chatbot_with_ChatGPT_KnowledgeGraph_ArangodB

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chatbot_with_ChatGPT_KnowledgeGraph_ArangodB

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Building Knowledge Graph-Driven Chatbot with ChatGPT and ArangoDB

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# How to Build a Knowledge Graph Enhanced Chatbot with ChatGPT and ArangoDB

In this repository, we will build a HealthCare Chatbot powered by 3 key technologies; Knowledge Graphs, ChatGPT, and ArangoDB (next-generation graph database). A detailed blog post for [Building Knowledge Graph-Driven Chatbot with ChatGPT and ArangoDB](https://sachinsharma9780.medium.com/how-to-build-a-knowledge-graph-enhanced-chatbot-with-chatgpt-and-arangodb-f609be6073d5#1cba-414b284d7d48) is also available. The benefits which come with building this type of chatbot are:

Intelligent Information Retrieval: The chatbot can structurally organize and represent healthcare data, such as medical conditions, treatments, prescriptions, and procedures, by leveraging a **Knowledge Graph**. When consumers ask inquiries or seek advice about healthcare topics, the chatbot may respond with accurate and pertinent information.

Processing Textual Information (or Natural Language): **ChatGPT** allows the chatbot to comprehend user inquiries and provide responses that sound human. Users can conversationally communicate with the chatbot by asking questions or requesting help in simple language (rather than writing complex database queries), thanks to its ability to interpret and process natural language input.

Seamless Integration of Data: **ArangoDB** (a multi-model Graph Database) can be used to store and manage healthcare data. The healthcare data can be stored as triplets in the knowledge graph. This will enable effective information querying, indexing, and retrieval, enabling the chatbot to respond quickly and accurately.

https://github.com/sachinsharma9780/chatbot_with_ChatGPT_KnowledgeGraph_ArangodB/assets/40523048/9e3e0f29-c6fc-4df0-a388-30ae69a5a1b6

### Restoring Healthcare Knowledge Graph into ArangoDB

Here is an example showing how to restore Healthcare Knowledge Graph dump into the ArangoDB (create Healthcare_KG database in ArangoDB):
```
arangorestore --server.endpoint "tcp://127.0.0.1:8529"  --server.username "root" --server.database "Healthcare_KG" --server.password "" --input-directory “./healthcare_kg_dump”
```

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