UPDATE

config/rag_config.yaml

@@ -71,6 +71,11 @@ knowledge_bases:
     tone_file: "config/tones/water_need_prediction_tone.txt"
     description: "پایگاه دانش تفسير نياز آبي کوتاه مدت و برنامه ريزي آبياري"
 
+  yield_harvest:
+    path: "config/knowledge_base/chat"
+    tone_file: "config/tones/yield_harvest_tone.txt"
+    description: "پایگاه دانش روایت کاربرپسند برای داشبورد Yield & Harvest Summary"
+
 services:
   support_bot:
     knowledge_base: "chat"
@@ -176,3 +181,21 @@ services:
       api_key_env: "GAPGPT_API_KEY"
       avalai_base_url: "https://api.avalai.ir/v1"
       avalai_api_key_env: "AVALAI_API_KEY"
+
+  yield_harvest:
+    knowledge_base: "yield_harvest"
+    tone_file: "config/tones/yield_harvest_tone.txt"
+    use_user_embeddings: true
+    description: "سرویس روایت داشبورد عملکرد و برداشت"
+    fallback_behavior:
+      on_invalid_json: "return_mocked_narrative"
+      on_missing_context: "use_only_deterministic_data"
+      on_number_conflict: "prefer_deterministic_data"
+    prompt_template: "config/tones/yield_harvest_tone.txt"
+    llm:
+      provider: "gapgpt"
+      model: "gpt-4o"
+      base_url: "https://api.gapgpt.app/v1"
+      api_key_env: "GAPGPT_API_KEY"
+      avalai_base_url: "https://api.avalai.ir/v1"
+      avalai_api_key_env: "AVALAI_API_KEY"

config/tones/yield_harvest_tone.txt

@@ -0,0 +1,39 @@
+You are the narrative assistant for the Yield & Harvest Summary dashboard.
+
+Golden Rule:
+- Never generate, infer, estimate, or invent any new numbers, dates, percentages, KPIs, rankings, scores, or comparisons.
+- Only use values that already exist in the provided deterministic_data and farm_context.
+- If a number, date, or KPI is not present in the input context, do not mention it.
+- Do not rewrite a numeric value into a different value, rounded estimate, or alternative unit unless that converted value already exists in the context.
+
+Your job:
+- Turn deterministic dashboard data into short, user-friendly text.
+- Write subtitles, summaries, descriptions, and operation notes only.
+- Keep the wording clear, calm, and practical.
+- Preserve the meaning of deterministic blocks exactly.
+
+Output rules:
+- Do not add new facts.
+- Do not add agronomic claims that are not directly supported by the provided context.
+- Do not contradict deterministic_data.
+- If the context is incomplete, stay general and say less.
+- Prefer concise JSON-ready text fragments over long paragraphs.
+
+Allowed narrative targets:
+- season_highlights_card.subtitle
+- harvest_prediction_card.description
+- harvest_operations_card.summary
+- harvest_operations_card.steps[].note
+
+Forbidden behavior:
+- No fabricated harvest dates.
+- No fabricated yield values.
+- No fabricated readiness percentages.
+- No fabricated quality grades or market conclusions.
+- No speculative recommendations that depend on missing measurements.
+
+Tone:
+- Helpful
+- Professional
+- Simple
+- User-facing

crop_simulation/growth_simulation.py

@@ -5,6 +5,7 @@ from dataclasses import dataclass
 from datetime import date, datetime, timedelta
 from math import exp
 from typing import Any
+import logging
 
 from django.core.paginator import EmptyPage, Paginator
 
@@ -18,6 +19,7 @@ from .services import CropSimulationService, build_simulation_payload_from_farm
 DEFAULT_DYNAMIC_PARAMETERS = ["DVS", "LAI", "TAGP", "TWSO", "SM"]
 DEFAULT_PAGE_SIZE = 10
 MAX_PAGE_SIZE = 50
+logger = logging.getLogger(__name__)
 
 DEFAULT_STAGE_LABELS = {
     "pre_emergence": "پیش از سبز شدن",
@@ -56,6 +58,24 @@ def _safe_float(value: Any, default: float = 0.0) -> float:
         return default
 
 
+def _pick_first_not_none(*values: Any) -> Any:
+    for value in values:
+        if value is not None:
+            return value
+    return None
+
+
+def _clamp(value: float, minimum: float, maximum: float) -> float:
+    if minimum > maximum:
+        minimum, maximum = maximum, minimum
+    return max(minimum, min(value, maximum))
+
+
+def _mm_to_cm_day(value: Any, default: float) -> float:
+    scaled = _safe_float(value, default * 10.0) / 10.0
+    return round(max(scaled, 0.0), 4)
+
+
 def _coerce_date(value: Any) -> date:
     if isinstance(value, date) and not isinstance(value, datetime):
         return value
@@ -134,10 +154,11 @@ def _build_weather_from_farm(sensor: SensorData) -> list[dict[str, Any]]:
                 "TMAX": _safe_float(forecast.temperature_max, 24.0),
                 "VAP": max(_safe_float(forecast.humidity_mean, 55.0) / 5.0, 6.0),
                 "WIND": _safe_float(forecast.wind_speed_max, 7.2) / 3.6,
-                "RAIN": _safe_float(forecast.precipitation, 0.0),
+                # WeatherForecast stores precipitation/ET0 in mm/day, while PCSE expects cm/day.
-                "E0": _safe_float(forecast.et0, 0.35),
+                "RAIN": _mm_to_cm_day(forecast.precipitation, 0.0),
-                "ES0": max(_safe_float(forecast.et0, 0.35) * 0.9, 0.1),
+                "E0": _mm_to_cm_day(forecast.et0, 0.35),
-                "ET0": _safe_float(forecast.et0, 0.35),
+                "ES0": max(round(_mm_to_cm_day(forecast.et0, 0.35) * 0.9, 4), 0.1),
+                "ET0": _mm_to_cm_day(forecast.et0, 0.35),
             }
         )
     return records
@@ -148,6 +169,10 @@ def _build_soil_and_site_from_farm(sensor: SensorData) -> tuple[dict[str, Any],
     top_depth = depths[0] if depths else None
     smfcf = _safe_float(getattr(top_depth, "wv0033", None), 0.34)
     smw = _safe_float(getattr(top_depth, "wv1500", None), 0.14)
+    sm0 = _safe_float(
+        _pick_first_not_none(getattr(top_depth, "porosity", None), getattr(top_depth, "wv0000", None)),
+        min(max(smfcf + 0.08, smw + 0.12), 0.6),
+    )
     soil_moisture = None
     payload = sensor.sensor_payload or {}
     if isinstance(payload, dict):
@@ -155,8 +180,23 @@ def _build_soil_and_site_from_farm(sensor: SensorData) -> tuple[dict[str, Any],
             if isinstance(block, dict) and block.get("soil_moisture") is not None:
                 soil_moisture = _safe_float(block.get("soil_moisture"))
                 break
-    site = {"WAV": soil_moisture if soil_moisture is not None else 40.0}
+    site = {
-    soil = {"SMFCF": smfcf, "SMW": smw, "RDMSOL": 120.0}
+        "WAV": soil_moisture if soil_moisture is not None else 40.0,
+        "IFUNRN": 0,
+        "NOTINF": 0.0,
+        "SSI": 0.0,
+        "SSMAX": 0.0,
+        "SMLIM": round(_clamp(smfcf, smw, sm0), 3),
+    }
+    soil = {
+        "SMFCF": smfcf,
+        "SMW": smw,
+        "SM0": sm0,
+        "RDMSOL": 120.0,
+        "CRAIRC": 0.06,
+        "SOPE": 10.0,
+        "KSUB": 10.0,
+    }
     return soil, site
 
 
@@ -193,7 +233,8 @@ def _build_default_agromanagement(plant_name: str, weather: list[dict[str, Any]]
                 "TimedEvents": [],
                 "StateEvents": [],
             }
-        }
+        },
+        {},
     ]
 
 
@@ -286,8 +327,27 @@ def build_growth_context(payload: dict[str, Any]) -> GrowthSimulationContext:
         site_parameters = {**farm_site, **site_parameters}
     soil_parameters.setdefault("SMFCF", 0.34)
     soil_parameters.setdefault("SMW", 0.14)
+    soil_parameters.setdefault("SM0", 0.42)
     soil_parameters.setdefault("RDMSOL", 120.0)
+    soil_parameters.setdefault("CRAIRC", 0.06)
+    soil_parameters.setdefault("SOPE", 10.0)
+    soil_parameters.setdefault("KSUB", 10.0)
     site_parameters.setdefault("WAV", 40.0)
+    site_parameters.setdefault("IFUNRN", 0)
+    site_parameters.setdefault("NOTINF", 0.0)
+    site_parameters.setdefault("SSI", 0.0)
+    site_parameters.setdefault("SSMAX", 0.0)
+    site_parameters.setdefault(
+        "SMLIM",
+        round(
+            _clamp(
+                _safe_float(site_parameters.get("SMLIM"), soil_parameters.get("SMFCF", 0.34)),
+                _safe_float(soil_parameters.get("SMW"), 0.14),
+                _safe_float(soil_parameters.get("SM0"), 0.42),
+            ),
+            3,
+        ),
+    )
 
     agromanagement = deepcopy(
         payload.get("agromanagement")
@@ -402,7 +462,15 @@ def _run_simulation(context: GrowthSimulationContext) -> tuple[dict[str, Any], i
         )
         return response["result"], response.get("scenario_id"), None
     except Exception as exc:
-        raise GrowthSimulationError(f"Simulation engine failed: {exc}") from exc
+        logger.warning(
+            "Falling back to projection engine for farm_uuid=%s plant_name=%s because PCSE failed: %s",
+            context.farm_uuid,
+            context.plant_name,
+            exc,
+        )
+        fallback_result = _run_projection_engine(context)
+        warning = f"Simulation engine failed, fallback projection used: {exc}"
+        return fallback_result, None, warning
 
 
 def summarize_growth_stages(

crop_simulation/recommendation_optimizer.py

@@ -19,6 +19,11 @@ def _safe_float(value: Any, default: float = 0.0) -> float:
         return default
 
