# 3. Create Agent prompt = hub.pull("hwchase17/openai-functions-agent") llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0) agent = create_openai_functions_agent(llm, tools, prompt) agent_executor = AgentExe
SQLDatabaseToolkit from langchain.sql_database import SQLDatabase from langchain import OpenAI db = SQLDatabase.from_databricks(catalog="samples", schema="nyctaxi") llm = OpenAI(temperature=.7) toolkit = SQLDatabaseToolkit(db=db, llm=llm) agent = create_sql_agent(llm=llm, toolkit=toolkit...
# 3. Create Agent prompt = hub.pull("hwchase17/openai-functions-agent") llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0) agent = create_openai_functions_agent(llm, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) # 4. App definition app = Fa...
importgetpassimportosos.environ["OPENAI_API_KEY"] = getpass.getpass()fromlangchain_openaiimportChatOpenAIllm = ChatOpenAI(model="gpt-3.5-turbo-0125")# Load, chunk and index the contents of the blog.loader = WebBaseLoader(web_paths=("https://lilianweng.github.io/posts/2023-06-23-agent/"...
This is my documentation """ chain_new = APIChain.from_llm_and_api_docs(llm, api_docs, verbose=True) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 chain_new.run('Can you tell me information about france?') 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ' France is an offi...
been considered during development.\n\n2. **Natural Language Processing (NLP) for Test Documentation**: Langsmith can assist in creating clear and concise test documentation, such as test plans, test cases, and test reports, by providing well-structured text based on the input provided.\n\n....
实现Agent 到目前为止,我们已经创建了使用链的例子,其中每个步骤都是预先知道的。接下来将要实现最后一个步骤:实现Agent代理。 (1)构建Agent代理的第一件事是决定它应该访问哪些工具,在本演示中,我们将让代理访问两个工具: 我们刚刚创建的检索器。这将使它能够轻松回答有关LangSmith的问题。 搜索工具。这将使它能够...
Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like) A slim version of ChatGPT Code-Interpreter Prompt Engineering Theory Section Introduction to LangGraph Introduction to Model Context Protocol (MCP) ...
LangChain'sSQL exampleuses an LLM to transform a natural language question into an SQL query. Tools like this make it easy to develop SQL queries that account for all the intuitive specifics of the question at hand. Getting started with LangChain ...
The Spark DataFrame Agent in LangChain allows interaction with a Spark DataFrame, optimized for question answering. LangChain’s Spark DataFrame Agent documentation provides a detailed example of how to create and use the Spark DataFrame Agent with a DataFrame....