Update app.py

app.py

@@ -1,50 +1,85 @@
 import os
-from openai import OpenAI
+import requests
 from dotenv import load_dotenv
+from typing import List, Dict
+import json
 
 # Load environment variables (e.g., API keys)
 load_dotenv()
 
-# Initialize the OpenAI client with Hugging Face API
-client = OpenAI(
-    base_url="https://api-inference.huggingface.co/v1",
-    api_key=os.getenv("TOKEN")
-)
-
-model = "meta-llama/Meta-Llama-3-8B-Instruct"
-
-def get_debyez_prompt_template(customer_message):
-    return f"""
-    Identity & Purpose
-    You are CSL Assistant, the official AI assistant for Cochin Shipyard Limited...
-    : '{customer_message}'
-    """
-
-# API or CLI that will interact with the model
-def get_response(prompt):
-    try:
-        messages = [{"role": "user", "content": prompt}]
-        stream = client.chat.completions.create(
-            model=model,
-            messages=[
-                {"role": m["role"], "content": get_debyez_prompt_template(m["content"])}
-                for m in messages
-            ],
-            temperature=0.5,
-            stream=True,
-            max_tokens=3000,
-        )
-        response = ""
-        for chunk in stream:
-            response += chunk.choices[0].delta.content or ""
-        if not response.strip():
-            response = "Sorry, I couldn't generate a response right now."
-        return response
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
-
-# Example execution
+class CSLAssistant:
+    def __init__(self):
+        self.api_token = os.getenv("TOKEN")
+        self.api_url = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
+        self.headers = {"Authorization": f"Bearer {self.api_token}"}
+
+    def get_system_prompt(self) -> str:
+        return """
+        Identity & Purpose:
+        You are CSL Assistant, the official AI assistant for Cochin Shipyard Limited.
+        You specialize in providing information about shipbuilding, marine engineering,
+        and Cochin Shipyard's capabilities and services.
+
+        Guidelines:
+        1. Provide accurate information about CSL's shipbuilding capabilities
+        2. Be professional and courteous in all interactions
+        3. If unsure about specific details, acknowledge limitations
+        4. Focus on publicly available information about CSL
+        """
+
+    def get_prompt_template(self, customer_message: str) -> str:
+        return f"{self.get_system_prompt()}\n\nCustomer Query: {customer_message}"
+
+    def get_response(self, prompt: str) -> str:
+        try:
+            # Prepare the payload
+            payload = {
+                "inputs": self.get_prompt_template(prompt),
+                "parameters": {
+                    "max_new_tokens": 3000,
+                    "temperature": 0.5,
+                    "return_full_text": False
+                }
+            }
+
+            # Make the API request
+            response = requests.post(
+                self.api_url,
+                headers=self.headers,
+                json=payload
+            )
+
+            # Check if the request was successful
+            response.raise_for_status()
+
+            # Parse the response
+            result = response.json()
+            
+            if isinstance(result, list) and len(result) > 0:
+                return result[0].get('generated_text', '').strip()
+            
+            return "Sorry, I couldn't generate a response right now."
+
+        except requests.exceptions.RequestException as e:
+            return f"API Request Error: {str(e)}"
+        except json.JSONDecodeError:
+            return "Error: Invalid response from the API"
+        except Exception as e:
+            return f"An unexpected error occurred: {str(e)}"
+
+def main():
+    assistant = CSLAssistant()
+    
+    # Example queries
+    test_queries = [
+        "What types of ships do you build?",
+        "What is your shipyard's capacity?",
+        "Tell me about your recent projects"
+    ]
+    
+    for query in test_queries:
+        print(f"\nQuery: {query}")
+        print("Response:", assistant.get_response(query))
+
 if __name__ == "__main__":
-    prompt = "What types of ships do you build?"
-    response = get_response(prompt)
-    print(response)
+    main()