├── .DS_Store ├── .dockerignore ├── .env.template ├── .gitignore ├── Dockerfile ├── LICENSE ├── README.md ├── llm.py ├── main.py ├── poetry.lock ├── pyproject.toml ├── requirements.txt ├── test_proxy.py ├── tests ├── __init__.py └── test_proxy.py └── utils.py /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/BerriAI/liteLLM-proxy/1ef69ae92bf22600f9a42d15e3b992e1010c9a7e/.DS_Store -------------------------------------------------------------------------------- /.dockerignore: -------------------------------------------------------------------------------- 1 | .venv 2 | -------------------------------------------------------------------------------- /.env.template: -------------------------------------------------------------------------------- 1 | # PROJECT_NAME="your-project-name" # Uncomment to use budget manager 2 | 3 | # OPTIONALS 4 | OPENAI_API_KEY="" # your openai api key 5 | ANTHROPIC_API_KEY="" # your anthropic api key 6 | REPLICATE_API_KEY="" # your replicate api key 7 | COHERE_API_KEY="" # your cohere api key 8 | HUGGINGFACE_API_KEY="" # your huggingface api key 9 | TOGETHERAI_API_KEY="" # your together ai api key 10 | BASETEN_API_KEY="" # your baseten api key 11 | AI21_API_KEY="" # your AI21 api key 12 | OPENROUTER_API_KEY="" # your Openrouter api key 13 | ALEPH_ALPHA_API_KEY="" # your Aleph Alpha api key 14 | 15 | ## AZURE 16 | AZURE_API_BASE="" 17 | AZURE_API_VERSION="" 18 | AZURE_API_KEY="" 19 | 20 | DEFAULT_MODEL="" # if you want this proxy to only make requests to one model 21 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .venv 2 | .vscode 3 | **/__pycache__ 4 | .mypy_cache 5 | .pytest_cache 6 | .env 7 | .aider* 8 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # Use an official Python runtime as a parent image 2 | FROM python:3.8 3 | 4 | # Set the working directory in the container 5 | WORKDIR /app 6 | 7 | # Copy the current directory contents into the container at /app 8 | COPY . /app 9 | 10 | # Install any needed packages specified in requirements.txt 11 | RUN pip install --no-cache-dir -r requirements.txt 12 | 13 | # Expose the port that your FastAPI application will run on 14 | EXPOSE 8080 15 | 16 | # Define the command to run your application 17 | CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8080"] 18 | 19 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | The MIT License 2 | 3 | Copyright (c) Yujong Lee 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in 13 | all copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN 21 | THE SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # liteLLM Proxy Server: 50+ LLM Models, Error Handling, Caching 2 | 3 | 4 | ⚠️ DEPRECATION WARNING: [LiteLLM](https://github.com/BerriAI/litellm) is our new home. You can find the LiteLLM Proxy there. Thank you for checking us out! ❤️ 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ### Azure, Llama2, OpenAI, Claude, Hugging Face, Replicate Models 14 | 15 | [![PyPI Version](https://img.shields.io/pypi/v/litellm.svg)](https://pypi.org/project/litellm/) 16 | [![PyPI Version](https://img.shields.io/badge/stable%20version-v0.1.345-blue?color=green&link=https://pypi.org/project/litellm/0.1.1/)](https://pypi.org/project/litellm/0.1.1/) 17 | ![Downloads](https://img.shields.io/pypi/dm/litellm) 18 | [![litellm](https://img.shields.io/badge/%20%F0%9F%9A%85%20liteLLM-OpenAI%7CAzure%7CAnthropic%7CPalm%7CCohere%7CReplicate%7CHugging%20Face-blue?color=green)](https://github.com/BerriAI/litellm) 19 | 20 | [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/DYqQAW?referralCode=t3ukrU) 21 | 22 | ![4BC6491E-86D0-4833-B061-9F54524B2579](https://github.com/BerriAI/litellm/assets/17561003/f5dd237b-db5e-42e1-b1ac-f05683b1d724) 23 | 24 | 25 | ## Usage 26 | **Step 1: Put your API keys in .env** 27 | Copy the .env.template and put in the relevant keys (e.g. OPENAI_API_KEY="sk-..") 