a prompt as part of a function docstring, with additional documentation for devs.    It needs to be a code block, marked as a `<prompt>` language    ```<prompt>    Write me a short header for my post about {topic} for {platform} platform.     It should be for {audience} audience.    (Max 15 words)    ```    Now only to code block above will be used as a prompt, and the rest of the docstring will be used as a description for developers.    (It has also a nice benefit that IDE (like VS code) will display the prompt properly (not trying to parse it as markdown, and thus not showing new lines properly))    """    return Chat messages prompt‚ÄãFor chat models is very useful to define prompt as a set of message templates... here is how to do it:@llm_promptdef simulate_conversation(human_input:str, agent_role:str="a pirate"):    """    ## System message     - note the `:system` sufix inside the <prompt:_role_> tag         ```<prompt:system>    You are a {agent_role} hacker. You mus act like one.    You reply always in code, using python or javascript code block...    for example:        ... do not reply with anything else.. just with code - respecting your role.    ```    # human message     (we are using the real role that are enforced by the LLM - GPT supports system, assistant, user)    ``` <prompt:user>    Helo, who are you    ```    a reply:        ``` <prompt:assistant>    \``` python <<- escaping inner code block with \ that should be part of the prompt    def hello():        print("Argh... hello you pesky pirate")    \```    ```        we can also add some history using placeholder    ```<prompt:placeholder>    {history}    ```    ```<prompt:user>    {human_input}    ```    Now only to code block above will be used as a prompt, and the rest of the docstring will be used as a description for developers.    (It has also a nice benefit that IDE (like VS code) will display the prompt properly (not trying to parse it as markdown, and thus not showing new lines
lanchchain decorators is a layer on the top of LangChain that provides syntactic sugar üç≠ for writing custom langchain prompts and chains
lanchchain decorators is a layer on the top of LangChain that provides syntactic sugar üç≠ for writing custom langchain prompts and chains ->: a prompt as part of a function docstring, with additional documentation for devs.    It needs to be a code block, marked as a `<prompt>` language    ```<prompt>    Write me a short header for my post about {topic} for {platform} platform.     It should be for {audience} audience.    (Max 15 words)    ```    Now only to code block above will be used as a prompt, and the rest of the docstring will be used as a description for developers.    (It has also a nice benefit that IDE (like VS code) will display the prompt properly (not trying to parse it as markdown, and thus not showing new lines properly))    """    return Chat messages prompt‚ÄãFor chat models is very useful to define prompt as a set of message templates... here is how to do it:@llm_promptdef simulate_conversation(human_input:str, agent_role:str="a pirate"):    """    ## System message     - note the `:system` sufix inside the <prompt:_role_> tag         ```<prompt:system>    You are a {agent_role} hacker. You mus act like one.    You reply always in code, using python or javascript code block...    for example:        ... do not reply with anything else.. just with code - respecting your role.    ```    # human message     (we are using the real role that are enforced by the LLM - GPT supports system, assistant, user)    ``` <prompt:user>    Helo, who are you    ```    a reply:        ``` <prompt:assistant>    \``` python <<- escaping inner code block with \ that should be part of the prompt    def hello():        print("Argh... hello you pesky pirate")    \```    ```        we can also add some history using placeholder    ```<prompt:placeholder>    {history}    ```    ```<prompt:user>    {human_input}    ```    Now only to code block above will be used as a prompt, and the rest of the docstring will be used as a description for developers.    (It has also a nice benefit that IDE (like VS code) will display the prompt properly (not trying to parse it as markdown, and thus not showing new lines