adding plugin interface instantiation

autogpt/plugins.py

@@ -1,21 +1,218 @@
 """Handles loading of plugins."""
 import importlib
 import json
-import mimetypes
 import os
 import zipfile
-from pathlib import Path
-from urllib.parse import urlparse
-from zipimport import zipimporter
-from typing import List, Optional, Tuple
-
 import openapi_python_client
 import requests
-from abstract_singleton import AbstractSingleton
-from openapi_python_client.cli import _process_config, Config as OpenAPIConfig
+import abc
+
+from pathlib import Path
+from typing import TypeVar
+from urllib.parse import urlparse
+from zipimport import zipimporter
+from openapi_python_client.cli import Config as OpenAPIConfig
+from typing import Any, Dict, List, Optional, Tuple, TypedDict
+from abstract_singleton import AbstractSingleton, Singleton
+
 
 from autogpt.config import Config
 
+PromptGenerator = TypeVar("PromptGenerator")
+
+
+class Message(TypedDict):
+    role: str
+    content: str
+
+
+class BaseOpenAIPlugin():
+    """
+    This is a template for Auto-GPT plugins.
+    """
+
+    def __init__(self, manifests_specs_clients: dict):
+        # super().__init__()
+        self._name = manifests_specs_clients["manifest"]["name_for_model"]
+        self._version = manifests_specs_clients["manifest"]["schema_version"]
+        self._description = manifests_specs_clients["manifest"]["description_for_model"]
+        self.client = manifests_specs_clients["client"]
+        self.manifest = manifests_specs_clients["manifest"]
+        self.openapi_spec = manifests_specs_clients["openapi_spec"]
+
+    def can_handle_on_response(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the on_response method.
+        Returns:
+            bool: True if the plugin can handle the on_response method."""
+        return False
+
+    def on_response(self, response: str, *args, **kwargs) -> str:
+        """This method is called when a response is received from the model."""
+        pass
+
+    def can_handle_post_prompt(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the post_prompt method.
+        Returns:
+            bool: True if the plugin can handle the post_prompt method."""
+        return False
+
+    def post_prompt(self, prompt: PromptGenerator) -> PromptGenerator:
+        """This method is called just after the generate_prompt is called,
+            but actually before the prompt is generated.
+        Args:
+            prompt (PromptGenerator): The prompt generator.
+        Returns:
+            PromptGenerator: The prompt generator.
+        """
+        pass
+
+    def can_handle_on_planning(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the on_planning method.
+        Returns:
+            bool: True if the plugin can handle the on_planning method."""
+        return False
+
+    def on_planning(
+            self, prompt: PromptGenerator, messages: List[Message]
+    ) -> Optional[str]:
+        """This method is called before the planning chat completion is done.
+        Args:
+            prompt (PromptGenerator): The prompt generator.
+            messages (List[str]): The list of messages.
+        """
+        pass
+
+    def can_handle_post_planning(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the post_planning method.
+        Returns:
+            bool: True if the plugin can handle the post_planning method."""
+        return False
+
+    def post_planning(self, response: str) -> str:
+        """This method is called after the planning chat completion is done.
+        Args:
+            response (str): The response.
+        Returns:
+            str: The resulting response.
+        """
+        pass
+
+    def can_handle_pre_instruction(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the pre_instruction method.
+        Returns:
+            bool: True if the plugin can handle the pre_instruction method."""
+        return False
+
+    def pre_instruction(self, messages: List[Message]) -> List[Message]:
+        """This method is called before the instruction chat is done.
+        Args:
+            messages (List[Message]): The list of context messages.
+        Returns:
+            List[Message]: The resulting list of messages.
+        """
+        pass
+
+    def can_handle_on_instruction(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the on_instruction method.
+        Returns:
+            bool: True if the plugin can handle the on_instruction method."""
+        return False
+
+    def on_instruction(self, messages: List[Message]) -> Optional[str]:
+        """This method is called when the instruction chat is done.
+        Args:
+            messages (List[Message]): The list of context messages.
+        Returns:
+            Optional[str]: The resulting message.
+        """
+        pass
+
+    def can_handle_post_instruction(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the post_instruction method.
+        Returns:
+            bool: True if the plugin can handle the post_instruction method."""
+        return False
+
+    def post_instruction(self, response: str) -> str:
+        """This method is called after the instruction chat is done.
+        Args:
+            response (str): The response.
+        Returns:
+            str: The resulting response.
+        """
+        pass
+
+    def can_handle_pre_command(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the pre_command method.
+        Returns:
+            bool: True if the plugin can handle the pre_command method."""
+        return False
+
+    def pre_command(
+            self, command_name: str, arguments: Dict[str, Any]
+    ) -> Tuple[str, Dict[str, Any]]:
+        """This method is called before the command is executed.
+        Args:
+            command_name (str): The command name.
+            arguments (Dict[str, Any]): The arguments.
+        Returns:
+            Tuple[str, Dict[str, Any]]: The command name and the arguments.
+        """
+        pass
+
+    def can_handle_post_command(self) -> bool:
+        """This method is called to check that the plugin can
+        handle the post_command method.
+        Returns:
+            bool: True if the plugin can handle the post_command method."""
+        return False
+
+    def post_command(self, command_name: str, response: str) -> str:
+        """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.
+        """
+        pass
+
+    def can_handle_chat_completion(
+            self, messages: Dict[Any, Any], model: str, temperature: float, max_tokens: int
+    ) -> bool:
+        """This method is called to check that the plugin can
+          handle the chat_completion method.
+        Args:
+            messages (List[Message]): The messages.
+            model (str): The model name.
+            temperature (float): The temperature.
+            max_tokens (int): The max tokens.
+          Returns:
+              bool: True if the plugin can handle the chat_completion method."""
+        return False
+
+    def handle_chat_completion(
+            self, messages: List[Message], model: str, temperature: float, max_tokens: int
+    ) -> str:
+        """This method is called when the chat completion is done.
+        Args:
+            messages (List[Message]): The messages.
+            model (str): The model name.
+            temperature (float): The temperature.
+            max_tokens (int): The max tokens.
+        Returns:
+            str: The resulting response.
+        """
+        pass
+
 
