step 2 is working

test-job-app.py

@@ -3,16 +3,17 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
 # Load the SmolLM model and tokenizer
-model_name = "HuggingFaceTB/SmolLM2-135M-Instruct" # "HuggingFaceTB/SmolLM2-360m-Instruct"
+# model_name = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
+model_name = "HuggingFaceTB/SmolLM2-360M-Instruct"
 model = AutoModelForCausalLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
-def smol_lm_process(job_description):
-    # System Prompt: "Extract key qualifications, skills, and requirements from this job description. Output as bullet points. Remove benefits/salary fluff."
+def smol_lm_process(job_description, system_prompt):
+    # System Prompt and job description
     prompt = f"""<|im_start|>system
-Extract key qualifications, skills, and requirements from this job description. Output as bullet points. Remove benefits/salary fluff.<|im_end|>
+{system_prompt}<|im_end|>
 <|im_start|>user
 {job_description}<|im_end|>
 <|im_start|>assistant
@@ -27,12 +28,20 @@ Extract key qualifications, skills, and requirements from this job description.
     return response
 
 def process_job_description(company_name, company_url, job_description):
-    role_requirements = smol_lm_process(job_description)
+    # Step 2: Extract key qualifications, skills, and requirements
+    system_prompt_requirements = "Extract key qualifications, skills, and requirements from this job description. Output as bullet points. Remove benefits/salary and fluff. ONLY INCLUDE INFORMATION THAT TELLS THE USER WHAT SKILLS THE EMPLOYER SEEKS."
+    role_requirements = smol_lm_process(job_description, system_prompt_requirements)
+
+    # Step 3: Create a concise summary of the job description
+    system_prompt_summary = "Create a concise 150-200 word summary of this job description. Remove company bragging and benefits information. FOCUS ON ASPECTS THAT POINT THE USER IN WHAT THE EMPLOYER WANTS FROM A CANDIDATE IN TERMS OF SKILLS, ACCOMPLISHMENTS, AND SUCH"
+    clean_job_description = smol_lm_process(job_description, system_prompt_summary)
+
     return {
         "Company Name": company_name,
         "Company URL": company_url,
-        "Job Description": job_description,
-        "Role Requirements": role_requirements
+        "Original Job Description": job_description,
+        "Role Requirements": role_requirements,
+        "Clean Job Description": clean_job_description
     }
 
 # Create the Gradio app
@@ -52,4 +61,3 @@ with demo:
 
 if __name__ == "__main__":
     demo.launch()
-