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Phase 5B commit 6: delete CallerBackground dataclass, relationship_context, update docs

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Final cleanup pass for the caller generation redesign:
- Delete CallerBackground dataclass + all isinstance() checks
- Delete orphaned _build_relationship_context and session.relationship_context
- Delete Session.get_caller_model (caller_dialog category routes to haiku-4.5)
- Delete dead _get_show_energy (CallRecord no longer tracks energy_level)
- Delete unused tone_streak field
- Drop topic_category/emotional_state/energy_level from CallRecord
- Simplify caller property, _find_thematic_match, enrich, promotion paths to slim dict
- Drop broken emotional_state=/energy_level= kwargs from generate_speech calls
- _load_checkpoint drops pre-slim schema backgrounds; startup re-pregens if empty
- Rewrite CLAUDE.md "Caller Generation System" section for the new two-stage architecture

35 tests passing. backend/main.py: 4981 -> 4810 lines.
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luke
2026-04-05 13:56:08 -06:00
parent 83c7f441a8
commit 9e37fbf124
2 changed files with 71 additions and 241 deletions
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CLAUDE.md
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@@ -58,13 +58,14 @@ Required in `.env`:
- `generate_with_tools()` in llm.py supports OpenRouter function calling for the intern feature
## Caller Generation System
- **CallerBackground dataclass**: Structured output from LLM background generation (JSON mode). Fields: name, age, gender, job, location, reason_for_calling, pool_name, communication_style, energy_level, emotional_state, signature_detail, situation_summary, natural_description, seeds, verbal_fluency, calling_from.
- **Voice-personality matching**: `_match_voices_to_styles()` runs after background generation. 68 voice profiles in `VOICE_PROFILES` (tts.py), 18 style-to-voice mappings in `STYLE_VOICE_PREFERENCES` (main.py). Soft matching — scores voices against style preferences.
- **Adaptive call shapes**: `SHAPE_STYLE_AFFINITIES` maps communication styles to shape weight multipliers. Consecutive shape repeats are dampened.
- **Inter-caller awareness**: Thematic matching in `get_show_history()` scores previous callers by keyword/category overlap. Adaptive reaction frequency (60%/35%/15%). Show energy tracking via `_get_show_energy()`.
- **Caller memory**: Returning callers store structured backgrounds, key moments, arc status, and relationships with other regulars. `RegularCallerService` has `add_relationship()` and expanded `update_after_call()`.
- **Show pacing**: `_sort_caller_queue()` sorts presentation order by energy alternation, topic variety, shape variety.
- **Call quality signals**: `_assess_call_quality()` captures exchange count, response length, host engagement, shape target hit, natural ending.
- **Two-stage pipeline**: (1) batch identity pregen via Sonnet 4.6 at session start, (2) live dialog via Haiku 4.5 per turn. Cost ~$1/show.
- **Slim caller dict**: Populated once at `Session._pregenerate_backgrounds()` via `caller_gen.generate_batch()`. Keys: `name`, `age`, `voice`, `location`, `identity`, `situation`, `reason_calling`, `opening_line`, `secret_want`, `specific_details`, `emotional_register`. Stored in `session.caller_backgrounds[caller_key]`.
- **Dialog model**: Always Haiku 4.5 via the `caller_dialog` category in `config.category_models`. No per-caller model routing — deleted in Phase 5B.
- **Prompt builder**: `get_caller_prompt(caller)` in main.py builds the slim system prompt from the dict; see `tests/test_caller_prompt.py` for the contract.
- **Regulars**: `backend/services/regulars_v2.py` loads lore from Obsidian markdown files for named recurring callers (e.g. Silas). The batch prompt optionally includes 2-3 active regulars per session.
- **Inter-caller awareness**: `get_show_history()` scores previous callers by keyword overlap with the current caller's `situation`/`reason_calling`. Reaction frequency scales with match strength (60%/35%/15%).
- **Caller memory**: Returning callers auto-promote from first-timers at ~5% probability after 8+ exchanges. `RegularCallerService` tracks summaries, relationships, arc state.
- **Call quality signals**: `_assess_call_quality()` captures exchange count, response length, host engagement, caller depth, natural ending.
## Devon (Intern Character)
- **Service**: `backend/services/intern.py` — persistent show character, not a caller
@@ -78,8 +79,8 @@ Required in `.env`:
## Frontend Control Panel
- **Keyboard shortcuts**: 1-0 (callers), H (hangup), W (wrap up), M (music toggle), D (ask Devon), Escape (close modals)
- **Wrap It Up**: Amber button that signals callers to wind down gracefully. Reduces response budget, injects wrap-up signals, forces goodbye after 2 exchanges.
- **Caller info panel**: Shows call shape, energy level, emotional state, signature detail, situation summary during active calls
- **Caller buttons**: Energy dots (colored by level) and shape badges on each button
- **Caller info panel**: Shows identity, situation, signature detail, secret want during active calls
- **Caller buttons**: Populated from the slim caller background dicts
- **Pinned SFX**: Cheer/Applause/Boo always visible, rest collapsible
- **Visual polish**: Thinking pulse, call glow, compact media row, smoother transitions