ReliAPI
Stop losing money on failed OpenAI and Anthropic API calls.
70 followers
Stop losing money on failed OpenAI and Anthropic API calls.
70 followers
Unlike generic API proxies, ReliAPI is built specifically for LLM APIs (OpenAI, Anthropic, Mistral) and HTTP APIs. Key differentiators: • Smart caching reduces costs by 50-80% • Idempotency prevents duplicate charges • Budget caps reject expensive requests • Automatic retries with exponential backoff & circuit breaker • Real-time cost tracking for LLM calls • Works with OpenAI, Anthropic, Mistral, and HTTP APIs • Understands LLM challenges: token costs, streaming, rate limits Use from RapidAPI
Products used by ReliAPI
Explore the tech stack and tools that power ReliAPI. See what products ReliAPI uses for development, design, marketing, analytics, and more.
Engineering & Development 4
Engineering & Development 4
RedisBuild AI apps with more speed, memory, and accuracy.
5.0 (16 reviews)
Using Redis for caching and idempotency instead of in-memory solutions (like Python's `functools.lru_cache`) because it's persistent, scalable, and handles concurrent requests perfectly. Tried Memcached, but Redis's data structures (sets, hashes) were perfect for idempotency keys. Essential for production reliability.
DockerAccelerate how you build, share, and run applications
5.0 (32 reviews)
Using Docker for deployment instead of manual setup or Kubernetes because it ensures consistency across environments and makes scaling trivial. Manual deployment was error-prone ("works on my machine"), Kubernetes was overkill for our scale. Docker Compose gave us the perfect balance. One image works everywhere.
FastAPIA modern, fast web framework for building APIs with Python
5.0 (32 reviews)
Chose FastAPI over Flask/Django because of its automatic OpenAPI generation, async support, and type hints. Flask was too simple for our needs, Django too heavy. FastAPI's type hints caught bugs at development time, not production. Perfect for building production-ready APIs fast.
Python.orgThe official home of the Python Programming Language
5.0 (33 reviews)
Built on Python 3.11+ because of its excellent async support, rich ecosystem, and developer experience. Considered Go for performance, but Python's ecosystem for LLM APIs is unmatched. Node.js was tempting, but Python's async/await is more mature. Perfect balance of performance and productivity.
General 1
General 1
PydanticMost widely used data validation library for Python.
5.0 (1 review)
Using Pydantic for data validation instead of manual validation or Marshmallow because it's type-safe, fast, and integrates perfectly with FastAPI. Started with manual validation (error-prone), considered Marshmallow, but Pydantic's type hints integration is seamless. Catches errors before they reach production.