cost_per_token": 3.5e-8, + "output_cost_per_token": 1.38e-7, "max_input_tokens": 65536, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32631,8 +32630,8 @@ "novita/moonshotai/kimi-k2-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.8e-03, - "output_cost_per_token": 2e-02, + "input_cost_per_token": 6e-7, + "output_cost_per_token": 2.5e-06, "max_input_tokens": 262144, "max_output_tokens": 262144, "max_tokens": 262144, @@ -32646,8 +32645,8 @@ "novita/minimax/minimax-m2": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-03, - "output_cost_per_token": 9.6e-03, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 1.2e-06, "max_input_tokens": 204800, "max_output_tokens": 131072, "max_tokens": 131072, @@ -32655,15 +32654,15 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true, "supports_system_messages": true, - "cache_read_input_token_cost": 2.4e-04, - "input_cost_per_token_cache_hit": 2.4e-04, + "cache_read_input_token_cost": 3e-8, + "input_cost_per_token_cache_hit": 3e-8, "supports_reasoning": true }, "novita/paddlepaddle/paddleocr-vl": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.6e-04, - "output_cost_per_token": 1.6e-04, + "input_cost_per_token": 2e-8, + "output_cost_per_token": 2e-8, "max_input_tokens": 16384, "max_output_tokens": 16384, "max_tokens": 16384, @@ -32673,8 +32672,8 @@ "novita/deepseek/deepseek-v3.2-exp": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.16e-03, - "output_cost_per_token": 3.28e-03, + "input_cost_per_token": 2.7e-7, + "output_cost_per_token": 4.1e-7, "max_input_tokens": 163840, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32688,8 +32687,8 @@ "novita/qwen/qwen3-vl-235b-a22b-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 7.84e-03, - "output_cost_per_token": 3.16e-02, + "input_cost_per_token": 9.8e-7, + "output_cost_per_token": 3.95e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32700,8 +32699,8 @@ "novita/zai-org/glm-4.6v": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3e-03, - "output_cost_per_token": 9e-03, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 9e-7, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32711,15 +32710,15 @@ "supports_vision": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 5.5e-04, - "input_cost_per_token_cache_hit": 5.5e-04, + "cache_read_input_token_cost": 5.5e-8, + "input_cost_per_token_cache_hit": 5.5e-8, "supports_reasoning": true }, "novita/zai-org/glm-4.6": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.4e-03, - "output_cost_per_token": 1.76e-02, + "input_cost_per_token": 5.5e-7, + "output_cost_per_token": 2.2e-06, "max_input_tokens": 204800, "max_output_tokens": 131072, "max_tokens": 131072, @@ -32728,15 +32727,31 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 8.8e-04, - "input_cost_per_token_cache_hit": 8.8e-04, + "cache_read_input_token_cost": 1.1e-7, + "input_cost_per_token_cache_hit": 1.1e-7, "supports_reasoning": true }, + "novita/kwaipilot/kat-coder-pro": { + "litellm_provider": "novita", + "mode": "chat", + "input_cost_per_token": 3e-7, + "output_cost_per_token": 1.2e-06, + "max_input_tokens": 256000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true, + "supports_system_messages": true, + "supports_response_schema": true, + "cache_read_input_token_cost": 6e-8, + "input_cost_per_token_cache_hit": 6e-8 + }, "novita/qwen/qwen3-next-80b-a3b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.2e-03, - "output_cost_per_token": 1.2e-02, + "input_cost_per_token": 1.5e-7, + "output_cost_per_token": 1.5e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32749,8 +32764,8 @@ "novita/qwen/qwen3-next-80b-a3b-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.2e-03, - "output_cost_per_token": 1.2e-02, + "input_cost_per_token": 1.5e-7, + "output_cost_per_token": 1.5e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32764,8 +32779,8 @@ "novita/deepseek/deepseek-ocr": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-04, - "output_cost_per_token": 2.4e-04, + "input_cost_per_token": 3e-8, + "output_cost_per_token": 3e-8, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -32777,8 +32792,8 @@ "novita/deepseek/deepseek-v3.1-terminus": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.16e-03, - "output_cost_per_token": 8e-03, + "input_cost_per_token": 2.7e-7, + "output_cost_per_token": 1e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32787,15 +32802,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 1.08e-03, - "input_cost_per_token_cache_hit": 1.08e-03, + "cache_read_input_token_cost": 1.35e-7, + "input_cost_per_token_cache_hit": 1.35e-7, "supports_reasoning": true }, "novita/qwen/qwen3-vl-235b-a22b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-03, - "output_cost_per_token": 1.2e-02, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 1.5e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32809,8 +32824,8 @@ "novita/qwen/qwen3-max": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.688e-02, - "output_cost_per_token": 6.76e-02, + "input_cost_per_token": 2.11e-06, + "output_cost_per_token": 8.45e-06, "max_input_tokens": 262144, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32823,8 +32838,8 @@ "novita/skywork/r1v4-lite": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2e-03, - "output_cost_per_token": 6e-03, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 6e-7, "max_input_tokens": 262144, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32836,8 +32851,8 @@ "novita/deepseek/deepseek-v3.1": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.16e-03, - "output_cost_per_token": 8e-03, + "input_cost_per_token": 2.7e-7, + "output_cost_per_token": 1e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32846,15 +32861,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 1.08e-03, - "input_cost_per_token_cache_hit": 1.08e-03, + "cache_read_input_token_cost": 1.35e-7, + "input_cost_per_token_cache_hit": 1.35e-7, "supports_reasoning": true }, "novita/moonshotai/kimi-k2-0905": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.8e-03, - "output_cost_per_token": 2e-02, + "input_cost_per_token": 6e-7, + "output_cost_per_token": 2.5e-06, "max_input_tokens": 262144, "max_output_tokens": 262144, "max_tokens": 262144, @@ -32867,8 +32882,8 @@ "novita/qwen/qwen3-coder-480b-a35b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-03, - "output_cost_per_token": 1.04e-02, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 1.3e-06, "max_input_tokens": 262144, "max_output_tokens": 65536, "max_tokens": 65536, @@ -32881,8 +32896,8 @@ "novita/qwen/qwen3-coder-30b-a3b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 7e-04, - "output_cost_per_token": 2.7e-03, + "input_cost_per_token": 7e-8, + "output_cost_per_token": 2.7e-7, "max_input_tokens": 160000, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32895,8 +32910,8 @@ "novita/openai/gpt-oss-120b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4e-04, - "output_cost_per_token": 2e-03, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 2.5e-7, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32911,8 +32926,8 @@ "novita/moonshotai/kimi-k2-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.56e-03, - "output_cost_per_token": 1.84e-02, + "input_cost_per_token": 5.7e-7, + "output_cost_per_token": 2.3e-06, "max_input_tokens": 131072, "max_output_tokens": 131072, "max_tokens": 131072, @@ -32925,8 +32940,8 @@ "novita/deepseek/deepseek-v3-0324": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.16e-03, - "output_cost_per_token": 8.96e-03, + "input_cost_per_token": 2.7e-7, + "output_cost_per_token": 1.12e-06, "max_input_tokens": 163840, "max_output_tokens": 163840, "max_tokens": 163840, @@ -32935,14 +32950,14 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 1.08e-03, - "input_cost_per_token_cache_hit": 1.08e-03 + "cache_read_input_token_cost": 1.35e-7, + "input_cost_per_token_cache_hit": 1.35e-7 }, "novita/zai-org/glm-4.5": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.8e-03, - "output_cost_per_token": 1.76e-02, + "input_cost_per_token": 6e-7, + "output_cost_per_token": 2.2e-06, "max_input_tokens": 131072, "max_output_tokens": 98304, "max_tokens": 98304, @@ -32950,15 +32965,15 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true, "supports_system_messages": true, - "cache_read_input_token_cost": 8.8e-04, - "input_cost_per_token_cache_hit": 8.8e-04, + "cache_read_input_token_cost": 1.1e-7, + "input_cost_per_token_cache_hit": 1.1e-7, "supports_reasoning": true }, "novita/qwen/qwen3-235b-a22b-thinking-2507": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-03, - "output_cost_per_token": 2.4e-02, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 3e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -32971,8 +32986,8 @@ "novita/meta-llama/llama-3.1-8b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2e-04, - "output_cost_per_token": 5e-04, + "input_cost_per_token": 2e-8, + "output_cost_per_token": 5e-8, "max_input_tokens": 16384, "max_output_tokens": 16384, "max_tokens": 16384, @@ -32981,8 +32996,8 @@ "novita/google/gemma-3-12b-it": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4e-04, - "output_cost_per_token": 8e-04, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 1e-7, "max_input_tokens": 131072, "max_output_tokens": 8192, "max_tokens": 8192, @@ -32994,8 +33009,8 @@ "novita/zai-org/glm-4.5v": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.8e-03, - "output_cost_per_token": 1.44e-02, + "input_cost_per_token": 6e-7, + "output_cost_per_token": 1.8e-06, "max_input_tokens": 65536, "max_output_tokens": 16384, "max_tokens": 16384, @@ -33005,15 +33020,15 @@ "supports_vision": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 8.8e-04, - "input_cost_per_token_cache_hit": 8.8e-04, + "cache_read_input_token_cost": 1.1e-7, + "input_cost_per_token_cache_hit": 1.1e-7, "supports_reasoning": true }, "novita/openai/gpt-oss-20b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.2e-04, - "output_cost_per_token": 1.2e-03, + "input_cost_per_token": 4e-8, + "output_cost_per_token": 1.5e-7, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33026,8 +33041,8 @@ "novita/qwen/qwen3-235b-a22b-instruct-2507": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 7.2e-04, - "output_cost_per_token": 4.64e-03, + "input_cost_per_token": 9e-8, + "output_cost_per_token": 5.8e-7, "max_input_tokens": 131072, "max_output_tokens": 16384, "max_tokens": 16384, @@ -33040,8 +33055,8 @@ "novita/deepseek/deepseek-r1-distill-qwen-14b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.2e-03, - "output_cost_per_token": 1.2e-03, + "input_cost_per_token": 1.5e-7, + "output_cost_per_token": 1.5e-7, "max_input_tokens": 32768, "max_output_tokens": 16384, "max_tokens": 16384, @@ -33053,8 +33068,8 @@ "novita/meta-llama/llama-3.3-70b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.08e-03, - "output_cost_per_token": 3.2e-03, + "input_cost_per_token": 1.35e-7, + "output_cost_per_token": 4e-7, "max_input_tokens": 131072, "max_output_tokens": 