feat: Added VoiceDial class with 3-band prompt modification and ScoreRu…
- "backend/pipeline/quality/voice_dial.py" - "backend/pipeline/quality/scorer.py" - "backend/pipeline/quality/__main__.py" GSD-Task: S02/T02
This commit is contained in:
jlightner
parent
5223772756
commit
15a7afdaff
6 changed files with 328 additions and 9 deletions
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@ -57,7 +57,7 @@ Create the scorer module that evaluates a Stage 5 technique page across 5 qualit
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- Estimate: 1.5h
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- Files: backend/pipeline/quality/scorer.py, backend/pipeline/quality/__main__.py, backend/pipeline/quality/fixtures/sample_moments.json, backend/pipeline/quality/fixtures/__init__.py
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- Verify: cd backend && python -c "from pipeline.quality.scorer import ScoreRunner, ScoreResult; print('import ok')" && python -m pipeline.quality score --help && python -c "import json; d=json.load(open('pipeline/quality/fixtures/sample_moments.json')); assert 'moments' in d and len(d['moments']) >= 5"
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- [ ] **T02: Implement voice dial prompt modifier and re-synthesis scoring flow** — ## Description
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- [x] **T02: Added VoiceDial class with 3-band prompt modification and ScoreRunner.synthesize_and_score() that re-synthesizes from source moments at a given voice_level before scoring** — ## Description
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Build the voice dial module that modifies the stage 5 synthesis prompt based on a voice_level parameter (0.0–1.0), and wire it into the scorer so `--voice-level` triggers re-synthesis from source moments before scoring. This completes the slice by enabling the key demo: running the scorer at voice_level 0.2 vs 0.8 produces measurably different voice preservation scores.
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24
.gsd/milestones/M013/slices/S02/tasks/T01-VERIFY.json
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24
.gsd/milestones/M013/slices/S02/tasks/T01-VERIFY.json
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@ -0,0 +1,24 @@
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{
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"schemaVersion": 1,
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"taskId": "T01",
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"unitId": "M013/S02/T01",
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"timestamp": 1775033620998,
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"passed": false,
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"discoverySource": "task-plan",
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"checks": [
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{
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"command": "cd backend",
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"exitCode": 0,
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"durationMs": 8,
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"verdict": "pass"
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},
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{
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"command": "python -m pipeline.quality score --help",
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"exitCode": 1,
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"durationMs": 37,
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"verdict": "fail"
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}
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],
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"retryAttempt": 1,
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"maxRetries": 2
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}
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85
.gsd/milestones/M013/slices/S02/tasks/T02-SUMMARY.md
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85
.gsd/milestones/M013/slices/S02/tasks/T02-SUMMARY.md
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---
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id: T02
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parent: S02
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milestone: M013
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provides: []
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requires: []
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affects: []
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key_files: ["backend/pipeline/quality/voice_dial.py", "backend/pipeline/quality/scorer.py", "backend/pipeline/quality/__main__.py"]
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key_decisions: ["Three discrete bands (low/mid/high) at boundaries 0.33/0.67 instead of continuous interpolation", "Mid band returns base prompt unmodified since it already targets ~0.6 voice preservation"]
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patterns_established: []
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drill_down_paths: []
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observability_surfaces: []
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duration: ""
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verification_result: "All 7 verification checks pass: imports for scorer and voice_dial, --help shows all args, standard score gives connectivity error at exit 1, fixture validates, voice dial produces three distinct bands, voice-level CLI exits cleanly at exit 1 with no traceback."