28 | 29 | **Step 2: Test your proxy** 30 | Start your proxy server 31 | ```shell 32 | $ cd litellm-proxy && python3 main.py 33 | ``` 34 | 35 | Make your first call 36 | ```python 37 | import openai 38 | 39 | openai.api_key = "sk-litellm-master-key" 40 | openai.api_base = "http://0.0.0.0:8080" 41 | 42 | response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hey"}]) 43 | 44 | print(response) 45 | ``` 46 | 47 | ## What does liteLLM proxy do 48 | 49 | - Make `/chat/completions` requests for 50+ LLM models **Azure, OpenAI, Replicate, Anthropic, Hugging Face** 50 | 51 | Example: for `model` use `claude-2`, `gpt-3.5`, `gpt-4`, `command-nightly`, `stabilityai/stablecode-completion-alpha-3b-4k` 52 | 53 | ```json 54 | { 55 | "model": "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1", 56 | "messages": [ 57 | { 58 | "content": "Hello, whats the weather in San Francisco??", 59 | "role": "user" 60 | } 61 | ] 62 | } 63 | ``` 64 | 65 | - **Consistent Input/Output** Format 66 | - Call all models using the OpenAI format - `completion(model, messages)` 67 | - Text responses will always be available at `['choices'][0]['message']['content']` 68 | - **Error Handling** Using Model Fallbacks (if `GPT-4` fails, try `llama2`) 69 | - **Logging** - Log Requests, Responses and Errors to `Supabase`, `Posthog`, `Mixpanel`, `Sentry`, `LLMonitor`, `Traceloop`, `Helicone` (Any of the supported providers here: https://docs.litellm.ai/docs/ 70 | 71 | **Example: Logs sent to Supabase** 72 | Screenshot 2023-08-11 at 4 02 46 PM 73 | 74 | - **Token Usage & Spend** - Track Input + Completion tokens used + Spend/model 75 | - **Caching** - Implementation of Semantic Caching 76 | - **Streaming & Async Support** - Return generators to stream text responses 77 | 78 | ## API Endpoints 79 | 80 | ### `/chat/completions` (POST) 81 | 82 | This endpoint is used to generate chat completions for 50+ support LLM API Models. Use llama2, GPT-4, Claude2 etc 83 | 84 | #### Input 85 | 86 | This API endpoint accepts all inputs in raw JSON and expects the following inputs 87 | 88 | - `model` (string, required): ID of the model to use for chat completions. See all supported models [here]: (https://docs.litellm.ai/docs/): 89 | eg `gpt-3.5-turbo`, `gpt-4`, `claude-2`, `command-nightly`, `stabilityai/stablecode-completion-alpha-3b-4k` 90 | - `messages` (array, required): A list of messages representing the conversation context. Each message should have a `role` (system, user, assistant, or function), `content` (message text), and `name` (for function role). 91 | - Additional Optional parameters: `temperature`, `functions`, `function_call`, `top_p`, `n`, `stream`. See the full list of supported inputs here: https://docs.litellm.ai/docs/ 92 | 93 | #### Example JSON body 94 | 95 | For claude-2 96 | 97 | ```json 98 | { 99 | "model": "claude-2", 100 | "messages": [ 101 | { 102 | "content": "Hello, whats the weather in San Francisco??", 103 | "role": "user" 104 | } 105 | ] 106 | } 107 | ``` 108 | 109 | ### Making an API request to the Proxy Server 110 | 111 | ```python 112 | import requests 113 | import json 114 | 115 | # TODO: use your URL 116 | url = "http://localhost:5000/chat/completions" 117 | 118 | payload = json.dumps({ 119 | "model": "gpt-3.5-turbo", 120 | "messages": [ 121 | { 122 | "content": "Hello, whats the weather in San Francisco??", 123 | "role": "user" 124 | } 125 | ] 126 | }) 127 | headers = { 128 | 'Content-Type': 'application/json' 129 | } 130 | response = requests.request("POST", url, headers=headers, data=payload) 131 | print(response.text) 132 | 133 | ``` 134 | 135 | ### Output [Response Format] 136 | 137 | Responses from the server are given in the following format. 