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---
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title: GenAI Career Agent
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emoji: 💬
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colorFrom: yellow
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colorTo: purple
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sdk: gradio
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sdk_version: 5.42.0
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app_file: app.py
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pinned: false
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hf_oauth: true
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hf_oauth_scopes:
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- inference-api
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short_description: A generative AI model that acts as a career coach
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---
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A Resume–Job Fit Analysis chatbot built using **Gradio**, **FAISS Vector Search**, and the **Hugging Face Inference API**.
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This Space hosts the **GenAI Career Agent**, a generative AI that analyzes user resumes, retrieves structured resume data through a vectorstore (FAISS), and evaluates how well a candidate fits any provided job description.
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### 🚀 Features
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- **AI Career Coach** – Helps users understand job fit, strengths, and areas for improvement.
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- **RAG Pipeline** – Uses FAISS to retrieve relevant resume chunks.
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- **LLM-Powered Analysis** – Uses a remote Hugging Face model via `InferenceClient`.
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- **Structured JSON Output** including:
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- `job_fit_score`
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- `fit_summary`
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- `strengths`
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- `missing_skills`
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- `recommendations`
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- **Secure Token Handling** with Hugging Face Space Secrets.
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### 📌 Current Capability
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✔ **Resume Parsing & Analysis**
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The system currently parses the user's resume (pre-embedded with MiniLM) and produces job-fit analytics using RAG + LLM inference.
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### 🛠️ Upcoming Features
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🔜 **GitHub Repo Intelligence**
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- Automatic retrieval of repositories
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- Summarization of project impact
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- Extraction of tech stack & coding patterns
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- Integration into the job-fit score
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🔜 **LinkedIn Profile Integration**
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- Work history extraction
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- Skill inference
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- Keyword alignment
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- Soft-skill assessment
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These features will be integrated into the same RAG pipeline so the model can reason across **Resume + GitHub + LinkedIn** for a unified career profile.
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### 🧠 How It Works
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1. Resume data is pre-embedded using
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`sentence-transformers/all-MiniLM-L6-v2`.
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2. Embeddings are stored inside
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`data/vectorstores/`.
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3. The FAISS retriever fetches the most relevant resume sections based on the job description.
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4. A custom prompt formats the retrieved text and sends it to the LLM.
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5. The LLM generates structured JSON insights.
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### 🗂️ Tech Stack
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- **Gradio 5** (ChatInterface front-end)
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- **LangChain Runnables**
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- **FAISS** Vector Search
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- **HuggingFace Embeddings**
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- **Hugging Face Inference API**
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### 🔒 Token Handling
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Set secrets in your Space
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### 📜 Model Licensing & Notices
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🧍 Personal / Educational Use
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This is a personal project, intended solely for educational and career-analysis purposes.
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Users are solely responsible for how they use the outputs. |
