Update app.py

app.py

@@ -1,41 +1,243 @@
 import gradio as gr
-from fastapi import FastAPI, UploadFile, File, Request
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import StreamingResponse
+import fastapi
 from fastapi.staticfiles import StaticFiles
-from app.agent import process_text
-from app.speech_to_text import transcribe_audio
-from app.text_to_speech import synthesize_speech
-import io
+from fastapi.responses import HTMLResponse, FileResponse
+from fastapi import FastAPI, Request, Form, UploadFile, File
+import os
+import time
+import logging
+import json
+import shutil
+import uvicorn
+from pathlib import Path
 
-app = FastAPI()
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
+# Create the FastAPI app
+app = FastAPI(title="AGI Telecom POC")
 
-app.mount("/", StaticFiles(directory="frontend", html=True), name="frontend")
+# Create static directory if it doesn't exist
+static_dir = Path("static")
+static_dir.mkdir(exist_ok=True)
 
-@app.post("/transcribe")
+# Copy index.html from templates to static if it doesn't exist
+html_template = Path("templates/index.html")
+static_html = static_dir / "index.html"
+if html_template.exists() and not static_html.exists():
+    shutil.copy(html_template, static_html)
+
+# Mount static files
+app.mount("/static", StaticFiles(directory="static"), name="static")
+
+# Mock data and functions to simulate the real implementation
+SESSIONS = {}
+
+def generate_session_id():
+    """Generate a unique session ID."""
+    import uuid
+    return str(uuid.uuid4())
+
+def mock_transcribe(audio_bytes):
+    """Mock function to simulate speech-to-text."""
+    # In production, this would use Whisper
+    logger.info("Transcribing audio...")
+    time.sleep(1)  # Simulate processing time
+    return "This is a mock transcription of the audio."
+
+def mock_agent_response(text, session_id="default"):
+    """Mock function to simulate agent reasoning."""
+    # In production, this would use a real LLM
+    logger.info(f"Processing query: {text}")
+    time.sleep(1.5)  # Simulate processing time
+    
+    # Simple keyword-based responses
+    if "5g" in text.lower():
+        return "5G is the fifth generation of cellular networks, offering higher speeds, lower latency, and more capacity than previous generations."
+    elif "telecom" in text.lower():
+        return "Telecommunications (telecom) refers to the exchange of information over significant distances by electronic means."
+    elif "webrtc" in text.lower():
+        return "WebRTC (Web Real-Time Communication) is a free, open-source project that enables web browsers and mobile applications to have real-time communication via simple APIs."
+    else:
+        return "I'm an AI assistant specialized in telecom topics. Feel free to ask me about 5G, network technologies, or telecommunications in general."
+
+def mock_synthesize_speech(text):
+    """Mock function to simulate text-to-speech."""
+    # In production, this would use a real TTS engine
+    logger.info("Synthesizing speech...")
+    time.sleep(0.5)  # Simulate processing time
+    
+    # Create a dummy audio file
+    import numpy as np
+    from scipy.io.wavfile import write
+    
+    sample_rate = 22050
+    duration = 2  # seconds
+    t = np.linspace(0, duration, int(sample_rate * duration), endpoint=False)
+    audio = np.sin(2 * np.pi * 440 * t) * 0.3
+    
+    output_file = "temp_audio.wav"
+    write(output_file, sample_rate, audio.astype(np.float32))
+    
+    with open(output_file, "rb") as f:
+        audio_bytes = f.read()
+    
+    # Clean up
+    os.remove(output_file)
+    
+    return audio_bytes
+
+# Routes for the API
+@app.get("/", response_class=HTMLResponse)
+async def root():
+    """Serve the main UI."""
+    return FileResponse("static/index.html")
+
+@app.post("/api/transcribe")
 async def transcribe(file: UploadFile = File(...)):
-    audio_bytes = await file.read()
-    text = transcribe_audio(audio_bytes)
-    return {"transcription": text}
-
-@app.post("/query")
-async def query_agent(request: Request):
-    data = await request.json()
-    input_text = data.get("input_text", "")
-    response = process_text(input_text)
-    return {"response": response}
-
-@app.get("/speak")
-async def speak(text: str):
-    audio = synthesize_speech(text)
-    return StreamingResponse(io.BytesIO(audio), media_type="audio/wav")
-
-# Required for Hugging Face Spaces
-gradio_app = gr.mount_gradio_app(app, None)
+    """Transcribe audio to text."""
+    try:
+        audio_bytes = await file.read()
+        text = mock_transcribe(audio_bytes)
+        return {"transcription": text}
+    except Exception as e:
+        logger.error(f"Transcription error: {str(e)}")
+        return {"error": f"Failed to transcribe audio: {str(e)}"}
+
+@app.post("/api/query")
+async def query_agent(input_text: str = Form(...), session_id: str = Form("default")):