120000, "max_tokens": 120000, @@ -33066,8 +33081,8 @@ "novita/qwen/qwen-2.5-72b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.04e-03, - "output_cost_per_token": 3.2e-03, + "input_cost_per_token": 3.8e-7, + "output_cost_per_token": 4e-7, "max_input_tokens": 32000, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33080,8 +33095,8 @@ "novita/mistralai/mistral-nemo": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.2e-04, - "output_cost_per_token": 1.36e-03, + "input_cost_per_token": 4e-8, + "output_cost_per_token": 1.7e-7, "max_input_tokens": 60288, "max_output_tokens": 16000, "max_tokens": 16000, @@ -33092,8 +33107,8 @@ "novita/minimaxai/minimax-m1-80k": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.4e-03, - "output_cost_per_token": 1.76e-02, + "input_cost_per_token": 5.5e-7, + "output_cost_per_token": 2.2e-06, "max_input_tokens": 1000000, "max_output_tokens": 40000, "max_tokens": 40000, @@ -33106,8 +33121,8 @@ "novita/deepseek/deepseek-r1-0528": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-03, - "output_cost_per_token": 2e-02, + "input_cost_per_token": 7e-7, + "output_cost_per_token": 2.5e-06, "max_input_tokens": 163840, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33116,15 +33131,15 @@ "supports_tool_choice": true, "supports_system_messages": true, "supports_response_schema": true, - "cache_read_input_token_cost": 2.8e-03, - "input_cost_per_token_cache_hit": 2.8e-03, + "cache_read_input_token_cost": 3.5e-7, + "input_cost_per_token_cache_hit": 3.5e-7, "supports_reasoning": true }, "novita/deepseek/deepseek-r1-distill-qwen-32b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-03, - "output_cost_per_token": 2.4e-03, + "input_cost_per_token": 3e-7, + "output_cost_per_token": 3e-7, "max_input_tokens": 64000, "max_output_tokens": 32000, "max_tokens": 32000, @@ -33136,8 +33151,8 @@ "novita/meta-llama/llama-3-8b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.2e-04, - "output_cost_per_token": 3.2e-04, + "input_cost_per_token": 4e-8, + "output_cost_per_token": 4e-8, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33146,8 +33161,8 @@ "novita/microsoft/wizardlm-2-8x22b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.96e-03, - "output_cost_per_token": 4.96e-03, + "input_cost_per_token": 6.2e-7, + "output_cost_per_token": 6.2e-7, "max_input_tokens": 65535, "max_output_tokens": 8000, "max_tokens": 8000, @@ -33156,8 +33171,8 @@ "novita/deepseek/deepseek-r1-0528-qwen3-8b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 4.8e-04, - "output_cost_per_token": 7.2e-04, + "input_cost_per_token": 6e-8, + "output_cost_per_token": 9e-8, "max_input_tokens": 128000, "max_output_tokens": 32000, "max_tokens": 32000, @@ -33167,8 +33182,8 @@ "novita/deepseek/deepseek-r1-distill-llama-70b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 6.4e-03, - "output_cost_per_token": 6.4e-03, + "input_cost_per_token": 8e-7, + "output_cost_per_token": 8e-7, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33180,8 +33195,8 @@ "novita/meta-llama/llama-3-70b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.1e-03, - "output_cost_per_token": 7.4e-03, + "input_cost_per_token": 5.1e-7, + "output_cost_per_token": 7.4e-7, "max_input_tokens": 8192, "max_output_tokens": 8000, "max_tokens": 8000, @@ -33192,8 +33207,8 @@ "novita/qwen/qwen3-235b-a22b-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.6e-03, - "output_cost_per_token": 6.4e-03, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 8e-7, "max_input_tokens": 40960, "max_output_tokens": 20000, "max_tokens": 20000, @@ -33203,8 +33218,8 @@ "novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.6e-03, - "output_cost_per_token": 7.2e-03, + "input_cost_per_token": 2.7e-7, + "output_cost_per_token": 8.5e-7, "max_input_tokens": 1048576, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33214,8 +33229,8 @@ "novita/meta-llama/llama-4-scout-17b-16e-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 8e-04, - "output_cost_per_token": 4e-03, + "input_cost_per_token": 1.8e-7, + "output_cost_per_token": 5.9e-7, "max_input_tokens": 131072, "max_output_tokens": 131072, "max_tokens": 131072, @@ -33225,8 +33240,8 @@ "novita/nousresearch/hermes-2-pro-llama-3-8b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.4e-03, - "output_cost_per_token": 1.4e-03, + "input_cost_per_token": 1.4e-7, + "output_cost_per_token": 1.4e-7, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33237,8 +33252,8 @@ "novita/qwen/qwen2.5-vl-72b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 6.4e-03, - "output_cost_per_token": 6.4e-03, + "input_cost_per_token": 8e-7, + "output_cost_per_token": 8e-7, "max_input_tokens": 32768, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33248,8 +33263,8 @@ "novita/sao10k/l3-70b-euryale-v2.1": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.48e-02, - "output_cost_per_token": 1.48e-02, + "input_cost_per_token": 1.48e-06, + "output_cost_per_token": 1.48e-06, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33261,8 +33276,8 @@ "novita/baidu/ernie-4.5-21B-a3b-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-04, - "output_cost_per_token": 2.24e-03, + "input_cost_per_token": 7e-8, + "output_cost_per_token": 2.8e-7, "max_input_tokens": 131072, "max_output_tokens": 65536, "max_tokens": 65536, @@ -33272,8 +33287,8 @@ "novita/sao10k/l3-8b-lunaris": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5e-04, - "output_cost_per_token": 5e-04, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 5e-8, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33284,33 +33299,18 @@ "novita/baichuan/baichuan-m2-32b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-04, - "output_cost_per_token": 5.6e-04, + "input_cost_per_token": 7e-8, + "output_cost_per_token": 7e-8, "max_input_tokens": 131072, "max_output_tokens": 131072, "max_tokens": 131072, - "supports_tool_choice": true, - "supports_system_messages": true, - "supports_response_schema": true, - "supports_reasoning": true - }, - "novita/thudm/glm-4.1v-9b-thinking": { - "litellm_provider": "novita", - "mode": "chat", - "input_cost_per_token": 2.8e-04, - "output_cost_per_token": 1.104e-03, - "max_input_tokens": 65536, - "max_output_tokens": 8000, - "max_tokens": 8000, - "supports_vision": true, - "supports_system_messages": true, - "supports_reasoning": true + "supports_system_messages": true }, "novita/baidu/ernie-4.5-vl-424b-a47b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.36e-03, - "output_cost_per_token": 1e-02, + "input_cost_per_token": 4.2e-7, + "output_cost_per_token": 1.25e-06, "max_input_tokens": 123000, "max_output_tokens": 16000, "max_tokens": 16000, @@ -33321,8 +33321,8 @@ "novita/baidu/ernie-4.5-300b-a47b-paddle": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.24e-03, - "output_cost_per_token": 8.8e-03, + "input_cost_per_token": 2.8e-7, + "output_cost_per_token": 1.1e-06, "max_input_tokens": 123000, "max_output_tokens": 12000, "max_tokens": 12000, @@ -33333,8 +33333,8 @@ "novita/deepseek/deepseek-prover-v2-671b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-03, - "output_cost_per_token": 2e-02, + "input_cost_per_token": 7e-7, + "output_cost_per_token": 2.5e-06, "max_input_tokens": 160000, "max_output_tokens": 160000, "max_tokens": 160000, @@ -33343,8 +33343,8 @@ "novita/qwen/qwen3-32b-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 8e-04, - "output_cost_per_token": 3.6e-03, + "input_cost_per_token": 1e-7, + "output_cost_per_token": 4.5e-7, "max_input_tokens": 40960, "max_output_tokens": 20000, "max_tokens": 20000, @@ -33354,8 +33354,8 @@ "novita/qwen/qwen3-30b-a3b-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 7.2e-04, - "output_cost_per_token": 3.6e-03, + "input_cost_per_token": 9e-8, + "output_cost_per_token": 4.5e-7, "max_input_tokens": 40960, "max_output_tokens": 20000, "max_tokens": 20000, @@ -33365,8 +33365,8 @@ "novita/google/gemma-3-27b-it": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 9.52e-04, - "output_cost_per_token": 1.6e-03, + "input_cost_per_token": 1.19e-7, + "output_cost_per_token": 2e-7, "max_input_tokens": 98304, "max_output_tokens": 16384, "max_tokens": 16384, @@ -33376,8 +33376,8 @@ "novita/deepseek/deepseek-v3-turbo": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.2e-03, - "output_cost_per_token": 1.04e-02, + "input_cost_per_token": 4e-7, + "output_cost_per_token": 1.3e-06, "max_input_tokens": 64000, "max_output_tokens": 16000, "max_tokens": 16000, @@ -33389,8 +33389,8 @@ "novita/deepseek/deepseek-r1-turbo": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-03, - "output_cost_per_token": 2e-02, + "input_cost_per_token": 7e-7, + "output_cost_per_token": 2.5e-06, "max_input_tokens": 64000, "max_output_tokens": 16000, "max_tokens": 16000, @@ -33403,8 +33403,8 @@ "novita/Sao10K/L3-8B-Stheno-v3.2": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5e-04, - "output_cost_per_token": 5e-04, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 5e-8, "max_input_tokens": 8192, "max_output_tokens": 32000, "max_tokens": 32000, @@ -33416,8 +33416,8 @@ "novita/gryphe/mythomax-l2-13b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 7.2e-04, - "output_cost_per_token": 7.2e-04, + "input_cost_per_token": 9e-8, + "output_cost_per_token": 9e-8, "max_input_tokens": 4096, "max_output_tokens": 3200, "max_tokens": 3200, @@ -33426,8 +33426,8 @@ "novita/baidu/ernie-4.5-vl-28b-a3b-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 3.9e-03, - "output_cost_per_token": 3.9e-03, + "input_cost_per_token": 3.9e-7, + "output_cost_per_token": 3.9e-7, "max_input_tokens": 131072, "max_output_tokens": 65536, "max_tokens": 65536, @@ -33442,8 +33442,8 @@ "novita/qwen/qwen3-vl-8b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 6.4e-04, - "output_cost_per_token": 4e-03, + "input_cost_per_token": 8e-8, + "output_cost_per_token": 5e-7, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33457,8 +33457,8 @@ "novita/zai-org/glm-4.5-air": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.04e-03, - "output_cost_per_token": 6.8e-03, + "input_cost_per_token": 1.3e-7, + "output_cost_per_token": 8.5e-7, "max_input_tokens": 131072, "max_output_tokens": 98304, "max_tokens": 98304, @@ -33471,8 +33471,8 @@ "novita/qwen/qwen3-vl-30b-a3b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.6e-03, - "output_cost_per_token": 5.6e-03, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 7e-7, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33486,8 +33486,8 @@ "novita/qwen/qwen3-vl-30b-a3b-thinking": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.6e-03, - "output_cost_per_token": 8e-03, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 1e-06, "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, @@ -33498,11 +33498,45 @@ "supports_system_messages": true, "supports_response_schema": true }, + "novita/qwen/qwen3-omni-30b-a3b-thinking": { + "litellm_provider": "novita", + "mode": "chat", + "input_cost_per_token": 2.5e-7, + "output_cost_per_token": 9.7e-7, + "max_input_tokens": 