{"name":"QueryWeaver: Transform Natural Language into SQL with Graph-Powered Text2SQL","description":"QueryWeaver is an open-source Text2SQL tool that allows users to query databases using plain English. It leverages graph-powered schema understanding to accurately convert natural language questions into SQL. This simplifies database interaction, making data accessible without deep SQL knowledge.","github":"https://github.com/FalkorDB/QueryWeaver","url":"https://osrepos.com/repo/falkordb-queryweaver","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/falkordb-queryweaver","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/falkordb-queryweaver.md","json":"https://osrepos.com/repo/falkordb-queryweaver.json","topics":["falkordb","semantic-layer","text2sql","typescript","database-tools","ai","natural-language-processing"],"keywords":["falkordb","semantic-layer","text2sql","typescript","database-tools","ai","natural-language-processing"],"stars":null,"summary":"QueryWeaver is an open-source Text2SQL tool that allows users to query databases using plain English. It leverages graph-powered schema understanding to accurately convert natural language questions into SQL. This simplifies database interaction, making data accessible without deep SQL knowledge.","content":"## Introduction\nQueryWeaver is an innovative open-source Text2SQL tool developed by FalkorDB. It empowers users to interact with their databases using natural language, transforming plain English questions into precise SQL queries. By employing graph-powered schema understanding, QueryWeaver accurately interprets user intent and database structure, making data access more intuitive and efficient for everyone, regardless of their SQL proficiency.\n\n## Installation\nGetting started with QueryWeaver is straightforward, especially using Docker for quick evaluation.\n\n**Docker (Recommended for evaluation):**\nbash\ndocker run -p 5000:5000 -it falkordb/queryweaver\n\nAfter running this command, you can launch QueryWeaver in your browser by navigating to `http://localhost:5000`.\n\nFor more advanced configurations, such as setting environment variables for AI providers or custom settings, you can utilize an `.env` file or pass individual environment variables directly to the Docker command. Refer to the official GitHub repository for detailed setup instructions.\n\n## Examples\nQueryWeaver exposes a powerful REST API for managing graphs (database schemas) and executing Text2SQL queries. All user-scoped operations require authentication via a bearer token.\n\n**1. List Graphs (GET)**\nRetrieve a list of available graphs for the authenticated user.\nbash\ncurl -s -H \"Authorization: Bearer $TOKEN\" \\\n   https://app.queryweaver.ai/graphs\n\n\n**2. Query a Graph (POST)**\nRun a chat-based Text2SQL request against a named graph. The endpoint streams processing steps and the final SQL back to the client.\nbash\ncurl -s -H \"Authorization: Bearer $TOKEN\" -H \"Content-Type: application/json\" \\\n   -d '{\"chat\": [\"Count orders last week\"]}' \\\n   https://app.queryweaver.ai/graphs/my_database\n\nThis example demonstrates how to query `my_database` to count orders from the last week using a natural language prompt.\n\n## Why Use QueryWeaver?\nQueryWeaver stands out as a powerful solution for database interaction due to several key features:\n*   **Natural Language Interface**: Ask database questions in plain English, significantly reducing the need for complex SQL query writing.\n*   **Graph-Powered Schema Understanding**: Utilizes advanced graph technology to accurately interpret database schemas and user intent, leading to more precise SQL generation.\n*   **Open-Source and Flexible**: As an open-source project, it offers transparency, community support, and extensive customization options. It supports integration with multiple AI providers, including OpenAI, Gemini, Anthropic, Azure, and Ollama.\n*   **Robust REST API**: Provides a comprehensive API for seamless integration into existing applications, dashboards, and automated workflows.\n*   **Conversation Memory**: Stores per-user conversation memory in FalkorDB, enabling more natural, contextual, and continuous interactions over time.\n\n## Links\n*   [GitHub Repository](https://github.com/FalkorDB/QueryWeaver)\n*   [Discord Community](https://discord.gg/b32KEzMzce)\n*   [Try QueryWeaver on FalkorDB Cloud](https://app.falkordb.cloud)\n*   [Docker Hub](https://hub.docker.com/r/falkordb/queryweaver/)\n*   [Swagger UI (API Documentation)](https://app.queryweaver.ai/docs)","metrics":{"detailViews":0,"githubClicks":1},"dates":{"published":null,"modified":"2026-03-23T21:06:41.000Z"}}