Template description
This n8n workflow demonstrates how to create an agent using LangChain and SQLite. The agent can understand natural language queries and interact with a SQLite database to provide accurate answers. πͺ
π Setup
Run the top part of the workflow once.
It downloads the example SQLite database, extracts from a ZIP file and saves locally (chinook.db).
π£οΈ Chatting with Your Data
- Send a message in a chat window.
- Locally saved SQLite database loads automatically.
- User's chat input is combined with the binary data.
- The LangChain Agend node gets both data and begins to work.
The AI Agent will process the user's message, perform necessary SQL queries, and generate a response based on the database information. ποΈ
π Example Queries
Try these sample queries to see the AI Agent in action:
- "Please describe the database" - Get a high-level overview of the database structure, only one or two queries are needed.
- "What are the revenues by genre?" - Retrieve revenue information grouped by genre, LangChain agent iterates several time before producing the answer.
The AI Agent will store the final answer in its memory, allowing for context-aware conversations. π¬
Read the full article: π https://blog.n8n.io/ai-agents/
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Please reach out to Eduard is you need further assistance with you n8n workflows and automations!
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