mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-10 03:28:53 +00:00
Add end to end integration tests for batches
This commit is contained in:
Ephrim Stanley
parent
fa14a9931f
commit
b84aafbab6
21 changed files with 3041 additions and 4 deletions
365
BATCH_FIXES_README.md
Normal file
365
BATCH_FIXES_README.md
Normal file
|
|
@ -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"
|
||||
```
|
||||
|
||||
---
|
||||
|
|
@ -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")
|
||||
|
||||
|
|
|
|||
|
|
@ -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]
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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(
|
||||
|
|
|
|||
15
tests/batches_tests/local-litellm/README.md
Normal file
15
tests/batches_tests/local-litellm/README.md
Normal file
|
|
@ -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
|
||||
```
|
||||
38
tests/batches_tests/local-litellm/docker-compose.dev.yml
Normal file
38
tests/batches_tests/local-litellm/docker-compose.dev.yml
Normal file
|
|
@ -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:
|
||||
|
||||
109
tests/batches_tests/local-litellm/docker-compose.yml
Normal file
109
tests/batches_tests/local-litellm/docker-compose.yml
Normal file
|
|
@ -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
|
||||
57
tests/batches_tests/local-litellm/litellm-config.yaml
Normal file
57
tests/batches_tests/local-litellm/litellm-config.yaml
Normal file
|
|
@ -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
|
||||
18
tests/batches_tests/local-litellm/mock-server/Dockerfile
Normal file
18
tests/batches_tests/local-litellm/mock-server/Dockerfile
Normal file
|
|
@ -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"]
|
||||
47
tests/batches_tests/local-litellm/mock-server/main.py
Normal file
47
tests/batches_tests/local-litellm/mock-server/main.py
Normal file
|
|
@ -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)
|
||||
|
|
@ -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 <token> 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()},
|
||||
}
|
||||
124
tests/batches_tests/local-litellm/mock-server/mock_chat.py
Normal file
124
tests/batches_tests/local-litellm/mock-server/mock_chat.py
Normal file
|
|
@ -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
|
||||
|
|
@ -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},
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
|
@ -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,
|
||||
}
|
||||
|
||||
|
||||
|
||||
20
tests/batches_tests/local-litellm/mock-server/pyproject.toml
Normal file
20
tests/batches_tests/local-litellm/mock-server/pyproject.toml
Normal file
|
|
@ -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 = ["."]
|
||||
416
tests/batches_tests/local-litellm/mock-server/uv.lock
generated
Normal file
416
tests/batches_tests/local-litellm/mock-server/uv.lock
generated
Normal file
|
|
@ -0,0 +1,416 @@
|
|||
version = 1
|
||||
revision = 1
|
||||
requires-python = ">=3.11"
|
||||
|
||||
[[package]]
|
||||
name = "annotated-doc"
|
||||
version = "0.0.4"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/57/ba/046ceea27344560984e26a590f90bc7f4a75b06701f653222458922b558c/annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1e/d3/26bf1008eb3d2daa8ef4cacc7f3bfdc11818d111f7e2d0201bc6e3b49d45/annotated_doc-0.0.4-py3-none-any.whl", hash = "sha256:571ac1dc6991c450b25a9c2d84a3705e2ae7a53467b5d111c24fa8baabbed320" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.7.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.12.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "idna" },
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/16/ce/8a777047513153587e5434fd752e89334ac33e379aa3497db860eeb60377/anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/7f/9c/36c5c37947ebfb8c7f22e0eb6e4d188ee2d53aa3880f3f2744fb894f0cb1/anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "click"
|
||||
version = "8.3.1"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/3d/fa/656b739db8587d7b5dfa22e22ed02566950fbfbcdc20311993483657a5c0/click-8.3.1.tar.gz", hash = "sha256:12ff4785d337a1bb490bb7e9c2b1ee5da3112e94a8622f26a6c77f5d2fc6842a" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/98/78/01c019cdb5d6498122777c1a43056ebb3ebfeef2076d9d026bfe15583b2b/click-8.3.1-py3-none-any.whl", hash = "sha256:981153a64e25f12d547d3426c367a4857371575ee7ad18df2a6183ab0545b2a6" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
version = "0.4.6"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "deprecated"
|
||||
version = "1.3.1"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "wrapt" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/49/85/12f0a49a7c4ffb70572b6c2ef13c90c88fd190debda93b23f026b25f9634/deprecated-1.3.1.tar.gz", hash = "sha256:b1b50e0ff0c1fddaa5708a2c6b0a6588bb09b892825ab2b214ac9ea9d92a5223" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/84/d0/205d54408c08b13550c733c4b85429e7ead111c7f0014309637425520a9a/deprecated-1.3.1-py2.py3-none-any.whl", hash = "sha256:597bfef186b6f60181535a29fbe44865ce137a5079f295b479886c82729d5f3f" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "fastapi"
|
||||
version = "0.125.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "annotated-doc" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "starlette" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/17/71/2df15009fb4bdd522a069d2fbca6007c6c5487fce5cb965be00fc335f1d1/fastapi-0.125.0.tar.gz", hash = "sha256:16b532691a33e2c5dee1dac32feb31dc6eb41a3dd4ff29a95f9487cb21c054c0" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/34/2f/ff2fcc98f500713368d8b650e1bbc4a0b3ebcdd3e050dcdaad5f5a13fd7e/fastapi-0.125.0-py3-none-any.whl", hash = "sha256:2570ec4f3aecf5cca8f0428aed2398b774fcdfee6c2116f86e80513f2f86a7a1" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "h11"
|
||||
version = "0.16.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "idna"
|
||||
version = "3.11"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "limits"
|
||||
version = "5.6.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "deprecated" },
|
||||
{ name = "packaging" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/bb/e5/c968d43a65128cd54fb685f257aafb90cd5e4e1c67d084a58f0e4cbed557/limits-5.6.0.tar.gz", hash = "sha256:807fac75755e73912e894fdd61e2838de574c5721876a19f7ab454ae1fffb4b5" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/40/96/4fcd44aed47b8fcc457653b12915fcad192cd646510ef3f29fd216f4b0ab/limits-5.6.0-py3-none-any.whl", hash = "sha256:b585c2104274528536a5b68864ec3835602b3c4a802cd6aa0b07419798394021" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "mock-server"
