Update app.py

app.py

@@ -1,6 +1,6 @@
 import os
 import gradio as gr
-import requests
+import google.generativeai as genai
 from dotenv import load_dotenv
 from gradio_client import Client, file  # Import Gradio client
 
@@ -8,45 +8,52 @@ from gradio_client import Client, file  # Import Gradio client
 load_dotenv()
 
 # Retrieve API key from environment variable
-API_KEY = os.getenv("API_KEY")
+API_KEY = os.getenv("GEMINI_API_KEY")
 
 # Retrieve system content from environment variable
 SYSTEM_CONTENT = os.getenv("SYSTEM_CONTENT")
 
-API_URL = "https://api.openai.com/v1/chat/completions"
-
 # Initialize conversation history
 conversation_history = []
 
 # Initialize Gradio client for new TTS API
 tts_client = Client("LeeSangHoon/HierSpeech_TTS")
 
+# Configure the Google Generative AI model
+genai.configure(api_key=API_KEY)
+
+generation_config = {
+    "temperature": 1,
+    "top_p": 0.95,
+    "top_k": 64,
+    "max_output_tokens": 8192,
+    "response_mime_type": "text/plain",
+}
+
+model = genai.GenerativeModel(
+    model_name="gemini-1.5-pro",
+    generation_config=generation_config,
+)
+
 def generate_response(user_input):
     global conversation_history
 
     # Add user message to conversation history
     conversation_history.append({"role": "user", "content": user_input})
 
-    # Send last 5 messages in conversation history to API
-    messages = conversation_history[-5:]
+    # Add system message to the beginning of the conversation history
+    conversation_history.insert(0, {"role": "system", "content": SYSTEM_CONTENT})
 
-    # Add system message to messages
-    messages.insert(0, {"role": "system", "content": SYSTEM_CONTENT})
-
-    headers = {
-        "Authorization": f"Bearer {API_KEY}",
-        "Content-Type": "application/json"
-    }
-
-    data = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages
-    }
-
-    response = requests.post(API_URL, headers=headers, json=data)
-    response.raise_for_status()  # Raise an error for bad status codes
+    # Create the chat session
+    chat_session = model.start_chat(
+        history=[
+            {"role": msg["role"], "content": msg["content"]} for msg in conversation_history
+        ]
+    )
 
-    response_text = response.json()['choices'][0]['message']['content']
+    # Send user input to the chat session
+    response = chat_session.send_message(user_input)
+    response_text = response.text
 
     # Add assistant response to conversation history
     conversation_history.append({"role": "assistant", "content": response_text})
@@ -57,8 +64,8 @@ def generate_response(user_input):
         file("audio.mp3"),  # Path to the local audio file
         0.333,  # ttv_temperature
         0.333,  # vc_temperature
-        1,  # duratuion_temperature
-        1,  # duratuion_length
+        1,  # duration_temperature
+        1,  # duration_length
         0,  # denoise_ratio
         0,  # random_seed
         api_name="/predict"
@@ -76,4 +83,4 @@ iface = gr.Interface(
     description="Contact me if you want another character/voice<br>WhatsApp me: +92-332-4399819<br> Email me: aheedsajid@gmail.com<br><b>Donate something to increase GPU power</b><br>[Click here to Donate](https://nowpayments.io/donation/aheed)"
 )
 
-iface.launch()
+iface.launch()