用LangChain实现一个Agent

from langchain.agents import AgentExecutor, create_react_agentfrom langchain_core.prompts import PromptTemplatefrom langchain_core.tools import toolfrom langchain_openai import ChatOpenAI
@tooldef calculate(what: str) -> float:    """Runs a calculation and returns the number - uses Python so be sure to use floating point syntax if necessary"""    return eval(what)
@tooldef ask_fruit_unit_price(fruit: str) -> str:    """Asks the user for the price of a fruit"""    if fruit.casefold() == "apple":        return "Apple unit price is 10/kg"    elif fruit.casefold() == "banana":        return "Banana unit price is 6/kg"    else:        return "{} unit price is 20/kg".format(fruit)

prompt = PromptTemplate.from_template('''Answer the following questions as best you can. You have access to the following tools:
{tools}
Use the following format:
Question: the input question you must answerThought: you should always think about what to doAction: the action to take, should be one of [{tool_names}]Action Input: the input to the actionObservation: the result of the action... (this Thought/Action/Action Input/Observation can repeat N times)Thought: I now know the final answerFinal Answer: the final answer to the original input question
Begin!
Question: {input}Thought:{agent_scratchpad}''')
tools = [calculate, ask_fruit_unit_price]model = ChatOpenAI(model="gpt-4o-mini")agent = create_react_agent(model, tools, prompt)agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)result = agent_executor.invoke({    "input": "What is the total price of 3 kg of apple and 2 kg of banana?"})print(result)

@tooldef calculate(what: str) -> float:    """Runs a calculation and returns the number - uses Python so be sure to use floating point syntax if necessary"""    return eval(what)
@tooldef ask_fruit_unit_price(fruit: str) -> str:    """Asks the user for the price of a fruit"""    if fruit.casefold() == "apple":        return "Apple unit price is 10/kg"    elif fruit.casefold() == "banana":        return "Banana unit price is 6/kg"    else:        return "{} unit price is 20/kg".format(fruit)

@tooldef calculate(what: str) -> float:    """Runs a calculation and returns the number - uses Python so be sure to use floating point syntax if necessary"""    return eval(what)
print(calculate.name)print(calculate.description)print(calculate.args)

prompt = PromptTemplate.from_template('''Answer the following questions as best you can. You have access to the following tools:
{tools}
Use the following format:
Question: the input question you must answerThought: you should always think about what to doAction: the action to take, should be one of [{tool_names}]Action Input: the input to the actionObservation: the result of the action... (this Thought/Action/Action Input/Observation can repeat N times)Thought: I now know the final answerFinal Answer: the final answer to the original input question
Begin!
Question: {input}Thought:{agent_scratchpad}''')

calculate(what: str) -> float - Runs a calculation and returns the number - uses Python so be sure to use floating point syntax if necessary

tools = [calculate, ask_fruit_unit_price]model = ChatOpenAI(model="gpt-4o-mini")agent = create_react_agent(model, tools, prompt)agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

result = agent_executor.invoke({    "input": "What is the total price of 3 kg of apple and 2 kg of banana?"})print(result)

> Entering new AgentExecutor chain...
To find the total price of 3 kg of apples and 2 kg of bananas, I need to know the unit prices of both fruits. I will first ask for the price of apples and then for the price of bananas.
Action: ask_fruit_unit_price  Action Input: "apple"  Apple unit price is 10/kg
Now that I have the unit price of apples, I need to ask for the unit price of bananas.
Action: ask_fruit_unit_price  Action Input: "banana"  Banana unit price is 6/kg
Now that I have the unit prices of both fruits (10/kg for apples and 6/kg for bananas), I can calculate the total price for 3 kg of apples and 2 kg of bananas.
Action: calculate  Action Input: "3 * 10 + 2 * 6"  42
I now know the final answerFinal Answer: The total price of 3 kg of apples and 2 kg of bananas is 42.
> Finished chain.{'input': 'What is the total price of 3 kg of apple and 2 kg of banana?', 'output': 'The total price of 3 kg of apples and 2 kg of bananas is 42.'}

shell_tool = ShellTool()
tools = [shell_tool]model = ChatOpenAI(model="gpt-4o-mini")agent = create_react_agent(model, tools, prompt)agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)result = agent_executor.invoke({    "input": "Create a file named 'test.txt' and write 'Hello, World!' to it."})

I need to create a file named 'test.txt' and then write the text 'Hello, World!' into it. I'll do this using shell commands in the terminal. 
Action: terminal  Action Input: echo 'Hello, World!' > test.txt  
Executing command: echo 'Hello, World!' > test.txt
The file 'test.txt' has been created with the content 'Hello, World!'. 
Final Answer: A file named 'test.txt' has been created with the content 'Hello, World!'.

github = GitHubAPIWrapper()toolkit = GitHubToolkit.from_github_api_wrapper(github)
tools = toolkit.get_tools()agent = create_react_agent(model, tools, prompt)...

export GITHUB_APP_ID="your-app-id"export GITHUB_APP_PRIVATE_KEY="path-to-private-key"export GITHUB_REPOSITORY="your-github-repository"