+    """Process a text query with the agent."""
+    try:
+        response = mock_agent_response(input_text, session_id)
+        return {"response": response}
+    except Exception as e:
+        logger.error(f"Query error: {str(e)}")
+        return {"error": f"Failed to process query: {str(e)}"}
+
+@app.post("/api/speak")
+async def speak(text: str = Form(...)):
+    """Convert text to speech."""
+    try:
+        audio_bytes = mock_synthesize_speech(text)
+        return FileResponse(
+            "temp_audio.wav",
+            media_type="audio/wav",
+            filename="response.wav"
+        )
+    except Exception as e:
+        logger.error(f"Speech synthesis error: {str(e)}")
+        return {"error": f"Failed to synthesize speech: {str(e)}"}
+
+@app.post("/api/session")
+async def create_session():
+    """Create a new session."""
+    session_id = generate_session_id()
+    SESSIONS[session_id] = {"created_at": time.time()}
+    return {"session_id": session_id}
+
+# Gradio interface
+with gr.Blocks(title="AGI Telecom POC", css="footer {visibility: hidden}") as interface:
+    gr.Markdown("# AGI Telecom POC Demo")
+    gr.Markdown("This is a demonstration of the AGI Telecom Proof of Concept. The full interface is available via the direct API.")
+    
+    with gr.Row():
+        with gr.Column():
+            # Input components
+            audio_input = gr.Audio(label="Voice Input", type="filepath")
+            text_input = gr.Textbox(label="Text Input", placeholder="Type your message here...", lines=2)
+            
+            # Session management
+            session_id = gr.Textbox(label="Session ID", value="default")
+            new_session_btn = gr.Button("New Session")
+            
+            # Action buttons
+            with gr.Row():
+                transcribe_btn = gr.Button("Transcribe Audio")
+                query_btn = gr.Button("Send Query")
+                speak_btn = gr.Button("Speak Response")
+        
+        with gr.Column():
+            # Output components
+            transcription_output = gr.Textbox(label="Transcription", lines=2)
+            response_output = gr.Textbox(label="Agent Response", lines=5)
+            audio_output = gr.Audio(label="Voice Response", autoplay=True)
+            
+            # Status and info
+            status_output = gr.Textbox(label="Status", value="Ready")
+    
+    # Link components with functions
+    def update_session():
+        new_id = generate_session_id()
+        status = f"Created new session: {new_id}"
+        return new_id, status
+    
+    new_session_btn.click(
+        update_session,
+        outputs=[session_id, status_output]
+    )
+    
+    def process_audio(audio_path, session):
+        if not audio_path:
+            return "No audio provided", "", None, "Error: No audio input"
+        
+        try:
+            with open(audio_path, "rb") as f:
+                audio_bytes = f.read()
+            
+            # Transcribe
+            text = mock_transcribe(audio_bytes)
+            
+            # Get response
+            response = mock_agent_response(text, session)
+            
+            # Synthesize
+            audio_bytes = mock_synthesize_speech(response)
+            
+            temp_file = "temp_response.wav"
+            with open(temp_file, "wb") as f:
+                f.write(audio_bytes)
+            
+            return text, response, temp_file, "Processed successfully"
+        except Exception as e:
+            logger.error(f"Error: {str(e)}")
+            return "", "", None, f"Error: {str(e)}"
+    
+    transcribe_btn.click(
+        lambda audio_path: mock_transcribe(open(audio_path, "rb").read()) if audio_path else "No audio provided",
+        inputs=[audio_input],
+        outputs=[transcription_output]
+    )
+    
+    query_btn.click(
+        lambda text, session: mock_agent_response(text, session),
+        inputs=[text_input, session_id],
+        outputs=[response_output]
+    )
+    
+    speak_btn.click(
+        lambda text: "temp_response.wav" if mock_synthesize_speech(text) else None,
+        inputs=[response_output],
+        outputs=[audio_output]
+    )
+    
+    # Full process
+    audio_input.change(
+        process_audio,
+        inputs=[audio_input, session_id],
+        outputs=[transcription_output, response_output, audio_output, status_output]
+    )
+
+# Mount Gradio app
+app = gr.mount_gradio_app(app, interface, path="/gradio")
+
+# Run the app
+if __name__ == "__main__":
+    # Check if running on HF Spaces
+    if os.environ.get("SPACE_ID"):
+        # Running on HF Spaces - use their port
+        port = int(os.environ.get("PORT", 7860))
+        uvicorn.run(app, host="0.0.0.0", port=port)
+    else:
+        # Running locally
+        uvicorn.run(app, host="0.0.0.0", port=8000)