Notes

client = anthropic.Anthropic(api_key='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')


def encode_image(image_path):
"""Encodes an image to base64."""
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')


def image_to_text_claude(image_base64, index):
"""
Sends a base64-encoded image to the Claude model for text extraction, returning the response text.
Args:
image_base64 (str): Base64-encoded image data.
Returns:
str: Extracted text from the image.
"""
day = day_index[index]
example_format1 = example_format.replace("Perticular Day Of Week", day)
response = client.messages.create(
model="claude-3-5-sonnet-20240620",
max_tokens=1024,
messages=[
{
"role": "user",
"content": [
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/png",
"data": image_base64,
},
},
{
"type": "text",
"text": f"""This image shows a weekly meal attendance table for a program or institution. The table has the following structure:
1. Rows represent individual participants, identified by their last name followed by first name (e.g., 'DEATER, STELLA').
2. Columns represent various days (e.g., 'Monday', 'Tuesday', etc.).
3. For each day, there are sub-columns representing different meal types:
* 'At'
* 'B'
* 'A'
* 'L'
* 'P'
* 'S'
* 'E'
4. In each cell, Crossmarks ("X") indicates True (the participant attended that meal on that day), while a blank cell indicates False (the participant did not attend).
5. The 'Age' column provides the age of each participant.
6. The table is labeled 'CLASS 3B (3 YRS)' on the left side.

**Please analyze this table and provide the extracted information in a JSON format with the following structure:{example_format1}**

**Ensure that all participants and their complete weekly attendance records are included in the JSON output.**

Rules:
1. Carefully examine each Crossmarks ("X") marking, ensuring it's assigned to the correct meal column based on where the majority of the Crossmarks ("X") appears.
2. Pay special attention to Crossmarks ("X") markings that cross multiple columns, assigning them to the column where the majority of the Crossmarks ("X") appears."""
}
],
}
],
)

response = response.content[0].text

return response