 
+def _mm_to_cm_day(value: Any, default: float) -> float:
+    scaled = _safe_float(value, default * 10.0) / 10.0
+    return round(max(scaled, 0.0), 4)
+
+
 def _clamp(value: float, lower: float, upper: float) -> float:
     return max(lower, min(value, upper))
 
@@ -113,7 +118,7 @@ def _build_weather_records(forecasts: list[Any], *, latitude: float, longitude:
         vap = max(6.0, round((humidity / 100.0) * 20.0, 3))
         wind_kmh = _safe_float(getattr(forecast, "wind_speed_max", None), 7.2)
         wind_ms = round(wind_kmh / 3.6, 3)
-        et0 = _safe_float(getattr(forecast, "et0", None), 0.35)
+        et0 = _mm_to_cm_day(getattr(forecast, "et0", None), 0.35)
         records.append(
             {
                 "DAY": forecast.forecast_date,
@@ -125,7 +130,7 @@ def _build_weather_records(forecasts: list[Any], *, latitude: float, longitude:
                 "TMAX": tmax,
                 "VAP": vap,
                 "WIND": wind_ms,
-                "RAIN": _safe_float(getattr(forecast, "precipitation", None), 0.0),
+                "RAIN": _mm_to_cm_day(getattr(forecast, "precipitation", None), 0.0),
                 "E0": et0,
                 "ES0": max(et0 * 0.9, 0.1),
                 "ET0": et0,

crop_simulation/serializers.py

@@ -127,3 +127,25 @@ class YieldPredictionResponseSerializer(serializers.Serializer):
     scenarioId = serializers.IntegerField(allow_null=True)
     simulationWarning = serializers.CharField(allow_null=True, allow_blank=True)
     supportingMetrics = serializers.JSONField()
+
+
+class YieldHarvestSummaryQuerySerializer(serializers.Serializer):
+    farm_uuid = serializers.UUIDField(required=True, help_text="شناسه یکتای مزرعه")
+    season_year = serializers.IntegerField(required=False, help_text="سال زراعی")
+    crop_name = serializers.CharField(required=False, allow_blank=True, help_text="نام محصول")
+    include_narrative = serializers.BooleanField(
+        required=False,
+        default=False,
+        help_text="در صورت true بودن، بخش روایت نیز در آینده اضافه می شود.",
+    )
+
+
+class YieldHarvestSummaryResponseSerializer(serializers.Serializer):
+    farm_uuid = serializers.CharField()
+    season_highlights_card = serializers.JSONField()
+    yield_prediction = serializers.JSONField()
+    harvest_prediction_card = serializers.JSONField()
+    harvest_readiness_zones = serializers.JSONField()
+    yield_quality_bands = serializers.JSONField()
+    harvest_operations_card = serializers.JSONField()
+    yield_prediction_chart = serializers.JSONField()

crop_simulation/services.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import importlib
 from copy import deepcopy
 from dataclasses import dataclass
-from datetime import date, datetime
+from datetime import date, datetime, timedelta
 from typing import Any
 
 from django.db import transaction
@@ -82,6 +82,11 @@ def _normalize_weather_records(weather: Any) -> list[dict[str, Any]]:
     return normalized
 
 
+def _mm_to_cm_day(value: Any, default: float) -> float:
+    scaled = _safe_float(value, default * 10.0) / 10.0
+    return round(max(scaled, 0.0), 4)
+
+
 def _normalize_agromanagement(agromanagement: Any) -> list[dict[str, Any]]:
     if isinstance(agromanagement, dict) and "AgroManagement" in agromanagement:
         campaigns = agromanagement["AgroManagement"]
@@ -94,7 +99,58 @@ def _normalize_agromanagement(agromanagement: Any) -> list[dict[str, Any]]:
 
     if not campaigns:
         raise CropSimulationError("Agromanagement input cannot be empty.")
-    return campaigns
+    return _ensure_trailing_empty_campaign(campaigns)
+
+
+def _ensure_trailing_empty_campaign(campaigns: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    normalized = list(campaigns)
+    if not normalized:
+        return normalized
+    last_campaign = normalized[-1]
+    if _is_explicit_empty_campaign(last_campaign):
+        return normalized
+
+    trailing = _build_trailing_empty_campaign(normalized)
+    if last_campaign == {}:
+        normalized[-1] = trailing
+    else:
+        normalized.append(trailing)
+    return normalized
+
+
+def _is_explicit_empty_campaign(campaign: dict[str, Any]) -> bool:
+    if not isinstance(campaign, dict) or len(campaign) != 1:
+        return False
+    start_date, payload = next(iter(campaign.items()))
+    return isinstance(start_date, date) and payload is None
+
+
+def _build_trailing_empty_campaign(campaigns: list[dict[str, Any]]) -> dict[date, None]:
+    last_campaign = next((item for item in reversed(campaigns) if isinstance(item, dict) and item), None)
+    if not last_campaign:
+        return {date.today(): None}
+
+    campaign_start, campaign_payload = next(iter(last_campaign.items()))
+    candidate_dates = [_coerce_date(campaign_start)]
+
+    if isinstance(campaign_payload, dict):
+        crop_calendar = campaign_payload.get("CropCalendar") or {}
+        for field_name in ("crop_end_date", "crop_start_date"):
+            value = crop_calendar.get(field_name)
+            if value:
+                candidate_dates.append(_coerce_date(value))
+
+        for bucket_name in ("TimedEvents",):
+            for event_group in campaign_payload.get(bucket_name, []) or []:
+                if not isinstance(event_group, dict):
+                    continue
+                for event in event_group.get("events_table", []) or []:
+                    if not isinstance(event, dict) or not event:
+                        continue
+                    event_date = next(iter(event.keys()))
+                    candidate_dates.append(_coerce_date(event_date))
+
+    return {max(candidate_dates) + timedelta(days=1): None}
 
 
 def _deep_copy_json_like(value: Any) -> Any:
@@ -296,7 +352,7 @@ def _build_default_agromanagement(crop_name: str, weather: list[dict[str, Any]])
     first_day = weather[0]["DAY"]
     last_day = weather[-1]["DAY"]
     crop_end = max(last_day, first_day + (last_day - first_day))
-    return [
+    return _ensure_trailing_empty_campaign([
         {
             first_day: {
                 "CropCalendar": {
@@ -312,7 +368,7 @@ def _build_default_agromanagement(crop_name: str, weather: list[dict[str, Any]])
                 "StateEvents": [],
             }
         }
-    ]
+    ])
 
 
 def _build_weather_from_forecasts(forecasts: list[Any], *, latitude: float, longitude: float) -> list[dict[str, Any]]:
@@ -333,10 +389,11 @@ def _build_weather_from_forecasts(forecasts: list[Any], *, latitude: float, long
             ),
             "VAP": max(_safe_float(forecast.humidity_mean, 55.0) / 5.0, 6.0),
             "WIND": _safe_float(forecast.wind_speed_max, 7.2) / 3.6,
-            "RAIN": _safe_float(forecast.precipitation, 0.0),
+            # WeatherForecast stores precipitation/ET0 in mm/day, while PCSE expects cm/day.
-            "E0": _safe_float(forecast.et0, 0.35),
+            "RAIN": _mm_to_cm_day(forecast.precipitation, 0.0),
-            "ES0": max(_safe_float(forecast.et0, 0.35) * 0.9, 0.1),
+            "E0": _mm_to_cm_day(forecast.et0, 0.35),
-            "ET0": _safe_float(forecast.et0, 0.35),
+            "ES0": max(round(_mm_to_cm_day(forecast.et0, 0.35) * 0.9, 4), 0.1),
+            "ET0": _mm_to_cm_day(forecast.et0, 0.35),
         }
         for forecast in forecasts
     ]
@@ -352,6 +409,17 @@ def _normalize_site_parameters_for_model(
     soil = soil_parameters or {}
 
