113 lines
3.9 KiB
Python
113 lines
3.9 KiB
Python
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"""风控 Agent 专用的模型工具调用客户端。"""
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from __future__ import annotations
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from typing import Any, Protocol
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import httpx
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from app.core.errors import (
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DependencyUnavailableError,
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RecoverableAgentError,
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UpstreamTimeoutError,
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)
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from app.service.model_gateway import (
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DatabaseModelEndpointResolver,
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EnvironmentSecretResolver,
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)
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class RiskAgentEndpointResolver(Protocol):
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async def resolve(self, *, agent_type: str, task_type: str) -> list[Any]: ...
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class RiskAgentSecretResolver(Protocol):
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def resolve(self, secret_ref: str) -> str: ...
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class RiskAgentModelClient:
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"""调用 OpenAI 兼容接口，并原样返回模型消息供业务编排校验。"""
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def __init__(
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self,
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*,
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endpoint_resolver: RiskAgentEndpointResolver | None = None,
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secret_resolver: RiskAgentSecretResolver | None = None,
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client: httpx.AsyncClient | None = None,
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max_attempts: int = 2,
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) -> None:
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self.endpoint_resolver = endpoint_resolver or DatabaseModelEndpointResolver()
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self.secret_resolver = secret_resolver or EnvironmentSecretResolver()
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self.client = client
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self.max_attempts = max(1, max_attempts)
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self._owns_client = client is None
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async def chat(
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self,
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messages: list[dict[str, Any]],
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*,
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tools: list[dict[str, Any]],
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) -> dict[str, Any]:
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endpoints = await self.endpoint_resolver.resolve(
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agent_type="risk",
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task_type="risk_agent_chat",
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)
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if not endpoints:
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raise RecoverableAgentError("没有可用的风控 Agent 模型端点")
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last_error: Exception | None = None
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client = self.client or httpx.AsyncClient()
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try:
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for endpoint in endpoints[: self.max_attempts]:
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try:
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return await self._chat_with_endpoint(client, endpoint, messages, tools)
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except Exception as exc:
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last_error = exc
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raise RecoverableAgentError("风控 Agent 模型端点调用失败") from last_error
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finally:
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if self._owns_client:
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await client.aclose()
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async def _chat_with_endpoint(
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self,
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client: httpx.AsyncClient,
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endpoint: Any,
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messages: list[dict[str, Any]],
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tools: list[dict[str, Any]],
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) -> dict[str, Any]:
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token = self.secret_resolver.resolve(endpoint.secret_ref)
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url = endpoint.base_url.rstrip("/") + "/chat/completions"
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payload: dict[str, Any] = {
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"model": endpoint.model_name,
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"messages": messages,
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"temperature": 0.2,
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"tools": tools,
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"tool_choice": "auto",
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}
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try:
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response = await client.post(
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url,
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headers={
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"Authorization": f"Bearer {token}",
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"Content-Type": "application/json",
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},
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json=payload,
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timeout=httpx.Timeout(endpoint.timeout_ms / 1000),
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)
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response.raise_for_status()
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body = response.json()
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except httpx.TimeoutException as exc:
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raise UpstreamTimeoutError("风控 Agent 模型调用超时") from exc
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except httpx.HTTPError as exc:
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raise DependencyUnavailableError("风控 Agent 模型调用失败") from exc
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except ValueError as exc:
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raise DependencyUnavailableError("风控 Agent 模型响应不是有效 JSON") from exc
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choices = body.get("choices") if isinstance(body, dict) else None
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if not isinstance(choices, list) or not choices:
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raise DependencyUnavailableError("风控 Agent 模型响应缺少 choices")
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message = choices[0].get("message") if isinstance(choices[0], dict) else None
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if not isinstance(message, dict):
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raise DependencyUnavailableError("风控 Agent 模型响应缺少 message")
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return message
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