Assessment Task: Web-Based Chatbot for Translating Natural Language to Cypher Queries

[drtamermansour]

Overview

Develop a web-based chatbot that translates natural language questions into Cypher queries to interact with a Neo4j database. The project involves integrating a lightweight Hugging Face LLM model, setting up a Neo4j database locally, building a user-friendly interface, and sharing the complete code on GitHub with thorough documentation.

Task Breakdown

1. LLM Model Integration

• Objective: Select and download a lightweight, efficient LLM model from Hugging Face.
• Steps:
  • Research and identify an appropriate model capable of translating natural language into Cypher queries.
  • Download and configure the model for local use.
  • Optimize for performance and resource efficiency.

2. Neo4j Database Setup

• Objective: Install and configure Neo4j locally.
• Steps:
  • Install Neo4j on your local machine.
  • Create or select a test database for querying.
  • Ensure connectivity and proper functioning of the database.

3. Web Interface Development

• Objective: Build a simple web interface for user input and output display.
• Steps:
  • Create a web page where users can enter natural language queries.
  • Integrate the LLM model to convert these queries into Cypher queries.
  • Execute the generated Cypher queries on the Neo4j database.
  • Display the query results in a clear, accessible format.

4. Project Sharing and Documentation

• Objective: Share the project on GitHub with complete instructions.
• Steps:
  • Upload all project code to a GitHub repository.
  • Provide detailed documentation that includes:
    • Setup instructions for both the LLM model and Neo4j.
    • Steps to run the web interface.
    • Explanation of how natural language is translated into Cypher queries.
    • List of dependencies and environment configurations.

Deliverables

• A fully functional web-based chatbot that:
  • Accepts natural language questions.
  • Translates them into Cypher queries using the selected Hugging Face LLM model.
  • Executes these queries against a local Neo4j database.
  • Displays the results to the user.
• A GitHub repository containing:
  • All project code.
  • Comprehensive documentation to reproduce the setup and execution.

[drtamermansour]

https://chat.qwenlm.ai/s/10aa4dc0-75d1-4280-ad13-871f76997887?fbclid=IwY2xjawIceJhleHRuA2FlbQIxMAABHYE8Il5Aj3zhraJncojPj88_oEAPJqI-6jQqqfQGAEB8Us6kcre9C7L0_Q_aem_3fstcNhUHIGgb6l1hzIcvQ

[drtamermansour]

https://chatgpt.com/share/67af9b40-1fd0-8002-856d-0d6528625bf1?fbclid=IwY2xjawIc0ylleHRuA2FlbQIxMAABHYpDW-HKdZCsBA2Szl4bFtGTlOo8o9u7XGWV4r3oNwOvZSKRP6MDpyYoAQ_aem_XuqKD-G2IiKHbWQxCYAprg

[drtamermansour]

https://chatgpt.com/share/67af9c02-dc1c-8002-8ff3-edbbf1e11b43?fbclid=IwY2xjawIdgd9leHRuA2FlbQIxMAABHR6aMOV2PhLvqaS7vKglJnwctlzEAqgEpD2EI_qePacx-9DX9b1Wxs7p4A_aem_-A5djOHHjFzgS1Qntvy7wA

[drtamermansour]

text2cypher

https://github.com/neo4j-labs/text2cypher?fbclid=IwY2xjawIguaxleHRuA2FlbQIxMAABHYypdRMs05ept_h0PrzyJpcgGmV-xQNiw6nG5CHCBfIVJYaPWZnE378Dtg_aem_PMVhYvmViJPpDxNUgVt4tA

https://huggingface.co/tomasonjo?fbclid=IwY2xjawIgufNleHRuA2FlbQIxMAABHYypdRMs05ept_h0PrzyJpcgGmV-xQNiw6nG5CHCBfIVJYaPWZnE378Dtg_aem_PMVhYvmViJPpDxNUgVt4tA

[mr-eyes]

text2cypher

https://github.com/neo4j-labs/text2cypher?fbclid=IwY2xjawIguaxleHRuA2FlbQIxMAABHYypdRMs05ept_h0PrzyJpcgGmV-xQNiw6nG5CHCBfIVJYaPWZnE378Dtg_aem_PMVhYvmViJPpDxNUgVt4tA

https://huggingface.co/tomasonjo?fbclid=IwY2xjawIgufNleHRuA2FlbQIxMAABHYypdRMs05ept_h0PrzyJpcgGmV-xQNiw6nG5CHCBfIVJYaPWZnE378Dtg_aem_PMVhYvmViJPpDxNUgVt4tA

Neo4J also supports the text2cypher internally.