Week 2: Technical Assistant - Salah (Bootcamp)
This commit is contained in:
Mohamed Salah
2
week2/community-contributions/salah/.env.example
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2
week2/community-contributions/salah/.env.example
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OPENAI_API_KEY=sk-or-v1-openai-api-key
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GEMINI_API_KEY=AI-gemini-api-key
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213
week2/community-contributions/salah/app.py
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213
week2/community-contributions/salah/app.py
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import gradio as gr
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from simple_assistant import Assistant
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class SimpleUI:
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def __init__(self):
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print("\n" + "="*60)
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print("Starting up...")
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print("="*60)
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self.assistant = Assistant()
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self.history = [] # Text history for API
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self.display_history = [] # Display history with audio for chat UI
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self.audio_enabled = True
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print("UI initialized")
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print("Audio features: Gemini STT + TTS")
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print("="*60 + "\n")
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def add_message(self, msg):
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print("\n" + ">"*60)
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print(f"[UI] New message: {msg[:50]}...")
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if not msg.strip():
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print("[UI] Empty message, ignoring")
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print(">"*60 + "\n")
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return self.display_history, ""
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print(f"[UI] Adding to history (current: {len(self.history)} messages)")
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# Add to API history (text only)
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self.history.append({"role": "user", "content": msg})
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# Add to display history
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self.display_history.append({"role": "user", "content": msg})
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print("[UI] Getting AI response...")
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response = self.assistant.chat(msg, self.history)
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print(f"[UI] Adding response to history")
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# Add to API history (text only)
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self.history.append({"role": "assistant", "content": response})
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# Add to display history
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self.display_history.append({"role": "assistant", "content": response})
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print(f"[UI] Total history: {len(self.history)} messages")
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print(f"[UI] Returning {len(self.display_history)} messages to display")
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print(">"*60 + "\n")
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return self.display_history, ""
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def handle_voice_input(self, audio_file):
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print("\n" + ">"*60)
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print("[UI] Voice input received")
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print(f"[UI] Audio file: {audio_file}")
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if not audio_file:
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print("[UI] No audio file")
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print(">"*60 + "\n")
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return self.display_history, None
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# Transcribe
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print("[UI] Transcribing with Gemini...")
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text = self.assistant.speech_to_text(audio_file)
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if not text:
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print("[UI] Transcription failed")
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print(">"*60 + "\n")
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error_msg = "Sorry, couldn't transcribe audio"
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self.history.append({"role": "assistant", "content": error_msg})
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self.display_history.append({"role": "assistant", "content": error_msg})
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return self.display_history, None
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print(f"[UI] Transcribed: {text}")
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# Add to API history (text only)
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self.history.append({"role": "user", "content": text})
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# Add voice message to display history with audio file
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self.display_history.append({
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"role": "user",
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"content": {
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"path": audio_file,
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"alt_text": f"🎤 {text}"
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}
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})
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# Get response
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print("[UI] Getting AI response...")
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response = self.assistant.chat(text, self.history)
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# Add text response to API history
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self.history.append({"role": "assistant", "content": response})
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# Generate audio response
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print("[UI] Generating audio with Gemini TTS...")
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audio_response = self.assistant.text_to_speech(response)
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if audio_response:
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print(f"[UI] ✓ Audio response generated")
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# Add response with audio to display history
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self.display_history.append({
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"role": "assistant",
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"content": {
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"path": audio_response,
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"alt_text": f"🔊 {response[:100]}..."
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}
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})
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else:
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print(f"[UI] ⚠ No audio, text only")
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self.display_history.append({"role": "assistant", "content": response})
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print(f"[UI] Returning {len(self.display_history)} messages")
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print(">"*60 + "\n")
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return self.display_history, None
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def analyze(self, code, lang):
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print("\n" + ">"*60)
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print(f"[UI] Code analysis request")
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print(f"[UI] Language: {lang}")
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print(f"[UI] Code length: {len(code)} chars")
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if not code.strip():
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print("[UI] Empty code, ignoring")
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print(">"*60 + "\n")
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return self.display_history
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print("[UI] Calling analyze_code...")
