Update app.py

app.py

@@ -7,11 +7,12 @@ import numpy as np
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.naive_bayes import MultinomialNB
 import asyncio
-from crewai import Agent, Task, Crew
+from crewai import Agent
 from huggingface_hub import InferenceClient
 import random
 import json
 import warnings
+from pydantic import Field
 
 # Suppress all deprecation warnings
 warnings.filterwarnings("ignore", category=DeprecationWarning)
@@ -53,9 +54,9 @@ classifier = MultinomialNB()
 classifier.fit(X, np.arange(len(approved_topics)))
 
 class CommunicationExpertAgent(Agent):
-    role = "Communication Expert"
-    goal = "To interpret and rephrase user queries with empathy and respect"
-    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."""
+    role: str = Field(default="Communication Expert", const=True)
+    goal: str = Field(default="To interpret and rephrase user queries with empathy and respect", const=True)
+    backstory: str = Field(default="""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.""", const=True)
 
     async def run(self, query):
         sanitized_query = re.sub(r'[<>&\']', '', query)
@@ -67,9 +68,9 @@ class CommunicationExpertAgent(Agent):
         return rephrased_query
 
 class ResponseExpertAgent(Agent):
-    role = "Response Expert"
-    goal = "To provide accurate, helpful, and emotionally intelligent responses to user queries"
-    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."""
+    role: str = Field(default="Response Expert", const=True)
+    goal: str = Field(default="To provide accurate, helpful, and emotionally intelligent responses to user queries", const=True)
+    backstory: str = Field(default="""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.""", const=True)
 
     async def run(self, rephrased_query):
         response = await hf_client.text_generation(rephrased_query, max_new_tokens=500, temperature=0.7)