pyr0ball
7dcdf551fc
Removes unused imports flagged by ruff F401 across 12 scripts. All removals are safe — ruff only auto-fixes imports that are verifiably unused.
85 lines
2.9 KiB
Python
85 lines
2.9 KiB
Python
# MIT License — see LICENSE
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"""Survey assistant: prompt builders and LLM inference for culture-fit survey analysis.
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Extracted from dev-api.py so task_runner can import this without importing the
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FastAPI application. Callable directly or via the survey_analyze background task.
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"""
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from __future__ import annotations
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import logging
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from pathlib import Path
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from typing import Optional
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log = logging.getLogger(__name__)
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SURVEY_SYSTEM = (
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"You are a job application advisor helping a candidate answer a culture-fit survey. "
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"The candidate values collaborative teamwork, clear communication, growth, and impact. "
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"Choose answers that present them in the best professional light."
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)
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def build_text_prompt(text: str, mode: str) -> str:
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if mode == "quick":
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return (
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"Answer each survey question below. For each, give ONLY the letter of the best "
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"option and a single-sentence reason. Format exactly as:\n"
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"1. B — reason here\n2. A — reason here\n\n"
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f"Survey:\n{text}"
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)
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return (
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"Analyze each survey question below. For each question:\n"
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"- Briefly evaluate each option (1 sentence each)\n"
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"- State your recommendation with reasoning\n\n"
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f"Survey:\n{text}"
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)
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def build_image_prompt(mode: str) -> str:
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if mode == "quick":
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return (
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"This is a screenshot of a culture-fit survey. Read all questions and answer each "
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"with the letter of the best option for a collaborative, growth-oriented candidate. "
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"Format: '1. B — brief reason' on separate lines."
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)
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return (
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"This is a screenshot of a culture-fit survey. For each question, evaluate each option "
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"and recommend the best choice for a collaborative, growth-oriented candidate. "
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"Include a brief breakdown per option and a clear recommendation."
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)
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def run_survey_analyze(
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text: Optional[str],
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image_b64: Optional[str],
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mode: str,
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config_path: Optional[Path] = None,
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) -> dict:
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"""Run LLM inference for survey analysis.
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Returns {"output": str, "source": "text_paste" | "screenshot"}.
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Raises on LLM failure — caller is responsible for error handling.
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"""
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from scripts.llm_router import LLMRouter
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router = LLMRouter(config_path=config_path) if config_path else LLMRouter()
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if image_b64:
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prompt = build_image_prompt(mode)
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output = router.complete(
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prompt,
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images=[image_b64],
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fallback_order=router.config.get("vision_fallback_order"),
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)
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source = "screenshot"
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else:
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prompt = build_text_prompt(text or "", mode)
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output = router.complete(
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prompt,
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system=SURVEY_SYSTEM,
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fallback_order=router.config.get("research_fallback_order"),
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)
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source = "text_paste"
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return {"output": output, "source": source}
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