| --- |
| title: Pathshala AI |
| colorFrom: green |
| colorTo: blue |
| sdk: gradio |
| sdk_version: 4.44.1 |
| app_file: app.py |
| python_version: 3.11 |
| pinned: false |
| --- |
| |
| # Pathshala AI |
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| Pathshala AI is a bilingual AI tutor demo for rural primary students in Nepal. |
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| This Hugging Face Space supports: |
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| - Uploading a text-based PDF textbook directly in the Space |
| - Asking questions in English, Nepali, or romanized Nepali |
| - Retrieving relevant textbook portions from the uploaded PDF |
| - Showing a simple English answer and Nepali explanation |
| - Generating Nepali quiz questions |
| - Basic quiz grading |
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| For the full web-app workflow, deploy the FastAPI backend separately and add a Space variable named `BACKEND_URL`. |
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| Without `BACKEND_URL`, the Space can still run the same style of workflow locally. Add these Space secrets/variables to match the web app more closely: |
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| - `LLM_BASE_URL`, `LLM_API_KEY`, `LLM_MODEL` for the AMD/vLLM tutor |
| - `TRANSLATION_PROVIDER=gemini`, `GEMINI_API_KEY`, `GEMINI_MODEL` for Nepali adaptation and romanized question normalization |
| - `TRANSLATION_PROVIDER=openai`, `OPENAI_API_KEY`, `OPENAI_MODEL` if you want to use OpenAI for Nepali adaptation instead |
| - `OCR_PROVIDER=gemini`, `OCR_MAX_PAGES=5` for scanned or custom-font PDFs |
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| Use `LLM_MODEL=Qwen/Qwen2.5-7B-Instruct` to match the project default unless your vLLM endpoint exposes a different model name. |
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