import os import gradio as gr from gradio import ChatMessage from typing import Iterator import google.generativeai as genai import time # Import time module for potential debugging/delay # get Gemini API Key from the environ variable GEMINI_API_KEY = os.getenv("GEMINI_API_KEY") genai.configure(api_key=GEMINI_API_KEY) # we will be using the Gemini 2.0 Flash model with Thinking capabilities model = genai.GenerativeModel("gemini-2.0-flash-thinking-exp-1219") def format_chat_history(messages: list) -> list: """ Formats the chat history into a structure Gemini can understand """ formatted_history = [] for message in messages: # Skip thinking messages (messages with metadata) if not (message.get("role") == "assistant" and "metadata" in message): formatted_history.append({ "role": "user" if message.get("role") == "user" else "assistant", "parts": [message.get("content", "")] }) return formatted_history def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]: """ Streams thoughts and response with conversation history support for text input only. """ if not user_message.strip(): # Robust check: if text message is empty or whitespace messages.append(ChatMessage(role="assistant", content="Please provide a non-empty text message. Empty input is not allowed.")) # More specific message yield messages return try: print(f"\n=== New Request (Text) ===") print(f"User message: {user_message}") # Format chat history for Gemini chat_history = format_chat_history(messages) # Initialize Gemini chat chat = model.start_chat(history=chat_history) response = chat.send_message(user_message, stream=True) # Initialize buffers and flags thought_buffer = "" response_buffer = "" thinking_complete = False # Add initial thinking message messages.append( ChatMessage( role="assistant", content="", metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"} ) ) for chunk in response: parts = chunk.candidates[0].content.parts current_chunk = parts[0].text if len(parts) == 2 and not thinking_complete: # Complete thought and start response thought_buffer += current_chunk print(f"\n=== Complete Thought ===\n{thought_buffer}") messages[-1] = ChatMessage( role="assistant", content=thought_buffer, metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"} ) yield messages # Start response response_buffer = parts[1].text print(f"\n=== Starting Response ===\n{response_buffer}") messages.append( ChatMessage( role="assistant", content=response_buffer ) ) thinking_complete = True elif thinking_complete: # Stream response response_buffer += current_chunk print(f"\n=== Response Chunk ===\n{current_chunk}") messages[-1] = ChatMessage( role="assistant", content=response_buffer ) else: # Stream thinking thought_buffer += current_chunk print(f"\n=== Thinking Chunk ===\n{current_chunk}") messages[-1] = ChatMessage( role="assistant", content=thought_buffer, metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"} ) #time.sleep(0.05) #Optional: Uncomment this line to add a slight delay for debugging/visualization of streaming. Remove for final version yield messages print(f"\n=== Final Response ===\n{response_buffer}") except Exception as e: print(f"\n=== Error ===\n{str(e)}") messages.append( ChatMessage( role="assistant", content=f"I apologize, but I encountered an error: {str(e)}" ) ) yield messages def user_message(msg: str, history: list) -> tuple[str, list]: """Adds user message to chat history""" history.append(ChatMessage(role="user", content=msg)) return "", history # Create the Gradio interface with gr.Blocks(theme=gr.themes.Soft(primary_hue="teal", secondary_hue="slate", neutral_hue="neutral")) as demo: # Using Soft theme with adjusted hues for a refined look gr.Markdown("# Chat with Gemini 2.0 Flash and See its Thoughts 💭") gr.HTML(""" """) chatbot = gr.Chatbot( type="messages", label="Gemini2.0 'Thinking' Chatbot (Streaming Output)", #Label now indicates streaming render_markdown=True, scale=1, avatar_images=(None,"https://lh3.googleusercontent.com/oxz0sUBF0iYoN4VvhqWTmux-cxfD1rxuYkuFEfm1SFaseXEsjjE4Je_C_V3UQPuJ87sImQK3HfQ3RXiaRnQetjaZbjJJUkiPL5jFJ1WRl5FKJZYibUA=w214-h214-n-nu") ) with gr.Row(equal_height=True): input_box = gr.Textbox( lines=1, label="Chat Message", placeholder="Type your message here...", scale=4 ) clear_button = gr.Button("Clear Chat", scale=1) # Add example prompts - removed file upload examples. Kept text focused examples. example_prompts = [ ["Write a short poem about the sunset."], ["Explain the theory of relativity in simple terms."], ["If a train leaves Chicago at 6am traveling at 60mph, and another train leaves New York at 8am traveling at 80mph, at what time will they meet?"], ["Summarize the plot of Hamlet."], ["Write a haiku about a cat."] ] gr.Examples( examples=example_prompts, inputs=input_box, label="Examples: Try these prompts to see Gemini's thinking!", examples_per_page=5 # Adjust as needed ) # Set up event handlers msg_store = gr.State("") # Store for preserving user message input_box.submit( lambda msg: (msg, msg, ""), # Store message and clear input inputs=[input_box], outputs=[msg_store, input_box, input_box], queue=False ).then( user_message, # Add user message to chat inputs=[msg_store, chatbot], outputs=[input_box, chatbot], queue=False ).then( stream_gemini_response, # Generate and stream response inputs=[msg_store, chatbot], outputs=chatbot ) clear_button.click( lambda: ([], "", ""), outputs=[chatbot, input_box, msg_store], queue=False ) gr.Markdown( # Description moved to the bottom - updated for text-only """


--- ### About this Chatbot This chatbot demonstrates the experimental 'thinking' capability of the **Gemini 2.0 Flash** model. You can observe the model's thought process as it generates responses, displayed with the "⚙️ Thinking" prefix. **Try out the example prompts below to see Gemini in action!** **Key Features:** * Powered by Google's **Gemini 2.0 Flash** model. * Shows the model's **thoughts** before the final answer (experimental feature). * Supports **conversation history** for multi-turn chats. * Uses **streaming** for a more interactive experience. **Instructions:** 1. Type your message in the input box below or select an example. 2. Press Enter or click Submit to send. 3. Observe the chatbot's "Thinking" process followed by the final response. 4. Use the "Clear Chat" button to start a new conversation. *Please note*: The 'thinking' feature is experimental and the quality of thoughts may vary. """ ) # Launch the interface if __name__ == "__main__": demo.launch(debug=True)