Requests 工具包集成

使用 LangChain Python 集成 Requests 工具包。

我们可以使用 Requests toolkit 来构建生成 HTTP 请求的智能体。

有关所有 API 工具包功能和配置的详细文档，请前往 RequestsToolkit 的 API 参考。

⚠️ 安全须知 ⚠️

赋予模型执行现实世界操作的自主权存在固有风险。采取预防措施以减轻这些风险：

• 确保与工具关联的权限范围狭窄（例如，用于数据库操作或 API 请求）；
• 如有需要，请使用人机协作工作流。

设置

安装

此工具包位于 langchain-community 包中：

pip install -qU langchain-community

要启用单个工具的自动追踪，请设置您的 LangSmith API 密钥：

os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
os.environ["LANGSMITH_TRACING"] = "true"

实例化

首先，我们将演示一个最小示例。

注意：赋予模型执行现实世界操作的自主权存在固有风险。我们必须通过设置 allow_dangerous_request=True 来“选择加入”这些风险才能使用这些工具。 这可能会导致调用不需要的请求，存在危险。请确保您的自定义 OpenAPI 规范 (yaml) 是安全的，并且与工具关联的权限范围狭窄。

ALLOW_DANGEROUS_REQUEST = True

我们可以使用 JSONPlaceholder API 作为测试平台。

让我们创建其 API 规范的一个子集：

from typing import Any, Dict, Union

import requests
import yaml


def _get_schema(response_json: Union[dict, list]) -> dict:
    if isinstance(response_json, list):
        response_json = response_json[0] if response_json else {}
    return {key: type(value).__name__ for key, value in response_json.items()}


def _get_api_spec() -> str:
    base_url = "https://jsonplaceholder.typicode.com"
    endpoints = [
        "/posts",
        "/comments",
    ]
    common_query_parameters = [
        {
            "name": "_limit",
            "in": "query",
            "required": False,
            "schema": {"type": "integer", "example": 2},
            "description": "Limit the number of results",
        }
    ]
    openapi_spec: Dict[str, Any] = {
        "openapi": "3.0.0",
        "info": {"title": "JSONPlaceholder API", "version": "1.0.0"},
        "servers": [{"url": base_url}],
        "paths": {},
    }
    # Iterate over the endpoints to construct the paths
    for endpoint in endpoints:
        response = requests.get(base_url + endpoint)
        if response.status_code == 200:
            schema = _get_schema(response.json())
            openapi_spec["paths"][endpoint] = {
                "get": {
                    "summary": f"Get {endpoint[1:]}",
                    "parameters": common_query_parameters,
                    "responses": {
                        "200": {
                            "description": "Successful response",
                            "content": {
                                "application/json": {
                                    "schema": {"type": "object", "properties": schema}
                                }
                            },
                        }
                    },
                }
            }
    return yaml.dump(openapi_spec, sort_keys=False)


api_spec = _get_api_spec()

接下来，我们可以实例化工具包。此 API 不需要授权或其他标头：

from langchain_community.agent_toolkits.openapi.toolkit import RequestsToolkit
from langchain_community.utilities.requests import TextRequestsWrapper

toolkit = RequestsToolkit(
    requests_wrapper=TextRequestsWrapper(headers={}),
    allow_dangerous_requests=ALLOW_DANGEROUS_REQUEST,
)

工具

查看可用工具：

tools = toolkit.get_tools()

tools

[RequestsGetTool(requests_wrapper=TextRequestsWrapper(headers={}, aiosession=None, auth=None, response_content_type='text', verify=True), allow_dangerous_requests=True),
 RequestsPostTool(requests_wrapper=TextRequestsWrapper(headers={}, aiosession=None, auth=None, response_content_type='text', verify=True), allow_dangerous_requests=True),
 RequestsPatchTool(requests_wrapper=TextRequestsWrapper(headers={}, aiosession=None, auth=None, response_content_type='text', verify=True), allow_dangerous_requests=True),
 RequestsPutTool(requests_wrapper=TextRequestsWrapper(headers={}, aiosession=None, auth=None, response_content_type='text', verify=True), allow_dangerous_requests=True),
 RequestsDeleteTool(requests_wrapper=TextRequestsWrapper(headers={}, aiosession=None, auth=None, response_content_type='text', verify=True), allow_dangerous_requests=True)]

• RequestsGetTool
• RequestsPostTool
• RequestsPatchTool
• RequestsPutTool
• RequestsDeleteTool

在智能体中使用

from langchain_openai import ChatOpenAI
from langchain.agents import create_agent


model = ChatOpenAI(model="gpt-4.1-mini")

system_message = """
You have access to an API to help answer user queries.
Here is documentation on the API:
{api_spec}
""".format(api_spec=api_spec)

agent = create_agent(model, tools, system_prompt=system_message)

example_query = "Fetch the top two posts. What are their titles?"

events = agent.stream(
    {"messages": [("user", example_query)]},
    stream_mode="values",
)
for event in events:
    event["messages"][-1].pretty_print()

================================ Human Message =================================

Fetch the top two posts. What are their titles?
================================== Ai Message ==================================
Tool Calls:
  requests_get (call_RV2SOyzCnV5h2sm4WPgG8fND)
 Call ID: call_RV2SOyzCnV5h2sm4WPgG8fND
  Args:
    url: https://jsonplaceholder.typicode.com/posts?_limit=2
================================= Tool Message =================================
Name: requests_get

[
  {
    "userId": 1,
    "id": 1,
    "title": "sunt aut facere repellat provident occaecati excepturi optio reprehenderit",
    "body": "quia et suscipit\nsuscipit recusandae consequuntur expedita et cum\nreprehenderit molestiae ut ut quas totam\nnostrum rerum est autem sunt rem eveniet architecto"
  },
  {
    "userId": 1,
    "id": 2,
    "title": "qui est esse",
    "body": "est rerum tempore vitae\nsequi sint nihil reprehenderit dolor beatae ea dolores neque\nfugiat blanditiis voluptate porro vel nihil molestiae ut reiciendis\nqui aperiam non debitis possimus qui neque nisi nulla"
  }
]
================================== Ai Message ==================================

The titles of the top two posts are:
1. "sunt aut facere repellat provident occaecati excepturi optio reprehenderit"
2. "qui est esse"

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API 参考

有关所有 API 工具包功能和配置的详细文档，请前往 RequestsToolkit 的 API 参考。

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