mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-24 18:24:20 +00:00
Merge branch 'main' into litellm_use_redis_for_updates
This commit is contained in:
Ishaan Jaff
commit
7e8a02099c
140 changed files with 2806 additions and 427 deletions
|
|
@ -500,6 +500,12 @@ jobs:
|
|||
working_directory: ~/project
|
||||
steps:
|
||||
- checkout
|
||||
- run:
|
||||
name: Install PostgreSQL
|
||||
command: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install postgresql postgresql-contrib
|
||||
echo 'export PATH=/usr/lib/postgresql/*/bin:$PATH' >> $BASH_ENV
|
||||
- setup_google_dns
|
||||
- run:
|
||||
name: Show git commit hash
|
||||
|
|
|
|||
35
.github/workflows/test-litellm.yml
vendored
Normal file
35
.github/workflows/test-litellm.yml
vendored
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
name: LiteLLM Tests
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches: [ main ]
|
||||
|
||||
jobs:
|
||||
test:
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 5
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Thank You Message
|
||||
run: |
|
||||
echo "### 🙏 Thank you for contributing to LiteLLM!" >> $GITHUB_STEP_SUMMARY
|
||||
echo "Your PR is being tested now. We appreciate your help in making LiteLLM better!" >> $GITHUB_STEP_SUMMARY
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: '3.12'
|
||||
|
||||
- name: Install Poetry
|
||||
uses: snok/install-poetry@v1
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
poetry install --with dev,proxy-dev --extras proxy
|
||||
poetry run pip install pytest-xdist
|
||||
|
||||
- name: Run tests
|
||||
run: |
|
||||
poetry run pytest tests/litellm -x -vv -n 4
|
||||
2
.gitignore
vendored
2
.gitignore
vendored
|
|
@ -83,4 +83,4 @@ tests/llm_translation/test_vertex_key.json
|
|||
litellm/proxy/migrations/0_init/migration.sql
|
||||
litellm/proxy/db/migrations/0_init/migration.sql
|
||||
litellm/proxy/db/migrations/*
|
||||
litellm/proxy/migrations/*
|
||||
litellm/proxy/migrations/*config.yaml
|
||||
|
|
|
|||
3
Makefile
3
Makefile
|
|
@ -14,6 +14,9 @@ help:
|
|||
install-dev:
|
||||
poetry install --with dev
|
||||
|
||||
install-proxy-dev:
|
||||
poetry install --with dev,proxy-dev
|
||||
|
||||
lint: install-dev
|
||||
poetry run pip install types-requests types-setuptools types-redis types-PyYAML
|
||||
cd litellm && poetry run mypy . --ignore-missing-imports
|
||||
|
|
|
|||
|
|
@ -16,9 +16,6 @@
|
|||
<a href="https://pypi.org/project/litellm/" target="_blank">
|
||||
<img src="https://img.shields.io/pypi/v/litellm.svg" alt="PyPI Version">
|
||||
</a>
|
||||
<a href="https://dl.circleci.com/status-badge/redirect/gh/BerriAI/litellm/tree/main" target="_blank">
|
||||
<img src="https://dl.circleci.com/status-badge/img/gh/BerriAI/litellm/tree/main.svg?style=svg" alt="CircleCI">
|
||||
</a>
|
||||
<a href="https://www.ycombinator.com/companies/berriai">
|
||||
<img src="https://img.shields.io/badge/Y%20Combinator-W23-orange?style=flat-square" alt="Y Combinator W23">
|
||||
</a>
|
||||
|
|
|
|||
|
|
@ -1,4 +1,3 @@
|
|||
import os
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
|
|
|||
|
|
@ -65,6 +65,6 @@ spec:
|
|||
tolerations:
|
||||
{{- toYaml . | nindent 8 }}
|
||||
{{- end }}
|
||||
ttlSecondsAfterFinished: {{ .Values.migrationJob.ttlSecondsAfterFinished }}
|
||||
ttlSecondsAfterFinished: {{ .Values.migrationJob.ttlSecondsAfterFinished }}
|
||||
backoffLimit: {{ .Values.migrationJob.backoffLimit }}
|
||||
{{- end }}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,3 @@
|
|||
-- AlterTable
|
||||
ALTER TABLE "LiteLLM_DailyUserSpend" ADD COLUMN "api_requests" INTEGER NOT NULL DEFAULT 0;
|
||||
|
||||
|
|
@ -188,7 +188,13 @@ Currently implemented for:
|
|||
- OpenAI (if OPENAI_API_KEY is set)
|
||||
- Fireworks AI (if FIREWORKS_AI_API_KEY is set)
|
||||
- LiteLLM Proxy (if LITELLM_PROXY_API_KEY is set)
|
||||
- Gemini (if GEMINI_API_KEY is set)
|
||||
- XAI (if XAI_API_KEY is set)
|
||||
- Anthropic (if ANTHROPIC_API_KEY is set)
|
||||
|
||||
You can also specify a custom provider to check:
|
||||
|
||||
**All providers**:
|
||||
```python
|
||||
from litellm import get_valid_models
|
||||
|
||||
|
|
@ -196,6 +202,14 @@ valid_models = get_valid_models(check_provider_endpoint=True)
|
|||
print(valid_models)
|
||||
```
|
||||
|
||||
**Specific provider**:
|
||||
```python
|
||||
from litellm import get_valid_models
|
||||
|
||||
valid_models = get_valid_models(check_provider_endpoint=True, custom_llm_provider="openai")
|
||||
print(valid_models)
|
||||
```
|
||||
|
||||
### `validate_environment(model: str)`
|
||||
|
||||
This helper tells you if you have all the required environment variables for a model, and if not - what's missing.
|
||||
|
|
|
|||
|
|
@ -813,6 +813,7 @@ from .llms.oobabooga.chat.transformation import OobaboogaConfig
|
|||
from .llms.maritalk import MaritalkConfig
|
||||
from .llms.openrouter.chat.transformation import OpenrouterConfig
|
||||
from .llms.anthropic.chat.transformation import AnthropicConfig
|
||||
from .llms.anthropic.common_utils import AnthropicModelInfo
|
||||
from .llms.groq.stt.transformation import GroqSTTConfig
|
||||
from .llms.anthropic.completion.transformation import AnthropicTextConfig
|
||||
from .llms.triton.completion.transformation import TritonConfig
|
||||
|
|
@ -848,6 +849,7 @@ from .llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
|
|||
VertexGeminiConfig,
|
||||
VertexGeminiConfig as VertexAIConfig,
|
||||
)
|
||||
from .llms.gemini.common_utils import GeminiModelInfo
|
||||
from .llms.gemini.chat.transformation import (
|
||||
GoogleAIStudioGeminiConfig,
|
||||
GoogleAIStudioGeminiConfig as GeminiConfig, # aliased to maintain backwards compatibility
|
||||
|
|
@ -984,6 +986,7 @@ from .llms.fireworks_ai.embed.fireworks_ai_transformation import (
|
|||
from .llms.friendliai.chat.transformation import FriendliaiChatConfig
|
||||
from .llms.jina_ai.embedding.transformation import JinaAIEmbeddingConfig
|
||||
from .llms.xai.chat.transformation import XAIChatConfig
|
||||
from .llms.xai.common_utils import XAIModelInfo
|
||||
from .llms.volcengine import VolcEngineConfig
|
||||
from .llms.codestral.completion.transformation import CodestralTextCompletionConfig
|
||||
from .llms.azure.azure import (
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import json
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from logging import Formatter
|
||||
|
||||
|
|
@ -40,9 +41,56 @@ class JsonFormatter(Formatter):
|
|||
return json.dumps(json_record)
|
||||
|
||||
|
||||
# Function to set up exception handlers for JSON logging
|
||||
def _setup_json_exception_handlers(formatter):
|
||||
# Create a handler with JSON formatting for exceptions
|
||||
error_handler = logging.StreamHandler()
|
||||
error_handler.setFormatter(formatter)
|
||||
|
||||
# Setup excepthook for uncaught exceptions
|
||||
def json_excepthook(exc_type, exc_value, exc_traceback):
|
||||
record = logging.LogRecord(
|
||||
name="LiteLLM",
|
||||
level=logging.ERROR,
|
||||
pathname="",
|
||||
lineno=0,
|
||||
msg=str(exc_value),
|
||||
args=(),
|
||||
exc_info=(exc_type, exc_value, exc_traceback),
|
||||
)
|
||||
error_handler.handle(record)
|
||||
|
||||
sys.excepthook = json_excepthook
|
||||
|
||||
# Configure asyncio exception handler if possible
|
||||
try:
|
||||
import asyncio
|
||||
|
||||
def async_json_exception_handler(loop, context):
|
||||
exception = context.get("exception")
|
||||
if exception:
|
||||
record = logging.LogRecord(
|
||||
name="LiteLLM",
|
||||
level=logging.ERROR,
|
||||
pathname="",
|
||||
lineno=0,
|
||||
msg=str(exception),
|
||||
args=(),
|
||||
exc_info=None,
|
||||
)
|
||||
error_handler.handle(record)
|
||||
else:
|
||||
loop.default_exception_handler(context)
|
||||
|
||||
asyncio.get_event_loop().set_exception_handler(async_json_exception_handler)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
# Create a formatter and set it for the handler
|
||||
if json_logs:
|
||||
handler.setFormatter(JsonFormatter())
|
||||
_setup_json_exception_handlers(JsonFormatter())
|
||||
else:
|
||||
formatter = logging.Formatter(
|
||||
"\033[92m%(asctime)s - %(name)s:%(levelname)s\033[0m: %(filename)s:%(lineno)s - %(message)s",
|
||||
|
|
@ -65,18 +113,24 @@ def _turn_on_json():
|
|||
handler = logging.StreamHandler()
|
||||
handler.setFormatter(JsonFormatter())
|
||||
|
||||
# Define a list of the loggers to update
|
||||
loggers = [verbose_router_logger, verbose_proxy_logger, verbose_logger]
|
||||
# Define all loggers to update, including root logger
|
||||
loggers = [logging.getLogger()] + [
|
||||
verbose_router_logger,
|
||||
verbose_proxy_logger,
|
||||
verbose_logger,
|
||||
]
|
||||
|
||||
# Iterate through each logger and update its handlers
|
||||
for logger in loggers:
|
||||
# Remove all existing handlers
|
||||
for h in logger.handlers[:]:
|
||||
logger.removeHandler(h)
|
||||
|
||||
# Add the new handler
|
||||
logger.addHandler(handler)
|
||||
|
||||
# Set up exception handlers
|
||||
_setup_json_exception_handlers(JsonFormatter())
|
||||
|
||||
|
||||
def _turn_on_debug():
|
||||
verbose_logger.setLevel(level=logging.DEBUG) # set package log to debug
|
||||
|
|
|
|||
|
|
@ -4,9 +4,11 @@ ROUTER_MAX_FALLBACKS = 5
|
|||
DEFAULT_BATCH_SIZE = 512
|
||||
DEFAULT_FLUSH_INTERVAL_SECONDS = 5
|
||||
DEFAULT_MAX_RETRIES = 2
|
||||
DEFAULT_MAX_RECURSE_DEPTH = 10
|
||||
DEFAULT_FAILURE_THRESHOLD_PERCENT = (
|
||||
0.5 # default cooldown a deployment if 50% of requests fail in a given minute
|
||||
)
|
||||
DEFAULT_MAX_TOKENS = 4096
|
||||
DEFAULT_REDIS_SYNC_INTERVAL = 1
|
||||
DEFAULT_COOLDOWN_TIME_SECONDS = 5
|
||||
DEFAULT_REPLICATE_POLLING_RETRIES = 5
|
||||
|
|
|
|||
|
|
@ -1,8 +1,9 @@
|
|||
import json
|
||||
from typing import Any, Union
|
||||
from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
|
||||
|
||||
|
||||
def safe_dumps(data: Any, max_depth: int = 10) -> str:
|
||||
def safe_dumps(data: Any, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH) -> str:
|
||||
"""
|
||||
Recursively serialize data while detecting circular references.
|
||||
If a circular reference is detected then a marker string is returned.
