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import logging |
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import re |
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import base64 |
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from io import BytesIO |
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from anthropic import Anthropic |
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def encode_image_to_base64(image): |
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buffered = BytesIO() |
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image.save(buffered, format="PNG") |
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img_str = base64.b64encode(buffered.getvalue()).decode("utf-8") |
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return img_str |
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def create_message(sample): |
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query = sample['query'] |
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all_contents = [] |
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matches = re.findall(r"<(image_\d+)>", query) |
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split_text = re.split(r"<image_\d+>", query) |
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for i, fragment in enumerate(split_text): |
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if fragment.strip(): |
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all_contents.extend([ |
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{"type": "text", "text": fragment} |
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]) |
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if i < len(matches): |
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if sample[matches[i]]: |
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img_base64 = encode_image_to_base64(sample[matches[i]]) |
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all_contents.extend([ |
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{ |
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"type": "image", |
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"source": { |
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"type": "base64", |
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"media_type": "image/png", |
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"data": img_base64 |
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} |
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} |
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]) |
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else: |
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logging.error( |
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f"The image token {matches[i]} is in the query, but there is no corresponding image provided by the data") |
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messages = [ |
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{ |
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"role": "user", |
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"content": all_contents |
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} |
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] |
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return messages |
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class Claude_Model(): |
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def __init__( |
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self, |
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client: Anthropic, |
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model="claude-3-5-sonnet-latest", |
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temperature=0, |
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max_tokens=1024 |
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): |
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self.client = client |
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self.model = model |
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self.temperature = temperature |
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self.max_tokens = max_tokens |
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def get_response(self, sample): |
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messages = create_message(sample) |
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try: |
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v_response = self.client.messages.create( |
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model=self.model, |
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max_tokens=self.max_tokens, |
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temperature=self.temperature, |
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messages=messages |
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) |
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response = v_response.content[0].text |
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return response |
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except Exception as e: |
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print(e) |
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return None |
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