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result = self.assistant.analyze_code(code, lang)
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print("[UI] Adding to history")
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# Add to API history
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self.history.append({"role": "user", "content": f"Analyze {lang} code"})
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self.history.append({"role": "assistant", "content": result})
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# Add to display history
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self.display_history.append({"role": "user", "content": f"Analyze {lang} code"})
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self.display_history.append({"role": "assistant", "content": result})
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print(f"[UI] Returning {len(self.display_history)} messages")
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print(">"*60 + "\n")
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return self.display_history
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def create_ui(self):
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print("\n" + "="*60)
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print("Creating Gradio UI...")
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print("="*60)
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with gr.Blocks() as app:
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gr.Markdown("# Tech Assistant")
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gr.Markdown("**Voice-enabled**: Type or record audio messages")
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# Chat panel - shows all messages including audio
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chat = gr.Chatbot(type="messages", height=500)
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print("✓ Chatbot created")
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# Input area at bottom (like ChatGPT)
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with gr.Row():
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msg = gr.Textbox(
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label="Message",
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placeholder="Type a message or record audio...",
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scale=9,
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container=False
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)
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mic = gr.Audio(
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sources=["microphone"],
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type="filepath",
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label="🎤 Record",
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scale=1,
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waveform_options={"show_controls": False}
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)
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print("✓ Message and record inputs created")
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# Wire events
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msg.submit(self.add_message, msg, [chat, msg])
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print("✓ Message submit event wired")
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mic.stop_recording(self.handle_voice_input, mic, [chat, mic])
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print("✓ Voice input event wired")
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# Tools section
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with gr.Accordion("Tools", open=False):
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gr.Markdown("### Code Analysis")
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code = gr.Textbox(label="Code", lines=8)
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lang = gr.Dropdown(
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choices=["python", "javascript", "java"],
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value="python",
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label="Language"
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)
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analyze_btn = gr.Button("Analyze")
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print("✓ Code analysis tools created")
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analyze_btn.click(self.analyze, [code, lang], chat)
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print("✓ Analyze button event wired")
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print("✓ UI creation complete")
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print("="*60 + "\n")
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return app
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def launch(self):
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print("\n" + "="*60)
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print("Launching Gradio app...")
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print("="*60)
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app = self.create_ui()
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print("Starting server on port 7862...")
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print("="*60 + "\n")
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app.launch(server_port=7862)
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if __name__ == "__main__":
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print("\n" + "#"*60)
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print("# TECH ASSISTANT - SIMPLE UI")
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print("#"*60 + "\n")
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ui = SimpleUI()
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ui.launch()
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259
week2/community-contributions/salah/assistant.py
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259
week2/community-contributions/salah/assistant.py
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import os
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import json
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from google import genai
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from google.genai import types
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from dotenv import load_dotenv
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from openai import OpenAI
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from pathlib import Path
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import tempfile
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import wave
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load_dotenv()
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class Assistant:
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def __init__(self):
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print("\n" + "="*60)
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print("Initializing Assistant...")
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print("="*60)
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openrouter_key = os.getenv('OPENAI_API_KEY')
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gemini_key = os.getenv('GEMINI_API_KEY')
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print(f"OpenRouter API Key: {openrouter_key[:20]}..." if openrouter_key else "OpenRouter API Key: NOT FOUND")
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print(f"Gemini API Key: {gemini_key[:20]}..." if gemini_key else "Gemini API Key: NOT FOUND")
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# OpenRouter client for text (GPT-4o-mini)
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print("Setting up OpenRouter client...")
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self.openrouter = OpenAI(
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api_key=openrouter_key,
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base_url="https://openrouter.ai/api/v1"
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)
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print("OpenRouter client ready")
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# Gemini client for audio and images
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print("Setting up Gemini client...")
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self.gemini_client = genai.Client(api_key=gemini_key)
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print("Gemini client ready (audio + images)")
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self.text_model = "openai/gpt-4o-mini"
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self.system_prompt = "You are a helpful technical assistant. Keep answers clear and practical."
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self.stt_model = "gemini-2.0-flash-exp"
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self.tts_model = "gemini-2.5-flash-preview-tts"
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print(f"Text Model: {self.text_model}")
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print(f"STT Model: {self.stt_model}")
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print(f"TTS Model: {self.tts_model}")
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def chat(self, message, history=[]):
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print(f"[Chat] User: {message[:50]}...")
