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