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completion plugin for tagma-sdk pipelines","maintainers":[{"name":"go-tagma","email":"danuberiverferryman@gmail.com"}],"readme":"# @tagma/completion-llm-judge\n\nLLM-as-judge completion plugin for [@tagma/sdk](https://www.npmjs.com/package/@tagma/sdk).\n\nUses an OpenAI-compatible chat completions endpoint to verify whether a task's output satisfies a rubric. Complements the deterministic built-in completions (`exit_code`, `file_exists`, `output_check`) when task success is defined semantically rather than by a grep-able pattern.\n\n**Default backend**: local [Ollama](https://ollama.com/) with `qwen3:4b` — a small reasoning model that runs on CPU with no API key. Swap `endpoint` + `model` to point at any OpenAI-compatible server (OpenAI, vLLM, llama.cpp, LM Studio, Groq, Together, OpenRouter, ...).\n\n## Install\n\n```bash\nbun add @tagma/completion-llm-judge\n```\n\nThen make sure Ollama is running with the default model pulled:\n\n```bash\nollama pull qwen3:4b\nollama serve  # usually auto-started\n```\n\n## Usage\n\n```yaml\npipeline:\n  name: qa-loop\n  plugins:\n    - '@tagma/completion-llm-judge'\n  tracks:\n    - id: qa\n      name: QA\n      driver: claude-code\n      tasks:\n        - id: find-bugs\n          name: Find failing tests\n          prompt: 'List all failing tests in the current workspace with their file paths.'\n          completion:\n            type: llm_judge\n            rubric: |\n              The output must list at least 3 failing tests. Each entry must\n              include the test name, the file path, and the assertion that\n              failed. The output must not be an empty placeholder.\n            # endpoint / model / api_key_env all default to local Ollama + qwen3:4b\n            timeout: 2h\n```\n\nSwap to a hosted backend:\n\n```yaml\ncompletion:\n  type: llm_judge\n  rubric: '...'\n  endpoint: https://api.openai.com/v1/chat/completions\n  model: gpt-4o-mini\n  api_key_env: OPENAI_API_KEY\n```\n\nOr load it programmatically:\n\n```ts\nimport { createTagma } from '@tagma/sdk';\n\nconst tagma = createTagma();\nawait tagma.registry.loadPlugins(['@tagma/completion-llm-judge'], process.cwd());\n```\n\n## Config\n\n| Field              | Type     | Default                                      | Notes                                                                                      |\n| ------------------ | -------- | -------------------------------------------- | ------------------------------------------------------------------------------------------ |\n| `rubric`           | string   | _(required)_                                 | Plain-language success criteria the judge should verify                                    |\n| `model`            | string   | `qwen3:4b`                                   | Judge model name. Swap for `qwen3:8b`, `deepseek-r1:7b`, `gpt-4o-mini`, etc.               |\n| `endpoint`         | string   | `http://localhost:11434/v1/chat/completions` | OpenAI-compatible chat completions URL. Default points at local Ollama                     |\n| `api_key_env`      | string   | _(none)_                                     | Env var holding the bearer token. Leave unset for local Ollama; set for hosted backends    |\n| `timeout`          | duration | `2h`                                         | Max time to wait for the judge response (reasoning models need more time than chat models) |\n| `max_output_chars` | number   | `8000`                                       | Truncate task stdout before judging (head+tail preserved)                                  |\n\n## Behavior\n\n- **Verdict format**: the judge is instructed to answer `PASS` or `FAIL` on the first line. Missing or ambiguous answers are treated as FAIL — a judge that errs open defeats the purpose of the gate.\n- **Repair feedback**: a FAIL verdict returns the bounded judge explanation as structured completion feedback, so a workflow with `lifecycle.repair: true` can act on the unmet rubric in its next attempt.\n- **Reasoning-model support**: `<think>...</think>` and `<thinking>...</thinking>` blocks are stripped from the response before verdict parsing, so qwen3, DeepSeek-R1, and other thinkers work without any extra config.\n- **Truncation**: task stdout longer than `max_output_chars` is truncated head-and-tail (70/30 split) with a marker in the middle, so the judge still sees the task's intent and its final summary.\n- **Error handling**: network errors, auth errors, timeout, or malformed responses all mark the task as not-complete and log a warning with the judge's verbatim response (if any).\n- **Abort propagation**: the pipeline abort signal is wired into the judge fetch call, so cancelling a pipeline also cancels any in-flight judge request.\n- **Determinism**: the call uses `temperature: 0` to keep verdicts as stable as the model allows.\n\n## Alternative endpoints\n\nAny OpenAI-compatible endpoint works — just point `endpoint` and `api_key_env` at it:\n\n- **Local Ollama** (default): `http://localhost:11434/v1/chat/completions`, no API key\n- **OpenAI**: `https://api.openai.com/v1/chat/completions`, `api_key_env: OPENAI_API_KEY`\n- **Local models** via LM Studio, vLLM, llama.cpp OpenAI-compatible servers\n- **Hosted**: Groq, Together, Fireworks, OpenRouter, DeepInfra, etc.\n- **Anthropic** via an OpenAI-compat proxy (e.g. `anthropic-openai-proxy`)\n\n## License\n\nMIT\n","readmeFilename":"README.md"}