initial structure implemented

docs -> _docs

models/recovery/__init__.py

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+from .search_session import SearchSession
+from .confidence_assessment import ConfidenceAssessment
+from .user_anchor import UserAnchor
+from .user_input_request import UserInputRequest
+
+__all__ = [
+    "SearchSession",
+    "ConfidenceAssessment",
+    "UserAnchor",
+    "UserInputRequest",
+]
+

models/recovery/confidence_assessment.py

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+from pydantic import BaseModel
+
+
+class ConfidenceAssessment(BaseModel):
+    overall_confidence: float
+    vo_confidence: float
+    litesam_confidence: float
+    inlier_count: int
+    tracking_status: str
+

models/recovery/search_session.py

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+from pydantic import BaseModel
+from ..core.gps_point import GPSPoint
+
+
+class SearchSession(BaseModel):
+    session_id: str
+    flight_id: str
+    frame_id: int
+    center_gps: GPSPoint
+    current_grid_size: int = 1
+    max_grid_size: int = 25
+    found: bool = False
+    exhausted: bool = False
+

models/recovery/user_anchor.py

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+from pydantic import BaseModel
+from ..core.gps_point import GPSPoint
+
+
+class UserAnchor(BaseModel):
+    uav_pixel: tuple[float, float]
+    satellite_gps: GPSPoint
+    confidence: float = 1.0
+

models/recovery/user_input_request.py

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+from datetime import datetime
+import numpy as np
+from pydantic import BaseModel, ConfigDict
+from ..satellite.tile_candidate import TileCandidate
+
+
+class UserInputRequest(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    request_id: str
+    flight_id: str
+    frame_id: int
+    uav_image: np.ndarray
+    candidate_tiles: list[TileCandidate]
+    message: str
+    created_at: datetime
+