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Chatbot Answering from Your Own Knowledge Base: Langchain, ChatGPT, Pinecone, and Streamlit

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farukalamai/ai-chatbot-using-Langchain-Pinecone

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Chatbot Answering from Your Own Knowledge Base: Langchain, ChatGPT, Pinecone, and Streamlit

main-·-Streamlit (1)

Deployment

1. Clone Repository

  git clone https://github.com/farukalampro/ai-chatbot-using-Langchain-Pinecone.git
  cd ai-chatbot-using-Langchain-Pinecone

2. Create Virtual Environment

  python -m venv env
  • For Windows:
  .\env\Scripts\activate
  • For macOS/Linux:
  source env/bin/activate

3. To install require packages

  pip install -r requirements.txt

4. Replace your own document in data folder

5. Replace your own OpenAI, Pinecone API Key and Pinecone environment in indexing.py, main.py & utils.py

6. When you are creating the pinecone index make sure,

  • index_name = "langchain-chatbot"
  • Dimensions of the index is 384

7. Run the web app

  streamlit run main.py

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Chatbot Answering from Your Own Knowledge Base: Langchain, ChatGPT, Pinecone, and Streamlit

Topics

ai chatbot artificial-intelligence openai aichatbot pinecone webapplication ai-bot streamlit streamlit-webapp gpt-3 gpt-4 llm generative-ai chatgpt langchain

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