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Commit 0804f32e by tinywell
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镜像编译及容器部署

parent 0a2be35f
Showing with 116 additions and 70 deletions
.dockerignore 0 → 100644
tmp
claie_crawler
faiss
gradio_file
init_db
lae_pg_data
test
\ No newline at end of file
Dockerfile
# 使用官方的Python 3.10基础镜像
FROM python:3.10
# 使用官方的Python 3.11基础镜像
FROM python:3.11
# 设置工作目录
WORKDIR /app
......@@ -12,10 +12,6 @@ RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
# 配置python环境
RUN pip install --no-cache-dir -r requirements.txt
RUN mv /usr/local/lib/python3.10/site-packages/gradio/templates/frontend/index.html /usr/local/lib/python3.10/site-packages/gradio/templates/frontend/index.html.back
RUN mv /usr/local/lib/python3.10/site-packages/gradio/templates/frontend/share.html /usr/local/lib/python3.10/site-packages/gradio/templates/frontend/share.html.back
RUN cp /app/gradio_file/index.html /usr/local/lib/python3.10/site-packages/gradio/templates/frontend
RUN cp /app/gradio_file/share.html /usr/local/lib/python3.10/site-packages/gradio/templates/frontend
# 运行一个简单的Python命令以确保环境正确配置
CMD ["python", "test/gradio_test.py"]
CMD cd src && python controller/api.py
\ No newline at end of file
Makefile 0 → 100644
lae_agent:
docker build -t brilliance/lae_agent .
docker-compose.yml
version: '3'
services:
postgres:
image: postgres
container_name: lae_pgsql
lae_agent:
image: brilliance/lae_agent
container_name: lae_agent
environment:
POSTGRES_PASSWORD: 111111
# GEO_AGENT_TOOL_BASE_URL: http://localhost:5001
GEO_AGENT_TOOL_BASE_URL: http://172.30.0.37:30007
# GEO_AGENT_API_BASE: http://192.168.10.14:8000/v1
# GEO_AGENT_LLM_MODEL: Qwen2-7B
ports:
- "5434:5432"
volumes:
- ./lae_pg_data:/var/lib/postgresql/data
- ./init_db/create_db.sql:/docker-entrypoint-initdb.d/create_db.sql
- ./init_db/create_table.sql:/docker-entrypoint-initdb.d/create_table.sql
- "8088:8088"
requirements.txt
#bitsandbytes==0.41.1
cpm-kernels==1.0.11
fastapi==0.100.0
Flask==2.1.1
jieba==0.42.1
langchain==0.1.13
peft==0.4.0
psycopg2==2.9.7
langchain
langchain-openai
langchain-community
langchain-core
pydantic==1.10.12
requests==2.31.0
sentence-transformers==2.2.2
transformers==4.31.0
uvicorn==0.23.1
unstructured==0.8.1
\ No newline at end of file
bs4==0.0.1
mdtex2html==1.2.0
faiss-cpu==1.7.2 # https://github.com/facebookresearch/faiss/blob/main/INSTALL.md
gradio==3.48.0
qianfan==0.3.13.1
modelscope==1.14.0
wkhtmltopdf==0.2
pdfkit==1.0.0
\ No newline at end of file
src/agent/http_tools.py
import httpx
from typing import List, Optional, Dict, TypeVar, Generic, Any
from typing import TypeVar, Generic, Any, Optional, List, Dict
from pydantic import BaseModel
import asyncio
from urllib.parse import urljoin
# 泛型类型定义
......
src/agent/tool_rate.py
from typing import Dict, List, Tuple, Any, Optional
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from datetime import datetime
from pydantic import BaseModel, Field
from typing import Type
from langchain_core.tools import BaseTool
......@@ -17,7 +13,7 @@ class BaseRateTool(BaseTool):
def __init__(self, **data):
super().__init__(**data)
def format_response(self, data: Dict[str, Any], chart: go.Figure) -> Dict[str, Any]:
def format_response(self, data: Dict[str, Any], chart: Any) -> Dict[str, Any]:
"""格式化返回结果"""
return {
'data': data,
......
