Update app.py

app.py

@@ -1,57 +1,70 @@
-import os
-from flask import Flask, render_template, request, jsonify
 import requests
-import time
+import os
 from dotenv import load_dotenv
+import time
 
 load_dotenv()  # Load environment variables from .env file
 
-app = Flask(__name__)
-
-class APIInferenceChatbot:
-    def __init__(self, api_token):
-        self.api_url = "https://api-inference.huggingface.co/models/Ouiam123/Llama-2-7b-chat-finetune-tourism"
-        self.headers = {
-            "Authorization": f"Bearer {api_token}",
-            "Content-Type": "application/json"
-        }
-
-    def generate_response(self, input_text):
-        formatted_prompt = f"<s>[INST] {input_text} [/INST>"
-        payload = {
-            "inputs": formatted_prompt,
-            "parameters": {
-                "max_new_tokens": 500,
-                "temperature": 0.7,
-                "top_p": 0.95,
-                "repetition_penalty": 1.15
-            }
-        }
-        response = requests.post(self.api_url, headers=self.headers, json=payload, timeout=30)
-        if response.status_code == 503:
-            time.sleep(20)
-            response = requests.post(self.api_url, headers=self.headers, json=payload)
-        response.raise_for_status()
-        result = response.json()
-        return result[0].get('generated_text', '').strip() if isinstance(result, list) and result else str(result)
-
-# Get the API token from the environment variable
-api_token = os.getenv("tok_read")
-if not api_token:
-    raise ValueError("Hugging Face API token not found in environment variables!")
-
-# Initialize the chatbot with the API token from the environment
-chatbot = APIInferenceChatbot(api_token)
-
-@app.route('/')
-def home():
-    return render_template('index.html')  # Serve the HTML file
-
-@app.route('/chat', methods=['POST'])
-def chat():
-    message = request.json.get('message', '')
-    response = chatbot.generate_response(message)
-    return jsonify({'response': response})  # Return the response as JSON
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860, debug=True)
+# Ensure the Hugging Face API token is set in your environment
+api_token = os.getenv("HF_API_TOKEN")
+
+# Check if the token is available
+if api_token is None:
+    print("API token is not set. Please set the 'HF_API_TOKEN' environment variable.")
+    exit(1)
+
+# Set the authorization header with the token
+headers = {
+    "Authorization": f"Bearer {api_token}",
+    "Content-Type": "application/json"
+}
+
+# URL for the Hugging Face model inference
+model_url = "https://api-inference.huggingface.co/models/Ouiam123/Llama-2-7b-chat-finetune-tourism"
+
+# Input text you want to send to the model (match the first code's formatting)
+input_text = "What should I do if I get lost in Morocco?"
+formatted_prompt = f"<s>[INST] {input_text} [/INST>"
+
+# Request payload
+payload = {
+    "inputs": formatted_prompt,
+    "parameters": {
+        "max_new_tokens": 500,
+        "temperature": 0.7,
+        "top_p": 0.95,
+        "repetition_penalty": 1.15
+    }
+}
+
+# Function to make the API request with retry on failure
+def get_model_response():
+    try:
+        response = requests.post(
+            model_url,
+            headers=headers,
+            json=payload,
+            timeout=30
+        )
+
+        if response.status_code == 200:
+            return response.json()  # Return the response if successful
+        elif response.status_code == 503:  # Retry on service unavailable (503)
+            print("Service unavailable, retrying...")
+            time.sleep(20)  # Wait before retrying
+            return get_model_response()  # Recursive retry
+        else:
+            print(f"Error {response.status_code}: {response.text}")
+            return None  # Return None in case of error
+    except requests.exceptions.RequestException as e:
+        print(f"Request error: {e}")
+        return None  # Handle request exceptions
+
+# Get the model response
+model_response = get_model_response()
+
+# Output the result
+if model_response:
+    print("Response:", model_response)  # Print the model's response
+else:
+    print("Failed to get a valid response from the model.")