wehub-resource-sync
121 lines
4.7 KiB
Python
121 lines
4.7 KiB
Python
"""
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Personality-driven text generation — lets a voice profile "speak" or
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restate text using an LLM that takes on the character described by the
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profile's ``personality`` prompt.
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Two entry points:
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- :func:`compose_as_profile` — zero-input, the character produces a fresh
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utterance. Wired to the Compose button in the generate box and to the
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``/profiles/{id}/compose`` endpoint.
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- :func:`rewrite_as_profile` — takes user text, restates it in the
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character's voice while keeping every idea. Invoked by ``POST /generate``
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(and ``POST /speak``) when ``personality=true`` and the profile has a
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personality prompt set.
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Both reuse the same local Qwen3 instance that refinement uses — no extra
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model downloads, no extra warm-up. Temperature is tuned per mode: compose
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runs hot (0.9) for variety, rewrite cool (0.3) for fidelity to the user's
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ideas.
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"""
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from dataclasses import dataclass
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from . import llm as llm_service
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from .refinement import collapse_repetitive_artifacts
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# Shared rules block embedded in every mode-specific system prompt. Kept
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# short because small LLMs (0.6B) degrade when the system prompt is long,
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# and because the per-mode instructions downstream carry the specifics.
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_CHARACTER_FRAMING = """You are roleplaying a specific character described below. Stay fully in character in everything you produce.
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Rules that apply to every response:
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- Do not break character. Do not explain what you are doing, refuse, apologize, greet the user, or acknowledge being an AI or assistant.
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- Do not narrate action ("*smiles*", "(leans back)") or stage directions. Produce speech only.
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- Do not wrap the output in quotes, code fences, or labels. Output the character's words and nothing else.
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- Match the character's register — if they are curt, be curt; if they ramble, ramble; if they swear, swear."""
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_COMPOSE_TASK = """Task: Produce one short utterance — one or two sentences at most — that this character might say right now, unprompted. A remark, an observation, a thought out loud. No greeting, no addressing anyone by name, no "Well, …" or "So, …" opener unless it fits the character naturally. Just a natural line of speech."""
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_REWRITE_TASK = """Task: The user's next message is a piece of text. Restate every idea in it using your character's voice — keep the meaning, change the wording. Do not add new ideas, do not drop any, do not reply to the text. Output only the restated version."""
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@dataclass
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class PersonalityResult:
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"""What the three service functions return."""
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text: str
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model_size: str
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def _build_system_prompt(personality: str, task: str) -> str:
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return (
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_CHARACTER_FRAMING
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+ "\n\nCharacter description:\n"
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+ personality.strip()
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+ "\n\n"
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+ task
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)
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def _require_personality(personality: str | None) -> str:
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if not personality or not personality.strip():
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raise ValueError(
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"This profile has no personality set. Add one on the profile to use compose or personality-rewrite."
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)
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return personality
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async def compose_as_profile(
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personality: str | None,
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model_size: str | None = None,
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) -> PersonalityResult:
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"""Produce a fresh utterance in the character's voice.
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No user input; the system prompt plus a trigger user turn ("Speak.")
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is all the model gets. Temperature is high so successive calls
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produce different outputs — the UI's Compose button is expected to
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be clicked repeatedly for variety.
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"""
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text = _require_personality(personality)
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backend = llm_service.get_llm_model()
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resolved_size = model_size or backend.model_size
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system_prompt = _build_system_prompt(text, _COMPOSE_TASK)
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output = await backend.generate(
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prompt="Speak.",
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system=system_prompt,
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max_tokens=256,
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temperature=0.9,
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model_size=resolved_size,
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)
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return PersonalityResult(text=output.strip(), model_size=resolved_size)
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async def rewrite_as_profile(
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personality: str | None,
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user_text: str,
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model_size: str | None = None,
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) -> PersonalityResult:
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"""Restate the user's text in the character's voice, ideas intact."""
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character = _require_personality(personality)
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cleaned = collapse_repetitive_artifacts(user_text)
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if not cleaned.strip():
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raise ValueError("Rewrite needs non-empty text to restate.")
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backend = llm_service.get_llm_model()
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resolved_size = model_size or backend.model_size
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system_prompt = _build_system_prompt(character, _REWRITE_TASK)
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output = await backend.generate(
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prompt=cleaned,
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system=system_prompt,
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max_tokens=1024,
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temperature=0.3,
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model_size=resolved_size,
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)
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return PersonalityResult(text=output.strip(), model_size=resolved_size)
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