Updated README to have appropriate tags and thumbnail also added

README.md

@@ -1,5 +1,5 @@
 ---
-title: interview-coach
+title: ai-interview-coach
 emoji: 🎙️
 colorFrom: purple
 colorTo: red
@@ -10,100 +10,107 @@ pinned: false
 python_version: '3.10'
 license: mit
 short_description: AI Interview Coach
+tags:
+- track:backyard
+- achievement:offgrid
+- achievement:offbrand
+- achievement:fieldnotes
+thumbnail: >-
+  https://cdn-uploads.huggingface.co/production/uploads/686f49a3a31e9a517952dd0c/HfuMUE233jLKwNgjefSmy.png
 ---
-
-# 🎙️ AI Interview Coach — Version Alpha
-
-An AI-powered interview preparation tool built with **Gradio** and **Mistral 7B** via the HuggingFace Inference API.
-
-> Built for the **HuggingFace Hackathon 2026** — Gradio on HF Spaces.
-
----
-
-## Features
-
-- 🔐 **Two-stage job description validation** — blocks spam and prompt injection
-- 🎚️ **3 interview modes** — Quick (3Q), Standard (5Q), Deep Dive (7Q)
-- 🤖 **Adaptive questions** — tailored to industry, role level, and detected keywords
-- 📊 **Keyword-aware scoring** — answers scored against job-specific expected terms
-- 🔑 **Keyword coverage badges** — see exactly which terms you hit and missed
-- 💡 **AI-generated Prep Sheet** — works for ANY industry (not just tech)
-- 📄 **Timestamped PDF report** — downloadable session summary
-- 🎨 **Premium dark UI** — glassmorphism, animated blobs, Inter font
-
----
-
-## Quick Start (Local)
-
-### 1. Clone and set up environment
-
-```bash
-cd HF_Hackathon
-python -m venv .venv
-.venv\Scripts\activate       # Windows
-# source .venv/bin/activate  # Mac/Linux
-pip install -r requirements.txt
-```
-
-### 2. Set your HuggingFace token
-
-```bash
-# Copy the example and fill in your token
-copy .env.example .env
-# Edit .env and replace hf_PASTE_YOUR_TOKEN_HERE with your actual token
-```
-
-Get a free token at: https://huggingface.co/settings/tokens  
-Required permission: **Inference** (read)
-
-### 3. Run
-
-```bash
-python interview_coach.py
-```
-
-Open http://localhost:7860
-
----
-
-## HuggingFace Spaces Deployment
-
-1. Push this repo to your HF Space (Gradio SDK)
-2. Go to **Settings → Secrets** and add `HF_TOKEN` = your token
-3. The app starts automatically — no other changes needed
-
----
-
-## Architecture
-
-```
-interview_coach.py   ← Gradio UI (pure layout + event wiring)
-engine.py            ← Orchestration (LLM client, session, PDF)
-config.py            ← All constants, CSS design system
-agents/
-  validator.py       ← 3-stage JD validation + profile extraction
-  question_gen.py    ← Adaptive question generation
-  scorer.py          ← Keyword-aware answer scoring (Agenda #4)
-```
-
----
-
-## Model
-
-- **Model:** `mistralai/Mistral-7B-Instruct-v0.3`
-- **Parameters:** 7B (within HF Hackathon ≤32B limit)
-- **Inference:** HuggingFace Serverless Inference API (free tier)
-- **Local fallback:** Ollama (`mistral:7b`) if no HF token is set
-
----
-
-## Scoring System
-
-| Score | Meaning |
-|-------|---------|
-| 8–10 | Excellent — strong STAR structure + good keyword coverage |
-| 5–7 | Good — missing key terms or depth |
-| 1–4 | Needs work — expand and use role-specific language |
-| NIL | Irrelevant response |
-
+
+# 🎙️ AI Interview Coach — Version Alpha
+
+An AI-powered interview preparation tool built with **Gradio** and **Mistral 7B** via the HuggingFace Inference API.
+
+> Built for the **HuggingFace Hackathon 2026** — Gradio on HF Spaces.
+
+---
+
+## Features
+
+- 🔐 **Two-stage job description validation** — blocks spam and prompt injection
+- 🎚️ **3 interview modes** — Quick (3Q), Standard (5Q), Deep Dive (7Q)
+- 🤖 **Adaptive questions** — tailored to industry, role level, and detected keywords
+- 📊 **Keyword-aware scoring** — answers scored against job-specific expected terms
+- 🔑 **Keyword coverage badges** — see exactly which terms you hit and missed
+- 💡 **AI-generated Prep Sheet** — works for ANY industry (not just tech)
+- 📄 **Timestamped PDF report** — downloadable session summary
+- 🎨 **Premium dark UI** — glassmorphism, animated blobs, Inter font
+
+---
+
+## Quick Start (Local)
+
+### 1. Clone and set up environment
+
+```bash
+cd HF_Hackathon
+python -m venv .venv
+.venv\Scripts\activate       # Windows
+# source .venv/bin/activate  # Mac/Linux
+pip install -r requirements.txt
+```
+
+### 2. Set your HuggingFace token
+
+```bash
+# Copy the example and fill in your token
+copy .env.example .env
+# Edit .env and replace hf_PASTE_YOUR_TOKEN_HERE with your actual token
+```
+
+Get a free token at: https://huggingface.co/settings/tokens  
+Required permission: **Inference** (read)
+
+### 3. Run
+
+```bash
+python interview_coach.py
+```
+
+Open http://localhost:7860
+
+---
+
+## HuggingFace Spaces Deployment
+
+1. Push this repo to your HF Space (Gradio SDK)
+2. Go to **Settings → Secrets** and add `HF_TOKEN` = your token
+3. The app starts automatically — no other changes needed
+
+---
+
+## Architecture
+
+```
+interview_coach.py   ← Gradio UI (pure layout + event wiring)
+engine.py            ← Orchestration (LLM client, session, PDF)
+config.py            ← All constants, CSS design system
+agents/
+  validator.py       ← 3-stage JD validation + profile extraction
+  question_gen.py    ← Adaptive question generation
+  scorer.py          ← Keyword-aware answer scoring (Agenda #4)
+```
+
+---
+
+## Model
+
+- **Model:** `mistralai/Mistral-7B-Instruct-v0.3`
+- **Parameters:** 7B (within HF Hackathon ≤32B limit)
+- **Inference:** HuggingFace Serverless Inference API (free tier)
+- **Local fallback:** Ollama (`mistral:7b`) if no HF token is set
+
+---
+
+## Scoring System
+
+| Score | Meaning |
+|-------|---------|
+| 8–10 | Excellent — strong STAR structure + good keyword coverage |
+| 5–7 | Good — missing key terms or depth |
+| 1–4 | Needs work — expand and use role-specific language |
+| NIL | Irrelevant response |
+
 **Keyword Coverage Rule:** < 40% of expected keywords → score capped at 5/10.