significant-gravitas / auto-gpt-plugin-template Goto Github PK

Could somebody please improve the documentation?

From what I can gather, a plugin must extend AutoGPTPluginTemplate and set:

• self._name
• self._version
• self._description

It should also implement can_handle_xxxx methods, returning True only if they do something other than pass in xxxx, the options of which are:

post_prompt

This method is called just after the generate_prompt is called, but actually before the prompt is generated.

...why?

This seems to be the only method that any of the existing plugins currently implement.

I can see that they register commands that they can support, presumably this is only called once. I'm not sure how the class registers it self though.

I can see that they define the args that are provided to the function being registered. "imap_search_command": "<imap_search_criteria_command>", seems to break a convention - any reason, or is the string content just arbitrary?

Parameters:

• prompt: PromptGenerator - okay, this is actually fairly well documented. The prompt is sent to the LLM

on_response

Parameters:

• response - I guess we're expecting it's as per below?
• *args - is this {"arg name": "value"} ?
• *kwargs ...I've got no idea

Return

A string - but what should it look like? Who/what reads it and when/why?
...Is this just a string, as you'd see in a response from ChatGPT?

This method is called when a response is received from the model

response format

        {
          "thoughts": {
                "text": "thought",
                "reasoning": "reasoning",
                "plan": "- short bulleted\n- list that conveys\n- long-term plan",
                "criticism": "constructive self-criticism",
                "speak": "thoughts summary to say to user",
            },
            "command": {"name": "command name", "args": {"arg name": "value"}},
        }

on_planning

This method is called before the planning chat completion is done

...Who is involved in this "planning chat"?
...What are the messages? Are they just {role: "", content: ""}? Can somebody please provide a realistic example?

Parameters

• prompt: PromptGenerator
• messages: List[Message]

Returns

Optional string - what/why?

post_planning

This method is called after the planning chat completion is done.

Parameters:

• response: str

Returns

• str - what should this be?

pre_instruction

This method is called before the instruction chat is done

Parameters

• messages (List[Message]): The list of context messages.

...can we get have an example?

Returns

the same messages?

on_instruction

This method is called when the instruction chat is done.

Parameters

• messages (List[Message]): The list of context messages.

...what do the context messages look like? Are they for humans or the system?

post_instruction

This method is called after the instruction chat is done

Args:
response (str): The response.

    Returns:
        str: The resulting response.

pre_command

This method is called before the command is executed

...some example use cases for some of these would be useful

Args:
command_name (str): The command name.
arguments (Dict[str, Any]): The arguments.

post_command

This method is called after the command is executed.

    Args:
        command_name (str): The command name.
        response (str): The response.

    Returns:
        str: The resulting response.

handle_chat_completion

This method is called when the chat completion is done.

...the whole session or one turn?

  Args:
        messages (List[Message]): The messages.
        model (str): The model name.
        temperature (float): The temperature.
        max_tokens (int): The max tokens.

user_input

This method is called to request user input to the user

• user_input (str): The question or prompt to ask the user.

returns the user input as a string

report

Generates a report to the user
...what's in the message?

• mesage: str

While running docker compose run --rm auto-gpt --install-plugin-deps, the following error appears:

Plugin config is invalid, continuing without plugins. Error: Invalid plugin config data type: <class 'list'>

My plugins_config.yaml file content is:

commercetools:
  - config: {} # Configs from the plugin README and installation instructions.
  - enabled: true

When i remove the hyphen from the plugins_config.yaml file, the error does not appear anymore but the plugin is not loaded

The auto-gpt-plugin-template package on pypi is out of date, and seems out of sync with this repo:

• Repo says version is 0.0.2, latest version on pypi is 0.0.3
• API in repo constains fixes that the 0.0.3 release on pypi lacks
  • List[Message] in the repo vs List[str] in the package

This causes type errors in the Auto-GPT codebase, because it imports the pypi package rather than the repo:

Hi my name is Kepar,
recently i found a chatgpt clone (3.5 turbo) model for free

i leave the code here, tell me if something happens with this, hope i helped the world

import json
import requests

safeInput = input('Request:  ')

# Prepare the data payload
data = {
    "prompt": safeInput
}
payload = json.dumps(data)

# Set the headers
headers = {
    "User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/110.0",
    "Accept": "application/json, text/plain, */*",
    "Accept-Language": "en-US,en;q=0.5",
    "Content-Type": "application/json",
    "Origin": "https://chatbot.theb.ai",
    "Referer": "https://chatbot.theb.ai/"
}

# Send the POST request
url = "https://chatbot.theb.ai/api/chat-process"
response = requests.post(url, data=payload, headers=headers)

# Process the response
if response.status_code == 200:
    response_text = response.text

    # Find the last JSON string in the response text
    json_strings = response_text.strip().split('\n')
    last_json_string = json_strings[-1]

    response_json = json.loads(last_json_string)
    print(response_json['text'])
else:
    print("Error:", response.status_code)
    ```
IF SOMEONE CAN MAKE A PLUGIN FOR THIS API, IT COULD BE REALLY APPRECIATED