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README.md
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# Self-Refining Resume Optimizer Agent
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An intelligent, multi-agent system built with **LangGraph**, **Llama 3**, and **Gradio** that autonomously refines resumes. Unlike standard tools, this agent scans for gaps, asks for human input, and iteratively critiques its own work until it hits a quality threshold.
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## Project Overview
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This project implements a sophisticated **Agentic Workflow** that mimics a professional writer/editor relationship. It goes beyond simple text generation by introducing state management
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### Key Features
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* **Gap Analysis:** Identifies exactly which skills (e.g., "SQL", "CI/CD") are missing from your profile.
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* **Human-in-the-Loop:** Pauses the workflow to ask you for context (e.g., *"You are missing SQL. Do you have this experience?"*) before writing.
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* **Self-Refinement:** A "Critic" node scores every draft (0-100). If the score is low, the "Writer" node must rewrite it.
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## Tech Stack
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* **Interface:** **Gradio** (Web UI for PDF uploads and interactive feedback).
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* **Data Processing:** `PyPDF` (Document Parsing) & `WebBaseLoader` (Scraping).
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* **Validation:** Pydantic (Structured Output).
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## How It Works (The Graph)
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| Node | Role | Behavior |
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| **Human Loop** | Manager | **Stops execution** to let the user add context/experience for the missing skills. |
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| **Improver** | Writer | Rephrases the resume using the user's notes. **Constraint:** Never hallucinates experience. |
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| **Reviewer** | Judge | Acts as a Hiring Manager. Returns a `Score` (0-100) and specific `Feedback`. |
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### The "Loop" Logic
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# Self-Refining Resume Optimizer Agent
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## Project Overview
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This project implements a sophisticated **Agentic Workflow** that mimics a professional writer/editor relationship. It goes beyond simple text generation by introducing state management, user feedback loops, and automated document formatting.
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### Key Features
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* **Gap Analysis:** Identifies exactly which skills (e.g., "SQL", "CI/CD") are missing from your profile.
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* **Human-in-the-Loop:** Pauses the workflow to ask you for context (e.g., *"You are missing SQL. Do you have this experience?"*) before writing.
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* **Self-Refinement:** A "Critic" node scores every draft (0-100). If the score is low, the "Writer" node must rewrite it.
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* **Professional Outputs:** Automatically generates a **tailored Cover Letter** and exports both documents as CSS-styled **PDFs**.
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## Tech Stack
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* **Interface:** **Gradio** (Web UI for PDF uploads and interactive feedback).
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* **Data Processing:** `PyPDF` (Document Parsing) & `WebBaseLoader` (Scraping).
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* **Validation:** Pydantic (Structured Output).
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* **Output Engine:** `markdown`& `xhtml2pdf` (Rendering CSS-styled documents).
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## How It Works (The Graph)
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The system is modeled as a State Graph with a specific multi-stage execution flow::
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| Node | Role | Behavior |
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|------|------|----------|
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| **Human Loop** | Manager | **Stops execution** to let the user add context/experience for the missing skills. |
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| **Improver** | Writer | Rephrases the resume using the user's notes. **Constraint:** Never hallucinates experience. |
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| **Reviewer** | Judge | Acts as a Hiring Manager. Returns a `Score` (0-100) and specific `Feedback`. |
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| **Cover Letter**| Author | Uses the finalized resume and job text to write a cohesive cover letter. |
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| **PDF Exporter**| Publisher| Renders the final Markdown text into professional PDFs with custom styling. |
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### The "Loop" Logic
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