65536, + "max_output_tokens": 16384, + "max_tokens": 16384, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_system_messages": true, + "supports_response_schema": true, + "supports_reasoning": true, + "supports_audio_input": true + }, + "novita/qwen/qwen3-omni-30b-a3b-instruct": { + "litellm_provider": "novita", + "mode": "chat", + "input_cost_per_token": 2.5e-7, + "output_cost_per_token": 9.7e-7, + "max_input_tokens": 65536, + "max_output_tokens": 16384, + "max_tokens": 16384, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_system_messages": true, + "supports_response_schema": true, + "supports_audio_input": true, + "supports_audio_output": true + }, "novita/qwen/qwen-mt-plus": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2e-03, - "output_cost_per_token": 6e-03, + "input_cost_per_token": 2.5e-7, + "output_cost_per_token": 7.5e-7, "max_input_tokens": 16384, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33511,8 +33545,8 @@ "novita/baidu/ernie-4.5-vl-28b-a3b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.12e-03, - "output_cost_per_token": 4.48e-03, + "input_cost_per_token": 1.4e-7, + "output_cost_per_token": 5.6e-7, "max_input_tokens": 30000, "max_output_tokens": 8000, "max_tokens": 8000, @@ -33526,8 +33560,8 @@ "novita/baidu/ernie-4.5-21B-a3b": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-04, - "output_cost_per_token": 2.24e-03, + "input_cost_per_token": 7e-8, + "output_cost_per_token": 2.8e-7, "max_input_tokens": 120000, "max_output_tokens": 8000, "max_tokens": 8000, @@ -33539,8 +33573,8 @@ "novita/qwen/qwen3-8b-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.8e-04, - "output_cost_per_token": 1.104e-03, + "input_cost_per_token": 3.5e-8, + "output_cost_per_token": 1.38e-7, "max_input_tokens": 128000, "max_output_tokens": 20000, "max_tokens": 20000, @@ -33550,8 +33584,8 @@ "novita/qwen/qwen3-4b-fp8": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-04, - "output_cost_per_token": 2.4e-04, + "input_cost_per_token": 3e-8, + "output_cost_per_token": 3e-8, "max_input_tokens": 128000, "max_output_tokens": 20000, "max_tokens": 20000, @@ -33561,8 +33595,8 @@ "novita/qwen/qwen2.5-7b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 5.6e-04, - "output_cost_per_token": 5.6e-04, + "input_cost_per_token": 7e-8, + "output_cost_per_token": 7e-8, "max_input_tokens": 32000, "max_output_tokens": 32000, "max_tokens": 32000, @@ -33575,8 +33609,8 @@ "novita/meta-llama/llama-3.2-3b-instruct": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 2.4e-04, - "output_cost_per_token": 4e-04, + "input_cost_per_token": 3e-8, + "output_cost_per_token": 5e-8, "max_input_tokens": 32768, "max_output_tokens": 32000, "max_tokens": 32000, @@ -33588,8 +33622,8 @@ "novita/sao10k/l31-70b-euryale-v2.2": { "litellm_provider": "novita", "mode": "chat", - "input_cost_per_token": 1.48e-02, - "output_cost_per_token": 1.48e-02, + "input_cost_per_token": 1.48e-06, + "output_cost_per_token": 1.48e-06, "max_input_tokens": 8192, "max_output_tokens": 8192, "max_tokens": 8192, @@ -33601,7 +33635,7 @@ "novita/qwen/qwen3-embedding-0.6b": { "litellm_provider": "novita", "mode": "embedding", - "input_cost_per_token": 5.6e-04, + "input_cost_per_token": 7e-8, "output_cost_per_token": 0, "max_input_tokens": 32768, "max_output_tokens": 32768, @@ -33610,7 +33644,7 @@ "novita/qwen/qwen3-embedding-8b": { "litellm_provider": "novita", "mode": "embedding", - "input_cost_per_token": 5.6e-04, + "input_cost_per_token": 7e-8, "output_cost_per_token": 0, "max_input_tokens": 32768, "max_output_tokens": 4096, @@ -33619,8 +33653,8 @@ "novita/baai/bge-m3": { "litellm_provider": "novita", "mode": "embedding", - "input_cost_per_token": 1e-04, - "output_cost_per_token": 1e-04, + "input_cost_per_token": 1e-8, + "output_cost_per_token": 1e-8, "max_input_tokens": 8192, "max_output_tokens": 96000, "max_tokens": 96000 @@ -33628,8 +33662,8 @@ "novita/qwen/qwen3-reranker-8b": { "litellm_provider": "novita", "mode": "rerank", - "input_cost_per_token": 4e-04, - "output_cost_per_token": 4e-04, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 5e-8, "max_input_tokens": 32768, "max_output_tokens": 4096, "max_tokens": 4096 @@ -33637,8 +33671,8 @@ "novita/baai/bge-reranker-v2-m3": { "litellm_provider": "novita", "mode": "rerank", - "input_cost_per_token": 1e-04, - "output_cost_per_token": 1e-04, + "input_cost_per_token": 1e-8, + "output_cost_per_token": 1e-8, "max_input_tokens": 8000, "max_output_tokens": 8000, "max_tokens": 8000 From d03c5017ffac9112aa37f2c3605d82756f737a79 Mon Sep 17 00:00:00 2001 From: Cesar Garcia <128240629+Chesars@users.noreply.github.com> Date: Tue, 13 Jan 2026 19:19:47 -0300 Subject: [PATCH 42/46] fix: correct context window sizes for GPT-5 model variants (#18928) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix: correct context window sizes for GPT-5 model variants Updates max_input_tokens for GPT-5, GPT-5.1, and GPT-5.2 model variants to match OpenAI's official specifications, resolving issue #18927. Changes: - GPT-5.1 (base, codex variants): 272k → 400k tokens - GPT-5.1-chat variants: 272k → 128k tokens (with max_output 16,384) - GPT-5 (base): 272k → 400k tokens - GPT-5-chat: 272k → 128k tokens (with max_output 16,384) - GPT-5-codex: 272k → 400k tokens - GPT-5-mini: 272k → 400k tokens - GPT-5-nano: 272k → 400k tokens - GPT-5-pro: 272k → 400k tokens (max_output 272k) - GPT-5 dated versions (2025-08-07): 272k → 400k tokens Affected providers: OpenAI, Azure (all regions), OpenRouter Fixes #18927 * fix: correct Azure GPT-5 context window limits to match Azure docs Azure OpenAI has different limits than OpenAI for GPT-5 models. Changes: - Azure GPT-5 models: max_input_tokens 400k → 272k (Azure limit) - Azure GPT-5 Pro: max_output_tokens 272k → 128k (Azure limit) - OpenAI GPT-5 models: remain at 400k (correct) - OpenRouter models: remain at 400k (routes to OpenAI) Azure docs specify 272k input + 128k output = 400k total context. OpenAI allows full 400k input + 128k output. * fix: correct Azure GPT-5 max_input_tokens to 272k Azure has explicit input limit of 272k tokens (not 400k like OpenAI). Context window 400k = 272k input + 128k output for Azure. OpenAI allows flexible input up to 400k (context - output). --- model_prices_and_context_window.json | 70 ++++++++++++++-------------- 1 file changed, 35 insertions(+), 35 deletions(-) diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 0b97d8761fc..6d814c731dc 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1644,7 +1644,7 @@ "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.38e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -1944,7 +1944,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -2893,7 +2893,7 @@ "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -2964,7 +2964,7 @@ "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -2997,7 +2997,7 @@ "input_cost_per_token": 2.5e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -3092,9 +3092,9 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, "source": "https://azure.microsoft.com/en-us/blog/gpt-5-in-azure-ai-foundry-the-future-of-ai-apps-and-agents-starts-here/", @@ -3377,7 +3377,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -3440,7 +3440,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -3500,7 +3500,7 @@ "cache_read_input_token_cost": 1.75e-07, "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -3637,7 +3637,7 @@ "azure/gpt-5.2-pro": { "input_cost_per_token": 2.1e-05, "litellm_provider": "azure", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -3668,7 +3668,7 @@ "azure/gpt-5.2-pro-2025-12-11": { "input_cost_per_token": 2.1e-05, "litellm_provider": "azure", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -4684,7 +4684,7 @@ "cache_read_input_token_cost": 1.4e-07, "input_cost_per_token": 1.38e-06, "litellm_provider": "azure", - "max_input_tokens": 272000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -17470,7 +17470,7 @@ "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -17507,7 +17507,7 @@ "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -17543,7 +17543,7 @@ "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -17852,7 +17852,7 @@ "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -17887,9 +17887,9 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, "supported_endpoints": [ @@ -17951,7 +17951,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -17983,7 +17983,7 @@ "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -18046,7 +18046,7 @@ "input_cost_per_token": 2.5e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", @@ -18081,7 +18081,7 @@ "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -18120,7 +18120,7 @@ "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -18158,7 +18158,7 @@ "input_cost_per_token_flex": 2.5e-08, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -18193,7 +18193,7 @@ "input_cost_per_token": 5e-08, "input_cost_per_token_flex": 2.5e-08, "litellm_provider": "openai", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -23206,9 +23206,9 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "openrouter", - "max_input_tokens": 272000, - "max_output_tokens": 128000, - "max_tokens": 128000, + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, "supported_modalities": [ @@ -23225,7 +23225,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "openrouter", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -23244,7 +23244,7 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "openrouter", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -23263,7 +23263,7 @@ "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 2.5e-07, "litellm_provider": "openrouter", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", @@ -23282,7 +23282,7 @@ "cache_read_input_token_cost": 5e-09, "input_cost_per_token": 5e-08, "litellm_provider": "openrouter", - "max_input_tokens": 272000, + "max_input_tokens": 400000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", From 478bdcb60b96792d8c70a57d2b5d9089e00a32d3 Mon Sep 17 00:00:00 2001 From: nulone <115600674+nulone@users.noreply.github.com> Date: Wed, 14 Jan 2026 05:22:50 +0700 Subject: [PATCH 43/46] fix(model_prices): sync DeepSeek chat/reasoner to V3.2 pricing (#18884) --- model_prices_and_context_window.json | 31 ++++++++++++++-------------- 1 file changed, 16 insertions(+), 15 deletions(-) diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 6d814c731dc..0005269ad58 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -7813,14 +7813,14 @@ "supports_vision": true }, "deepseek-chat": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 6e-07, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, "max_output_tokens": 8192, "max_tokens": 8192, "mode": "chat", - "output_cost_per_token": 1.7e-06, + "output_cost_per_token": 4.2e-07, "source": "https://api-docs.deepseek.com/quick_start/pricing", "supported_endpoints": [ "/v1/chat/completions" @@ -7834,14 +7834,14 @@ "supports_tool_choice": true }, "deepseek-reasoner": { - "cache_read_input_token_cost": 