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Model: jarminraws/hotel-llm-search
Source: Original Platform

contract.py

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+"""SHARED CONTRACT — the prompt + output schema the model is trained and served on.
+
+This file is the single source of truth for:
+  - FIELD_ORDER          : canonical key order of the extracted JSON
+  - build_prompt()       : the EXACT prompt string used at train AND inference time
+  - format_completion()  : training target serialization (also used by eval)
+  - extract_json()       : brace-matched JSON extraction from raw model text
+  - HotelExtraction      : Pydantic schema for validation
+  - validate()           : parse+validate -> clean dict (or None)
+
+It is intentionally DEPENDENCY-LIGHT (only json + pydantic) so both the heavy
+training env and the lean serving env can import it. A COPY of this file lives in
+BOTH training/ and deployment/; tests/test_contract_parity.py asserts they are
+byte-identical, so the prompt can never silently drift between train and serve.
+
+DO NOT EDIT one copy without the other. Edit the source, re-sync, re-run the test.
+"""
+
+from __future__ import annotations
+
+import json
+from typing import Any, Literal, Optional
+
+from pydantic import BaseModel, ConfigDict, Field, ValidationError
+
+DEFAULT_BASE_MODEL = "Qwen/Qwen3-1.7B"
+
+# `filters` is emitted as a comma-separated string of NATURAL PHRASES
+# (e.g. "swimming pool, pet friendly"), NOT production codes. A downstream matcher
+# resolves phrases -> codes (FL_HF_29, ...), keeping the model taxonomy-agnostic.
+FIELD_ORDER = [
+    "destination", "locality", "hotelName", "checkinDate", "checkoutDate",
+    "adultCount", "roomCount", "childCount", "childAges", "infantCount",
+    "sortCriteria", "minPrice", "maxPrice", "filters", "deepSearch", "isNearMe", "resetAction",
+]
+
+
+def build_prompt(query: str, today: str) -> str:
+    """The exact user-message content used for BOTH training and inference."""
+    return (
+        "Extract hotel-search entities.\n"
+        "Return strict JSON only.\n"
+        "Schema:\n"
+        "destination, locality, hotelName, checkinDate, checkoutDate, "
+        "adultCount, roomCount, childCount, childAges, infantCount, "
+        "sortCriteria, minPrice, maxPrice, filters, deepSearch, isNearMe, resetAction.\n\n"
+        "Rules:\n"
+        "- Dates are DDMMYYYY.\n"
+        '- deepSearch and isNearMe must be "true" or "false".\n'
+        "- filters is a comma-separated list of amenity/type phrases (e.g. "
+        '"swimming pool, pet friendly"); prefix removals with "no ".\n'
+        "- Omit unknown optional fields.\n\n"
+        f"today={today}\n"
+        f"query={query}"
+    )
+
+
+def format_completion(expected: dict[str, Any]) -> str:
+    """Stable-key-order minified JSON — the training target / gold serialization."""
+    ordered = {f: expected[f] for f in FIELD_ORDER if f in expected}
+    for k in expected:
+        if k not in ordered:
+            ordered[k] = expected[k]
+    return json.dumps(ordered, ensure_ascii=False, separators=(",", ":"))
+
+
+def extract_json(text: str) -> dict | None:
+    """Pull the first balanced {...} object out of raw model text."""
+    start = text.find("{")
+    if start < 0:
+        return None
+    depth = 0
+    in_str = esc = False
+    for i in range(start, len(text)):
+        c = text[i]
+        if esc:
+            esc = False
+            continue
+        if c == "\\":
+            esc = True
+            continue
+        if c == '"':
+            in_str = not in_str
+            continue
+        if in_str:
+            continue
+        if c == "{":
+            depth += 1
+        elif c == "}":
+            depth -= 1
+            if depth == 0:
+                try:
+                    return json.loads(text[start:i + 1])
+                except json.JSONDecodeError:
+                    return None
+    return None
+
+
+class HotelExtraction(BaseModel):
+    """Output contract. `filters` is a comma-separated PHRASE string (e.g.
+    "swimming pool, pet friendly"); a downstream matcher resolves it to codes."""
+    model_config = ConfigDict(extra="forbid")
+    deepSearch: Literal["true", "false"]
+    isNearMe: Literal["true", "false"]
+    destination: Optional[str] = Field(default=None, min_length=1)
+    locality: Optional[str] = Field(default=None, min_length=1)
+    hotelName: Optional[str] = Field(default=None, min_length=1)
+    checkinDate: Optional[str] = Field(default=None, pattern=r"^\d{8}$")
+    checkoutDate: Optional[str] = Field(default=None, pattern=r"^\d{8}$")
+    adultCount: Optional[int] = Field(default=None, ge=0, le=20)
+    roomCount: Optional[int] = Field(default=None, ge=0, le=20)
+    childCount: Optional[int] = Field(default=None, ge=0, le=20)
+    childAges: Optional[list[int]] = None
+    infantCount: Optional[int] = Field(default=None, ge=0, le=20)
+    sortCriteria: Optional[Literal["SC_P_LH", "SC_P_HL", "SC_UR", "SC_P", "SC_DIST"]] = None
+    minPrice: Optional[int] = Field(default=None, ge=0, le=10_000_000)
+    maxPrice: Optional[int] = Field(default=None, ge=0, le=10_000_000)
+    filters: Optional[str] = Field(default=None, min_length=1)
+    resetAction: Optional[Literal["filters", "guests", "dates", "all"]] = None
+
+
+def validate(d: dict) -> dict | None:
+    """Validate a parsed dict against the schema; return clean dict or None."""
+    try:
+        return HotelExtraction.model_validate(d).model_dump(exclude_none=True)
+    except ValidationError:
+        return None