feat: HF and github integration
Browse files- .env.sample +1 -1
- .github/workflows/sync_with_hf.yml +33 -0
- Dockerfile +25 -0
- README.md +11 -0
- requirements.txt +0 -0
.env.sample
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@@ -5,7 +5,7 @@ DB_URL=
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DB_SCHEMA=
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# DB URL with root.crt for yugabyte
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# DB_URL="postgresql://username:password@
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GEMINI_API_KEY=
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GEMINI_MODEL=
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DB_SCHEMA=
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# DB URL with root.crt for yugabyte
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# DB_URL="postgresql://username:[email protected]:5433/yugabyte?sslmode=verify-full&sslrootcert=root.crt"
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GEMINI_API_KEY=
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GEMINI_MODEL=
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.github/workflows/sync_with_hf.yml
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name: Sync to Hugging Face Hub
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on:
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push:
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branches: [demo-tmp-memory] # ana branch'e push yapıldığında çalışacak
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jobs:
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sync-to-hub:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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lfs: true
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- name: Push to HF Space
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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HF_ORGANIZATION: ${{ vars.HF_ORGANIZATION }}
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HF_SPACE: ${{ vars.HF_SPACE }}
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run: |
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git config --global user.email "[email protected]"
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git config --global user.name "GitHub Actions"
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git remote add hf "https://api:[email protected]/spaces/$HF_ORGANIZATION/$HF_SPACE"
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git fetch hf
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git push hf main --force
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# - name: Restart Space
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# run: |
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# curl -X POST \
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# -H "Authorization: Bearer ${{ secrets.HF_TOKEN }}" \
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# https://huggingface.co/api/spaces/${{ vars.HF_ORGANIZATION }}/${{ vars.HF_SPACE }}/restart
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Dockerfile
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FROM python:3.11
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RUN useradd -m -u 1000 chameleon
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USER chameleon
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ENV PATH="/home/chameleon/.local/bin:$PATH"
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WORKDIR /app
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COPY --chown=chameleon requirements.txt requirements.txt
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RUN pip install --no-cache-dir --upgrade -r requirements.txt
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COPY --chown=chameleon . .
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# Hugging Face Space port
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ENV PORT=7860
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# Expose the port
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EXPOSE 7860
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# Start command for Hugging Face Space
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# CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
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CMD ["python", "gradio_app.py"]
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README.md
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@@ -1,3 +1,14 @@
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# Natural Language SQL Query Agent with Visualization
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A smart and interactive PostgreSQL query system that translates natural language requests into SQL queries, executes them, and generates visualizations using PandasAI. Built with modern technologies including LangChain, FastMCP, and Gradio.
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---
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title: Defect Solver API
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emoji: 🤯
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colorFrom: pink
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colorTo: yellow
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sdk: docker
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pinned: false
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short_description: Defect Solver - Bug Localization API
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---
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# Natural Language SQL Query Agent with Visualization
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A smart and interactive PostgreSQL query system that translates natural language requests into SQL queries, executes them, and generates visualizations using PandasAI. Built with modern technologies including LangChain, FastMCP, and Gradio.
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requirements.txt
CHANGED
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Binary files a/requirements.txt and b/requirements.txt differ
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