Update app.py

app.py

@@ -60,8 +60,11 @@ class AutonomousEmailAgent:
         print("Autonomous Reasoning: Letting the LLM fully reason and act on available data...")
         
         reasoning_prompt = f"""
-        You are an autonomous agent responsible for generating a job application email.
-        
+        You are an AI agent tasked with generating a job application email using Simon Sinek's Start with Why model. 
+        The email must begin with why the candidate is passionate about the role, then explain how their skills and 
+        experience align with the company and role, and finally describe specific achievements that demonstrate their 
+        capabilities.
+
         Here’s the current data:
         - LinkedIn profile: {self.linkedin_url}
         - Company Name: {self.company_name}
@@ -70,11 +73,7 @@ class AutonomousEmailAgent:
         - Candidate's Skills: {', '.join(self.skills)}
         - Candidate's Experiences: {', '.join([exp['title'] for exp in self.experiences])}
 
-        Based on this data, decide if it is sufficient to generate the email. If some information is missing or insufficient, respond with:
-        1. "generate_email" to proceed with the email generation using available data.
-        2. "fallback" to use default values.
-
-        After generating the email, reflect on whether the content aligns with the role and company and whether any improvements are needed. Respond clearly with one of the above options.
+        Generate the email using this structure and make it compelling and tailored to the company and role.
         """
         
         return self.send_request_to_llm(reasoning_prompt)
@@ -106,7 +105,7 @@ class AutonomousEmailAgent:
                 if choices and "message" in choices[0]:
                     content = choices[0]["message"]["content"]
                     print(f"Content: {content}")
-                    return self.act_on_llm_instructions(content)
+                    return self.generate_email(content)
                 else:
                     print("Error: Unrecognized format in LLM response.")
                     return "Error: Unrecognized response format."
@@ -117,33 +116,11 @@ class AutonomousEmailAgent:
             print(f"Error: Unable to connect to Groq Cloud LLM. Status Code: {response.status_code}")
             return "Error: Unable to generate response."
 
-    # Function to act on the LLM's structured instructions
-    def act_on_llm_instructions(self, reasoning_output):
-        print(f"LLM Instruction: {reasoning_output}")
-        instruction = reasoning_output.lower().strip()
-
-        if "generate_email" in instruction:
-            return self.generate_email()
-
-        elif "fallback" in instruction:
-            print("Action: Using fallback values for missing data.")
-            return self.generate_email()
-
-        else:
-            print("Error: Unrecognized instruction from LLM. Proceeding with available data.")
-            return self.generate_email()
-
-    # Generate email based on the collected data
-    def generate_email(self):
-        print("Generating email based on the provided and/or fallback data...")
+    # Generate email based on the structured response
+    def generate_email(self, llm_response):
+        print("Generating email based on the structured response...")
         email_content = f"""
-        Subject: Application for {self.role} at {self.company_name}
-        
-        Dear Hiring Manager,
-
-        I am excited to apply for the {self.role} role at {self.company_name}. With a strong background in {self.bio}, I believe my skills in {', '.join(self.skills)} would make me a valuable addition to your team.
-
-        Please find my LinkedIn profile for more details: {self.linkedin}
+        {llm_response}
 
         Best regards,
         {self.user_name}