|
||||
version = "0.1.0"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "fastapi" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "python-dotenv" },
|
||||
{ name = "python-multipart" },
|
||||
{ name = "slowapi" },
|
||||
{ name = "uvicorn" },
|
||||
]
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "fastapi" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "python-dotenv", specifier = ">=0.2.0" },
|
||||
{ name = "python-multipart" },
|
||||
{ name = "slowapi" },
|
||||
{ name = "uvicorn" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "packaging"
|
||||
version = "25.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a1/d4/1fc4078c65507b51b96ca8f8c3ba19e6a61c8253c72794544580a7b6c24d/packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "2.12.5"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "annotated-types" },
|
||||
{ name = "pydantic-core" },
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "typing-inspection" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/69/44/36f1a6e523abc58ae5f928898e4aca2e0ea509b5aa6f6f392a5d882be928/pydantic-2.12.5.tar.gz", hash = "sha256:4d351024c75c0f085a9febbb665ce8c0c6ec5d30e903bdb6394b7ede26aebb49" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5a/87/b70ad306ebb6f9b585f114d0ac2137d792b48be34d732d60e597c2f8465a/pydantic-2.12.5-py3-none-any.whl", hash = "sha256:e561593fccf61e8a20fc46dfc2dfe075b8be7d0188df33f221ad1f0139180f9d" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pydantic-core"
|
||||
version = "2.41.5"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/71/70/23b021c950c2addd24ec408e9ab05d59b035b39d97cdc1130e1bce647bb6/pydantic_core-2.41.5.tar.gz", hash = "sha256:08daa51ea16ad373ffd5e7606252cc32f07bc72b28284b6bc9c6df804816476e" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e8/72/74a989dd9f2084b3d9530b0915fdda64ac48831c30dbf7c72a41a5232db8/pydantic_core-2.41.5-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:a3a52f6156e73e7ccb0f8cced536adccb7042be67cb45f9562e12b319c119da6" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/12/44/37e403fd9455708b3b942949e1d7febc02167662bf1a7da5b78ee1ea2842/pydantic_core-2.41.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7f3bf998340c6d4b0c9a2f02d6a400e51f123b59565d74dc60d252ce888c260b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/33/7f/1d5cab3ccf44c1935a359d51a8a2a9e1a654b744b5e7f80d41b88d501eec/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:378bec5c66998815d224c9ca994f1e14c0c21cb95d2f52b6021cc0b2a58f2a5a" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/6e/6a/30d94a9674a7fe4f4744052ed6c5e083424510be1e93da5bc47569d11810/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e7b576130c69225432866fe2f4a469a85a54ade141d96fd396dffcf607b558f8" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/50/be/76e5d46203fcb2750e542f32e6c371ffa9b8ad17364cf94bb0818dbfb50c/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6cb58b9c66f7e4179a2d5e0f849c48eff5c1fca560994d6eb6543abf955a149e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d3/ee/fed784df0144793489f87db310a6bbf8118d7b630ed07aa180d6067e653a/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:88942d3a3dff3afc8288c21e565e476fc278902ae4d6d134f1eeda118cc830b1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/c8/be/8fed28dd0a180dca19e72c233cbf58efa36df055e5b9d90d64fd1740b828/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f31d95a179f8d64d90f6831d71fa93290893a33148d890ba15de25642c5d075b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/b0/3b/698cf8ae1d536a010e05121b4958b1257f0b5522085e335360e53a6b1c8b/pydantic_core-2.41.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c1df3d34aced70add6f867a8cf413e299177e0c22660cc767218373d0779487b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/b8/ba/15d537423939553116dea94ce02f9c31be0fa9d0b806d427e0308ec17145/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4009935984bd36bd2c774e13f9a09563ce8de4abaa7226f5108262fa3e637284" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/58/7f/0de669bf37d206723795f9c90c82966726a2ab06c336deba4735b55af431/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:34a64bc3441dc1213096a20fe27e8e128bd3ff89921706e83c0b1ac971276594" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e5/de/e7482c435b83d7e3c3ee5ee4451f6e8973cff0eb6007d2872ce6383f6398/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c9e19dd6e28fdcaa5a1de679aec4141f691023916427ef9bae8584f9c2fb3b0e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/fe/e6/8c9e81bb6dd7560e33b9053351c29f30c8194b72f2d6932888581f503482/pydantic_core-2.41.5-cp311-cp311-win32.whl", hash = "sha256:2c010c6ded393148374c0f6f0bf89d206bf3217f201faa0635dcd56bd1520f6b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/11/66/f14d1d978ea94d1bc21fc98fcf570f9542fe55bfcc40269d4e1a21c19bf7/pydantic_core-2.41.5-cp311-cp311-win_amd64.whl", hash = "sha256:76ee27c6e9c7f16f47db7a94157112a2f3a00e958bc626e2f4ee8bec5c328fbe" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/56/d8/0e271434e8efd03186c5386671328154ee349ff0354d83c74f5caaf096ed/pydantic_core-2.41.5-cp311-cp311-win_arm64.whl", hash = "sha256:4bc36bbc0b7584de96561184ad7f012478987882ebf9f9c389b23f432ea3d90f" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5f/5d/5f6c63eebb5afee93bcaae4ce9a898f3373ca23df3ccaef086d0233a35a7/pydantic_core-2.41.5-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f41a7489d32336dbf2199c8c0a215390a751c5b014c2c1c5366e817202e9cdf7" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/aa/32/9c2e8ccb57c01111e0fd091f236c7b371c1bccea0fa85247ac55b1e2b6b6/pydantic_core-2.41.