Started work on job call context extraction

configuration.py

@@ -17,4 +17,22 @@ You will receive structured text extracted from a LinkedIn profile PDF and GitHu
 - Education
 
 Format the resume using Markdown syntax, ensuring that it is easy to read and visually appealing. Use appropriate headings, bullet points, and formatting to enhance clarity and presentation.
+"""
+
+JOB_CALL_EXTRACTION_PROMPT = """
+The following text is a job description from a LinkedIn job call. Please summarize and format it so that it can be used as context for an AI agent to use when writing a resume that is tailored to this specific job.
+Format your output as a JSON string as follows:
+{
+    'Job title': 'Name of position',
+    'Job description': 'Summary job description and company',
+    'Key skills': 'List of skills from job post',
+    'Tools/technologies': 'List of any tools or technologies mentioned in the job post',
+    'Experience level': 'Description of the experience level required for the job (e.g., entry-level, mid-level, senior)',
+    'Education requirements': 'Description of the education requirements for the job (e.g., degree, certifications)',
+}
+
+Here is the the job call to extract the information from
+
+JOB CALL
+
 """

functions/gradio.py

@@ -7,6 +7,7 @@ Functions for handling Gradio UI interactions and processing user inputs.
 import logging
 from functions.linkedin_resume import extract_text_from_linkedin_pdf
 from functions.github import get_github_repositories
+from functions.job_call import summarize_job_call
 from functions.writer_agent import write_resume
 
 # Set up logging
@@ -76,6 +77,9 @@ def process_inputs(linkedin_pdf, github_url, job_post_text, user_instructions):
     if job_post_text and job_post_text.strip():
         result += "✅ Job post text provided\n"
         logger.info(f"Job post text provided ({len(job_post_text)} characters)")
+        summary = summarize_job_call(job_post_text)
+        result += "  ✅ Job post summary generated\n"
+        result += summary
     else:
         result += "❌ Job post not provided\n"
         logger.info("No job post text provided")

functions/job_call.py

@@ -0,0 +1,54 @@
+'''Functions for summarizing and formatting job calls.'''
+
+import os
+from openai import OpenAI
+from configuration import JOB_CALL_EXTRACTION_PROMPT
+
+def summarize_job_call(job_call: dict) -> str:
+    '''Extracts and summarizes key information from job call.'''
+
+        client = OpenAI(api_key=os.environ['MODAL_API_KEY'])
+
+    client.base_url = (
+        'https://gperdrizet--vllm-openai-compatible-summarization-serve.modal.run/v1'
+    )
+
+    # Default to first available model
+    model = client.models.list().data[0]
+    model_id = model.id
+
+    messages = [
+        {
+            'role': 'system',
+            'content': f'{JOB_CALL_EXTRACTION_PROMPT}{content}'
+        }
+    ]
+
+    completion_args = {
+        'model': model_id,
+        'messages': messages,
+        # "frequency_penalty": args.frequency_penalty,
+        # "max_tokens": 128,
+        # "n": args.n,
+        # "presence_penalty": args.presence_penalty,
+        # "seed": args.seed,
+        # "stop": args.stop,
+        # "stream": args.stream,
+        # "temperature": args.temperature,
+        # "top_p": args.top_p,
+    }
+
+    try:
+        response = client.chat.completions.create(**completion_args)
+
+    except Exception as e: # pylint: disable=broad-exception-caught
+        response = None
+        logger.error('Error during Modal API call: %s', e)
+
+    if response is not None:
+        summary = response.choices[0].message.content
+
+    else:
+        summary = None
+
+    return summary