Moving this tool into the correct Org

README.md

@@ -1,2 +1,7 @@
 # OpenWebUI-Bedrock-Image-Tool
 
+For any model to use this tool, you must set the valve values, and add something to the model to let it know to use the tool.
+
+```
+You have access to a tool that allows you to get descriptions of images called  "Bedrock Image Description". Any image handling should be sent through this tool.
+```

bedrock-image-tool.py

@@ -0,0 +1,100 @@
+"""
+title: Bedrock Image Description
+author: Josh Knapp
+version: 0.1.0
+description="Provide Direct Bedrock call for image generation"
+"""
+
+import subprocess
+import json
+from pydantic import BaseModel, Field
+
+
+# Try to import boto3, install if not present
+try:
+    import boto3
+except ImportError:
+    print("boto3 package not found. Attempting to install...")
+    try:
+        subprocess.check_call([sys.executable, "-m", "pip", "install", "boto3"])
+        import boto3
+
+        print("boto3 package installed successfully")
+    except subprocess.CalledProcessError as e:
+        print(f"Failed to install boto3 package: {str(e)}")
+
+
+class Tools:
+    class Valves(BaseModel):
+        AWS_ACCESS_KEY: str = Field(
+            default="",
+            description="AWS Access Key",
+        )
+        AWS_SECRET_KEY: str = Field(
+            default="",
+            description="AWS Secret Key",
+        )
+        AWS_BEDROCK_MODEL: str = Field(
+            default="",
+            description="AWS Bedrock Model to use"
+        )
+
+    def __init__(self):
+        self.valves = self.Valves()
+        pass
+
+    def analyze_image(self, base64_image: str) -> str:
+        """
+        Analyze an image using AWS Bedrock's vision model
+        Args:
+            base64_image (str): Base64 encoded image string
+        Returns:
+            str: Description of the image
+        """
+        try:
+            # Initialize Bedrock runtime client
+            bedrock = boto3.client(
+                service_name="bedrock-runtime",
+                aws_access_key_id=self.valves.AWS_ACCESS_KEY,
+                aws_secret_access_key=self.valves.AWS_SECRET_KEY,
+                region_name="us-east-1"  # or your preferred region
+            )
+
+            # Prepare the request body
+            request_body = {
+                "anthropic_version": "bedrock-2023-05-31",
+                "max_tokens": 1000,
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "image",
+                                "source": {
+                                    "type": "base64",
+                                    "media_type": "image/jpeg",
+                                    "data": base64_image
+                                }
+                            },
+                            {
+                                "type": "text",
+                                "text": "Please describe this image in detail."
+                            }
+                        ]
+                    }
+                ]
+            }
+
+            # Invoke the model
+            response = bedrock.invoke_model(
+                modelId=self.valves.AWS_BEDROCK_MODEL,
+                body=json.dumps(request_body)
+            )
+
+            # Parse and return the response
+            response_body = json.loads(response['body'].read())
+            return response_body['messages'][0]['content'][0]['text']
+
+        except Exception as e:
+            print(f"Error analyzing image: {str(e)}")
+            return f"Error analyzing image: {str(e)}"