1.7 KiB

Raw Blame History

Structured Output Demo

A minimal demo application showing how to use PocketFlow to extract structured data from a resume using direct prompting and YAML formatting.

Features

Extracts structured data using prompt engineering
Validates output structure before processing

Run It

Make sure your OpenAI API key is set:
```
export OPENAI_API_KEY="your-api-key-here"
```
Alternatively, you can edit the utils.py file to include your API key directly.
Edit data.txt with the resume you want to parse (a sample resume is already included)

Install requirements and run the application:

pip install -r requirements.txt
python main.py

How It Works

flowchart LR
    parser[ResumeParserNode]

The Resume Parser application uses a single node that:

Takes resume text from the shared state (loaded from data.txt)
Sends the resume to an LLM with a prompt that requests YAML formatted output
Extracts and validates the structured YAML data
Outputs the structured result

Files

main.py: Implementation of the ResumeParserNode
utils.py: LLM utilities
data.txt: Sample resume text file

Example Output

=== STRUCTURED RESUME DATA ===

name: John Smith
email: johnsmtih1983@gnail.com
experience:
- title: Sales Manager
  company: ABC Corporation
- title: Assistant Manager
  company: XYZ Industries
- title: Customer Service Representative
  company: Fast Solutions Inc
skills:
- Microsoft Office: Excel, Word, PowerPoint (Advanced)
- Customer relationship management (CRM) software
- Team leadership & management
- Project management
- Public speaking
- Time management

============================

1.7 KiB Raw Blame History