helicone

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Basic Information

Helicone is an open-source LLM developer platform focused on observability, logging, and management for applications that use large language models. The repo provides code and deployment options to capture and inspect LLM requests and responses across many providers, enabling developers to route API calls through a Helicone gateway or use one-line integration code to log activity. It supports both a hosted cloud offering and self-hosted deployment via Docker and Helm. The project targets debugging, tracing, session inspection, prompt versioning, automated evaluation, and analytics for chatbots, agents, and document pipelines. The README documents supported integrations, self-host architecture components, and quick-start examples for connecting OpenAI and other providers. The repository also includes tooling for exports, data ownership, and enterprise features such as compliance and production Helm charts.

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App Details

Features
Helicone bundles observability features designed for LLM applications. Core features include one-line integration for logging requests to many LLM providers, a UI playground for testing prompts and sessions, and tracing and session inspection to debug agent and pipeline behavior. Analytics capabilities track cost, latency, and quality metrics with export options to analytics tools. Prompt management supports versioning and experimentation on production data. Evaluation integrations let you run automated evals against traces or sessions. Fine-tuning integrations with partners are included. The gateway offers caching, custom rate limits, and LLM security controls. Deployment options include Docker compose for local/self-hosted setups and a production-ready Helm chart for enterprises. Architecture components listed are a Next.js web frontend, Cloudflare worker proxy, an express server for logs, Supabase, ClickHouse, and Minio for storage.
Use Cases
Helicone helps development teams monitor, debug, and optimize applications that use LLMs by centralizing request and trace data and surfacing operational metrics. Teams can quickly integrate Helicone to capture calls across OpenAI, Anthropic, Gemini, local models, and other providers, then inspect sessions to find prompt regressions or latency issues. The platform supports prompt versioning and experimentation so teams can iterate on prompts using real production traffic. Export and analytics integrations enable custom dashboards and cost tracking. Self-hosting options and enterprise Helm charts provide on-prem or private deployments, while the cloud offering reduces latency and simplifies onboarding. Compliance and data ownership tools help organizations meet governance requirements while enabling fine-tuning and evaluation workflows.

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