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print(f"[Chat] History messages: {len(history)}")
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print(f"[Chat] Model: {self.text_model}")
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messages = [{"role": "system", "content": self.system_prompt}]
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messages.extend(history)
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messages.append({"role": "user", "content": message})
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print(f"[Chat] Total messages to send: {len(messages)}")
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print("[Chat] Calling OpenRouter API...")
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try:
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response = self.openrouter.chat.completions.create(
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model=self.text_model,
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messages=messages,
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extra_body={
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"usage": {
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"include": True
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}
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}
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)
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reply = response.choices[0].message.content
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print(f"[Chat] Response received")
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print(f"[Chat] GPT-4o-mini: {len(reply)} chars")
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print(f"[Chat] Preview: {reply[:100]}...")
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# Print usage and cost
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if hasattr(response, 'usage') and response.usage:
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usage = response.usage
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print(f"[Chat] Usage:")
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print(f" - Prompt tokens: {usage.prompt_tokens}")
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print(f" - Completion tokens: {usage.completion_tokens}")
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print(f" - Total tokens: {usage.total_tokens}")
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if hasattr(usage, 'cost') and usage.cost:
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print(f" - Cost: ${usage.cost:.6f}")
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print("-"*60 + "\n")
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return reply
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except Exception as e:
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print(f"[Error] ✗ API call failed: {e}")
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print("-"*60 + "\n")
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return f"Error: {str(e)}"
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def analyze_code(self, code, language="python"):
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print("\n" + "="*60)
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print(f"[Code] Analyzing {language} code...")
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print(f"[Code] Code length: {len(code)} characters")
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print(f"[Code] Lines: {len(code.splitlines())}")
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print("="*60)
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prompt = f"Analyze this {language} code for bugs and improvements:\n\n```{language}\n{code}\n```"
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result = self.chat(prompt)
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print("[Code] Analysis complete\n")
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return result
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def generate_image(self, description):
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print("\n" + "="*60)
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print(f"[Image] Gemini generating: {description[:50]}...")
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print(f"[Image] Model: gemini-2.0-flash-exp")
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try:
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prompt = f"Generate an image of: {description}. Make it clear and professional."
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print("[Image] Calling Gemini API...")
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response = self.gemini_client.models.generate_content(
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model='gemini-2.0-flash-exp',
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contents=prompt
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)
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print("[Image] Response received")
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print(f"[Image] Result length: {len(response.text)} chars")
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# Print usage and cost (Gemini 2.0 Flash: $0.30/1M input, $2.50/1M output)
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if hasattr(response, 'usage_metadata'):
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usage = response.usage_metadata
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input_tokens = usage.prompt_token_count
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output_tokens = usage.candidates_token_count
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total_tokens = usage.total_token_count
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cost = (input_tokens * 0.30 + output_tokens * 2.50) / 1_000_000
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print(f"[Image] Usage:")
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print(f" - Input tokens: {input_tokens}")
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print(f" - Output tokens: {output_tokens}")
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print(f" - Total tokens: {total_tokens}")
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print(f" - Cost: ${cost:.6f}")
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print("="*60 + "\n")
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return response.text
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except Exception as e:
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print(f"[Error] ✗ Image generation failed: {e}")
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print("="*60 + "\n")
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return None
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def speech_to_text(self, audio_file_path):
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print("\n" + "="*60)
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print("[STT] Gemini speech-to-text...")
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print(f"[STT] Audio file: {audio_file_path}")
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try:
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print("[STT] Uploading audio file to Gemini...")
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audio_file = self.gemini_client.files.upload(file=audio_file_path)
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print(f"[STT] File uploaded: {audio_file.name}")
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print("[STT] Transcribing with Gemini...")
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prompt = "Generate a transcript of the speech."
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response = self.gemini_client.models.generate_content(
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model=self.stt_model,
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contents=[prompt, audio_file]
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)
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text = response.text.strip()
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print(f"[STT] Transcribed: {text[:100]}...")
