# uni-api

docker pull

[English](./README.md) | [Chinese](./README_CN.md) ## Introduction If used personally, one/new-api is too complex and has many commercial features that individuals do not need. If you do not want a complex front-end interface and want to support more models, you can try uni-api. This is a project that unifies the management of large model APIs, allowing multiple backend services to be called through a unified API interface and uniformly converted to the OpenAI format, supporting load balancing. Currently supported backend services include: OpenAI, Anthropic, Gemini, Vertex, Cohere, Groq, Cloudflare, DeepBricks, OpenRouter, etc. ## Features - No frontend, pure configuration file setup for API channels. You can run your own API site by just writing one file, with detailed configuration guides in the documentation, beginner-friendly. - Unified management of multiple backend services, supporting providers like OpenAI, Deepseek, DeepBricks, OpenRouter, and other APIs in the OpenAI format. Supports OpenAI Dalle-3 image generation. - Supports Anthropic, Gemini, Vertex AI, Cohere, Groq, Cloudflare. Vertex supports both Claude and Gemini APIs. - Supports OpenAI, Anthropic, Gemini, Vertex native tool use function calls. - Supports OpenAI, Anthropic, Gemini, Vertex native image recognition API. - Supports four types of load balancing. 1. Supports channel-level weighted load balancing, which can allocate requests based on different channel weights. Disabled by default, requires channel weight configuration. 2. Supports Vertex regional load balancing, supports Vertex high concurrency, and can increase Gemini, Claude concurrency by up to (number of APIs * number of regions) times. Automatically enabled without additional configuration. 3. In addition to Vertex region-level load balancing, all APIs support channel-level sequential load balancing, enhancing the immersive translation experience. Automatically enabled without additional configuration. 4. Support automatic API key-level round-robin load balancing for multiple API Keys in a single channel. - Supports automatic retry, when an API channel response fails, automatically retry the next API channel. - Supports fine-grained access control. Supports using wildcards to set specific models for API key available channels. - Supports rate limiting, can set the maximum number of requests per minute, can be set as an integer, such as 2/min, 2 times per minute, 5/hour, 5 times per hour, 10/day, 10 times per day, 10/month, 10 times per month, 10/year, 10 times per year. Default is 60/min. ## Configuration Using the api.yaml configuration file, multiple models can be configured, and each model can be configured with multiple backend services, supporting load balancing. Below is an example of the api.yaml configuration file: ```yaml providers: - provider: provider_name # Service provider name, such as openai, anthropic, gemini, openrouter, deepbricks, can be any name, required base_url: https://api.your.com/v1/chat/completions # Backend service API address, required api: sk-YgS6GTi0b4bEabc4C # Provider's API Key, required model: # At least one model is required - gpt-4o # Usable model name, required - claude-3-5-sonnet-20240620: claude-3-5-sonnet # Rename model, claude-3-5-sonnet-20240620 is the provider's model name, claude-3-5-sonnet is the renamed name, you can use a concise name instead of the original complex name, optional - dall-e-3 - provider: anthropic base_url: https://api.anthropic.com/v1/messages api: # Supports multiple API Keys, multiple keys automatically enable round-robin load balancing, at least one key, required - sk-ant-api03-bNnAOJyA-xQw_twAA - sk-ant-api02-bNnxxxx model: - claude-3-5-sonnet-20240620: claude-3-5-sonnet # Rename model, claude-3-5-sonnet-20240620 is the provider's model name, claude-3-5-sonnet is the renamed name, you can use a concise name instead of the original complex name, optional tools: true # Whether to support tools, such as code generation, document generation, etc., default is true, optional - provider: gemini base_url: https://generativelanguage.googleapis.com/v1beta # base_url supports v1beta/v1, only for Gemini models, required api: AIzaSyAN2k6IRdgw model: - gemini-1.5-pro - gemini-1.5-flash-exp-0827: gemini-1.5-flash # After renaming, the original model name gemini-1.5-flash-exp-0827 cannot be used, if you want to use the original name, you can add the original name in the model, just add the line below to use the original name - gemini-1.5-flash-exp-0827 # Add this line, both gemini-1.5-flash-exp-0827 and gemini-1.5-flash can be requested tools: true - provider: vertex project_id: gen-lang-client-xxxxxxxxxxxxxx # Description: Your Google Cloud Project ID. Format: String, usually consists of lowercase letters, numbers, and hyphens. How to get it: You can find your project ID in the project selector of the Google Cloud Console. private_key: "-----BEGIN PRIVATE KEY-----\nxxxxx\n-----END PRIVATE" # Description: Private key of Google Cloud Vertex AI service account. Format: A JSON formatted string containing the private key information of the service account. How to get it: Create a service account in the Google Cloud Console, generate a JSON formatted key file, and then set its content as the value of this environment variable. client_email: xxxxxxxxxx@xxxxxxx.gserviceaccount.com # Description: Email address of the Google Cloud Vertex AI service account. Format: Usually a string like "service-account-name@project-id.iam.gserviceaccount.com". How to get it: Generated when creating the service account, can also be found in the "IAM & admin" section of the Google Cloud Console. model: - gemini-1.5-pro - gemini-1.5-flash - claude-3-5-sonnet@20240620: claude-3-5-sonnet - claude-3-opus@20240229: claude-3-opus - claude-3-sonnet@20240229: claude-3-sonnet - claude-3-haiku@20240307: claude-3-haiku tools: true notes: https://xxxxx.com/ # You can put the service provider's website, notes, official documentation, optional - provider: cloudflare api: f42b3xxxxxxxxxxq4aoGAh # Cloudflare API Key, required cf_account_id: 8ec0xxxxxxxxxxxxe721 # Cloudflare Account ID, required model: - '@cf/meta/llama-3.1-8b-instruct': llama-3.1-8b # Rename model, @cf/meta/llama-3.1-8b-instruct is the provider's original model name, must be enclosed in quotes, otherwise a yaml syntax error, llama-3.1-8b is the renamed name, you can use a concise name instead of the original complex name, optional - '@cf/meta/llama-3.1-8b-instruct' # Must be enclosed in quotes, otherwise a yaml syntax error - provider: other-provider base_url: https://api.xxx.com/v1/messages api: sk-bNnAOJyA-xQw_twAA model: - causallm-35b-beta2ep-q6k: causallm-35b - anthropic/claude-3-5-sonnet tools: false engine: openrouter # Force the use of a specific message format, currently supports gpt, claude, gemini, openrouter native format, optional api_keys: - api: sk-KjjI60Yf0JFWtfgRmXqFWyGtWUd9GZnmi3KlvowmRWpWpQRo # API Key, users need an API key to use this service, required model: # Models that this API Key can use, required - gpt-4o # Usable model name, can use all gpt-4o models provided by providers - claude-3-5-sonnet # Usable model name, can use all claude-3-5-sonnet models provided by providers - gemini/* # Usable model name, can only use all models provided by the provider named gemini, where gemini is the provider name, * represents all models role: admin - api: sk-pkhf60Yf0JGyJygRmXqFQyTgWUd9GZnmi3KlvowmRWpWqrhy model: - anthropic/claude-3-5-sonnet # Usable model name, can only use the claude-3-5-sonnet model provided by the provider named anthropic. This method will not match the model named anthropic/claude-3-5-sonnet provided by other-provider. - # By adding angle brackets on both sides of the model name, it will not look for the claude-3-5-sonnet model under the channel named anthropic, but will take the entire anthropic/claude-3-5-sonnet as the model name. This method can match the model named anthropic/claude-3-5-sonnet provided by other-provider. But it will not match the claude-3-5-sonnet model under anthropic. preferences: USE_ROUND_ROBIN: true # Whether to use round-robin load balancing, true to use, false to not use, default is true. When enabled, each request to the model will be made