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
from typing import Any, Dict, Optional, Set
|
||||
from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
|
||||
|
||||
|
||||
class SensitiveDataMasker:
|
||||
|
|
@ -39,7 +40,7 @@ class SensitiveDataMasker:
|
|||
return result
|
||||
|
||||
def mask_dict(
|
||||
self, data: Dict[str, Any], depth: int = 0, max_depth: int = 10
|
||||
self, data: Dict[str, Any], depth: int = 0, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH
|
||||
) -> Dict[str, Any]:
|
||||
if depth >= max_depth:
|
||||
return data
|
||||
|
|
|
|||
|
|
@ -300,6 +300,15 @@ class AnthropicConfig(BaseConfig):
|
|||
model: str,
|
||||
drop_params: bool,
|
||||
) -> dict:
|
||||
|
||||
is_thinking_enabled = self.is_thinking_enabled(
|
||||
non_default_params=non_default_params
|
||||
)
|
||||
|
||||
## handle thinking tokens
|
||||
self.update_optional_params_with_thinking_tokens(
|
||||
non_default_params=non_default_params, optional_params=optional_params
|
||||
)
|
||||
for param, value in non_default_params.items():
|
||||
if param == "max_tokens":
|
||||
optional_params["max_tokens"] = value
|
||||
|
|
@ -349,19 +358,23 @@ class AnthropicConfig(BaseConfig):
|
|||
- Remember that the model will pass the input to the tool, so the name of the tool and description should be from the model’s perspective.
|
||||
"""
|
||||
|
||||
_tool_choice = {"name": RESPONSE_FORMAT_TOOL_NAME, "type": "tool"}
|
||||
if not is_thinking_enabled:
|
||||
_tool_choice = {"name": RESPONSE_FORMAT_TOOL_NAME, "type": "tool"}
|
||||
optional_params["tool_choice"] = _tool_choice
|
||||
|
||||
_tool = self._create_json_tool_call_for_response_format(
|
||||
json_schema=json_schema,
|
||||
)
|
||||
optional_params = self._add_tools_to_optional_params(
|
||||
optional_params=optional_params, tools=[_tool]
|
||||
)
|
||||
optional_params["tool_choice"] = _tool_choice
|
||||
|
||||
optional_params["json_mode"] = True
|
||||
if param == "user":
|
||||
optional_params["metadata"] = {"user_id": value}
|
||||
if param == "thinking":
|
||||
optional_params["thinking"] = value
|
||||
|
||||
return optional_params
|
||||
|
||||
def _create_json_tool_call_for_response_format(
|
||||
|
|
|
|||
|
|
@ -2,11 +2,14 @@
|
|||
This file contains common utils for anthropic calls.
|
||||
"""
|
||||
|
||||
from typing import Optional, Union
|
||||
from typing import List, Optional, Union
|
||||
|
||||
import httpx
|
||||
|
||||
import litellm
|
||||
from litellm.llms.base_llm.base_utils import BaseLLMModelInfo
|
||||
from litellm.llms.base_llm.chat.transformation import BaseLLMException
|
||||
from litellm.secret_managers.main import get_secret_str
|
||||
|
||||
|
||||
class AnthropicError(BaseLLMException):
|
||||
|
|
@ -19,6 +22,54 @@ class AnthropicError(BaseLLMException):
|
|||
super().__init__(status_code=status_code, message=message, headers=headers)
|
||||
|
||||
|
||||
class AnthropicModelInfo(BaseLLMModelInfo):
|
||||
@staticmethod
|
||||
def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
|
||||
return (
|
||||
api_base
|
||||
or get_secret_str("ANTHROPIC_API_BASE")
|
||||
or "https://api.anthropic.com"
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
|
||||
return api_key or get_secret_str("ANTHROPIC_API_KEY")
|
||||
|
||||
@staticmethod
|
||||
def get_base_model(model: Optional[str] = None) -> Optional[str]:
|
||||
return model.replace("anthropic/", "") if model else None
|
||||
|
||||
def get_models(
|
||||
self, api_key: Optional[str] = None, api_base: Optional[str] = None
|
||||
) -> List[str]:
|
||||
api_base = AnthropicModelInfo.get_api_base(api_base)
|
||||
api_key = AnthropicModelInfo.get_api_key(api_key)
|
||||
if api_base is None or api_key is None:
|
||||
raise ValueError(
|
||||
"ANTHROPIC_API_BASE or ANTHROPIC_API_KEY is not set. Please set the environment variable, to query Anthropic's `/models` endpoint."
|
||||
)
|
||||
response = litellm.module_level_client.get(
|
||||
url=f"{api_base}/v1/models",
|
||||
headers={"x-api-key": api_key, "anthropic-version": "2023-06-01"},
|
||||
)
|
||||
|
||||
try:
|
||||
response.raise_for_status()
|
||||
except httpx.HTTPStatusError:
|
||||
raise Exception(
|
||||
f"Failed to fetch models from Anthropic. Status code: {response.status_code}, Response: {response.text}"
|
||||
)
|
||||
|
||||
models = response.json()["data"]
|
||||
|
||||
litellm_model_names = []
|
||||
for model in models:
|
||||
stripped_model_name = model["id"]
|
||||
litellm_model_name = "anthropic/" + stripped_model_name
|
||||
litellm_model_names.append(litellm_model_name)
|
||||
return litellm_model_names
|
||||
|
||||
|
||||
def process_anthropic_headers(headers: Union[httpx.Headers, dict]) -> dict:
|
||||
openai_headers = {}
|
||||
if "anthropic-ratelimit-requests-limit" in headers:
|
||||
|
|
|
|||
|
|
@ -19,11 +19,19 @@ class BaseLLMModelInfo(ABC):
|
|||
self,
|
||||
model: str,
|
||||
) -> Optional[ProviderSpecificModelInfo]:
|
||||
"""
|
||||
Default values all models of this provider support.
|
||||
"""
|
||||
return None
|
||||
|
||||
@abstractmethod
|
||||
def get_models(self) -> List[str]:
|
||||
pass
|
||||
def get_models(
|
||||
self, api_key: Optional[str] = None, api_base: Optional[str] = None
|
||||
) -> List[str]:
|
||||
"""
|
||||
Returns a list of models supported by this provider.
|
||||
"""
|
||||
return []
|
||||
|
||||
@staticmethod
|
||||
@abstractmethod
|
||||
|
|
|
|||
|
|
@ -13,12 +13,13 @@ from typing import (
|
|||
Optional,
|
||||
Type,
|
||||
Union,
|
||||
cast,
|
||||
)
|
||||
|
||||
import httpx
|
||||
from pydantic import BaseModel
|
||||
|
||||
from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
|
||||
from litellm.constants import DEFAULT_MAX_TOKENS, RESPONSE_FORMAT_TOOL_NAME
|
||||
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
|
||||
from litellm.types.llms.openai import (
|
||||
AllMessageValues,
|
||||
|
|
@ -102,6 +103,29 @@ class BaseConfig(ABC):
|
|||
) -> Optional[dict]:
|
||||
return type_to_response_format_param(response_format=response_format)
|
||||
|
||||
def is_thinking_enabled(self, non_default_params: dict) -> bool:
|
||||
return non_default_params.get("thinking", {}).get("type", None) == "enabled"
|
||||
|
||||
def update_optional_params_with_thinking_tokens(
|
||||
self, non_default_params: dict, optional_params: dict
|
||||
):
|
||||
"""
|
||||
Handles scenario where max tokens is not specified. For anthropic models (anthropic api/bedrock/vertex ai), this requires having the max tokens being set and being greater than the thinking token budget.
|
||||
|
||||
Checks 'non_default_params' for 'thinking' and 'max_tokens'
|
||||
|
||||
if 'thinking' is enabled and 'max_tokens' is not specified, set 'max_tokens' to the thinking token budget + DEFAULT_MAX_TOKENS
|
||||
"""
|
||||
is_thinking_enabled = self.is_thinking_enabled(non_default_params)
|
||||
if is_thinking_enabled and "max_tokens" not in non_default_params:
|
||||
thinking_token_budget = cast(dict, non_default_params["thinking"]).get(
|
||||
"budget_tokens", None
|
||||
)
|
||||
if thinking_token_budget is not None:
|
||||
optional_params["max_tokens"] = (
|
||||
thinking_token_budget + DEFAULT_MAX_TOKENS
|
||||
)
|
||||
|
||||
def should_fake_stream(
|
||||
self,
|
||||
model: Optional[str],
|
||||
|
|
|
|||
|
|
@ -210,6 +210,10 @@ class AmazonConverseConfig(BaseConfig):
|
|||
drop_params: bool,
|
||||
messages: Optional[List[AllMessageValues]] = None,
|
||||
) -> dict:
|
||||
is_thinking_enabled = self.is_thinking_enabled(non_default_params)
|
||||
self.update_optional_params_with_thinking_tokens(
|
||||
non_default_params=non_default_params, optional_params=optional_params
|
||||
)
|
||||
for param, value in non_default_params.items():
|
||||
if param == "response_format" and isinstance(value, dict):
|
||||
|
||||
|
|
@ -247,8 +251,11 @@ class AmazonConverseConfig(BaseConfig):
|
|||
optional_params = self._add_tools_to_optional_params(
|
||||
optional_params=optional_params, tools=[_tool]
|
||||
)
|
||||
if litellm.utils.supports_tool_choice(
|
||||
model=model, custom_llm_provider=self.custom_llm_provider
|
||||
if (
|
||||
litellm.utils.supports_tool_choice(
|
||||
model=model, custom_llm_provider=self.custom_llm_provider
|
||||
)
|
||||
and not is_thinking_enabled
|
||||
):
|
||||
optional_params["tool_choice"] = ToolChoiceValuesBlock(
|
||||
tool=SpecificToolChoiceBlock(
|
||||
|
|
@ -284,6 +291,7 @@ class AmazonConverseConfig(BaseConfig):
|
|||
optional_params["tool_choice"] = _tool_choice_value
|
||||
if param == "thinking":
|
||||
optional_params["thinking"] = value
|
||||
|
||||
return optional_params
|
||||
|
||||
@overload
|
||||
|
|
|
|||
52
litellm/llms/gemini/common_utils.py
Normal file
52
litellm/llms/gemini/common_utils.py
Normal file
|
|
@ -0,0 +1,52 @@
|
|||
from typing import List, Optional
|
||||
|
||||
import litellm
|
||||
from litellm.llms.base_llm.base_utils import BaseLLMModelInfo
|
||||
from litellm.secret_managers.main import get_secret_str
|
||||
|
||||
|
||||
class GeminiModelInfo(BaseLLMModelInfo):
|
||||
@staticmethod
|
||||
def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
|
||||
return (
|
||||
api_base
|
||||
or get_secret_str("GEMINI_API_BASE")
|
||||
or "https://generativelanguage.googleapis.com/v1beta"
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
|
||||
return api_key or (get_secret_str("GEMINI_API_KEY"))
|
||||
|
||||
@staticmethod
|
||||
def get_base_model(model: str) -> Optional[str]:
|
||||
return model.replace("gemini/", "")
|
||||
|
||||
def get_models(
|
||||
self, api_key: Optional[str] = None, api_base: Optional[str] = None
|
||||
) -> List[str]:
|
||||
|
||||
api_base = GeminiModelInfo.get_api_base(api_base)
|
||||
api_key = GeminiModelInfo.get_api_key(api_key)
|
||||
if api_base is None or api_key is None:
|
||||
raise ValueError(
|
||||
"GEMINI_API_BASE or GEMINI_API_KEY is not set. Please set the environment variable, to query Gemini's `/models` endpoint."