     site.setdefault("WAV", _safe_float(site.get("WAV"), DEFAULT_WAV))
+    smw = _safe_float(soil.get("SMW"), 0.14)
+    smfcf = _safe_float(soil.get("SMFCF"), 0.34)
+    sm0 = _safe_float(
+        _pick_first_not_none(soil.get("SM0"), soil.get("SMMAX")),
+        min(max(smfcf + 0.08, smw + 0.12), 0.6),
+    )
+    site.setdefault("IFUNRN", 0)
+    site.setdefault("NOTINF", 0.0)
+    site.setdefault("SSI", 0.0)
+    site.setdefault("SSMAX", 0.0)
+    site.setdefault("SMLIM", round(_clamp(_safe_float(site.get("SMLIM"), smfcf), smw, sm0), 3))
     if model_name.startswith("Wofost81_NWLP"):
         navaili = _pick_first_not_none(
             site.get("NAVAILI"),
@@ -416,6 +484,14 @@ def build_simulation_payload_from_farm(
     top_depth = depths[0] if depths else None
     smfcf = _clamp(_safe_float(getattr(top_depth, "wv0033", None), 0.34), 0.2, 0.55)
     smw = _clamp(_safe_float(getattr(top_depth, "wv1500", None), 0.14), 0.05, max(smfcf - 0.02, 0.06))
+    sm0 = _clamp(
+        _safe_float(
+            _pick_first_not_none(getattr(top_depth, "porosity", None), getattr(top_depth, "wv0000", None)),
+            min(max(smfcf + 0.08, smw + 0.12), 0.6),
+        ),
+        max(smfcf + 0.02, smw + 0.05),
+        0.8,
+    )
     soil_moisture = _sensor_metric(farm, "soil_moisture")
     wav = (
         round(_clamp((soil_moisture or DEFAULT_WAV) / 100.0, smw, smfcf) * 100.0, 3)
@@ -431,7 +507,11 @@ def build_simulation_payload_from_farm(
     resolved_soil = {
         "SMFCF": round(smfcf, 3),
         "SMW": round(smw, 3),
+        "SM0": round(sm0, 3),
         "RDMSOL": 120.0,
+        "CRAIRC": 0.06,
+        "SOPE": 10.0,
+        "KSUB": 10.0,
         "soil_moisture": soil_moisture,
         "nitrogen": _safe_float(nitrogen, DEFAULT_NAVAILI),
         "phosphorus": _safe_float(phosphorus, 0.0),
@@ -454,6 +534,11 @@ def build_simulation_payload_from_farm(
         "K_STATUS": _safe_float(potassium, 0.0),
         "SOIL_PH": _safe_float(soil_ph, 7.0),
         "EC": _safe_float(ec, 0.0),
+        "IFUNRN": 0,
+        "NOTINF": 0.0,
+        "SSI": 0.0,
+        "SSMAX": 0.0,
+        "SMLIM": round(_clamp(_safe_float(_pick_first_not_none(site_parameters and site_parameters.get("SMLIM"), smfcf), smfcf), smw, sm0), 3),
     }
     if site_parameters:
         resolved_site.update(site_parameters)
@@ -469,10 +554,11 @@ def build_simulation_payload_from_farm(
         resolved_crop.update(crop_parameters)
     resolved_crop.setdefault("crop_name", plant_name or getattr(plant, "name", "crop"))
     resolved_crop.setdefault("farm_uuid", str(farm_uuid))
-    resolved_crop.setdefault("soil_ph", _safe_float(soil_ph, 7.0))
     resolved_crop.setdefault("soil_nitrogen", _safe_float(nitrogen, DEFAULT_NAVAILI))
     resolved_crop.setdefault("soil_phosphorus", _safe_float(phosphorus, 0.0))
     resolved_crop.setdefault("soil_potassium", _safe_float(potassium, 0.0))
+    # Keep pH in soil/site payloads only; duplicating it in cropdata breaks some PCSE parameter providers.
+    resolved_crop.pop("soil_ph", None)
 
     default_agromanagement = (
         deepcopy(simulation_profile.get("agromanagement"))

crop_simulation/test_growth_simulation_api.py

@@ -102,6 +102,19 @@ class PlantGrowthSimulationApiTests(TestCase):
         self.assertEqual(response.status_code, 202)
         self.assertEqual(response.json()["data"]["task_id"], "growth-task-1")
 
+    def test_queue_api_returns_400_for_missing_weather_and_farm_uuid(self):
+        response = self.client.post(
+            "/growth/",
+            data={
+                "plant_name": self.plant.name,
+                "dynamic_parameters": ["DVS", "LAI"],
+            },
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 400)
+        self.assertEqual(response.json()["code"], 400)
+
     @patch("crop_simulation.views._get_async_result")
     def test_status_api_returns_paginated_stages(self, mock_get_async_result):
         stage_timeline = [
@@ -159,6 +172,31 @@ class PlantGrowthSimulationApiTests(TestCase):
         self.assertEqual(len(payload["stages_page"]), 1)
         self.assertEqual(payload["stages_page"][0]["stage_code"], "vegetative")
 
+    @patch("crop_simulation.views._get_async_result")
+    def test_status_api_returns_pending_state(self, mock_get_async_result):
+        mock_get_async_result.return_value = SimpleNamespace(state="PENDING")
+
+        response = self.client.get("/growth/growth-task-1/status/")
+
+        self.assertEqual(response.status_code, 200)
+        payload = response.json()["data"]
+        self.assertEqual(payload["status"], "PENDING")
+        self.assertIn("message", payload)
+
+    @patch("crop_simulation.views._get_async_result")
+    def test_status_api_returns_failure_state(self, mock_get_async_result):
+        mock_get_async_result.return_value = SimpleNamespace(
+            state="FAILURE",
+            result=RuntimeError("task crashed"),
+        )
+
+        response = self.client.get("/growth/growth-task-1/status/")
+
+        self.assertEqual(response.status_code, 200)
+        payload = response.json()["data"]
+        self.assertEqual(payload["status"], "FAILURE")
+        self.assertEqual(payload["error"], "task crashed")
+
     @patch("crop_simulation.views.apps.get_app_config")
     def test_current_farm_chart_api_returns_simulation_payload(self, mock_get_app_config):
         mock_simulator = SimpleNamespace(
@@ -218,6 +256,37 @@ class PlantGrowthSimulationApiTests(TestCase):
         self.assertEqual(payload["current_state"]["leaf_count_estimate"], 140.0)
         self.assertEqual(payload["series"][0]["key"], "leaf_count_estimate")
 
+    def test_current_farm_chart_api_returns_400_for_missing_farm_uuid(self):
+        response = self.client.post(
+            "/current-farm-chart/",
+            data={"plant_name": self.plant.name},
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 400)
+        self.assertEqual(response.json()["code"], 400)
+
+    @patch("crop_simulation.views.apps.get_app_config")
+    def test_current_farm_chart_api_returns_500_when_simulator_fails(self, mock_get_app_config):
+        mock_simulator = SimpleNamespace(
+            simulate=lambda **_kwargs: (_ for _ in ()).throw(RuntimeError("simulator offline"))
+        )
+        mock_get_app_config.return_value = SimpleNamespace(
+            get_current_farm_chart_simulator=lambda: mock_simulator
+        )
+
+        response = self.client.post(
+            "/current-farm-chart/",
+            data={
+                "farm_uuid": "550e8400-e29b-41d4-a716-446655440000",
+                "plant_name": self.plant.name,
+            },
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 500)
+        self.assertEqual(response.json()["code"], 500)
+
     @patch("crop_simulation.views.apps.get_app_config")
     def test_harvest_prediction_api_returns_payload(self, mock_get_app_config):
         mock_service = SimpleNamespace(
@@ -254,6 +323,38 @@ class PlantGrowthSimulationApiTests(TestCase):
         self.assertEqual(payload["daysUntil"], 43)
         self.assertEqual(payload["gddDetails"]["simulation_engine"], "growth_projection")
 
+    def test_harvest_prediction_api_returns_400_for_missing_farm_uuid(self):
+        response = self.client.post(
+            "/harvest-prediction/",
+            data={"plant_name": self.plant.name},
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 400)
+        self.assertEqual(response.json()["code"], 400)
+
+    @patch("crop_simulation.views.apps.get_app_config")
+    def test_harvest_prediction_api_returns_500_when_service_fails(self, mock_get_app_config):
+        class BrokenService:
+            def get_harvest_prediction(self, **_kwargs):
+                raise RuntimeError("harvest offline")
+
+        mock_get_app_config.return_value = SimpleNamespace(
+            get_harvest_prediction_service=lambda: BrokenService()
+        )
+
+        response = self.client.post(
+            "/harvest-prediction/",
+            data={
+                "farm_uuid": "550e8400-e29b-41d4-a716-446655440000",
+                "plant_name": self.plant.name,
+            },
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 500)
+        self.assertEqual(response.json()["code"], 500)
+
     @patch("crop_simulation.views.apps.get_app_config")
     def test_yield_prediction_api_returns_payload(self, mock_get_app_config):
         mock_service = SimpleNamespace(
@@ -288,3 +389,70 @@ class PlantGrowthSimulationApiTests(TestCase):
         payload = response.json()["data"]
         self.assertEqual(payload["predictedYieldTons"], 5.4)
         self.assertEqual(payload["sourceUnit"], "kg/ha")
+
+    def test_yield_prediction_api_returns_400_for_missing_farm_uuid(self):
+        response = self.client.post(
+            "/yield-prediction/",
+            data={"plant_name": self.plant.name},
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 400)
+        self.assertEqual(response.json()["code"], 400)
+
+    @patch("crop_simulation.views.apps.get_app_config")
+    def test_yield_prediction_api_returns_500_when_service_fails(self, mock_get_app_config):
+        class BrokenService:
+            def get_yield_prediction(self, **_kwargs):
+                raise RuntimeError("yield offline")
+
+        mock_get_app_config.return_value = SimpleNamespace(
+            get_yield_prediction_service=lambda: BrokenService()
+        )
+
+        response = self.client.post(
+            "/yield-prediction/",
+            data={
+                "farm_uuid": "550e8400-e29b-41d4-a716-446655440000",
+                "plant_name": self.plant.name,
+            },
+            format="json",
+        )
+
+        self.assertEqual(response.status_code, 500)
+        self.assertEqual(response.json()["code"], 500)
+
+    @patch("crop_simulation.views.YieldHarvestSummaryService")
+    def test_yield_harvest_summary_api_returns_payload(self, mock_service_cls):
+        mock_service_cls.return_value.get_summary.return_value = {
+            "farm_uuid": "550e8400-e29b-41d4-a716-446655440000",
+            "season_highlights_card": {"title": "Season highlights", "subtitle": "Good season."},
+            "yield_prediction": {"predicted_yield_tons": 5.4, "explanation": "Stable projection."},
+            "harvest_prediction_card": {"harvest_date": "2026-05-14"},
+            "harvest_readiness_zones": {"averageReadiness": 74, "summary": "Readiness improving."},
+            "yield_quality_bands": {"primary_quality_grade": "A"},
+            "harvest_operations_card": {"steps": [{"key": "harvesting", "note": "Prepare combine."}]},
+            "yield_prediction_chart": {"series": [], "xAxis": {"type": "datetime"}},
+        }
+
+        response = self.client.get(
+            "/yield-harvest-summary/?farm_uuid=550e8400-e29b-41d4-a716-446655440000"
+            "&season_year=1404&crop_name=wheat&include_narrative=true"
+        )
+
+        self.assertEqual(response.status_code, 200)
+        payload = response.json()["data"]
+        self.assertEqual(payload["farm_uuid"], "550e8400-e29b-41d4-a716-446655440000")
+        self.assertEqual(payload["yield_quality_bands"]["primary_quality_grade"], "A")
+        mock_service_cls.return_value.get_summary.assert_called_once_with(
+            farm_uuid="550e8400-e29b-41d4-a716-446655440000",
+            season_year="1404",
+            crop_name="wheat",
+            include_narrative=True,
+        )
+
+    def test_yield_harvest_summary_api_returns_400_for_missing_farm_uuid(self):
+        response = self.client.get("/yield-harvest-summary/?season_year=1404&crop_name=wheat")
+
+        self.assertEqual(response.status_code, 400)
+        self.assertEqual(response.json()["code"], 400)

crop_simulation/urls.py

@@ -5,6 +5,7 @@ from .views import (
     HarvestPredictionView,
     PlantGrowthSimulationStatusView,
     PlantGrowthSimulationView,
+    YieldHarvestSummaryView,
     YieldPredictionView,
 )
 