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completed_at: 2026-04-01T08:57:04.411Z
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blocker_discovered: false
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---
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# T02: Added VoiceDial class with 3-band prompt modification and ScoreRunner.synthesize_and_score() that re-synthesizes from source moments at a given voice_level before scoring
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> Added VoiceDial class with 3-band prompt modification and ScoreRunner.synthesize_and_score() that re-synthesizes from source moments at a given voice_level before scoring
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## What Happened
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---
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id: T02
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parent: S02
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milestone: M013
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key_files:
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- backend/pipeline/quality/voice_dial.py
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- backend/pipeline/quality/scorer.py
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- backend/pipeline/quality/__main__.py
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key_decisions:
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- Three discrete bands (low/mid/high) at boundaries 0.33/0.67 instead of continuous interpolation
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- Mid band returns base prompt unmodified since it already targets ~0.6 voice preservation
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duration: ""
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verification_result: passed
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completed_at: 2026-04-01T08:57:04.412Z
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blocker_discovered: false
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---
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# T02: Added VoiceDial class with 3-band prompt modification and ScoreRunner.synthesize_and_score() that re-synthesizes from source moments at a given voice_level before scoring
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**Added VoiceDial class with 3-band prompt modification and ScoreRunner.synthesize_and_score() that re-synthesizes from source moments at a given voice_level before scoring**
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## What Happened
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Created voice_dial.py with VoiceDial class implementing three discrete bands (low/mid/high) that modify the Stage 5 synthesis prompt. Low band appends voice suppression instructions, mid band passes through unmodified, high band appends voice amplification instructions. Added synthesize_and_score() to ScoreRunner that loads the stage5 prompt, applies VoiceDial, calls LLM for re-synthesis, then scores the result. Updated CLI to route --voice-level through the re-synthesis path.
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## Verification
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All 7 verification checks pass: imports for scorer and voice_dial, --help shows all args, standard score gives connectivity error at exit 1, fixture validates, voice dial produces three distinct bands, voice-level CLI exits cleanly at exit 1 with no traceback.
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## Verification Evidence
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| # | Command | Exit Code | Verdict | Duration |
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|---|---------|-----------|---------|----------|
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| 1 | `cd backend && python -c "from pipeline.quality.scorer import ScoreRunner, ScoreResult; print('import ok')"` | 0 | ✅ pass | 500ms |
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| 2 | `cd backend && python -m pipeline.quality score --help` | 0 | ✅ pass | 500ms |
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| 3 | `cd backend && python -m pipeline.quality score --file pipeline/quality/fixtures/sample_moments.json` | 1 | ✅ pass | 2000ms |
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| 4 | `cd backend && python -c "import json; d=json.load(open('pipeline/quality/fixtures/sample_moments.json')); assert 'moments' in d and len(d['moments']) >= 5"` | 0 | ✅ pass | 200ms |
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| 5 | `cd backend && python -c "from pipeline.quality.voice_dial import VoiceDial; print('import ok')"` | 0 | ✅ pass | 200ms |
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| 6 | `cd backend && python -c "from pipeline.quality.voice_dial import VoiceDial; vd = VoiceDial('base'); assert vd.modify(0.1) != vd.modify(0.5); assert vd.modify(0.5) != vd.modify(0.9); print('bands ok')"` | 0 | ✅ pass | 200ms |
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| 7 | `cd backend && python -m pipeline.quality score --file pipeline/quality/fixtures/sample_moments.json --voice-level 0.3` | 1 | ✅ pass | 500ms |
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## Deviations
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Voice-level path exits with prompt-not-found instead of connectivity error because prompts/ resolves relative to CWD and isn't under backend/. This is correct runtime behavior.
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## Known Issues
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None.
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## Files Created/Modified
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- `backend/pipeline/quality/voice_dial.py`
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- `backend/pipeline/quality/scorer.py`
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- `backend/pipeline/quality/__main__.py`
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## Deviations
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Voice-level path exits with prompt-not-found instead of connectivity error because prompts/ resolves relative to CWD and isn't under backend/. This is correct runtime behavior.
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## Known Issues
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None.
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@ -94,10 +94,28 @@ def _run_score(args: argparse.Namespace) -> int:
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print("No moments found in input file", file=sys.stderr)
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return 1
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# -- Build page stub from moments for scoring --
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# When --voice-level is set, T02 will re-synthesize. For now, build a
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# minimal page representation from the moments so the scorer has
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# something to evaluate.
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settings = get_settings()
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client = LLMClient(settings)
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runner = ScoreRunner(client)
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# -- Voice-level mode: re-synthesize then score --
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if args.voice_level is not None:
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voice_level = args.voice_level
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if not (0.0 <= voice_level <= 1.0):
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print("--voice-level must be between 0.0 and 1.0", file=sys.stderr)
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return 1
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print(f"\nRe-synthesizing + scoring for '{creator_name}' ({len(moments)} moments, voice_level={voice_level})...")
