Add AI gardening advisor (Qwen2.5-3B-Instruct via HF Inference)

Adds a per-plant "Ask the assistant" panel backed by modules/advisor.py,
grounded in each plant's care profile (sunlight, soil, watering, fertilization).

app.py

@@ -29,6 +29,7 @@ from modules.recommender import generate_care_notes
 from modules.weather_utils import did_or_will_rain, last_rained_date, weather_values
 from modules.watering import get_watering_frequency, should_water
 from modules import pixel_art
+from modules import advisor
 from utils.geo import city_to_coordinates
 
 # ── Config ─────────────────────────────────────────────────────────────────────
@@ -408,6 +409,12 @@ with gr.Blocks(title="🌿 Plant Watering Planner") as app:
                     return_btn = gr.Button("🔙 Back to gallery")
                 action_status = gr.Markdown()
 
+                # Ask-the-assistant panel — hidden until a plant is selected
+                with gr.Group(visible=False) as advisor_panel:
+                    advisor_question = gr.Textbox(label="Ask about this plant", placeholder="e.g. Why are the leaves turning yellow?")
+                    advisor_ask_btn = gr.Button("🤖 Ask the assistant")
+                    advisor_answer = gr.Markdown()
+
             # ── Sidebar: watering recommendations + forecast ────────────────────
             with gr.Column(scale=2, elem_id="sidebar"):
                 gr.Markdown("### 💧 Watering today")
@@ -439,7 +446,7 @@ with gr.Blocks(title="🌿 Plant Watering Planner") as app:
 
         def _store_and_show(evt: gr.SelectData, user_id):
             """Update detail panel, reveal action buttons, and return the selected index."""
-            return on_plant_selected(evt, user_id), evt.index, gr.Row(visible=True)
+            return on_plant_selected(evt, user_id), evt.index, gr.Row(visible=True), gr.Group(visible=True), ""
 
         add_plant_btn.click(
             fn=lambda: gr.Column(visible=True),
@@ -461,7 +468,7 @@ with gr.Blocks(title="🌿 Plant Watering Planner") as app:
         garden_gallery.select(
             fn=_store_and_show,
             inputs=[user_id_state],
-            outputs=[plant_detail, selected_idx, action_row],
+            outputs=[plant_detail, selected_idx, action_row, advisor_panel, advisor_answer],
         )
 
         def _mark_watered_by_idx(idx, user_id):
@@ -503,8 +510,24 @@ with gr.Blocks(title="🌿 Plant Watering Planner") as app:
             outputs=[action_status, garden_gallery],
         )
         return_btn.click(
-            fn=lambda: ("", None, gr.Row(visible=False)),
-            outputs=[plant_detail, selected_idx, action_row],
+            fn=lambda: ("", None, gr.Row(visible=False), gr.Group(visible=False), ""),
+            outputs=[plant_detail, selected_idx, action_row, advisor_panel, advisor_answer],
+        )
+
+        def ask_plant_advisor(question, idx, user_id):
+            if not question.strip():
+                return "Type a question first."
+            plants = _visible_plants(user_id)
+            if idx is None or idx >= len(plants):
+                return "Select a plant first."
+            plant = plants[idx]
+            info = get_plant_info(plant["genus"])
+            return advisor.ask_about_plant(question, info, plant_name=plant.get("nickname"), genus=plant["genus"])
+
+        advisor_ask_btn.click(
+            fn=ask_plant_advisor,
+            inputs=[advisor_question, selected_idx, user_id_state],
+            outputs=[advisor_answer],
         )
 
         refresh_btn.click(

modules/advisor.py

@@ -0,0 +1,48 @@
+import os
+
+from huggingface_hub import InferenceClient
+
+ADVISOR_MODEL_ID = os.getenv("ADVISOR_MODEL_ID", "Qwen/Qwen2.5-3B-Instruct")
+
+_client = None
+
+
+def _get_client() -> InferenceClient:
+    global _client
+    if _client is None:
+        _client = InferenceClient(model=ADVISOR_MODEL_ID, token=os.getenv("HF_TOKEN"))
+    return _client
+
+
+def _build_system_prompt(plant_info: dict, plant_name: str | None = None, genus: str | None = None) -> str:
+    name = plant_name or genus or "this plant"
+    return (
+        "You are an expert gardening assistant with deep knowledge of houseplant "
+        "and garden plant care. Be practical, encouraging, and specific.\n\n"
+        f"The user is asking about their plant: {name} (genus: {genus}). "
+        "Known care profile for this plant:\n"
+        f"- Sunlight: {plant_info.get('sunlight')}\n"
+        f"- Soil: {plant_info.get('soil')}\n"
+        f"- Watering frequency: every {plant_info.get('watering_frequency_days')} days\n"
+        f"- Fertilization: {plant_info.get('fertilization_type')}\n\n"
+        "Use this profile as context, but also draw on your general gardening "
+        "knowledge for issues it doesn't cover (pests, diseases, yellowing "
+        "leaves, repotting, etc.). Give concrete, actionable advice and never "
+        "recommend dangerous or toxic substances. Answer in 2-4 sentences, in "
+        "the same language as the question."
+    )
+
+
+def ask_about_plant(question: str, plant_info: dict, plant_name: str | None = None, genus: str | None = None) -> str:
+    """Ask the advisor a question about a specific plant, grounded in its care data."""
+    try:
+        completion = _get_client().chat_completion(
+            messages=[
+                {"role": "system", "content": _build_system_prompt(plant_info, plant_name, genus)},
+                {"role": "user", "content": question},
+            ],
+            max_tokens=300,
+        )
+        return completion.choices[0].message.content
+    except Exception:
+        return "Sorry, the assistant is unavailable right now — please try again later."

requirements.txt

@@ -9,6 +9,9 @@ datasets==5.0.0
 transformers==5.12.0
 accelerate==1.14.0
 
+# ML — plant-care advisor chat via HF Inference Providers (modules/advisor.py)
+huggingface_hub==1.19.0
+
 # torch: left unpinned on purpose — Colab/HF Spaces ship a CUDA-matched build,
 # and pinning here would force a CPU reinstall over it. Tested with 2.12.0.
 torch>=2.12