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Update app.py
Browse files
app.py
CHANGED
@@ -1,42 +1,160 @@
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import gradio as gr
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from ultralytics import YOLO
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model = YOLO("yolo11n.pt")
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with gr.Blocks() as demo:
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#
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chatbot = gr.Chatbot(
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show_label=False,
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)
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# Simple textbox for input
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msg = gr.Textbox(
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show_label=False,
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placeholder="Type your message here..."
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)
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msg.submit(
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respond,
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[
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[msg, chatbot],
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)
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#
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def
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demo.load(
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inputs=None,
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outputs=[chatbot],
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)
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@@ -44,5 +162,5 @@ def create_minimal_chat_interface():
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# Launch the application
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if __name__ == "__main__":
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app =
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app.launch()
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import gradio as gr
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from ultralytics import YOLO
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from typing import List
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import time
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model = YOLO("yolo11n.pt")
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def create_chat_interface():
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"""Create a minimal chat interface that mirrors the original structure."""
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with gr.Blocks() as demo:
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# Match the original chatbot structure
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chatbot = gr.Chatbot(
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show_label=False,
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)
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msg = gr.Textbox(
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show_label=False,
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placeholder="Type your message here..."
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)
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# Keep all the original state objects
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transcript_processor_state = gr.State()
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call_id_state = gr.State()
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colab_id_state = gr.State()
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origin_state = gr.State()
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ct_state = gr.State()
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turl_state = gr.State()
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uid_state = gr.State()
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# Keep the streaming functionality
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def respond(
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message: str,
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chat_history: List,
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transcript_processor,
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cid,
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rsid,
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origin,
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ct,
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uid,
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):
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if not transcript_processor:
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bot_message = "Transcript processor not initialized."
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chat_history.append((message, bot_message))
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return "", chat_history
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chat_history.append((message, ""))
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# Simulate streaming with a simple loop
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for i in range(5):
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partial_response = f"Processing... {i+1}/5"
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chat_history[-1] = (message, partial_response)
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yield "", chat_history
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time.sleep(0.3)
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# Final response
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final_response = f"Processed message: {message}\nWith call_id: {cid}"
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chat_history[-1] = (message, final_response)
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yield "", chat_history
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# Keep the exact same function call structure
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msg.submit(
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respond,
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[
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msg,
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chatbot,
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transcript_processor_state,
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call_id_state,
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colab_id_state,
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origin_state,
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ct_state,
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uid_state,
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],
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[msg, chatbot],
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)
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# Match the original on_app_load function
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def on_app_load(request: gr.Request):
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# Simplified parameter handling
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cid = "test_cid"
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rsid = "test_rsid"
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origin = "test_origin"
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ct = "test_ct"
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turl = "test_turl"
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uid = "test_uid"
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# Create a dummy transcript processor
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transcript_processor = {"initialized": True}
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# Initialize with welcome message
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chatbot_value = [(None, "Welcome to the debug interface")]
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return [
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chatbot_value,
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transcript_processor,
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cid,
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rsid,
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origin,
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ct,
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turl,
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uid,
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]
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def display_processing_message(chatbot_value):
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"""Display the processing message while maintaining state."""
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# Create new chatbot value with processing message
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new_chatbot_value = [
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(None, "Processing... Please wait...")
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]
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return new_chatbot_value
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def stream_initial_analysis(
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chatbot_value, transcript_processor, cid, rsid, origin, ct, uid
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):
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if not transcript_processor:
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return chatbot_value
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# Simulate streaming with a simple loop
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for i in range(3):
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# Update the existing message
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chatbot_value[0] = (None, f"Initial analysis step {i+1}/3...")
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yield chatbot_value
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time.sleep(0.5)
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# Final message
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chatbot_value[0] = (None, "Ready to chat! Call ID: " + cid)
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yield chatbot_value
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# Keep the exact same load chain
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demo.load(
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on_app_load,
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inputs=None,
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outputs=[
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chatbot,
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transcript_processor_state,
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call_id_state,
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colab_id_state,
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origin_state,
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ct_state,
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turl_state,
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uid_state,
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],
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).then(
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display_processing_message,
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inputs=[chatbot],
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outputs=[chatbot],
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).then(
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stream_initial_analysis,
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inputs=[
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chatbot,
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transcript_processor_state,
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call_id_state,
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colab_id_state,
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origin_state,
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ct_state,
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uid_state,
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],
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outputs=[chatbot],
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)
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# Launch the application
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if __name__ == "__main__":
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app = create_chat_interface()
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app.launch()
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