Fix four correctness bugs surfaced in the post-MOS-rip diagnostic (#3)

1. Unit mismatch: KAMIS publishes KES per kg; pipeline expected per quintal
Result: SMS showed "Net: KES 14/qtl" for a maize farmer because the
optimizer subtracted per-quintal transport costs from a per-kg price.
Fix: normalize to KES/quintal at both KAMIS PriceRecord creation sites
(demo CSV reader and live API) via a named KG_TO_QUINTAL=100 constant.

2. CI bounds missing for 14d/30d horizons
Neon's price_forecasts rows had ci_lower/ci_upper NULL for 14d and 30d.
Root cause: pipeline.py:1075-1088 only copied ci_lower_7d/ci_upper_7d
into the dict sent to save_pipeline_run; the other four CI fields from
the PriceForecast dataclass were dropped. Fix: include all six CI keys.

3. Swahili SMS leaked the example greeting's name
FMR-K0003's SMS started "Habari Wanjiku, Owino Muriuki,". The translation
prompt said "start naturally, like 'Habari Wanjiku...'" — Claude copied
the example name verbatim before the real farmer's name. Fix: rewrite
the prompt to instruct preserving the English source's farmer name
exactly; remove the now-unused local_greeting_example config key.

4. Optimizer conflated three empty-result cases as "No mandis in range"
FMR-K0003's bean farmer got "No mandis in range" even though all 11
Kenya markets trade beans — the real issue was that KAMIS had no bean
prices in today's ingest. Fix: distinguish
- "{commodity} not traded at tracked markets" (config gap)
- "No recent price data for {commodity}" (ingest gap)
- "No markets in range" (true distance constraint)

32 tests pass.

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/ingestion/kamis.py

@@ -44,6 +44,12 @@ log = logging.getLogger(__name__)
 
 # --- KAMIS portal configuration -----------------------------------------
 
+# KAMIS publishes prices in KES per kilogram. The rest of the MI pipeline
+# (storage costs, transport costs, mandi fees, forecast training data) uses
+# KES per quintal (100 kg) — matching the Indian Agmarknet convention. All
+# PriceRecord emits in this module apply this conversion.
+KG_TO_QUINTAL = 100
+
 PORTAL_BASE_URL = "https://kamis.kilimo.go.ke/site/market_search"
 
 KAMIS_ATTRIBUTION = (
@@ -463,13 +469,16 @@ def _load_demo_snapshot(
             min_price = _safe_float(row.get("Min Price")) or modal
             max_price = _safe_float(row.get("Max Price")) or modal
             arrivals = _safe_float(row.get("Arrivals (Tonnes)")) or 0.0
+            # KAMIS publishes KES per kg; the rest of the pipeline expects
+            # per-quintal (100 kg) — matching Agmarknet's convention and the
+            # transport/storage/fee constants in optimizer.py. Normalize here.
             results[_market_id(market_obj)].append(PriceRecord(
                 mandi_id=_market_id(market_obj),
                 commodity_id=commodity["id"],
                 date=price_date.strftime("%Y-%m-%d"),
-                min_price_rs=min_price,
-                max_price_rs=max_price,
-                modal_price_rs=modal,
+                min_price_rs=min_price * KG_TO_QUINTAL,
+                max_price_rs=max_price * KG_TO_QUINTAL,
+                modal_price_rs=modal * KG_TO_QUINTAL,
                 arrivals_tonnes=arrivals,
                 source="kamis",
                 freshness_hours=24.0,
@@ -549,8 +558,11 @@ def _to_price_record(
     and retail as `max_price_rs`. `arrivals_tonnes` stays 0 because
     KAMIS's "volume" field is an unconfirmed unit.
     """
-    wholesale = float(raw["wholesale"])
-    retail = float(raw["retail"])
+    # KAMIS publishes KES per kg; the rest of the pipeline expects
+    # per-quintal (100 kg) — matching Agmarknet's convention and the
+    # transport/storage/fee constants in optimizer.py. Normalize here.
+    wholesale = float(raw["wholesale"]) * KG_TO_QUINTAL
+    retail = float(raw["retail"]) * KG_TO_QUINTAL
     return PriceRecord(
         mandi_id=_market_id(market),
         commodity_id=commodity["id"],