138 | All responses from the server are returned in the following format (for all LLM models). More info on output here: https://docs.litellm.ai/docs/ 139 | 140 | ```json 141 | { 142 | "choices": [ 143 | { 144 | "finish_reason": "stop", 145 | "index": 0, 146 | "message": { 147 | "content": "I'm sorry, but I don't have the capability to provide real-time weather information. However, you can easily check the weather in San Francisco by searching online or using a weather app on your phone.", 148 | "role": "assistant" 149 | } 150 | } 151 | ], 152 | "created": 1691790381, 153 | "id": "chatcmpl-7mUFZlOEgdohHRDx2UpYPRTejirzb", 154 | "model": "gpt-3.5-turbo-0613", 155 | "object": "chat.completion", 156 | "usage": { 157 | "completion_tokens": 41, 158 | "prompt_tokens": 16, 159 | "total_tokens": 57 160 | } 161 | } 162 | ``` 163 | 164 | ## Installation & Usage 165 | 166 | ### Running Locally 167 | 168 | 1. Clone liteLLM repository to your local machine: 169 | ``` 170 | git clone https://github.com/BerriAI/liteLLM-proxy 171 | ``` 172 | 2. Install the required dependencies using pip 173 | ``` 174 | pip install requirements.txt 175 | ``` 176 | 3. (optional)Set your LiteLLM proxy master key 177 | ``` 178 | os.environ['LITELLM_PROXY_MASTER_KEY]` = "YOUR_LITELLM_PROXY_MASTER_KEY" 179 | or 180 | set LITELLM_PROXY_MASTER_KEY in your .env file 181 | ``` 182 | 4. Set your LLM API keys 183 | ``` 184 | os.environ['OPENAI_API_KEY]` = "YOUR_API_KEY" 185 | or 186 | set OPENAI_API_KEY in your .env file 187 | ``` 188 | 5. Run the server: 189 | ``` 190 | python main.py 191 | ``` 192 | 193 | ## Deploying 194 | 195 | 1. Quick Start: Deploy on Railway 196 | 197 | [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/DYqQAW?referralCode=t3ukrU) 198 | 199 | 2. `GCP`, `AWS`, `Azure` 200 | This project includes a `Dockerfile` allowing you to build and deploy a Docker Project on your providers 201 | 202 | # Support / Talk with founders 203 | 204 | - [Our calendar 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version) 205 | - [Community Discord 💭](https://discord.gg/wuPM9dRgDw) 206 | - Our numbers 📞 +1 (770) 8783-106 / +1 (412) 618-6238 207 | - Our emails ✉️ ishaan@berri.ai / krrish@berri.ai 208 | 209 | ## Roadmap 210 | 211 | - [ ] Support hosted db (e.g. Supabase) 212 | - [ ] Easily send data to places like posthog and sentry. 213 | - [ ] Add a hot-cache for project spend logs - enables fast checks for user + project limitings 214 | - [ ] Implement user-based rate-limiting 215 | - [ ] Spending controls per project - expose key creation endpoint 216 | - [ ] Need to store a keys db -> mapping created keys to their alias (i.e. project name) 217 | - [ ] Easily add new models as backups / as the entry-point (add this to the available model list) 218 | -------------------------------------------------------------------------------- /llm.py: -------------------------------------------------------------------------------- 1 | from typing import Dict 2 | from collections import defaultdict 3 | import threading 4 | 5 | from fastapi import HTTPException 6 | 7 | from utils import getenv 8 | 9 | import backoff 10 | import openai.error 11 | 12 | import litellm 13 | import os 14 | import litellm.exceptions 15 | from litellm.caching import Cache 16 | 17 | # litellm.cache = Cache( # optional if you want to use cache 18 | # type="redis", 19 | # host=getenv("REDISHOST", ""), 20 | # port=getenv("REDISPORT", ""), 21 | # password=getenv("REDISPASSWORD", ""), 22 | # ) 23 | 24 | cost_dict: Dict[str, Dict[str, float]] = defaultdict(dict) 25 | cost_dict_lock = threading.Lock() 26 | 27 | 28 | def _update_costs_thread(budget_manager: litellm.BudgetManager): 29 | thread = threading.Thread(target=budget_manager.save_data) 30 | thread.start() 31 | 32 | 33 | class RetryConstantError(Exception): 34 | pass 35 | 36 | 37 | class RetryExpoError(Exception): 38 | pass 39 | 40 | 41 | class UnknownLLMError(Exception): 42 | pass 43 | 44 | 45 | def handle_llm_exception(e: Exception): 46 | if isinstance( 47 | e, 48 | ( 49 | openai.error.APIError, 50 | openai.error.TryAgain, 51 | openai.error.Timeout, 52 | openai.error.ServiceUnavailableError, 53 | ), 54 | ): 55 | raise RetryConstantError from e 56 | elif isinstance(e, openai.error.RateLimitError): 57 | raise RetryExpoError from e 58 | elif isinstance( 59 | e, 60 | ( 61 | openai.error.APIConnectionError, 62 | openai.error.InvalidRequestError, 63 | openai.error.AuthenticationError, 64 | openai.error.PermissionError, 65 | openai.error.InvalidAPIType, 66 | openai.error.SignatureVerificationError, 67 | ), 68 | ): 69 | raise e 70 | else: 71 | raise UnknownLLMError from e 72 | 73 | 74 | @backoff.on_exception( 75 | wait_gen=backoff.constant, 76 | exception=RetryConstantError, 77 | max_tries=3, 78 | interval=3, 79 | ) 80 | @backoff.on_exception( 81 | wait_gen=backoff.expo, 82 | exception=RetryExpoError, 83 | jitter=backoff.full_jitter, 84 | max_value=100, 85 | factor=1.5, 86 | ) 87 | def completion(**kwargs) -> litellm.ModelResponse: 88 | 89 | user_key = kwargs.pop("user_key") 90 | master_key = kwargs.pop("master_key") 91 | budget_manager: litellm.BudgetManager = kwargs.pop("budget_manager") 92 | 93 | def _completion(): 94 | try: 95 | default_model = os.getenv("DEFAULT_MODEL", None) 96 | if default_model is not None and default_model != "": 97 | kwargs["model"] = default_model 98 | 99 | if user_key == master_key: 100 | # use as admin of the server 101 | response = litellm.completion(**kwargs) 102 | else: 103 | # for end user based rate limiting 104 | if budget_manager.get_current_cost( 105 | user=user_key 106 | ) > budget_manager.get_total_budget(user=user_key): 107 | raise HTTPException( 108 | status_code=429, detail={"error": "budget exceeded"} 109 | ) 110 | response = litellm.completion(**kwargs) 111 | 112 | if "stream" not in kwargs or kwargs["stream"] is not True: 113 | print(f"user_key: {user_key}") 114 | print(f"master_key: {master_key}") 115 | if user_key != master_key: # no budget on master key 116 | # updates both user 117 | budget_manager.update_cost(completion_obj=response, user=user_key) 118 | _update_costs_thread(budget_manager) # Non-blocking 119 | 120 | return response 121 | except Exception as e: 122 | print(f"LiteLLM Server: Got exception {e}") 123 | handle_llm_exception(e) # this tries fallback requests 124 | 125 | try: 126 | return _completion() 127 | except Exception as e: 128 | raise e 129 | 130 | 131 | # LiteLLM Config 132 | # config = { 133 | # "function": "completion", 134 | # "default_fallback_models": ["gpt-3.5-turbo", "claude-instant-1", "j2-ultra"], 135 | # "available_models": litellm.utils.get_valid_models(), 136 | # "adapt_to_prompt_size": True, 137 | # "model": { 138 | # "claude-instant-1": { 139 | # "needs_moderation": True 140 | # }, 141 | # "claude-2": { 142 | # "needs_moderation": True 143 | # }, 144 | # "gpt-3.5-turbo": { 145 | # "error_handling": { 146 | # "ContextWindowExceededError": {"fallback_model": "gpt-3.5-turbo-16k"} 147 | # } 148 | # }, 149 | # "gpt-3.5-turbo-0613": { 150 | # "error_handling": { 151 | # "ContextWindowExceededError": {"fallback_model": "gpt-3.5-turbo-16k-0613"} 152 | # } 153 | # }, 154 | # "gpt-4": { 155 | # "error_handling": { 156 | # "ContextWindowExceededError": {"fallback_model": "claude-2"} 157 | # } 158 | # } 159 | # } 160 | # } -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | # import sys, os 2 | # sys.path.insert( 3 | # 0, os.path.abspath("../") 4 | # ) # Adds the parent directory to the system path 5 | import os 6 | import secrets 7 | import traceback 8 | import llm as llm 9 | from utils import getenv, set_env_variables 10 | import json, time 11 | 12 | import litellm 13 | from litellm import BudgetManager 14 | litellm.max_budget = 1000 15 | 16 | budget_manager = BudgetManager(project_name=os.getenv("PROJECT_NAME"), client_type="hosted") 17 | 18 | from fastapi import FastAPI, Request, status, HTTPException, Depends 19 | from fastapi.responses import StreamingResponse 20 | from fastapi.security import OAuth2PasswordBearer 21 | from fastapi.middleware.cors import CORSMiddleware 22 | app = FastAPI() 23 | 24 | app.add_middleware( 25 | CORSMiddleware, 26 | allow_origins=["*"], 27 | allow_credentials=True, 28 | allow_methods=["*"], 29 | allow_headers=["*"], 30 | ) 31 | master_key = os.getenv("LITELLM_PROXY_MASTER_KEY", "sk-litellm-master-key") 32 | user_api_keys = set(budget_manager.get_users()) 33 | oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token") 34 | 35 | ######## AUTH UTILITIES ################ 36 | 37 | def user_api_key_auth(api_key: str = Depends(oauth2_scheme)): 38 | if api_key == master_key: 39 | return 40 | if api_key not in user_api_keys: 41 | raise HTTPException( 42 | status_code=status.HTTP_401_UNAUTHORIZED, 43 | detail={"error": "invalid user key"}, 44 | # TODO: this will be {'detail': {'error': 'something'}} 45 | ) 46 | 47 | 48 | def key_auth(api_key: str = Depends(oauth2_scheme)): 49 | if api_key != master_key: 50 | raise HTTPException( 51 | status_code=status.HTTP_401_UNAUTHORIZED, 52 | detail={"error": "invalid admin key"}, 53 | # TODO: this will be {'detail': {'error': 'something'}} 54 | ) 55 | 56 | ######## CHAT COMPLETIONS ################ 57 | 58 | # for streaming 59 | def data_generator(response): 60 | for chunk in response: 61 | # print(f"chunk: {chunk}") 62 | yield f"data: {json.dumps(chunk)}\n\n" 63 | 64 | # for completion 65 | @app.post("/chat/completions", dependencies=[Depends(user_api_key_auth)]) 66 | async def completion(request: Request): 67 | key = request.headers.get("Authorization").replace("Bearer ", "") # type: ignore 68 | data = await request.json() 69 | print(f"received request data: {data}") 70 | data["user_key"] = key 71 | data["budget_manager"] = budget_manager 72 | data["master_key"] = master_key 73 | set_env_variables(data) 74 | # handle how users send streaming 75 | if 'stream' in data: 76 | if type(data['stream']) == str: # if users send stream as str convert to bool 77 | # convert to bool 78 | if data['stream'].lower() == "true": 79 | data['stream'] = True # convert to boolean 80 | 81 | response = llm.completion(**data) 82 | if 'stream' in data and data['stream'] == True: # use generate_responses to stream responses 83 | return StreamingResponse(data_generator(response), media_type='text/event-stream') 84 | return response 85 | 86 | 87 | @app.get("/models/available") 88 | def get_available_models(): 89 | return {"models": litellm.utils.get_valid_models()} 90 | 91 | 92 | @app.get("/models") # if project requires model list 93 | def model_list(): 94 | available_models = litellm.utils.get_valid_models() 95 | data = [] 96 | for model in available_models: 97 | { 98 | "id": model, 99 | "object": model, 100 | "created": int(time.time()), 101 | "owned_by": "openai" 102 | } 103 | return dict( 104 | data=data, 105 | object="list", 106 | ) 107 | 108 | 109 | @app.get("/health") 110 | async def health(): 111 | return {"status": "ok"} 112 | 113 | ######## KEY MANAGEMENT ################ 114 | 115 | @app.get("/key/cost", dependencies=[Depends(user_api_key_auth)]) 116 | async def report_current(request: Request): 117 | key = request.headers.get("Authorization").replace("Bearer ", "") # type: ignore 118 | return budget_manager.get_model_cost(key) 119 | 120 | 121 | @app.post("/key/new", dependencies=[Depends(key_auth)]) 122 | async def generate_key(request: Request): 123 | try: 124 | data = await request.json() 125 | data.get("total_budget") 126 | except: 127 | raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST) 128 | 129 | total_budget = data["total_budget"] 130 | 131 | api_key = f"sk-litellm-{secrets.token_urlsafe(16)}" 132 | 133 | try: 134 | budget_manager.create_budget( 135 | total_budget=total_budget, user=api_key, duration="monthly" 136 | ) 137 | user_api_keys.add(api_key) 138 | except Exception as e: 139 | traceback.print_exc() 140 | raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR) 141 | 142 | return {"api_key": api_key, "total_budget": total_budget, "duration": "monthly"} 143 | 144 | 145 | if __name__ == "__main__": 146 | import uvicorn 147 | uvicorn.run(app, host="0.0.0.0", port=getenv("PORT", 8080)) 148 | -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically 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authors = ["yujonglee "] 6 | readme = "README.md" 7 | license = "MIT" 8 | 9 | [tool.poetry.dependencies] 10 | python = ">=3.9,<3.12" 11 | litellm = "^0.1.698" 12 | backoff = "^2.2.1" 13 | fastapi = "^0.103.1" 14 | redis = "^5.0.0" 15 | supabase = "^1.0.4" 16 | 17 | [tool.poetry.group.dev.dependencies] 18 | pytest = "^7.4.1" 19 | mypy = "^1.5.0" 20 | black = "^23.7.0" 21 | httpx = "^0.24.1" 22 | uvicorn = "^0.23.2" 23 | 24 | [tool.mypy] 25 | exclude = [".venv"] 26 | explicit_package_bases = "True" 27 | ignore_missing_imports = "True" 28 | 29 | [build-system] 30 | requires = ["poetry-core"] 31 | build-backend = "poetry.core.masonry.api" 32 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | uvicorn 2 | fastapi 3 | litellm 4 | backoff 5 | redis 6 | supabase -------------------------------------------------------------------------------- /test_proxy.py: -------------------------------------------------------------------------------- 1 | from typing import Dict 2 | 3 | import requests 4 | 5 | FASTREPL_PROXY_URL_BASE = "https://fastrepl-proxy-o8ph.zeet-berri.zeet.app" 6 | FASTREPL_PROXY_ADMIN_KEY = "sk-fastrepl-YWp4Yw0-3_g8eaHLK3EJLw" # TODO 7 | 8 | 9 | def new_user(monthly_budget: int) -> str: 10 | resp = requests.post( 11 | f"{FASTREPL_PROXY_URL_BASE}/key/new", 12 | headers={ 13 | "Content-Type": "application/json", 14 | "Authorization": f"Bearer {FASTREPL_PROXY_ADMIN_KEY}", 15 | }, 16 | json={"total_budget": monthly_budget}, 17 | ) 18 | print(resp.json()) 19 | return resp.json() 20 | 21 | 22 | def cost_reset(user_api_key: str): 23 | requests.get( 24 | f"{FASTREPL_PROXY_URL_BASE}/cost/reset", 25 | headers={ 26 | "Content-Type": "application/json", 27 | "Authorization": f"Bearer {user_api_key}", 28 | }, 29 | json={"api_key": user_api_key}, 