Ethanfel/ComfyUI-Prompt-Calibrator
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describe emits one canonical reference; compare can anchor on it

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Describe mode now produces a single coherent, internally-consistent canonical
scene description (paragraph + per-axis spec, written to canonical_reference in
the report). Compare gains an optional reference_description input: when set, it
anchors on that fixed text and shows only the generated image (no swap) — so the
reference side never drifts or self-contradicts across iterations; only the
generated image is re-described each turn. agent_bridge gains --ref-desc /
--ref-desc-file (reads the describe report's canonical_reference). Docs + example
workflow updated.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Ethanfel
2026-06-26 23:22:57 +02:00
parent 53f1f9b9b4
commit 69c1d6deb4
6 changed files with 149 additions and 51 deletions
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docs/AGENT_LOOP.md
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@@ -37,8 +37,8 @@ supports a `source_file` for file-first workflows if you ever want it.)
| Piece | Role |
|---|---|
| `CalibratorPromptReceptor` (`SxCP External Prompt (Receptor)`) | Stable node the agent injects `prompt/negative/seed` into. Feeds the sampler. |
| `QwenVLImageJudge` (`Qwen3-VL Image Judge (Calibrator)`) | Scores generated vs reference; writes `calib_<run_tag>.json`, `latest.json`, `calib_<run_tag>.md` to `report_dir`. |
| `agent_bridge.py` | One CLI call = one iteration: inject prompt → queue → wait → print the analysis JSON to stdout. Stdlib only. |
| `QwenVLImageJudge` (`Qwen3-VL Image Judge (Calibrator)`) | `describe` (first pass) emits the canonical reference; `compare` judges generated vs reference per axis (verdict match/partial/mismatch). When given `reference_description`, compare anchors on that fixed text. Writes `calib_<run_tag>.json` + `latest.json` to `report_dir`. |
| `agent_bridge.py` | One CLI call = one iteration: inject prompt (+`--ref-desc-file` for the canonical anchor) → queue → wait → print the analysis JSON to stdout. Stdlib only. |
## One iteration (what the agent runs)
@@ -86,7 +86,9 @@ not sampler noise; vary the seed only once near target. Stop at `overall_score
`caption` it returns is the seed prompt; the `axes` are the seed axis_state.
3. **Compare loop:** build a workflow with `CalibratorPromptReceptor` → (Prompt-Builder formatting,
optional) → T2I → `QwenVLImageJudge` (mode `compare`; feed the **reference** into
`reference_image`, the T2I output into `generated_image`).
`reference_image`, the T2I output into `generated_image`). Pass `--ref-desc-file
<report_dir>/calib_seed.json` so compare anchors on the canonical reference from step 2
(the `ref` side stays fixed across iterations; only the generated image is re-described).
4. Set the Judge's `report_dir` to a known path; pass the same path as `--analysis-dir`.
5. Export each workflow in **API format**.
6. Drive it from the agent with `agent_bridge.py`, once per iteration (describe once, then compare in a loop).