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:070259a8818988b9a84a449a2a7337c7f430a22acc0859c6b110aa7212a6d9c0" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/68/b8/a01b53cb0e59139fbc9e4fda3e9724ede8de279097179be4ff31f1abb65a/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e96cea19e34778f8d59fe40775a7a574d95816eb150850a85a7a4c8f4b94ac69" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/38/de/8c36b5198a29bdaade07b5985e80a233a5ac27137846f3bc2d3b40a47360/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed2e99c456e3fadd05c991f8f437ef902e00eedf34320ba2b0842bd1c3ca3a75" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/00/b5/0e8e4b5b081eac6cb3dbb7e60a65907549a1ce035a724368c330112adfdd/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:65840751b72fbfd82c3c640cff9284545342a4f1eb1586ad0636955b261b0b05" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/77/56/87a61aad59c7c5b9dc8caad5a41a5545cba3810c3e828708b3d7404f6cef/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e536c98a7626a98feb2d3eaf75944ef6f3dbee447e1f841eae16f2f0a72d8ddc" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0d/76/941cc9f73529988688a665a5c0ecff1112b3d95ab48f81db5f7606f522d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eceb81a8d74f9267ef4081e246ffd6d129da5d87e37a77c9bde550cb04870c1c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d3/43/ebef01f69baa07a482844faaa0a591bad1ef129253ffd0cdaa9d8a7f72d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d38548150c39b74aeeb0ce8ee1d8e82696f4a4e16ddc6de7b1d8823f7de4b9b5" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/b1/87/41f3202e4193e3bacfc2c065fab7706ebe81af46a83d3e27605029c1f5a6/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:c23e27686783f60290e36827f9c626e63154b82b116d7fe9adba1fda36da706c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/49/7d/4c00df99cb12070b6bccdef4a195255e6020a550d572768d92cc54dba91a/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:482c982f814460eabe1d3bb0adfdc583387bd4691ef00b90575ca0d2b6fe2294" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cc/6a/ebf4b1d65d458f3cda6a7335d141305dfa19bdc61140a884d165a8a1bbc7/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:bfea2a5f0b4d8d43adf9d7b8bf019fb46fdd10a2e5cde477fbcb9d1fa08c68e1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/49/3b/774f2b5cd4192d5ab75870ce4381fd89cf218af999515baf07e7206753f0/pydantic_core-2.41.5-cp312-cp312-win32.whl", hash = "sha256:b74557b16e390ec12dca509bce9264c3bbd128f8a2c376eaa68003d7f327276d" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/86/45/00173a033c801cacf67c190fef088789394feaf88a98a7035b0e40d53dc9/pydantic_core-2.41.5-cp312-cp312-win_amd64.whl", hash = "sha256:1962293292865bca8e54702b08a4f26da73adc83dd1fcf26fbc875b35d81c815" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f9/22/91fbc821fa6d261b376a3f73809f907cec5ca6025642c463d3488aad22fb/pydantic_core-2.41.5-cp312-cp312-win_arm64.whl", hash = "sha256:1746d4a3d9a794cacae06a5eaaccb4b8643a131d45fbc9af23e353dc0a5ba5c3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/87/06/8806241ff1f70d9939f9af039c6c35f2360cf16e93c2ca76f184e76b1564/pydantic_core-2.41.5-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:941103c9be18ac8daf7b7adca8228f8ed6bb7a1849020f643b3a14d15b1924d9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/94/02/abfa0e0bda67faa65fef1c84971c7e45928e108fe24333c81f3bfe35d5f5/pydantic_core-2.41.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:112e305c3314f40c93998e567879e887a3160bb8689ef3d2c04b6cc62c33ac34" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/15/df/a4c740c0943e93e6500f9eb23f4ca7ec9bf71b19e608ae5b579678c8d02f/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cbaad15cb0c90aa221d43c00e77bb33c93e8d36e0bf74760cd00e732d10a6a0" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/9a/e3/6324802931ae1d123528988e0e86587c2072ac2e5394b4bc2bc34b61ff6e/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:03ca43e12fab6023fc79d28ca6b39b05f794ad08ec2feccc59a339b02f2b3d33" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/c9/d4/2230d7151d4957dd79c3044ea26346c148c98fbf0ee6ebd41056f2d62ab5/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc799088c08fa04e43144b164feb0c13f9a0bc40503f8df3e9fde58a3c0c101e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e6/9f/eaac5df17a3672fef0081b6c1bb0b82b33ee89aa5cec0d7b05f52fd4a1fa/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97aeba56665b4c3235a0e52b2c2f5ae9cd071b8a8310ad27bddb3f7fb30e9aa2" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cf/4e/35a80cae583a37cf15604b44240e45c05e04e86f9cfd766623149297e971/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:406bf18d345822d6c21366031003612b9c77b3e29ffdb0f612367352aab7d586" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/bf/e3/f6e262673c6140dd3305d144d032f7bd5f7497d3871c1428521f19f9efa2/pydantic_core-2.41.5-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b93590ae81f7010dbe380cdeab6f515902ebcbefe0b9327cc4804d74e93ae69d" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/75/c7/20bd7fc05f0c6ea2056a4565c6f36f8968c0924f19b7d97bbfea55780e73/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:01a3d0ab748ee531f4ea6c3e48ad9dac84ddba4b0d82291f87248f2f9de8d740" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/3a/8d/34318ef985c45196e004bc46c6eab2eda437e744c124ef0dbe1ff2c9d06b/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:6561e94ba9dacc9c61bce40e2d6bdc3bfaa0259d3ff36ace3b1e6901936d2e3e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/9c/59/013626bf8c78a5a5d9350d12e7697d3d4de951a75565496abd40ccd46bee/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:915c3d10f81bec3a74fbd4faebe8391013ba61e5a1a8d48c4455b923bdda7858" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1a/d9/c248c103856f807ef70c18a4f986693a46a8ffe1602e5d361485da502d20/pydantic_core-2.41.5-cp313-cp313-win32.whl", hash = "sha256:650ae77860b45cfa6e2cdafc42618ceafab3a2d9a3811fcfbd3bbf8ac3c40d36" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/9e/8b/341991b158ddab181cff136acd2552c9f35bd30380422a639c0671e99a91/pydantic_core-2.41.5-cp313-cp313-win_amd64.whl", hash = "sha256:79ec52ec461e99e13791ec6508c722742ad745571f234ea6255bed38c6480f11" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/73/7d/f2f9db34af103bea3e09735bb40b021788a5e834c81eedb541991badf8f5/pydantic_core-2.41.5-cp313-cp313-win_arm64.whl", hash = "sha256:3f84d5c1b4ab906093bdc1ff10484838aca54ef08de4afa9de0f5f14d69639cd" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ea/28/46b7c5c9635ae96ea0fbb779e271a38129df2550f763937659ee6c5dbc65/pydantic_core-2.41.5-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:3f37a19d7ebcdd20b96485056ba9e8b304e27d9904d233d7b1015db320e51f0a" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/74/1a/145646e5687e8d9a1e8d09acb278c8535ebe9e972e1f162ed338a622f193/pydantic_core-2.41.