From 300b9d9dc54eb7bc4ce46b7f43fa439a0f8b159f Mon Sep 17 00:00:00 2001 From: zk Date: Mon, 22 Jun 2026 20:21:41 +0800 Subject: [PATCH] ChatAnthropic --- .env | 8 ++++++-- app/ai/model_config.py | 8 ++++---- app/ai/models.py | 36 ++++++++++++++++++++++++------------ app/config/settings.py | 5 +++++ app/services/ai_tool.py | 6 +++--- requirements.txt | 1 + 6 files changed, 43 insertions(+), 21 deletions(-) diff --git a/.env b/.env index 1f7122d..c5a9f1e 100644 --- a/.env +++ b/.env @@ -19,9 +19,13 @@ DB_NAME=offerpie VOLCENGINE_API_KEY=fd065993-bee2-4f31-8bf2-56d5d3012c02 VOLCENGINE_BASE_URL=https://ark.cn-beijing.volces.com/api/v3 +# Claude（Anthropic 风格） +ANTHROPIC_API_KEY=sk-43ccdb29caa7e9ebe0db8ac0958c63f6d3a2d62e59064d3d26d94332055a9bc9 +ANTHROPIC_BASE_URL=https://code.warpdevloper.cloud + # 岗位清洗参数 -CLEAN_BATCH_SIZE=100 -CLEAN_CONCURRENCY=50 +CLEAN_BATCH_SIZE=10 +CLEAN_CONCURRENCY=10 CLEAN_INTERVAL_SECONDS=180 # 公司补充参数 diff --git a/app/ai/model_config.py b/app/ai/model_config.py index 03082f5..2ebf59c 100644 --- a/app/ai/model_config.py +++ b/app/ai/model_config.py @@ -9,14 +9,14 @@ from app.ai.models import LLM class JobCleanModel: """岗位清洗模块""" # 第一次AI：结构化提取岗位信息 - STRUCTURE = LLM.DOUBAO_SEED_LITE.create(temperature=0) + STRUCTURE = LLM.CLAUDE_OPUS.create(temperature=0) # 第二次AI：专业匹配 - MAJOR_MATCH = LLM.DOUBAO_SEED_LITE.create(temperature=0) + MAJOR_MATCH = LLM.CLAUDE_OPUS.create(temperature=0) # 第三次AI：技能提取 - SKILL_EXTRACT = LLM.DOUBAO_SEED_LITE.create(temperature=0) + SKILL_EXTRACT = LLM.CLAUDE_OPUS.create(temperature=0) class CompanyCleanModel: """公司补充模块""" # 公司信息补充 - ENRICH = LLM.DOUBAO_SEED_LITE.create(temperature=0) + ENRICH = LLM.CLAUDE_OPUS.create(temperature=0) diff --git a/app/ai/models.py b/app/ai/models.py index 4cb6ca9..1cf3562 100644 --- a/app/ai/models.py +++ b/app/ai/models.py @@ -4,36 +4,48 @@ Usage: from app.ai.models import LLM llm = LLM.DOUBAO_SEED_LITE.create(temperature=0) + llm = LLM.CLAUDE_OPUS.create(temperature=0) """ from enum import Enum +from langchain_anthropic import ChatAnthropic +from langchain_core.language_models import BaseChatModel from langchain_openai import ChatOpenAI from app.config import settings -# 供应商连接配置 +# 供应商连接配置 = (api_key函数, base_url函数) _VOLCENGINE = (lambda: settings.volcengine_api_key, lambda: settings.volcengine_base_url) +_ANTHROPIC = (lambda: settings.anthropic_api_key, lambda: settings.anthropic_base_url) class LLM(Enum): - """所有可用模型，每个枚举值 = (模型名, api_key函数, base_url函数)""" + """所有可用模型，每个枚举值 = (模型名, 封装类, api_key函数, base_url函数)""" - # 火山引擎 - DOUBAO_PRO_32K = ("doubao-1-5-pro-32k-250115", *_VOLCENGINE) - DOUBAO_LITE_32K = ("doubao-1-5-lite-32k-250115", *_VOLCENGINE) - DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", *_VOLCENGINE) - DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", *_VOLCENGINE) - DEEPSEEK_V4_FLASH = ("deepseek-v4-flash-260425", *_VOLCENGINE) + # 火山引擎（OpenAI 兼容） + DOUBAO_PRO_32K = ("doubao-1-5-pro-32k-250115", ChatOpenAI, *_VOLCENGINE) + DOUBAO_LITE_32K = ("doubao-1-5-lite-32k-250115", ChatOpenAI, *_VOLCENGINE) + DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", ChatOpenAI, *_VOLCENGINE) + DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", ChatOpenAI, *_VOLCENGINE) + DEEPSEEK_V4_FLASH = ("deepseek-v4-flash-260425", ChatOpenAI, *_VOLCENGINE) - def __init__(self, model_name: str, api_key_fn, base_url_fn): + # Claude（Anthropic 风格） + CLAUDE_OPUS = ("claude-opus-4-6", ChatAnthropic, *_ANTHROPIC) + + def __init__(self, model_name: str, cls, api_key_fn, base_url_fn): self.model_name = model_name + self._cls = cls self._api_key_fn = api_key_fn self._base_url_fn = base_url_fn - def create(self, **kwargs) -> ChatOpenAI: - """创建 LLM 实例，kwargs 透传给 ChatOpenAI（temperature, max_tokens 等）""" - return ChatOpenAI( + def create(self, **kwargs) -> BaseChatModel: + """创建 LLM 实例，kwargs 透传给底层封装（temperature, max_tokens 等） + + 封装类（ChatOpenAI / ChatAnthropic）均实现 langchain BaseChatModel 接口， + 对上层调用方完全透明。 + """ + return self._cls( model=self.model_name, api_key=self._api_key_fn(), base_url=self._base_url_fn(), diff --git a/app/config/settings.py b/app/config/settings.py index 2015271..321c82b 100644 --- a/app/config/settings.py +++ b/app/config/settings.py @@ -26,9 +26,14 @@ class Settings(BaseSettings): mysql_max_overflow: int = 20 # ──────────── AI 供应商 ──────────── + # 火山引擎（OpenAI 兼容风格） volcengine_api_key: str = "fd065993-bee2-4f31-8bf2-56d5d3012c02" volcengine_base_url: str = "https://ark.cn-beijing.volces.com/api/v3" + # Claude（Anthropic 风格） + anthropic_api_key: str = "sk-43ccdb29caa7e9ebe0db8ac0958c63f6d3a2d62e59064d3d26d94332055a9bc9" + anthropic_base_url: str = "https://code.warpdevloper.cloud" + # ──────────── 岗位清洗参数 ──────────── clean_batch_size: int = 100 clean_concurrency: int = 80 diff --git a/app/services/ai_tool.py b/app/services/ai_tool.py index 3b87c4b..43fa852 100644 --- a/app/services/ai_tool.py +++ b/app/services/ai_tool.py @@ -4,7 +4,7 @@ import re from typing import Any from json_repair import repair_json -from langchain_openai import ChatOpenAI +from langchain_core.language_models import BaseChatModel from langchain_core.messages import SystemMessage, HumanMessage from app.core.logger import log @@ -28,7 +28,7 @@ def parse_llm_json(text: str) -> Any: return repair_json(cleaned, return_objects=True) -async def ai_chat(llm: ChatOpenAI, system_prompt: str, user_message: str) -> str: +async def ai_chat(llm: BaseChatModel, system_prompt: str, user_message: str) -> str: """异步调用 LLM，返回原始文本""" messages = [ SystemMessage(content=system_prompt), @@ -38,7 +38,7 @@ async def ai_chat(llm: ChatOpenAI, system_prompt: str, user_message: str) -> str return response.content -async def ai_chat_json(llm: ChatOpenAI, system_prompt: str, user_message: str) -> Any: +async def ai_chat_json(llm: BaseChatModel, system_prompt: str, user_message: str) -> Any: """异步调用 LLM，返回解析后的 JSON 对象""" raw = await ai_chat(llm, system_prompt, user_message) if not raw or not raw.strip(): diff --git a/requirements.txt b/requirements.txt index f5a3904..58e4838 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,6 +7,7 @@ apscheduler>=3.10 # AI langchain-openai>=0.3 +langchain-anthropic>=0.3 langchain-core>=0.3 # 工具