30 | ) 31 | 32 | 33 | def cost_current(user_api_key: str) -> Dict[str, str]: 34 | resp = requests.get( 35 | f"{FASTREPL_PROXY_URL_BASE}/cost/current", 36 | headers={ 37 | "Content-Type": "application/json", 38 | "Authorization": f"Bearer {user_api_key}", 39 | }, 40 | json={"api_key": user_api_key}, 41 | ) 42 | return resp.json() 43 | 44 | 45 | def completion_request(user_api_key): 46 | resp = requests.post( 47 | f"{FASTREPL_PROXY_URL_BASE}/chat/completions", 48 | headers={ 49 | "Content-Type": "application/json", 50 | "Authorization": f"Bearer {user_api_key}", 51 | }, 52 | json={ 53 | "model": "gpt-3.5-turbo", 54 | "messages": [ 55 | { 56 | "content": "what is YC?", 57 | "role": "user" 58 | } 59 | ] 60 | 61 | } 62 | ) 63 | return resp.json() 64 | 65 | 66 | if __name__ == "__main__": 67 | key = new_user(100)["api_key"] 68 | print("new key", key) 69 | 70 | for _ in range(20): 71 | print(cost_current(key)) 72 | 73 | response = completion_request(key) 74 | print(response) 75 | 76 | 77 | 78 | 79 | 80 | 81 | """ 82 | Using the Proxy: 83 | # Step1 Get a key 84 | 85 | 86 | # Step 2 Make a completion request 87 | playground_api_key = "sk-fastrepl-vSvPSy5YLQxeODhi__GSww" 88 | 89 | resp = requests.post( 90 | f"https://fastrepl-proxy-o8ph.zeet-berri.zeet.app/chat/completions", 91 | headers={ 92 | "Content-Type": "application/json", 93 | "Authorization": f"Bearer sk-fastrepl-vSvPSy5YLQxeODhi__GSww", 94 | }, 95 | json={ 96 | "model": "gpt-3.5-turbo", 97 | "messages": [ 98 | { 99 | "content": "what is YC?", 100 | "role": "user" 101 | } 102 | ] 103 | 104 | } 105 | ) 106 | return resp.json() 107 | 108 | 109 | """ 110 | 111 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/BerriAI/liteLLM-proxy/1ef69ae92bf22600f9a42d15e3b992e1010c9a7e/tests/__init__.py -------------------------------------------------------------------------------- /tests/test_proxy.py: -------------------------------------------------------------------------------- 1 | import pytest 2 | 3 | import litellm 4 | from fastapi.testclient import TestClient 5 | 6 | import proxy.main as main 7 | 8 | 9 | @pytest.fixture 10 | def mock_client(): 11 | client = TestClient(main.app) 12 | yield client 13 | client.close() 14 | 15 | 16 | FASTREPL_PROXY_ADMIN_KEY = "FASTREPL_PROXY_ADMIN_KEY" 17 | 18 | 19 | @pytest.fixture(autouse=True) 20 | def set_env(monkeypatch): 21 | monkeypatch.setenv("FASTREPL_PROXY_ADMIN_KEY", "FASTREPL_PROXY_ADMIN_KEY") 22 | monkeypatch.setattr( 23 | main, 24 | "budget_manager", 25 | litellm.BudgetManager(client_type="local", project_name="fastrepl_proxy"), 26 | ) 27 | 28 | 29 | # TODO: consider https://docs.litellm.ai/docs/completion/mock_requests 30 | @pytest.fixture(autouse=True) 31 | def mock_llm(monkeypatch): 32 | def _completion(**kwargs): 33 | return { 34 | "model": "gpt-3.5-turbo", 35 | "usage": { 36 | "prompt_tokens": 5, 37 | "completion_tokens": 10, 38 | }, 39 | } 40 | 41 | monkeypatch.setattr(litellm, "completion", _completion) 42 | 43 | 44 | def test_auth(mock_client): 45 | response = mock_client.post( 46 | "/chat/completions", headers={"Authorization": "NONE"}, json={} 47 | ) 48 | assert response.status_code == 401 49 | 50 | response = mock_client.post( 51 | "/key/new", 52 | headers={"Authorization": "NONE"}, 53 | json={"total_budget": 1}, 54 | ) 55 | assert response.status_code == 401 56 | 57 | response = mock_client.post( 58 | "/key/new", 59 | headers={"Authorization": f"Bearer {FASTREPL_PROXY_ADMIN_KEY}"}, 60 | json={"total_budget": 1}, 61 | ) 62 | assert response.status_code == 200 63 | key = response.json()["api_key"] 64 | 65 | response = mock_client.post( 