@@ -12,6 +13,7 @@ from .views import (
 urlpatterns = [
     path("current-farm-chart/", CurrentFarmSimulationChartView.as_view(), name="current-farm-chart"),
     path("harvest-prediction/", HarvestPredictionView.as_view(), name="harvest-prediction"),
+    path("yield-harvest-summary/", YieldHarvestSummaryView.as_view(), name="yield-harvest-summary"),
     path("yield-prediction/", YieldPredictionView.as_view(), name="yield-prediction"),
     path("growth/", PlantGrowthSimulationView.as_view(), name="growth-simulation"),
     path(

crop_simulation/views.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from django.apps import apps
 
-from drf_spectacular.utils import OpenApiExample, extend_schema
+from drf_spectacular.utils import OpenApiExample, OpenApiParameter, extend_schema
 from rest_framework import status
 from rest_framework.response import Response
 from rest_framework.views import APIView
@@ -22,10 +22,13 @@ from .serializers import (
     GrowthSimulationResultSerializer,
     HarvestPredictionRequestSerializer,
     HarvestPredictionResponseSerializer,
+    YieldHarvestSummaryQuerySerializer,
+    YieldHarvestSummaryResponseSerializer,
     YieldPredictionRequestSerializer,
     YieldPredictionResponseSerializer,
 )
 from .tasks import run_growth_simulation_task
+from .yield_harvest_summary import YieldHarvestSummaryService
 
 
 GrowthSimulationQueuedResponseSerializer = build_envelope_serializer(
@@ -196,6 +199,10 @@ YieldPredictionEnvelopeSerializer = build_envelope_serializer(
     "YieldPredictionEnvelopeSerializer",
     YieldPredictionResponseSerializer,
 )
+YieldHarvestSummaryEnvelopeSerializer = build_envelope_serializer(
+    "YieldHarvestSummaryEnvelopeSerializer",
+    YieldHarvestSummaryResponseSerializer,
+)
 
 
 class CurrentFarmSimulationChartView(APIView):
@@ -349,3 +356,91 @@ class YieldPredictionView(APIView):
                 status=status.HTTP_500_INTERNAL_SERVER_ERROR,
             )
         return Response({"code": 200, "msg": "success", "data": result}, status=status.HTTP_200_OK)
+
+
+class YieldHarvestSummaryView(APIView):
+    @extend_schema(
+        tags=["Crop Simulation"],
+        summary="خلاصه عملکرد و برداشت",
+        description=(
+            "خروجی داشبورد Yield & Harvest Summary را با اتکا به داده های قطعی شبیه سازی برمی گرداند. "
+            "فعلا پاسخ به صورت mock با کارت های خالی بازگردانده می شود."
+        ),
+        parameters=[
+            OpenApiParameter(
+                name="farm_uuid",
+                type=str,
+                location=OpenApiParameter.QUERY,
+                required=True,
+                description="شناسه یکتای مزرعه",
+            ),
+            OpenApiParameter(
+                name="season_year",
+                type=int,
+                location=OpenApiParameter.QUERY,
+                required=False,
+                description="سال زراعی",
+            ),
+            OpenApiParameter(
+                name="crop_name",
+                type=str,
+                location=OpenApiParameter.QUERY,
+                required=False,
+                description="نام محصول",
+            ),
+            OpenApiParameter(
+                name="include_narrative",
+                type=bool,
+                location=OpenApiParameter.QUERY,
+                required=False,
+                description="در آینده روایت متنی را نیز اضافه می کند.",
+            ),
+        ],
+        responses={
+            200: build_response(
+                YieldHarvestSummaryEnvelopeSerializer,
+                "خروجی خلاصه عملکرد و برداشت مزرعه.",
+            ),
+            400: build_response(
+                GrowthSimulationErrorSerializer,
+                "پارامترهای query نامعتبر است.",
+            ),
+        },
+        examples=[
+            OpenApiExample(
+                "نمونه پاسخ yield harvest summary",
+                value={
+                    "code": 200,
+                    "msg": "success",
+                    "data": {
+                        "farm_uuid": "11111111-1111-1111-1111-111111111111",
+                        "season_highlights_card": {},
+                        "yield_prediction": {},
+                        "harvest_prediction_card": {},
+                        "harvest_readiness_zones": {},
+                        "yield_quality_bands": {},
+                        "harvest_operations_card": {},
+                        "yield_prediction_chart": {},
+                    },
+                },
+                response_only=True,
+            ),
+        ],
+    )
+    def get(self, request):
+        serializer = YieldHarvestSummaryQuerySerializer(data=request.query_params)
+        if not serializer.is_valid():
+            return Response(
+                {"code": 400, "msg": "داده نامعتبر.", "data": serializer.errors},
+                status=status.HTTP_400_BAD_REQUEST,
+            )
+
+        validated = serializer.validated_data
+        service = YieldHarvestSummaryService()
+        payload = service.get_summary(
+            farm_uuid=str(validated["farm_uuid"]),
+            season_year=str(validated.get("season_year") or ""),
+            crop_name=validated.get("crop_name") or "",
+            include_narrative=validated.get("include_narrative", False),
+        )
+        return Response({"code": 200, "msg": "success", "data": payload}, status=status.HTTP_200_OK)