 def inspect_zip_for_module(zip_path: str, debug: bool = False) -> Optional[str]:
     """
@@ -37,6 +234,8 @@ def inspect_zip_for_module(zip_path: str, debug: bool = False) -> Optional[str]:
     if debug:
         print(f"Module '__init__.py' not found in the zipfile @ {zip_path}.")
     return None
+
+
 def write_dict_to_json_file(data: dict, file_path: str):
     """
     Write a dictionary to a JSON file.
@@ -156,6 +355,29 @@ def initialize_openai_plugins(manifests_specs: dict, cfg: Config, debug: bool =
     return manifests_specs
 
 
+def instantiate_openai_plugin_clients(manifests_specs_clients: dict, cfg: Config, debug: bool = False) -> dict:
+    """
+    Instantiates BaseOpenAIPluginClient instances for each OpenAI plugin.
+    Args:
+        manifests_specs_clients (dict): per url dictionary of manifest, spec and client.
+        cfg (Config): Config instance including plugins config
+        debug (bool, optional): Enable debug logging. Defaults to False.
+    Returns:
+          plugins (dict): per url dictionary of BaseOpenAIPluginClient instances.
+
+    """
+    plugins = {}
+    for url, manifest_spec_client in manifests_specs_clients.items():
+        plugins[url] = BaseOpenAIPluginClient(
+            manifest=manifest_spec_client['manifest'],
+            openapi_spec=manifest_spec_client['openapi_spec'],
+            client=manifest_spec_client['client'],
+            cfg=cfg,
+            debug=debug
+        )
+    return plugins
+
+
 def scan_plugins(cfg: Config, debug: bool = False) -> List[Tuple[str, Path]]:
     """Scan the plugins directory for plugins.
 
@@ -177,6 +399,11 @@ def scan_plugins(cfg: Config, debug: bool = False) -> List[Tuple[str, Path]]:
         manifests_specs = fetch_openai_plugins_manifest_and_spec(cfg)
         if manifests_specs.keys():
             manifests_specs_clients = initialize_openai_plugins(manifests_specs, cfg, debug)
+            for url, openai_plugin_meta in manifests_specs_clients.items():
+                plugin = BaseOpenAIPlugin(openai_plugin_meta)
+                plugins.append((plugin, url))
+
+
     return plugins
 
 

requirements.txt

@@ -28,3 +28,9 @@ gitpython==3.1.31
 pytest
 pytest-mock
 tweepy
+
+
+# OpenAI plugins import
+openapi-python-client==0.13.4
+abstract-singleton
+auto-vicuna