8f3a82e0df* Update docs from Notion * feat: Add RAG (Retrieval-Augmented Generation) components documentation This commit adds documentation for RAG (Retrieval-Augmented Generation) components. It explains how these components process a user query by retrieving relevant documents and generating a concise summary that addresses the user's question. The documentation includes information about the Vectara component, its parameters, and the Vectara corpus. For more details, refer to the [Vectara documentation](https://docs.vectara.com/docs). --------- Co-authored-by: ogabrielluiz <ogabrielluiz@users.noreply.github.com> Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
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| title | sidebar_position | slug |
|---|---|---|
| LangWatch | 1 | /integrations-langwatch |
LangWatch
LangWatch is an all-in-one LLMOps platform for monitoring, observability, analytics, evaluations and alerting for getting user insights and improve your LLM workflows.
To integrate with Langflow, just add your LangWatch API as a Langflow environment variable and you are good to go!
Step-by-step Configuration
- Obtain your LangWatch API key from https://app.langwatch.ai/
- Add the following key to Langflow .env file:
LANGWATCH_API_KEY="your-api-key"
or export it in your terminal:
export LANGWATCH_API_KEY="your-api-key"
- Restart Langflow using
langflow run --env-file .env - Run any project and check the LangWatch dashboard for monitoring and observability.