|
||||
)
|
||||
|
||||
response = litellm.module_level_client.get(
|
||||
url=f"{api_base}/models?key={api_key}",
|
||||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
raise ValueError(
|
||||
f"Failed to fetch models from Gemini. Status code: {response.status_code}, Response: {response.json()}"
|
||||
)
|
||||
|
||||
models = response.json()["models"]
|
||||
|
||||
litellm_model_names = []
|
||||
for model in models:
|
||||
stripped_model_name = model["name"].strip("models/")
|
||||
litellm_model_name = "gemini/" + stripped_model_name
|
||||
litellm_model_names.append(litellm_model_name)
|
||||
return litellm_model_names
|
||||
|
|
@ -80,6 +80,7 @@ class MistralConfig(OpenAIGPTConfig):
|
|||
"temperature",
|
||||
"top_p",
|
||||
"max_tokens",
|
||||
"max_completion_tokens",
|
||||
"tools",
|
||||
"tool_choice",
|
||||
"seed",
|
||||
|
|
@ -105,6 +106,10 @@ class MistralConfig(OpenAIGPTConfig):
|
|||
for param, value in non_default_params.items():
|
||||
if param == "max_tokens":
|
||||
optional_params["max_tokens"] = value
|
||||
if (
|
||||
param == "max_completion_tokens"
|
||||
): # max_completion_tokens should take priority
|
||||
optional_params["max_tokens"] = value
|
||||
if param == "tools":
|
||||
optional_params["tools"] = value
|
||||
if param == "stream" and value is True:
|
||||
|
|
|
|||
|
|
@ -11,7 +11,9 @@ class TopazException(BaseLLMException):
|
|||
|
||||
|
||||
class TopazModelInfo(BaseLLMModelInfo):
|
||||
def get_models(self) -> List[str]:
|
||||
def get_models(
|
||||
self, api_key: Optional[str] = None, api_base: Optional[str] = None
|
||||
) -> List[str]:
|
||||
return [
|
||||
"topaz/Standard V2",
|
||||
"topaz/Low Resolution V2",
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import httpx
|
|||
|
||||
import litellm
|
||||
from litellm import supports_response_schema, supports_system_messages, verbose_logger
|
||||
from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
|
||||
from litellm.llms.base_llm.chat.transformation import BaseLLMException
|
||||
from litellm.types.llms.vertex_ai import PartType
|
||||
|
||||
|
|
@ -177,7 +178,7 @@ def _build_vertex_schema(parameters: dict):
|
|||
# * https://github.com/pydantic/pydantic/issues/1270
|
||||
# * https://stackoverflow.com/a/58841311
|
||||
# * https://github.com/pydantic/pydantic/discussions/4872
|
||||
convert_to_nullable(parameters)
|
||||
convert_anyof_null_to_nullable(parameters)
|
||||
add_object_type(parameters)
|
||||
# Postprocessing
|
||||
# 4. Suppress unnecessary title generation:
|
||||
|
|
@ -228,34 +229,43 @@ def unpack_defs(schema, defs):
|
|||
continue
|
||||
|
||||
|
||||
def convert_to_nullable(schema):
|
||||
anyof = schema.pop("anyOf", None)
|
||||
def convert_anyof_null_to_nullable(schema, depth=0):
|
||||
if depth > DEFAULT_MAX_RECURSE_DEPTH:
|
||||
raise ValueError(
|
||||
f"Max depth of {DEFAULT_MAX_RECURSE_DEPTH} exceeded while processing schema. Please check the schema for excessive nesting."
|
||||
)
|
||||
""" Converts null objects within anyOf by removing them and adding nullable to all remaining objects """
|
||||
anyof = schema.get("anyOf", None)
|
||||
if anyof is not None:
|
||||
if len(anyof) != 2:
|
||||
contains_null = False
|
||||
for atype in anyof:
|
||||
if atype == {"type": "null"}:
|
||||
# remove null type
|
||||
anyof.remove(atype)
|
||||
contains_null = True
|
||||
|
||||
if len(anyof) == 0:
|
||||
# Edge case: response schema with only null type present is invalid in Vertex AI
|
||||
raise ValueError(
|
||||
"Invalid input: Type Unions are not supported, except for `Optional` types. "
|
||||
"Please provide an `Optional` type or a non-Union type."
|
||||
"Invalid input: AnyOf schema with only null type is not supported. "
|
||||
"Please provide a non-null type."
|
||||
)
|
||||
a, b = anyof
|
||||
if a == {"type": "null"}:
|
||||
schema.update(b)
|
||||
elif b == {"type": "null"}:
|
||||
schema.update(a)
|
||||
else:
|
||||
raise ValueError(
|
||||
"Invalid input: Type Unions are not supported, except for `Optional` types. "
|
||||
"Please provide an `Optional` type or a non-Union type."
|
||||
)
|
||||
schema["nullable"] = True
|
||||
|
||||
|
||||
if contains_null:
|
||||
# set all types to nullable following guidance found here: https://cloud.google.com/vertex-ai/generative-ai/docs/samples/generativeaionvertexai-gemini-controlled-generation-response-schema-3#generativeaionvertexai_gemini_controlled_generation_response_schema_3-python
|
||||
for atype in anyof:
|
||||
atype["nullable"] = True
|
||||
|
||||
|
||||
properties = schema.get("properties", None)
|
||||
if properties is not None:
|
||||
for name, value in properties.items():
|
||||
convert_to_nullable(value)
|
||||
convert_anyof_null_to_nullable(value, depth=depth + 1)
|
||||
|
||||
items = schema.get("items", None)
|
||||
if items is not None:
|
||||
convert_to_nullable(items)
|
||||
convert_anyof_null_to_nullable(items, depth=depth + 1)
|
||||
|
||||
|
||||
def add_object_type(schema):
|
||||
|
|
|
|||
51
litellm/llms/xai/common_utils.py
Normal file
51
litellm/llms/xai/common_utils.py
Normal file
|
|
@ -0,0 +1,51 @@
|
|||
from typing import List, Optional
|
||||
|
||||
import httpx
|
||||
|
||||
import litellm
|
||||
from litellm.llms.base_llm.base_utils import BaseLLMModelInfo
|
||||
from litellm.secret_managers.main import get_secret_str
|
||||
|
||||
|
||||
class XAIModelInfo(BaseLLMModelInfo):
|
||||
@staticmethod
|
||||
def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
|
||||
return api_base or get_secret_str("XAI_API_BASE") or "https://api.x.ai"
|
||||
|
||||
@staticmethod
|
||||
def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
|
||||
return api_key or get_secret_str("XAI_API_KEY")
|
||||
|
||||
@staticmethod
|
||||
def get_base_model(model: str) -> Optional[str]:
|
||||
return model.replace("xai/", "")
|
||||
|
||||
def get_models(
|
||||
self, api_key: Optional[str] = None, api_base: Optional[str] = None
|
||||
) -> List[str]:
|
||||
api_base = self.get_api_base(api_base)
|
||||
api_key = self.get_api_key(api_key)
|
||||
if api_base is None or api_key is None:
|
||||
raise ValueError(
|
||||
"XAI_API_BASE or XAI_API_KEY is not set. Please set the environment variable, to query XAI's `/models` endpoint."
|
||||
)
|
||||
response = litellm.module_level_client.get(
|
||||
url=f"{api_base}/v1/models",
|
||||
headers={"Authorization": f"Bearer {api_key}"},
|
||||
)
|
||||
|
||||
try:
|
||||
response.raise_for_status()
|
||||
except httpx.HTTPStatusError:
|
||||
raise Exception(
|
||||
f"Failed to fetch models from XAI. Status code: {response.status_code}, Response: {response.text}"
|
||||
)
|
||||
|
||||
models = response.json()["data"]
|
||||
|
||||
litellm_model_names = []
|
||||
for model in models:
|
||||
stripped_model_name = model["id"]
|
||||
litellm_model_name = "xai/" + stripped_model_name
|
||||
litellm_model_names.append(litellm_model_name)
|
||||
return litellm_model_names
|
||||
File diff suppressed because one or more lines are too long
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|
|
@ -0,0 +1 @@
|
|||
(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[185],{96443:function(n,e,t){Promise.resolve().then(t.t.bind(t,39974,23)),Promise.resolve().then(t.t.bind(t,2778,23))},2778:function(){},39974:function(n){n.exports={style:{fontFamily:"'__Inter_cf7686', '__Inter_Fallback_cf7686'",fontStyle:"normal"},className:"__className_cf7686"}}},function(n){n.O(0,[919,986,971,117,744],function(){return n(n.s=96443)}),_N_E=n.O()}]);
|
||||
|
|
@ -1 +0,0 @@
|
|||
(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[185],{6580:function(n,e,t){Promise.resolve().then(t.t.bind(t,39974,23)),Promise.resolve().then(t.t.bind(t,2778,23))},2778:function(){},39974:function(n){n.exports={style:{fontFamily:"'__Inter_cf7686', '__Inter_Fallback_cf7686'",fontStyle:"normal"},className:"__className_cf7686"}}},function(n){n.O(0,[919,986,971,117,744],function(){return n(n.s=6580)}),_N_E=n.O()}]);
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||||
|
|
@ -1 +1 @@
|
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(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[418],{11790:function(e,n,u){Promise.resolve().then(u.bind(u,52829))},52829:function(e,n,u){"use strict";u.r(n),u.d(n,{default:function(){return f}});var t=u(57437),s=u(2265),r=u(99376),c=u(92699);function f(){let e=(0,r.useSearchParams)().get("key"),[n,u]=(0,s.useState)(null);return(0,s.useEffect)(()=>{e&&u(e)},[e]),(0,t.jsx)(c.Z,{accessToken:n,publicPage:!0,premiumUser:!1})}}},function(e){e.O(0,[42,261,250,699,971,117,744],function(){return e(e.s=11790)}),_N_E=e.O()}]);
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|
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@ -1 +0,0 @@
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3:I[12011,["665","static/chunks/3014691f-0b72c78cfebbd712.js","42","static/chunks/42-1cbed529ecb084e0.js","899","static/chunks/899-9af4feaf6f21839c.js","250","static/chunks/250-a75ee9d79f1140b0.js","461","static/chunks/app/onboarding/page-1ffe69692e4b2037.js"],"default",1]
|
||||
3:I[12011,["665","static/chunks/3014691f-0b72c78cfebbd712.js","42","static/chunks/42-1cbed529ecb084e0.js","899","static/chunks/899-9af4feaf6f21839c.js","250","static/chunks/250-601568e45a5ffece.js","461","static/chunks/app/onboarding/page-5110f2c6a3c9a2f4.js"],"default",1]
|
||||
4:I[4707,[],""]
|
||||
5:I[36423,[],""]
|
||||
0:["9yIyUkG6nV2cO0gn7kJ-Q",[[["",{"children":["onboarding",{"children":["__PAGE__",{}]}]},"$undefined","$undefined",true],["",{"children":["onboarding",{"children":["__PAGE__",{},[["$L1",["$","$L2",null,{"props":{"params":{},"searchParams":{}},"Component":"$3"}],null],null],null]},[null,["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children","onboarding","children"],"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","notFoundStyles":"$undefined"}]],null]},[[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/86f6cc749f6b8493.css","precedence":"next","crossOrigin":"$undefined"}],["$","link","1",{"rel":"stylesheet","href":"/ui/_next/static/css/169f9187db1ec37e.css","precedence":"next","crossOrigin":"$undefined"}]],["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_cf7686","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[]}]}]}]],null],null],["$L6",null]]]]
|
||||
0:["soi--ciJeUE6G2Fk4NMBG",[[["",{"children":["onboarding",{"children":["__PAGE__",{}]}]},"$undefined","$undefined",true],["",{"children":["onboarding",{"children":["__PAGE__",{},[["$L1",["$","$L2",null,{"props":{"params":{},"searchParams":{}},"Component":"$3"}],null],null],null]},[null,["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children","onboarding","children"],"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":"$undefined","notFoundStyles":"$undefined"}]],null]},[[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/86f6cc749f6b8493.css","precedence":"next","crossOrigin":"$undefined"}],["$","link","1",{"rel":"stylesheet","href":"/ui/_next/static/css/169f9187db1ec37e.css","precedence":"next","crossOrigin":"$undefined"}]],["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_cf7686","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[]}]}]}]],null],null],["$L6",null]]]]
|
||||
6:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"LiteLLM Dashboard"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
|
|
|||
|
|
@ -19,19 +19,11 @@ model_list:
|
|||
|
||||
litellm_settings:
|
||||
num_retries: 0
|
||||
callbacks: ["prometheus"]
|
||||
json_logs: true
|
||||
|
||||
router_settings:
|
||||
routing_strategy: usage-based-routing-v2 # 👈 KEY CHANGE
|
||||
redis_host: os.environ/REDIS_HOST
|
||||
redis_password: os.environ/REDIS_PASSWORD
|
||||
redis_port: os.environ/REDIS_PORT
|
||||
|
||||
general_settings:
|
||||
enable_jwt_auth: True
|
||||
litellm_jwtauth:
|
||||
admin_jwt_scope: "ai.admin"
|
||||
# team_id_jwt_field: "client_id" # 👈 CAN BE ANY FIELD
|
||||
user_id_jwt_field: "sub" # 👈 CAN BE ANY FIELD
|
||||
org_id_jwt_field: "org_id" # 👈 CAN BE ANY FIELD
|
||||
end_user_id_jwt_field: "customer_id" # 👈 CAN BE ANY FIELD
|
||||
user_id_upsert: True
|
||||
|
|
@ -2733,6 +2733,7 @@ class DailyUserSpendTransaction(TypedDict):
|
|||
prompt_tokens: int
|
||||
completion_tokens: int
|
||||
spend: float
|
||||
api_requests: int
|
||||
|
||||
|
||||
class DBSpendUpdateTransactions(TypedDict):
|
||||
|
|
|
|||
|
|
@ -3,6 +3,7 @@ This file contains the PrismaWrapper class, which is used to wrap the Prisma cli
|
|||
"""
|
||||
|
||||
import asyncio
|
||||
import glob
|
||||
import os
|
||||
import random
|
||||
import subprocess
|
||||
|
|
@ -178,6 +179,69 @@ class PrismaManager:
|
|||
verbose_proxy_logger.warning(f"Error creating baseline migration: {e}")
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def _copy_spend_tracking_migrations(prisma_dir: str) -> bool:
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
|
||||
"""
|
||||
Check for and copy over spend tracking migrations if they exist in the deploy directory.
