Upload 3 files

README.md

@@ -1,13 +1,89 @@
----
-title: Simple Chat Bot
-emoji: 👁
-colorFrom: blue
-colorTo: blue
-sdk: gradio
-sdk_version: 6.2.0
-app_file: app.py
-pinned: false
-short_description: Testing simple chat bot
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🤖 LangChain Groq Chatbot
+
+A conversational AI chatbot built with LangChain and Groq, deployable on Hugging Face Spaces.
+
+
+## Deploying to Hugging Face Spaces
+
+### Method 1: Using the Hugging Face Web Interface
+
+1. Go to [huggingface.co/spaces](https://huggingface.co/spaces)
+2. Click "Create new Space"
+3. Choose a name for your Space
+4. Select "Gradio" as the SDK
+5. Click "Create Space"
+6. Upload the following files:
+   - `chatbot_app.py` (rename to `app.py` for Hugging Face)
+   - `requirements.txt`
+   - `README.md`
+7. In your Space settings, go to "Settings" → "Variables and secrets"
+8. Add a new secret: `GROQ_API_KEY` with your Groq API key
+9. Your Space will automatically build and deploy!
+
+### Method 2: Using Git
+
+1. Create a new Space on Hugging Face
+2. Clone your Space repository:
+```bash
+git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
+cd YOUR_SPACE_NAME
+```
+
+3. Copy the files:
+```bash
+cp /path/to/chatbot_app.py app.py
+cp /path/to/requirements.txt .
+cp /path/to/README.md .
+```
+
+4. Commit and push:
+```bash
+git add .
+git commit -m "Initial commit"
+git push
+```
+
+5. Add your `GROQ_API_KEY` as a secret in your Space settings
+
+## Usage
+
+1. Enter your Groq API key in the text field (or use the environment variable)
+2. Type your message in the message box
+3. Click "Send" or press Enter
+4. The AI will respond to your message
+5. Click "Clear Conversation" to start a new conversation
+
+## Supported Models
+
+The chatbot uses the `mixtral-8x7b-32768` model by default. You can modify the model in the code to use other Groq-supported models:
+
+- `mixtral-8x7b-32768`
+- `llama2-70b-4096`
+- `gemma-7b-it`
+- And more available on Groq
+
+## Project Structure
+
+```
+chatbot/
+├── chatbot_app.py      # Main application file (rename to app.py for HF)
+├── requirements.txt    # Python dependencies
+├── README.md          # This file
+└── .env.example       # Example environment variables
+```
+
+## Configuration
+
+You can customize the chatbot by modifying these parameters in `chatbot_app.py`:
+
+- `model_name`: Change the Groq model
+- `temperature`: Control randomness (0.0 to 1.0)
+- `max_tokens`: Maximum response length
+
+
+## Acknowledgments
+
+- Built with [LangChain](https://langchain.com/)
+- Powered by [Groq](https://groq.com/)
+- UI created with [Gradio](https://gradio.app/)
+- Hosted on [Hugging Face Spaces](https://huggingface.co/spaces)

app.py

@@ -0,0 +1,110 @@
+import os
+import gradio as gr
+from langchain_groq import ChatGroq
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationChain
+from langchain.prompts import PromptTemplate
+
+def initialize_chatbot(api_key, model_name="mixtral-8x7b-32768"):
+    llm = ChatGroq(
+        groq_api_key=api_key,
+        model_name=model_name,
+        temperature=0.7,
+        max_tokens=1024
+    )
+    
+    memory = ConversationBufferMemory(
+        return_messages=True,
+        memory_key="history"
+    )
+    
+    template = """You are a helpful AI assistant. Have a natural conversation with the user.
+
+Current conversation:
+{history}
+Human: {input}
+AI Assistant:"""
+    
+    prompt = PromptTemplate(
+        input_variables=["history", "input"],
+        template=template
+    )
+    
+    conversation = ConversationChain(
+        llm=llm,
+        memory=memory,
+        prompt=prompt,
+        verbose=False
+    )
+    
+    return conversation
+
+conversation_chain = None
+
+def chat_function(message, history, api_key):
+    global conversation_chain
+    
+    if not api_key:
+        return "Please provide a Groq API key to start chatting."
+    
+    if conversation_chain is None:
+        try:
+            conversation_chain = initialize_chatbot(api_key)
+        except Exception as e:
+            return f"Error initializing chatbot: {str(e)}"
+    
+    try:
+        response = conversation_chain.predict(input=message)
+        return response
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def reset_conversation():
+    global conversation_chain
+    conversation_chain = None
+    return None
+
+with gr.Blocks(title="LangChain Groq Chatbot") as demo:
+    gr.Markdown("# 🤖 LangChain Groq Chatbot")
+    gr.Markdown("Chat with an AI assistant powered by LangChain and Groq")
+    
+    with gr.Row():
+        api_key_input = gr.Textbox(
+            label="Groq API Key",
+            placeholder="Enter your Groq API key here...",
+            type="password",
+            value=os.getenv("GROQ_API_KEY", "")
+        )
+    
+    chatbot = gr.Chatbot(height=400)
+    
+    with gr.Row():
+        msg = gr.Textbox(
+            label="Message",
+            placeholder="Type your message here...",
+            scale=4
+        )
+        submit_btn = gr.Button("Send", scale=1)
+    
+    with gr.Row():
+        clear_btn = gr.Button("Clear Conversation")
+    
+    gr.Markdown("### Instructions:")
+    gr.Markdown("1. Get a free API key from [Groq Console](https://console.groq.com)")
+    gr.Markdown("2. Enter your API key above")
+    gr.Markdown("3. Start chatting!")
+    
+    def respond(message, chat_history, api_key):
+        if not message.strip():
+            return chat_history, ""
+        
+        bot_message = chat_function(message, chat_history, api_key)
+        chat_history.append((message, bot_message))
+        return chat_history, ""
+    
+    msg.submit(respond, [msg, chatbot, api_key_input], [chatbot, msg])
+    submit_btn.click(respond, [msg, chatbot, api_key_input], [chatbot, msg])
+    clear_btn.click(lambda: (reset_conversation(), None), None, chatbot)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio==4.44.0
+langchain==0.3.7
+langchain-groq==0.2.1
+python-dotenv==1.0.0