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| import re | |
| import os | |
| os.system(f"pip install open-interpreter") | |
| os.system(f"pip install matplotlib") | |
| import json | |
| import gradio as gr | |
| from interpreter import interpreter | |
| import time | |
| import matplotlib | |
| matplotlib.use('Agg') | |
| #get openaiapikey from environment variable | |
| openaiapikey = os.environ.get('OPENAI_API_KEY') | |
| #install open-interpreter package | |
| os.system(f"pip install open-interpreter") | |
| interpreter.auto_run = True | |
| interpreter.llm.model = "gpt-4-turbo" | |
| interpreter.custom_instructions = "First ask the user what they want to do. Based on the input, describe the next steps. If user agrees, proceed; if not, ask what they want next.If it is anything to display , always at the end open up the file." | |
| def json_to_markdown(json_data): | |
| full_message = "" | |
| images = [] | |
| for item in json_data: | |
| if item['role'] == 'assistant': | |
| if item['type'] == 'message': | |
| content = item.get('content', " ") | |
| full_message += content + " " | |
| elif item['type'] == 'image' and 'path' in item: | |
| images.append(item['path']) | |
| return full_message.strip(), images | |
| def list_png_files(directory): | |
| """List .png files in a given directory, sorted by modification time.""" | |
| png_files = [os.path.join(directory, f) for f in os.listdir(directory) if f.endswith('.png')] | |
| png_files.sort(key=lambda x: os.path.getmtime(x), reverse=True) # Newest first | |
| return png_files | |
| def update_images(image_component, directory="/home/user/app/"): | |
| """Update the image component with the latest image from the directory.""" | |
| png_files = list_png_files(directory) | |
| if png_files: | |
| # Load the most recent image file | |
| return png_files[0] | |
| return "No images available" | |
| def create_chat_widget(): | |
| with gr.Blocks() as chatblock: | |
| # Declare chatbot and txt here so they are accessible later | |
| chatbot = gr.Chatbot( | |
| [], | |
| elem_id="gpt4", | |
| elem_classes="gpt4", | |
| layout="llm", | |
| bubble_full_width=False, | |
| height=600, | |
| ) | |
| txt = gr.Textbox( | |
| placeholder="Enter text and press enter to chat with the bot.", | |
| show_label=False, | |
| ) | |
| # Main chat interface row | |
| with gr.Row(): | |
| send_button = gr.Button("Send") | |
| txt.submit(update_bot, inputs=[txt, chatbot], outputs=[chatbot, txt]) | |
| send_button.click(update_bot, inputs=[txt, chatbot], outputs=[chatbot, txt]) | |
| # Adding a row for the New Chat button at the top | |
| with gr.Row(): | |
| new_chat_button = gr.Button("New Chat", scale=3, interactive=True) | |
| # Ensure new_chat function resets both chatbot and txt components | |
| new_chat_button.click(new_chat, inputs=[], outputs=[chatbot, txt]) | |
| # Image display row | |
| with gr.Row(): | |
| image_display = gr.Image() | |
| update_image_button = gr.Button("Update Image") | |
| update_image_button.click(update_images, inputs=[], outputs=image_display) | |
| return chatblock | |
| def new_chat(): | |
| return [], "" | |
| def update_bot(text, chatbot): | |
| if text: # Append user input to the chat with "User:" prefix | |
| chatbot.append(("User", f"User: {text}")) | |
| response_json = interpreter.chat(text, stream=True, display=False) | |
| formatted_response, images = json_to_markdown(response_json) | |
| # Append text response with "Assistant:" prefix if it exists | |
| if formatted_response.strip(): | |
| chatbot.append(("Assistant", f"Assistant: {formatted_response}")) | |
| # Append images if any | |
| for img_path in images: | |
| if os.path.exists(img_path) and img_path.endswith('.png'): | |
| chatbot.append(("Assistant", img_path)) # Assuming the path is accessible | |
| else: | |
| chatbot.append(("Assistant", "Image not found or path is invalid.")) | |
| return chatbot, "" | |
| with gr.Blocks() as demo: | |
| with gr.Tab("HEXON Chatbot Assignment"): | |
| chat_interface = create_chat_widget() | |
| demo.launch() |