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README.md

HR Manager Agentic-AI

Overview

The HR Manager API is a FastAPI-based application designed to analyze resumes, respond to HR-related queries, and provide insightful analyses of candidate qualifications. Leveraging advanced AI models and a PDF-based knowledge base, the API serves as a robust tool for Human Resources teams looking to streamline recruitment and resume review processes.

Features

  • Natural Language Query Handling: Processes user queries using OpenAI's advanced chat models.
  • Resume Knowledge Base: Uses a PDF-based knowledge base to store, search, and analyze resumes.
  • Skills Matching: Identifies individuals with specific skills or qualifications.
  • Session Management: Maintains agent interaction history in a PostgreSQL database for consistency.
  • Dynamic Instructions: Executes tasks based on detailed HR-centric instructions to ensure professional and actionable responses.
  • Chunked PDF Processing: Efficiently processes large documents by dividing them into manageable chunks for analysis.

API Endpoints

POST /ask

Submit a query to the HR Manager API.

Request Body

  • query (string, required): Your query or question related to resumes or HR tasks.

Response

  • On success: 
    {
  "response": "Answer to the query"
}
  • On error: 
    {
  "error": "Error message"
}

Dependencies

  • OpenAIChat: Powers the AI-driven query handling and response generation.
  • PDFKnowledgeBase: Stores and retrieves information from uploaded PDF documents.
  • PgVector: Facilitates vector-based search and retrieval within the knowledge base.
  • PgAgentStorage: Handles session storage in PostgreSQL.
  • PDFReader: Processes and parses resume PDFs into analyzable chunks.

Key Components

  • Knowledge Base: A PDF-based system for storing and retrieving resumes.
  • Agent: The core intelligence system that answers queries and analyzes resumes based on predefined instructions.
  • PostgreSQL Integration: Manages session data and historical interactions to enhance continuity in responses.
  • Dynamic Analysis: Tailors responses to the query context by extracting relevant information from stored resumes.

How It Works

  1. Query Handling:

    • Users submit queries through the /ask endpoint.
    • The agent processes the query using its knowledge base and instructions.

  2. Resume Analysis:

    • The knowledge base stores resumes in a vectorized format for efficient search and retrieval.
    • When a query is submitted, relevant resumes are analyzed for skills, experience, and qualifications.

  3. Session Management:

    • Maintains user sessions and interaction history to ensure continuity and accuracy in multi-step interactions.

Notes

  • Ensure the OpenAI API key is set in the environment (OPENAI_API_KEY).
  • Configure the PostgreSQL database correctly for both agent session storage and resume knowledge base storage.
  • Resumes should be uploaded as PDFs and will be processed in chunks to enable detailed analysis.
  • For running the knowledgebase like the example Pgvector you can run this command for docker: 
      docker run -d -e POSTGRES_DB=ai -e POSTGRES_USER=ai -e POSTGRES_PASSWORD=ai -e PGDATA=/var/lib/postgresql/data/pgdata -v pgvolume:/var/lib/postgresql/data -p 5532:5432 --name pgvector phidata/pgvector:16