crop_simulation/yield_harvest_summary.py

@@ -0,0 +1,985 @@
+from __future__ import annotations
+
+import copy
+import logging
+import math
+from datetime import date, datetime
+from typing import Any, Callable
+
+from django.apps import apps
+from django.conf import settings
+
+from farm_data.models import SensorData
+from farm_data.services import get_farm_details
+from location_data.models import NdviObservation, SoilLocation
+
+from rag.services.yield_harvest import YieldHarvestRAGService
+
+logger = logging.getLogger(__name__)
+
+
+class YieldHarvestSummaryService:
+    def get_summary(
+        self,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool = True,
+    ) -> dict[str, Any]:
+        farm_context = self._get_farm_context(farm_uuid)
+        farm_context["season_year"] = season_year
+        farm_context["crop_name"] = crop_name or farm_context.get("crop_name") or ""
+        yield_prediction = self._build_yield_prediction(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+        )
+        harvest_prediction_card = self._build_harvest_prediction_card(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+        )
+        harvest_readiness_zones = self._build_harvest_readiness_zones(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+        )
+        yield_quality_bands = self._build_yield_quality_bands(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+        )
+        harvest_operations_card = self._build_harvest_operations_card(
+            farm_context=farm_context,
+            harvest_prediction_card=harvest_prediction_card,
+            pcse_dvs_stage=self._extract_pcse_dvs_stage(harvest_prediction_card),
+        )
+        yield_prediction_chart = self._build_yield_prediction_chart(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+        )
+        season_highlights_card = self._build_season_highlights_card(
+            farm_uuid=farm_uuid,
+            season_year=season_year,
+            crop_name=crop_name,
+            include_narrative=include_narrative,
+            farm_context=farm_context,
+            yield_prediction=yield_prediction,
+            harvest_prediction_card=harvest_prediction_card,
+            harvest_readiness_zones=harvest_readiness_zones,
+            yield_quality_bands=yield_quality_bands,
+        )
+
+        deterministic_payload = {
+            "farm_uuid": farm_uuid,
+            "season_highlights_card": season_highlights_card,
+            "yield_prediction": yield_prediction,
+            "harvest_prediction_card": harvest_prediction_card,
+            "harvest_readiness_zones": harvest_readiness_zones,
+            "yield_quality_bands": yield_quality_bands,
+            "harvest_operations_card": harvest_operations_card,
+            "yield_prediction_chart": yield_prediction_chart,
+        }
+        context_payload = {
+            **copy.deepcopy(deterministic_payload),
+            "farm_context": farm_context,
+        }
+
+        if not include_narrative:
+            return deterministic_payload
+
+        try:
+            rag_service = YieldHarvestRAGService()
+            narrative_data = rag_service.generate_narrative(context_payload)
+        except Exception as exc:
+            logger.warning(
+                "Yield harvest narrative generation failed for farm_uuid=%s: %s",
+                farm_uuid,
+                exc,
+            )
+            narrative_data = {}
+        return self._merge_narrative(deterministic_payload, narrative_data)
+
+    def _build_yield_prediction(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        service = apps.get_app_config("crop_simulation").get_yield_prediction_service()
+        result = service.get_yield_prediction(
+            farm_uuid=farm_uuid,
+            plant_name=crop_name or None,
+        )
+        supporting_metrics = dict(result.get("supportingMetrics") or {})
+
+        # Secondary KPIs are placeholders until dedicated deterministic formulas land.
+        supporting_metrics.setdefault(
+            "estimatedKpis",
+            {
+                "season_year": season_year,
+                "applied_rule": "simple_placeholder_rules",
+                "is_estimated": True,
+            },
+        )
+
+        return {
+            "farm_uuid": result.get("farm_uuid", farm_uuid),
+            "crop_name": result.get("plant_name") or crop_name,
+            "season_year": season_year,
+            "predicted_yield_tons": result.get("predictedYieldTons"),
+            "predicted_yield_raw": result.get("predictedYieldRaw"),
+            "unit": result.get("unit"),
+            "source_unit": result.get("sourceUnit"),
+            "simulation_engine": result.get("simulationEngine"),
+            "simulation_model": result.get("simulationModel"),
+            "scenario_id": result.get("scenarioId"),
+            "simulation_warning": result.get("simulationWarning"),
+            "secondary_kpis_estimated": True,
+            "descriptionSource": "deterministic",
+            "farm_context": {
+                "soil_type": farm_context.get("soil", {}).get("soil_type"),
+                "soil_data_provider": farm_context.get("soil", {}).get("provider"),
+            },
+            "supporting_metrics": supporting_metrics,
+        }
+
+    def _build_harvest_prediction_card(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        service = apps.get_app_config("crop_simulation").get_harvest_prediction_service()
+        result = service.get_harvest_prediction(
+            farm_uuid=farm_uuid,
+            plant_name=crop_name or None,
+        )
+
+        fallback_description = (
+            f"Deterministic harvest forecast for {crop_name or 'the selected crop'} "
+            f"in season {season_year}."
+        )
+
+        return {
+            "farm_uuid": farm_uuid,
+            "crop_name": crop_name,
+            "season_year": season_year,
+            "harvest_date": result.get("date"),
+            "harvest_date_formatted": result.get("dateFormatted"),
+            "days_until": result.get("daysUntil"),
+            "optimal_window_start": result.get("optimalWindowStart"),
+            "optimal_window_end": result.get("optimalWindowEnd"),
+            "description": result.get("description") or fallback_description,
+            "descriptionSource": "deterministic",
+            "field_conditions": {
+                "soil_moisture": farm_context.get("recent_sensor_averages", {}).get("soil_moisture"),
+                "soil_temperature": farm_context.get("recent_sensor_averages", {}).get("soil_temperature"),
+            },
+            "readiness_metrics": result.get("gddDetails") or {},
+        }
+
+    def _build_yield_prediction_chart(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        simulator = apps.get_app_config("crop_simulation").get_current_farm_chart_simulator()
+        result = simulator.simulate(
+            farm_uuid=farm_uuid,
+            plant_name=crop_name or None,
+        )
+        pcse_timeseries = list(result.get("daily_output") or [])
+
+        yield_series: list[list[float]] = []
+        biomass_series: list[list[float]] = []
+        for item in pcse_timeseries:
+            timestamp = self._to_unix_timestamp(item.get("DAY"))
+            if timestamp is None:
+                continue
+
+            twso = self._safe_chart_value(item.get("TWSO"))
+            if twso is not None:
+                yield_series.append([timestamp, twso])
+
+            tagp = self._safe_chart_value(item.get("TAGP"))
+            if tagp is not None:
+                biomass_series.append([timestamp, tagp])
+
+        return {
+            "farm_uuid": farm_uuid,
+            "crop_name": result.get("plant_name") or crop_name,
+            "season_year": season_year,
+            "series": [
+                {
+                    "name": "Predicted Yield",
+                    "type": "line",
+                    "data": yield_series,
+                },
+                {
+                    "name": "Biomass",
+                    "type": "area",
+                    "data": biomass_series,
+                },
+            ],
+            "xAxis": {"type": "datetime"},
+            "meta": {
+                "unit": "kg/ha",
+                "simulation_engine": result.get("engine"),
+                "simulation_model": result.get("model_name"),
+                "scenario_id": result.get("scenario_id"),
+                "simulation_warning": result.get("simulation_warning"),
+                "field_context": {
+                    "soil_type": farm_context.get("soil", {}).get("soil_type"),
+                    "center_coordinates": farm_context.get("center_coordinates"),
+                },
+            },
+        }
+
+    def _build_harvest_operations_card(
+        self,
+        *,
+        farm_context: dict[str, Any],
+        harvest_prediction_card: dict[str, Any],
+        pcse_dvs_stage: float,
+    ) -> dict[str, Any]:
+        days_until = int(harvest_prediction_card.get("days_until") or 0)
+        stage_label, phase_name = self._map_dvs_to_phase(pcse_dvs_stage)
+        steps = self._build_operations_steps(
+            phase_name=phase_name,
+            days_until=days_until,
+            soil_moisture=farm_context.get("recent_sensor_averages", {}).get("soil_moisture"),
+        )
+
+        return {
+            "farm_uuid": farm_context.get("farm_uuid"),
+            "crop_name": farm_context.get("crop_name"),
+            "season_year": farm_context.get("season_year"),
+            "stage_label": stage_label,
+            "phase_name": phase_name,
+            "days_until_harvest": days_until,
+            "current_dvs": round(pcse_dvs_stage, 4),
+            "summary": (
+                f"Operations are prioritized for {farm_context.get('crop_name') or 'the selected crop'} "
+                f"with {days_until} days remaining until the predicted harvest window."
+            ),
+            "rules_source": "deterministic_dvs_rules",
+            "field_context": {
+                "soil_type": farm_context.get("soil", {}).get("soil_type"),
+                "soil_moisture": farm_context.get("recent_sensor_averages", {}).get("soil_moisture"),
+                "soil_temperature": farm_context.get("recent_sensor_averages", {}).get("soil_temperature"),
+            },
+            "steps": steps,
+        }
+
+    def _build_season_highlights_card(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+        yield_prediction: dict[str, Any],
+        harvest_prediction_card: dict[str, Any],
+        harvest_readiness_zones: dict[str, Any],
+        yield_quality_bands: dict[str, Any],
+    ) -> dict[str, Any]:
+        primary_quality_grade = (
+            yield_quality_bands.get("primary_quality_grade")
+            or yield_quality_bands.get("top_band")
+            or yield_quality_bands.get("summary")
+        )
+        average_readiness = harvest_readiness_zones.get("averageReadiness")
+        total_predicted_yield = yield_prediction.get("predicted_yield_tons")
+        target_harvest_date = (
+            harvest_prediction_card.get("harvest_date_formatted")
+            or harvest_prediction_card.get("harvest_date")
+        )
+        estimated_revenue = self._get_estimated_revenue(
+            farm_uuid=farm_uuid,
+            total_predicted_yield=total_predicted_yield,
+        )
+        return {
+            "farm_uuid": farm_uuid,
+            "crop_name": crop_name,
+            "season_year": season_year,
+            "title": "Season highlights",
+            # Left blank for narrative merge unless a non-LLM fallback is needed later.
+            "subtitle": "",
+            "total_predicted_yield": total_predicted_yield,
+            "yield_unit": yield_prediction.get("unit"),
+            "target_harvest_date": target_harvest_date,
+            "days_until_harvest": harvest_prediction_card.get("days_until"),
+            "average_readiness": average_readiness,
+            "primary_quality_grade": primary_quality_grade,
+            "estimated_revenue": estimated_revenue,
+            "soil_type": farm_context.get("soil", {}).get("soil_type"),
+        }
+
+    def _build_harvest_readiness_zones(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        sensor = (
+            SensorData.objects.select_related("center_location")
+            .filter(farm_uuid=farm_uuid)
+            .first()
+        )
+        if sensor is None or sensor.center_location is None:
+            return {
+                "farm_uuid": farm_uuid,
+                "averageReadiness": None,
+                "zones": [],
+                "source": "ndvi_health_service",
+            }
+
+        location = sensor.center_location
+        ndvi_service = apps.get_app_config("location_data").get_ndvi_health_service()
+        health_card = ndvi_service.get_ndvi_health(farm_uuid=farm_uuid)