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1d1d9764366c73f996edd17abb6d9d7649a7eb690006ab6adbda117717099b14" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/23/04/e89c29e267b8060b40dca97bfc64a19b2a3cf99018167ea1677d96368273/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e1c2af0fce638d5f1988b686f3b3ea8cd7de5f244ca147c777769e798a9cd1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/84/a3/15a82ac7bd97992a82257f777b3583d3e84bdb06ba6858f745daa2ec8a85/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:506d766a8727beef16b7adaeb8ee6217c64fc813646b424d0804d67c16eddb66" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/74/9b/0046701313c6ef08c0c1cf0e028c67c770a4e1275ca73131563c5f2a310a/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4819fa52133c9aa3c387b3328f25c1facc356491e6135b459f1de698ff64d869" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/8a/cd/6bac76ecd1b27e75a95ca3a9a559c643b3afcd2dd62086d4b7a32a18b169/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b761d210c9ea91feda40d25b4efe82a1707da2ef62901466a42492c028553a2" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/4c/d2/ef2074dc020dd6e109611a8be4449b98cd25e1b9b8a303c2f0fca2f2bcf7/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22f0fb8c1c583a3b6f24df2470833b40207e907b90c928cc8d3594b76f874375" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/18/66/e9db17a9a763d72f03de903883c057b2592c09509ccfe468187f2a2eef29/pydantic_core-2.41.5-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2782c870e99878c634505236d81e5443092fba820f0373997ff75f90f68cd553" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d3/9e/3ce66cebb929f3ced22be85d4c2399b8e85b622db77dad36b73c5387f8f8/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:0177272f88ab8312479336e1d777f6b124537d47f2123f89cb37e0accea97f90" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a6/62/205a998f4327d2079326b01abee48e502ea739d174f0a89295c481a2272e/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:63510af5e38f8955b8ee5687740d6ebf7c2a0886d15a6d65c32814613681bc07" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/3c/0d/f05e79471e889d74d3d88f5bd20d0ed189ad94c2423d81ff8d0000aab4ff/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:e56ba91f47764cc14f1daacd723e3e82d1a89d783f0f5afe9c364b8bb491ccdb" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ec/e1/e08a6208bb100da7e0c4b288eed624a703f4d129bde2da475721a80cab32/pydantic_core-2.41.5-cp314-cp314-win32.whl", hash = "sha256:aec5cf2fd867b4ff45b9959f8b20ea3993fc93e63c7363fe6851424c8a7e7c23" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/48/5d/56ba7b24e9557f99c9237e29f5c09913c81eeb2f3217e40e922353668092/pydantic_core-2.41.5-cp314-cp314-win_amd64.whl", hash = "sha256:8e7c86f27c585ef37c35e56a96363ab8de4e549a95512445b85c96d3e2f7c1bf" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/4e/bb/f7a190991ec9e3e0ba22e4993d8755bbc4a32925c0b5b42775c03e8148f9/pydantic_core-2.41.5-cp314-cp314-win_arm64.whl", hash = "sha256:e672ba74fbc2dc8eea59fb6d4aed6845e6905fc2a8afe93175d94a83ba2a01a0" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/92/ed/77542d0c51538e32e15afe7899d79efce4b81eee631d99850edc2f5e9349/pydantic_core-2.41.5-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:8566def80554c3faa0e65ac30ab0932b9e3a5cd7f8323764303d468e5c37595a" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/bb/3d/6913dde84d5be21e284439676168b28d8bbba5600d838b9dca99de0fad71/pydantic_core-2.41.5-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:b80aa5095cd3109962a298ce14110ae16b8c1aece8b72f9dafe81cf597ad80b3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5a/f0/e5e6b99d4191da102f2b0eb9687aaa7f5bea5d9964071a84effc3e40f997/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3006c3dd9ba34b0c094c544c6006cc79e87d8612999f1a5d43b769b89181f23c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/71/48/36fb760642d568925953bcc8116455513d6e34c4beaa37544118c36aba6d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:72f6c8b11857a856bcfa48c86f5368439f74453563f951e473514579d44aa612" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/20/25/92dc684dd8eb75a234bc1c764b4210cf2646479d54b47bf46061657292a8/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5cb1b2f9742240e4bb26b652a5aeb840aa4b417c7748b6f8387927bc6e45e40d" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e2/09/f53e0b05023d3e30357d82eb35835d0f6340ca344720a4599cd663dca599/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd3d54f38609ff308209bd43acea66061494157703364ae40c951f83ba99a1a9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/aa/4e/2ae1aa85d6af35a39b236b1b1641de73f5a6ac4d5a7509f77b814885760c/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ff4321e56e879ee8d2a879501c8e469414d948f4aba74a2d4593184eb326660" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cd/13/2e215f17f0ef326fc72afe94776edb77525142c693767fc347ed6288728d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d0d2568a8c11bf8225044aa94409e21da0cb09dcdafe9ecd10250b2baad531a9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/02/7a/f999a6dcbcd0e5660bc348a3991c8915ce6599f4f2c6ac22f01d7a10816c/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:a39455728aabd58ceabb03c90e12f71fd30fa69615760a075b9fec596456ccc3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/3a/b1/6c990ac65e3b4c079a4fb9f5b05f5b013afa0f4ed6780a3dd236d2cbdc64/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_armv7l.whl", hash = "sha256:239edca560d05757817c13dc17c50766136d21f7cd0fac50295499ae24f90fdf" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d9/02/3c562f3a51afd4d88fff8dffb1771b30cfdfd79befd9883ee094f5b6c0d8/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:2a5e06546e19f24c6a96a129142a75cee553cc018ffee48a460059b1185f4470" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5c/96/5fb7d8c3c17bc8c62fdb031c47d77a1af698f1d7a406b0f79aaa1338f9ad/pydantic_core-2.41.5-cp314-cp314t-win32.whl", hash = "sha256:b4ececa40ac28afa90871c2cc2b9ffd2ff0bf749380fbdf57d165fd23da353aa" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/22/ed/182129d83032702912c2e2d8bbe33c036f342cc735737064668585dac28f/pydantic_core-2.41.5-cp314-cp314t-win_amd64.whl", hash = "sha256:80aa89cad80b32a912a65332f64a4450ed00966111b6615ca6816153d3585a8c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/9f/ed/068e41660b832bb0b1aa5b58011dea2a3fe0ba7861ff38c4d4904c1c1a99/pydantic_core-2.41.5-cp314-cp314t-win_arm64.whl", hash = "sha256:35b44f37a3199f771c3eaa53051bc8a70cd7b54f333531c59e29fd4db5d15008" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/11/72/90fda5ee3b97e51c494938a4a44c3a35a9c96c19bba12372fb9c634d6f57/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b96d5f26b05d03cc60f11a7761a5ded1741da411e7fe0909e27a5e6a0cb7b034" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1f/53/8942f884fa33f50794f119012dc6a1a02ac43a56407adaac20463df8e98f/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:634e8609e89ceecea15e2d61bc9ac3718caaaa71963717bf3c8f38bfde64242c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/79/c8/ecb9ed9cd942bce09fc888ee960b52654fbdbede4ba6c2d6e0d3b1d8b49c/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:93e8740d7503eb008aa2df04d3b9735f845d43ae845e6dcd2be0b55a2da43cd2" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/2e/1b/687711069de7efa6af934e74f601e2a4307365e8fdc404703afc453eab26/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f15489ba13d61f670dcc96772e733aad1a6f9c429cc27574c6cdaed82d0146ad" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/09/32/59b0c7e63e277fa7911c2fc70ccfb45ce4b98991e7ef37110663437005af/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:7da7087d756b19037bc2c06edc6c170eeef3c3bafcb8f532ff17d64dc427adfd" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/aa/81/05e400037eaf55ad400bcd318c05bb345b57e708887f07ddb2d20e3f0e98/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:aabf5777b5c8ca26f7824cb4a120a740c9588ed58df9b2d196ce92fba42ff8dc" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/6e/0d/e3549b2399f71d56476b77dbf3cf8937cec5cd70536bdc0e374a421d0599/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c007fe8a43d43b3969e8469004e9845944f1a80e6acd47c150856bb87f230c56" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f7/07/34573da085946b6a313d7c42f82f16e8920bfd730665de2d11c0c37a74b5/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:76d0819de158cd855d1cbb8fcafdf6f5cf1eb8e470abe056d5d161106e38062b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5f/9b/1b3f0e9f9305839d7e84912f9e8bfbd191ed1b1ef48083609f0dabde978c/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:b2379fa7ed44ddecb5bfe4e48577d752db9fc10be00a6b7446e9663ba143de26" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a4/ed/d71fefcb4263df0da6a85b5d8a7508360f2f2e9b3bf5814be9c8bccdccc1/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:266fb4cbf5e3cbd0b53669a6d1b039c45e3ce651fd5442eff4d07c2cc8d66808" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ce/3a/626b38db460d675f873e4444b4bb030453bbe7b4ba55df821d026a0493c4/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58133647260ea01e4d0500089a8c4f07bd7aa6ce109682b1426394988d8aaacc" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/83/d9/8412d7f06f616bbc053d30cb4e5f76786af3221462ad5eee1f202021eb4e/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:287dad91cfb551c363dc62899a80e9e14da1f0e2b6ebde82c806612ca2a13ef1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/55/4c/162d906b8e3ba3a99354e20faa1b49a85206c47de97a639510a0e673f5da/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:03b77d184b9eb40240ae9fd676ca364ce1085f203e1b1256f8ab9984dca80a84" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1f/f2/f11dd73284122713f5f89fc940f370d035fa8e1e078d446b3313955157fe/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:a668ce24de96165bb239160b3d854943128f4334822900534f2fe947930e5770" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/88/9d/b06ca6acfe4abb296110fb1273a4d848a0bfb2ff65f3ee92127b3244e16b/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f14f8f046c14563f8eb3f45f499cc658ab8d10072961e07225e507adb700e93f" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/36/c7/cfc8e811f061c841d7990b0201912c3556bfeb99cdcb7ed24adc8d6f8704/pydantic_core-2.41.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:56121965f7a4dc965bff783d70b907ddf3d57f6eba29b6d2e5dabfaf07799c51" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "python-dotenv"
|
||||
version = "1.2.1"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "python-multipart"
|
||||
version = "0.0.21"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/78/96/804520d0850c7db98e5ccb70282e29208723f0964e88ffd9d0da2f52ea09/python_multipart-0.0.21.tar.gz", hash = "sha256:7137ebd4d3bbf70ea1622998f902b97a29434a9e8dc40eb203bbcf7c2a2cba92" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/aa/76/03af049af4dcee5d27442f71b6924f01f3efb5d2bd34f23fcd563f2cc5f5/python_multipart-0.0.21-py3-none-any.whl", hash = "sha256:cf7a6713e01c87aa35387f4774e812c4361150938d20d232800f75ffcf266090" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "slowapi"
|
||||
version = "0.1.9"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "limits" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a0/99/adfc7f94ca024736f061257d39118e1542bade7a52e86415a4c4ae92d8ff/slowapi-0.1.9.tar.gz", hash = "sha256:639192d0f1ca01b1c6d95bf6c71d794c3a9ee189855337b4821f7f457dddad77" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/2b/bb/f71c4b7d7e7eb3fc1e8c0458a8979b912f40b58002b9fbf37729b8cb464b/slowapi-0.1.9-py3-none-any.whl", hash = "sha256:cfad116cfb84ad9d763ee155c1e5c5cbf00b0d47399a769b227865f5df576e36" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "starlette"
|
||||
version = "0.50.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "anyio" },
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ba/b8/73a0e6a6e079a9d9cfa64113d771e421640b6f679a52eeb9b32f72d871a1/starlette-0.50.0.tar.gz", hash = "sha256:a2a17b22203254bcbc2e1f926d2d55f3f9497f769416b3190768befe598fa3ca" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d9/52/1064f510b141bd54025f9b55105e26d1fa970b9be67ad766380a3c9b74b0/starlette-0.50.0-py3-none-any.whl", hash = "sha256:9e5391843ec9b6e472eed1365a78c8098cfceb7a74bfd4d6b1c0c0095efb3bca" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.15.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-inspection"
|
||||
version = "0.4.2"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "uvicorn"
|
||||
version = "0.38.0"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
dependencies = [
|
||||
{ name = "click" },
|
||||
{ name = "h11" },
|
||||
]
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cb/ce/f06b84e2697fef4688ca63bdb2fdf113ca0a3be33f94488f2cadb690b0cf/uvicorn-0.38.0.tar.gz", hash = "sha256:fd97093bdd120a2609fc0d3afe931d4d4ad688b6e75f0f929fde1bc36fe0e91d" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ee/d9/d88e73ca598f4f6ff671fb5fde8a32925c2e08a637303a1d12883c7305fa/uvicorn-0.38.0-py3-none-any.whl", hash = "sha256:48c0afd214ceb59340075b4a052ea1ee91c16fbc2a9b1469cca0e54566977b02" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "wrapt"
|
||||
version = "2.0.1"
|
||||
source = { registry = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/simple" }
|
||||
