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shell committed 2026-11-01 21:38:30 +08:00
1 parent 2c1bac9bcb
commit cfb7b52fbd
6 files changed
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pyproject.toml
+5
View File
@@ -20,3 +20,8 @@ mini-agent = "mini_agent:main"
[build-system]
requires = ["uv_build>=0.13.6,<0.14.0"]
build-backend = "uv_build"
[dependency-groups]
dev = [
"ruff>=0.17.3",
]
src/mini_agent/react_agent.py
+28 -33
View File
@@ -2,15 +2,16 @@ import json
import os
from typing import Any
from mini_agent.tools.tavily_search import TavilySearch
from dotenv import load_dotenv
from openai import OpenAI
from mini_agent.tools.tool_search import ToolSearch
from mini_agent.tools.tavily_search import TavilySearch
from mini_agent.tools.tool_manager import ToolManager
from dotenv import load_dotenv
from mini_agent.tools.tool_search import ToolSearch
load_dotenv()
class ReActAgent:
SYSTEM_PROMPT = """
你是一个能够调用外部工具的智能助手。
@@ -51,9 +52,7 @@ class ReActAgent:
self.timeout = timeout or int(os.getenv("LLM_TIMEOUT", 60))
if not all([self.model, self.base_url, self.api_key]):
raise ValueError(
"模型ID、API密钥和服务地址必须被提供或在.env文件中定义。"
)
raise ValueError("模型ID、API密钥和服务地址必须被提供或在.env文件中定义。")
self.client = OpenAI(
api_key=self.api_key,
@@ -67,7 +66,7 @@ class ReActAgent:
self.search_tool = ToolSearch(self.tool_manager)
self.tool_manager.register(self.search_tool)
web_search_tool = TavilySearch()
web_search_tool.config(**{"api_key":os.getenv("TAVILY_KEY","")})
web_search_tool.config(**{"api_key": os.getenv("TAVILY_KEY", "")})
self.tool_manager.register(web_search_tool)
def run(self, question: str) -> str:
@@ -78,12 +77,9 @@ class ReActAgent:
available_tools = [self.search_tool]
tool_calls_count = 0
messages = [
{"role":"user","content":question}
]
messages = [{"role": "user", "content": question}]
for step in range(self.max_steps):
print(f"\n========== Step {step + 1} ==========")
tools = [self.tool_manager.tool_to_openai(tool) for tool in available_tools]
@@ -105,34 +101,31 @@ class ReActAgent:
raise RuntimeError("模型没有返回有效内容")
# 保存模型的工具调用消息
messages.append(
message.model_dump(exclude_none=True)
)
messages.append(message.model_dump(exclude_none=True))
for tool_call in message.tool_calls:
tool_name = tool_call.function.name
try:
arguments = json.loads(
tool_call.function.arguments or "{}"
)
arguments = json.loads(tool_call.function.arguments or "{}")
except json.JSONDecodeError:
observation = json.dumps(
{"error": "工具参数不是合法的 JSON"},
ensure_ascii=False,
)
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": observation,
})
messages.append(
{
"role": "tool",
"tool_call_id": tool_call.id,
"content": observation,
}
)
continue
print(f"调用工具: {tool_name}")
print(f"参数: {arguments}")
observation = self.tool_manager.call_tool(tool_name,arguments)
observation = self.tool_manager.call_tool(tool_name, arguments)
# 更新当前可用工具
if tool_name == self.search_tool.name:
new_tools = []
@@ -140,14 +133,16 @@ class ReActAgent:
if not any(tool.name == item.name for tool in available_tools):
available_tools.append(item)
new_tools.append(item)
observation = [self.tool_manager.tool_to_openai(tool) for tool in new_tools]
observation = [
self.tool_manager.tool_to_openai(tool) for tool in new_tools
]
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": str(observation),
})
messages.append(
{
"role": "tool",
"tool_call_id": tool_call.id,
"content": str(observation),
}
)
raise RuntimeError(
f"Agent 已达到最大执行步数 ({self.max_steps})，任务未完成"
)
raise RuntimeError(f"Agent 已达到最大执行步数 ({self.max_steps})，任务未完成")
src/mini_agent/tools/tavily_search.py
+24 -20
View File
@@ -1,26 +1,28 @@
from mini_agent.tools.tool import Configuration, Tool,Parameter
from pydantic import BaseModel, Field
from tavily import TavilyClient
from mini_agent.tools.tool import Configuration, Parameter, Tool
class ResultItem(BaseModel):
url:str
title:str
content:str
score:float
raw_content:str | None = None
id:str
url: str
title: str
content: str
score: float
raw_content: str | None = None
id: str
class SearchResult(BaseModel):
query:str
answer:str | None
images:list[str] = []
query: str
answer: str | None
images: list[str] = []
results: list[ResultItem]
class TavilySearch(Tool[SearchResult]):
class TavilySearch(Tool[SearchResult]):
@property
def name(self)->str:
def name(self) -> str:
return "Tavily网络搜索工具 "
@property
@@ -36,25 +38,27 @@ class TavilySearch(Tool[SearchResult]):
@property
def configurations(self) -> list[Configuration]:
return [
Configuration(name="api_key",type="str",required=True)
]