|
||||
Returns True if migrations were found and copied, False otherwise.
|
||||
"""
|
||||
try:
|
||||
# Get the current file's directory
|
||||
current_dir = Path(__file__).parent
|
||||
|
||||
# Check for migrations in the deploy directory (../../deploy/migrations)
|
||||
deploy_migrations_dir = (
|
||||
current_dir.parent.parent.parent / "deploy" / "migrations"
|
||||
)
|
||||
|
||||
# Local migrations directory
|
||||
local_migrations_dir = Path(prisma_dir + "/migrations")
|
||||
|
||||
if deploy_migrations_dir.exists():
|
||||
# Create local migrations directory if it doesn't exist
|
||||
local_migrations_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Copy all migration files
|
||||
# Copy entire migrations folder recursively
|
||||
shutil.copytree(
|
||||
deploy_migrations_dir, local_migrations_dir, dirs_exist_ok=True
|
||||
)
|
||||
|
||||
return True
|
||||
return False
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def _get_migration_names(migrations_dir: str) -> list:
|
||||
"""Get all migration directory names from the migrations folder"""
|
||||
migration_paths = glob.glob(f"{migrations_dir}/*/migration.sql")
|
||||
return [Path(p).parent.name for p in migration_paths]
|
||||
|
||||
@staticmethod
|
||||
def _resolve_all_migrations(migrations_dir: str):
|
||||
"""Mark all existing migrations as applied"""
|
||||
migration_names = PrismaManager._get_migration_names(migrations_dir)
|
||||
for migration_name in migration_names:
|
||||
try:
|
||||
verbose_proxy_logger.info(f"Resolving migration: {migration_name}")
|
||||
subprocess.run(
|
||||
["prisma", "migrate", "resolve", "--applied", migration_name],
|
||||
timeout=60,
|
||||
check=True,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
)
|
||||
verbose_proxy_logger.debug(f"Resolved migration: {migration_name}")
|
||||
except subprocess.CalledProcessError as e:
|
||||
if "is already recorded as applied in the database." not in e.stderr:
|
||||
verbose_proxy_logger.warning(
|
||||
f"Failed to resolve migration {migration_name}: {e.stderr}"
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def setup_database(use_migrate: bool = False) -> bool:
|
||||
"""
|
||||
|
|
@ -194,8 +258,10 @@ class PrismaManager:
|
|||
os.chdir(prisma_dir)
|
||||
try:
|
||||
if use_migrate:
|
||||
PrismaManager._copy_spend_tracking_migrations(
|
||||
prisma_dir
|
||||
) # place a migration in the migrations directory
|
||||
verbose_proxy_logger.info("Running prisma migrate deploy")
|
||||
# First try to run migrate deploy directly
|
||||
try:
|
||||
subprocess.run(
|
||||
["prisma", "migrate", "deploy"],
|
||||
|
|
@ -205,25 +271,31 @@ class PrismaManager:
|
|||
text=True,
|
||||
)
|
||||
verbose_proxy_logger.info("prisma migrate deploy completed")
|
||||
|
||||
# Resolve all migrations in the migrations directory
|
||||
migrations_dir = os.path.join(prisma_dir, "migrations")
|
||||
PrismaManager._resolve_all_migrations(migrations_dir)
|
||||
|
||||
return True
|
||||
except subprocess.CalledProcessError as e:
|
||||
# Check if this is the non-empty schema error
|
||||
verbose_proxy_logger.warning(
|
||||
f"prisma db error: {e.stderr}, e: {e.stdout}"
|
||||
)
|
||||
if (
|
||||
"P3005" in e.stderr
|
||||
and "database schema is not empty" in e.stderr
|
||||
):
|
||||
# Create baseline migration
|
||||
verbose_proxy_logger.info("Creating baseline migration")
|
||||
if PrismaManager._create_baseline_migration(schema_path):
|
||||
# Try migrate deploy again after baseline
|
||||
subprocess.run(
|
||||
["prisma", "migrate", "deploy"],
|
||||
timeout=60,
|
||||
check=True,
|
||||
verbose_proxy_logger.info(
|
||||
"Resolving all migrations after baseline"
|
||||
)
|
||||
|
||||
# Resolve all migrations after baseline
|
||||
migrations_dir = os.path.join(prisma_dir, "migrations")
|
||||
PrismaManager._resolve_all_migrations(migrations_dir)
|
||||
|
||||
return True
|
||||
else:
|
||||
# If it's a different error, raise it
|
||||
raise e
|
||||
else:
|
||||
# Use prisma db push with increased timeout
|
||||
subprocess.run(
|
||||
|
|
|
|||
|
|
@ -14,8 +14,9 @@ These are members of a Team on LiteLLM
|
|||
import asyncio
|
||||
import traceback
|
||||
import uuid
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from typing import Any, List, Optional, Union, cast
|
||||
from datetime import date, datetime, timedelta, timezone
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, TypedDict, Union, cast
|
||||
|
||||
import fastapi
|
||||
from fastapi import APIRouter, Depends, Header, HTTPException, Request, status
|
||||
|
|
@ -1242,3 +1243,291 @@ async def ui_view_users(
|
|||
except Exception as e:
|
||||
verbose_proxy_logger.exception(f"Error searching users: {str(e)}")
|
||||
raise HTTPException(status_code=500, detail=f"Error searching users: {str(e)}")
|
||||
|
||||
|
||||
class GroupByDimension(str, Enum):
|
||||
DATE = "date"
|
||||
MODEL = "model"
|
||||
API_KEY = "api_key"
|
||||
TEAM = "team"
|
||||
ORGANIZATION = "organization"
|
||||
MODEL_GROUP = "model_group"
|
||||
PROVIDER = "custom_llm_provider"
|
||||
|
||||
|
||||
class SpendMetrics(BaseModel):
|
||||
spend: float = Field(default=0.0)
|
||||
prompt_tokens: int = Field(default=0)
|
||||
completion_tokens: int = Field(default=0)
|
||||
total_tokens: int = Field(default=0)
|
||||
api_requests: int = Field(default=0)
|
||||
|
||||
|
||||
class BreakdownMetrics(BaseModel):
|
||||
"""Breakdown of spend by different dimensions"""
|
||||
|
||||
models: Dict[str, SpendMetrics] = Field(default_factory=dict) # model -> metrics
|
||||
providers: Dict[str, SpendMetrics] = Field(
|
||||
default_factory=dict
|
||||
) # provider -> metrics
|
||||
api_keys: Dict[str, SpendMetrics] = Field(
|
||||
default_factory=dict
|
||||
) # api_key -> metrics
|
||||
|
||||
|
||||
class DailySpendData(BaseModel):
|
||||
date: date
|
||||
metrics: SpendMetrics
|
||||
breakdown: BreakdownMetrics = Field(default_factory=BreakdownMetrics)
|
||||
|
||||
|
||||
class DailySpendMetadata(BaseModel):
|
||||
total_spend: float = Field(default=0.0)
|
||||
total_prompt_tokens: int = Field(default=0)
|
||||
total_completion_tokens: int = Field(default=0)
|
||||
total_api_requests: int = Field(default=0)
|
||||
page: int = Field(default=1)
|
||||
total_pages: int = Field(default=1)
|
||||
has_more: bool = Field(default=False)
|
||||
|
||||
|
||||
class SpendAnalyticsPaginatedResponse(BaseModel):
|
||||
results: List[DailySpendData]
|
||||
metadata: DailySpendMetadata = Field(default_factory=DailySpendMetadata)
|
||||
|
||||
|
||||
class LiteLLM_DailyUserSpend(BaseModel):
|
||||
id: str
|
||||
user_id: str
|
||||
date: str
|
||||
api_key: str
|
||||
model: str
|
||||
model_group: Optional[str] = None
|
||||
custom_llm_provider: Optional[str] = None
|
||||
prompt_tokens: int = 0
|
||||
completion_tokens: int = 0
|
||||
spend: float = 0.0
|
||||
api_requests: int = 0
|
||||
|
||||
|
||||
class GroupedData(TypedDict):
|
||||
metrics: SpendMetrics
|
||||
breakdown: BreakdownMetrics
|
||||
|
||||
|
||||
def update_metrics(
|
||||
group_metrics: SpendMetrics, record: LiteLLM_DailyUserSpend
|
||||
) -> SpendMetrics:
|
||||
group_metrics.spend += record.spend
|
||||
group_metrics.prompt_tokens += record.prompt_tokens
|
||||
group_metrics.completion_tokens += record.completion_tokens
|
||||
group_metrics.total_tokens += record.prompt_tokens + record.completion_tokens
|
||||
group_metrics.api_requests += record.api_requests
|
||||
return group_metrics
|
||||
|
||||
|
||||
def update_breakdown_metrics(
|
||||
breakdown: BreakdownMetrics, record: LiteLLM_DailyUserSpend
|
||||
) -> BreakdownMetrics:
|
||||
"""Updates breakdown metrics for a single record using the existing update_metrics function"""
|
||||
|
||||
# Update model breakdown
|
||||
if record.model not in breakdown.models:
|
||||
breakdown.models[record.model] = SpendMetrics()
|
||||
breakdown.models[record.model] = update_metrics(
|
||||
breakdown.models[record.model], record
|
||||
)
|
||||
|
||||
# Update provider breakdown
|
||||
provider = record.custom_llm_provider or "unknown"
|
||||
if provider not in breakdown.providers:
|
||||
breakdown.providers[provider] = SpendMetrics()
|
||||
breakdown.providers[provider] = update_metrics(
|
||||
breakdown.providers[provider], record
|
||||
)
|
||||
|
||||
# Update api key breakdown
|
||||
if record.api_key not in breakdown.api_keys:
|
||||
breakdown.api_keys[record.api_key] = SpendMetrics()
|
||||
breakdown.api_keys[record.api_key] = update_metrics(
|
||||
breakdown.api_keys[record.api_key], record
|
||||
)
|
||||
|
||||
return breakdown
|
||||
|
||||
|
||||
@router.get(
|
||||
"/user/daily/activity",
|
||||
tags=["Budget & Spend Tracking", "Internal User management"],
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
response_model=SpendAnalyticsPaginatedResponse,
|
||||
)
|
||||
async def get_user_daily_activity(
|
||||
start_date: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="Start date in YYYY-MM-DD format",
|
||||
),
|
||||
end_date: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="End date in YYYY-MM-DD format",
|
||||
),
|
||||
group_by: List[GroupByDimension] = fastapi.Query(
|
||||
default=[GroupByDimension.DATE],
|
||||
description="Dimensions to group by. Can combine multiple (e.g. date,team)",
|
||||
),
|
||||
view_by: Literal["team", "organization", "user"] = fastapi.Query(
|
||||
default="user",
|
||||
description="View spend at team/org/user level",
|
||||
),
|
||||
team_id: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="Filter by specific team",
|
||||
),
|
||||
org_id: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="Filter by specific organization",
|
||||
),
|
||||
model: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="Filter by specific model",
|
||||
),
|
||||
api_key: Optional[str] = fastapi.Query(
|
||||
default=None,
|
||||
description="Filter by specific API key",
|
||||
),
|
||||
page: int = fastapi.Query(
|
||||
default=1, description="Page number for pagination", ge=1
|
||||
),
|
||||
page_size: int = fastapi.Query(
|
||||
default=50, description="Items per page", ge=1, le=100
|
||||
),
|
||||
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
|
||||
) -> SpendAnalyticsPaginatedResponse:
|
||||
"""
|
||||
[BETA] This is a beta endpoint. It will change.