66 | "/chat/completions", headers={"Authorization": f"Bearer {key}"}, json={} 67 | ) 68 | assert response.status_code == 200 69 | 70 | 71 | def test_cost(mock_client): 72 | response = mock_client.post( 73 | "/key/new", 74 | headers={"Authorization": f"Bearer {FASTREPL_PROXY_ADMIN_KEY}"}, 75 | json={"total_budget": 100}, 76 | ) 77 | assert response.status_code == 200 78 | key = response.json()["api_key"] 79 | 80 | # once 81 | response = mock_client.post( 82 | "/chat/completions", 83 | headers={"Authorization": f"Bearer {key}"}, 84 | json={}, 85 | ) 86 | response = mock_client.get( 87 | "/cost/current", headers={"Authorization": f"Bearer {key}"} 88 | ) 89 | costs = response.json() 90 | assert costs["gpt-3.5-turbo"] == pytest.approx(2.7499e-05, abs=1e10) 91 | 92 | # twice 93 | response = mock_client.post( 94 | "/chat/completions", 95 | headers={"Authorization": f"Bearer {key}"}, 96 | json={}, 97 | ) 98 | response = mock_client.get( 99 | "/cost/current", headers={"Authorization": f"Bearer {key}"} 100 | ) 101 | costs = response.json() 102 | assert costs["gpt-3.5-turbo"] == pytest.approx(2 * 2.7499e-05, abs=1e10) 103 | 104 | # reset 105 | mock_client.get("/cost/reset", headers={"Authorization": f"Bearer {key}"}) 106 | response = mock_client.get( 107 | "/cost/current", headers={"Authorization": f"Bearer {key}"} 108 | ) 109 | costs = response.json() 110 | assert costs == {} 111 | 112 | 113 | class TestBudgetManager: 114 | def test_budget_enough(self, mock_client): 115 | response = mock_client.post( 116 | "/key/new", 117 | headers={"Authorization": f"Bearer {FASTREPL_PROXY_ADMIN_KEY}"}, 118 | json={"total_budget": 2.7499e-05 + 1}, 119 | ) 120 | assert response.status_code == 200 121 | key = response.json()["api_key"] 122 | 123 | # once 124 | response = mock_client.post( 125 | "/chat/completions", 126 | headers={"Authorization": f"Bearer {key}"}, 127 | json={}, 128 | ) 129 | response = mock_client.get( 130 | "/cost/current", headers={"Authorization": f"Bearer {key}"} 131 | ) 132 | costs = response.json() 133 | assert costs["gpt-3.5-turbo"] == pytest.approx(2.7499e-05, abs=1e10) 134 | 135 | def test_budget_exceed(self, mock_client): 136 | response = mock_client.post( 137 | "/key/new", 138 | headers={"Authorization": f"Bearer {FASTREPL_PROXY_ADMIN_KEY}"}, 139 | json={"total_budget": 1.7499e-05}, 140 | ) 141 | assert response.status_code == 200 142 | key = response.json()["api_key"] 143 | 144 | # once (pass) 145 | response = mock_client.post( 146 | "/chat/completions", 147 | headers={"Authorization": f"Bearer {key}"}, 148 | json={}, 149 | ) 150 | response = mock_client.get( 151 | "/cost/current", headers={"Authorization": f"Bearer {key}"} 152 | ) 153 | costs = response.json() 154 | assert costs["gpt-3.5-turbo"] == pytest.approx(2.7499e-05, abs=1e10) 155 | 156 | # twice (fail) 157 | with pytest.raises(Exception): 158 | mock_client.post( 159 | "/chat/completions", 160 | headers={"Authorization": f"Bearer {key}"}, 161 | json={}, 162 | ) 163 | -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | import os 2 | import functools 3 | from dotenv import load_dotenv 4 | 5 | load_dotenv() 6 | 7 | 8 | @functools.lru_cache(maxsize=None) 9 | def getenv(key, default=0): 10 | return type(default)(os.getenv(key, default)) 11 | 12 | 13 | def set_env_variables(data): 14 | try: 15 | if "env_variables" in data: 16 | env_variables = data["env_variables"] 17 | for key in env_variables: 18 | os.environ[key] = env_variables[key] 19 | data.pop("env_variables") 20 | except: 21 | pass 22 | --------------------------------------------------------------------------------