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print(f"[STT] Length: {len(text)} chars")
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# Print usage and cost (Flash Native Audio Input: $3.00/1M tokens)
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if hasattr(response, 'usage_metadata'):
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usage = response.usage_metadata
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input_tokens = usage.prompt_token_count
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output_tokens = usage.candidates_token_count
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total_tokens = usage.total_token_count
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# Audio input is $3.00/1M, text output is $2.50/1M
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cost = (input_tokens * 3.00 + output_tokens * 2.50) / 1_000_000
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print(f"[STT] Usage:")
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print(f" - Input tokens (audio): {input_tokens}")
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print(f" - Output tokens (text): {output_tokens}")
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print(f" - Total tokens: {total_tokens}")
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print(f" - Cost: ${cost:.6f}")
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print("="*60 + "\n")
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return text
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except Exception as e:
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print(f"[Error] ✗ STT failed: {e}")
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print(f"[Error] Full error: {type(e).__name__}: {str(e)}")
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print("="*60 + "\n")
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return None
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def text_to_speech(self, text):
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print("\n" + "="*60)
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print(f"[TTS] Gemini text-to-speech...")
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print(f"[TTS] Text: {text[:50]}...")
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print(f"[TTS] Length: {len(text)} chars")
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try:
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# Limit text length for TTS
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text_to_speak = text[:500] if len(text) > 500 else text
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print("[TTS] Generating audio with Gemini TTS model...")
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response = self.gemini_client.models.generate_content(
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model=self.tts_model,
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contents=f"Say cheerfully: {text_to_speak}",
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config=types.GenerateContentConfig(
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response_modalities=["AUDIO"],
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speech_config=types.SpeechConfig(
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voice_config=types.VoiceConfig(
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prebuilt_voice_config=types.PrebuiltVoiceConfig(
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voice_name='Kore',
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)
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)
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),
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)
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)
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print("[TTS] Audio generated, converting to WAV...")
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# Extract raw PCM audio data
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pcm_data = response.candidates[0].content.parts[0].inline_data.data
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print(f"[TTS] Raw PCM size: {len(pcm_data)} bytes")
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# Print usage and cost (2.5 Flash Preview TTS: $10.00/1M audio output tokens)
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if hasattr(response, 'usage_metadata'):
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usage = response.usage_metadata
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input_tokens = usage.prompt_token_count
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output_tokens = usage.candidates_token_count
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total_tokens = usage.total_token_count
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# Text input is $0.30/1M, audio output is $10.00/1M
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cost = (input_tokens * 0.30 + output_tokens * 10.00) / 1_000_000
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print(f"[TTS] Usage:")
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print(f" - Input tokens (text): {input_tokens}")
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print(f" - Output tokens (audio): {output_tokens}")
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print(f" - Total tokens: {total_tokens}")
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print(f" - Cost: ${cost:.6f}")
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# Create WAV file with proper headers
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# Gemini TTS outputs: 24kHz sample rate, mono, 16-bit PCM
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temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
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with wave.open(temp_file.name, 'wb') as wav_file:
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wav_file.setnchannels(1) # Mono
|
||||
wav_file.setsampwidth(2) # 16-bit = 2 bytes
|
||||
wav_file.setframerate(24000) # 24kHz
|
||||
wav_file.writeframes(pcm_data)
|
||||
|
||||
temp_file.close()
|
||||
|
||||
print(f"[TTS] WAV file saved: {temp_file.name}")
|
||||
print("="*60 + "\n")
|
||||
return temp_file.name
|
||||
|
||||
except Exception as e:
|
||||
print(f"[Error] ✗ TTS failed: {e}")
|
||||
print(f"[Error] Full error: {type(e).__name__}: {str(e)}")
|
||||
print("="*60 + "\n")
|
||||
return None
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
assistant = Assistant()
|
||||
|
||||
# Test it
|
||||
response = assistant.chat("What is Python?")
|
||||
print(f"\nResponse: {response}")
|
||||
4
week2/community-contributions/salah/requirements.txt
Normal file
4
week2/community-contributions/salah/requirements.txt
Normal file
@@ -0,0 +1,4 @@
|
||||
openai>=1.3.0
|
||||
gradio>=4.0.0
|
||||
python-dotenv>=1.0.0
|
||||
google-genai>=0.3.0
|
||||
Reference in New Issue
Block a user