|
||||
|
||||
Meant to optimize querying spend data for analytics for a user.
|
||||
|
||||
Returns:
|
||||
(by date/team/org/user/model/api_key/model_group/provider)
|
||||
- spend
|
||||
- prompt_tokens
|
||||
- completion_tokens
|
||||
- total_tokens
|
||||
- api_requests
|
||||
- breakdown by team, organization, user, model, api_key, model_group, provider
|
||||
"""
|
||||
from litellm.proxy.proxy_server import prisma_client
|
||||
|
||||
if prisma_client is None:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={"error": CommonProxyErrors.db_not_connected_error.value},
|
||||
)
|
||||
|
||||
if start_date is None or end_date is None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail={"error": "Please provide start_date and end_date"},
|
||||
)
|
||||
|
||||
try:
|
||||
# Build filter conditions
|
||||
where_conditions: Dict[str, Any] = {
|
||||
"date": {
|
||||
"gte": start_date,
|
||||
"lte": end_date,
|
||||
}
|
||||
}
|
||||
|
||||
if team_id:
|
||||
where_conditions["team_id"] = team_id
|
||||
if org_id:
|
||||
where_conditions["organization_id"] = org_id
|
||||
if model:
|
||||
where_conditions["model"] = model
|
||||
if api_key:
|
||||
where_conditions["api_key"] = api_key
|
||||
|
||||
# Get total count for pagination
|
||||
total_count = await prisma_client.db.litellm_dailyuserspend.count(
|
||||
where=where_conditions
|
||||
)
|
||||
|
||||
# Fetch paginated results
|
||||
daily_spend_data = await prisma_client.db.litellm_dailyuserspend.find_many(
|
||||
where=where_conditions,
|
||||
order=[
|
||||
{"date": "desc"},
|
||||
],
|
||||
skip=(page - 1) * page_size,
|
||||
take=page_size,
|
||||
)
|
||||
|
||||
# Process results
|
||||
results = []
|
||||
total_metrics = SpendMetrics()
|
||||
|
||||
# Group data by date and other dimensions
|
||||
|
||||
grouped_data: Dict[str, Dict[str, Any]] = {}
|
||||
for record in daily_spend_data:
|
||||
date_str = record.date
|
||||
if date_str not in grouped_data:
|
||||
grouped_data[date_str] = {
|
||||
"metrics": SpendMetrics(),
|
||||
"breakdown": BreakdownMetrics(),
|
||||
}
|
||||
|
||||
# Update metrics
|
||||
grouped_data[date_str]["metrics"] = update_metrics(
|
||||
grouped_data[date_str]["metrics"], record
|
||||
)
|
||||
# Update breakdowns
|
||||
grouped_data[date_str]["breakdown"] = update_breakdown_metrics(
|
||||
grouped_data[date_str]["breakdown"], record
|
||||
)
|
||||
|
||||
# Update total metrics
|
||||
total_metrics.spend += record.spend
|
||||
total_metrics.prompt_tokens += record.prompt_tokens
|
||||
total_metrics.completion_tokens += record.completion_tokens
|
||||
total_metrics.total_tokens += (
|
||||
record.prompt_tokens + record.completion_tokens
|
||||
)
|
||||
total_metrics.api_requests += 1
|
||||
|
||||
# Convert grouped data to response format
|
||||
for date_str, data in grouped_data.items():
|
||||
results.append(
|
||||
DailySpendData(
|
||||
date=datetime.strptime(date_str, "%Y-%m-%d").date(),
|
||||
metrics=data["metrics"],
|
||||
breakdown=data["breakdown"],
|
||||
)
|
||||
)
|
||||
|
||||
# Sort results by date
|
||||
results.sort(key=lambda x: x.date, reverse=True)
|
||||
|
||||
return SpendAnalyticsPaginatedResponse(
|
||||
results=results,
|
||||
metadata=DailySpendMetadata(
|
||||
total_spend=total_metrics.spend,
|
||||
total_prompt_tokens=total_metrics.prompt_tokens,
|
||||
total_completion_tokens=total_metrics.completion_tokens,
|
||||
total_api_requests=total_metrics.api_requests,
|
||||
page=page,
|
||||
total_pages=-(-total_count // page_size), # Ceiling division
|
||||
has_more=(page * page_size) < total_count,
|
||||
),
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
verbose_proxy_logger.exception(
|
||||
"/spend/daily/analytics: Exception occured - {}".format(str(e))
|
||||
)
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||||
detail={"error": f"Failed to fetch analytics: {str(e)}"},
|
||||
)
|
||||
|
|
|
|||
|
|
@ -405,9 +405,24 @@ class ModelManagementAuthChecks:
|
|||
model_params.model_info is not None
|
||||
and model_params.model_info.team_id is not None
|
||||
):
|
||||
team_obj_row = await prisma_client.db.litellm_teamtable.find_unique(
|
||||
where={"team_id": model_params.model_info.team_id}
|
||||
)
|
||||
if team_obj_row is None:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail={
|
||||
"error": "Team id={} does not exist in db".format(
|
||||
model_params.model_info.team_id
|
||||
)
|
||||
},
|
||||
)
|
||||
team_obj = LiteLLM_TeamTable(**team_obj_row.model_dump())
|
||||
|
||||
return ModelManagementAuthChecks.can_user_make_team_model_call(
|
||||
team_id=model_params.model_info.team_id,
|
||||
user_api_key_dict=user_api_key_dict,
|
||||
team_obj=team_obj,
|
||||
premium_user=premium_user,
|
||||
)
|
||||
## Check non-team model auth
|
||||
|
|
|
|||
|
|
@ -24,6 +24,7 @@ from typing import (
|
|||
get_type_hints,
|
||||
)
|
||||
|
||||
from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
|
||||
from litellm.types.utils import (
|
||||
ModelResponse,
|
||||
ModelResponseStream,
|
||||
|
|
@ -462,6 +463,8 @@ async def proxy_startup_event(app: FastAPI):
|
|||
if premium_user is False:
|
||||
premium_user = _license_check.is_premium()
|
||||
|
||||
## CHECK MASTER KEY IN ENVIRONMENT ##
|
||||
master_key = get_secret_str("LITELLM_MASTER_KEY")
|
||||
### LOAD CONFIG ###
|
||||
worker_config: Optional[Union[str, dict]] = get_secret("WORKER_CONFIG") # type: ignore
|
||||
env_config_yaml: Optional[str] = get_secret_str("CONFIG_FILE_PATH")
|
||||
|
|
@ -509,9 +512,6 @@ async def proxy_startup_event(app: FastAPI):
|
|||
if isinstance(worker_config, dict):
|
||||
await initialize(**worker_config)
|
||||
|
||||
### LOAD MASTER KEY ###
|
||||
# check if master key set in environment - load from there
|
||||
master_key = get_secret("LITELLM_MASTER_KEY", None) # type: ignore
|
||||
# check if DATABASE_URL in environment - load from there
|
||||
if prisma_client is None:
|
||||
_db_url: Optional[str] = get_secret("DATABASE_URL", None) # type: ignore
|
||||
|
|
@ -1320,7 +1320,7 @@ class ProxyConfig:
|
|||
yaml.dump(new_config, config_file, default_flow_style=False)
|
||||
|
||||
def _check_for_os_environ_vars(
|
||||
self, config: dict, depth: int = 0, max_depth: int = 10
|
||||
self, config: dict, depth: int = 0, max_depth: int = DEFAULT_MAX_RECURSE_DEPTH
|
||||
) -> dict:
|
||||
"""
|
||||
Check for os.environ/ variables in the config and replace them with the actual values.
|
||||
|
|
@ -1769,6 +1769,7 @@ class ProxyConfig:
|
|||
|
||||
if master_key and master_key.startswith("os.environ/"):
|
||||
master_key = get_secret(master_key) # type: ignore
|
||||
|
||||
if not isinstance(master_key, str):
|
||||
raise Exception(
|
||||
"Master key must be a string. Current type - {}".format(
|
||||
|
|
@ -3231,6 +3232,7 @@ async def model_list(
|
|||
else:
|
||||
proxy_model_list = llm_router.get_model_names()
|
||||
model_access_groups = llm_router.get_model_access_groups()
|
||||
|
||||
key_models = get_key_models(
|
||||
user_api_key_dict=user_api_key_dict,
|
||||
proxy_model_list=proxy_model_list,
|
||||
|
|
@ -3240,6 +3242,7 @@ async def model_list(
|
|||
team_models: List[str] = user_api_key_dict.team_models
|
||||
|
||||
if team_id:
|
||||
key_models = []
|
||||
team_object = await get_team_object(
|
||||
team_id=team_id,
|
||||
prisma_client=prisma_client,
|
||||
|
|
@ -3256,7 +3259,7 @@ async def model_list(
|
|||
)
|
||||
|
||||
all_models = get_complete_model_list(
|
||||
key_models=key_models if not team_models else [],
|
||||
key_models=key_models,
|
||||
team_models=team_models,
|
||||
proxy_model_list=proxy_model_list,
|
||||
user_model=user_model,
|
||||
|
|
@ -6690,6 +6693,14 @@ async def login(request: Request): # noqa: PLR0915
|
|||
user_email = getattr(_user_row, "user_email", "unknown")
|
||||
_password = getattr(_user_row, "password", "unknown")
|
||||
|
||||
if _password is None:
|
||||
raise ProxyException(
|
||||
message="User has no password set. Please set a password for the user via `/user/update`.",
|
||||
type=ProxyErrorTypes.auth_error,
|
||||
param="password",
|
||||
code=status.HTTP_401_UNAUTHORIZED,
|
||||
)
|
||||
|
||||
# check if password == _user_row.password
|
||||
hash_password = hash_token(token=password)
|
||||
if secrets.compare_digest(password, _password) or secrets.compare_digest(
|
||||
|
|
|
|||
|
|
@ -314,19 +314,19 @@ model LiteLLM_AuditLog {
|
|||
updated_values Json? // value of the row after change
|
||||
}
|
||||
|
||||
|
||||
// Track daily user spend metrics per model and key
|
||||
model LiteLLM_DailyUserSpend {
|
||||
id String @id @default(uuid())
|
||||
user_id String
|
||||
date String
|
||||
api_key String // Hashed API Token
|
||||
model String // The specific model used
|
||||
model_group String? // public model_name / model_group
|
||||
custom_llm_provider String? // The LLM provider (e.g., "openai", "anthropic")
|
||||
api_key String
|
||||
model String
|
||||
model_group String?
|
||||
custom_llm_provider String?
|
||||
prompt_tokens Int @default(0)
|
||||
completion_tokens Int @default(0)
|
||||
spend Float @default(0.0)
|
||||
api_requests Int @default(0)
|
||||
created_at DateTime @default(now())
|
||||
updated_at DateTime @updatedAt
|
||||
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ import collections
|
|||
import os
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from functools import lru_cache
|
||||
from typing import TYPE_CHECKING, Any, List, Optional
|
||||
from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional
|
||||
|
||||
import fastapi
|
||||
from fastapi import APIRouter, Depends, HTTPException, status
|
||||
|
|
|
|||
|
|
@ -1182,6 +1182,7 @@ class PrismaClient:
|
|||
daily_transaction["spend"] += payload["spend"]
|
||||
daily_transaction["prompt_tokens"] += payload["prompt_tokens"]
|
||||
daily_transaction["completion_tokens"] += payload["completion_tokens"]
|
||||
daily_transaction["api_requests"] += 1
|
||||
else:
|
||||
daily_transaction = DailyUserSpendTransaction(
|
||||
user_id=payload["user"],
|
||||
|
|
@ -1193,6 +1194,7 @@ class PrismaClient:
|
|||
prompt_tokens=payload["prompt_tokens"],
|
||||
completion_tokens=payload["completion_tokens"],
|
||||
spend=payload["spend"],
|
||||
api_requests=1,
|
||||
)
|
||||
|
||||
self.daily_user_spend_transactions[daily_transaction_key] = (
|
||||
|
|
@ -2601,6 +2603,7 @@ class ProxyUpdateSpend:
|
|||
"completion_tokens"
|
||||
],
|
||||
"spend": transaction["spend"],
|
||||
"api_requests": transaction["api_requests"],
|
||||
},
|
||||
"update": {
|
||||
"prompt_tokens": {
|
||||
|
|
@ -2612,6 +2615,9 @@ class ProxyUpdateSpend:
|
|||
]
|
||||
},
|
||||
"spend": {"increment": transaction["spend"]},
|
||||
"api_requests": {
|
||||
"increment": transaction["api_requests"]
|
||||
},
|
||||
},
|
||||
},
|
||||
)
|
||||
|
|
|
|||
|
|
@ -5744,13 +5744,15 @@ def trim_messages(
|
|||
return messages
|
||||
|
||||
|
||||
def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
|
||||
def get_valid_models(
|
||||
check_provider_endpoint: bool = False, custom_llm_provider: Optional[str] = None
|
||||
) -> List[str]:
|
||||
"""
|
||||
Returns a list of valid LLMs based on the set environment variables
|
||||
|
||||
Args:
|
||||
check_provider_endpoint: If True, will check the provider's endpoint for valid models.
