Deploy from GitHub: e41cf0cdffa82676b7c2034ffdca57d930b5e475

app/routers/disease.py

@@ -17,7 +17,10 @@ def _looks_agri_product(title: str | None, source: str | None) -> bool:
     text = f"{title or ''} {source or ''}".lower()
     agri_keywords = [
         "fungicide", "pesticide", "insecticide", "herbicide", "fertilizer",
-        "agri", "agriculture", "crop", "plant", "seed", "biofungicide"
+        "agri", "agriculture", "crop", "plant", "seed", "biofungicide",
+        "garden", "horticulture", "foliar", "micronutrient", "nutrient",
+        "calcium", "magnesium", "zinc", "boron", "sulfate", "sulphate",
+        "npk", "chelate", "soil conditioner", "plant tonic"
     ]
     bad_keywords = [
         "amplifier", "speaker", "audio", "guitar", "home", "quilt", "comforter"
@@ -38,11 +41,19 @@ async def process_disease(request: DiseaseRequest):
     seen_links = set()
     for item in extracted_products:
         product_name = (item.get("name") or "").strip() if isinstance(item, dict) else ""
+        category = (item.get("category") or "other").strip().lower() if isinstance(item, dict) else "other"
         if not product_name:
             continue
 
-        # Enrich search query so generic names do not fetch irrelevant products.
-        search_query = f"{product_name} agricultural fungicide pesticide crop treatment india"
+        # Use category-aware query; previous fungicide-only bias caused misses for nutrient disorders.
+        if category == "nutrient":
+            suffix = "agriculture plant nutrient foliar spray india"
+        elif category in ("fungicide", "pesticide", "bio"):
+            suffix = f"agriculture {category} crop treatment india"
+        else:
+            suffix = "agriculture crop plant treatment india"
+
+        search_query = f"{product_name} {suffix}"
         search_results = search_shopping(search_query)
         shopping = search_results.get('shopping', [])
 

app/services/llm_service.py

@@ -1,5 +1,6 @@
 import json
 import base64
+import re
 from app.config import settings
 
 try:
@@ -76,11 +77,45 @@ def detect_disease(image_data: str, query: str = ""):
 
 
 def extract_agri_products(detection_text: str):
+    def _heuristic_product_candidates(text: str):
+        # Fallback parser from chemical solution sections when model extraction is empty/invalid.
+        candidates = []
+        seen = set()
+
+        patterns = [
+            r"active\s+ingredient\(s\)\s*:\s*(.+)",
+            r"product\s+type\s*:\s*(.+)",
+            r"recommended\s+products?\s*:\s*(.+)",
+        ]
+
+        for line in (text or "").splitlines():
+            clean = line.strip(" -•*\t")
+            if not clean:
+                continue
+
+            for p in patterns:
+                m = re.search(p, clean, flags=re.IGNORECASE)
+                if not m:
+                    continue
+                values = re.split(r",|/|\band\b", m.group(1), flags=re.IGNORECASE)
+                for value in values:
+                    name = value.strip(" .:;-")
+                    if len(name) < 3:
+                        continue
+                    key = name.lower()
+                    if key in seen:
+                        continue
+                    seen.add(key)
+                    candidates.append({"name": name, "category": "other"})
+
+        return candidates[:8]
+
     prompt = (
-        "From the disease analysis below, extract only AGRICULTURAL products that a farmer can buy "
-        "for treatment (fungicides, pesticides, bio-products, etc.). "
+        "From the disease analysis below, extract only AGRICULTURAL treatment inputs that a farmer can buy "
+        "(fungicides, pesticides, bio-products, micronutrients, plant supplements, soil amendments, etc.). "
+        "Prefer active ingredients and practical market search terms. "
         "Return STRICT JSON only with this format: "
-        "{\"products\": [{\"name\": \"...\", \"category\": \"fungicide|pesticide|bio|other\"}]}. "
+        "{\"products\": [{\"name\": \"...\", \"category\": \"fungicide|pesticide|bio|nutrient|other\"}]}. "
         "Do not include non-agriculture items. If none are present return {\"products\": []}. "
         f"Analysis: {detection_text}"
     )
@@ -88,7 +123,8 @@ def extract_agri_products(detection_text: str):
     oai = _get_openai_client()
     completion = oai.chat.completions.create(
         model="gpt-4o-mini",
-        temperature=0.1,
+        temperature=0,
+        response_format={"type": "json_object"},
         messages=[{"role": "user", "content": prompt}],
     )
     extraction_text = completion.choices[0].message.content or ""
@@ -96,9 +132,12 @@ def extract_agri_products(detection_text: str):
     extraction_text = _clean_fenced_json(extraction_text)
     try:
         parsed = json.loads(extraction_text)
-        return parsed.get("products", []) if isinstance(parsed, dict) else []
+        products = parsed.get("products", []) if isinstance(parsed, dict) else []
+        if isinstance(products, list) and products:
+            return products
+        return _heuristic_product_candidates(detection_text)
     except json.JSONDecodeError:
-        return []
+        return _heuristic_product_candidates(detection_text)
 
 def chat_bot(query: str, image_data: bytes = None):
     system_instruction = (