Create app.py

app.py

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+import gradio as gr
+import os
+import json
+import uuid
+import threading
+import time
+import re
+
+from openai import OpenAI
+from realtime_transcriber import WebSocketClient, connections, WEBSOCKET_URI, WEBSOCKET_HEADERS
+
+# ------------------ Load API Key ------------------
+from dotenv import load_dotenv
+load_dotenv()
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+ASSISTANT_ID = os.getenv("ASSISTANT_ID")
+
+if not OPENAI_API_KEY or not ASSISTANT_ID:
+    raise ValueError("Missing OPENAI_API_KEY or ASSISTANT_ID in environment variables")
+
+client = OpenAI(api_key=OPENAI_API_KEY)
+
+# ------------------ Chat Logic ------------------
+session_threads = {}
+session_messages = {}
+
+def reset_session():
+    session_id = str(uuid.uuid4())
+    thread = client.beta.threads.create()
+    session_threads[session_id] = thread.id
+    session_messages[session_id] = []
+    return session_id
+
+def process_chat(message, history, session_id):
+    thread_id = session_threads.get(session_id)
+    if not thread_id:
+        thread_id = client.beta.threads.create().id
+        session_threads[session_id] = thread_id
+
+    # Store user message
+    client.beta.threads.messages.create(
+        thread_id=thread_id,
+        role="user",
+        content=message
+    )
+
+    # Run assistant
+    run = client.beta.threads.runs.create(
+        thread_id=thread_id,
+        assistant_id=ASSISTANT_ID
+    )
+
+    while True:
+        run_status = client.beta.threads.runs.retrieve(
+            thread_id=thread_id,
+            run_id=run.id
+        )
+        if run_status.status == "completed":
+            break
+        time.sleep(1)
+
+    # Retrieve assistant message
+    messages = client.beta.threads.messages.list(thread_id=thread_id)
+    for msg in reversed(messages.data):
+        if msg.role == "assistant":
+            assistant_response = msg.content[0].text.value
+            break
+    else:
+        assistant_response = "⚠️ Assistant did not respond."
+
+    # Detect image if present
+    image_url = None
+    match = re.search(r'https://raw\.githubusercontent\.com/AndrewLORTech/surgical-pathology-manual/main/[\w\-/]*\.png', assistant_response)
+    if match:
+        image_url = match.group(0)
+
+    return assistant_response, image_url
+
+# ------------------ Transcription Logic ------------------
+def create_websocket_client():
+    client_id = str(uuid.uuid4())
+    connections[client_id] = WebSocketClient(WEBSOCKET_URI, WEBSOCKET_HEADERS, client_id)
+    threading.Thread(target=connections[client_id].run, daemon=True).start()
+    return client_id
+
+def clear_transcript(client_id):
+    if client_id in connections:
+        connections[client_id].transcript = ""
+    return ""
+
+def send_audio_chunk(audio, client_id):
+    if client_id not in connections:
+        return "Initializing connection..."
+    sr, y = audio
+    connections[client_id].enqueue_audio_chunk(sr, y)
+    return connections[client_id].transcript
+
+# ------------------ Gradio Interface ------------------
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🧠 Document AI + 🎙️ Voice Assistant")
+
+    session_id = gr.State(value=reset_session())
+    client_id = gr.State()
+
+    # ---------- Section 1: Document Image Display ----------
+    with gr.Row():
+        image_display = gr.Image(label="📄 Document Page (auto-extracted if available)", interactive=False, visible=False)
+
+    # ---------- Section 2: Chat Interface ----------
+    with gr.Row():
+        chatbot = gr.ChatInterface(
+            fn=lambda message, history, session_id: (
+                process_chat(message, history, session_id)[0],
+                process_chat(message, history, session_id)[1],
+            ),
+            additional_inputs=[session_id],
+            render_markdown=True,
+            examples=["What does clause 3.2 mean?", "Summarize the timeline from the image."],
+            title="💬 Document Assistant",
+            retry_btn="🔁 Retry",
+            undo_btn="↩️ Undo",
+            clear_btn="🗑️ Clear",
+        )
+
+    # Link image preview if extracted
+    def update_image_display(message, history, session_id):
+        _, image_url = process_chat(message, history, session_id)
+        return gr.update(value=image_url, visible=bool(image_url))
+
+    chatbot.chatbot.change(fn=update_image_display, inputs=[chatbot.input, chatbot.chatbot, session_id], outputs=[image_display])
+
+    # ---------- Section 3: Voice Transcription ----------
+    gr.Markdown("## 🎙️ Realtime Voice Transcription")
+
+    with gr.Row():
+        transcript_box = gr.Textbox(label="Live Transcript", lines=7, interactive=False, autoscroll=True)
+    
+    with gr.Row():
+        mic_input = gr.Audio(source="microphone", streaming=True)
+        clear_button = gr.Button("Clear Transcript")
+
+    mic_input.stream(fn=send_audio_chunk, inputs=[mic_input, client_id], outputs=transcript_box)
+    clear_button.click(fn=clear_transcript, inputs=[client_id], outputs=transcript_box)
+    demo.load(fn=create_websocket_client, outputs=client_id)
+
+demo.launch()