281 lines
12 KiB
Python
281 lines
12 KiB
Python
"""
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MaxKB-specific configuration extensions.
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This module extends the base configuration with MaxKB-specific settings.
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"""
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import os
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from typing import Dict, Any
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from ..config_base import MinerUConfig
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class MaxKBMinerUConfig(MinerUConfig):
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"""MaxKB-specific configuration for MinerU"""
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def __post_init__(self):
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"""Initialize with MaxKB-specific settings"""
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# Call parent initialization first
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super().__post_init__()
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# MaxKB specific settings from environment or defaults
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# 如果环境变量中设置了具体的UUID，使用UUID；否则使用默认值或自动检测
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self.llm_model_id = os.getenv('MAXKB_LLM_MODEL_ID', self._get_default_llm_model_id())
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self.vision_model_id = os.getenv('MAXKB_VISION_MODEL_ID', self._get_default_vision_model_id())
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# MaxKB API settings
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self.maxkb_api_key = os.getenv('MAXKB_API_KEY')
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self.maxkb_api_url = os.getenv('MAXKB_API_URL', 'https://api.maxkb.com')
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# File storage settings
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self.file_storage_type = os.getenv('MAXKB_STORAGE_TYPE', 'local') # local, s3, oss
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self.file_storage_path = os.getenv('MAXKB_STORAGE_PATH', '/opt/maxkb/storage')
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self.file_storage_bucket = os.getenv('MAXKB_STORAGE_BUCKET')
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# Model client settings
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self.model_client_timeout = int(os.getenv('MAXKB_MODEL_TIMEOUT', '60'))
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self.model_client_max_retries = int(os.getenv('MAXKB_MODEL_MAX_RETRIES', '3'))
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# Image optimizer settings
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self.image_optimizer_enabled = os.getenv('MAXKB_IMAGE_OPTIMIZER', 'true').lower() == 'true'
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self.image_optimizer_quality = int(os.getenv('MAXKB_IMAGE_QUALITY', '85'))
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self.image_optimizer_max_width = int(os.getenv('MAXKB_IMAGE_MAX_WIDTH', '2048'))
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self.image_optimizer_max_height = int(os.getenv('MAXKB_IMAGE_MAX_HEIGHT', '2048'))
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# Override base settings if MaxKB specific values exist
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if self.maxkb_api_key:
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self.llm_api_key = self.maxkb_api_key
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self.multimodal_api_key = self.maxkb_api_key
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# MaxKB specific processing parameters
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self.max_concurrent_uploads = int(os.getenv('MAXKB_MAX_CONCURRENT_UPLOADS', str(self.max_concurrent_uploads)))
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self.max_concurrent_api_calls = int(os.getenv('MAXKB_MAX_CONCURRENT_API_CALLS', str(self.max_concurrent_api_calls)))
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def get_model_client_config(self) -> Dict[str, Any]:
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"""Get MaxKB model client configuration"""
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return {
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'llm_model_id': self.llm_model_id,
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'vision_model_id': self.vision_model_id,
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'api_key': self.maxkb_api_key,
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'api_url': self.maxkb_api_url,
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'timeout': self.model_client_timeout,
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'max_retries': self.model_client_max_retries
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}
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def get_file_storage_config(self) -> Dict[str, Any]:
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"""Get MaxKB file storage configuration"""
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return {
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'type': self.file_storage_type,
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'path': self.file_storage_path,
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'bucket': self.file_storage_bucket
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}
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def get_image_optimizer_config(self) -> Dict[str, Any]:
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"""Get MaxKB image optimizer configuration"""
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return {
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'enabled': self.image_optimizer_enabled,
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'quality': self.image_optimizer_quality,
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'max_width': self.image_optimizer_max_width,
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'max_height': self.image_optimizer_max_height
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}
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def get_learn_info(self, learn_type: int) -> dict:
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"""Get learn_info for MaxKB - map from model IDs"""
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# MaxKB doesn't use learn_type, return empty or mapped config
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return {
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'model_id': self.llm_model_id,
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'vision_model_id': self.vision_model_id
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}
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def get_model_config(self, model_type: int, use_llm: bool = False) -> dict:
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"""Get model configuration for MaxKB"""
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# Map model_type to MaxKB model configuration
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if use_llm:
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return {
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'model': self.llm_model_id,
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'api_key': self.maxkb_api_key,
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'api_url': self.maxkb_api_url,
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'keyname': 'MAXKB_API_KEY',
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'key': self.maxkb_api_key
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}
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else:
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return {
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'model': self.vision_model_id,
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'api_key': self.maxkb_api_key,
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'api_url': self.maxkb_api_url,
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'keyname': 'MAXKB_API_KEY',
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'key': self.maxkb_api_key
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}
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async def call_litellm(self, model_type: int, messages: list, use_llm: bool = False, **kwargs) -> any:
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"""Override litellm call to use MaxKB model client"""
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from .maxkb_model_client import maxkb_model_client
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from .logger import get_module_logger
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logger = get_module_logger('config_maxkb')
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import json
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try:
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# Determine which model to use
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if use_llm:
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model_id = self.llm_model_id
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else:
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model_id = self.vision_model_id
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logger.debug(f"MaxKB: Calling model {model_id} with {len(messages)} messages")
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# Check if this is a vision request (has images)
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has_images = False
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for msg in messages:
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if isinstance(msg.get('content'), list):
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for content_item in msg['content']:
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if isinstance(content_item, dict) and content_item.get('type') == 'image_url':
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has_images = True
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break
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# Call appropriate method based on content type
