aizynthfinder

# AiZynthFinder Repo Skill Use this skill when a user is working with AiZynthFinder, a retrosynthetic route-finding package for planning molecule syntheses with policy-guided tree search. ## First Steps 1. Confirm the user has AiZynthFinder installed in a Python `>=3.10,<3.13` environment. 2. If the task mentions a config, stock, policy model, template library, public-data bundle, or optional service, start with [configuration-and-data](sub-skills/configuration-and-data/SKILL.md). 3. If the task is to run retrosynthesis or one-step expansion, use [planning-workflows](sub-skills/planning-workflows/SKILL.md). 4. If the task starts from an existing `output.json.gz`, HDF5 output, `trees.json`, checkpoint, route collection, or reaction tree, use [route-analysis](sub-skills/route-analysis/SKILL.md). 5. If the task is about custom scorers, stocks, policies, search algorithms, plugin strategies, hooks, or source edits, use [extension-and-development](sub-skills/extension-and-development/SKILL.md). ## Install and Import Check For end users, install the public package with base dependencies unless the task needs optional features: ```bash python -m pip install aizynthfinder python - <<'PY' from aizynthfinder.aizynthfinder import AiZynthFinder, AiZynthExpander print(AiZynthFinder, AiZynthExpander) PY ``` Use `python -m pip install "aizynthfinder[all]"` only when the task needs optional MongoDB, molbloom, route-distance, timeout, or similar extras. Use TensorFlow/gRPC-related extras only for TensorFlow Serving or remote model workflows. Run [scripts/check_aizynthfinder_env.py](scripts/check_aizynthfinder_env.py) when diagnosing import, version, CLI, or optional-dependency availability without launching a search. ## Sub-Skill Routes - [planning-workflows](sub-skills/planning-workflows/SKILL.md): build and run `aizynthcli` commands, use `AiZynthFinder` or `AiZynthExpander`, handle single vs batch SMILES, checkpoints, multiprocessing, clustering flags, and GUI/notebook launch decisions. - [configuration-and-data](sub-skills/configuration-and-data/SKILL.md): write and validate YAML configs, stock files, policy/filter model references, public data commands, `smiles2stock`, `download_public_data`, and optional dependency choices. - [route-analysis](sub-skills/route-analysis/SKILL.md): inspect `output.json.gz`, HDF5 tables, `trees.json`, checkpoints, `ReactionTree`, `RouteCollection`, route scores, clustering, images, and result summaries. - [extension-and-development](sub-skills/extension-and-development/SKILL.md): implement or validate custom hooks, stocks, scorers, policies, plugin expansion strategies, search algorithms, and focused source-checkout tests. ## Shared References - Read [references/troubleshooting.md](references/troubleshooting.md) for cross-cutting install, optional dependency, model/stock asset, CLI/API, and backend failures before drilling into sub-skill-specific troubleshooting. - Read [references/repo-provenance.md](references/repo-provenance.md) before deciding whether this skill is current for an AiZynthFinder checkout or should be refreshed. - `references/repo-routing-metadata.json` is structured metadata used by the managed repo-skills-router during import. ## Routing Guardrails - Do not run `download_public_data`, MongoDB stock creation, long retrosynthesis batches, GUI launches, or plugin service calls unless the user explicitly asks for those side effects. - Do not assume user assets exist. Configs normally require a stock file, an expansion policy model, and a reaction template library; filter policies are optional. - Prefer static validation and CLI/API help checks before running searches with user data. - Keep optional plugins and service-backed models separate from core install troubleshooting; missing Chemformer, ModelZoo, MongoDB, molbloom, route-distance, or TensorFlow Serving dependencies are feature-specific, not proof that core AiZynthFinder is broken.