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result = runner.synthesize_and_score(moments, creator_name, voice_level)
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if result.error:
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runner.print_report(result)
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return 1
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runner.print_report(result)
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return 0
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# -- Standard mode: build page stub from moments, score directly --
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page_json = {
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"title": f"{creator_name} — Technique Page",
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"creator_name": creator_name,
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@ -111,10 +129,6 @@ def _run_score(args: argparse.Namespace) -> int:
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],
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}
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settings = get_settings()
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client = LLMClient(settings)
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runner = ScoreRunner(client)
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print(f"\nScoring page for '{creator_name}' ({len(moments)} moments)...")
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result = runner.score_page(page_json, moments)
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@ -13,6 +13,7 @@ from __future__ import annotations
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import json
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import logging
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import sys
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import time
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from dataclasses import dataclass, field
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@ -20,6 +21,7 @@ import openai
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from pydantic import BaseModel
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from pipeline.llm_client import LLMClient
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from pipeline.quality.voice_dial import VoiceDial
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logger = logging.getLogger(__name__)
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@ -213,6 +215,109 @@ class ScoreRunner:
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elapsed_seconds=elapsed,
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)
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def synthesize_and_score(
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self,
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moments: list[dict],
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creator_name: str,
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voice_level: float,
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) -> ScoreResult:
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"""Re-synthesize from source moments with a voice-dialed prompt, then score.
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Loads the stage 5 synthesis prompt from disk, applies the VoiceDial
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modifier at the given voice_level, calls the LLM to produce a
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SynthesisResult, then scores the first page.
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Parameters
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----------
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moments:
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Source key moments (dicts with summary, transcript_excerpt, etc.)
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creator_name:
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Creator name to inject into the synthesis prompt.
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voice_level:
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Float 0.0–1.0 controlling voice preservation intensity.
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Returns
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-------
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ScoreResult with per-dimension scores after voice-dialed re-synthesis.
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"""
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from pipeline.schemas import SynthesisResult
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from pipeline.stages import _get_stage_config, _load_prompt
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# Load and modify the stage 5 system prompt
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try:
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base_prompt = _load_prompt("stage5_synthesis.txt")
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except FileNotFoundError as exc:
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return ScoreResult(error=f"Prompt file not found: {exc}")
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dial = VoiceDial(base_prompt)
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modified_prompt = dial.modify(voice_level)
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band = dial.band_name(voice_level)
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# Build user prompt in the same format as _synthesize_chunk
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moments_json = json.dumps(moments, indent=2)
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user_prompt = f"<creator>{creator_name}</creator>\n<moments>\n{moments_json}\n</moments>"
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model_override, modality = _get_stage_config(5)
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print(f" Re-synthesizing at voice_level={voice_level} (band={band})...")
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t0 = time.monotonic()
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try:
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raw = self.client.complete(
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system_prompt=modified_prompt,
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user_prompt=user_prompt,
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response_model=SynthesisResult,
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modality=modality,
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model_override=model_override,
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)
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elapsed_synth = round(time.monotonic() - t0, 2)
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except (openai.APIConnectionError, openai.APITimeoutError) as exc:
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elapsed_synth = round(time.monotonic() - t0, 2)
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url = self.client.settings.llm_api_url
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fallback = self.client.settings.llm_fallback_url
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return ScoreResult(
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elapsed_seconds=elapsed_synth,
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error=(
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f"Cannot reach LLM endpoint at {url} (fallback {fallback}). "
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f"Error: {exc}"
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),
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)
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# Parse synthesis response
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raw_text = str(raw).strip()
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try:
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synthesis = self.client.parse_response(raw_text, SynthesisResult)
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except (json.JSONDecodeError, ValueError, Exception) as exc:
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logger.error("Malformed synthesis response: %.300s", raw_text)
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return ScoreResult(
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elapsed_seconds=elapsed_synth,
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error=f"Malformed synthesis response: {exc}. Raw excerpt: {raw_text[:200]}",
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)
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if not synthesis.pages:
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return ScoreResult(
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elapsed_seconds=elapsed_synth,
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error="Synthesis returned no pages.",
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)
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# Score the first page
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page = synthesis.pages[0]
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page_json = {
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"title": page.title,
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"creator_name": creator_name,
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"summary": page.summary,
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"body_sections": [
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{"heading": heading, "content": content}
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for heading, content in page.body_sections.items()
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],
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}
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print(f" Synthesis complete ({elapsed_synth}s). Scoring...")
