[DRAFT] vercel ai webshop example

contrib/recipes/webshop/.gitignore

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+node_modules/
+.venv/
+.next/
+dist/
+*.tsbuildinfo
+server/webshop/
+
+# Log files from make train
+logs/

contrib/recipes/webshop/Dockerfile

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+# Unified WebShop Training Image
+#
+# This Dockerfile creates a single image containing all components needed for
+# the WebShop training pipeline:
+#   - WebShop Flask server (Python + Java for pyserini)
+#   - Agent Lightning coordinator (Python + optional VERL for GPU)
+#   - Headless runner (Node.js + pnpm)
+#
+# Build context must be the repository root:
+#   docker build -f examples/vercel_ai_webshop/Dockerfile -t webshop-agl .
+#
+# For GPU training:
+#   docker build -f examples/vercel_ai_webshop/Dockerfile --build-arg INSTALL_GPU=true -t webshop-agl-gpu .
+#
+# Run modes:
+#   - Full stack: docker run webshop-agl scripts/run_stack.sh qwen
+#   - WebShop only: docker run webshop-agl python server/webshop_server.py
+#   - Runner only:  docker run webshop-agl pnpm headless
+
+# Base image with CUDA support for GPU training
+FROM mcr.microsoft.com/azureml/openmpi5.0-cuda12.4-ubuntu22.04:latest
+
+# Build argument for GPU support
+ARG INSTALL_GPU=false
+
+# Environment variables
+ENV PYTHONUNBUFFERED=1 \
+    DEBIAN_FRONTEND=noninteractive \
+    JAVA_HOME=/usr/lib/jvm/temurin-21-jdk-amd64 \
+    PATH="/usr/lib/jvm/temurin-21-jdk-amd64/bin:${PATH}"
+
+WORKDIR /app
+
+# ==============================================================================
+# System Dependencies
+# ==============================================================================
+
+# Install system packages:
+# - Java 21 (Temurin) for pyserini search engine
+# - Node.js 20 for headless runner
+# - Git, curl, wget for general utilities
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    git curl wget gnupg ca-certificates procps \
+    # Add Adoptium (Temurin) repository for Java 21
+    && mkdir -p /etc/apt/keyrings \
+    && wget -qO- https://packages.adoptium.net/artifactory/api/gpg/key/public | gpg --dearmor -o /etc/apt/keyrings/adoptium.gpg \
+    && echo "deb [signed-by=/etc/apt/keyrings/adoptium.gpg] https://packages.adoptium.net/artifactory/deb bookworm main" > /etc/apt/sources.list.d/adoptium.list \
+    # Add NodeSource repository for Node.js 20
+    && curl -fsSL https://deb.nodesource.com/setup_20.x | bash - \
+    && apt-get update \
+    && apt-get install -y --no-install-recommends \
+        temurin-21-jdk \
+        nodejs \
+    # Install pnpm globally
+    && npm install -g pnpm \
+    # Clean up
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# ==============================================================================
+# Python Dependencies
+# ==============================================================================
+
+# Copy Agent Lightning package files from repo root
+COPY pyproject.toml uv.lock README.md ./
+COPY agentlightning/ ./agentlightning/
+
+# Install Agent Lightning (with optional GPU extras)
+RUN pip install --no-cache-dir --upgrade pip wheel setuptools && \
+    if [ "$INSTALL_GPU" = "true" ]; then \
+        pip install --no-cache-dir -e ".[verl]" || pip install --no-cache-dir -e .; \
+    else \
+        pip install --no-cache-dir -e .; \
+    fi
+
+# Copy and install WebShop server requirements
+COPY examples/vercel_ai_webshop/server/requirements.txt ./server-requirements.txt
+RUN pip install --no-cache-dir -r server-requirements.txt && \
+    python -m spacy download en_core_web_sm
+
+# Copy and install AGL coordinator requirements
+COPY examples/vercel_ai_webshop/agl/requirements.txt ./agl-requirements.txt
+RUN pip install --no-cache-dir -r agl-requirements.txt
+
+# ==============================================================================
+# WebShop Setup
+# ==============================================================================
+
+# Clone WebShop repository
+RUN git clone --depth 1 https://github.com/princeton-nlp/WebShop.git /app/webshop
+
+# Install WebShop-specific dependencies
+RUN cd /app/webshop && \
+    pip install --no-cache-dir -r requirements.txt || \
+    pip install --no-cache-dir flask gym beautifulsoup4 rank_bm25 thefuzz numpy pandas tqdm
+
+ENV PYTHONPATH="/app/webshop:${PYTHONPATH}"
+
+# ==============================================================================
+# Node.js Dependencies
+# ==============================================================================
+
+# Copy package files and install dependencies
+COPY examples/vercel_ai_webshop/package.json examples/vercel_ai_webshop/pnpm-lock.yaml* ./
+RUN pnpm install --frozen-lockfile || pnpm install
+
+# ==============================================================================
+# Application Code
+# ==============================================================================
+
+# Copy example source code
+COPY examples/vercel_ai_webshop/tsconfig.json ./
+COPY examples/vercel_ai_webshop/src/ ./src/
+COPY examples/vercel_ai_webshop/scripts/ ./scripts/
+COPY examples/vercel_ai_webshop/agl/ ./agl/
+COPY examples/vercel_ai_webshop/server/webshop_server.py ./server/webshop_server.py
+COPY examples/vercel_ai_webshop/server/docker-entrypoint.sh ./server/docker-entrypoint.sh
+
+# Make scripts executable
+RUN chmod +x scripts/*.sh server/docker-entrypoint.sh
+
+# ==============================================================================
+# Runtime Configuration
+# ==============================================================================
+
+# Default environment variables
+ENV AGENT_LIGHTNING_STORE_HOST=0.0.0.0 \
+    AGENT_LIGHTNING_STORE_PORT=4747 \
+    WEBSHOP_URL=http://127.0.0.1:3000 \
+    N_RUNNERS=1
+
+# Expose ports
+# - 3000: WebShop server
+# - 4747: Agent Lightning Store
+EXPOSE 3000 4747
+
+# Volume for WebShop dataset persistence
+VOLUME /app/webshop/data
+
+# Health check for the Store server
+HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
+    CMD curl -f http://localhost:4747/v1/agl/health || exit 1
+
+# Default: run full stack with qwen config
+CMD ["bash", "scripts/run_stack.sh", "qwen"]