sdist = { url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/49/2a/6de8a50cb435b7f42c46126cf1a54b2aab81784e74c8595c8e025e8f36d3/wrapt-2.0.1.tar.gz", hash = "sha256:9c9c635e78497cacb81e84f8b11b23e0aacac7a136e73b8e5b2109a1d9fc468f" }
|
||||
wheels = [
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/98/60/553997acf3939079dab022e37b67b1904b5b0cc235503226898ba573b10c/wrapt-2.0.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0e17283f533a0d24d6e5429a7d11f250a58d28b4ae5186f8f47853e3e70d2590" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/2d/50/e5b3d30895d77c52105c6d5cbf94d5b38e2a3dd4a53d22d246670da98f7c/wrapt-2.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:85df8d92158cb8f3965aecc27cf821461bb5f40b450b03facc5d9f0d4d6ddec6" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f0/40/660b2898703e5cbbb43db10cdefcc294274458c3ca4c68637c2b99371507/wrapt-2.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c1be685ac7700c966b8610ccc63c3187a72e33cab53526a27b2a285a662cd4f7" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5b/36/825b44c8a10556957bc0c1d84c7b29a40e05fcf1873b6c40aa9dbe0bd972/wrapt-2.0.1-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:df0b6d3b95932809c5b3fecc18fda0f1e07452d05e2662a0b35548985f256e28" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/83/73/0a5d14bb1599677304d3c613a55457d34c344e9b60eda8a737c2ead7619e/wrapt-2.0.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4da7384b0e5d4cae05c97cd6f94faaf78cc8b0f791fc63af43436d98c4ab37bb" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/01/22/1c158fe763dbf0a119f985d945711d288994fe5514c0646ebe0eb18b016d/wrapt-2.0.1-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ec65a78fbd9d6f083a15d7613b2800d5663dbb6bb96003899c834beaa68b242c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5c/28/4f16861af67d6de4eae9927799b559c20ebdd4fe432e89ea7fe6fcd9d709/wrapt-2.0.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7de3cc939be0e1174969f943f3b44e0d79b6f9a82198133a5b7fc6cc92882f16" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a0/8b/7960122e625fad908f189b59c4aae2d50916eb4098b0fb2819c5a177414f/wrapt-2.0.1-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:fb1a5b72cbd751813adc02ef01ada0b0d05d3dcbc32976ce189a1279d80ad4a2" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/3e/73/7881eee5ac31132a713ab19a22c9e5f1f7365c8b1df50abba5d45b781312/wrapt-2.0.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3fa272ca34332581e00bf7773e993d4f632594eb2d1b0b162a9038df0fd971dd" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/45/00/9499a3d14e636d1f7089339f96c4409bbc7544d0889f12264efa25502ae8/wrapt-2.0.1-cp311-cp311-win32.whl", hash = "sha256:fc007fdf480c77301ab1afdbb6ab22a5deee8885f3b1ed7afcb7e5e84a0e27be" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/70/5d/8f3d7eea52f22638748f74b102e38fdf88cb57d08ddeb7827c476a20b01b/wrapt-2.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:47434236c396d04875180171ee1f3815ca1eada05e24a1ee99546320d54d1d1b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/14/e2/32195e57a8209003587bbbad44d5922f13e0ced2a493bb46ca882c5b123d/wrapt-2.0.1-cp311-cp311-win_arm64.whl", hash = "sha256:837e31620e06b16030b1d126ed78e9383815cbac914693f54926d816d35d8edf" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cb/73/8cb252858dc8254baa0ce58ce382858e3a1cf616acebc497cb13374c95c6/wrapt-2.0.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1fdbb34da15450f2b1d735a0e969c24bdb8d8924892380126e2a293d9902078c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/19/42/44a0db2108526ee6e17a5ab72478061158f34b08b793df251d9fbb9a7eb4/wrapt-2.0.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:3d32794fe940b7000f0519904e247f902f0149edbe6316c710a8562fb6738841" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/4d/8a/5b4b1e44b791c22046e90d9b175f9a7581a8cc7a0debbb930f81e6ae8e25/wrapt-2.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:386fb54d9cd903ee0012c09291336469eb7b244f7183d40dc3e86a16a4bace62" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/11/53/3e794346c39f462bcf1f58ac0487ff9bdad02f9b6d5ee2dc84c72e0243b2/wrapt-2.0.1-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:7b219cb2182f230676308cdcacd428fa837987b89e4b7c5c9025088b8a6c9faf" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/c6/7e/10b7b0e8841e684c8ca76b462a9091c45d62e8f2de9c4b1390b690eadf16/wrapt-2.0.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:641e94e789b5f6b4822bb8d8ebbdfc10f4e4eae7756d648b717d980f657a9eb9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0e/d1/3c1e4321fc2f5ee7fd866b2d822aa89b84495f28676fd976c47327c5b6aa/wrapt-2.0.1-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:fe21b118b9f58859b5ebaa4b130dee18669df4bd111daad082b7beb8799ad16b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a4/b0/d2f0a413cf201c8c2466de08414a15420a25aa83f53e647b7255cc2fab5d/wrapt-2.0.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:17fb85fa4abc26a5184d93b3efd2dcc14deb4b09edcdb3535a536ad34f0b4dba" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/bd/45/bddb11d28ca39970a41ed48a26d210505120f925918592283369219f83cc/wrapt-2.0.1-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:b89ef9223d665ab255ae42cc282d27d69704d94be0deffc8b9d919179a609684" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/81/af/34ba6dd570ef7a534e7eec0c25e2615c355602c52aba59413411c025a0cb/wrapt-2.0.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a453257f19c31b31ba593c30d997d6e5be39e3b5ad9148c2af5a7314061c63eb" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e2/3e/693a13b4146646fb03254636f8bafd20c621955d27d65b15de07ab886187/wrapt-2.0.1-cp312-cp312-win32.whl", hash = "sha256:3e271346f01e9c8b1130a6a3b0e11908049fe5be2d365a5f402778049147e7e9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a7/36/715ec5076f925a6be95f37917b66ebbeaa1372d1862c2ccd7a751574b068/wrapt-2.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:2da620b31a90cdefa9cd0c2b661882329e2e19d1d7b9b920189956b76c564d75" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ef/3e/62451cd7d80f65cc125f2b426b25fbb6c514bf6f7011a0c3904fc8c8df90/wrapt-2.0.1-cp312-cp312-win_arm64.whl", hash = "sha256:aea9c7224c302bc8bfc892b908537f56c430802560e827b75ecbde81b604598b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ad/fe/41af4c46b5e498c90fc87981ab2972fbd9f0bccda597adb99d3d3441b94b/wrapt-2.0.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:47b0f8bafe90f7736151f61482c583c86b0693d80f075a58701dd1549b0010a9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1c/92/d68895a984a5ebbbfb175512b0c0aad872354a4a2484fbd5552e9f275316/wrapt-2.0.