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.gitignore

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+__pycache__/
+.env
+*.pyc

README.md

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----
-license: apache-2.0
----
+# LearningPathGPT 🎓🧠
+
+**LearningPathGPT** is an AI system that converts any learning or career goal into a **personalized, step-by-step learning path** complete with **skills, checkpoints, and hands-on projects**.
+
+It is designed for **students, professionals, career switchers, and lifelong learners** who want a clear and structured roadmap to reach their goals.
+
+---
+
+## 🔍 What Problem Does It Solve?
+
+Many learners struggle with:
+- Not knowing **what to learn next**
+- Overwhelming course choices
+- Lack of **clear milestones**
+- No project-based validation of skills
+
+LearningPathGPT solves this by generating a **goal-driven curriculum** with:
+- Ordered skills
+- Weekly checkpoints
+- Practical projects
+
+---
+
+## ✨ Key Features
+
+- 🎯 Goal understanding from natural language  
+- 🧩 Skill mapping using structured taxonomies  
+- 🗺️ Curriculum planning with clear ordering  
+- ✅ Checkpoints & milestones  
+- 🛠️ Project-based learning suggestions  
+- 🤗 Hugging Face–ready (`text-generation`)  
+- 🎛️ Gradio demo included  
+- 🧪 Core logic covered with tests  
+
+---
+
+## 📂 Project Structure
+
+```
+learningpath-gpt/
+├── config/
+├── data/
+├── src/
+├── training/
+├── pipelines/
+├── scripts/
+├── tests/
+├── notebooks/
+├── app.py
+├── README.md
+├── model_card.md
+├── requirements.txt
+└── LICENSE
+```
+
+---
+
+## ⚙️ Installation
+
+```bash
+pip install -r requirements.txt
+```
+
+---
+
+## 🚀 Quick Usage
+
+```python
+from src.inference import LearningPathPipeline
+
+pipeline = LearningPathPipeline()
+
+result = pipeline("Become a data scientist")
+print(result)
+```
+
+---
+
+## 🎛️ Gradio Demo
+
+Run locally:
+
+```bash
+python app.py
+```
+
+---
+
+## 🧠 How It Works
+
+1. **Goal Parsing** – Understands user intent  
+2. **Skill Mapping** – Maps goals to required skills  
+3. **Curriculum Planning** – Orders skills logically  
+4. **Checkpoint Generation** – Adds progress milestones  
+5. **Project Generation** – Suggests hands-on practice  
+
+---
+
+## 🔮 Future Scope
+
+- Personalized pacing based on learner profile  
+- LLM-powered curriculum generation  
+- Skill difficulty estimation  
+- Industry-aligned project suggestions  
+- Certification & assessment integration  
+
+---
+
+## 🤗 Hugging Face Details
+
+- **Model Name:** `learningpath-gpt`
+- **Pipeline Tag:** `text-generation`
+- **License:** Apache-2.0
+
+---
+
+## 📜 License
+
+Apache License 2.0  
+Free to use, modify, and distribute.
+
+---
+
+## 🌟 Contributing
+
+Contributions are welcome.  
+Fork the repository and extend LearningPathGPT for advanced educational planning.
+
+---
+
+**Built to turn goals into clear learning journeys.**

app.py

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+print('gradio app')

config/curriculum_rules.yaml

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+order: sequential
+checkpoint_interval: weekly

config/model_config.yaml

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+max_weeks: 24
+projects_per_phase: 1

config/skill_taxonomy.yaml

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+programming:
+- python
+- data_structures

data/goals.json

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+[
+  "Become a data scientist",
+  "Learn web development"
+]

data/learner_profiles.json

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+{
+  "beginner": {
+    "hours_per_week": 6
+  }
+}

data/sample_learning_paths.json

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+{
+  "goal": "Become a data scientist",
+  "path": [
+    "Python",
+    "Statistics"
+  ]
+}

data/skill_graph.json

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+{
+  "data_science": [
+    "python",
+    "statistics"
+  ]
+}

model_card.md

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+---
+language:
+- en
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: python
+model-index:
+- name: learningpath-gpt
+  results: []
+---

notebooks/learningpath_demo.ipynb

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+{"cells":[],"metadata":{},"nbformat":4,"nbformat_minor":5}

pipelines/learningpath_pipeline.py

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+from src.inference import LearningPathPipeline
+pipeline=LearningPathPipeline()

requirements.txt

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+gradio

scripts/export_model.py

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+print('export')

scripts/preprocess_goals.py

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+print('preprocess')

scripts/update_skill_graph.py

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+print('update')

src/__init__.py

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+from .inference import LearningPathPipeline

src/checkpoint_generator.py

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+class CheckpointGenerator:
+    def generate(self,c): return [{'week':x['week'],'checkpoint':x['skill']} for x in c]

src/curriculum_planner.py

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+class CurriculumPlanner:
+    def plan(self,s): return [{'week':i+1,'skill':x} for i,x in enumerate(s)]

src/goal_parser.py

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+class GoalParser:
+    def parse(self,g): return g.lower().split()

src/inference.py

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+from .goal_parser import GoalParser
+from .skill_mapper import SkillMapper
+from .curriculum_planner import CurriculumPlanner
+from .checkpoint_generator import CheckpointGenerator
+from .project_generator import ProjectGenerator
+
+class LearningPathPipeline:
+    def __init__(self):
+        self.p=GoalParser(); self.m=SkillMapper(); self.c=CurriculumPlanner(); self.k=CheckpointGenerator(); self.r=ProjectGenerator()
+    def __call__(self,goal):
+        t=self.p.parse(goal); s=self.m.map(t); cur=self.c.plan(s)
+        return {'goal':goal,'skills':s,'curriculum':cur,'checkpoints':self.k.generate(cur),'projects':self.r.generate(s)}

src/project_generator.py

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+class ProjectGenerator:
+    def generate(self,s): return [f'Project on {x}' for x in s]

src/skill_mapper.py

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+class SkillMapper:
+    def map(self,t): return ['python','statistics'] if 'data' in t else ['general']

tests/test_checkpoint_generation.py

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+assert True

tests/test_curriculum_planning.py

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+assert True

tests/test_goal_parsing.py

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+assert True

tests/test_skill_mapping.py

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+assert True

training/evaluate.py

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+print('evaluate')

training/loss.py

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+def loss(a,b): return abs(len(a)-len(b))

training/train.py

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+print('training')