+
+        observations = list(
+            location.ndvi_observations.order_by("-observation_date", "-created_at")[:2]
+        )
+        latest_observation = observations[0] if observations else None
+        previous_observation = observations[1] if len(observations) > 1 else None
+
+        latest_ndvi = self._safe_float(health_card.get("mean_ndvi"), None)
+        previous_ndvi = self._safe_float(
+            previous_observation.mean_ndvi if previous_observation else None,
+            None,
+        )
+        ndvi_trend = None
+        if latest_ndvi is not None and previous_ndvi is not None:
+            ndvi_trend = round(latest_ndvi - previous_ndvi, 4)
+
+        grid = {}
+        if latest_observation and isinstance(latest_observation.ndvi_map, dict):
+            grid = latest_observation.ndvi_map
+        ndvi_grid = grid.get("grid") if isinstance(grid, dict) else None
+
+        zones: list[dict[str, Any]] = []
+        if isinstance(ndvi_grid, list) and ndvi_grid:
+            zone_index = 1
+            for row_index, row in enumerate(ndvi_grid):
+                if not isinstance(row, list):
+                    continue
+                for col_index, cell in enumerate(row):
+                    cell_ndvi = self._safe_chart_value(cell)
+                    if cell_ndvi is None:
+                        continue
+                    readiness = self._ndvi_to_readiness(cell_ndvi, ndvi_trend)
+                    zones.append(
+                        {
+                            "zoneId": f"zone-{zone_index}",
+                            "zoneLabel": f"Zone {zone_index}",
+                            "gridPosition": {"row": row_index, "col": col_index},
+                            "meanNdvi": cell_ndvi,
+                            "readiness": readiness,
+                            "daysUntil": self._estimate_days_until_from_readiness(readiness),
+                            "status": self._readiness_status(readiness),
+                        }
+                    )
+                    zone_index += 1
+
+        if not zones and latest_ndvi is not None:
+            readiness = self._ndvi_to_readiness(latest_ndvi, ndvi_trend)
+            zones.append(
+                {
+                    "zoneId": "zone-center",
+                    "zoneLabel": "Center field zone",
+                    "gridPosition": None,
+                    "meanNdvi": latest_ndvi,
+                    "readiness": readiness,
+                    "daysUntil": self._estimate_days_until_from_readiness(readiness),
+                    "status": self._readiness_status(readiness),
+                }
+            )
+
+        average_readiness = None
+        if zones:
+            average_readiness = round(
+                sum(zone["readiness"] for zone in zones) / len(zones),
+                2,
+            )
+
+        return {
+            "farm_uuid": farm_uuid,
+            "observationDate": (
+                latest_observation.observation_date.isoformat()
+                if latest_observation
+                else health_card.get("observation_date")
+            ),
+            "vegetationHealthClass": health_card.get("vegetation_health_class"),
+            "meanNdvi": latest_ndvi,
+            "ndviTrend": ndvi_trend,
+            "averageReadiness": average_readiness,
+            "zones": zones,
+            "source": "ndvi_health_service",
+        }
+
+    def _to_unix_timestamp(self, value: Any) -> int | None:
+        if isinstance(value, datetime):
+            return int(value.timestamp() * 1000)
+        if isinstance(value, date):
+            return int(datetime.combine(value, datetime.min.time()).timestamp() * 1000)
+        if isinstance(value, str):
+            try:
+                if "T" in value:
+                    parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
+                else:
+                    parsed = datetime.combine(date.fromisoformat(value), datetime.min.time())
+                return int(parsed.timestamp() * 1000)
+            except ValueError:
+                return None
+        return None
+
+    def _safe_chart_value(self, value: Any) -> float | None:
+        parsed = self._safe_float(value, None)
+        if parsed is None or math.isnan(parsed) or math.isinf(parsed):
+            return None
+        return round(parsed, 4)
+
+    def _ndvi_to_readiness(self, mean_ndvi: float, trend_delta: float | None) -> int:
+        base_score = ((0.75 - mean_ndvi) / 0.55) * 100.0
+        if trend_delta is not None and trend_delta < 0:
+            # A falling NDVI near season end suggests drying and harvest readiness.
+            base_score += min(abs(trend_delta) * 120.0, 18.0)
+        if trend_delta is not None and trend_delta > 0.05:
+            base_score -= min(trend_delta * 80.0, 12.0)
+        return int(round(max(0.0, min(base_score, 100.0))))
+
+    def _estimate_days_until_from_readiness(self, readiness: int) -> int:
+        return max(int(round((100 - readiness) / 12.0)), 0)
+
+    def _readiness_status(self, readiness: int) -> str:
+        if readiness >= 80:
+            return "ready"
+        if readiness >= 55:
+            return "approaching"
+        if readiness >= 30:
+            return "monitoring"
+        return "not_ready"
+
+    def _build_yield_quality_bands(
+        self,
+        *,
+        farm_uuid: str,
+        season_year: str,
+        crop_name: str,
+        include_narrative: bool,
+        farm_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        crop_key = (crop_name or farm_context.get("crop_name") or "").strip().lower()
+        yield_service = apps.get_app_config("crop_simulation").get_yield_prediction_service()
+        yield_payload = yield_service.get_yield_prediction(
+            farm_uuid=farm_uuid,
+            plant_name=crop_name or None,
+        )
+        predicted_yield_raw = self._safe_float(yield_payload.get("predictedYieldRaw"), 0.0) or 0.0
+        soil_metrics = farm_context.get("soil", {}).get("resolved_metrics") or {}
+        sensor_metrics = farm_context.get("recent_sensor_averages") or {}
+
+        try:
+            service = self._resolve_service(
+                getter_names=(
+                    "get_yield_quality_bands_service",
+                    "get_quality_grading_service",
+                    "get_quality_model_service",
+                )
+            )
+            method = self._resolve_service_method(
+                service,
+                method_names=(
+                    "get_yield_quality_bands",
+                    "get_quality_bands",
+                    "grade_yield_quality",
+                ),
+            )
+            return method(
+                farm_uuid=farm_uuid,
+                season_year=season_year,
+                crop_name=crop_name or None,
+                include_narrative=include_narrative,
+            )
+        except AttributeError:
+            pass
+
+        protein_content = self._estimate_protein_content(
+            crop_key=crop_key,
+            nitrogen_value=self._safe_float(soil_metrics.get("nitrogen"), None),
+            predicted_yield_raw=predicted_yield_raw,
+        )
+        moisture_percent = self._estimate_moisture_percent(
+            crop_key=crop_key,
+            soil_moisture=sensor_metrics.get("soil_moisture"),
+        )
+        quality_score = self._estimate_quality_score(
+            protein_content=protein_content,
+            moisture_percent=moisture_percent,
+            predicted_yield_raw=predicted_yield_raw,
+        )
+        grade_distribution = self._build_grade_distribution(quality_score)
+        primary_quality_grade = max(
+            grade_distribution,
+            key=lambda item: item.get("share_percent", 0),
+        )["grade"]
+
+        return {
+            "farm_uuid": farm_uuid,
+            "crop_name": crop_name,
+            "season_year": season_year,
+            "source": "deterministic_grading_rules",
+            "is_estimated": True,
+            "protein_content": {
+                "value": protein_content,
+                "unit": "%",
+            },
+            "moisture_percentage": {
+                "value": moisture_percent,
+                "unit": "%",
+            },
+            "grade_distribution": grade_distribution,
+            "primary_quality_grade": primary_quality_grade,
+            "quality_score": quality_score,
+            "summary": f"Primary quality grade is {primary_quality_grade}.",
+        }
+
+    def _get_estimated_revenue(
+        self,
+        *,
+        farm_uuid: str,
+        total_predicted_yield: float | None,
+    ) -> float | None:
+        try:
+            service = apps.get_app_config("economy").get_economic_overview_service()
+            overview = service.get_economic_overview(farm_uuid=farm_uuid)
+        except Exception:
+            return None
+
+        if not isinstance(overview, dict):
+            return None
+
+        price_per_ton = None
+        for item in overview.get("economicData") or []:
+            if not isinstance(item, dict):
+                continue
+            title = str(item.get("title") or "").lower()
+            value = item.get("value")
+            if "price" in title or "قیمت" in title:
+                price_per_ton = self._extract_numeric(value)
+                break
+
+        if price_per_ton is None or total_predicted_yield is None:
+            return None
+        return round(total_predicted_yield * price_per_ton, 2)
+
+    def _estimate_protein_content(
+        self,
+        *,
+        crop_key: str,
+        nitrogen_value: float | None,
+        predicted_yield_raw: float,
+    ) -> float:
+        nitrogen_factor = 0.0 if nitrogen_value is None else min(nitrogen_value / 2500.0, 2.0)
+        yield_factor = min(predicted_yield_raw / 10000.0, 1.5)
+        if "wheat" in crop_key or "گندم" in crop_key:
+            base = 11.8
+            return round(base + (nitrogen_factor * 1.2) - (yield_factor * 0.35), 2)
+        if "barley" in crop_key or "جو" in crop_key:
+            base = 10.4
+            return round(base + (nitrogen_factor * 0.9) - (yield_factor * 0.25), 2)
+        return round(9.5 + (nitrogen_factor * 0.8), 2)
+
+    def _estimate_moisture_percent(
+        self,
+        *,
+        crop_key: str,
+        soil_moisture: float | None,
+    ) -> float:
+        soil_component = 0.0 if soil_moisture is None else min(max((soil_moisture - 20.0) / 10.0, -2.0), 4.0)
+        if "wheat" in crop_key or "barley" in crop_key or "گندم" in crop_key or "جو" in crop_key:
+            return round(12.6 + soil_component, 2)
+        return round(11.8 + soil_component, 2)
+
+    def _estimate_quality_score(
+        self,
+        *,
+        protein_content: float,
+        moisture_percent: float,
+        predicted_yield_raw: float,
+    ) -> int:
+        protein_score = min(max((protein_content / 14.0) * 50.0, 0.0), 50.0)
+        moisture_penalty = min(abs(moisture_percent - 12.5) * 4.5, 22.0)
+        yield_bonus = min(predicted_yield_raw / 1500.0, 18.0)
+        score = protein_score + yield_bonus + 32.0 - moisture_penalty
+        return int(round(max(0.0, min(score, 100.0))))
+
+    def _build_grade_distribution(self, quality_score: int) -> list[dict[str, Any]]:
+        if quality_score >= 85:
+            return [
+                {"grade": "A", "share_percent": 62},
+                {"grade": "B", "share_percent": 28},
+                {"grade": "C", "share_percent": 10},
+            ]
+        if quality_score >= 70:
+            return [
+                {"grade": "A", "share_percent": 38},
+                {"grade": "B", "share_percent": 44},
+                {"grade": "C", "share_percent": 18},
+            ]
+        return [
+            {"grade": "A", "share_percent": 16},
+            {"grade": "B", "share_percent": 41},
+            {"grade": "C", "share_percent": 43},
+        ]
+
+    def _extract_numeric(self, value: Any) -> float | None:
+        if isinstance(value, (int, float)):
+            return float(value)
+        if not isinstance(value, str):
+            return None
+        cleaned = "".join(ch for ch in value if ch.isdigit() or ch in {".", "-"})
+        return self._safe_float(cleaned, None)
+
+    def _get_farm_context(
+        self,
+        farm_uuid: str,
+    ) -> dict[str, Any]:
+        farm = (
+            SensorData.objects.select_related("center_location", "weather_forecast")
+            .prefetch_related("center_location__depths", "plants")
+            .filter(farm_uuid=farm_uuid)
+            .first()
+        )
+        if farm is None:
+            return {
+                "farm_uuid": farm_uuid,
+                "center_coordinates": None,
+                "soil": {"provider": getattr(settings, "SOIL_DATA_PROVIDER", "unknown")},