|
||||
|
||||
custom_llm_provider: If provided, will only check the provider's endpoint for valid models.
|
||||
Returns:
|
||||
A list of valid LLMs
|
||||
"""
|
||||
|
|
@ -5762,6 +5764,9 @@ def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
|
|||
valid_models = []
|
||||
|
||||
for provider in litellm.provider_list:
|
||||
if custom_llm_provider and provider != custom_llm_provider:
|
||||
continue
|
||||
|
||||
# edge case litellm has together_ai as a provider, it should be togetherai
|
||||
env_provider_1 = provider.replace("_", "")
|
||||
env_provider_2 = provider
|
||||
|
|
@ -5783,10 +5788,17 @@ def get_valid_models(check_provider_endpoint: bool = False) -> List[str]:
|
|||
provider=LlmProviders(provider),
|
||||
)
|
||||
|
||||
if custom_llm_provider and provider != custom_llm_provider:
|
||||
continue
|
||||
|
||||
if provider == "azure":
|
||||
valid_models.append("Azure-LLM")
|
||||
elif provider_config is not None and check_provider_endpoint:
|
||||
valid_models.extend(provider_config.get_models())
|
||||
try:
|
||||
models = provider_config.get_models()
|
||||
valid_models.extend(models)
|
||||
except Exception as e:
|
||||
verbose_logger.debug(f"Error getting valid models: {e}")
|
||||
else:
|
||||
models_for_provider = litellm.models_by_provider.get(provider, [])
|
||||
valid_models.extend(models_for_provider)
|
||||
|
|
@ -6400,10 +6412,16 @@ class ProviderConfigManager:
|
|||
return litellm.FireworksAIConfig()
|
||||
elif LlmProviders.OPENAI == provider:
|
||||
return litellm.OpenAIGPTConfig()
|
||||
elif LlmProviders.GEMINI == provider:
|
||||
return litellm.GeminiModelInfo()
|
||||
elif LlmProviders.LITELLM_PROXY == provider:
|
||||
return litellm.LiteLLMProxyChatConfig()
|
||||
elif LlmProviders.TOPAZ == provider:
|
||||
return litellm.TopazModelInfo()
|
||||
elif LlmProviders.ANTHROPIC == provider:
|
||||
return litellm.AnthropicModelInfo()
|
||||
elif LlmProviders.XAI == provider:
|
||||
return litellm.XAIModelInfo()
|
||||
|
||||
return None
|
||||
|
||||
|
|
|
|||
444
poetry.lock
generated
444
poetry.lock
generated
File diff suppressed because it is too large
Load diff
|
|
@ -99,6 +99,11 @@ mypy = "^1.0"
|
|||
pytest = "^7.4.3"
|
||||
pytest-mock = "^3.12.0"
|
||||
pytest-asyncio = "^0.21.1"
|
||||
respx = "^0.20.2"
|
||||
|
||||
[tool.poetry.group.proxy-dev.dependencies]
|
||||
prisma = "0.11.0"
|
||||
hypercorn = "^0.15.0"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core", "wheel"]
|
||||
|
|
|
|||
|
|
@ -326,6 +326,7 @@ model LiteLLM_DailyUserSpend {
|
|||
prompt_tokens Int @default(0)
|
||||
completion_tokens Int @default(0)
|
||||
spend Float @default(0.0)
|
||||
api_requests Int @default(0)
|
||||
created_at DateTime @default(now())
|
||||
updated_at DateTime @updatedAt
|
||||
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ IGNORE_FUNCTIONS = [
|
|||
"_check_for_os_environ_vars",
|
||||
"clean_message",
|
||||
"unpack_defs",
|
||||
"convert_to_nullable",
|
||||
"convert_anyof_null_to_nullable", # has a set max depth
|
||||
"add_object_type",
|
||||
"strip_field",
|
||||
"_transform_prompt",
|
||||
|
|
@ -76,15 +76,26 @@ def find_recursive_functions_in_directory(directory):
|
|||
ignored_recursive_functions[file_path] = ignored
|
||||
return recursive_functions, ignored_recursive_functions
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Example usage
|
||||
# raise exception if any recursive functions are found, except for the ignored ones
|
||||
# this is used in the CI/CD pipeline to prevent recursive functions from being merged
|
||||
|
||||
# Example usage
|
||||
directory_path = "./litellm"
|
||||
recursive_functions, ignored_recursive_functions = (
|
||||
find_recursive_functions_in_directory(directory_path)
|
||||
)
|
||||
print("ALL RECURSIVE FUNCTIONS: ", recursive_functions)
|
||||
print("IGNORED RECURSIVE FUNCTIONS: ", ignored_recursive_functions)
|
||||
if len(recursive_functions) > 0:
|
||||
raise Exception(
|
||||
f"🚨 Recursive functions found in {file}: {functions}. THIS IS REALLY BAD, it has caused CPU Usage spikes in the past. Only keep this if it's ABSOLUTELY necessary."
|
||||
directory_path = "./litellm"
|
||||
recursive_functions, ignored_recursive_functions = (
|
||||
find_recursive_functions_in_directory(directory_path)
|
||||
)
|
||||
print("UNIGNORED RECURSIVE FUNCTIONS: ", recursive_functions)
|
||||
print("IGNORED RECURSIVE FUNCTIONS: ", ignored_recursive_functions)
|
||||
|
||||
if len(recursive_functions) > 0:
|
||||
# raise exception if any recursive functions are found
|
||||
for file, functions in recursive_functions.items():
|
||||
print(
|
||||
f"🚨 Unignored recursive functions found in {file}: {functions}. THIS IS REALLY BAD, it has caused CPU Usage spikes in the past. Only keep this if it's ABSOLUTELY necessary."
|
||||
)
|
||||
file, functions = list(recursive_functions.items())[0]
|
||||
raise Exception(
|
||||
f"🚨 Unignored recursive functions found include {file}: {functions}. THIS IS REALLY BAD, it has caused CPU Usage spikes in the past. Only keep this if it's ABSOLUTELY necessary."
|
||||
)
|
||||
|
||||
|
|
|
|||
63
tests/litellm/conftest.py
Normal file
63
tests/litellm/conftest.py
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
# conftest.py
|
||||
|
||||
import importlib
|
||||
import os
|
||||
import sys
|
||||
|
||||
import pytest
|
||||
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../..")
|
||||
) # Adds the parent directory to the system path
|
||||
import litellm
|
||||
|
||||
|
||||
@pytest.fixture(scope="function", autouse=True)
|
||||
def setup_and_teardown():
|
||||
"""
|
||||
This fixture reloads litellm before every function. To speed up testing by removing callbacks being chained.
|
||||
"""
|
||||
curr_dir = os.getcwd() # Get the current working directory
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../..")
|
||||
) # Adds the project directory to the system path
|
||||
|
||||
import litellm
|
||||
from litellm import Router
|
||||
|
||||
importlib.reload(litellm)
|
||||
|
||||
try:
|
||||
if hasattr(litellm, "proxy") and hasattr(litellm.proxy, "proxy_server"):
|
||||
import litellm.proxy.proxy_server
|
||||
|
||||
importlib.reload(litellm.proxy.proxy_server)
|
||||
except Exception as e:
|
||||
print(f"Error reloading litellm.proxy.proxy_server: {e}")
|
||||
|
||||
import asyncio
|
||||
|
||||
loop = asyncio.get_event_loop_policy().new_event_loop()
|
||||
asyncio.set_event_loop(loop)
|
||||
print(litellm)
|
||||
# from litellm import Router, completion, aembedding, acompletion, embedding
|
||||
yield
|
||||
|
||||
# Teardown code (executes after the yield point)
|
||||
loop.close() # Close the loop created earlier
|
||||
asyncio.set_event_loop(None) # Remove the reference to the loop
|
||||
|
||||
|
||||
def pytest_collection_modifyitems(config, items):
|
||||
# Separate tests in 'test_amazing_proxy_custom_logger.py' and other tests
|
||||
custom_logger_tests = [
|
||||
item for item in items if "custom_logger" in item.parent.name
|
||||
]
|
||||
other_tests = [item for item in items if "custom_logger" not in item.parent.name]
|
||||
|
||||
# Sort tests based on their names
|
||||
custom_logger_tests.sort(key=lambda x: x.name)
|
||||
other_tests.sort(key=lambda x: x.name)
|
||||
|
||||
# Reorder the items list
|
||||
items[:] = custom_logger_tests + other_tests
|
||||
|
|
@ -19,6 +19,11 @@ from litellm.types.llms.openai import AllMessageValues
|
|||
from litellm.types.utils import StandardCallbackDynamicParams
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def setup_anthropic_api_key(monkeypatch):
|
||||
monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-some-key")
|
||||
|
||||
|
||||
class TestCustomPromptManagement(CustomPromptManagement):
|
||||
def get_chat_completion_prompt(
|
||||
self,
|
||||
|
|
@ -50,7 +55,7 @@ class TestCustomPromptManagement(CustomPromptManagement):
|
|||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_custom_prompt_management_with_prompt_id():
|
||||
async def test_custom_prompt_management_with_prompt_id(monkeypatch):
|
||||
custom_prompt_management = TestCustomPromptManagement()
|
||||
litellm.callbacks = [custom_prompt_management]
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import os
|
||||
import sys
|
||||
from unittest.mock import MagicMock, call, patch
|
||||
from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
|
||||
|
||||
import pytest
|
||||
|
||||
|
|
@ -12,6 +13,7 @@ import litellm
|
|||
from litellm.llms.vertex_ai.common_utils import (
|
||||
get_vertex_location_from_url,
|
||||
get_vertex_project_id_from_url,
|
||||
convert_anyof_null_to_nullable
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -42,6 +44,98 @@ async def test_get_vertex_location_from_url():
|
|||
location = get_vertex_location_from_url(url)
|
||||
assert location is None
|
||||
|
||||
def test_basic_anyof_conversion():
|
||||
"""Test basic conversion of anyOf with 'null'."""
|
||||
schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"example": {
|
||||
"anyOf": [
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
||||
expected = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"example": {
|
||||
"anyOf": [
|
||||
{"type": "string", "nullable": True}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
assert schema == expected
|
||||
|
||||
|
||||
def test_nested_anyof_conversion():
|
||||
"""Test nested conversion with 'anyOf' inside properties."""
|
||||
schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"outer": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"inner": {
|
||||
"anyOf": [
|
||||
{"type": "array", "items": {"type": "string"}},
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
||||
expected = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"outer": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"inner": {
|
||||
"anyOf": [
|
||||
{"type": "array", "items": {"type": "string"}, "nullable": True},
|
||||
{"type": "string", "nullable": True}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
assert schema == expected
|
||||
|
||||
def test_anyof_with_excessive_nesting():
|
||||
"""Test conversion with excessive nesting > max levels +1 deep."""
