Update app.py

app.py

@@ -16,7 +16,8 @@ import requests
 # Configuración de la clave API
 load_dotenv()
 openai.api_key = os.getenv("OPENAI_API_KEY")
-os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your/google-cloud-credentials.json"
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "botidinamix-g.json"
+PEXELS_API_KEY = os.getenv("sWMvMKk7Mvv5o6Q90XGMfP2vliUiagc9rESBAO9DVZQdmlcla0LMJ8O3")
 
 # Inicialización de Vertex AI
 vertexai.init(project="your-project-id", location="us-central1")  # Reemplaza "your-project-id" y "us-central1"
@@ -75,7 +76,7 @@ st.markdown(
 )
 
 # Encabezado
-st.image("biblie.jpg")
+st.image("biblia.jpg")
 st.title("📖 LOS CÓDIGOS DE DIOS - BOTIDINAMIX AI")
 st.markdown("Bienvenido al Asistente Teológico, donde puedes preguntar sobre interpretaciones y reflexiones bíblicas.")
 
@@ -162,7 +163,6 @@ elif page == "Generador de Frases Bíblicas":
 
     # Función para generar una imagen alusiva usando Pexels
     def generar_imagen(frase):
-        PEXELS_API_KEY = os.getenv("sWMvMKk7Mvv5o6Q90XGMfP2vliUiagc9rESBAO9DVZQdmlcla0LMJ8O3")
         headers = {
             "Authorization": f"Bearer {PEXELS_API_KEY}"
         }
@@ -205,3 +205,59 @@ elif page == "Generador de Frases Bíblicas":
         else:
             st.warning("Por favor, ingresa un versículo o una palabra antes de generar.")
 
+# Función para obtener respuesta de OpenAI
+def obtener_respuesta(pregunta, modelo="gpt-4", temperatura=0.5):
+    response = openai.ChatCompletion.create(
+        model=modelo,
+        messages=[{"role": "system", "content": "You are a knowledgeable theological assistant."},
+                  {"role": "user", "content": pregunta}],
+        temperature=temperatura,
+        max_tokens=150,
+    )
+    respuesta = response['choices'][0]['message']['content']
+    return respuesta
+
+# Función para convertir texto a voz usando Google Cloud Text-to-Speech
+def text_to_speech(text):
+    client = texttospeech.TextToSpeechClient()
+    synthesis_input = texttospeech.SynthesisInput(text=text)
+    voice = texttospeech.VoiceSelectionParams(language_code="es-ES", ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
+    audio_config = texttospeech.AudioConfig(audio_encoding=texttospeech.AudioEncoding.MP3)
+    response = client.synthesize_speech(input=synthesis_input, voice=voice, audio_config=audio_config)
+    audio_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3").name
+    with open(audio_path, "wb") as out:
+        out.write(response.audio_content)
+    return audio_path
+
+# Función para convertir texto a voz y devolver base64
+def text_to_speech_base64(text):
+    client = texttospeech.TextToSpeechClient()
+    synthesis_input = texttospeech.SynthesisInput(text=text)
+    voice = texttospeech.VoiceSelectionParams(language_code="es-ES", ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
+    audio_config = texttospeech.AudioConfig(audio_encoding=texttospeech.AudioEncoding.MP3)
+    response = client.synthesize_speech(input=synthesis_input, voice=voice, audio_config=audio_config)
+    audio_base64 = base64.b64encode(response.audio_content).decode('utf-8')
+    return audio_base64
+
+# Clase para procesar audio
+class AudioProcessor(AudioProcessorBase):
+    def __init__(self):
+        self.audio_bytes = b''
+
+    def recv(self, frame):
+        self.audio_bytes += frame.to_ndarray().tobytes()
+        return frame
+
+# Función para transcribir audio a texto usando Google Cloud Speech-to-Text
+def transcribir_audio(audio_bytes):
+    client = SpeechClient()
+    audio = RecognitionAudio(content=audio_bytes)
+    config = RecognitionConfig(
+        encoding=RecognitionConfig.AudioEncoding.LINEAR16,
+        sample_rate_hertz=16000,
+        language_code="es-ES",
+    )
+    response = client.recognize(config=config, audio=audio)
+    for result in response.results:
+        return result.alternatives[0].transcript
+    return ""