yym68686/uni-api
Uni Api
Acest proiect este un gateway API de inteligență artificială care centralizează conexiunile către mai mulți furnizori de modele într-o singură interfață standardizată. Acționând ca un proxy, traduce diverse protocoale ale furnizorilor într-un format compatibil cu clienții existenți, permițând dezvoltatorilor să integreze diverse modele de limbaj fără a gestiona SDK-uri specifice fiecărui furnizor.
Gateway-ul se distinge printr-un strat robust de gestionare a traficului care include rutarea inteligentă a cererilor, echilibrarea ponderată a sarcinii și mecanisme automate de failover pentru a asigura disponibilitatea serviciului. Încorporează un pipeline modular de middleware care gestionează autentificarea, limitarea ratei (rate limiting) și moderarea conținutului, menținând în același timp controlul centralizat asupra credențialelor furnizorilor și a căilor de rutare a modelelor prin fișiere de configurare.
Dincolo de proxy-ul de bază, sistemul oferă o vizibilitate operațională completă prin monitorizarea volumului de cereri, a latenței și a consumului de token-uri în toate serviciile conectate. Suportă controale de acces administrativ și monitorizarea stării de sănătate a serviciilor pentru a facilita analiza performanței și gestionarea costurilor în diverse medii de deployment.
Features
- LLM Gateways - Centralizes multiple artificial intelligence provider connections into a single standard interface.
- Weighted Load Balancing - Distributes incoming traffic across multiple backend model providers using weighted strategies to optimize performance and throughput.
- Unified Provider Interfaces - Provides a unified interface that bridges diverse artificial intelligence service protocols.
- Unified AI API Endpoints - Translates diverse artificial intelligence service protocols into a consistent format to simplify integration.
- AI Model Load Balancers - Distributes incoming requests across multiple backend AI providers to optimize performance and availability.
- Authenticated Request Proxies - Acts as a centralized gateway managing authentication, rate limiting, and usage tracking for upstream AI services.
- Gateway-Based Request Routings - Directs incoming traffic through a centralized gateway that manages authentication, rate limiting, and request distribution.
- API Access Security - Secures API access through rate limiting and permission management to protect backend resources from excessive traffic.
- Request Rate Limiters - Restricts request volume per API key to maintain predictable service usage and prevent resource exhaustion.
- OpenAI-Compatible Model Servers - Converts requests from various model providers into a consistent format for seamless integration with existing applications.
- Server Capability Exposure - Exposes specialized model capabilities like tool use and image processing through a unified interface.
- Request Retries - Automatically reroutes failed requests to alternative service channels to ensure continuous uptime.
- Configuration-Driven Deployments - Uses centralized configuration files to define routing paths, credentials, and service policies.
- Middleware-Based Request Pipelines - Processes incoming API calls through a modular pipeline of filters for logging, security, and usage tracking.
- Gateway Configuration - Centralizes gateway settings, provider credentials, and routing paths within configuration files.
- Load Balancing Strategies - Distributes API requests across multiple service channels using weighted or failure-aware algorithms.
- API Credential Managers - Centralizes and secures third-party service credentials while isolating upstream provider keys from client-facing interfaces.
- Service Failover Mechanisms - Ensures continuous uptime by automatically rerouting failed requests to alternative service channels and managing unresponsive providers.
- AI Usage - Tracks request volume, latency, and token consumption across multiple language model providers.
- Service Health Monitoring - Exports request metrics and logs to track performance trends and identify integration issues.
- Cost and Token Trackers - Measures request volume, latency, and token consumption to maintain visibility into operational performance and costs.
- Protocol Adapters - Translates diverse third-party artificial intelligence service protocols into a single standardized format.
