Create app3.py

app3.py

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+import streamlit as st
+from smolagents.agents import ToolCallingAgent
+from smolagents import tool, LiteLLMModel
+from typing import Optional
+import cv2
+import pytesseract
+from PIL import Image
+import io
+
+# Define the LiteLLMModel
+model = LiteLLMModel(model_id="gpt-4o")
+
+@tool
+def extract_components(image_data: bytes) -> str:
+    """
+    Extract components from a web design image.
+
+    Args:
+        image_data: The image data in bytes.
+
+    Returns:
+        A string describing the components found in the image.
+    """
+    image = Image.open(io.BytesIO(image_data))
+    gray = cv2.cvtColor(np.array(image), cv2.COLOR_BGR2GRAY)
+    components = pytesseract.image_to_string(gray)
+    return components
+
+@tool
+def generate_code(components: str) -> str:
+    """
+    Generate code for the given components.
+
+    Args:
+        components: A string describing the components.
+
+    Returns:
+        The generated code for the components.
+    """
+    # This is a placeholder implementation. You can replace it with actual code generation logic.
+    return f"Generated code for components: {components}"
+
+# Define the ToolCallingAgent
+agent = ToolCallingAgent(tools=[extract_components, generate_code], model=model)
+
+# Streamlit app title
+st.title("Web Design Component Extractor")
+
+# File uploader for the web design image
+uploaded_file = st.file_uploader("Upload a web design image", type=["png", "jpg", "jpeg"])
+
+# Button to run the agent
+if st.button("Extract and Generate Code"):
+    if uploaded_file is not None:
+        image_data = uploaded_file.read()
+        components = agent.run("extract_components", image_data=image_data)
+        code = agent.run("generate_code", components=components)
+        st.write("Extracted Components:", components)
+        st.write("Generated Code:", code)
+    else:
+        st.write("Please upload an image.")