contrib/recipes/webshop/Makefile

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+# WebShop Training Workflow
+#
+# Usage:
+#   make setup       # Initialize .env
+#   make train       # Run training stack (GPU)
+#   make stop        # Stop all services
+#
+# Azure ML:
+#   make aml-setup   # One-time AML setup (compute + environment)
+#   make aml-train   # Submit training job to Azure ML
+#   make aml-logs    # Stream logs from running AML job
+
+.PHONY: help setup build build-gpu train scale stop clean status \
+        aml-setup aml-compute aml-train aml-train-qwen aml-logs aml-status
+
+N ?= 1
+
+# Azure ML defaults (override with environment variables)
+AML_RG ?= <your-resource-group>
+AML_WS ?= <your-workspace>
+
+.DEFAULT_GOAL := help
+
+#==============================================================================
+# Help
+#==============================================================================
+
+help: ## Show this help message
+	@echo "WebShop Agent - Commands"
+	@echo "------------------------"
+	@echo ""
+	@echo "Setup:"
+	@echo "  make setup       Create .env configuration"
+	@echo "  make build-gpu   Build GPU Docker image"
+	@echo ""
+	@echo "Run:"
+	@echo "  make train       Start Training Stack (single container, GPU)"
+	@echo "  make scale N=3   Set number of runners (default: 1)"
+	@echo ""
+	@echo "Manage:"
+	@echo "  make status      Show container status"
+	@echo "  make stop        Stop all services"
+	@echo "  make clean       Stop and remove volumes"
+	@echo ""
+	@echo "Azure ML:"
+	@echo "  make aml-train       Submit Qwen training job"
+	@echo "  make aml-compute     Create AML compute cluster"
+	@echo ""
+#==============================================================================
+# Setup
+#==============================================================================
+
+setup: ## Create .env configuration
+	@if [ ! -f .env ]; then \
+		cp .env.example .env; \
+		echo "Created .env from .env.example"; \
+		echo "Please edit .env and add your OPENAI_API_KEY"; \
+	else \
+		echo ".env already exists"; \
+	fi
+
+build-gpu: ## Build GPU Docker image
+	@echo "Building WebShop GPU image..."
+	docker build -f Dockerfile --build-arg INSTALL_GPU=true -t webshop-agl-gpu ../..
+	@echo "Build complete."
+
+#==============================================================================
+# Run
+#==============================================================================
+
+train: setup ## Start Training Stack (GPU)
+	@echo "Starting Training Stack (GPU)..."
+	@echo "  - WebShop:     http://localhost:3000"
+	@echo "  - Coordinator: http://localhost:4747"
+	@echo ""
+	N_RUNNERS=$(N) docker compose --profile gpu up --build -d
+
+scale: ## Set number of runners (e.g., make scale N=3)
+	@echo "To change runner count, stop and restart with N=$(N):"
+	@echo "  make stop && N=$(N) make train"
+	@echo ""
+	@echo "Or set N_RUNNERS=$(N) in your .env file"
+
+#==============================================================================
+# Azure ML
+#==============================================================================
+
+aml-compute: ## Create Azure ML compute cluster
+	@echo "Creating Azure ML compute cluster..."
+	az ml compute create -f aml/compute.yml -g $(AML_RG) -w $(AML_WS) || \
+		echo "Compute cluster may already exist (this is OK)"
+
+
+aml-train: ## Submit Qwen training job
+	@echo "Submitting Qwen training job to Azure ML..."
+	@echo "Note: Requires HF_TOKEN and WANDB_API_KEY environment variables"
+	az ml job create -f aml/jobs/webshop-qwen.yml --stream \
+		--set environment_variables.HF_TOKEN="$$HF_TOKEN" \
+		--set environment_variables.WANDB_API_KEY="$$WANDB_API_KEY" \
+		-g $(AML_RG) -w $(AML_WS)