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c484fda | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | # Smart Career Advisor Agent (OpenEnv)
A lightweight **OpenEnv-compatible smart agent** that provides career guidance based on user interests, with intelligent suggestions and random exploration tips.
---
## Features
* Intent-based career suggestions (AI, Web, Data, Design)
* Smart agent behavior with structured responses
* Random growth tips for exploration
* Stateless design (OpenEnv compliant)
* Ready for Hugging Face Spaces deployment
---
## Project Structure
```
smart_agent_openenv/
│
├── inference.py # OpenEnv entrypoint (REQUIRED)
├── app.py # Application controller
├── agents.py # Smart agent logic
├── requirements.txt # Dependencies
├── openenv.yaml # OpenEnv config (optional)
├── Dockerfile # HF deployment
└── README.md
```
---
## Requirements
* Python **3.10 / 3.11 / 3.12**
* pip
* Git
---
## Installation
```bash
pip install -r requirements.txt
```
---
## Local Testing
Since CLI may not work on all systems, test manually:
```bash
python test_openenv.py
```
Or create a quick test:
```python
from inference import predict, reset
print(predict({"query": "I like AI"}))
print(reset())
```
---
## OpenEnv Contract
This project follows required OpenEnv structure:
* `inference.py` at root
* `predict(input_data)` function
* `reset()` function
* Stateless execution
---
## Docker Deployment (Hugging Face)
Build runs automatically on HF Spaces using Dockerfile.
### Steps:
1. Push code to GitHub
2. Go to Hugging Face Spaces
3. Create new Space:
* SDK → **Docker**
4. Connect repo or upload files
5. Wait for build
---
## Usage Example
Input:
```json
{
"query": "I am interested in AI"
}
```
Output:
```json
{
"output": {
"intent": "ai",
"careers": ["AI Engineer", "ML Engineer", "Deep Learning Engineer"],
"tip": "Build real-world projects",
"message": "Based on your interest in ai, these careers fit you."
}
}
```
---
## Common Issues & Fixes
### `openenv not recognized`
Use:
```bash
python -m pip install openenv-core
```
---
### `reset post failed`
✔ Ensure `reset()` exists in `inference.py`
---
### `inference.py not detected`
✔ File must be in root directory
---
### Python version issues
✔ Use Python 3.10–3.12 (avoid 3.13)
---
## Submission Steps
1. Build project using OpenEnv structure
2. Test locally
3. Push to GitHub
4. Deploy on Hugging Face Spaces
5. Submit Space URL
---
## Future Improvements
* Multi-agent system (planner + executor)
* Memory-based reasoning (vector / graph)
* Integration with LLM APIs
* Real-world problem solving agents
---
## Author
**Junaid Khan**
AI Researcher & Developer
---
## License
Open-source project for educational and experimental use.
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