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:cbeb0971e13b4bd81d34169ed57a6dda017328d1a22b62fda45e1d21dd06148f" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e8/26/ba83dc5ae7cf5aa2b02364a3d9cf74374b86169906a1f3ade9a2d03cf21c/wrapt-2.0.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:eb7cffe572ad0a141a7886a1d2efa5bef0bf7fe021deeea76b3ab334d2c38218" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/cf/67/d7a7c276d874e5d26738c22444d466a3a64ed541f6ef35f740dbd865bab4/wrapt-2.0.1-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:c8d60527d1ecfc131426b10d93ab5d53e08a09c5fa0175f6b21b3252080c70a9" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0f/6b/806dbf6dd9579556aab22fc92908a876636e250f063f71548a8660382184/wrapt-2.0.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c654eafb01afac55246053d67a4b9a984a3567c3808bb7df2f8de1c1caba2e1c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e5/08/cdbb965fbe4c02c5233d185d070cabed2ecc1f1e47662854f95d77613f57/wrapt-2.0.1-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:98d873ed6c8b4ee2418f7afce666751854d6d03e3c0ec2a399bb039cd2ae89db" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/2d/d1/6aae2ce39db4cb5216302fa2e9577ad74424dfbe315bd6669725569e048c/wrapt-2.0.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c9e850f5b7fc67af856ff054c71690d54fa940c3ef74209ad9f935b4f66a0233" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/79/35/565abf57559fbe0a9155c29879ff43ce8bd28d2ca61033a3a3dd67b70794/wrapt-2.0.1-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:e505629359cb5f751e16e30cf3f91a1d3ddb4552480c205947da415d597f7ac2" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/e1/e0/53ff5e76587822ee33e560ad55876d858e384158272cd9947abdd4ad42ca/wrapt-2.0.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:2879af909312d0baf35f08edeea918ee3af7ab57c37fe47cb6a373c9f2749c7b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/7c/7b/38df30fd629fbd7612c407643c63e80e1c60bcc982e30ceeae163a9800e7/wrapt-2.0.1-cp313-cp313-win32.whl", hash = "sha256:d67956c676be5a24102c7407a71f4126d30de2a569a1c7871c9f3cabc94225d7" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/85/64/d3954e836ea67c4d3ad5285e5c8fd9d362fd0a189a2db622df457b0f4f6a/wrapt-2.0.1-cp313-cp313-win_amd64.whl", hash = "sha256:9ca66b38dd642bf90c59b6738af8070747b610115a39af2498535f62b5cdc1c3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/89/4e/3c8b99ac93527cfab7f116089db120fef16aac96e5f6cdb724ddf286086d/wrapt-2.0.1-cp313-cp313-win_arm64.whl", hash = "sha256:5a4939eae35db6b6cec8e7aa0e833dcca0acad8231672c26c2a9ab7a0f8ac9c8" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f9/f4/eff2b7d711cae20d220780b9300faa05558660afb93f2ff5db61fe725b9a/wrapt-2.0.1-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:a52f93d95c8d38fed0669da2ebdb0b0376e895d84596a976c15a9eb45e3eccb3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0c/67/cb945563f66fd0f61a999339460d950f4735c69f18f0a87ca586319b1778/wrapt-2.0.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:4e54bbf554ee29fcceee24fa41c4d091398b911da6e7f5d7bffda963c9aed2e1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ec/ca/f63e177f0bbe1e5cf5e8d9b74a286537cd709724384ff20860f8f6065904/wrapt-2.0.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:908f8c6c71557f4deaa280f55d0728c3bca0960e8c3dd5ceeeafb3c19942719d" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/39/a1/1b88fcd21fd835dca48b556daef750952e917a2794fa20c025489e2e1f0f/wrapt-2.0.1-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:e2f84e9af2060e3904a32cea9bb6db23ce3f91cfd90c6b426757cf7cc01c45c7" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/62/1c/d9185500c1960d9f5f77b9c0b890b7fc62282b53af7ad1b6bd779157f714/wrapt-2.0.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e3612dc06b436968dfb9142c62e5dfa9eb5924f91120b3c8ff501ad878f90eb3" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/91/60/5d796ed0f481ec003220c7878a1d6894652efe089853a208ea0838c13086/wrapt-2.0.1-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6d2d947d266d99a1477cd005b23cbd09465276e302515e122df56bb9511aca1b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/04/f8/75282dd72f102ddbfba137e1e15ecba47b40acff32c08ae97edbf53f469e/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:7d539241e87b650cbc4c3ac9f32c8d1ac8a54e510f6dca3f6ab60dcfd48c9b10" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/5a/27/fe39c51d1b344caebb4a6a9372157bdb8d25b194b3561b52c8ffc40ac7d1/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:4811e15d88ee62dbf5c77f2c3ff3932b1e3ac92323ba3912f51fc4016ce81ecf" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/83/2b/9f6b643fe39d4505c7bf926d7c2595b7cb4b607c8c6b500e56c6b36ac238/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:c1c91405fcf1d501fa5d55df21e58ea49e6b879ae829f1039faaf7e5e509b41e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/bb/b6/20ffcf2558596a7f58a2e69c89597128781f0b88e124bf5a4cadc05b8139/wrapt-2.0.1-cp313-cp313t-win32.whl", hash = "sha256:e76e3f91f864e89db8b8d2a8311d57df93f01ad6bb1e9b9976d1f2e83e18315c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/87/6a/0e56111cbb3320151eed5d3821ee1373be13e05b376ea0870711f18810c3/wrapt-2.0.1-cp313-cp313t-win_amd64.whl", hash = "sha256:83ce30937f0ba0d28818807b303a412440c4b63e39d3d8fc036a94764b728c92" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1d/54/5ab4c53ea1f7f7e5c3e7c1095db92932cc32fd62359d285486d00c2884c3/wrapt-2.0.1-cp313-cp313t-win_arm64.whl", hash = "sha256:4b55cacc57e1dc2d0991dbe74c6419ffd415fb66474a02335cb10efd1aa3f84f" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/73/81/d08d83c102709258e7730d3cd25befd114c60e43ef3891d7e6877971c514/wrapt-2.0.1-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:5e53b428f65ece6d9dad23cb87e64506392b720a0b45076c05354d27a13351a1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f6/14/393afba2abb65677f313aa680ff0981e829626fed39b6a7e3ec807487790/wrapt-2.0.1-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:ad3ee9d0f254851c71780966eb417ef8e72117155cff04821ab9b60549694a55" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/c4/10/a4a1f2fba205a9462e36e708ba37e5ac95f4987a0f1f8fd23f0bf1fc3b0f/wrapt-2.0.