Update app.py

app.py

@@ -1,179 +1,161 @@
 import gradio as gr
-import asyncio
-from websockets import connect, Data, ClientConnection
-from dotenv import load_dotenv
-import json
-import os 
-import threading
+import os, time, re, json, base64, asyncio, threading, uuid, io
 import numpy as np
-import base64
 import soundfile as sf
-import io
 from pydub import AudioSegment
-import time
-import uuid
-
-# =========================
-# Setup & Configuration
-# =========================
-
-class LogColors:
-    OK = '\033[94m'
-    SUCCESS = '\033[92m'
-    WARNING = '\033[93m'
-    ERROR = '\033[91m'
-    ENDC = '\033[0m'
-
-load_dotenv() 
-OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
-if not OPENAI_API_KEY:
-    raise ValueError("OPENAI_API_KEY environment variable must be set")
-
-WEBSOCKET_URI = "wss://api.openai.com/v1/realtime?intent=transcription"
-WEBSOCKET_HEADERS = {
-    "Authorization": "Bearer " + OPENAI_API_KEY,
-    "OpenAI-Beta": "realtime=v1"
-}
-
-css = ""
-connections = {}
+from openai import OpenAI
+from websockets import connect
+from dotenv import load_dotenv
 
-# =========================
-# WebSocket Client Class
-# =========================
+# Load environment variables
+load_dotenv()
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+ASSISTANT_ID = os.getenv("ASSISTANT_ID")
+client = OpenAI(api_key=OPENAI_API_KEY)
 
+HEADERS = {"Authorization": f"Bearer {OPENAI_API_KEY}", "OpenAI-Beta": "realtime=v1"}
+WS_URI = "wss://api.openai.com/v1/realtime?intent=transcription"
+connections = {}
+
+# ---------------- WebSocket Client for Voice ----------------
 class WebSocketClient:
-    def __init__(self, uri: str, headers: dict, client_id: str):
-        self.uri = uri
-        self.headers = headers
-        self.websocket: ClientConnection = None
+    def __init__(self, uri, headers, client_id):
+        self.uri, self.headers, self.client_id = uri, headers, client_id
+        self.websocket = None
         self.queue = asyncio.Queue(maxsize=10)
-        self.loop = None
-        self.client_id = client_id
         self.transcript = ""
 
     async def connect(self):
-        try:
-            self.websocket = await connect(self.uri, additional_headers=self.headers)
-            print(f"{LogColors.SUCCESS}Connected to OpenAI WebSocket{LogColors.ENDC}\n")
-
-            with open("openai_transcription_settings.json", "r") as f:
-                settings = f.read()
-                await self.websocket.send(settings)
-
-            await asyncio.gather(self.receive_messages(), self.send_audio_chunks())
-        except Exception as e:
-            print(f"{LogColors.ERROR}WebSocket Connection Error: {e}{LogColors.ENDC}")
+        self.websocket = await connect(self.uri, additional_headers=self.headers)
+        with open("openai_transcription_settings.json", "r") as f:
+            await self.websocket.send(f.read())
+        await asyncio.gather(self.receive_messages(), self.send_audio_chunks())
 
     def run(self):
-        self.loop = asyncio.new_event_loop()
-        asyncio.set_event_loop(self.loop)
-        self.loop.run_until_complete(self.connect())
-
-    def process_websocket_message(self, message: Data):
-        message_object = json.loads(message)
-        if message_object["type"] != "error":
-            print(f"{LogColors.OK}Received message: {LogColors.ENDC} {message}")
-            if message_object["type"] == "conversation.item.input_audio_transcription.delta":
-                delta = message_object["delta"]
-                self.transcript += delta
-            elif message_object["type"] == "conversation.item.input_audio_transcription.completed":
-                self.transcript += ' ' if self.transcript and self.transcript[-1] != ' ' else ''
-        else:
-            print(f"{LogColors.ERROR}Error: {message}{LogColors.ENDC}")
+        loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(loop)
+        loop.run_until_complete(self.connect())
 
