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from ..smp import * |
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import os |
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from .base import BaseAPI |
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class CWWrapper(BaseAPI): |
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is_api: bool = True |
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def __init__(self, |
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model: str = 'cw-congrong-v1.5', |
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retry: int = 10, |
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wait: int = 5, |
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key: str = None, |
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verbose: bool = True, |
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system_prompt: str = None, |
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temperature: float = 0, |
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timeout: int = 600, |
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api_base: str = 'http://cwapi-vlm01.cw_rb.azurebot.tk/v1/chat/completions', |
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max_tokens: int = 2048, |
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img_size: int = 512, |
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img_detail: str = 'low', |
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**kwargs): |
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self.model = model |
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self.cur_idx = 0 |
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self.fail_msg = 'Failed to obtain answer via API. ' |
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self.max_tokens = max_tokens |
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self.temperature = temperature |
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base = os.environ.get('CW_API_BASE', None) |
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self.api_base = base if base is not None else api_base |
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env_key = os.environ.get('CW_API_KEY', None) |
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self.key = env_key if env_key is not None else key |
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assert self.key is not None, 'API key not provided. Please set CW_API_KEY environment variable or \ |
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pass it to the constructor.' |
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assert img_size > 0 or img_size == -1 |
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self.img_size = -1 |
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assert img_detail in ['high', 'low'] |
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self.img_detail = img_detail |
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self.vision = True |
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self.timeout = timeout |
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super().__init__(wait=wait, retry=retry, system_prompt=system_prompt, verbose=verbose, **kwargs) |
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def prepare_inputs(self, inputs): |
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input_msgs = [] |
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if self.system_prompt is not None: |
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input_msgs.append(dict(role='system', content=self.system_prompt)) |
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has_images = np.sum([x['type'] == 'image' for x in inputs]) |
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if has_images: |
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content_list = [] |
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for msg in inputs: |
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if msg['type'] == 'text': |
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content_list.append(dict(type='text', text=msg['value'])) |
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elif msg['type'] == 'image': |
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from PIL import Image |
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img = Image.open(msg['value']) |
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b64 = encode_image_to_base64(img, target_size=self.img_size) |
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img_struct = dict(url=f"data:image/jpeg;base64,{b64}", detail=self.img_detail) |
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content_list.append(dict(type='image_url', image_url=img_struct)) |
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input_msgs.append(dict(role='user', content=content_list)) |
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else: |
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assert all([x['type'] == 'text' for x in inputs]) |
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text = '\n'.join([x['value'] for x in inputs]) |
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input_msgs.append(dict(role='user', content=text)) |
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return input_msgs |
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def generate_inner(self, inputs, **kwargs) -> str: |
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input_msgs = self.prepare_inputs(inputs) |
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temperature = kwargs.pop('temperature', self.temperature) |
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max_tokens = kwargs.pop('max_tokens', self.max_tokens) |
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if 0 < max_tokens <= 100: |
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self.logger.warning( |
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'Less than 100 tokens left, ' |
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'may exceed the context window with some additional meta symbols. ' |
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) |
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if max_tokens <= 0: |
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return 0, self.fail_msg + 'Input string longer than context window. ', 'Length Exceeded. ' |
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headers = {'Content-Type': 'application/json', 'Authorization': f'{self.key}'} |
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payload = dict( |
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model=self.model, |
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messages=input_msgs, |
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max_tokens=max_tokens, |
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n=1, |
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temperature=temperature, |
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**kwargs) |
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response = requests.post(self.api_base, headers=headers, data=json.dumps(payload), timeout=self.timeout * 1.1) |
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ret_code = response.status_code |
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ret_code = 0 if (200 <= int(ret_code) < 300) else ret_code |
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answer = self.fail_msg |
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try: |
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resp_struct = json.loads(response.text) |
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answer = resp_struct['choices'][0]['message']['content'].strip() |
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except Exception as err: |
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if self.verbose: |
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self.logger.error(f'{type(err)}: {err}') |
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self.logger.error(response.text if hasattr(response, 'text') else response) |
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return ret_code, answer, response |
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