return [Configuration(name="api_key", type="str", required=True)]
@property
def parameters(self) -> list[Parameter]:
return [
Parameter(name="query",type="str",description="query keyword",required=True)
Parameter(
name="query", type="str", description="query keyword", required=True
)
]
def config(self,**kwargs) -> None:
api_key = kwargs.get("api_key",None)
def config(self, **kwargs) -> None:
api_key = kwargs.get("api_key", None)
if not api_key:
raise ValueError("API Key is required")
self.client = TavilyClient(api_key=api_key)
def run(self, **kwargs) -> SearchResult:
query = kwargs.get("query",None)
query = kwargs.get("query", None)
if not query:
raise ValueError("查询参数不能为空")
response = self.client.search(query=query,search_depth="advanced",include_answer="advanced")
response = self.client.search(
query=query, search_depth="advanced", include_answer="advanced"
)
return SearchResult.model_validate(response)
src/mini_agent/tools/tool.py
+18 -16
View File
@@ -1,49 +1,51 @@
from abc import ABC, abstractmethod
from pydantic import BaseModel
from abc import ABC,abstractmethod
class Parameter(BaseModel):
name:str
type:str
description:str
required:bool =True
name: str
type: str
description: str
required: bool = True
class Configuration(BaseModel):
name:str
type:str
required:bool = True
name: str
type: str
required: bool = True
class Tool[T](ABC):
@property
@abstractmethod
def name(self)->str:
def name(self) -> str:
pass
@property
@abstractmethod
def description(self)->str:
def description(self) -> str:
pass
@property
@abstractmethod
def catalog(self)->str:
def catalog(self) -> str:
pass
@property
@abstractmethod
def parameters(self)->list[Parameter]:
def parameters(self) -> list[Parameter]:
pass
@property
@abstractmethod
def configurations(self)->list[Configuration]:
def configurations(self) -> list[Configuration]:
pass
@abstractmethod
def config(self,**kwargs)->None:
def config(self, **kwargs) -> None:
pass
@abstractmethod
def run(self,**kwargs)->T:
def run(self, **kwargs) -> T:
pass
src/mini_agent/tools/tool_manager.py
+21 -24
View File
@@ -4,19 +4,20 @@ from mini_agent.tools.tool import Tool
class ToolManager:
_tools: dict[str, Tool] = {}
_tools:dict[str,Tool] = {}
def register[T](self,tool:Tool[T])->None:
def register[T](self, tool: Tool[T]) -> None:
if tool.name in self._tools:
raise ValueError(f"{tool.name} is already registered")
self._tools[tool.name] = tool
def get_tools(self,keyword:str,catalog:str | None)->list[Tool]:
def get_tools(self, keyword: str, catalog: str | None) -> list[Tool]:
return list(self._tools.values())
def get_tools_for_openai(self,keyword:str,catalog:str|None)->list[dict[str,Any]]:
tools = self.get_tools(keyword,catalog)
def get_tools_for_openai(
self, keyword: str, catalog: str | None
) -> list[dict[str, Any]]:
tools = self.get_tools(keyword, catalog)
result = []
for tool in tools:
result.append(self.tool_to_openai(tool))
@@ -30,37 +31,33 @@ class ToolManager:
return tool.run(**arguments)
def tool_to_openai[T](self,tool:Tool[T])->dict[str,Any]:
def tool_to_openai[T](self, tool: Tool[T]) -> dict[str, Any]:
type_mapping = {
"str": "string",
"string": "string",
"int": "integer",
"integer": "integer",
"float": "number",
"number": "number",
"bool": "boolean",
"boolean": "boolean",
"list": "array",
"dict": "object",
}
"str": "string",
"string": "string",
"int": "integer",
"integer": "integer",
"float": "number",
"number": "number",
"bool": "boolean",
"boolean": "boolean",
"list": "array",
"dict": "object",
}
properties = {}
required = []
for parameter in tool.parameters:
json_type = type_mapping.get(parameter.type)
if json_type is None:
raise ValueError(
f"不支持的参数类型: {parameter.type}"
)
raise ValueError(f"不支持的参数类型: {parameter.type}")
properties[parameter.name] = {
"type": json_type,
}
if parameter.description:
properties[parameter.name]["description"] = (
parameter.description
)
properties[parameter.name]["description"] = parameter.description
if parameter.required:
required.append(parameter.name)
uv.lock
Generated
+33
View File
@@ -219,6 +219,11 @@ dependencies = [
{ name = "tavily-python" },
]
[package.dev-dependencies]
dev = [
{ name = "ruff" },
]
[package.metadata]
requires-dist = [
{ name = "openai", specifier = ">=3.42.0" },
@@ -227,6 +232,9 @@ requires-dist = [
{ name = "tavily-python", specifier = ">=0.8.5" },
]
[package.metadata.requires-dev]
dev = [{ name = "ruff", specifier = ">=0.17.3" }]
[[package]]
name = "openai"
version = "3.42.0"
@@ -364,6 +372,31 @@ wheels = [
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