# 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/"...
# 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...
**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." 可以通过提示模板来指导其响应。提示模板将...
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...
("./examples/sql.md")loader.load()"""[Document(page_content="## 创建表\n\n```sql\n# 分区表\ncreate table test_t2(words string,frequency string) partitioned by (partdate string) row format delimited fields terminated by ','...", metadata={'source': './examples/sql.md'})]"""...
read_sql_query(query, connection) # Close the connection connection.close() 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # Display the result in the first column first cell print(df.iloc[0,0]) 六,代码理解(Code Understanding) 代码理解用到的工具和文档问答差不多,不过我们的输入是一...
AgentExecutorto create a runtime for agents ChatPromptTemplateto create a prompt template that we can change at runtime by passing our inputs HumanMessage,AIMessage, andSystemMessageclasses to create the appropriate message type Before we create an agent, let's connect to an LLM and test if ...
# 使用自然语言查询一个 SQLite 数据库,我们将使用旧金山树木数据集# Don't run following code if you don't run sqlite and follow dbfrom langchain import OpenAI, SQLDatabase, SQLDatabaseChain llm = OpenAI(temperature=0, openai_api_key=openai_api_key) sqlite_db_path = 'data/San_Francisco_Tre...
**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." 可以通过提示模板来指导其响应。提示模板...