6e-08, - "input_cost_per_token": 6e-07, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, "max_output_tokens": 65536, "max_tokens": 65536, "mode": "chat", - "output_cost_per_token": 1.7e-06, + "output_cost_per_token": 4.2e-07, "source": "https://api-docs.deepseek.com/quick_start/pricing", "supported_endpoints": [ "/v1/chat/completions" @@ -10045,15 +10045,15 @@ }, "deepseek/deepseek-chat": { "cache_creation_input_token_cost": 0.0, - "cache_read_input_token_cost": 7e-08, - "input_cost_per_token": 2.7e-07, - "input_cost_per_token_cache_hit": 7e-08, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 2.8e-07, + "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", - "max_input_tokens": 65536, + "max_input_tokens": 128000, "max_output_tokens": 8192, "max_tokens": 8192, "mode": "chat", - "output_cost_per_token": 1.1e-06, + "output_cost_per_token": 4.2e-07, "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, @@ -10089,14 +10089,15 @@ "supports_tool_choice": true }, "deepseek/deepseek-reasoner": { - "input_cost_per_token": 5.5e-07, - "input_cost_per_token_cache_hit": 1.4e-07, + "cache_read_input_token_cost": 2.8e-08, + "input_cost_per_token": 2.8e-07, + "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", - "max_input_tokens": 65536, + "max_input_tokens": 128000, "max_output_tokens": 8192, "max_tokens": 8192, "mode": "chat", - "output_cost_per_token": 2.19e-06, + "output_cost_per_token": 4.2e-07, "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, From a445d8a4b491a189bc01cc62ccbbf9be70903769 Mon Sep 17 00:00:00 2001 From: Cesar Garcia <128240629+Chesars@users.noreply.github.com> Date: Tue, 13 Jan 2026 19:39:24 -0300 Subject: [PATCH 44/46] fix(pricing): correct cache_read pricing for gemini-2.5-pro models (#18157) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Fix cache_read_input_token_cost: 3.125e-07 → 1.25e-07 ($0.125/1M) - Add cache_read_input_token_cost_above_200k_tokens: 2.5e-07 ($0.25/1M) Models updated: - gemini-2.5-pro - gemini-2.5-pro-exp-03-25 - gemini-2.5-pro-preview-03-25 - gemini-2.5-pro-preview-05-06 - gemini-2.5-pro-preview-06-05 - gemini-2.5-pro-preview-tts - gemini/gemini-2.5-pro - gemini/gemini-2.5-pro-preview-03-25 - gemini/gemini-2.5-pro-preview-05-06 - gemini/gemini-2.5-pro-preview-06-05 - gemini/gemini-2.5-pro-preview-tts Pricing source: https://ai.google.dev/gemini-api/docs/pricing --- ...odel_prices_and_context_window_backup.json | 31 +++++++++++++------ model_prices_and_context_window.json | 31 +++++++++++++------ 2 files changed, 42 insertions(+), 20 deletions(-) diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index f818a2c82e2..91cb1b8d27a 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -12996,6 +12996,7 @@ }, "gemini-2.5-pro": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13178,7 +13179,8 @@ "supports_web_search": true }, "gemini-2.5-pro-exp-03-25": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -13222,7 +13224,8 @@ }, "gemini-2.5-pro-preview-03-25": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13268,7 +13271,8 @@ }, "gemini-2.5-pro-preview-05-06": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13316,7 +13320,8 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-06-05": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13361,7 +13366,8 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-tts": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -14850,7 +14856,8 @@ "tpm": 250000 }, "gemini/gemini-2.5-pro": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "gemini", @@ -15112,7 +15119,8 @@ }, "gemini/gemini-2.5-pro-preview-03-25": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15153,7 +15161,8 @@ }, "gemini/gemini-2.5-pro-preview-05-06": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15194,7 +15203,8 @@ "tpm": 10000000 }, "gemini/gemini-2.5-pro-preview-06-05": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15235,7 +15245,8 @@ "tpm": 10000000 }, "gemini/gemini-2.5-pro-preview-tts": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 0005269ad58..39008d802be 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -12997,6 +12997,7 @@ }, "gemini-2.5-pro": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13179,7 +13180,8 @@ "supports_web_search": true }, "gemini-2.5-pro-exp-03-25": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -13223,7 +13225,8 @@ }, "gemini-2.5-pro-preview-03-25": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13269,7 +13272,8 @@ }, "gemini-2.5-pro-preview-05-06": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13317,7 +13321,8 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-06-05": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 1.25e-06, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -13362,7 +13367,8 @@ "supports_web_search": true }, "gemini-2.5-pro-preview-tts": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -14851,7 +14857,8 @@ "tpm": 250000 }, "gemini/gemini-2.5-pro": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "gemini", @@ -15113,7 +15120,8 @@ }, "gemini/gemini-2.5-pro-preview-03-25": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15154,7 +15162,8 @@ }, "gemini/gemini-2.5-pro-preview-05-06": { "deprecation_date": "2025-12-02", - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15195,7 +15204,8 @@ "tpm": 10000000 }, "gemini/gemini-2.5-pro-preview-06-05": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, @@ -15236,7 +15246,8 @@ "tpm": 10000000 }, "gemini/gemini-2.5-pro-preview-tts": { - "cache_read_input_token_cost": 3.125e-07, + "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, From 308d24d067b0df1b8bd6ecdbf8892658649ece2c Mon Sep 17 00:00:00 2001 From: yuneng-jiang Date: Tue, 13 Jan 2026 14:42:28 -0800 Subject: [PATCH 45/46] Resolve Team ID and Team name in export --- .../EntityUsageExportModal.test.tsx | 20 +- .../EntityUsageExportModal.tsx | 62 +- .../EntityUsageExport/UsageExportHeader.tsx | 4 + .../src/components/EntityUsageExport/types.ts | 2 + .../EntityUsageExport/utils.test.ts | 1004 +++++++++++++++++ .../src/components/EntityUsageExport/utils.ts | 83 +- .../EntityUsage/EntityUsage.test.tsx | 6 +- .../components/EntityUsage/EntityUsage.tsx | 1 + 8 files changed, 1135 insertions(+), 47 deletions(-) create mode 100644 ui/litellm-dashboard/src/components/EntityUsageExport/utils.test.ts diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx index d881e225273..820adfcdd55 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx @@ -10,7 +10,7 @@ */ import { describe, it, expect, vi, beforeEach } from "vitest"; -import { render } from "@testing-library/react"; +import { renderWithProviders } from "../../../tests/test-utils"; import userEvent from "@testing-library/user-event"; import EntityUsageExportModal from "./EntityUsageExportModal"; @@ -35,6 +35,16 @@ vi.mock("../molecules/notifications_manager", () => { }; }); +// Mock useTeams hook +vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({ + useTeams: vi.fn(() => ({ + data: [], + isLoading: false, + error: null, + refetch: vi.fn(), + })), +})); + // JSDOM stubs for download flow used by the modal // @ts-ignore global.URL.createObjectURL = vi.fn(() => "blob:mock"); @@ -74,7 +84,7 @@ describe("EntityUsageExportModal", () => { const user = userEvent.setup(); const { handleExportCSV } = await import("./utils"); - const { getByRole } = render(); + const { getByRole } = renderWithProviders(); // Default primary action reflects CSV export expect(getByRole("button", { name: /Export CSV/i })).toBeInTheDocument(); @@ -83,7 +93,7 @@ describe("EntityUsageExportModal", () => { await user.click(getByRole("button", { name: /Export CSV/i })); // Verifies export function was invoked with correct parameters - expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily", "Tag", "tag"); + expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily", "Tag", "tag", {}); // Modal closes after export expect(baseProps.onClose).toHaveBeenCalled(); @@ -98,7 +108,7 @@ describe("EntityUsageExportModal", () => { const user = userEvent.setup(); const { handleExportCSV } = await import("./utils"); - const { getByText, getByRole } = render(); + const { getByText, getByRole } = renderWithProviders(); // Choose the alternate export type - click the label to trigger radio const dailyModelLabel = getByText(/Day-by-day by tag and model/i); @@ -109,7 +119,7 @@ describe("EntityUsageExportModal", () => { await user.click(exportBtn); // Ensure the selected scope flowed through - expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily_with_models", "Tag", "tag"); + expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily_with_models", "Tag", "tag", {}); // Modal closes after export expect(baseProps.onClose).toHaveBeenCalled(); diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.tsx b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.tsx index 5b40d761983..4c934bbf1d3 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.tsx +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.tsx @@ -1,12 +1,13 @@ -import React, { useState } from "react"; -import { Button } from "@tremor/react"; -import { Modal } from "antd"; +import { useTeams } from "@/app/(dashboard)/hooks/teams/useTeams"; +import { createTeamAliasMap } from "@/utils/teamUtils"; +import { Button, Modal, Skeleton } from "antd"; +import React, { useMemo, useState } from "react"; import NotificationsManager from "../molecules/notifications_manager"; +import ExportFormatSelector from "./ExportFormatSelector"; import ExportSummary from "./ExportSummary"; import ExportTypeSelector from "./ExportTypeSelector"; -import ExportFormatSelector from "./ExportFormatSelector"; -import { handleExportCSV, handleExportJSON } from "./utils"; import type { EntityUsageExportModalProps, ExportFormat, ExportScope } from "./types"; +import { handleExportCSV, handleExportJSON } from "./utils"; const EntityUsageExportModal: React.FC = ({ isOpen, @@ -20,19 +21,22 @@ const EntityUsageExportModal: React.FC = ({ const [exportFormat, setExportFormat] = useState("csv"); const [exportScope, setExportScope] = useState("daily"); const [isExporting, setIsExporting] = useState(false); + const { data: teams, isLoading: isLoadingTeams } = useTeams(); const entityLabel = entityType.charAt(0).toUpperCase() + entityType.slice(1); const modalTitle = customTitle || `Export ${entityLabel} Usage`; + // Cache team alias map using useMemo + const teamAliasMap = useMemo(() => createTeamAliasMap(teams), [teams]); const handleExport = async (format?: ExportFormat) => { const formatToUse = format || exportFormat; setIsExporting(true); try { if (formatToUse === "csv") { - handleExportCSV(spendData, exportScope, entityLabel, entityType); + handleExportCSV(spendData, exportScope, entityLabel, entityType, teamAliasMap); NotificationsManager.success(`${entityLabel} usage data exported successfully as CSV`); } else { - handleExportJSON(spendData, exportScope, entityLabel, entityType, dateRange, selectedFilters); + handleExportJSON(spendData, exportScope, entityLabel, entityType, dateRange, selectedFilters, teamAliasMap); NotificationsManager.success(`${entityLabel} usage data exported successfully as JSON`); } onClose(); @@ -51,23 +55,37 @@ const EntityUsageExportModal: React.FC = ({ onCancel={onClose} footer={null} width={480} - destroyOnClose >
