from langchain_community.tools.convert_to_openai import format_tool_to_openai_tool llm_with_tools = get_glm(0.01).bind(tools=[format_tool_to_openai_tool(tool) for tool in tools]) 创建Agent from langchain.agents.format_scratchpad.openai_tools import ( format_to_openai_tool_messages, ) from...
import json from langchain_core.utils.function_calling import convert_to_openai_tool def multiply(a: int, b: int) -> int: """Multiply two integers together. Args: a: First integer b: Second integer """ return a * b print(json.dumps(convert_to_openai_tool(multiply), indent=2)) 1....
from langgraph.prebuilt.tool_executorimportToolExecutor,ToolInvocationdefcreate_agent(llm,tools,system_message:str):"""Create an agent."""functions=[convert_to_openai_function(t)fortintools]prompt=ChatPromptTemplate.from_messages([("system","You are a helpful AI assistant, collaborating with other ...
prompt = ChatPromptTemplate.from_messages({ ("system", _EXTRACTION_TEMPLATE), ("user", "{input}") }) # 将Pydantic对象转换为适当的模式 tools = [convert_pydantic_to_openai_tool(p) for p in pydantic_schemas] # 给模型提供这些工具的访问 model = llm.bind(tools=tools) # 创建一个端到端链...
全球范围内,新兴的智能体技术如OpenAI的WebGPT为模型赋予了利用网页信息的能力,Adept培养的ACT-1能独立于网站操作并使用Excel、Salesforce等软件,谷歌的PaLM项目旗下的SayCan和PaLM-E尝试将LLM与机器人相结合,Meta的Toolformer探索使LLM能够自主调用API,而普林斯顿的Shunyu Yao所做的ReAct工作则结合了思维链prompting技术...
return format_tool_to_openai_function(function) elif callable(function): return convert_python_function_to_openai_function(function) Modified script: from langchain_core.utils.function_calling import convert_to_openai_function from enum import Enum ...
实例化OpenAI函数调用: from langchain_core.utils.function_calling import convert_to_openai_function # model = ChatOpenAI(temperature=0) # functions = [convert_to_openai_function(t) for t in tool_belt] model = model.bind_functions(functions) ...
Langchain 通过向应用程序提供对 OpenAI 嵌入API的访问权限来处理拆分和嵌入。霓虹灯在存储过程中发挥作用。 对于检索过程,pgVector 使用其向量相似性索引功能来搜索查询向量与 Neon 数据库中存储的向量之间的距离。然后 Langchain 使用 OpenAI 作为 LLM,以自然语言从查询中生成所需的结果。
自定义tool:最常用扩展方式 fromdatetimeimportdatetimefromlangchain_core.toolsimporttool#函数自定义@tool("weekday")defweekday(date_str:str) ->str:"""Convert date to weekday name"""date_object = datetime.strptime(date_str,'%Y-%m-%d')
方案一:远程调用OpenAI的ChatGPT系统API,效果较好,token花费较贵; 方案二:远程调用智谱AI的GLM-4的API,效果较好,token花费较低; 方案三:本地部署开源大语言模型ChatGLM3-6B,效果较差,不需要收费,但电脑需要有13GB以上的GPU。 综合考虑,方案二最理想。远程调用智谱AI的GLM-4的API的方式门槛最低,提示词工程的效果...