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:d7b822c61ed04ee6ad64bc90d13368ad6eb094db54883b5dde2182f67a7f22c0" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/12/db/99ba5c37cf1c4fad35349174f1e38bd8d992340afc1ff27f526729b98986/wrapt-2.0.1-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:7164a55f5e83a9a0b031d3ffab4d4e36bbec42e7025db560f225489fa929e509" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/30/3f/a1c8d2411eb826d695fc3395a431757331582907a0ec59afce8fe8712473/wrapt-2.0.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e60690ba71a57424c8d9ff28f8d006b7ad7772c22a4af432188572cd7fa004a1" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/b3/8d/72c74a63f201768d6a04a8845c7976f86be6f5ff4d74996c272cefc8dafc/wrapt-2.0.1-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:3cd1a4bd9a7a619922a8557e1318232e7269b5fb69d4ba97b04d20450a6bf970" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/c7/5a/df37cf4042cb13b08256f8e27023e2f9b3d471d553376616591bb99bcb31/wrapt-2.0.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b4c2e3d777e38e913b8ce3a6257af72fb608f86a1df471cb1d4339755d0a807c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/54/34/40d6bc89349f9931e1186ceb3e5fbd61d307fef814f09fbbac98ada6a0c8/wrapt-2.0.1-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:3d366aa598d69416b5afedf1faa539fac40c1d80a42f6b236c88c73a3c8f2d41" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/70/66/81c3461adece09d20781dee17c2366fdf0cb8754738b521d221ca056d596/wrapt-2.0.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:c235095d6d090aa903f1db61f892fffb779c1eaeb2a50e566b52001f7a0f66ed" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/46/3a/d0146db8be8761a9e388cc9cc1c312b36d583950ec91696f19bbbb44af5a/wrapt-2.0.1-cp314-cp314-win32.whl", hash = "sha256:bfb5539005259f8127ea9c885bdc231978c06b7a980e63a8a61c8c4c979719d0" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1a/38/5359da9af7d64554be63e9046164bd4d8ff289a2dd365677d25ba3342c08/wrapt-2.0.1-cp314-cp314-win_amd64.whl", hash = "sha256:4ae879acc449caa9ed43fc36ba08392b9412ee67941748d31d94e3cedb36628c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/aa/3f/96db0619276a833842bf36343685fa04f987dd6e3037f314531a1e00492b/wrapt-2.0.1-cp314-cp314-win_arm64.whl", hash = "sha256:8639b843c9efd84675f1e100ed9e99538ebea7297b62c4b45a7042edb84db03e" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/71/49/5f5d1e867bf2064bf3933bc6cf36ade23505f3902390e175e392173d36a2/wrapt-2.0.1-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:9219a1d946a9b32bb23ccae66bdb61e35c62773ce7ca6509ceea70f344656b7b" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/2b/89/0009a218d88db66ceb83921e5685e820e2c61b59bbbb1324ba65342668bc/wrapt-2.0.1-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:fa4184e74197af3adad3c889a1af95b53bb0466bced92ea99a0c014e48323eec" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/ae/18/9b968e920dd05d6e44bcc918a046d02afea0fb31b2f1c80ee4020f377cbe/wrapt-2.0.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c5ef2f2b8a53b7caee2f797ef166a390fef73979b15778a4a153e4b5fedce8fa" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/a6/7d/78bdcb75826725885d9ea26c49a03071b10c4c92da93edda612910f150e4/wrapt-2.0.1-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:e042d653a4745be832d5aa190ff80ee4f02c34b21f4b785745eceacd0907b815" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/dd/77/cac1d46f47d32084a703df0d2d29d47e7eb2a7d19fa5cbca0e529ef57659/wrapt-2.0.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:2afa23318136709c4b23d87d543b425c399887b4057936cd20386d5b1422b6fa" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/8a/11/b521406daa2421508903bf8d5e8b929216ec2af04839db31c0a2c525eee0/wrapt-2.0.1-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6c72328f668cf4c503ffcf9434c2b71fdd624345ced7941bc6693e61bbe36bef" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/0c/c0/340b272bed297baa7c9ce0c98ef7017d9c035a17a6a71dce3184b8382da2/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:3793ac154afb0e5b45d1233cb94d354ef7a983708cc3bb12563853b1d8d53747" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/f3/93/bfcb1fb2bdf186e9c2883a4d1ab45ab099c79cbf8f4e70ea453811fa3ea7/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:fec0d993ecba3991645b4857837277469c8cc4c554a7e24d064d1ca291cfb81f" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/d2/6b/dca504fb18d971139d232652656180e3bd57120e1193d9a5899c3c0b7cdd/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:949520bccc1fa227274da7d03bf238be15389cd94e32e4297b92337df9b7a349" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/1d/f6/a1de4bd3653afdf91d250ca5c721ee51195df2b61a4603d4b373aa804d1d/wrapt-2.0.1-cp314-cp314t-win32.whl", hash = "sha256:be9e84e91d6497ba62594158d3d31ec0486c60055c49179edc51ee43d095f79c" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/01/3a/07cd60a9d26fe73efead61c7830af975dfdba8537632d410462672e4432b/wrapt-2.0.1-cp314-cp314t-win_amd64.whl", hash = "sha256:61c4956171c7434634401db448371277d07032a81cc21c599c22953374781395" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/41/99/8a06b8e17dddbf321325ae4eb12465804120f699cd1b8a355718300c62da/wrapt-2.0.1-cp314-cp314t-win_arm64.whl", hash = "sha256:35cdbd478607036fee40273be8ed54a451f5f23121bd9d4be515158f9498f7ad" },
|
||||
{ url = "https://artifacts.prod.devops.point72.com/artifactory/api/pypi/pypi-remote/packages/packages/15/d1/b51471c11592ff9c012bd3e2f7334a6ff2f42a7aed2caffcf0bdddc9cb89/wrapt-2.0.1-py3-none-any.whl", hash = "sha256:4d2ce1bf1a48c5277d7969259232b57645aae5686dba1eaeade39442277afbca" },
|
||||
]
|
||||
231
tests/batches_tests/local-litellm/patches/README.md
Normal file
231
tests/batches_tests/local-litellm/patches/README.md
Normal file
|
|
@ -0,0 +1,231 @@
|
|||
# LiteLLM Patches
|
||||
|
||||
Patches for LiteLLM `main-latest` (as of 2025-12-19).
|
||||
|
||||
---
|
||||
|
||||
## 1. 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
|
||||
```
|
||||
220
tests/batches_tests/test_managed_files_base.py
Normal file
220
tests/batches_tests/test_managed_files_base.py
Normal file
|
|
@ -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}")
|
||||
|
||||
|
||||
|
||||
204
tests/batches_tests/test_managed_files_endtoend.py
Normal file
204
tests/batches_tests/test_managed_files_endtoend.py
Normal file
|
|
@ -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")
|
||||
|
||||
|
||||
|
||||
436
tests/batches_tests/test_managed_files_permissions.py
Normal file
436
tests/batches_tests/test_managed_files_permissions.py
Normal file
|
|
@ -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
|
||||
|
||||
|
||||
|
||||
Loading…
Add table
Reference in a new issue