diegosouzapw/OmniRoute

Features

• LLM Gateways - Provides a unified API gateway that aggregates multiple LLM providers into a single standardized endpoint.
• Unified AI API Endpoints - Provides a single OpenAI-compatible endpoint that abstracts multiple AI providers into a unified interface.
• AI Model Routing Strategies - Distributes prompts across providers using logic like cost-optimization, priority-based fallbacks, and round-robin.
• OpenAI-Compatible APIs - Provides an OpenAI-compatible endpoint to integrate a wide range of AI tools without manual configuration.
• AI Request Routing - Routes AI requests across providers using cost-optimization and priority-based fallbacks to ensure uptime.
• API Translation Layers - Maps proprietary model formats to standard API specifications, allowing multiple AI models to share one endpoint.
• Conversation Memory Stores - Persists interaction history to maintain state and context across multi-turn AI conversations.
• LLM Cost Management - Optimizes token usage and operational costs through semantic prompt compression and free tier aggregation.
• Model Fallbacks - Automatically switches to alternative AI models when the primary provider fails or hits rate limits.
• Sampling Provider Fallbacks - Provides instant failover to backup providers when the primary AI service is unavailable or rate-limited.
• Provider Failover Handlers - Implements millisecond failover to alternative providers when primary quotas are exhausted or services fail.
• LLM Token Compression - Reduces billed token usage through semantic pruning and deduplication of prompts to maximize the context window.
• Conversation Memory Retrieval - Enables context-aware recall of conversation history using a hybrid of keyword search and vector retrieval.
• Local Database Security - Implements local database security to ensure the privacy of encrypted API keys and usage history.
• Local-First Storage - Implements a local-first storage strategy using an encrypted database to ensure user data sovereignty and privacy.
• Encrypted - Saves API keys and usage history in an AES-256-GCM encrypted database residing entirely on the user's hardware.
• Routing Strategies - Selects the next provider based on specific logic such as priority, round-robin, or cost-optimization.
• Vector Memory Stores - Uses hybrid vector and keyword indexing to store and retrieve long-term context for AI agents.
• API Protocol Translations - Transparently converts requests and responses between different AI provider formats to ensure cross-service compatibility.
• Model Connectivity Resilience - Ensures high availability of AI APIs through a multi-layer resilience model including circuit breakers and cooldowns.
• Credential Encryption - Secures API keys and authentication tokens using AES-256-GCM encryption when stored on the local disk.
• Encrypted Storage - Stores sensitive API keys and conversation history in an AES-256-GCM encrypted database on local hardware.
• Encrypted Credential Storage - Secures API keys and conversation history in an AES-256-GCM encrypted local-first database.
• Multi-Provider Credential Stores - Manages API key storage and granular access scopes for multiple AI providers in a centralized store.
• AI Provider Gateways - Provides a specialized gateway for AI agents to autonomously manage routing, providers, and data compression.
• Provider Circuit Breakers - Implements failure isolation for external AI provider calls using circuit breakers to allow for service recovery.
• Provider-Agnostic LLM Routing - Directs LLM prompts to multiple providers using automatic scoring for availability, speed, and cost.
• Agent Communication Protocols - Runs standardized servers that facilitate communication between agents using industry-standard AI protocols.
• Agent Gateways - Provides a unified interface for AI agents to autonomously manage routing and provider configurations.
• Configuration Utilities - Offers a one-command setup to route multiple coding agents through the unified gateway.
• AI Agent Servers - Implements a standardized server that exposes routing and provider configurations to AI agents.
• MCP Server Integrations - Serves tools over multiple transport layers using the Model Context Protocol for external integration.
• Free AI Tier Aggregators - Integrates with numerous free provider tiers to access AI capabilities without requiring a credit card.
• Free Tier Aggregators - Aggregates free service tiers from multiple AI providers into a single dashboard to maximize available resources.
• Token Quota Managers - Provides systems to track and maximize the consumption of free token quotas across multiple AI providers.
• MCP Gateways - Integrates Model Context Protocol gateways to allow AI agents to manage routing and memory autonomously.
• Tool Output Compression - Implements specialized compression for tool call results to minimize token consumption and reduce processing costs.
• Quota Aggregators - Combines documented free tiers from various provider pools to track and maximize total available tokens.
• AI - Tests how requests flow through different strategy combinations without sending actual data to a provider.
• A2A Protocol Servers - Runs a server using the A2A protocol to enable smart routing and health reporting between agents.
• CLI Gateways - Provides a command-line interface to manage providers, routing rules, and token compression settings.
• Local Reverse Proxies - Operates as a local proxy on the user's hardware to prevent sensitive data from leaving the machine.
• Routing Decision Audit Trails - Maintains a searchable audit trail of routing decisions and tool calls for operational observability.
• AI Content Filters - Employs automated guardrails to scan and filter AI model prompts and responses for harmful content.
• LLM Prompt Injection Prevention - Inspects LLM requests using a dedicated security guard to prevent prompt injection attacks.
• CLI System Management - Allows configuration of provider keys and routing rules directly from the terminal.
• Cost and Token Trackers - Tracks token consumption and calculates costs per session, accounting for cache hits and compression.
• Endpoint Tool Mappers - Maps diverse AI provider endpoints into a unified format for seamless integration with external tools.
• LLM Applications - Self-hostable AI gateway with automatic fallback routing.
• Task Runners and Orchestration - Intelligent routing across multiple LLM providers with load balancing.
• High-Performance Serving Systems - Unified AI gateway and proxy supporting multiple providers with token compression.

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