Update image_analyzer.py

image_analyzer.py

@@ -29,50 +29,7 @@ class ImageAnalysisTool(Tool):
             "Content-Type": "application/json"
         }
 
-    def forward(self, image_path: str, question: str) -> str:
-        try:
-            with open(image_path, "rb") as img_file:
-                image_bytes = img_file.read()
-
-            # Encode image to base64 string
-            img_b64 = base64.b64encode(image_bytes).decode("utf-8")
-
-            # Prepare JSON payload - the exact structure depends on the model capabilities
-            # Here we send just the image for captioning
-            payload = {
-                "inputs": img_b64
-            }
-
-            response = requests.post(
-                self.api_url,
-                headers=self.headers,
-                json=payload,
-                timeout=60
-            )
-
-            if response.status_code == 200:
-                result = response.json()
-
-                caption = None
-                # Try common keys for caption output
-                if isinstance(result, dict):
-                    caption = result.get("generated_text") or result.get("caption") or result.get("text")
-                elif isinstance(result, list) and len(result) > 0 and isinstance(result[0], dict):
-                    caption = result[0].get("generated_text") or result[0].get("caption") or result[0].get("text")
-
-                if not caption:
-                    return "Error: No caption found in model response."
-
-                # Combine caption with the question to form a simple answer
-                answer = f"Caption: {caption}\nAnswer to question '{question}': {caption}"
-                return answer.strip()
-
-            else:
-                return f"Error analyzing image: {response.status_code} {response.text}"
-
-        except Exception as e:
-            return f"Error analyzing image: {e}"
-
+    def forward(self, image_path: str, question: str) -> str