🗣️ Conversational Chatbot

A modern conversational chatbot built with Streamlit and LangChain, powered by Together AI's LLM models.

This repository includes two chatbot applications:

1. app.py - Standard conversational chatbot
2. hinglish_bot.py - Hinglish chatbot with customizable system messages

Features

• 💬 Interactive chat interface with message history
• 🧠 Powered by Meta's Llama 4 Maverick model via Together AI
• 🔄 Conversation memory using LangChain's latest patterns
• 🎨 Clean and intuitive UI built with Streamlit
• 🔒 Secure API key management with Streamlit secrets
• 🇮🇳 NEW: Hinglish bot with customizable personality
• ⚙️ NEW: Editable system messages and preset templates

Tech Stack

• Frontend: Streamlit
• LLM Framework: LangChain (latest version)
• LLM Provider: Together AI
• Model: meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8
• Python: 3.8+

Prerequisites

• Python 3.8 or higher
• Together AI API key (Get one here)

Installation

1. Clone the repository (or navigate to the project directory):

   cd chatbot_Course

2. Install dependencies:

   pip install -r requirements.txt

3. Set up your API key:

   • Open .streamlit/secrets.toml
   • Replace your-together-api-key-here with your actual Together AI API key:

     TOGETHER_API_KEY = "your-actual-api-key-here"

Usage

Standard Chatbot (app.py)

1. Run the application:

   streamlit run app.py

2. Access the chatbot:

   • The app will automatically open in your browser
   • Default URL: http://localhost:8501

3. Start chatting:

   • Type your message in the chat input at the bottom
   • Press Enter to send
   • The AI will respond with context from your conversation history

Hinglish Chatbot (hinglish_bot.py)

1. Run the Hinglish bot:

   streamlit run hinglish_bot.py

2. Customize the bot (Optional):

   • Open hinglish_bot.py in a text editor
   • Edit the system_message variable (line 17)
   • Save and restart the bot

3. Chat in Hinglish:

   • Type in Hindi, English, or Hinglish
   • The bot will respond in natural Hinglish
   • Example: "Bhai, machine learning kaise seekhun?"

Project Structure

chatbot_Course/
├── app.py                          # Standard conversational chatbot
├── hinglish_bot.py                 # Hinglish chatbot (customizable)
├── requirements.txt                # Python dependencies
├── README.md                       # Main documentation
├── .streamlit/
│   └── secrets.toml               # API keys (not committed to git)
└── .gitignore                     # Git ignore file

Configuration

Changing the LLM Model

To use a different model, modify the llm initialization in app.py:

llm = ChatOpenAI(
    model="your-model-name",  # Change this
    api_key=st.secrets["TOGETHER_API_KEY"],
    base_url="https://api.together.xyz/v1",
    temperature=0.7  # Adjust temperature (0.0 - 1.0)
)

Using OpenAI Instead

1. Update requirements.txt to include OpenAI support
2. Add your OpenAI API key to .streamlit/secrets.toml:

   OPENAI_API_KEY = "your-openai-api-key"

3. Update the LLM initialization:

   llm = ChatOpenAI(
       model="gpt-4o-mini",
       api_key=st.secrets["OPENAI_API_KEY"]
   )

Adjusting Conversation Memory

The chatbot uses InMemoryChatMessageHistory to maintain conversation context. To limit the number of messages remembered, you can implement a custom message history with a window size.

Customizing System Messages (Hinglish Bot)

The Hinglish bot allows you to customize the AI's personality by editing the code:

1. Open hinglish_bot.py in any text editor
2. Find the system_message variable (around line 17)
3. Replace the text with your custom message
4. Save and restart the bot

Example custom system message:

system_message = """You are a coding tutor who teaches in Hinglish. 
Explain programming concepts using simple Hindi-English mix.
Use examples that Indian students can relate to.
Be encouraging and patient.
"""

Key Features Explained

Modern LangChain Implementation

This project uses the latest LangChain patterns:

• ✅ RunnableWithMessageHistory for conversation management
• ✅ ChatPromptTemplate with MessagesPlaceholder for structured prompts
• ✅ LCEL (LangChain Expression Language) with the | operator
• ✅ Proper session management with configurable session IDs

No Deprecated Code

All deprecated imports and patterns have been removed:

• ❌ No ConversationChain
• ❌ No ConversationBufferWindowMemory
• ✅ Uses modern langchain_core components

Security

⚠️ Important: Never commit your .streamlit/secrets.toml file to version control. It's already included in .gitignore to prevent accidental exposure of API keys.

Troubleshooting

Model Not Available Error

If you see an error about the model not being available:

1. Check that your Together AI API key is valid
2. Verify the model name is correct and available
3. Some models require a dedicated endpoint - check the Together AI dashboard

Import Errors

If you encounter import errors:

pip install --upgrade langchain langchain-openai streamlit

Dependencies

• langchain - LLM framework
• langchain-openai - OpenAI-compatible LLM integration
• streamlit - Web interface
• streamlit-chat - Chat UI components

Contributing

Feel free to submit issues, fork the repository, and create pull requests for any improvements.

License

This project is open source and available under the MIT License.

Acknowledgments

• Built with Streamlit
• Powered by LangChain
• LLM by Together AI
• Tutorial by Build Fast with AI

Support

For questions or issues:

1. Check the LangChain documentation
2. Review Streamlit documentation
3. Visit Together AI documentation

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Happy Chatting! 🚀