Update app.py

app.py

@@ -1,14 +1,50 @@
 import streamlit as st
 import os
 import google.generativeai as genai
+import io
+import soundfile as sf
+from groq import Groq
 
 # Streamlit Seite konfigurieren
 st.set_page_config(
-    page_title="Gemini-2 Chatbot",
+    page_title="Gemini-2 Chatbot mit Spracheingabe",
     page_icon="🤖"
 )
 
+# Load environment variables for Groq
+api_key = os.getenv('groqwhisper')
+if api_key is None:
+    st.error("The 'groq_whisper' environment variable is not set. Please set it and restart the app.")
+    st.stop()
 
+# Initialize Groq client
+client = Groq(api_key=api_key)
+
+# Funktion zur Verarbeitung von Audio
+def process_audio(audio_data):
+    """Process audio data and return transcription."""
+    try:
+        sample_rate, samples = audio_data
+        
+        # Create in-memory WAV file
+        with io.BytesIO() as wav_buffer:
+            sf.write(wav_buffer, samples, sample_rate, format='WAV')
+            wav_buffer.seek(0)
+            
+            # Send to Groq for transcription
+            transcription = client.audio.transcriptions.create(
+                file=("recording.wav", wav_buffer.read(), "audio/wav"),
+                model="whisper-large-v3-turbo",
+                prompt="transcribe",
+                language="de",
+                response_format="json",
+                temperature=0.0
+            )
+        return transcription.text
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+
+# Gemini API Konfiguration
 genai.configure(api_key=os.environ["geminiapi"])
 
 # Modell-Konfiguration
@@ -31,12 +67,36 @@ if "chat_session" not in st.session_state:
     st.session_state.chat_session = model.start_chat(history=[])
 
 # UI Komponenten
-st.title("Gemini-2 Chatbot")
-user_input = st.text_input("Stelle deine Frage:", key="user_input")
+st.title("Gemini-2 Chatbot mit Spracheingabe")
+
+# Audio recorder component
+audio_bytes = st.audio_input("Klicke zum Aufnehmen", key="audio_input")
+
+# Chat Input
+user_input = st.text_input("Oder schreibe deine Frage:", key="text_input")
+
+if audio_bytes:
+    # Extrahiere die Bytes aus dem UploadedFile-Objekt
+    audio_bytes_content = audio_bytes.getvalue()
+    
+    # Konvertiere die Bytes in ein numpy-Array mit soundfile
+    with io.BytesIO(audio_bytes_content) as wav_io:
+        samples, sample_rate = sf.read(wav_io)
+        
+        # Konvertiere Stereo in Mono, falls erforderlich
+        if len(samples.shape) > 1 and samples.shape[1] == 2:
+            samples = samples.mean(axis=1)
+        
+        # Verarbeite das Audio
+        with st.spinner("Transcribing..."):
+            transcription = process_audio((sample_rate, samples))
+        
+        # Verarbeitet die Transkription als Eingabe für den Chatbot
+        if transcription:
+           user_input = transcription
 
 if user_input:
     messages = st.container()
-    #messages.chat_message("user").write(f"{user_input}")
     # Prompt mit Sprachaufforderung kombinieren
     full_prompt = f"{user_input}\nAntworte immer auf Deutsch"
     
@@ -50,12 +110,5 @@ if user_input:
         response_text = "Keine Antwort erhalten"
     
     # Antwort anzeigen
-    #st.subheader("Antwort:")
-    #st.chat_input(response_text)
-    messages.chat_message("assistant").write(f"{response_text}")
-    # Quellen anzeigen falls vorhanden
-    #if response.grounding_metadata:
-        #st.subheader("Quellen:")
-        #for source in response.grounding_metadata.sources:
-            #st.markdown(f"- [{source.url}]({source.url})")
-
+    messages.chat_message("user").write(f"{user_input}")
+    messages.chat_message("assistant").write(f"{response_text}")