| # Hugging Face Spaces Deployment |
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| This project is prepared for deployment as a Hugging Face Docker Space. |
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| ## 1. Login Locally |
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| Run: |
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| ```powershell |
| .\.venv\Scripts\hf.exe auth login |
| ``` |
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| Use a Hugging Face token with write access. |
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| ## 2. Upload Model Artifacts |
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| Create two Hugging Face model repositories: |
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| ```text |
| your_username/mental-health-language-detector |
| your_username/mental-health-emotion-detector |
| ``` |
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| Upload: |
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| - `src/models/saved_lang_model.pkl` to the language model repository. |
| - All files inside `src/models/saved_emotion_model/` to the emotion model repository. |
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| The emotion model folder should contain: |
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| ```text |
| config.json |
| model.safetensors |
| tokenizer.json |
| tokenizer_config.json |
| ``` |
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| ## 3. Create The Space |
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| Create a Hugging Face Space: |
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| ```text |
| SDK: Docker |
| Visibility: Public or Private |
| App port: 7860 |
| ``` |
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| ## 4. Add Space Secrets |
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| In the Space settings, add: |
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| ```text |
| GROQ_API_KEY |
| QDRANT_URL |
| QDRANT_API_KEY |
| QDRANT_COLLECTION |
| LANGUAGE_MODEL_REPO_ID |
| LANGUAGE_MODEL_FILENAME |
| EMOTION_MODEL_ID |
| ``` |
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| Recommended values: |
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| ```text |
| LANGUAGE_MODEL_FILENAME=saved_lang_model.pkl |
| QDRANT_COLLECTION=mental_health_rag |
| EMBEDDING_MODEL_NAME=intfloat/multilingual-e5-base |
| EMBEDDING_BATCH_SIZE=2 |
| TORCH_NUM_THREADS=1 |
| ``` |
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| ## 5. Push To The Space Repo |
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| After the Space is created, add it as a Git remote: |
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| ```powershell |
| git remote add space https://huggingface.co/spaces/your_username/your_space_name |
| git push space main |
| ``` |
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| The Dockerfile starts the production app with: |
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| ```text |
| uvicorn src.api_app:app --host 0.0.0.0 --port 7860 |
| ``` |
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| Open the Space URL after the build finishes. |
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