+                "recent_sensor_averages": {},
+            }
+
+        farm_details = get_farm_details(str(farm_uuid)) or {}
+        center_location = farm.center_location
+        soil_details = (farm_details.get("soil") or {}).get("resolved_metrics") or {}
+        weather_details = farm_details.get("weather") or {}
+        recent_sensor_averages = {
+            "soil_moisture": self._safe_float(soil_details.get("soil_moisture", farm.soil_moisture), None),
+            "soil_temperature": self._safe_float(soil_details.get("soil_temperature", farm.soil_temperature), None),
+            "air_temperature_mean": self._safe_float(weather_details.get("temperature_mean"), None),
+        }
+
+        crop_name = ""
+        plant_names = farm_details.get("plants") or []
+        if plant_names:
+            first_plant = plant_names[0]
+            if isinstance(first_plant, dict):
+                crop_name = str(first_plant.get("name") or "")
+
+        return {
+            "farm_uuid": farm_uuid,
+            "crop_name": crop_name,
+            "center_coordinates": {
+                "lat": float(center_location.latitude),
+                "lon": float(center_location.longitude),
+            },
+            "farm_boundary": farm_details.get("center_location", {}).get("farm_boundary"),
+            "soil": {
+                "provider": getattr(settings, "SOIL_DATA_PROVIDER", "unknown"),
+                "soil_type": self._infer_soil_type(soil_details),
+                "resolved_metrics": soil_details,
+            },
+            "recent_sensor_averages": recent_sensor_averages,
+            "weather": {
+                "temperature_mean": self._safe_float(weather_details.get("temperature_mean"), None),
+                "temperature_min": self._safe_float(weather_details.get("temperature_min"), None),
+                "temperature_max": self._safe_float(weather_details.get("temperature_max"), None),
+            },
+            "source_models": {
+                "sensor_data": SensorData.__name__,
+                "soil_location": SoilLocation.__name__,
+            },
+        }
+
+    def _extract_pcse_dvs_stage(self, harvest_prediction_card: dict[str, Any]) -> float:
+        readiness_metrics = harvest_prediction_card.get("readiness_metrics") or {}
+        forecast = readiness_metrics.get("daily_gdd_forecast") or [{}]
+        return self._safe_float(forecast[-1].get("development_stage"), 0.0) or 0.0
+
+    def _map_dvs_to_phase(self, dvs: float) -> tuple[str, str]:
+        if dvs >= 2.0:
+            return "ready", "maturity"
+        if dvs >= 1.7:
+            return "final_pre_harvest", "late_reproductive"
+        if dvs >= 1.2:
+            return "mid_pre_harvest", "grain_fill"
+        if dvs >= 0.8:
+            return "monitoring", "reproductive_transition"
+        return "early_pre_harvest", "vegetative"
+
+    def _build_operations_steps(
+        self,
+        *,
+        phase_name: str,
+        days_until: int,
+        soil_moisture: float | None,
+    ) -> list[dict[str, Any]]:
+        field_ready = soil_moisture is None or soil_moisture <= 35.0
+
+        if phase_name == "maturity":
+            return [
+                {
+                    "key": "desiccation",
+                    "title": "Desiccation check",
+                    "status": "ready",
+                    "is_completed": False,
+                    "estimated_days": 0,
+                },
+                {
+                    "key": "harvesting",
+                    "title": "Harvesting",
+                    "status": "ready" if field_ready else "watch_field_conditions",
+                    "is_completed": False,
+                    "estimated_days": max(min(days_until, 2), 0),
+                },
+                {
+                    "key": "transportation",
+                    "title": "Transportation",
+                    "status": "ready",
+                    "is_completed": False,
+                    "estimated_days": max(min(days_until + 1, 3), 1),
+                },
+            ]
+        if phase_name == "late_reproductive":
+            return [
+                {
+                    "key": "equipment_check",
+                    "title": "Inspect harvest equipment",
+                    "status": "priority",
+                    "is_completed": False,
+                    "estimated_days": 1,
+                },
+                {
+                    "key": "labor_plan",
+                    "title": "Confirm labor and transport plan",
+                    "status": "priority",
+                    "is_completed": False,
+                    "estimated_days": 2,
+                },
+                {
+                    "key": "field_entry",
+                    "title": "Verify field access and dry windows",
+                    "status": "ready" if field_ready else "monitor",
+                    "is_completed": False,
+                    "estimated_days": max(min(days_until, 5), 1),
+                },
+            ]
+        if phase_name == "grain_fill":
+            return [
+                {
+                    "key": "monitor_maturity",
+                    "title": "Track maturity and storage organ growth",
+                    "status": "active",
+                    "is_completed": False,
+                    "estimated_days": 7,
+                },
+                {
+                    "key": "review_readiness",
+                    "title": "Review zone readiness differences",
+                    "status": "active",
+                    "is_completed": False,
+                    "estimated_days": 10,
+                },
+                {
+                    "key": "prepare_logistics",
+                    "title": "Prepare harvest logistics plan",
+                    "status": "upcoming",
+                    "is_completed": False,
+                    "estimated_days": 14,
+                },
+            ]
+        return [
+            {
+                "key": "weekly_monitoring",
+                "title": "Run weekly crop maturity checks",
+                "status": "active",
+                "is_completed": False,
+                "estimated_days": 14,
+            },
+            {
+                "key": "update_forecast",
+                "title": "Refresh harvest timing forecast",
+                "status": "active",
+                "is_completed": False,
+                "estimated_days": 10,
+            },
+            {
+                "key": "draft_operations",
+                "title": "Draft harvest operation checklist",
+                "status": "upcoming",
+                "is_completed": False,
+                "estimated_days": 21,
+            },
+        ]
+
+    def _infer_soil_type(self, soil_metrics: dict[str, Any]) -> str | None:
+        sand = self._safe_float(soil_metrics.get("sand"), None)
+        clay = self._safe_float(soil_metrics.get("clay"), None)
+        silt = self._safe_float(soil_metrics.get("silt"), None)
+        if sand is None or clay is None or silt is None:
+            return None
+        if clay >= 40:
+            return "clay"
+        if sand >= 70 and clay <= 15:
+            return "sandy"
+        if silt >= 50 and clay < 27:
+            return "silty_loam"
+        return "loam"
+
+    def _safe_float(self, value: Any, default: float | None = 0.0) -> float | None:
+        try:
+            if value in (None, ""):
+                return default
+            return float(value)
+        except (TypeError, ValueError):
+            return default
+
+    def _merge_narrative(
+        self,
+        final_payload: dict[str, Any],
+        narratives: dict[str, Any],
+    ) -> dict[str, Any]:
+        merged = copy.deepcopy(final_payload)
+        if not isinstance(narratives, dict):
+            narratives = {}
+
+        season_card = merged.setdefault("season_highlights_card", {})
+        fallback_subtitle = self._default_season_highlights_subtitle(merged)
+        season_card["subtitle"] = self._coalesce_text(
+            narratives.get("season_highlights_subtitle"),
+            season_card.get("subtitle"),
+            fallback_subtitle,
+        )
+
+        yield_card = merged.setdefault("yield_prediction", {})
+        fallback_yield_explanation = self._default_yield_prediction_explanation(merged)
+        yield_card["explanation"] = self._coalesce_text(
+            narratives.get("yield_prediction_explanation"),
+            yield_card.get("explanation"),
+            fallback_yield_explanation,
+        )
+
+        readiness_card = merged.setdefault("harvest_readiness_zones", {})
+        fallback_readiness_summary = self._default_harvest_readiness_summary(merged)
+        readiness_card["summary"] = self._coalesce_text(
+            narratives.get("harvest_readiness_summary"),
+            readiness_card.get("summary"),
+            fallback_readiness_summary,
+        )
+
+        operations_card = merged.setdefault("harvest_operations_card", {})
+        deterministic_steps = operations_card.get("steps")
+        operation_notes = narratives.get("operation_notes")
+        if isinstance(deterministic_steps, list):
+            note_items = operation_notes if isinstance(operation_notes, list) else []
+            for index, step in enumerate(deterministic_steps):
+                if not isinstance(step, dict):
+                    continue
+                fallback_note = self._default_operation_note(step)
+                candidate_note = note_items[index] if index < len(note_items) else None
+                step["note"] = self._coalesce_text(
+                    candidate_note,
+                    step.get("note"),
+                    fallback_note,
+                )
+
+        return merged
+
+    def _coalesce_text(self, *values: Any) -> str:
+        for value in values:
+            if isinstance(value, str) and value.strip():
+                return value.strip()
+        return ""
+
+    def _default_season_highlights_subtitle(self, payload: dict[str, Any]) -> str:
+        highlights = payload.get("season_highlights_card") or {}
+        total_yield = highlights.get("total_predicted_yield")
+        unit = highlights.get("yield_unit") or ""
+        harvest_date = highlights.get("target_harvest_date") or "the predicted harvest window"
+        if total_yield is None:
+            return f"Harvest is targeted for {harvest_date} based on the deterministic season outlook."
+        return f"Predicted yield is {total_yield} {unit} and harvest is targeted for {harvest_date}.".strip()
+
+    def _default_yield_prediction_explanation(self, payload: dict[str, Any]) -> str:
+        yield_card = payload.get("yield_prediction") or {}
+        predicted = yield_card.get("predicted_yield_tons")
+        unit = yield_card.get("unit") or ""
+        if predicted is None:
+            return "Yield forecast is based on the deterministic crop simulation output."
+        return f"Yield forecast is based on the deterministic crop simulation and currently projects {predicted} {unit}.".strip()
+
+    def _default_harvest_readiness_summary(self, payload: dict[str, Any]) -> str:
+        readiness = payload.get("harvest_readiness_zones") or {}
+        average = readiness.get("averageReadiness")
+        if average is None:
+            return "Harvest readiness is derived from the latest deterministic zone signals."
+        return f"Average harvest readiness is {average} based on the latest deterministic zone signals.".strip()
+
+    def _default_operation_note(self, step: dict[str, Any]) -> str:
+        title = step.get("title") or "This operation"
+        status = step.get("status") or "planned"
+        estimate = step.get("estimated_days")
+        if estimate is None:
+            return f"{title} is currently marked as {status}."
+        return f"{title} is {status} with an estimated timing of {estimate} days.".strip()
+
+    def _resolve_service(self, *, getter_names: tuple[str, ...]) -> Any:
+        app_config = apps.get_app_config("crop_simulation")
+        for getter_name in getter_names:
+            getter = getattr(app_config, getter_name, None)
+            if callable(getter):
+                return getter()
+        raise AttributeError(
+            f"None of the expected service getters were found on crop_simulation app config: {getter_names}"
+        )
+
+    def _resolve_service_method(
+        self,
+        service: Any,
+        *,
+        method_names: tuple[str, ...],
+    ) -> Callable[..., dict[str, Any]]:
+        for method_name in method_names:
+            method = getattr(service, method_name, None)
+            if callable(method):
+                return method
+        raise AttributeError(
+            f"None of the expected service methods were found on {service.__class__.__name__}: {method_names}"
+        )

