Update agent/image_symptom_tool.py

agent/image_symptom_tool.py

@@ -1,3 +1,5 @@
+# agent/image_symptom_tool.py
+
 from langchain_core.tools import tool
 import requests
 import base64
@@ -5,52 +7,45 @@ from PIL import Image
 import io
 
 @tool
-def analyze_symptom_image(image_url: str, image_description: str = "") -> str:
+def analyze_symptom_image(image_base64: str, image_description: str = "") -> str:
     """
-    Analyzes symptom images using vision classification model via FastAPI backend.
-    Input: Image URL and optional image description
-    Output: Image symptom analysis with confidence scores 
+    Analyze a base64-encoded image using the Nivra Vision FastAPI backend.
     """
+
     try:
-        # Download image from URL
-        print(f"📥 Downloading image from: {image_url}")
-        image_response = requests.get(image_url, timeout=120)
-        image_response.raise_for_status()
-        image = Image.open(io.BytesIO(image_response.content)).convert('RGB')
-        
-        # Convert to base64 for FastAPI transmission
-        buffered = io.BytesIO()
-        image.save(buffered, format="PNG")
-        img_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
-        
-        # Call your HF FastAPI Space
+        # Decode base64 to image
+        image_bytes = base64.b64decode(image_base64)
+        image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+
+        # Re-encode cleanly (prevents corruption)
+        buffer = io.BytesIO()
+        image.save(buffer, format="JPEG", quality=85)
+        clean_base64 = base64.b64encode(buffer.getvalue()).decode()
+
+        # Call Vision HF Space
         api_url = "https://datdevsteve-nivra-vision-diagnosis.hf.space/run/predict"
+
         payload = {
-            "data": [img_base64],
-            "description": image_description or ""
+            "data": [clean_base64, image_description]
         }
-        
-        print("🔬 Calling Nivra Vision FastAPI backend...")
-        response = requests.post(api_url, json=payload, timeout=60)
+
+        response = requests.post(api_url, json=payload, timeout=45)
         response.raise_for_status()
-        
+
         result = response.json()
-        
-        # Extract diagnosis from HF Space response format
-        if "data" in result and len(result["data"]) > 0:
-            diagnosis = result["data"][0]
-            return f"""
-[SYMPTOM IMAGE ANALYSIS - SUCCESS]:
-✅ FastAPI Backend Response: {diagnosis}
-
-🔍 **Image Description**: {image_description or "Not provided"}
-📡 **Backend**: nivra-vision-diagnosis HF Space"""
-        else:
-            return "[SYMPTOM IMAGE ANALYSIS - WARNING]: No diagnosis returned from backend"
-            
+
+        if "data" not in result or not result["data"]:
+            return "[IMAGE ANALYSIS] No diagnosis returned."
+
+        diagnosis = result["data"][0]
+
+        return f"""
+[IMAGE TOOL RESULT]
+{diagnosis}
+"""
+
     except requests.exceptions.Timeout:
-        return "[SYMPTOM IMAGE ANALYSIS - ERROR]: Backend timeout. Please try again."
-    except requests.exceptions.RequestException as e:
-        return f"[SYMPTOM IMAGE ANALYSIS - ERROR]: Network error: {str(e)}"
+        return "[IMAGE TOOL ERROR] Vision backend timeout."
+
     except Exception as e:
-        return f"[SYMPTOM IMAGE ANALYSIS - ERROR]: Unexpected error: {str(e)}"
+        return f"[IMAGE TOOL ERROR] {str(e)}"