|
||||
# generate a schema with excessive nesting
|
||||
schema = {"type": "object", "properties": {}}
|
||||
current = schema
|
||||
for _ in range(DEFAULT_MAX_RECURSE_DEPTH + 1):
|
||||
current["properties"] = {
|
||||
"nested": {
|
||||
"anyOf": [
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
],
|
||||
"properties": {}
|
||||
}
|
||||
}
|
||||
current = current["properties"]["nested"]
|
||||
|
||||
|
||||
# running the conversion will raise an error
|
||||
with pytest.raises(ValueError, match=f"Max depth of {DEFAULT_MAX_RECURSE_DEPTH} exceeded while processing schema. Please check the schema for excessive nesting."):
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_supports_system_message():
|
||||
|
|
@ -59,3 +153,93 @@ async def test_get_supports_system_message():
|
|||
model="random-model-name", custom_llm_provider="vertex_ai"
|
||||
)
|
||||
assert result == False
|
||||
def test_basic_anyof_conversion():
|
||||
"""Test basic conversion of anyOf with 'null'."""
|
||||
schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"example": {
|
||||
"anyOf": [
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
||||
expected = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"example": {
|
||||
"anyOf": [
|
||||
{"type": "string", "nullable": True}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
assert schema == expected
|
||||
|
||||
|
||||
def test_nested_anyof_conversion():
|
||||
"""Test nested conversion with 'anyOf' inside properties."""
|
||||
schema = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"outer": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"inner": {
|
||||
"anyOf": [
|
||||
{"type": "array", "items": {"type": "string"}},
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
||||
expected = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"outer": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"inner": {
|
||||
"anyOf": [
|
||||
{"type": "array", "items": {"type": "string"}, "nullable": True},
|
||||
{"type": "string", "nullable": True}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
assert schema == expected
|
||||
|
||||
def test_anyof_with_excessive_nesting():
|
||||
"""Test conversion with excessive nesting > max levels +1 deep."""
|
||||
# generate a schema with excessive nesting
|
||||
schema = {"type": "object", "properties": {}}
|
||||
current = schema
|
||||
for _ in range(DEFAULT_MAX_RECURSE_DEPTH + 1):
|
||||
current["properties"] = {
|
||||
"nested": {
|
||||
"anyOf": [
|
||||
{"type": "string"},
|
||||
{"type": "null"}
|
||||
],
|
||||
"properties": {}
|
||||
}
|
||||
}
|
||||
current = current["properties"]["nested"]
|
||||
|
||||
|
||||
# running the conversion will raise an error
|
||||
with pytest.raises(ValueError, match=f"Max depth of {DEFAULT_MAX_RECURSE_DEPTH} exceeded while processing schema. Please check the schema for excessive nesting."):
|
||||
convert_anyof_null_to_nullable(schema)
|
||||
|
|
|
|||
|
|
@ -23,8 +23,9 @@ from litellm.types.router import Deployment, LiteLLM_Params, updateDeployment
|
|||
|
||||
|
||||
class MockPrismaClient:
|
||||
def __init__(self, team_exists: bool = True):
|
||||
def __init__(self, team_exists: bool = True, user_admin: bool = True):
|
||||
self.team_exists = team_exists
|
||||
self.user_admin = user_admin
|
||||
self.db = self
|
||||
|
||||
async def find_unique(self, where):
|
||||
|
|
@ -32,7 +33,11 @@ class MockPrismaClient:
|
|||
return LiteLLM_TeamTable(
|
||||
team_id=where["team_id"],
|
||||
team_alias="test_team",
|
||||
members_with_roles=[Member(user_id="test_user", role="admin")],
|
||||
members_with_roles=[
|
||||
Member(
|
||||
user_id="test_user", role="admin" if self.user_admin else "user"
|
||||
)
|
||||
],
|
||||
)
|
||||
return None
|
||||
|
||||
|
|
@ -164,7 +169,7 @@ class TestModelManagementAuthChecks:
|
|||
),
|
||||
model_info={"team_id": "test_team"},
|
||||
)
|
||||
prisma_client = MockPrismaClient()
|
||||
prisma_client = MockPrismaClient(team_exists=True)
|
||||
|
||||
result = await ModelManagementAuthChecks.can_user_make_model_call(
|
||||
model_params=model_params,
|
||||
|
|
@ -184,7 +189,7 @@ class TestModelManagementAuthChecks:
|
|||
),
|
||||
model_info={"team_id": "test_team"},
|
||||
)
|
||||
prisma_client = MockPrismaClient()
|
||||
prisma_client = MockPrismaClient(team_exists=True, user_admin=False)
|
||||
|
||||
with pytest.raises(Exception) as exc_info:
|
||||
await ModelManagementAuthChecks.can_user_make_model_call(
|
||||
|
|
|
|||
|
|
@ -26,6 +26,11 @@ def client():
|
|||
return TestClient(app)
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def add_anthropic_api_key_to_env(monkeypatch):
|
||||
monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-1234567890")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_ui_view_spend_logs_with_user_id(client, monkeypatch):
|
||||
# Mock data for the test
|
||||
|
|
@ -501,7 +506,7 @@ class TestSpendLogsPayload:
|
|||
return mock_response
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_spend_logs_payload_success_log_with_api_base(self):
|
||||
async def test_spend_logs_payload_success_log_with_api_base(self, monkeypatch):
|
||||
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
|
||||
|
||||
litellm.callbacks = [_ProxyDBLogger(message_logging=False)]
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ from unittest.mock import AsyncMock, MagicMock, mock_open, patch
|
|||
import click
|
||||
import httpx
|
||||
import pytest
|
||||
import yaml
|
||||
from fastapi import FastAPI
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
|
|
@ -74,3 +75,92 @@ async def test_initialize_scheduled_jobs_credentials(monkeypatch):
|
|||
call[0] for call in mock_proxy_config.get_credentials.mock_calls
|
||||
]
|
||||
assert len(mock_scheduler_calls) > 0
|
||||
|
||||
|
||||
# Mock Prisma
|
||||
class MockPrisma:
|
||||
def __init__(self, database_url=None, proxy_logging_obj=None, http_client=None):
|
||||
self.database_url = database_url
|
||||
self.proxy_logging_obj = proxy_logging_obj
|
||||
self.http_client = http_client
|
||||
|
||||
async def connect(self):
|
||||
pass
|
||||
|
||||
async def disconnect(self):
|
||||
pass
|
||||
|
||||
|
||||
mock_prisma = MockPrisma()
|
||||
|
||||
|
||||
@patch(
|
||||
"litellm.proxy.proxy_server.ProxyStartupEvent._setup_prisma_client",
|
||||
return_value=mock_prisma,
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
async def test_aaaproxy_startup_master_key(mock_prisma, monkeypatch, tmp_path):
|
||||
"""
|
||||
Test that master_key is correctly loaded from either config.yaml or environment variables
|
||||
"""
|
||||
import yaml
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Import happens here - this is when the module probably reads the config path
|
||||
from litellm.proxy.proxy_server import proxy_startup_event
|
||||
|
||||
# Mock the Prisma import
|
||||
monkeypatch.setattr("litellm.proxy.proxy_server.PrismaClient", MockPrisma)
|
||||
|
||||
# Create test app
|
||||
app = FastAPI()
|
||||
|
||||
# Test Case 1: Master key from config.yaml
|
||||
test_master_key = "sk-12345"
|
||||
test_config = {"general_settings": {"master_key": test_master_key}}
|
||||
|
||||
# Create a temporary config file
|
||||
config_path = tmp_path / "config.yaml"
|
||||
with open(config_path, "w") as f:
|
||||
yaml.dump(test_config, f)
|
||||
|
||||
print(f"SET ENV VARIABLE - CONFIG_FILE_PATH, str(config_path): {str(config_path)}")
|
||||
# Second setting of CONFIG_FILE_PATH to a different value
|
||||
monkeypatch.setenv("CONFIG_FILE_PATH", str(config_path))
|
||||
print(f"config_path: {config_path}")
|
||||
print(f"os.getenv('CONFIG_FILE_PATH'): {os.getenv('CONFIG_FILE_PATH')}")
|
||||
async with proxy_startup_event(app):
|
||||
from litellm.proxy.proxy_server import master_key
|
||||
|
||||
assert master_key == test_master_key
|
||||
|
||||
# Test Case 2: Master key from environment variable
|
||||
test_env_master_key = "sk-67890"
|
||||
|
||||
# Create empty config
|
||||
empty_config = {"general_settings": {}}
|
||||
with open(config_path, "w") as f:
|
||||
yaml.dump(empty_config, f)
|
||||
|
||||
monkeypatch.setenv("LITELLM_MASTER_KEY", test_env_master_key)
|
||||
print("test_env_master_key: {}".format(test_env_master_key))
|
||||
async with proxy_startup_event(app):
|
||||
from litellm.proxy.proxy_server import master_key
|
||||
|
||||
assert master_key == test_env_master_key
|
||||
|
||||
# Test Case 3: Master key with os.environ prefix
|
||||
test_resolved_key = "sk-resolved-key"
|
||||
test_config_with_prefix = {
|
||||
"general_settings": {"master_key": "os.environ/CUSTOM_MASTER_KEY"}
|
||||
}
|
||||
|
||||
# Create config with os.environ prefix
|
||||
with open(config_path, "w") as f:
|
||||
yaml.dump(test_config_with_prefix, f)
|
||||
|
||||
monkeypatch.setenv("CUSTOM_MASTER_KEY", test_resolved_key)
|
||||
async with proxy_startup_event(app):
|
||||
from litellm.proxy.proxy_server import master_key
|
||||
|
||||
assert master_key == test_resolved_key
|
||||
|
|
|
|||
|
|
@ -1,51 +0,0 @@
|
|||
import json
|
||||
import os
|
||||
import sys
|
||||
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../../..")