rag/services/__init__.py

@@ -7,6 +7,7 @@ from .fertilization import get_fertilization_recommendation
 from .pest_disease import get_pest_disease_detection, get_pest_disease_risk
 from .soil_anomaly import get_soil_anomaly_insight
 from .water_need_prediction import get_water_need_prediction_insight
+from .yield_harvest import YieldHarvestRAGService
 
 __all__ = [
     "get_irrigation_recommendation",
@@ -15,4 +16,5 @@ __all__ = [
     "get_pest_disease_risk",
     "get_soil_anomaly_insight",
     "get_water_need_prediction_insight",
+    "YieldHarvestRAGService",
 ]

rag/services/yield_harvest.py

@@ -0,0 +1,227 @@
+from __future__ import annotations
+
+import json
+import logging
+from typing import Any
+
+from pydantic import BaseModel, Field, ValidationError
+
+from rag.api_provider import get_chat_client
+from rag.chat import (
+    _complete_audit_log,
+    _create_audit_log,
+    _fail_audit_log,
+    _load_service_tone,
+)
+from rag.config import RAGConfig, get_service_config, load_rag_config
+
+logger = logging.getLogger(__name__)
+
+SERVICE_ID = "yield_harvest"
+
+YIELD_HARVEST_PROMPT = (
+    "You are an expert agronomist writing concise dashboard narratives for farmers. "
+    "Return only valid JSON matching this schema exactly: "
+    "{"
+    '"season_highlights_subtitle": string, '
+    '"yield_prediction_explanation": string, '
+    '"harvest_readiness_summary": string, '
+    '"operation_notes": [string, ...]'
+    "}. "
+    "Do not add markdown, explanations, or extra keys. "
+    "Strict Golden Rule: do not invent numbers, dates, prices, revenues, percentages, KPIs, scores, or measurements. "
+    "Use only values already present in the deterministic context. "
+    "If a fact is missing from the context, say less rather than guessing."
+)
+
+
+class YieldHarvestNarrativeSchema(BaseModel):
+    season_highlights_subtitle: str
+    yield_prediction_explanation: str
+    harvest_readiness_summary: str
+    operation_notes: list[str] = Field(default_factory=list)
+
+
+class YieldHarvestRAGService:
+    def generate_narrative(
+        self,
+        deterministic_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        cfg = load_rag_config()
+        service, client, model = self._build_service_client(cfg)
+        structured_context = self._build_structured_context(
+            deterministic_context=deterministic_context,
+        )
+        user_prompt = (
+            "Generate short user-friendly narrative fields for the Yield & Harvest Summary dashboard "
+            "using only the deterministic context. Keep the language practical and agronomy-focused."
+        )
+        system_prompt, messages = self._build_messages(
+            service=service,
+            cfg=cfg,
+            structured_context=structured_context,
+            query=user_prompt,
+        )
+
+        farm_uuid = str(deterministic_context.get("farm_uuid") or "")
+        audit_log = None
+        if farm_uuid:
+            try:
+                audit_log = _create_audit_log(
+                    farm_uuid=farm_uuid,
+                    service_id=SERVICE_ID,
+                    model=model,
+                    query=user_prompt,
+                    system_prompt=system_prompt,
+                    messages=messages,
+                )
+            except Exception as exc:
+                logger.warning("Yield harvest audit log creation failed for %s: %s", farm_uuid, exc)
+
+        try:
+            response = client.chat.completions.create(
+                model=model,
+                messages=messages,
+                response_format={"type": "json_object"},
+            )
+            raw = (response.choices[0].message.content or "").strip()
+            parsed = self._clean_json(raw)
+            validated = YieldHarvestNarrativeSchema.model_validate(parsed)
+            if audit_log is not None:
+                _complete_audit_log(audit_log, raw)
+            return {
+                "season_highlights_subtitle": validated.season_highlights_subtitle,
+                "yield_prediction_explanation": validated.yield_prediction_explanation,
+                "harvest_readiness_summary": validated.harvest_readiness_summary,
+                "operation_notes": validated.operation_notes,
+            }
+        except (ValidationError, ValueError, KeyError, IndexError) as exc:
+            logger.warning("Yield harvest narrative parsing failed for farm_uuid=%s: %s", farm_uuid, exc)
+            if audit_log is not None:
+                _fail_audit_log(audit_log, str(exc))
+            return {}
+        except Exception as exc:
+            logger.error("Yield harvest narrative LLM call failed for farm_uuid=%s: %s", farm_uuid, exc)
+            if audit_log is not None:
+                _fail_audit_log(audit_log, str(exc))
+            return {}
+
+    def _build_service_client(self, cfg: RAGConfig):
+        service = get_service_config(SERVICE_ID, cfg)
+        service_cfg = RAGConfig(
+            embedding=cfg.embedding,
+            qdrant=cfg.qdrant,
+            chunking=cfg.chunking,
+            llm=service.llm,
+            knowledge_bases=cfg.knowledge_bases,
+            services=cfg.services,
+            chromadb=cfg.chromadb,
+        )
+        client = get_chat_client(service_cfg)
+        return service, client, service.llm.model
+
+    def _build_messages(
+        self,
+        *,
+        service: Any,
+        cfg: RAGConfig,
+        structured_context: dict[str, Any],
+        query: str,
+    ) -> tuple[str, list[dict[str, str]]]:
+        tone = _load_service_tone(service, cfg)
+        system_parts = [tone] if tone else []
+        if service.system_prompt:
+            system_parts.append(service.system_prompt)
+        system_parts.append(YIELD_HARVEST_PROMPT)
+        system_parts.append(
+            "[deterministic_context]\n"
+            + json.dumps(structured_context, ensure_ascii=False, indent=2, default=str)
+        )
+        system_prompt = "\n\n".join(part for part in system_parts if part)
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": query},
+        ]
+        return system_prompt, messages
+
+    def _build_structured_context(
+        self,
+        *,
+        deterministic_context: dict[str, Any],
+    ) -> dict[str, Any]:
+        season = deterministic_context.get("season_highlights_card") or {}
+        harvest = deterministic_context.get("harvest_prediction_card") or {}
+        operations = deterministic_context.get("harvest_operations_card") or {}
+        yield_prediction = deterministic_context.get("yield_prediction") or {}
+        readiness = deterministic_context.get("harvest_readiness_zones") or {}
+
+        operation_steps = []
+        for step in operations.get("steps") or []:
+            if not isinstance(step, dict):
+                continue
+            operation_steps.append(
+                {
+                    "key": step.get("key"),
+                    "title": step.get("title"),
+                    "status": step.get("status"),
+                }
+            )
+
+        return {
+            "farm_context": deterministic_context.get("farm_context") or {},
+            "yield_prediction": {
+                "predicted_yield_tons": yield_prediction.get("predicted_yield_tons"),
+                "unit": yield_prediction.get("unit"),
+                "simulation_warning": yield_prediction.get("simulation_warning"),
+                "supporting_metrics": yield_prediction.get("supporting_metrics"),
+            },
+            "season_highlights_card": {
+                "title": season.get("title"),
+                "subtitle": season.get("subtitle"),
+                "total_predicted_yield": season.get("total_predicted_yield"),
+                "yield_unit": season.get("yield_unit"),
+                "target_harvest_date": season.get("target_harvest_date"),
+                "days_until_harvest": season.get("days_until_harvest"),
+                "average_readiness": season.get("average_readiness"),
+                "primary_quality_grade": season.get("primary_quality_grade"),
+                "estimated_revenue": season.get("estimated_revenue"),
+            },
+            "harvest_prediction_card": {
+                "harvest_date": harvest.get("harvest_date"),
+                "harvest_date_formatted": harvest.get("harvest_date_formatted"),
+                "days_until": harvest.get("days_until"),
+                "optimal_window_start": harvest.get("optimal_window_start"),
+                "optimal_window_end": harvest.get("optimal_window_end"),
+                "description": harvest.get("description"),
+            },
+            "harvest_readiness_zones": {
+                "average_readiness": readiness.get("averageReadiness"),
+                "mean_ndvi": readiness.get("meanNdvi"),
+                "ndvi_trend": readiness.get("ndviTrend"),
+                "zones": readiness.get("zones"),
+            },
+            "harvest_operations_card": {
+                "stage_label": operations.get("stage_label"),
+                "days_until_harvest": operations.get("days_until_harvest"),
+                "current_dvs": operations.get("current_dvs"),
+                "summary": operations.get("summary"),
+                "steps": operation_steps,
+            },
+        }
+
+    def _clean_json(self, raw: str) -> dict[str, Any]:
+        cleaned = (raw or "").strip()
+        if cleaned.startswith("```"):
+            cleaned = cleaned.strip("`")
+            if cleaned.startswith("json"):
+                cleaned = cleaned[4:]
+            cleaned = cleaned.strip()
+        if not cleaned:
+            raise ValueError("Yield harvest narrative response was empty.")
+        try:
+            parsed = json.loads(cleaned)
+        except (json.JSONDecodeError, ValueError) as exc:
+            raise ValueError("Yield harvest narrative response was not valid JSON.") from exc
+        if not isinstance(parsed, dict):
+            raise ValueError("Yield harvest narrative response root must be a JSON object.")
+        return parsed