feat(llm): add json_output support for structured LLM responses
This commit is contained in:
@@ -1,7 +1,7 @@
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from __future__ import annotations
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import os
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from typing import Any, Dict, Optional, TypeVar
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from typing import Any, Dict, List, Optional, TypeVar
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from langchain_aws import ChatBedrock
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from langchain_community.chat_models import ChatTongyi
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@@ -9,7 +9,7 @@ from langchain_core.embeddings import Embeddings
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from langchain_core.language_models import BaseLLM
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from langchain_ollama import OllamaLLM
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from langchain_openai import ChatOpenAI, OpenAI
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from pydantic import BaseModel, Field
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from pydantic import BaseModel, Field, model_validator
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from app.core.error_codes import BizCode
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from app.core.exceptions import BusinessException
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@@ -25,10 +25,11 @@ class RedBearModelConfig(BaseModel):
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provider: str
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api_key: str
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base_url: Optional[str] = None
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capability: List[str] = Field(default_factory=list) # 模型能力列表,驱动所有能力开关
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is_omni: bool = False # 是否为 Omni 模型
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deep_thinking: bool = False # 是否启用深度思考模式
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thinking_budget_tokens: Optional[int] = None # 深度思考 token 预算
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support_thinking: bool = False # 模型是否支持 enable_thinking 参数(capability 含 thinking)
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json_output: bool = False # 是否强制 JSON 输出
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# 请求超时时间(秒)- 默认120秒以支持复杂的LLM调用,可通过环境变量 LLM_TIMEOUT 配置
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timeout: float = Field(default_factory=lambda: float(os.getenv("LLM_TIMEOUT", "120.0")))
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# 最大重试次数 - 默认2次以避免过长等待,可通过环境变量 LLM_MAX_RETRIES 配置
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@@ -36,6 +37,29 @@ class RedBearModelConfig(BaseModel):
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concurrency: int = 5 # 并发限流
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extra_params: Dict[str, Any] = {}
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@model_validator(mode="after")
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def _resolve_capabilities(self) -> "RedBearModelConfig":
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from app.core.logging_config import get_business_logger
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logger = get_business_logger()
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if self.deep_thinking and "thinking" not in self.capability:
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logger.warning(
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f"模型 {self.model_name} 不支持深度思考(capability 中无 'thinking'),已自动关闭 deep_thinking"
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)
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self.deep_thinking = False
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self.thinking_budget_tokens = None
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if self.json_output and "json_output" not in self.capability:
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logger.warning(
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f"模型 {self.model_name} 不支持 JSON 输出(capability 中无 'json_output'),已自动关闭 json_output"
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)
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self.json_output = False
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if self.json_output and self.deep_thinking:
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logger.warning(
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f"模型 {self.model_name} json_output 与 deep_thinking 互斥,已自动关闭 deep_thinking"
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)
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self.deep_thinking = False
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self.thinking_budget_tokens = None
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return self
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class RedBearModelFactory:
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"""模型工厂类"""
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@@ -74,17 +98,20 @@ class RedBearModelFactory:
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is_streaming = bool(config.extra_params.get("streaming"))
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if is_streaming:
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params["stream_usage"] = True
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# 只有支持 thinking 的模型才传 enable_thinking
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if config.support_thinking:
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model_kwargs: Dict[str, Any] = config.extra_params.get("model_kwargs", {})
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if is_streaming:
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model_kwargs["enable_thinking"] = config.deep_thinking
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if config.deep_thinking:
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model_kwargs["incremental_output"] = True
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if config.thinking_budget_tokens:
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model_kwargs["thinking_budget"] = config.thinking_budget_tokens
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else:
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model_kwargs["enable_thinking"] = False
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# 支持 thinking 的模型始终传 enable_thinking,关闭时显式传 False 避免模型默认开启思考
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if "thinking" in config.capability:
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extra_body = params.setdefault("extra_body", {})
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if config.deep_thinking:
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extra_body["enable_thinking"] = False
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if is_streaming:
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extra_body["enable_thinking"] = True
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if config.thinking_budget_tokens:
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extra_body["thinking_budget"] = config.thinking_budget_tokens
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params["extra_body"] = extra_body
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# JSON 输出模式
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if config.json_output:
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model_kwargs = params.setdefault("model_kwargs", {})
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model_kwargs["response_format"] = {"type": "json_object"}
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params["model_kwargs"] = model_kwargs
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return params
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@@ -108,27 +135,30 @@ class RedBearModelFactory:
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**config.extra_params
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}
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# 流式模式下启用 stream_usage 以获取 token 统计
