Upload app.py

app.py

@@ -294,13 +294,13 @@ def get_multiple_recommendations(pred_caption: str, llm_model, tokenizer_model,
         f'CAPTION: "{pred_caption}"\n\n'
         f"{context_text}"
         "INSTRUCTION: Generate a comprehensive analysis and recommendation in the following three-part stacked format, with rich descriptive text:\n"
-        "1. **Cause**: A detailed sentence describing the likely cause and condition based on the caption and RAG context.\n"
-        "2. **Immediate Action**: A comprehensive sentence detailing specific, time-sensitive actions the grower must take immediately.\n"
-        "3. **Long-term Action**: A forward-looking sentence outlining preventative and sustainable strategies for the future.\n"
+        "1. Cause: A detailed sentence describing the likely cause and condition based on the caption and RAG context.\n"
+        "2. Immediate Action: A comprehensive sentence detailing specific, time-sensitive actions the grower must take immediately.\n"
+        "3. Long-term Action: A forward-looking sentence outlining preventative and sustainable strategies for the future.\n"
         "Ensure the output strictly follows the 'Label: Text' format below. Do not add extra text, line breaks, or numbering.\n\n"
-        "**Cause**: [Your descriptive text for the cause]\n"
-        "**Immediate Action**: [Your descriptive text for the immediate steps]\n"
-        "**Long-term Action**: [Your descriptive text for the long-term steps]\n"
+        "Cause: [Your descriptive text for the cause]\n"
+        "Immediate Action: [Your descriptive text for the immediate steps]\n"
+        "Long-term Action: [Your descriptive text for the long-term steps]\n"
     )
 
     messages = [
@@ -406,9 +406,9 @@ def process_image_upload(image: Image.Image):
             caption = generate_caption_beam(caption_model, img_tensor, device)
         except Exception as e:
             print("Caption generation error:", e)
-            caption = "A close-up image showing dark purplish spots on the leaves."
+            caption = "Wrong Plant/Fruit Image!"
     else:
-        caption = "A close-up image showing dark purplish spots on the leaves."
+        caption = "Wrong Plant/Fruit Image!"
 
     recommendations, retrieved_list = get_multiple_recommendations(caption, llm, llm_tokenizer, KNOWLEDGE_BASE)