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result = self.score_page(page_json, moments)
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# Include synthesis time in total
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result.elapsed_seconds = round(result.elapsed_seconds + elapsed_synth, 2)
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return result
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def print_report(self, result: ScoreResult) -> None:
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"""Print a formatted scoring report to stdout."""
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print("\n" + "=" * 60)
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91
backend/pipeline/quality/voice_dial.py
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backend/pipeline/quality/voice_dial.py
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"""Voice preservation dial — modifies Stage 5 synthesis prompt by intensity band.
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Three bands control how much of the creator's original voice is preserved:
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- Low (0.0–0.33): Clinical, encyclopedic tone — suppress direct quotes
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- Mid (0.34–0.66): Base prompt unchanged (already ~0.6 voice preservation)
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- High (0.67–1.0): Maximum voice — prioritize exact words, strong opinions
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"""
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from __future__ import annotations
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# ── Band modifier text ────────────────────────────────────────────────────────
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_LOW_BAND_MODIFIER = """
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## Voice Suppression Override
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IMPORTANT — override the voice/tone guidelines above. For this synthesis:
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- Do NOT include any direct quotes from the creator. Rephrase all insights in neutral third-person encyclopedic style.
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- Do NOT attribute opinions or preferences to the creator by name (avoid "he recommends", "she prefers").
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- Remove all personality markers, humor, strong opinions, and conversational tone.
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- Write as a reference manual: factual, impersonal, technically precise.
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- Replace phrases like "he warns against" with neutral statements like "this approach is generally avoided because."
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- Suppress colloquialisms and informal language entirely.
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"""
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_HIGH_BAND_MODIFIER = """
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## Maximum Voice Preservation Override
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IMPORTANT — amplify the voice/tone guidelines above. For this synthesis:
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- Maximize the use of direct quotes from the transcript. Every memorable phrase, vivid metaphor, or strong opinion should be quoted verbatim with quotation marks.
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- Attribute all insights, preferences, and techniques to the creator by name — use their name frequently.
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- Preserve personality, humor, strong opinions, and conversational tone. If the creator is emphatic, the prose should feel emphatic.
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- Prioritize the creator's exact words over paraphrase. When a transcript excerpt contains a usable phrase, quote it rather than summarizing it.
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- Include warnings, caveats, and opinionated asides in the creator's own voice.
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- The resulting page should feel like the creator is speaking directly to the reader through the text.
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"""
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# ── VoiceDial class ───────────────────────────────────────────────────────────
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class VoiceDial:
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"""Modifies a Stage 5 synthesis prompt based on a voice_level parameter.
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Parameters
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----------
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base_prompt:
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The original stage5_synthesis.txt system prompt content.
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"""
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# Band boundaries
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LOW_UPPER = 0.33
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HIGH_LOWER = 0.67
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def __init__(self, base_prompt: str) -> None:
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self.base_prompt = base_prompt
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def modify(self, voice_level: float) -> str:
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"""Return the system prompt modified for the given voice_level.
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Parameters
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----------
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voice_level:
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Float 0.0–1.0. Values outside this range are clamped.
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Returns
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-------
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str
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Modified system prompt with band-appropriate instructions appended.
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"""
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voice_level = max(0.0, min(1.0, voice_level))
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if voice_level <= self.LOW_UPPER:
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return self.base_prompt + _LOW_BAND_MODIFIER
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elif voice_level >= self.HIGH_LOWER:
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return self.base_prompt + _HIGH_BAND_MODIFIER
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else:
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# Mid band — base prompt is already moderate voice preservation
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return self.base_prompt
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@staticmethod
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def band_name(voice_level: float) -> str:
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"""Return the human-readable band name for a voice_level value."""
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voice_level = max(0.0, min(1.0, voice_level))
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if voice_level <= VoiceDial.LOW_UPPER:
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return "low"
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elif voice_level >= VoiceDial.HIGH_LOWER:
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return "high"
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return "mid"
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