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if config.extra_params.get("streaming"):
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params["stream_usage"] = True
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# 深度思考模式
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is_streaming = bool(config.extra_params.get("streaming"))
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if config.support_thinking:
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if is_streaming and not config.is_omni:
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if provider == ModelProvider.VOLCANO:
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# 火山引擎深度思考仅流式调用支持,非流式时不传 thinking 参数
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thinking_config: Dict[str, Any] = {
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"type": "enabled" if config.deep_thinking else "disabled"
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}
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if config.deep_thinking and config.thinking_budget_tokens:
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thinking_config["budget_tokens"] = config.thinking_budget_tokens
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params["extra_body"] = {"thinking": thinking_config}
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else:
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# 始终显式传递 enable_thinking,不支持该参数的模型(如 DeepSeek-R1)会直接忽略
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model_kwargs: Dict[str, Any] = config.extra_params.get("model_kwargs", {})
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model_kwargs["enable_thinking"] = config.deep_thinking
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if config.deep_thinking and config.thinking_budget_tokens:
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model_kwargs["thinking_budget"] = config.thinking_budget_tokens
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params["model_kwargs"] = model_kwargs
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if is_streaming:
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params["stream_usage"] = True
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# 支持 thinking 的模型始终传 enable_thinking,关闭时显式传 False 避免模型默认开启思考
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if "thinking" in config.capability:
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# VOLCANO 深度思考仅流式支持
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if provider == ModelProvider.VOLCANO:
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thinking_config: Dict[str, Any] = {"type": "enabled" if config.deep_thinking else "disabled"}
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if config.deep_thinking and config.thinking_budget_tokens:
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thinking_config["budget_tokens"] = config.thinking_budget_tokens
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params["extra_body"] = {"thinking": thinking_config}
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else:
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extra_body = params.setdefault("extra_body", {})
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if config.deep_thinking:
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extra_body["enable_thinking"] = False
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if is_streaming:
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extra_body["enable_thinking"] = True
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if config.thinking_budget_tokens:
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extra_body["thinking_budget"] = config.thinking_budget_tokens
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params["extra_body"] = extra_body
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# JSON 输出模式
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if config.json_output:
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params.setdefault("model_kwargs", {})
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params["model_kwargs"]["response_format"] = {"type": "json_object"}
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return params
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elif provider == ModelProvider.DASHSCOPE:
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params = {
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@@ -137,18 +167,21 @@ class RedBearModelFactory:
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"max_retries": config.max_retries,
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**config.extra_params
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}
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# 只有支持 thinking 的模型才传 enable_thinking
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if config.support_thinking:
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# 支持 thinking 的模型始终传 enable_thinking,关闭时显式传 False 避免模型默认开启思考
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if "thinking" in config.capability:
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is_streaming = bool(config.extra_params.get("streaming"))
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model_kwargs: Dict[str, Any] = config.extra_params.get("model_kwargs", {})
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if is_streaming:
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model_kwargs["enable_thinking"] = config.deep_thinking
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if config.deep_thinking:
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model_kwargs["incremental_output"] = True
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if config.thinking_budget_tokens:
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model_kwargs["thinking_budget"] = config.thinking_budget_tokens
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else:
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model_kwargs = params.setdefault("model_kwargs", {})
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if config.deep_thinking:
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model_kwargs["enable_thinking"] = False
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if is_streaming:
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model_kwargs["enable_thinking"] = True
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model_kwargs["incremental_output"] = True
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if config.thinking_budget_tokens:
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model_kwargs["thinking_budget"] = config.thinking_budget_tokens
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params["model_kwargs"] = model_kwargs
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if config.json_output:
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model_kwargs = params.setdefault("model_kwargs", {})
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model_kwargs["response_format"] = {"type": "json_object"}
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params["model_kwargs"] = model_kwargs
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return params
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elif provider == ModelProvider.BEDROCK:
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@@ -196,6 +229,10 @@ class RedBearModelFactory:
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params["additional_model_request_fields"] = {
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"thinking": {"type": "enabled", "budget_tokens": budget}
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}
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# JSON 输出模式
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if config.json_output:
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params.setdefault("model_kwargs", {})
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params["model_kwargs"]["response_format"] = {"type": "json_object"}
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return params
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else:
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raise BusinessException(f"不支持的提供商: {provider}", code=BizCode.PROVIDER_NOT_SUPPORTED)
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