src/controller/api.py
import os
import sys
import argparse
sys.path.append('../')
import argparse
from typing import Optional
from fastapi import FastAPI, Header
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from src.server.agent_rate import new_rate_agent
from src.server.classify import new_router_llm
from src.controller.request import GeoAgentRateRequest
from langchain_openai import ChatOpenAI
# 默认配置
DEFAULT_CONFIG = {
"PORT": 8088,
"HOST": "0.0.0.0",
"LLM_MODEL": "Qwen2-7B",
"API_BASE": "http://192.168.10.14:8000/v1",
"TOOL_BASE_URL": "http://localhost:5001",
"API_KEY": "xxxxxxxxxxxxx"
}
def get_config(key: str, args: Optional[argparse.Namespace] = None) -> str:
"""
获取配置值，优先级：环境变量 > 命令行参数 > 默认值
Args:
key: 配置键名
args: 命令行参数对象
Returns:
str: 配置值
"""
# 环境变量名转换为大写
env_key = f"GEO_AGENT_{key.upper()}"
# 优先从环境变量获取
value = os.getenv(env_key)
if value is not None:
return value
print(f"env_key: {env_key} value: {value}")
# 其次从命令行参数获取
if args is not None:
arg_value = getattr(args, key.lower(), None)
if arg_value is not None:
return str(arg_value)
# 最后使用默认值
return str(DEFAULT_CONFIG[key.upper()])
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # 允许所有域访问，也可以指定特定域名
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"], # 允许所有HTTP方法
allow_headers=["*"], # 允许所有HTTP头
allow_methods=["*"],
allow_headers=["*"],
)
global base_llm, tool_base_url
base_llm = None
tool_base_url = None
class AgentManager:
def __init__(self):
self.llm = None
self.agent = None
self.router_llm = None
def initialize(self, api_key: str, api_base: str, model_name: str, tool_base_url: str):
self.llm = ChatOpenAI(
......@@ -35,7 +76,7 @@ class AgentManager:
model_name=model_name,
verbose=True
)
self.agent = new_rate_agent(self.llm,verbose=True,tool_base_url=tool_base_url)
self.agent = new_rate_agent(self.llm, verbose=True, tool_base_url=tool_base_url)
self.router_llm = new_router_llm(self.llm)
def get_llm(self):
......@@ -49,10 +90,8 @@ class AgentManager:
agent_manager = AgentManager()
@app.post('/api/agent/rate')
def rate(chat_request: GeoAgentRateRequest, token: str = Header(None)):
agent = agent_manager.get_agent()
try:
res = agent.exec(prompt_args={"input": chat_request.query})
......@@ -69,7 +108,6 @@ def rate(chat_request: GeoAgentRateRequest, token: str = Header(None)):
@app.post('/api/classify')
def classify(chat_request: GeoAgentRateRequest):
llm = agent_manager.get_router_llm()
try:
res = llm.invoke(chat_request.query)
......@@ -84,22 +122,43 @@ def classify(chat_request: GeoAgentRateRequest):
'data': res
}
if __name__ == "__main__":
# 参数解析
def main():
# 命令行参数解析
parser = argparse.ArgumentParser(description="启动API服务")
parser.add_argument("--port", type=int, default=8088, help="API服务端口")
parser.add_argument("--host", type=str, default='0.0.0.0', help="API服务地址")
parser.add_argument("--llm", type=str, default='Qwen2-7B', help="API服务地址")
parser.add_argument("--api_base", type=str, default='http://192.168.10.14:8000/v1', help="API服务地址")
parser.add_argument("--tool_base_url", type=str, default='http://localhost:5001', help="API服务地址")
parser.add_argument("--port", type=int, help="API服务端口")
parser.add_argument("--host", type=str, help="API服务地址")
parser.add_argument("--llm", type=str, help="LLM模型名称")
parser.add_argument("--api_base", type=str, help="OpenAI API基础地址")
parser.add_argument("--tool_base_url", type=str, help="工具服务基础地址")
parser.add_argument("--api_key", type=str, help="OpenAI API密钥")
args = parser.parse_args()
# 获取配置
port = int(get_config("PORT", args))
host = get_config("HOST", args)
llm_model = get_config("LLM_MODEL", args)
api_base = get_config("API_BASE", args)
tool_base_url = get_config("TOOL_BASE_URL", args)
api_key = get_config("API_KEY", args)
# 初始化 agent
agent_manager.initialize(
api_key='xxxxxxxxxxxxx',
api_base=args.api_base,
model_name=args.llm,
tool_base_url=args.tool_base_url
api_key=api_key,
api_base=api_base,
model_name=llm_model,
tool_base_url=tool_base_url
)
uvicorn.run(app, host=args.host, port=args.port)
# 启动服务
print(f"Starting server with configuration:")
print(f"Host: {host}")
print(f"Port: {port}")
print(f"LLM Model: {llm_model}")
print(f"API Base: {api_base}")
print(f"Tool Base URL: {tool_base_url}")
uvicorn.run(app, host=host, port=port)
if __name__ == "__main__":
main()
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