- - - - - - -
- - -
+ {isLoadingTeams ? ( + + ) : ( + <> + + + + + )} + {isLoadingTeams ? ( +
+ + +
+ ) : ( +
+ + +
+ )}
); diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/UsageExportHeader.tsx b/ui/litellm-dashboard/src/components/EntityUsageExport/UsageExportHeader.tsx index b390c19df16..989ff8703e8 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/UsageExportHeader.tsx +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/UsageExportHeader.tsx @@ -4,6 +4,7 @@ import { Select } from "antd"; import React, { useState } from "react"; import EntityUsageExportModal from "./EntityUsageExportModal"; import type { EntitySpendData, EntityType } from "./types"; +import type { Team } from "@/components/key_team_helpers/key_list"; interface UsageExportHeaderProps { dateValue: DateRangePickerValue; @@ -18,6 +19,7 @@ interface UsageExportHeaderProps { filterOptions?: Array<{ label: string; value: string }>; customTitle?: string; compactLayout?: boolean; + teams?: Team[]; } const UsageExportHeader: React.FC = ({ @@ -32,6 +34,7 @@ const UsageExportHeader: React.FC = ({ filterOptions = [], customTitle, compactLayout = false, + teams = [], }) => { const [isExportModalOpen, setIsExportModalOpen] = useState(false); @@ -95,6 +98,7 @@ const UsageExportHeader: React.FC = ({ dateRange={dateValue} selectedFilters={selectedFilters} customTitle={customTitle} + teams={teams} /> ); diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/types.ts b/ui/litellm-dashboard/src/components/EntityUsageExport/types.ts index 81b0307c712..84a20da7cba 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/types.ts +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/types.ts @@ -1,4 +1,5 @@ import type { DateRangePickerValue } from "@tremor/react"; +import type { Team } from "@/components/key_team_helpers/key_list"; export type ExportFormat = "csv" | "json"; export type ExportScope = "daily" | "daily_with_models"; @@ -23,6 +24,7 @@ export interface EntityUsageExportModalProps { dateRange: DateRangePickerValue; selectedFilters: string[]; customTitle?: string; + teams?: Team[]; } export interface ExportMetadata { diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/utils.test.ts b/ui/litellm-dashboard/src/components/EntityUsageExport/utils.test.ts new file mode 100644 index 00000000000..127e3fc208f --- /dev/null +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/utils.test.ts @@ -0,0 +1,1004 @@ +import type { DateRangePickerValue } from "@tremor/react"; +import Papa from "papaparse"; +import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"; +import type { EntitySpendData, ExportScope } from "./types"; +import { + generateDailyData, + generateDailyWithModelsData, + generateExportData, + generateMetadata, + getEntityBreakdown, + handleExportCSV, + handleExportJSON, +} from "./utils"; + +vi.mock("@/utils/dataUtils", () => ({ + formatNumberWithCommas: vi.fn((value: number, decimals: number = 0) => { + if (value === null || value === undefined || !Number.isFinite(value)) { + return "-"; + } + return value.toFixed(decimals); + }), +})); + +vi.mock("papaparse", () => ({ + default: { + unparse: vi.fn((data: any[]) => "mocked-csv-data"), + }, +})); + +describe("EntityUsageExport utils", () => { + const mockSpendData: EntitySpendData = { + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + key_alias: "alias-1", + }, + }, + }, + }, + entity2: { + metrics: { + spend: 20.3, + api_requests: 200, + successful_requests: 190, + failed_requests: 10, + total_tokens: 2000, + prompt_tokens: 1200, + completion_tokens: 800, + cache_read_input_tokens: 100, + cache_creation_input_tokens: 60, + }, + api_key_breakdown: { + key2: { + metrics: { + spend: 20.3, + api_requests: 200, + successful_requests: 190, + failed_requests: 10, + total_tokens: 2000, + }, + metadata: { + team_id: "team-2", + key_alias: "alias-2", + }, + }, + }, + }, + }, + }, + }, + { + date: "2025-01-02", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 15.2, + api_requests: 150, + successful_requests: 145, + failed_requests: 5, + total_tokens: 1500, + prompt_tokens: 900, + completion_tokens: 600, + cache_read_input_tokens: 75, + cache_creation_input_tokens: 45, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 15.2, + api_requests: 150, + successful_requests: 145, + failed_requests: 5, + total_tokens: 1500, + }, + metadata: { + team_id: "team-1", + key_alias: "alias-1", + }, + }, + }, + }, + }, + }, + }, + ], + metadata: { + total_spend: 46.0, + total_api_requests: 450, + total_successful_requests: 430, + total_failed_requests: 20, + total_tokens: 4500, + }, + }; + + const mockTeamAliasMap: Record = { + "team-1": "Team One", + "team-2": "Team Two", + }; + + beforeEach(() => { + vi.clearAllMocks(); + }); + + afterEach(() => { + vi.restoreAllMocks(); + }); + + describe("getEntityBreakdown", () => { + it("should aggregate entity spend data across multiple days", () => { + const result = getEntityBreakdown(mockSpendData); + + expect(result).toHaveLength(2); + expect(result[0].metadata.id).toBe("team-1"); + expect(result[0].metrics.spend).toBe(25.7); + expect(result[1].metadata.id).toBe("team-2"); + expect(result[1].metrics.spend).toBe(20.3); + }); + + it("should sort entities by spend descending", () => { + const result = getEntityBreakdown(mockSpendData); + + expect(result[0].metrics.spend).toBeGreaterThan(result[1].metrics.spend); + }); + + it("should aggregate all metrics correctly", () => { + const result = getEntityBreakdown(mockSpendData); + const entity1 = result.find((e) => e.metadata.id === "team-1"); + + expect(entity1?.metrics.api_requests).toBe(250); + expect(entity1?.metrics.successful_requests).toBe(240); + expect(entity1?.metrics.failed_requests).toBe(10); + expect(entity1?.metrics.total_tokens).toBe(2500); + expect(entity1?.metrics.prompt_tokens).toBe(1500); + expect(entity1?.metrics.completion_tokens).toBe(1000); + expect(entity1?.metrics.cache_read_input_tokens).toBe(125); + expect(entity1?.metrics.cache_creation_input_tokens).toBe(75); + }); + + it("should use key alias when available", () => { + const result = getEntityBreakdown(mockSpendData); + const entity1 = result.find((e) => e.metadata.id === "team-1"); + + expect(entity1?.metadata.alias).toBe("alias-1"); + }); + + it("should use team alias map when key alias is not available", () => { + const spendDataWithoutAlias: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = getEntityBreakdown(spendDataWithoutAlias, mockTeamAliasMap); + const entity1 = result.find((e) => e.metadata.id === "team-1"); + + expect(entity1?.metadata.alias).toBe("Team One"); + }); + + it("should use entity id when team alias is not available", () => { + const spendDataWithoutTeamId: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: {}, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = getEntityBreakdown(spendDataWithoutTeamId); + const entity1 = result.find((e) => e.metadata.id === "entity1"); + + expect(entity1?.metadata.alias).toBe("entity1"); + }); + + it("should handle empty spend data", () => { + const emptySpendData: EntitySpendData = { + results: [], + metadata: { + total_spend: 0, + total_api_requests: 0, + total_successful_requests: 0, + total_failed_requests: 0, + total_tokens: 0, + }, + }; + + const result = getEntityBreakdown(emptySpendData); + + expect(result).toHaveLength(0); + }); + + it("should handle missing optional token fields", () => { + const spendDataWithMissingTokens: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = getEntityBreakdown(spendDataWithMissingTokens); + const entity1 = result.find((e) => e.metadata.id === "team-1"); + + expect(entity1?.metrics.prompt_tokens).toBe(0); + expect(entity1?.metrics.completion_tokens).toBe(0); + }); + }); + + describe("generateDailyData", () => { + it("should generate daily breakdown data with correct structure", () => { + const result = generateDailyData(mockSpendData, "Team", mockTeamAliasMap); + + expect(result).toHaveLength(3); + expect(result[0]).toHaveProperty("Date"); + expect(result[0]).toHaveProperty("Team"); + expect(result[0]).toHaveProperty("Team ID"); + expect(result[0]).toHaveProperty("Spend ($)"); + expect(result[0]).toHaveProperty("Requests"); + expect(result[0]).toHaveProperty("Successful Requests"); + expect(result[0]).toHaveProperty("Failed Requests"); + expect(result[0]).toHaveProperty("Total Tokens"); + expect(result[0]).toHaveProperty("Prompt Tokens"); + expect(result[0]).toHaveProperty("Completion Tokens"); + }); + + it("should sort data by date ascending", () => { + const result = generateDailyData(mockSpendData, "Team"); + + const dates = result.map((r) => new Date(r.Date).getTime()); + for (let i = 0; i < dates.length - 1; i++) { + expect(dates[i]).toBeLessThanOrEqual(dates[i + 1]); + } + }); + + it("should use team alias when available", () => { + const result = generateDailyData(mockSpendData, "Team", mockTeamAliasMap); + const team1Entry = result.find((r) => r["Team ID"] === "team-1"); + + expect(team1Entry?.["Team"]).toBe("Team One"); + }); + + it("should use dash when team alias is not available", () => { + const result = generateDailyData(mockSpendData, "Team"); + const entryWithoutTeamId = result.find((r) => !r["Team ID"] || r["Team ID"] === "-"); + + if (entryWithoutTeamId) { + expect(entryWithoutTeamId["Team"]).toBe("-"); + } + }); + + it("should use dash when team id is not available", () => { + const spendDataWithoutTeamId: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + }, + api_key_breakdown: {}, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = generateDailyData(spendDataWithoutTeamId, "Team"); + const entry = result[0]; + + expect(entry["Team ID"]).toBe("-"); + expect(entry["Team"]).toBe("-"); + }); + + it("should format spend values correctly", () => { + const result = generateDailyData(mockSpendData, "Team"); + + expect(result[0]["Spend ($)"]).toBeDefined(); + }); + + it("should handle missing optional token fields", () => { + const spendDataWithMissingTokens: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = generateDailyData(spendDataWithMissingTokens, "Team"); + + expect(result[0]["Prompt Tokens"]).toBe(0); + expect(result[0]["Completion Tokens"]).toBe(0); + }); + }); + + describe("generateDailyWithModelsData", () => { + const mockSpendDataWithModels: EntitySpendData = { + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 5.0, + api_requests: 50, + successful_requests: 48, + failed_requests: 2, + total_tokens: 500, + }, + metadata: { + team_id: "team-1", + }, + }, + key2: { + metrics: { + spend: 5.5, + api_requests: 50, + successful_requests: 47, + failed_requests: 3, + total_tokens: 500, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + models: { + "gpt-4": { + metrics: { + spend: 5.0, + api_requests: 50, + successful_requests: 48, + failed_requests: 2, + total_tokens: 500, + }, + }, + "gpt-3.5-turbo": { + metrics: { + spend: 5.5, + api_requests: 50, + successful_requests: 47, + failed_requests: 3, + total_tokens: 500, + }, + }, + }, + }, + }, + ], + metadata: { + total_spend: 10.5, + total_api_requests: 100, + total_successful_requests: 95, + total_failed_requests: 5, + total_tokens: 1000, + }, + }; + + it("should generate daily breakdown with model data", () => { + const result = generateDailyWithModelsData(mockSpendDataWithModels, "Team", mockTeamAliasMap); + + expect(result.length).toBeGreaterThan(0); + expect(result[0]).toHaveProperty("Date"); + expect(result[0]).toHaveProperty("Team"); + expect(result[0]).toHaveProperty("Team ID"); + expect(result[0]).toHaveProperty("Model"); + expect(result[0]).toHaveProperty("Spend ($)"); + expect(result[0]).toHaveProperty("Requests"); + expect(result[0]).toHaveProperty("Successful"); + expect(result[0]).toHaveProperty("Failed"); + expect(result[0]).toHaveProperty("Total Tokens"); + }); + + it("should sort data by date ascending", () => { + const multiDayData: EntitySpendData = { + results: [ + { + date: "2025-01-02", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + models: { + "gpt-4": { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + }, + }, + }, + }, + ...mockSpendDataWithModels.results, + ], + metadata: mockSpendDataWithModels.metadata, + }; + + const result = generateDailyWithModelsData(multiDayData, "Team"); + + expect(new Date(result[0].Date).getTime()).toBeLessThanOrEqual( + new Date(result[result.length - 1].Date).getTime(), + ); + }); + + it("should aggregate model metrics from api key breakdown", () => { + const result = generateDailyWithModelsData(mockSpendDataWithModels, "Team"); + + const gpt4Entry = result.find((r) => r.Model === "gpt-4"); + expect(gpt4Entry).toBeDefined(); + expect(gpt4Entry?.Requests).toBeGreaterThan(0); + }); + + it("should use team alias when available", () => { + const result = generateDailyWithModelsData(mockSpendDataWithModels, "Team", mockTeamAliasMap); + const team1Entry = result.find((r) => r["Team ID"] === "team-1"); + + expect(team1Entry?.["Team"]).toBe("Team One"); + }); + + it("should use dash when team alias is not available", () => { + const result = generateDailyWithModelsData(mockSpendDataWithModels, "Team"); + const entryWithoutTeamId = result.find((r) => !r["Team ID"] || r["Team ID"] === "-"); + + if (entryWithoutTeamId) { + expect(entryWithoutTeamId["Team"]).toBe("-"); + } + }); + + it("should handle empty models breakdown", () => { + const spendDataWithoutModels: EntitySpendData = { + ...mockSpendDataWithModels, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + models: {}, + }, + }, + ], + metadata: mockSpendDataWithModels.metadata, + }; + + const result = generateDailyWithModelsData(spendDataWithoutModels, "Team"); + + expect(result).toHaveLength(0); + }); + }); + + describe("generateExportData", () => { + it("should return daily data when scope is daily", () => { + const result = generateExportData(mockSpendData, "daily", "Team", mockTeamAliasMap); + + expect(result.length).toBeGreaterThan(0); + expect(result[0]).toHaveProperty("Date"); + expect(result[0]).not.toHaveProperty("Model"); + }); + + it("should return daily with models data when scope is daily_with_models", () => { + const mockDataWithModels: EntitySpendData = { + ...mockSpendData, + results: [ + { + date: "2025-01-01", + breakdown: { + entities: { + entity1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + prompt_tokens: 600, + completion_tokens: 400, + cache_read_input_tokens: 50, + cache_creation_input_tokens: 30, + }, + api_key_breakdown: { + key1: { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + metadata: { + team_id: "team-1", + }, + }, + }, + }, + }, + models: { + "gpt-4": { + metrics: { + spend: 10.5, + api_requests: 100, + successful_requests: 95, + failed_requests: 5, + total_tokens: 1000, + }, + }, + }, + }, + }, + ], + metadata: mockSpendData.metadata, + }; + + const result = generateExportData(mockDataWithModels, "daily_with_models", "Team", mockTeamAliasMap); + + expect(result.length).toBeGreaterThan(0); + expect(result[0]).toHaveProperty("Model"); + }); + + it("should default to daily data for unknown scope", () => { + const result = generateExportData(mockSpendData, "unknown" as ExportScope, "Team", mockTeamAliasMap); + + expect(result.length).toBeGreaterThan(0); + expect(result[0]).not.toHaveProperty("Model"); + }); + }); + + describe("generateMetadata", () => { + const mockDateRange: DateRangePickerValue = { + from: new Date("2025-01-01"), + to: new Date("2025-01-31"), + }; + + it("should generate metadata with correct structure", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result).toHaveProperty("export_date"); + expect(result).toHaveProperty("entity_type"); + expect(result).toHaveProperty("date_range"); + expect(result).toHaveProperty("filters_applied"); + expect(result).toHaveProperty("export_scope"); + expect(result).toHaveProperty("summary"); + }); + + it("should include export date as ISO string", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result.export_date).toMatch(/^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}/); + }); + + it("should include entity type", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result.entity_type).toBe("team"); + }); + + it("should format date range correctly", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result.date_range.from).toBe("2025-01-01T00:00:00.000Z"); + expect(result.date_range.to).toBe("2025-01-31T00:00:00.000Z"); + }); + + it("should handle missing date range values", () => { + const incompleteDateRange: DateRangePickerValue = { + from: undefined, + to: undefined, + }; + + const result = generateMetadata("team", incompleteDateRange, [], "daily", mockSpendData); + + expect(result.date_range.from).toBeUndefined(); + expect(result.date_range.to).toBeUndefined(); + }); + + it("should set filters_applied to None when empty", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result.filters_applied).toBe("None"); + }); + + it("should include filters when provided", () => { + const result = generateMetadata("team", mockDateRange, ["filter1", "filter2"], "daily", mockSpendData); + + expect(result.filters_applied).toEqual(["filter1", "filter2"]); + }); + + it("should include export scope", () => { + const result = generateMetadata("team", mockDateRange, [], "daily_with_models", mockSpendData); + + expect(result.export_scope).toBe("daily_with_models"); + }); + + it("should include summary metrics from spend data", () => { + const result = generateMetadata("team", mockDateRange, [], "daily", mockSpendData); + + expect(result.summary.total_spend).toBe(46.0); + expect(result.summary.total_requests).toBe(450); + expect(result.summary.successful_requests).toBe(430); + expect(result.summary.failed_requests).toBe(20); + expect(result.summary.total_tokens).toBe(4500); + }); + }); + + describe("handleExportCSV", () => { + beforeEach(() => { + document.body.innerHTML = ""; + window.URL.createObjectURL = vi.fn(() => "blob:mock-url"); + window.URL.revokeObjectURL = vi.fn(); + }); + + afterEach(() => { + vi.restoreAllMocks(); + }); + + it("should create CSV file and trigger download", () => { + const createObjectURLSpy = vi.spyOn(window.URL, "createObjectURL").mockReturnValue("blob:mock-url"); + const revokeObjectURLSpy = vi.spyOn(window.URL, "revokeObjectURL"); + const createElementSpy = vi.spyOn(document, "createElement"); + const appendChildSpy = vi.spyOn(document.body, "appendChild"); + const removeChildSpy = vi.spyOn(document.body, "removeChild"); + + handleExportCSV(mockSpendData, "daily", "Team", "team", mockTeamAliasMap); + + expect(Papa.unparse).toHaveBeenCalled(); + expect(createObjectURLSpy).toHaveBeenCalled(); + expect(createElementSpy).toHaveBeenCalledWith("a"); + expect(appendChildSpy).toHaveBeenCalled(); + expect(removeChildSpy).toHaveBeenCalled(); + }); + + it("should generate correct filename", () => { + const anchorElement = document.createElement("a"); + const createElementSpy = vi.spyOn(document, "createElement").mockReturnValue(anchorElement); + + const today = new Date().toISOString().split("T")[0]; + + handleExportCSV(mockSpendData, "daily", "Team", "team", mockTeamAliasMap); + + expect(anchorElement.download).toBe(`team_usage_daily_${today}.csv`); + }); + + it("should create blob with correct type", () => { + let blobType = ""; + const originalBlob = window.Blob; + + window.Blob = class extends Blob { + constructor(parts?: BlobPart[] | undefined, options?: BlobPropertyBag | undefined) { + super(parts, options); + if (options?.type) { + blobType = options.type; + } + } + } as any; + + handleExportCSV(mockSpendData, "daily", "Team", "team", mockTeamAliasMap); + + expect(blobType).toBe("text/csv;charset=utf-8;"); + + window.Blob = originalBlob; + }); + }); + + describe("handleExportJSON", () => { + beforeEach(() => { + document.body.innerHTML = ""; + window.URL.createObjectURL = vi.fn(() => "blob:mock-url"); + window.URL.revokeObjectURL = vi.fn(); + }); + + afterEach(() => { + vi.restoreAllMocks(); + }); + + it("should create JSON file and trigger download", () => { + const createObjectURLSpy = vi.spyOn(window.URL, "createObjectURL").mockReturnValue("blob:mock-url"); + const revokeObjectURLSpy = vi.spyOn(window.URL, "revokeObjectURL"); + const createElementSpy = vi.spyOn(document, "createElement"); + const appendChildSpy = vi.spyOn(document.body, "appendChild"); + const removeChildSpy = vi.spyOn(document.body, "removeChild"); + + const mockDateRange: DateRangePickerValue = { + from: new Date("2025-01-01"), + to: new Date("2025-01-31"), + }; + + handleExportJSON(mockSpendData, "daily", "Team", "team", mockDateRange, [], mockTeamAliasMap); + + expect(createObjectURLSpy).toHaveBeenCalled(); + expect(createElementSpy).toHaveBeenCalledWith("a"); + expect(appendChildSpy).toHaveBeenCalled(); + expect(removeChildSpy).toHaveBeenCalled(); + }); + + it("should generate correct filename", () => { + const anchorElement = document.createElement("a"); + const createElementSpy = vi.spyOn(document, "createElement").mockReturnValue(anchorElement); + + const today = new Date().toISOString().split("T")[0]; + const mockDateRange: DateRangePickerValue = { + from: new Date("2025-01-01"), + to: new Date("2025-01-31"), + }; + + handleExportJSON(mockSpendData, "daily", "Team", "team", mockDateRange, [], mockTeamAliasMap); + + expect(anchorElement.download).toBe(`team_usage_daily_${today}.json`); + }); + + it("should create blob with correct type", () => { + let blobType = ""; + const originalBlob = window.Blob; + + window.Blob = class extends Blob { + constructor(parts?: BlobPart[] | undefined, options?: BlobPropertyBag | undefined) { + super(parts, options); + if (options?.type) { + blobType = options.type; + } + } + } as any; + + const