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README.md
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---
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# Conversational Q&A Chatbot
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This is a conversational Q&A chatbot built using Streamlit. The chatbot interacts with users by answering questions related to financial analysis of IPOs for startup companies.
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## Setup and Usage
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1. Clone the repository to your local machine:
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```bash
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git clone https://github.com/sancharika/LLM-QA-ChatBot.git
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```
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2. Navigate to the project directory:
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```bash
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cd LLM-QA-ChatBot
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```
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3. Install dependencies:
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```bash
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pip install -r requirements.txt
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```
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4. Run the Streamlit app:
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```bash
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streamlit run app.py
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```
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5. Once the app is running, you can interact with the chatbot by typing your questions in the provided text input field and clicking the "Ask" button.
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## Project Structure
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- **app.py**: This is the main Python script containing the Streamlit UI code and the logic for interacting with the chatbot.
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- **langchain**: This directory contains the schema for defining different types of messages (HumanMessage, SystemMessage, AIMessage).
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- **langchain_openai**: This directory contains the code for interacting with the OpenAI GPT-3 model for generating responses to user questions.
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- **.env**: This file contains environment variables used in the application (not included in this example).
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## Dependencies
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- Streamlit
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- langchain
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- langchain_openai
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- python-dotenv
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## How It Works
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1. Users interact with the chatbot by typing questions related to financial analysis of IPOs for startup companies into the text input field.
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2. The chatbot processes the user's question and generates a response using the OpenAI GPT-3 model.
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3. The response is displayed to the user in the Streamlit app interface.
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## Note
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Make sure to set up your environment variables properly, especially if you're using any API keys or sensitive information.
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## Contributors
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- [Sancharika Debnath](https://github.com/sancharika)
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Feel free to contribute to this project by submitting pull requests or reporting issues. Happy chatting! 🤖💬
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