Create app.py

app.py

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+import openai
+import speech_recognition as sr
+import os
+import gradio as gr
+from dotenv import load_dotenv
+from gtts import gTTS
+
+# Load your OpenAI API key from the Hugging Face secrets
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+# The prompt will be retrieved from Hugging Face secrets
+def get_prompt():
+    return os.getenv("AI_PROMPT_SECRET")
+
+# Initialize speech recognition
+recognizer = sr.Recognizer()
+
+# Function to convert speech to text
+def speech_to_text(audio):
+    if not audio:  # Check if audio is None or empty
+        return "No audio input detected. Please provide a valid audio file."
+    try:
+        with sr.AudioFile(audio) as source:
+            recognizer.adjust_for_ambient_noise(source)
+            audio_data = recognizer.record(source)
+            text = recognizer.recognize_google(audio_data)
+            return text
+    except sr.UnknownValueError:
+        return "Sorry, I could not understand the audio."
+    except sr.RequestError as e:
+        return f"Could not request results; {e}"
+
+# Function to get GPT-3.5-turbo response
+def get_gpt_response(prompt):
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": get_prompt()},  # Using the secret prompt
+                {"role": "user", "content": prompt}
+            ]
+        )
+        return response['choices'][0]['message']['content']
+    except Exception as e:
+        return f"Error: {e}"
+
+# Function to convert text to speech using gTTS
+def text_to_speech(response):
+    tts = gTTS(response)
+    tts.save("response.mp3")
+    return "response.mp3"
+
+# Gradio function that integrates all components
+def chatbot(audio):
+    user_input = speech_to_text(audio)
+    if "Sorry" in user_input or "No audio input" in user_input:
+        return user_input, None
+    response = get_gpt_response(user_input)
+    if response:
+        audio_response = text_to_speech(response)
+        return response, audio_response
+    return "Error generating response.", None
+
+# Gradio interface
+iface = gr.Interface(
+    fn=chatbot,
+    inputs=gr.Audio(type="filepath"),
+    outputs=[gr.Textbox(label="Transcription"), gr.Audio(label="AI Response")],
+    live=True,
+    title="Conversational Assistant",
+    description="Upload an audio file or record your voice to get a response from the AI."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()