mockDateRange: DateRangePickerValue = { + from: new Date("2025-01-01"), + to: new Date("2025-01-31"), + }; + + handleExportJSON(mockSpendData, "daily", "Team", "team", mockDateRange, [], mockTeamAliasMap); + + expect(blobType).toBe("application/json"); + + window.Blob = originalBlob; + }); + + it("should include metadata and data in JSON export", () => { + let jsonString = ""; + const originalBlob = window.Blob; + + window.Blob = class extends Blob { + constructor(parts?: BlobPart[] | undefined, options?: BlobPropertyBag | undefined) { + super(parts, options); + if (parts && parts[0]) { + jsonString = parts[0] as string; + } + } + } as any; + + const mockDateRange: DateRangePickerValue = { + from: new Date("2025-01-01"), + to: new Date("2025-01-31"), + }; + + handleExportJSON(mockSpendData, "daily", "Team", "team", mockDateRange, ["filter1"], mockTeamAliasMap); + + const exportObject = JSON.parse(jsonString); + expect(exportObject).toHaveProperty("metadata"); + expect(exportObject).toHaveProperty("data"); + expect(exportObject.metadata.entity_type).toBe("team"); + expect(exportObject.metadata.filters_applied).toEqual(["filter1"]); + + window.Blob = originalBlob; + }); + }); +}); diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/utils.ts b/ui/litellm-dashboard/src/components/EntityUsageExport/utils.ts index c93155feb23..cdb5d011af4 100644 --- a/ui/litellm-dashboard/src/components/EntityUsageExport/utils.ts +++ b/ui/litellm-dashboard/src/components/EntityUsageExport/utils.ts @@ -1,13 +1,43 @@ import { formatNumberWithCommas } from "@/utils/dataUtils"; -import Papa from "papaparse"; -import type { EntitySpendData, EntityBreakdown, ExportMetadata, ExportScope, EntityType } from "./types"; import type { DateRangePickerValue } from "@tremor/react"; +import Papa from "papaparse"; +import type { EntityBreakdown, EntitySpendData, EntityType, ExportMetadata, ExportScope } from "./types"; -export const getEntityBreakdown = (spendData: EntitySpendData): EntityBreakdown[] => { +// Helper function to extract team_id from api_key_breakdown +const extractTeamIdFromApiKeyBreakdown = (apiKeyBreakdown: Record | undefined): string | null => { + if (!apiKeyBreakdown) return null; + + // Look through all API keys to find the first non-null team_id + for (const apiKeyData of Object.values(apiKeyBreakdown)) { + const teamId = (apiKeyData as any)?.metadata?.team_id; + if (teamId) { + return teamId; + } + } + return null; +}; + +export const getEntityBreakdown = ( + spendData: EntitySpendData, + teamAliasMap: Record = {}, +): EntityBreakdown[] => { const entitySpend: { [key: string]: EntityBreakdown } = {}; spendData.results.forEach((day) => { Object.entries(day.breakdown.entities || {}).forEach(([entity, data]: [string, any]) => { + // Extract team_id from api_key_breakdown metadata (not data.metadata which is empty) + const teamId = extractTeamIdFromApiKeyBreakdown(data.api_key_breakdown) || entity; + // Extract key_alias from the first API key that has one + const apiKeyBreakdown = data.api_key_breakdown || {}; + let keyAlias: string | null = null; + for (const apiKeyData of Object.values(apiKeyBreakdown)) { + const alias = (apiKeyData as any)?.metadata?.key_alias; + if (alias) { + keyAlias = alias; + break; + } + } + if (!entitySpend[entity]) { entitySpend[entity] = { metrics: { @@ -22,8 +52,8 @@ export const getEntityBreakdown = (spendData: EntitySpendData): EntityBreakdown[ cache_creation_input_tokens: 0, }, metadata: { - alias: data.metadata?.team_alias || entity, - id: entity, + alias: keyAlias || teamAliasMap[teamId] || entity, + id: teamId, }, }; } @@ -42,15 +72,23 @@ export const getEntityBreakdown = (spendData: EntitySpendData): EntityBreakdown[ return Object.values(entitySpend).sort((a, b) => b.metrics.spend - a.metrics.spend); }; -export const generateDailyData = (spendData: EntitySpendData, entityLabel: string): any[] => { +export const generateDailyData = ( + spendData: EntitySpendData, + entityLabel: string, + teamAliasMap: Record = {}, +): any[] => { const dailyBreakdown: any[] = []; spendData.results.forEach((day) => { Object.entries(day.breakdown.entities || {}).forEach(([entity, data]: [string, any]) => { + // Extract team_id from api_key_breakdown metadata (not data.metadata which is empty) + const teamId = extractTeamIdFromApiKeyBreakdown(data.api_key_breakdown); + const teamAlias = teamId ? teamAliasMap[teamId] || null : null; + dailyBreakdown.push({ Date: day.date, - [entityLabel]: data.metadata?.team_alias || entity, - [`${entityLabel} ID`]: entity, + [entityLabel]: teamAlias || "-", + [`${entityLabel} ID`]: teamId || "-", "Spend ($)": formatNumberWithCommas(data.metrics.spend, 4), Requests: data.metrics.api_requests, "Successful Requests": data.metrics.successful_requests, @@ -65,15 +103,17 @@ export const generateDailyData = (spendData: EntitySpendData, entityLabel: strin return dailyBreakdown.sort((a, b) => new Date(a.Date).getTime() - new Date(b.Date).getTime()); }; -export const generateDailyWithModelsData = (spendData: EntitySpendData, entityLabel: string): any[] => { +export const generateDailyWithModelsData = ( + spendData: EntitySpendData, + entityLabel: string, + teamAliasMap: Record = {}, +): any[] => { const dailyModelBreakdown: any[] = []; spendData.results.forEach((day) => { const dailyEntityModels: { [key: string]: { [key: string]: any } } = {}; Object.entries(day.breakdown.entities || {}).forEach(([entity, entityData]: [string, any]) => { - const entityName = entityData.metadata?.team_alias || entity; - if (!dailyEntityModels[entity]) { dailyEntityModels[entity] = {}; } @@ -102,13 +142,15 @@ export const generateDailyWithModelsData = (spendData: EntitySpendData, entityLa Object.entries(dailyEntityModels).forEach(([entity, models]) => { const entityData = day.breakdown.entities?.[entity]; - const entityName = entityData?.metadata?.team_alias || entity; + // Extract team_id from api_key_breakdown metadata (not entityData.metadata which is empty) + const teamId = extractTeamIdFromApiKeyBreakdown(entityData?.api_key_breakdown); + const teamAlias = teamId ? teamAliasMap[teamId] || null : null; Object.entries(models).forEach(([model, metrics]: [string, any]) => { dailyModelBreakdown.push({ Date: day.date, - [entityLabel]: entityName, - [`${entityLabel} ID`]: entity, + [entityLabel]: teamAlias || "-", + [`${entityLabel} ID`]: teamId || "-", Model: model, "Spend ($)": formatNumberWithCommas(metrics.spend, 4), Requests: metrics.requests, @@ -127,14 +169,15 @@ export const generateExportData = ( spendData: EntitySpendData, exportScope: ExportScope, entityLabel: string, + teamAliasMap: Record = {}, ): any[] => { switch (exportScope) { case "daily": - return generateDailyData(spendData, entityLabel); + return generateDailyData(spendData, entityLabel, teamAliasMap); case "daily_with_models": - return generateDailyWithModelsData(spendData, entityLabel); + return generateDailyWithModelsData(spendData, entityLabel, teamAliasMap); default: - return generateDailyData(spendData, entityLabel); + return generateDailyData(spendData, entityLabel, teamAliasMap); } }; @@ -167,8 +210,9 @@ export const handleExportCSV = ( exportScope: ExportScope, entityLabel: string, entityType: EntityType, + teamAliasMap: Record = {}, ): void => { - const data = generateExportData(spendData, exportScope, entityLabel); + const data = generateExportData(spendData, exportScope, entityLabel, teamAliasMap); const csv = Papa.unparse(data); const blob = new Blob([csv], { type: "text/csv;charset=utf-8;" }); const url = window.URL.createObjectURL(blob); @@ -189,8 +233,9 @@ export const handleExportJSON = ( entityType: EntityType, dateRange: DateRangePickerValue, selectedFilters: string[], + teamAliasMap: Record = {}, ): void => { - const data = generateExportData(spendData, exportScope, entityLabel); + const data = generateExportData(spendData, exportScope, entityLabel, teamAliasMap); const metadata = generateMetadata(entityType, dateRange, selectedFilters, exportScope, spendData); const exportObject = { metadata, diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.test.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.test.tsx index 46714857c1f..60674a7c332 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.test.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.test.tsx @@ -36,7 +36,11 @@ vi.mock("./TopModelView", () => ({ default: () =>
Top Models
, })); -vi.mock("./EntityUsageExport", () => ({ +vi.mock("../../../EntityUsageExport/EntityUsageExportModal", () => ({ + default: () =>
Entity Usage Export Modal
, +})); + +vi.mock("../../../EntityUsageExport", () => ({ UsageExportHeader: () =>
Usage Export Header
, })); diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.tsx index 52e75005ccc..abd21765ce0 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.tsx +++ b/ui/litellm-dashboard/src/components/UsagePage/components/EntityUsage/EntityUsage.tsx @@ -399,6 +399,7 @@ const EntityUsage: React.FC = ({ selectedFilters={selectedTags} onFiltersChange={setSelectedTags} filterOptions={getAllTags() || undefined} + teams={teams || []} /> From a1dd3ead4da7177549d34a353126a3a17cb6d3c5 Mon Sep 17 00:00:00 2001 From: Alexsander Hamir Date: Tue, 13 Jan 2026 15:22:09 -0800 Subject: [PATCH 46/46] [Perf] Remove bottleneck causing high CPU usage & overhead under heavy load (#19049) --- .gitignore | 1 + litellm/proxy/proxy_server.py | 9 +- litellm/utils.py | 98 +++++++++- .../test_get_model_info_performance.py | 179 ++++++++++++++++++ 4 files changed, 281 insertions(+), 6 deletions(-) create mode 100644 tests/litellm_utils_tests/test_get_model_info_performance.py diff --git a/.gitignore b/.gitignore index fafacd874a0..9d9e28dc466 100644 --- a/.gitignore +++ b/.gitignore @@ -59,6 +59,7 @@ litellm/proxy/_super_secret_config.yaml litellm/proxy/myenv/bin/activate litellm/proxy/myenv/bin/Activate.ps1 myenv/* +litellm/proxy/_experimental/out/_next/ litellm/proxy/_experimental/out/404/index.html litellm/proxy/_experimental/out/model_hub/index.html litellm/proxy/_experimental/out/onboarding/index.html diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 2e99a2f6824..1dfaf78cb5b 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -57,7 +57,10 @@ from litellm.types.utils import ( TextCompletionResponse, TokenCountResponse, ) -from litellm.utils import load_credentials_from_list +from litellm.utils import ( + _invalidate_model_cost_lowercase_map, + load_credentials_from_list, +) if TYPE_CHECKING: from aiohttp import ClientSession @@ -3822,6 +3825,8 @@ class ProxyConfig: model_cost_map_url = litellm.model_cost_map_url new_model_cost_map = get_model_cost_map(url=model_cost_map_url) litellm.model_cost = new_model_cost_map + # Invalidate case-insensitive lookup map since model_cost was replaced + _invalidate_model_cost_lowercase_map() # Update pod's in-memory last reload time last_model_cost_map_reload = current_time.isoformat() @@ -10074,6 +10079,8 @@ async def reload_model_cost_map( model_cost_map_url = litellm.model_cost_map_url new_model_cost_map = get_model_cost_map(url=model_cost_map_url) litellm.model_cost = new_model_cost_map + # Invalidate case-insensitive lookup map since model_cost was replaced + _invalidate_model_cost_lowercase_map() # Update pod's in-memory last reload time global last_model_cost_map_reload diff --git a/litellm/utils.py b/litellm/utils.py index 7c7591cdbab..6d4028d3ad8 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -2639,6 +2639,10 @@ def register_model(model_cost: Union[str, dict]): # noqa: PLR0915 ## override / add new keys to the existing model cost dictionary updated_dictionary = _update_dictionary(existing_model, value) litellm.model_cost.setdefault(model_cost_key, {}).update(updated_dictionary) + + # Invalidate case-insensitive lookup map since model_cost was modified + _invalidate_model_cost_lowercase_map() + verbose_logger.debug( f"added/updated model={model_cost_key} in litellm.model_cost: {model_cost_key}" ) @@ -4993,25 +4997,109 @@ def _strip_model_name(model: str, custom_llm_provider: Optional[str]) -> str: return model +# Global case-insensitive lookup map for model_cost (built eagerly at module import) +_model_cost_lowercase_map: Optional[Dict[str, str]] = None + + +def _invalidate_model_cost_lowercase_map() -> None: + """Invalidate the case-insensitive lookup map for model_cost. + + Call this whenever litellm.model_cost is modified to ensure the map is rebuilt. + """ + global _model_cost_lowercase_map + _model_cost_lowercase_map = None + + +def _rebuild_model_cost_lowercase_map() -> Dict[str, str]: + """Rebuild the case-insensitive lookup map from the current model_cost. + + Returns: + The rebuilt map (guaranteed to be not None). + """ + global _model_cost_lowercase_map + _model_cost_lowercase_map = {k.lower(): k for k in litellm.model_cost} + return _model_cost_lowercase_map + + +def _handle_stale_map_entry_rebuild( + potential_key_lower: str, +) -> Optional[str]: + """ + Handle stale _model_cost_lowercase_map entry (key was popped). + + Rebuilds the map and retries the lookup. + + Returns: + The matched key if found after rebuild, None otherwise. + """ + global _model_cost_lowercase_map + _model_cost_lowercase_map = _rebuild_model_cost_lowercase_map() + matched_key = _model_cost_lowercase_map.get(potential_key_lower) + if matched_key is not None and matched_key in litellm.model_cost: + return matched_key + return None + + +def _handle_new_key_with_scan( + potential_key_lower: str, +) -> Optional[str]: + """ + Handle new key added to model_cost without invalidating _model_cost_lowercase_map. + + Scans model_cost for case-insensitive match and rebuilds the map if found. + + Returns: + The matched key if found, None otherwise. + """ + global _model_cost_lowercase_map + for key in litellm.model_cost: + if key.lower() == potential_key_lower: + _model_cost_lowercase_map = _rebuild_model_cost_lowercase_map() + return key + return None + + def _get_model_cost_key(potential_key: str) -> Optional[str]: """ Get the actual key from model_cost, with case-insensitive fallback. Returns the key if found (exact match preferred, then case-insensitive), or None if not found. """ + global _model_cost_lowercase_map + # Try exact match first (most common case, O(1)) if potential_key in litellm.model_cost: return potential_key - # Fallback to case-insensitive match + # Fallback to case-insensitive match using O(1) lookup map + if _model_cost_lowercase_map is None: + _model_cost_lowercase_map = _rebuild_model_cost_lowercase_map() + potential_key_lower = potential_key.lower() - for key in litellm.model_cost: - if key.lower() == potential_key_lower: - return key - + matched_key = _model_cost_lowercase_map.get(potential_key_lower) + + # Verify the matched key still exists in model_cost (defense against stale cache) + # This handles cases where model_cost is modified directly (e.g., model_cost.pop()) + if matched_key is not None and matched_key in litellm.model_cost: + return matched_key + + # If matched_key exists in _model_cost_lowercase_map but not in model_cost, the map is stale (key was popped) + # Rebuild _model_cost_lowercase_map to remove stale entries and keep it in sync + if matched_key is not None: + matched_key = _handle_stale_map_entry_rebuild(potential_key_lower) + if matched_key is not None: + return matched_key + + # Fallback: if _model_cost_lowercase_map lookup failed, check if a new key was added without invalidating the map + # This handles cases where litellm.model_cost[key] = value was done directly + matched_key = _handle_new_key_with_scan(potential_key_lower) + if matched_key is not None: + return matched_key + return None + def _get_model_info_from_model_cost(key: str) -> dict: return litellm.model_cost[key] diff --git a/tests/litellm_utils_tests/test_get_model_info_performance.py b/tests/litellm_utils_tests/test_get_model_info_performance.py new file mode 100644 index 00000000000..0e7900dd4f4 --- /dev/null +++ b/tests/litellm_utils_tests/test_get_model_info_performance.py @@ -0,0 +1,179 @@ +""" +Performance test for litellm.get_model_info + +This test ensures that get_model_info performs within acceptable limits. +The function is called by Router.get_router_model_info and should not +contribute significant overhead. +""" + +import statistics +import time +from typing import Dict, List, Optional + +import pytest + +import litellm + +# Performance test constants +ITERATIONS = 100000 +WARMUP_ITERATIONS = 10 +# Threshold accounts for CI slowness (~1.3ms/call) vs local (~0.03ms/call) +# Still catches regressions: unoptimized was ~38-46s, CI optimized is ~133s +PERFORMANCE_THRESHOLD_MS = 200000 # 200 seconds - allows for CI variance while catching major regressions +MS_PER_SECOND = 1000 +P95_QUANTILE_N = 20 +P95_QUANTILE_INDEX = 18 + + +def benchmark_get_model_info( + model: str, + custom_llm_provider: Optional[str] = None, + iterations: int = ITERATIONS, + warmup: int = WARMUP_ITERATIONS, + silent: bool = True, +) -> Dict[str, float]: + """ + Benchmark get_model_info function + + Args: + model: Model name to pass to the function + custom_llm_provider: Optional custom LLM provider + iterations: Number of iterations to run + warmup: Number of warmup iterations + silent: Suppress error messages + + Returns: + Dictionary with timing statistics + """ + times: List[float] = [] + + # Warmup iterations + for _ in range(warmup): + try: + litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) + except Exception: + pass # Silently ignore errors during warmup + + # Actual benchmark iterations + for i in range(iterations): + start = time.perf_counter() + try: + litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) + end = time.perf_counter() + elapsed = (end - start) * MS_PER_SECOND # Convert to milliseconds + times.append(elapsed) + except Exception: + end = time.perf_counter() + elapsed = (end - start) * MS_PER_SECOND + times.append(elapsed) + if not silent: + print(f" Error on iteration {i}") + + if not times: + return {} + + return { + "mean": statistics.mean(times), + "median": statistics.median(times), + "min": min(times), + "max": max(times), + "p95": statistics.quantiles(times, n=P95_QUANTILE_N)[P95_QUANTILE_INDEX] if len(times) > 1 else times[0], + "total_time": sum(times), + "iterations": len(times), + } + + +def construct_model_info_name(model: str, custom_llm_provider: str) -> str: + """ + Simulate how Router.get_router_model_info constructs model_info_name + (matching router.py lines 6332-6335) + """ + if not model.startswith(f"{custom_llm_provider}/"): + model_info_name = f"{custom_llm_provider}/{model}" + else: + model_info_name = model + return model_info_name + + +@pytest.mark.parametrize( + "model,model_info_name", + [ + ("gpt-4", "openai/gpt-4"), # Basic model name (router would construct "openai/gpt-4") + ("openai/gpt-4", "openai/gpt-4"), # Model already with provider prefix + ("openai/*", "openai/*"), # Wildcard model + ], +) +def test_get_model_info_performance(model: str, model_info_name: str): + """ + Test that get_model_info completes 100k iterations within acceptable time. + + After the _get_model_cost_key optimization, performance improved significantly: + - Optimized (local): ~1.5-3 seconds for 100k iterations (~0.015-0.03 ms/call) + - Optimized (CI): ~133 seconds for 100k iterations (~1.3 ms/call) - CI is slower + - Previous (unoptimized): ~38-46 seconds for 100k iterations + + We set a threshold of 200 seconds (200000 ms) to: + - Allow for CI environment slowness (CI is typically 10-50x slower than local) + - Still catch significant performance regressions (e.g., if it degrades back to unoptimized or worse) + + This ensures the optimization remains effective and catches any future regressions. + """ + custom_llm_provider = "openai" + + # Use the model_info_name as constructed by the router + if model_info_name == "openai/*": + test_model = model_info_name + else: + test_model = construct_model_info_name(model, custom_llm_provider) + + # Run benchmark + results = benchmark_get_model_info(model=test_model, iterations=ITERATIONS, silent=True) + + # Assert total time is under the performance threshold + # Optimized results show ~1.5-3 seconds, so threshold allows for variance + # while catching significant regressions (like the old 38-46 second performance) + assert results["total_time"] < PERFORMANCE_THRESHOLD_MS, ( + f"get_model_info took {results['total_time']:.2f} ms for {ITERATIONS} iterations, " + f"exceeding {PERFORMANCE_THRESHOLD_MS / MS_PER_SECOND} second threshold. " + f"Mean: {results['mean']:.4f} ms, P95: {results['p95']:.4f} ms. " + f"Expected: ~1.5-3 seconds (optimized), Previous: ~38-46 seconds (unoptimized)" + ) + + +def test_get_model_info_performance_summary(): + """ + Run a comprehensive performance test and print summary statistics. + This test always passes but provides detailed performance metrics. + """ + custom_llm_provider = "openai" + + test_cases = [ + ("gpt-4", "openai/gpt-4"), + ("openai/gpt-4", "openai/gpt-4"), + ("openai/*", "openai/*"), + ] + + all_results = [] + + for model, model_info_name in test_cases: + if model_info_name == "openai/*": + test_model = model_info_name + else: + test_model = construct_model_info_name(model, custom_llm_provider) + + results = benchmark_get_model_info(model=test_model, iterations=ITERATIONS, silent=True) + all_results.append((model_info_name, results)) + + # Print summary (for debugging/CI logs) + print("\n" + "=" * 70) + print("get_model_info Performance Summary") + print("=" * 70) + for model_info_name, results in all_results: + print(f"\n{model_info_name}:") + print(f" Mean: {results['mean']:.4f} ms | Median: {results['median']:.4f} ms | P95: {results['p95']:.4f} ms") + print(f" Total: {results['total_time']:.2f} ms ({results['iterations']} iterations)") + print(f" Throughput: {MS_PER_SECOND / results['mean']:.0f} calls/sec") + print("=" * 70 + "\n") + + # Test passes - this is just for reporting + assert True