|
||||
) # Adds the parent directory to the system path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
from litellm import rerank
|
||||
from litellm.llms.custom_httpx.http_handler import HTTPHandler
|
||||
|
||||
|
||||
def test_rerank_infer_region_from_model_arn(monkeypatch):
|
||||
mock_response = MagicMock()
|
||||
|
||||
monkeypatch.setenv("AWS_REGION_NAME", "us-east-1")
|
||||
args = {
|
||||
"model": "bedrock/arn:aws:bedrock:us-west-2::foundation-model/amazon.rerank-v1:0",
|
||||
"query": "hello",
|
||||
"documents": ["hello", "world"],
|
||||
}
|
||||
|
||||
def return_val():
|
||||
return {
|
||||
"results": [
|
||||
{"index": 0, "relevanceScore": 0.6716859340667725},
|
||||
{"index": 1, "relevanceScore": 0.0004994205664843321},
|
||||
]
|
||||
}
|
||||
|
||||
mock_response.json = return_val
|
||||
mock_response.headers = {"key": "value"}
|
||||
mock_response.status_code = 200
|
||||
|
||||
client = HTTPHandler()
|
||||
|
||||
with patch.object(client, "post", return_value=mock_response) as mock_post:
|
||||
rerank(
|
||||
model=args["model"],
|
||||
query=args["query"],
|
||||
documents=args["documents"],
|
||||
client=client,
|
||||
)
|
||||
mock_post.assert_called_once()
|
||||
print(f"mock_post.call_args: {mock_post.call_args.kwargs}")
|
||||
assert "us-west-2" in mock_post.call_args.kwargs["url"]
|
||||
assert "us-east-1" not in mock_post.call_args.kwargs["url"]
|
||||
|
|
@ -14,6 +14,15 @@ from unittest.mock import MagicMock, patch
|
|||
import litellm
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def add_api_keys_to_env(monkeypatch):
|
||||
monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-api03-1234567890")
|
||||
monkeypatch.setenv("OPENAI_API_KEY", "sk-openai-api03-1234567890")
|
||||
monkeypatch.setenv("AWS_ACCESS_KEY_ID", "my-fake-aws-access-key-id")
|
||||
monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "my-fake-aws-secret-access-key")
|
||||
monkeypatch.setenv("AWS_REGION", "us-east-1")
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def openai_api_response():
|
||||
mock_response_data = {
|
||||
|
|
@ -130,7 +139,8 @@ def test_completion_missing_role(openai_api_response):
|
|||
)
|
||||
@pytest.mark.parametrize("sync_mode", [True, False])
|
||||
@pytest.mark.asyncio
|
||||
async def test_url_with_format_param(model, sync_mode):
|
||||
async def test_url_with_format_param(model, sync_mode, monkeypatch):
|
||||
|
||||
from litellm import acompletion, completion
|
||||
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
|
||||
|
||||
|
|
|
|||
|
|
@ -303,6 +303,24 @@ def test_aget_valid_models():
|
|||
os.environ = old_environ
|
||||
|
||||
|
||||
@pytest.mark.parametrize("custom_llm_provider", ["gemini", "anthropic", "xai"])
|
||||
def test_get_valid_models_with_custom_llm_provider(custom_llm_provider):
|
||||
from litellm.utils import ProviderConfigManager
|
||||
from litellm.types.utils import LlmProviders
|
||||
|
||||
provider_config = ProviderConfigManager.get_provider_model_info(
|
||||
model=None,
|
||||
provider=LlmProviders(custom_llm_provider),
|
||||
)
|
||||
assert provider_config is not None
|
||||
valid_models = get_valid_models(
|
||||
check_provider_endpoint=True, custom_llm_provider=custom_llm_provider
|
||||
)
|
||||
print(valid_models)
|
||||
assert len(valid_models) > 0
|
||||
assert provider_config.get_models() == valid_models
|
||||
|
||||
|
||||
# test_get_valid_models()
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1008,6 +1008,11 @@ class BaseAnthropicChatTest(ABC):
|
|||
"""Must return the base completion call args"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
def get_base_completion_call_args_with_thinking(self) -> dict:
|
||||
"""Must return the base completion call args"""
|
||||
pass
|
||||
|
||||
@property
|
||||
def completion_function(self):
|
||||
return litellm.completion
|
||||
|
|
@ -1066,3 +1071,21 @@ class BaseAnthropicChatTest(ABC):
|
|||
json.loads(built_response.choices[0].message.content).keys()
|
||||
== json.loads(non_stream_response.choices[0].message.content).keys()
|
||||
), f"Got={json.loads(built_response.choices[0].message.content)}, Expected={json.loads(non_stream_response.choices[0].message.content)}"
|
||||
|
||||
def test_completion_thinking_with_response_format(self):
|
||||
from pydantic import BaseModel
|
||||
|
||||
class RFormat(BaseModel):
|
||||
question: str
|
||||
answer: str
|
||||
|
||||
base_completion_call_args = self.get_base_completion_call_args_with_thinking()
|
||||
|
||||
messages = [{"role": "user", "content": "Generate 5 question + answer pairs"}]
|
||||
response = self.completion_function(
|
||||
**base_completion_call_args,
|
||||
messages=messages,
|
||||
response_format=RFormat,
|
||||
)
|
||||
|
||||
print(response)
|
||||
|
|
|
|||
|
|
@ -467,6 +467,12 @@ class TestAnthropicCompletion(BaseLLMChatTest, BaseAnthropicChatTest):
|
|||
def get_base_completion_call_args(self) -> dict:
|
||||
return {"model": "anthropic/claude-3-5-sonnet-20240620"}
|
||||
|
||||
def get_base_completion_call_args_with_thinking(self) -> dict:
|
||||
return {
|
||||
"model": "anthropic/claude-3-7-sonnet-latest",
|
||||
"thinking": {"type": "enabled", "budget_tokens": 16000},
|
||||
}
|
||||
|
||||
def test_tool_call_no_arguments(self, tool_call_no_arguments):
|
||||
"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
|
||||
from litellm.litellm_core_utils.prompt_templates.factory import (
|
||||
|
|
|
|||
|
|
@ -35,7 +35,7 @@ from litellm import (
|
|||
from litellm.llms.bedrock.chat import BedrockLLM
|
||||
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
|
||||
from litellm.litellm_core_utils.prompt_templates.factory import _bedrock_tools_pt
|
||||
from base_llm_unit_tests import BaseLLMChatTest
|
||||
from base_llm_unit_tests import BaseLLMChatTest, BaseAnthropicChatTest
|
||||
from base_rerank_unit_tests import BaseLLMRerankTest
|
||||
from base_embedding_unit_tests import BaseLLMEmbeddingTest
|
||||
|
||||
|
|
@ -2191,6 +2191,19 @@ class TestBedrockConverseChatCrossRegion(BaseLLMChatTest):
|
|||
assert cost > 0
|
||||
|
||||
|
||||
class TestBedrockConverseAnthropicUnitTests(BaseAnthropicChatTest):
|
||||
def get_base_completion_call_args(self) -> dict:
|
||||
return {
|
||||
"model": "bedrock/us.anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
}
|
||||
|
||||
def get_base_completion_call_args_with_thinking(self) -> dict:
|
||||
return {
|
||||
"model": "bedrock/us.anthropic.claude-3-7-sonnet-20250219-v1:0",
|
||||
"thinking": {"type": "enabled", "budget_tokens": 16000},
|
||||
}
|
||||
|
||||
|
||||
class TestBedrockConverseChatNormal(BaseLLMChatTest):
|
||||
def get_base_completion_call_args(self) -> dict:
|
||||
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
|
||||
|
|
|
|||
|
|
@ -22,6 +22,7 @@ litellm.num_retries = 3
|
|||
|
||||
|
||||
@pytest.mark.parametrize("stream", [True, False])
|
||||
@pytest.mark.flaky(retries=3, delay=1)
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_completion_cohere_citations(stream):
|
||||
try:
|
||||
|
|
@ -55,6 +56,8 @@ async def test_chat_completion_cohere_citations(stream):
|
|||
assert citations_chunk
|
||||
else:
|
||||
assert response.citations is not None
|
||||
except litellm.ServiceUnavailableError:
|
||||
pass
|
||||
except Exception as e:
|
||||
pytest.fail(f"Error occurred: {e}")
|
||||
|
||||
|
|
|
|||
|
|
@ -481,3 +481,42 @@ def test_rerank_cohere_api():
|
|||
assert response.results[0]["document"]["text"] is not None
|
||||
assert response.results[0]["document"]["text"] == "hello"
|
||||
assert response.results[1]["document"]["text"] == "world"
|
||||
|
||||
|
||||
def test_rerank_infer_region_from_model_arn(monkeypatch):
|
||||
|
||||
mock_response = MagicMock()
|
||||
|
||||
monkeypatch.setenv("AWS_REGION_NAME", "us-east-1")
|
||||
args = {
|
||||
"model": "bedrock/arn:aws:bedrock:us-west-2::foundation-model/amazon.rerank-v1:0",
|
||||
"query": "hello",
|
||||
"documents": ["hello", "world"],
|
||||
}
|
||||
|
||||
def return_val():
|
||||
return {
|
||||
"results": [
|
||||
{"index": 0, "relevanceScore": 0.6716859340667725},
|
||||
{"index": 1, "relevanceScore": 0.0004994205664843321},
|
||||
]
|
||||
}
|
||||
|
||||
mock_response.json = return_val
|
||||
mock_response.headers = {"key": "value"}
|
||||
mock_response.status_code = 200
|
||||
|
||||
client = HTTPHandler()
|
||||
|
||||
with patch.object(client, "post", return_value=mock_response) as mock_post:
|
||||
litellm.rerank(
|
||||
model=args["model"],
|
||||
query=args["query"],
|
||||
documents=args["documents"],
|
||||
client=client,
|
||||
)
|
||||
|
||||
mock_post.assert_called_once()
|
||||
print(f"mock_post.call_args: {mock_post.call_args.kwargs}")
|
||||
assert "us-west-2" in mock_post.call_args.kwargs["url"]
|
||||
assert "us-east-1" not in mock_post.call_args.kwargs["url"]
|
||||
|
|
|
|||
|
|
@ -40,12 +40,7 @@ import logging
|
|||
|
||||
def setup_cache():
|
||||
# Set up the cache
|
||||
cache = Cache(
|
||||
type=LiteLLMCacheType.REDIS,
|
||||
host=os.environ["REDIS_HOST"],
|
||||
port=os.environ["REDIS_PORT"],
|
||||
password=os.environ["REDIS_PASSWORD"],
|
||||
)
|
||||
cache = Cache(type=LiteLLMCacheType.LOCAL)
|
||||
litellm.cache = cache
|
||||
return cache
|
||||
|
||||
|
|
|
|||
|
|
@ -17,12 +17,12 @@ def schema_setup(postgresql_my):
|
|||
return postgresql_my
|
||||
|
||||
|
||||
def test_schema_migration_check(schema_setup):
|
||||
def test_aaaasschema_migration_check(schema_setup, monkeypatch):
|
||||
"""Test to check if schema requires migration"""
|
||||
# Set test database URL
|
||||
test_db_url = f"postgresql://{schema_setup.info.user}:@{schema_setup.info.host}:{schema_setup.info.port}/{schema_setup.info.dbname}"
|
||||
# test_db_url = "postgresql://neondb_owner:npg_JiZPS0DAhRn4@ep-delicate-wave-a55cvbuc.us-east-2.aws.neon.tech/neondb?sslmode=require"
|
||||
os.environ["DATABASE_URL"] = test_db_url
|
||||
monkeypatch.setenv("DATABASE_URL", test_db_url)
|
||||
|
||||
deploy_dir = Path("./deploy")
|
||||
source_migrations_dir = deploy_dir / "migrations"
|
||||
|
|
|
|||
|
|
@ -3286,6 +3286,7 @@ async def test_aadmin_only_routes(prisma_client):
|
|||
only an admin should be able to access admin only routes
|
||||
"""
|
||||
litellm.set_verbose = True
|
||||
print(f"os.getenv('DATABASE_URL')={os.getenv('DATABASE_URL')}")
|
||||
setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client)
|
||||
setattr(litellm.proxy.proxy_server, "master_key", "sk-1234")
|
||||
await litellm.proxy.proxy_server.prisma_client.connect()
|
||||
|
|
@ -3882,7 +3883,11 @@ async def test_get_paginated_teams(prisma_client):
|
|||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.flaky(retries=3, delay=1)
|
||||
@pytest.mark.parametrize("entity_type", ["key", "user", "team"])
|
||||
@pytest.mark.skip(
|
||||
reason="Skipping reset budget job test. Fails on ci/cd due to db timeout errors. Need to replace with mock db."
|
||||
)
|
||||
async def test_reset_budget_job(prisma_client, entity_type):
|
||||
"""
|
||||
Test that the ResetBudgetJob correctly resets budgets for keys, users, and teams.
|
||||
|
|
|
|||
|
|
@ -22,12 +22,13 @@ class MockPrismaClient:
|
|||
def __init__(self):
|
||||
self.db = MagicMock()
|
||||
self.spend_log_transactions = []
|
||||
self.user_list_transactions = {}
|
||||
self.end_user_list_transactions = {}
|
||||
self.key_list_transactions = {}
|
||||
self.team_list_transactions = {}
|
||||
self.team_member_list_transactions = {}
|
||||
self.org_list_transactions = {}
|
||||
self.user_list_transactons = {}
|
||||
self.end_user_list_transactons = {}
|
||||
self.key_list_transactons = {}
|
||||
self.team_list_transactons = {}
|
||||
self.team_member_list_transactons = {}
|
||||
self.org_list_transactons = {}
|
||||
self.daily_user_spend_transactions = {}
|
||||
|
||||
def jsonify_object(self, obj):
|
||||
return obj
|
||||
|
|
|
|||
|
|
@ -160,7 +160,7 @@ async def test_end_user_new():
|
|||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_end_user_specific_region():
|
||||
async def test_aaaend_user_specific_region():
|
||||
"""
|
||||
- Specify region user can make calls in
|
||||
- Make a generic call
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -0,0 +1 @@
|
|||
(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[185],{96443:function(n,e,t){Promise.resolve().then(t.t.bind(t,39974,23)),Promise.resolve().then(t.t.bind(t,2778,23))},2778:function(){},39974:function(n){n.exports={style:{fontFamily:"'__Inter_cf7686', '__Inter_Fallback_cf7686'",fontStyle:"normal"},className:"__className_cf7686"}}},function(n){n.O(0,[919,986,971,117,744],function(){return n(n.s=96443)}),_N_E=n.O()}]);
|
||||
|
|
@ -1 +0,0 @@
|
|||
(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[185],{6580:function(n,e,t){Promise.resolve().then(t.t.bind(t,39974,23)),Promise.resolve().then(t.t.bind(t,2778,23))},2778:function(){},39974:function(n){n.exports={style:{fontFamily:"'__Inter_cf7686', '__Inter_Fallback_cf7686'",fontStyle:"normal"},className:"__className_cf7686"}}},function(n){n.O(0,[919,986,971,117,744],function(){return n(n.s=6580)}),_N_E=n.O()}]);
|
||||
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