Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""app.py
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1fuzwSkyjYRLfvGxQGclxwX0Y9OD2IK6s
+"""
+
+# app.py
+
+# Step 1: Install necessary libraries
+# This is handled by requirements.txt in Hugging Face Spaces,
+# but you would run this line in a fresh environment:
+# !pip install -q gradio transformers torch sentencepiece
+
+# Step 2: Import libraries
+import gradio as gr
+import re
+from transformers import pipeline
+
+# --- Backend Logic ---
+
+# Step 3: Load the Hugging Face Model
+print("Loading Hugging Face model (google/flan-t5-small)... This may take a moment.")
+text_generator = pipeline(
+    "text2text-generation",
+    model="google/flan-t5-small"
+)
+print("Model loaded successfully!")
+
+
+def parse_chat_file(file_content):
+    """
+    A robust parser for both WhatsApp and Telegram text exports.
+    """
+    lines = file_content.split('\n')
+    chat_data = []
+    pattern = re.compile(
+        r'^(?:\u200e)?\[?(\d{1,2}[/.]\d{1,2}[/.]\d{2,4}),?\s+(\d{1,2}:\d{2}(?::\d{2})?(?:\s*[AP]M)?)\]?\s*-\s*([^:]+):\s*(.*)',
+        re.IGNORECASE
+    )
+    for line in lines:
+        match = pattern.match(line)
+        if match:
+            sender, message = match.group(3), match.group(4)
+            if "created this group" not in message and "added" not in message and "changed the subject" not in message:
+                 chat_data.append(f"{sender}: {message}")
+        elif chat_data and line.strip():
+            chat_data[-1] += "\n" + line
+    return "\n".join(chat_data) if chat_data else "Could not parse chat file."
+
+
+def process_chat_request(user_question, chat_history, state_data):
+    """
+    The main function that handles the chat logic using the local Hugging Face model.
+    """
+    context_size = state_data.get("context_size")
+    chat_content = state_data.get("chat_content")
+    temperature = state_data.get("temperature")
+
+    if not all([context_size, chat_content, temperature is not None]):
+        raise gr.Error("Chat content or configuration is missing. Please restart by uploading a file.")
+    if not user_question:
+        raise gr.Error("Please enter a question.")
+
+    context_to_use = chat_content[-int(context_size):]
+
+    prompt = f"""
+    Based on the following chat history, provide a detailed answer to the user's question.
+
+    CONTEXT:
+    ---
+    {context_to_use}
+    ---
+
+    QUESTION: {user_question}
+
+    ANSWER:
+    """
+
+    try:
+        result = text_generator(
+            prompt,
+            max_length=300,
+            num_beams=3,
+            temperature=temperature
+        )
+        bot_response = result[0]['generated_text']
+    except Exception as e:
+        raise gr.Error(f"An error occurred with the model: {e}")
+
+    chat_history.append((user_question, bot_response))
+    return "", chat_history
+
+# --- Gradio UI Definition ---
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="orange", secondary_hue="orange"), title="Local Chat Analyzer") as demo:
+    app_state = gr.State({})
+
+    with gr.Column(visible=True) as welcome_page:
+        gr.Markdown(
+            """
+            <div style='text-align: center; font-family: "Garamond", serif; padding-top: 30px;'>
+                <h1 style='font-size: 3.5em;'>Local Chat Analyzer</h1>
+                <p style='font-size: 1.5em; color: #555;'>Powered by a Hugging Face Model. No API key needed!</p>
+            </div>
+            """
+        )
+        gr.HTML(
+            """
+            <div style='text-align: center; padding: 20px;'>
+                <img src='https://media.giphy.com/media/v1.Y2lkPTc5MGI3NjExd2Vjb3M2eGZzN2FkNWZpZzZ0bWl0c2JqZzZlMHVwZ2l4b2t0eXFpcyZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/YWjDA4k2n6d5Ew42zC/giphy.gif'
+                     style='max-width: 350px; margin: auto; border-radius: 20px; box-shadow: 0 8px 16px rgba(0,0,0,0.1);' />
+            </div>
+            """
+        )
+        with gr.Row():
+            with gr.Column():
+                with gr.Accordion("How do I get my chat file?", open=False):
+                    gr.Markdown("""
+                    ### Exporting your WhatsApp Chat
+                    1.  **On your phone**, open the WhatsApp chat you want to analyze.
+                    2.  Tap the **three dots** (⋮) in the top-right corner.
+                    3.  Select **More** > **Export chat**.
+                    4.  Choose **Without media**. This will create a smaller `.txt` file.
+                    5.  Save the file to your phone or email it to yourself to access it on your computer.
+                    6.  For more details, visit the [official WhatsApp Help Center](https://faq.whatsapp.com/1180414079177245/).
+                    """)
+                gr.Markdown("### 1. Upload Your Chat File")
+                chat_file_upload = gr.File(label="Upload WhatsApp/Telegram .txt Export")
+            with gr.Column():
+                gr.Markdown("### 2. Customize Parameters")
+                context_slider = gr.Slider(500, 20000, value=5000, step=500, label="Context Window Size (Characters)")
+                temp_slider = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature (Creativity)")
+        lets_chat_button = gr.Button("💬 Start Chatting 💬", variant="primary")
+
+    with gr.Column(visible=False) as chat_page:
+        gr.Markdown("<h1 style='text-align: center;'>Chat Analyzer</h1>")
+        chatbot_ui = gr.Chatbot(height=600, bubble_full_width=False)
+        with gr.Row():
+            user_input_box = gr.Textbox(placeholder="Ask a question about your chat...", scale=5)
+            submit_button = gr.Button("Send", variant="primary", scale=1)
+
+    def go_to_chat(current_state, chat_file, context_size, temperature):
+        if chat_file is None:
+            raise gr.Error("A chat file must be uploaded.")
+        with open(chat_file.name, 'r', encoding='utf-8') as f:
+            content = f.read()
+        parsed_content = parse_chat_file(content)
+        if "Could not parse" in parsed_content:
+            raise gr.Error("Failed to parse the chat file. Please check the format.")
+        new_state = {
+            "chat_content": parsed_content,
+            "context_size": context_size,
+            "temperature": temperature,
+        }
+        return (
+            new_state,
+            gr.Column(visible=False),
+            gr.Column(visible=True)
+        )
+
+    lets_chat_button.click(
+        fn=go_to_chat,
+        inputs=[app_state, chat_file_upload, context_slider, temp_slider],
+        outputs=[app_state, welcome_page, chat_page]
+    )
+    submit_button.click(
+        fn=process_chat_request,
+        inputs=[user_input_box, chatbot_ui, app_state],
+        outputs=[user_input_box, chatbot_ui]
+    )
+    user_input_box.submit(
+        fn=process_chat_request,
+        inputs=[user_input_box, chatbot_ui, app_state],
+        outputs=[user_input_box, chatbot_ui]
+    )
+
+if __name__ == "__main__":
+    demo.launch()