Helicone vs LangSmith

Docs • Changelog • Bug reports • See Helicone in Action! (Free)

Helicone is an AI Gateway & LLM Observability Platform for AI Engineers

• 🌐 AI Gateway: Access 100+ AI models with 1 API key through the OpenAI API with intelligent routing and automatic fallbacks. Get started in 2 minutes.
• 🔌 Quick integration: One-line of code to log all your requests from OpenAI, Anthropic, LangChain, Gemini, Vercel AI SDK, and more.
• 📊 Observe: Inspect and debug traces & sessions for agents, chatbots, document processing pipelines, and more
• 📈 Analyze: Track metrics like cost, latency, quality, and more. Export to PostHog in one-line for custom dashboards
• 🎮 Playground: Rapidly test and iterate on prompts, sessions and traces in our UI.
• 🧠 Prompt Management: Version prompts using production data. Deploy prompts through the AI Gateway without code changes. Your prompts remain under your control, always accessible.
• 🎛️ Fine-tune: Fine-tune with one of our fine-tuning partners: OpenPipe or Autonomi (more coming soon)
• 🛡️ Enterprise Ready: SOC 2 and GDPR compliant

🎁 Generous monthly free tier (10k requests/month) - No credit card required!

Quick Start ⚡️

1. Get your API key by signing up here and add credits at helicone.ai/credits

2. Update the baseURL in your code and add your API key.

   import OpenAI from "openai";
   
   const client = new OpenAI({
     baseURL: "https://ai-gateway.helicone.ai",
     apiKey: process.env.HELICONE_API_KEY,
   });
   
   const response = await client.chat.completions.create({
     model: "gpt-4o-mini",  // claude-sonnet-4, gemini-2.0-flash or any model from https://www.helicone.ai/models
     messages: [{ role: "user", content: "Hello!" }]
   });
   

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3. 🎉 You're all set! View your logs at Helicone and access 100+ models through one API.

Self-Hosting Open Source LLM Observability

Docker

Helicone is simple to self-host and update. To get started locally, just use our docker-compose file.

## Clone the repository
git clone https://github.com/Helicone/helicone.git
cd docker
cp .env.example .env

## Start the services
./helicone-compose.sh helicone up

Helm

For Enterprise workloads, we also have a production-ready Helm chart available. To access, contact us at enterprise@helicone.ai.

Manual (Not Recommended)

Manual deployment is not recommended. Please use Docker or Helm. If you must, follow the instructions here.

Architecture

Helicone is comprised of five services:

• Web: Frontend Platform (NextJS)
• Worker: Proxy Logging (Cloudflare Workers)
• Jawn: Dedicated Server for serving collecting logs (Express + Tsoa)
• Supabase: Application Database and Auth
• ClickHouse: Analytics Database
• Minio: Object Storage for logs.

Integrations 🔌

Inference Providers

Frameworks

This list may be out of date. Don't see your provider or framework? Check out the latest integrations in our docs. If not found there, request a new integration by contacting help@helicone.ai.

Contributing

We ❤️ our contributors! We warmly welcome contributions for documentation, integrations, costs, and feature requests.

If you have an idea for how Helicone can be better, create a GitHub issue.

License

Helicone is licensed under the Apache v2.0 License.

Additional Resources

• LLM Cost API: We have the largest open-source API pricing database with 300+ models and providers such as OpenAI, Anthropic and more. Start querying here.

• Data Management: Manage and export your Helicone data with our API or access it with our MCP server.

  • Guides: ETL, Request Exporting

• Data Ownership: Learn about Data Ownership and Autonomy

For more information, visit our documentation.

Contributors

Overview

LangSmith Observability is LangChain's platform for seeing what AI agents and LLM applications actually do in production. It captures traces of every model call, tool call, retrieval step and agent decision, then lets you inspect, compare, evaluate and alert on them.

It is framework-agnostic: you can trace LangGraph and LangChain applications, or instrument any stack with the Python, TypeScript, Go or Java SDKs.

Core capabilities

• Tracing — hierarchical traces show each run, its inputs/outputs, latency, token usage and errors, including nested tool and retrieval calls.
• Agent visibility — follow an agent's reasoning and tool use across steps to find where it went wrong.
• Evaluation — build datasets from real traces, run offline and online evaluators, and compare prompt/model versions.
• Prompt management — version, test and deploy prompts from a central registry.
• Monitoring and alerts — dashboards for latency, error rate, cost and quality; alert when behavior drifts.
• Framework and SDK coverage — native integrations for LangGraph/LangChain plus OpenTelemetry-style instrumentation for other stacks.
• Self-hosting and BYOC — Enterprise can run LangSmith in their own Kubernetes cluster on AWS, GCP or Azure so data never leaves their environment.
• Low overhead — the SDK uses an async callback handler and a distributed collector, so tracing does not block application requests; if LangSmith has an incident, the agent keeps running.

Data and privacy

LangSmith cloud data is stored in GCP us-central-1. LangChain states it does not train on customer data, and customers retain rights to their data. Enterprise self-hosted/BYOC options exist for compliance-sensitive teams.

Getting started

1. Create a LangSmith account at smith.langchain.com.
2. Install the SDK for your language and set the API key.
3. Wrap your app or agent; traces appear in the project view.
4. Build a dataset from interesting traces and add evaluators.
5. Set up monitoring dashboards and alerts for production.
6. For self-hosting, follow the Kubernetes deployment guide.

Pricing

LangSmith has a free tier for development and small-scale production; paid plans scale with trace volume, and Enterprise adds self-hosting/BYOC and support. See langchain.com/pricing for current tiers.

Links

• Product: langchain.com/langsmith/observability
• App: smith.langchain.com
• Docs: docs.smith.langchain.com
• Self-hosting: docs.smith.langchain.com/self_hosting/kubernetes