Create app.py

app.py

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+import gradio as gr
+import openai
+import os
+import json
+
+# OpenAI API setup
+openai.api_key = os.getenv("GROQ_API_KEY")
+openai.api_base = "https://api.groq.com/openai/v1"
+
+# File to store conversation history
+CONVERSATION_FILE = "conversation_history.json"
+
+# Function to load conversation history
+def load_history():
+    if not os.path.exists(CONVERSATION_FILE):
+        # Create the file with an empty list as default content
+        with open(CONVERSATION_FILE, "w") as file:
+            json.dump([], file)
+    try:
+        with open(CONVERSATION_FILE, "r") as file:
+            return json.load(file)
+    except json.JSONDecodeError:
+        return []
+
+# Function to save conversation history
+def save_history(history):
+    try:
+        with open(CONVERSATION_FILE, "w") as file:
+            json.dump(history, file, indent=4)
+    except Exception as e:
+        print(f"Error saving history: {e}")
+
+# Function to clear conversation history
+def clear_conversation_history():
+    try:
+        with open(CONVERSATION_FILE, "w") as file:
+            json.dump([], file)
+        return "Conversation history cleared successfully.", ""
+    except Exception as e:
+        return f"Error clearing history: {e}", ""
+
+# Function to get response from the LLM
+def get_groq_response(message, history=[]):
+    try:
+        messages = [{"role": "system", "content": "Precise answer"}] + history + [{"role": "user", "content": message}]
+        response = openai.ChatCompletion.create(
+            model="llama-3.1-70b-versatile",
+            messages=messages
+        )
+        return response.choices[0].message["content"]
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Chatbot function
+def chatbot(user_input, history):
+    # Load conversation history
+    conversation_history = history or load_history()
+    
+    # Format history for the LLM
+    formatted_history = [{"role": "user" if i % 2 == 0 else "assistant", "content": msg} for i, (msg, _) in enumerate(conversation_history)] + \
+                        [{"role": "assistant", "content": response} for _, response in conversation_history]
+    
+    # Get bot response
+    bot_response = get_groq_response(user_input, formatted_history)
+    
+    # Update history with the new conversation
+    conversation_history.append((user_input, bot_response))
+    
+    # Save the updated history
+    save_history(conversation_history)
+    
+    # Format for HTML display
+    display_html = "<br>".join(
+        f"<div><b>User:</b> {user}</div><div><b>Bot:</b> {bot}</div><br>"
+        for user, bot in conversation_history
+    )
+    
+    return conversation_history, display_html, ""  # Clear the user input field
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Chatbot with Enhanced Formatting and Selectable Chat History")
+    
+    chat_display = gr.HTML(label="Conversation")
+    user_input = gr.Textbox(label="Type your message here:")
+    clear_button = gr.Button("Clear History")
+    system_message = gr.Textbox(label="System Message", interactive=False)
+
+    history_state = gr.State(load_history())
+
+    # Chat interaction
+    user_input.submit(chatbot, inputs=[user_input, history_state], outputs=[history_state, chat_display, user_input])
+    
+    # Clear history button action
+    clear_button.click(clear_conversation_history, inputs=None, outputs=[system_message, chat_display])
+    clear_button.click(lambda: [], outputs=history_state)  # Reset the history state
+
+# Launch the app
+demo.launch()