src/optimizer.py

@@ -201,7 +201,24 @@ def optimize_sell(
     all_options.sort(key=lambda o: o.net_price_rs, reverse=True)
 
     if not all_options:
-        # No mandis found -- return empty recommendation
+        # Distinguish between the three distinct empty-result cases so the
+        # farmer-facing message is honest:
+        #   1. Commodity not traded at any tracked market (config gap)
+        #   2. Commodity traded somewhere, but no recent price data (ingest
+        #      gap — e.g. KAMIS had no bean prices today)
+        #   3. Data exists but everything is beyond max_distance_km
+        mandis_trading = [m for m in MANDIS if commodity_id in m.commodities_traded]
+        mandis_with_prices = [
+            m for m in mandis_trading
+            if reconciled_prices.get(m.mandi_id, {}).get(commodity_id, {}).get("price_rs", 0) > 0
+        ]
+        if not mandis_trading:
+            fallback_label = f"{commodity_name} not traded at tracked markets"
+        elif not mandis_with_prices:
+            fallback_label = f"No recent price data for {commodity_name}"
+        else:
+            fallback_label = "No markets in range"
+
         return SellRecommendation(
             commodity_id=commodity_id,
             commodity_name=commodity_name,
@@ -209,7 +226,7 @@ def optimize_sell(
             farmer_lat=farmer_lat,
             farmer_lon=farmer_lon,
             best_option=SellOption(
-                mandi_id="", mandi_name="No mandis in range",
+                mandi_id="", mandi_name=fallback_label,
                 commodity_id=commodity_id, sell_timing="now",
                 market_price_rs=0, transport_cost_rs=0, storage_loss_rs=0,
                 storage_cost_rs=0, mandi_fee_rs=0, net_price_rs=0,

src/pipeline.py

@@ -1083,6 +1083,10 @@ class MarketIntelligencePipeline:
                     "price_30d": fc.price_30d,
                     "ci_lower_7d": fc.ci_lower_7d,
                     "ci_upper_7d": fc.ci_upper_7d,
+                    "ci_lower_14d": fc.ci_lower_14d,
+                    "ci_upper_14d": fc.ci_upper_14d,
+                    "ci_lower_30d": fc.ci_lower_30d,
+                    "ci_upper_30d": fc.ci_upper_30d,
                     "direction": fc.direction,
                     "confidence": fc.confidence,
                 })

src/recommendation_agent.py

@@ -38,7 +38,6 @@ REGION_CONFIG: dict[str, dict[str, str]] = {
         "market_type": "mandi",
         "local_language_name": "Tamil",
         "local_language_code": "ta",
-        "local_greeting_example": "வணக்கம் Lakshmi...",
         "typical_crops": "paddy, cotton, turmeric, groundnut",
         "phone_country_code": "+91",
     },
@@ -50,7 +49,6 @@ REGION_CONFIG: dict[str, dict[str, str]] = {
         "market_type": "market",
         "local_language_name": "Swahili",
         "local_language_code": "sw",
-        "local_greeting_example": "Habari Wanjiku...",
         "typical_crops": "dry maize, beans, Irish potatoes, green grams",
         "phone_country_code": "+254",
     },
@@ -181,7 +179,9 @@ _TRANSLATION_PROMPT_TEMPLATE = (
     "Translate the following agricultural sell recommendation into {local_language_name}. "
     "Keep all numbers, {market_type} names, and {currency_symbol} amounts as-is. "
     "Use simple, conversational {local_language_name} that a rural farmer would "
-    "understand (e.g. start naturally, like \"{local_greeting_example}\"). "
+    "understand. If the English text opens with a greeting and a farmer's name, "
+    "translate the greeting naturally but keep the farmer's name exactly as "
+    "written in the English source — do NOT substitute any other name. "
     "Do not add any preamble -- just output the {local_language_name} text.\n\n"
 )