Update app.py

app.py

@@ -15,7 +15,6 @@ import queue
 from langchain_openai import ChatOpenAI
 from typing import List, Dict, Optional
 from pydantic import BaseModel, Field, confloat
-from langchain_groq import ChatGroq  # Import Groq LLM
 
 class SkillScore(BaseModel):
     skill_name: str = Field(description="Name of the skill being scored")
@@ -232,7 +231,6 @@ class CompanyResearch(BaseModel):
     interview_questions: List[str] = Field(
         description="Strategic questions to ask during the interview"
     )
-llm = ChatGroq(model="groq/llama3-70b-8192", groq_api_key=groq_api_key)
 
 resume_analyzer = Agent(
                         role= "Resume Optimization Expert",
@@ -243,7 +241,6 @@ resume_analyzer = Agent(
                                 providing actionable suggestions for improvement. Your recommendations always
                                 focus on both human readability and ATS compatibility.""",
             verbose=True,
-            llm=llm,
             # knowledge_sources=[pdf_source],
         )
 job_analyzer = Agent(
@@ -256,7 +253,6 @@ job_analyzer = Agent(
                 and soft skills requirements, and can evaluate experience levels accurately.""",
             verbose=True,
             tools=[ScrapeWebsiteTool()],
-            llm=llm,
             # knowledge_sources=[pdf_source],
 )
 company_researcher = Agent(
@@ -269,7 +265,6 @@ company_researcher = Agent(
                 candidates for interviews. """,
             tools=[SerperDevTool()],
             verbose=True,
-            llm=llm,
             # knowledge_sources=[pdf_source],
 
         )
@@ -282,7 +277,6 @@ resume_writer = Agent (
                     beautifully formatted, ATS-friendly documents that maintain professionalism
                     while showcasing candidate strengths effectively.""",
                 verbose=True,
-                llm=llm,
         )
 report_generator = Agent(
                 role= "Career Report Generator and Markdown Specialist",
@@ -294,7 +288,6 @@ report_generator = Agent(
                     into clear, actionable insights with proper markdown formatting, emojis, and
                     visual elements that make information both appealing and easily digestible.""",
                 verbose=True,
-                llm=llm,
         )
 
 analyze_job_task = Task(
@@ -490,7 +483,7 @@ def run_crew(api_key: str, job_url: str, company_name: str, resume_pdf_path: str
     if not api_key:
         return "⚠️ Please provide a valid OpenAI API Key."
 
-    os.environ["GROQ_API_KEY"] = f"{api_key}"  # Set API key securely
+    os.environ["OPENAI_API_KEY"] = f"{api_key}"  # Set API key securely
 
     # Load PDF as knowledge source
     # pdf_source = resume_pdf_path
@@ -573,7 +566,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🤖 AI Resume Optimizer 🚀")
     gr.Markdown("Get Complete analysis of your resume")
 
-    api_key = gr.Textbox(label="🔑 Groq API Key", placeholder="Enter your Groq API Key securely")
+    api_key = gr.Textbox(label="🔑 Open AI API Key", placeholder="Enter your OpenAI API Key securely")
     job_url = gr.Textbox(label="🔗 Job URL", placeholder="Paste job listing URL here")
     company_name = gr.Textbox(label="🏢 Company Name", placeholder="Enter company name")
     resume_pdf = gr.File(label="📄 Upload Resume (PDF Only)")