     async def send_audio_chunks(self):
         while True:
-            audio_data = await self.queue.get()
-            sample_rate, audio_array = audio_data
-            if self.websocket:
-                if audio_array.ndim > 1:
-                    audio_array = audio_array.mean(axis=1)
-                audio_array = audio_array.astype(np.float32)
-                audio_array /= np.max(np.abs(audio_array)) if np.max(np.abs(audio_array)) > 0 else 1.0
-                audio_array_int16 = (audio_array * 32767).astype(np.int16)
-
-                audio_buffer = io.BytesIO()
-                sf.write(audio_buffer, audio_array_int16, sample_rate, format='WAV', subtype='PCM_16')
-                audio_buffer.seek(0) 
-                audio_segment = AudioSegment.from_file(audio_buffer, format="wav")
-                resampled_audio = audio_segment.set_frame_rate(24000)
-
-                output_buffer = io.BytesIO()
-                resampled_audio.export(output_buffer, format="wav")
-                output_buffer.seek(0)
-                base64_audio = base64.b64encode(output_buffer.read()).decode("utf-8")
-
-                await self.websocket.send(json.dumps({"type": "input_audio_buffer.append", "audio": base64_audio}))
-                print(f"{LogColors.OK}Sent audio chunk{LogColors.ENDC}")
+            sr, arr = await self.queue.get()
+            if arr.ndim > 1: arr = arr.mean(axis=1)
+            arr = (arr / np.max(np.abs(arr))) if np.max(np.abs(arr)) > 0 else arr
+            int16 = (arr * 32767).astype(np.int16)
+            buf = io.BytesIO(); sf.write(buf, int16, sr, format='WAV', subtype='PCM_16')
+            audio = AudioSegment.from_file(buf, format="wav").set_frame_rate(24000)
+            out = io.BytesIO(); audio.export(out, format="wav"); out.seek(0)
+            await self.websocket.send(json.dumps({
+                "type": "input_audio_buffer.append",
+                "audio": base64.b64encode(out.read()).decode()
+            }))
 
     async def receive_messages(self):
-        async for message in self.websocket:
-            self.process_websocket_message(message)
+        async for msg in self.websocket:
+            data = json.loads(msg)
+            if data["type"] == "conversation.item.input_audio_transcription.delta":
+                self.transcript += data["delta"]
 
-    def enqueue_audio_chunk(self, sample_rate: int, chunk_array: np.ndarray):
+    def enqueue_audio_chunk(self, sr, arr):
         if not self.queue.full():
-            asyncio.run_coroutine_threadsafe(self.queue.put((sample_rate, chunk_array)), self.loop)
-        else:
-            print(f"{LogColors.WARNING}Queue is full, dropping audio chunk{LogColors.ENDC}")
-
-    async def close(self):
-        if self.websocket:
-            await self.websocket.close()
-            connections.pop(self.client_id)
-        print(f"{LogColors.WARNING}WebSocket connection closed{LogColors.ENDC}")
-
-
-# =========================
-# Helper Functions
-# =========================
-
-def send_audio_chunk(new_chunk: gr.Audio, client_id: str):
-    if client_id not in connections:
-        return "Connection is being established, please try again in a few seconds."
-    sr, y = new_chunk
-    connections[client_id].enqueue_audio_chunk(sr, y)
-    return connections[client_id].transcript
-
-def create_new_websocket_connection():
-    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 = ""
+            asyncio.run_coroutine_threadsafe(self.queue.put((sr, arr)), asyncio.get_event_loop())
+
+def create_ws():
+    cid = str(uuid.uuid4())
+    client = WebSocketClient(WS_URI, HEADERS, cid)
+    threading.Thread(target=client.run, daemon=True).start()
+    connections[cid] = client
+    return cid
+
+def send_audio(chunk, cid):
+    if cid not in connections: return "Connecting..."
+    sr, arr = chunk
+    connections[cid].enqueue_audio_chunk(sr, arr)
+    return connections[cid].transcript
+
+def clear_transcript(cid):
+    if cid in connections: connections[cid].transcript = ""
     return ""
 
