Update app.py

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import os
 from huggingface_hub import InferenceClient
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
@@ -7,9 +8,30 @@ def format_prompt(agent_id, message):
     return f"<s><Agent {agent_id}>[INST] {message} [/INST]"
 
 def generate_response(agent_id, message):
-    formatted_prompt = format_prompt(agent_id, message)
-    response = client.text_generation(formatted_prompt, stream=False)
-    return response['generated_text']
+    api_url = "https://api-inference.huggingface.co/models/mistralai/mistral-tiny"  # Replace with your model path
+    headers = {
+        'Authorization': f'Bearer {os.getenv("HUGGINGFACE_API_KEY")}'
+    }
+    data = {
+        "inputs": {
+            "past_user_inputs": [],
+            "generated_responses": [],
+            "text": message
+        }
+    }
+
+    response = requests.post(api_url, headers=headers, json=data)
+    if response.status_code == 200:
+        response_data = response.json()  # Parse the JSON response into a dictionary
+        # Ensure that 'generated_text' is accessed from a dictionary
+        if isinstance(response_data, dict) and 'generated_text' in response_data:
+            return response_data['generated_text']
+        else:
+            # Handle unexpected response format
+            return "Received an unexpected response format from the API."
+    else:
+        return f"Error: {response.status_code}"
+
 
 def generate_group_therapy_responses(message):
     responses = []