in sequence according to the model configuration. It has nothing to do with the original channel order in providers. Therefore, you can set a different request order for each API key. AUTO_RETRY: true # Whether to automatically retry, automatically retry the next provider, true to automatically retry, false to not automatically retry, default is true RATE_LIMIT: 2/min # Supports rate limiting, maximum number of requests per minute, can be set to an integer, such as 2/min, 2 times per minute, 5/hour, 5 times per hour, 10/day, 10 times per day, 10/month, 10 times per month, 10/year, 10 times per year. Default is 60/min, optional # Channel-level weighted load balancing configuration example - api: sk-KjjI60Yf0JFWtxxxxxxxxxxxxxxwmRWpWpQRo model: - gcp1/*: 5 # The number after the colon is the weight, the weight only supports positive integers. - gcp2/*: 3 # The larger the number, the greater the probability of the request. - gcp3/*: 2 # In this example, there are a total of 10 weights for all channels, and 5 out of 10 requests will request the gcp1/* model, 2 requests will request the gcp2/* model, and 3 requests will request the gcp3/* model. preferences: USE_ROUND_ROBIN: true # When USE_ROUND_ROBIN must be true and there is no weight after the above channels, it will request according to the original channel order, if there is weight, it will request according to the weighted order. AUTO_RETRY: true ``` ## Environment Variables - CONFIG_URL: The download address of the configuration file, it can be a local file or a remote file, optional - TIMEOUT: Request timeout, default is 100 seconds, the timeout can control the time needed to switch to the next channel when a channel does not respond. Optional ## Docker Local Deployment Start the container ```bash docker run --user root -p 8001:8000 --name uni-api -dit \ -e CONFIG_URL=http://file_url/api.yaml \ # If the local configuration file is already mounted, you do not need to set CONFIG_URL -v ./api.yaml:/home/api.yaml \ # If CONFIG_URL is already set, you do not need to mount the configuration file -v ./uniapi_db:/home/data \ # If you do not want to save statistical data, you do not need to mount the stats.db file yym68686/uni-api:latest ``` Or if you want to use Docker Compose, here is a docker-compose.yml example: ```yaml services: uni-api: container_name: uni-api image: yym68686/uni-api:latest environment: - CONFIG_URL=http://file_url/api.yaml # If the local configuration file is already mounted, there is no need to set CONFIG_URL ports: - 8001:8000 volumes: - ./api.yaml:/home/api.yaml # If CONFIG_URL is already set, there is no need to mount the configuration file - ./uniapi_db:/home/data # If you do not want to save statistical data, there is no need to mount the stats.db file ``` CONFIG_URL is used to automatically download remote configuration files. For example, if it is inconvenient to modify the configuration file on a certain platform, you can upload the configuration file to a hosting service and provide a direct link for uni-api to download. CONFIG_URL is this direct link. If you are using a locally mounted configuration file, you do not need to set CONFIG_URL. CONFIG_URL is used in situations where it is inconvenient to mount the configuration file. Run Docker Compose container in the background ```bash docker-compose pull docker-compose up -d ``` Docker build ```bash docker build --no-cache -t uni-api:latest -f Dockerfile --platform linux/amd64 . docker tag uni-api:latest yym68686/uni-api:latest docker push yym68686/uni-api:latest ``` One-Click Restart Docker Image ```bash set -eu docker pull yym68686/uni-api:latest docker rm -f uni-api docker run --user root -p 8001:8000 -dit --name uni-api \ -e CONFIG_URL=http://file_url/api.yaml \ -v ./api.yaml:/home/api.yaml \ -v ./uniapi_db:/home/data \ yym68686/uni-api:latest docker logs -f uni-api ``` RESTful curl test ```bash curl -X POST http://127.0.0.1:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -H "Authorization: Bearer ${API}" \ -d '{"model": "gpt-4o","messages": [{"role": "user", "content": "Hello"}],"stream": true}' ``` ## Star History Star History Chart