Update app.py

app.py

@@ -9,33 +9,48 @@ from sklearn.naive_bayes import MultinomialNB
 import asyncio
 from crewai import Agent, Task, Crew
 from huggingface_hub import InferenceClient
+from langchain.tools import Tool
+from langchain.agents import Tool as LangChainTool
 import random
 import json
+import warnings
+from langchain.deprecation import LangChainDeprecationWarning
+
+# Suppress LangChain deprecation warnings
+warnings.filterwarnings("ignore", category=LangChainDeprecationWarning)
 
 # Set up logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
 
-# Function to get Hugging Face API token
 def get_huggingface_api_token():
     token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
-    if not token:
-        try:
-            with open('config.json', 'r') as config_file:
-                config = json.load(config_file)
-                token = config.get('HUGGINGFACEHUB_API_TOKEN')
-        except (FileNotFoundError, json.JSONDecodeError):
-            logger.warning("Config file not found or invalid. Please provide the Hugging Face API token.")
-    
-    if not token:
-        token = input("Please enter your Hugging Face API token: ")
-    
-    return token
+    if token:
+        logger.info("Hugging Face API token found in environment variables.")
+        return token
+
+    try:
+        with open('config.json', 'r') as config_file:
+            config = json.load(config_file)
+            token = config.get('HUGGINGFACEHUB_API_TOKEN')
+            if token:
+                logger.info("Hugging Face API token found in config.json file.")
+                return token
+    except FileNotFoundError:
+        logger.warning("Config file not found.")
+    except json.JSONDecodeError:
+        logger.error("Error reading the config file. Please check its format.")
+
+    logger.error("Hugging Face API token not found. Please set it up.")
+    return None
 
 # Initialize the Hugging Face Inference Client
 try:
     hf_token = get_huggingface_api_token()
+    if not hf_token:
+        raise ValueError("Hugging Face API token is not set. Please set it up before running the application.")
     client = InferenceClient(model="mistralai/Mistral-7B-Instruct-v0.2", token=hf_token)
+    logger.info("Hugging Face Inference Client initialized successfully.")
 except Exception as e:
     logger.error(f"Failed to initialize Hugging Face client: {e}")
     sys.exit(1)
@@ -106,6 +121,13 @@ def post_process_response(response):
     
     return response
 
+# Define the tool for CrewAI
+generate_response_tool = Tool(
+    name="GenerateResponse",
+    func=generate_response,
+    description="Generate a response using the Mistral model"
+)
+
 # CrewAI setup
 communication_expert_crew = Agent(
     role='Communication Expert',
@@ -113,7 +135,7 @@ communication_expert_crew = Agent(
     backstory="""You are an expert in communication, specializing in understanding and rephrasing queries to ensure they are interpreted in the most positive and constructive light. Your role is crucial in setting the tone for respectful and empathetic interactions.""",
     verbose=True,
     allow_delegation=False,
-    tools=[generate_response]
+    tools=[generate_response_tool]
 )
 
 response_expert_crew = Agent(
@@ -122,7 +144,7 @@ response_expert_crew = Agent(
     backstory="""You are an expert in Zerodha's services and policies, with a keen ability to provide comprehensive and empathetic responses. Your role is to ensure that all user queries are addressed accurately while maintaining a respectful and supportive tone.""",
     verbose=True,
     allow_delegation=False,
-    tools=[generate_response]
+    tools=[generate_response_tool]
 )
 
 # Main function