e5da4b21b0
Drawbar's compose doesn't have a rerank service today — the llama-rerank container I spun up earlier was a standalone docker run, not a compose service. For Docker DNS resolution (http://llama-rerank:8080) to work between MCP + reranker, both need to be siblings in the same compose stack. Added the llama-rerank service entry with: - :server-cuda image (CUDA-built llama.cpp; the plain :server is CPU-only and 25× slower for our 50-doc rerank pool) - -ngl 99 to offload all layers to GPU - deploy.resources.reservations.devices block for compose v3 GPU passthrough (preferred over the older `runtime: nvidia` syntax) - volume for the HuggingFace model cache so first-start GGUF download survives container recreates - no host port mapping — internal-network-only Tesla P4 compatibility notes inline: Pascal (CC 6.1) is in the :server-cuda image's compute-arch list (500-1200) so no special handling beyond the standard compose entry. Also: cleanup instruction to docker rm -f the standalone llama-rerank from the earlier setup before bringing up compose (name collision). And: noted that if trashpanda's existing Ollama is a host-mode process rather than a compose service, the MCP needs host.docker.internal override (snippet included). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
149 lines
4.8 KiB
Markdown
149 lines
4.8 KiB
Markdown
# Drawbar deploy — `crop-chem-docs` MCP server snippet
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Drop these two services into Drawbar's `docker-compose.yml`. Targets
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the trashpanda stack: shared Docker network with the existing
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Drawbar services + the Cloudflare Tunnel.
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## Pre-reqs (one-time on the deploy host)
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1. **Docker login to the Gitea registry:**
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```bash
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docker login git.jpaul.io -u justin # PAT for password
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```
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2. **NVIDIA Container Toolkit** — already installed on trashpanda
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(the existing standalone `llama-rerank` container ran with
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`--gpus all` fine).
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3. **If a standalone `llama-rerank` container is already running**
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(left over from earlier setup), remove it so the compose service
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can bind the same name:
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```bash
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docker rm -f llama-rerank
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```
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## Compose services
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```yaml
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services:
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# ---- Reranker sidecar -----------------------------------------
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# jina-reranker-v2-base-multilingual via llama.cpp on the Tesla P4.
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# Internal port only (no host port mapping needed — the MCP reaches
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# it via Docker DNS). ~280 MB GPU VRAM at idle, ~500 MB during a
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# 50-doc rerank. Co-exists fine with any other GPU users on the P4.
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llama-rerank:
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image: ghcr.io/ggml-org/llama.cpp:server-cuda
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container_name: llama-rerank
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restart: unless-stopped
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command:
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- "-hf"
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- "gpustack/jina-reranker-v2-base-multilingual-GGUF:Q8_0"
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- "--reranking"
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- "--host"
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- "0.0.0.0"
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- "--port"
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- "8080"
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- "-ngl"
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- "99" # offload all layers to GPU
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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# Model cache survives container recreates; first start downloads
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# the GGUF (~280 MB) from HuggingFace.
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volumes:
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- llama-rerank-cache:/root/.cache/huggingface
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networks:
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- default
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# ---- MCP server ------------------------------------------------
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crop-chem-docs:
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image: git.jpaul.io/justin/crop-chem-docs:corpus-2026.05.24
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# :latest for dev / Watchtower auto-pull
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container_name: crop-chem-docs
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restart: unless-stopped
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ports:
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- "8001:8000" # MCP server (streamable-http). Adjust host port.
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# No environment block needed — the image's defaults handle it:
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# OLLAMA_URL=http://ollama:11434
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# RERANK_URL=http://llama-rerank:8080
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# HYBRID_SEARCH=true
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# PRODUCT_NAME=crop_chem
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# Override here only if your services have different names.
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depends_on:
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- llama-rerank
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networks:
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- default
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labels:
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com.centurylinklabs.watchtower.enable: "true"
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volumes:
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llama-rerank-cache:
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```
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## Note on the existing `ollama` service
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The Dockerfile default is `OLLAMA_URL=http://ollama:11434` — that
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assumes there's an `ollama` service in the same compose stack. If
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trashpanda's Ollama is a host-mode process (not a compose service),
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override the env in the `crop-chem-docs` block:
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```yaml
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environment:
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OLLAMA_URL: "http://host.docker.internal:11434"
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extra_hosts:
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- "host.docker.internal:host-gateway"
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```
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Or just add Ollama itself to the compose stack as a sibling service.
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## Test once both are up
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```bash
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docker compose up -d llama-rerank crop-chem-docs
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# Wait ~10s for both to come up, then:
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docker exec crop-chem-docs python -c \
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"from docs_mcp.server import corpus_status; print(corpus_status())"
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```
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Expect: `# crop-chem-docs corpus status`, 4,159 labels, 216,467
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chunks, BM25 db present, `RERANK_URL=http://llama-rerank:8080`,
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`HYBRID_SEARCH=on`.
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Then a live search to verify hybrid+rerank:
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```bash
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docker exec crop-chem-docs python -c \
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"from docs_mcp.server import search_docs; print(search_docs('soybean herbicide for waterhemp', k=2))"
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```
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Expect: 2 hits with Sencor/Tackle/Warrant in top-2, `mode=hybrid-rrf+rerank` in the header.
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## What the MCP container exposes
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| Tool | What it does |
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| `search_docs` | Hybrid+rerank pesticide-label search with optional filters |
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| `get_page` | Full label markdown + metadata by `(source, source_key)` |
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| `list_versions` | Discover sources, product classes, signal words, registrants |
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| `corpus_status` | Counts + freshness; useful for health probes |
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| `crop_chem_api_lessons` | Curated agronomy / label-handling knowledge — call before recommending |
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## Tag scheme
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| Tag | When | Use for |
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|---|---|---|
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| `:latest` | Every monthly refresh + every code push | Dev / Watchtower auto-pull |
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| `:<sha12>` | Every build | Rollback pin |
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| `:corpus-YYYY.MM.DD` | Every build | **Production pin** (frozen corpus version) |
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## Updating the corpus
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- **Monthly cron** — 1st @ 06:00 UTC, full re-scrape of Bayer + EPA PPLS,
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reindex, image push. Watchtower pulls the new `:latest` automatically.
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- **Manual** — Gitea Actions UI → `Monthly corpus refresh` → `Run workflow`.
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Optional `sources` input for single-source refresh (e.g., `bayer` only).
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