| from __future__ import annotations |
| import logging |
| from datetime import datetime |
|
|
| from schemas.signal import NormalizedSignal, SignalType |
| from skills.normalize_signal import normalize_signal |
|
|
| logger = logging.getLogger(__name__) |
|
|
|
|
| class NormalizationAgent: |
| def __init__(self, vllm_client=None) -> None: |
| self.vllm_client = vllm_client |
|
|
| async def run(self, raw_text: str, report_id: str, modality: str) -> NormalizedSignal: |
| logger.debug("NormalizationAgent processing text from report %s", report_id) |
| data = await normalize_signal(raw_text, modality, report_id, vllm_client=self.vllm_client) |
|
|
| signal_type_str = data.get("signal_type", "unknown") |
| try: |
| signal_type = SignalType(signal_type_str) |
| except ValueError: |
| signal_type = SignalType.UNKNOWN |
|
|
| created_raw = data.get("created_at", datetime.utcnow().isoformat()) |
| if isinstance(created_raw, str): |
| try: |
| created_at = datetime.fromisoformat(created_raw) |
| except ValueError: |
| created_at = datetime.utcnow() |
| else: |
| created_at = created_raw |
|
|
| return NormalizedSignal( |
| source_report_id=report_id, |
| signal_type=signal_type, |
| description=data.get("description", raw_text[:200]), |
| location=data.get("location"), |
| coordinates=data.get("coordinates"), |
| affected_people=data.get("affected_people"), |
| raw_text=raw_text, |
| confidence=data.get("confidence", 0.7), |
| modality=modality, |
| created_at=created_at, |
| ) |
|
|
