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43de248325
Improves the competitor reference analysis (Step 8) by replacing the previous LLM-only approach with a grounded, scraping-based method. - Implemented a new scraper to actively search for and parse competitor reference/case study pages. - The analysis is now based on actual website content, significantly increasing the accuracy and reliability of the results and preventing model hallucinations. - Updated documentation to reflect the new 'Grounded References' architecture.
33 lines
786 B
Docker
33 lines
786 B
Docker
# Stage 1: Build the React frontend
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FROM node:18-alpine AS build-stage
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WORKDIR /app
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# Copy package files and install dependencies
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COPY package*.json ./
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RUN npm install
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# Copy the rest of the frontend code and build
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COPY . .
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RUN npm run build
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# Stage 2: Python backend orchestrator
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FROM python:3.11-slim
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WORKDIR /app
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# Copy requirements and install
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy the build from the first stage
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COPY --from=build-stage /app/dist ./dist
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# Copy the orchestrator script and .env if needed (though env should be passed via docker-compose)
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# Expose the port the app runs on
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EXPOSE 8000
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# Command to run the orchestrator
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CMD ["uvicorn", "competitor_analysis_orchestrator:app", "--host", "0.0.0.0", "--port", "8000"]
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