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if has_images:
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# Extract image and combine all text content for vision model
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image_path = None
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combined_prompt = ""
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# First, collect system message if exists
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for msg in messages:
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if msg.get('role') == 'system':
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combined_prompt = msg.get('content', '') + "\n\n"
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break
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# Then extract user message content
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for msg in messages:
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if msg.get('role') == 'user':
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if isinstance(msg.get('content'), list):
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for content_item in msg['content']:
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if content_item.get('type') == 'text':
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combined_prompt += content_item.get('text', '')
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elif content_item.get('type') == 'image_url':
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image_url = content_item.get('image_url', {})
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if isinstance(image_url, dict):
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url = image_url.get('url', '')
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if url.startswith('data:'):
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# Handle base64 image
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import base64
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import tempfile
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# Extract base64 data
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base64_data = url.split(',')[1] if ',' in url else url
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image_data = base64.b64decode(base64_data)
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# Save to temp file
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with tempfile.NamedTemporaryFile(suffix='.jpg', delete=False) as tmp:
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tmp.write(image_data)
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image_path = tmp.name
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else:
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image_path = url
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elif isinstance(msg.get('content'), str):
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combined_prompt += msg.get('content', '')
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if image_path:
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response_text = await maxkb_model_client.vision_completion(
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model_id=model_id,
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image_path=image_path,
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prompt=combined_prompt,
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**kwargs
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)
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else:
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# Fallback to text completion
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response_text = await maxkb_model_client.chat_completion(
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model_id=model_id,
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messages=messages,
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**kwargs
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)
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else:
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# Regular text completion
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response_text = await maxkb_model_client.chat_completion(
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model_id=model_id,
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messages=messages,
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**kwargs
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)
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# Create response object similar to litellm response
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class MockResponse:
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def __init__(self, content):
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self.choices = [type('obj', (object,), {
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'message': type('obj', (object,), {
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'content': content
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})()
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})()]
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# Add usage attribute for compatibility
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self.usage = type('obj', (object,), {
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'prompt_tokens': 0,
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'completion_tokens': 0,
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'total_tokens': 0
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})()
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return MockResponse(response_text)
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except Exception as e:
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logger.error(f"MaxKB model call failed: {str(e)}")
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# Return a mock response with error message
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class MockResponse:
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def __init__(self, content):
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self.choices = [type('obj', (object,), {
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'message': type('obj', (object,), {
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'content': content
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})()
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})()]
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# Add usage attribute for compatibility
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self.usage = type('obj', (object,), {
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'prompt_tokens': 0,
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'completion_tokens': 0,
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'total_tokens': 0
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})()
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# Return a valid JSON response on error to prevent parsing issues
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# This will be parsed as a brief_description type
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error_response = json.dumps({
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"type": "brief_description",
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"title": "Error",
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"description": f"Model call failed: {str(e)}"
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})
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return MockResponse(error_response)
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def _get_default_llm_model_id(self) -> str:
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"""获取默认的LLM模型ID"""
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try:
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# 尝试从数据库获取第一个可用的LLM模型
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from django.db.models import QuerySet
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from models_provider.models import Model
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model = QuerySet(Model).filter(
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model_type__in=['LLM', 'CHAT']
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).first()
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if model:
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return str(model.id)
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except Exception:
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pass
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# 返回默认值
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return 'default-llm'
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def _get_default_vision_model_id(self) -> str:
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"""获取默认的视觉模型ID"""
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try:
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# 尝试从数据库获取第一个可用的视觉或多模态模型
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from django.db.models import QuerySet
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from models_provider.models import Model
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# 首先尝试获取专门的视觉模型
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model = QuerySet(Model).filter(
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model_type__in=['VISION', 'MULTIMODAL']
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).first()
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# 如果没有，获取任意LLM模型（许多LLM支持视觉）
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if not model:
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model = QuerySet(Model).filter(
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model_type__in=['LLM', 'CHAT']
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).first()
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if model:
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return str(model.id)
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except Exception:
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pass
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# 返回默认值
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return 'default-vision' |