Delete image_analyzer.py

image_analyzer.py

@@ -1,77 +0,0 @@
-import os
-import base64
-import requests
-from smolagents import Tool
-
-class ImageAnalysisTool(Tool):
-    name = "image_analysis"
-    description = "Analyze the content of an image and answer a specific question about it using Hugging Face Inference API."
-    inputs = {
-        "image_path": {
-            "type": "string",
-            "description": "Path to the image file (jpg, png, etc.)"
-        },
-        "question": {
-            "type": "string",
-            "description": "A question about the image content"
-        }
-    }
-    output_type = "string"
-
-    def __init__(self):
-        super().__init__()
-        api_token = os.getenv("HF_API_TOKEN")
-        if not api_token:
-            raise EnvironmentError("HF_API_TOKEN not found in environment variables.")
-        self.api_url = "https://api-inference.huggingface.co/models/microsoft/git-base-captioning"
-        self.headers = {
-            "Authorization": f"Bearer {api_token}",
-            "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 payload for the API
-            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}"
-
-
-
-