From 935c249c4582934d84db443024468fa202a9e7a1 Mon Sep 17 00:00:00 2001 From: Ephrim Stanley Date: Mon, 12 Jan 2026 09:53:54 -0500 Subject: [PATCH] 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, - "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 deleted file mode 100644 index ecb462983cc..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/pyproject.toml +++ /dev/null @@ -1,20 +0,0 @@ -[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 deleted file mode 100644 index 9f00d16db95..00000000000 --- a/tests/batches_tests/local-litellm/mock-server/uv.lock +++ /dev/null @@ -1,416 +0,0 @@ -version = 1 -revision = 1 -requires-python = ">=3.11" - 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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): +