Update app.py

app.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from crewai import Agent, Task, Crew, Process
-from langchain_groq import ChatGroq  # Import ChatGroq
+from langchain_google_genai import ChatGoogleGenerativeAI  # Import ChatGoogleGenerativeAI
 import os
 import fitz  # PyMuPDF for PDF handling
 import tempfile
@@ -38,11 +38,13 @@ def wrap_text(text, width=80):
 def create_crew(job_description, resume_text):
     """Creates the CrewAI crew with agents and tasks."""
 
-    # Groq LLM configuration using ChatGroq
-    llm = ChatGroq(
-        model_name="groq/llama-guard-3-8b",  # Use a Groq-supported model
-        api_key=os.environ.get("GROQ_API_KEY"),  # Use 'api_key' instead of 'groq_api_key'
+    # Gemini LLM configuration using ChatGoogleGenerativeAI
+    llm = ChatGoogleGenerativeAI(
+        model="gemini-1.5-flash-002",  # Specify the Gemini 1.5 Flash model
+        google_api_key=os.environ.get("GOOGLE_API_KEY"),  # Use GOOGLE_API_KEY
         temperature=0.7,
+        convert_system_message_to_human=True #Need this to work well with CrewAI
+
     )
 
     # 1. Resume Analyzer Agent
@@ -54,7 +56,7 @@ def create_crew(job_description, resume_text):
         identifying key skills, experiences, and formatting issues.""",
         verbose=True,
         allow_delegation=False,
-        llm=llm  # Use the ChatGroq instance
+        llm=llm
     )
 
     # 2. Job Description Analyzer Agent
@@ -95,7 +97,7 @@ def create_crew(job_description, resume_text):
         --------------
         """,
         agent=resume_analyzer,
-        expected_output="A structured report summarizing the resume's strengths, weaknesses, key skills, and areas for improvement." # Added expected_output
+        expected_output="A structured report summarizing the resume's strengths, weaknesses, key skills, and areas for improvement."
     )
 
     # Task 2: Analyze the Job Description
@@ -109,7 +111,7 @@ def create_crew(job_description, resume_text):
         --------------
         """,
         agent=job_analyzer,
-        expected_output="A structured summary of the job description, including key requirements, desired skills, qualifications, and important keywords." # Added expected_output
+        expected_output="A structured summary of the job description, including key requirements, desired skills, qualifications, and important keywords."
     )
 
     # Task 3: Suggest Improvements
@@ -125,15 +127,15 @@ def create_crew(job_description, resume_text):
         The job description analysis is: {task_analyze_job_description.output}
         """,
         agent=improvement_suggestor,
-        expected_output="A list of specific, actionable suggestions for improving the resume, covering content, keywords, formatting, and overall strategy, tailored to the job description." # Added expected_output
+        expected_output="A list of specific, actionable suggestions for improving the resume, covering content, keywords, formatting, and overall strategy, tailored to the job description."
     )
 
     # --- Crew ---
     crew = Crew(
         agents=[resume_analyzer, job_analyzer, improvement_suggestor],
         tasks=[task_analyze_resume, task_analyze_job_description, task_suggest_improvements],
-        verbose=True,  # You can set this to 1 or 2 for different levels of verbosity
-        process=Process.sequential  # Tasks are executed in the defined order
+        verbose=True,
+        process=Process.sequential
     )
 
     return crew
@@ -157,7 +159,7 @@ if st.button("Tailor Resume"):
                 crew = create_crew(job_description, resume_text)
                 result = crew.kickoff()
                 st.subheader("Suggested Improvements:")
-                st.write(wrap_text(result))  # Wrap the output for better readability
+                st.write(wrap_text(result))
             else:
                 st.error("Failed to read the resume content.")