-# =========================
-# Gradio UI Sections
-# =========================
-
-with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
-
-    with gr.Tab("💬 Chat Assistant"):
-        gr.Markdown("### Chat Section (Coming Soon)")
-        gr.Textbox(label="Your question")
-        gr.Button("Send")
-
-    with gr.Tab("📄 Document Viewer"):
-        gr.Markdown("### Upload and View Documents")
-        gr.File(label="Upload Document", file_types=[".pdf", ".txt", ".docx"])
-        gr.Textbox(label="Document Preview", lines=10)
-
-    with gr.Tab("🎤 Voice Transcription"):
-        gr.Markdown("### Realtime Voice-to-Text Transcription")
-        with gr.Row():
-            output_textbox = gr.Textbox(label="Transcript", lines=7, interactive=False, autoscroll=True)
-        with gr.Row():
-            with gr.Column(scale=5):
-                audio_input = gr.Audio(streaming=True, format="wav")
-            with gr.Column():
-                clear_button = gr.Button("Clear Transcript")
-        client_id = gr.State()
-        clear_button.click(clear_transcript, inputs=[client_id], outputs=[output_textbox])
-        audio_input.stream(send_audio_chunk, [audio_input, client_id], [output_textbox], stream_every=0.5)
-        demo.load(create_new_websocket_connection, outputs=[client_id])
-
-demo.launch()
+# ---------------- Chat Assistant Logic ----------------
+def handle_chat(user_input, history, thread_id, image_url):
+    if not OPENAI_API_KEY or not ASSISTANT_ID:
+        return "❌ Missing API key or Assistant ID.", history, thread_id, image_url
+
+    try:
+        if thread_id is None:
+            thread = client.beta.threads.create()
+            thread_id = thread.id
+
+        client.beta.threads.messages.create(thread_id=thread_id, role="user", content=user_input)
+        run = client.beta.threads.runs.create(thread_id=thread_id, assistant_id=ASSISTANT_ID)
+
+        while True:
+            status = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
+            if status.status == "completed": break
+            time.sleep(1)
+
+        msgs = client.beta.threads.messages.list(thread_id=thread_id)
+        for msg in reversed(msgs.data):
+            if msg.role == "assistant":
+                content = msg.content[0].text.value
+                history.append((user_input, content))
+                match = re.search(
+                    r'https://raw\.githubusercontent\.com/AndrewLORTech/surgical-pathology-manual/main/[\w\-/]*\.png',
+                    content
+                )
+                if match:
+                    image_url = match.group(0)
+                break
+
+        return "", history, thread_id, image_url
+
+    except Exception as e:
+        return f"❌ {e}", history, thread_id, image_url
+
+# ---------------- UI ----------------
+with gr.Blocks(theme="lone17/kotaemon") as app:
+    gr.Markdown("# 📄 Document AI Assistant")
+
+    # States
+    chat_state = gr.State([])
+    thread_state = gr.State()
+    image_state = gr.State()
+    client_id = gr.State()
+    mic_shown = gr.State(False)
+
+    with gr.Row(equal_height=True):
+        # Left: Document Viewer
+        with gr.Column(scale=1):
+            image_display = gr.Image(label="🖼️ Document Preview", type="filepath", show_download_button=False)
+
+        # Right: Chat + Mic
+        with gr.Column(scale=1.4):
+            chat = gr.Chatbot(label="💬 Chat", height=450)
+
+            with gr.Row():
+                user_input = gr.Textbox(placeholder="Ask your question...", show_label=False, scale=6)
+                mic_btn = gr.Button("🎙️", scale=1)
+                send_btn = gr.Button("Send", scale=2)
+
+            # Hidden Voice Section
+            with gr.Row(visible=False) as mic_row:
+                with gr.Column(scale=4):
+                    audio = gr.Audio(label="🎤 Speak", streaming=True)
+                with gr.Column(scale=5):
+                    transcript = gr.Textbox(label="Transcript", lines=2, interactive=False)
+                with gr.Column(scale=2):
+                    clear_btn = gr.Button("🧹 Clear")
+
+    # Logic Wiring
+    def toggle_mic(state): return not state, gr.update(visible=not state)
+    mic_btn.click(toggle_mic, inputs=mic_shown, outputs=[mic_shown, mic_row])
+    send_btn.click(handle_chat,
+                   inputs=[user_input, chat_state, thread_state, image_state],
+                   outputs=[user_input, chat, thread_state, image_state])
+    image_state.change(fn=lambda x: x, inputs=image_state, outputs=image_display)
+    audio.stream(fn=send_audio, inputs=[audio, client_id], outputs=transcript, stream_every=0.5)
+    clear_btn.click(fn=clear_transcript, inputs=[client_id], outputs=transcript)
+    app.load(fn=create_ws, outputs=[client_id])
+
+app.launch()