add non-software role/action BaseModel

metagpt/actions/clone_function.py

@@ -1,8 +1,12 @@
 import traceback
 from pathlib import Path
 
+from pydantic import Field
+
 from metagpt.actions.write_code import WriteCode
+from metagpt.llm import LLM
 from metagpt.logs import logger
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.schema import Message
 from metagpt.utils.highlight import highlight
 
@@ -27,8 +31,9 @@ def run(*args) -> pd.DataFrame:
 
 
 class CloneFunction(WriteCode):
-    def __init__(self, name="CloneFunction", context: list[Message] = None, llm=None):
-        super().__init__(name, context, llm)
+    name: str = "CloneFunction"
+    context: list[Message] = []
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     def _save(self, code_path, code):
         if isinstance(code_path, str):

metagpt/actions/design_api_review.py

@@ -5,12 +5,20 @@
 @Author  : alexanderwu
 @File    : design_api_review.py
 """
+
+from typing import Optional
+
+from pydantic import Field
+
 from metagpt.actions.action import Action
+from metagpt.llm import LLM
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 
 
 class DesignReview(Action):
-    def __init__(self, name, context=None, llm=None):
-        super().__init__(name, context, llm)
+    name: str = "DesignReview"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     async def run(self, prd, api_design):
         prompt = (

metagpt/actions/execute_task.py

@@ -5,13 +5,19 @@
 @Author  : femto Zheng
 @File    : execute_task.py
 """
+
+from pydantic import Field
+
 from metagpt.actions import Action
+from metagpt.llm import LLM
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.schema import Message
 
 
 class ExecuteTask(Action):
-    def __init__(self, name="ExecuteTask", context: list[Message] = None, llm=None):
-        super().__init__(name, context, llm)
+    name: str = "ExecuteTask"
+    context: list[Message] = []
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     def run(self, *args, **kwargs):
         pass

metagpt/actions/generate_questions.py

@@ -21,5 +21,7 @@ class GenerateQuestions(Action):
     """This class allows LLM to further mine noteworthy details based on specific "##TOPIC"(discussion topic) and
     "##RECORD" (discussion records), thereby deepening the discussion."""
 
+    name: str = "GenerateQuestions"
+
     async def run(self, context):
         return await QUESTIONS.fill(context=context, llm=self.llm)

metagpt/actions/invoice_ocr.py

@@ -12,17 +12,21 @@ import os
 import zipfile
 from datetime import datetime
 from pathlib import Path
+from typing import Optional
 
 import pandas as pd
 from paddleocr import PaddleOCR
+from pydantic import Field
 
 from metagpt.actions import Action
 from metagpt.const import INVOICE_OCR_TABLE_PATH
+from metagpt.llm import LLM
 from metagpt.logs import logger
 from metagpt.prompts.invoice_ocr import (
     EXTRACT_OCR_MAIN_INFO_PROMPT,
     REPLY_OCR_QUESTION_PROMPT,
 )
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.utils.common import OutputParser
 from metagpt.utils.file import File
 
@@ -36,8 +40,9 @@ class InvoiceOCR(Action):
 
     """
 
-    def __init__(self, name: str = "", *args, **kwargs):
-        super().__init__(name, *args, **kwargs)
+    name: str = "InvoiceOCR"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     @staticmethod
     async def _check_file_type(file_path: Path) -> str:
@@ -125,9 +130,9 @@ class GenerateTable(Action):
 
     """
 
-    def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
-        super().__init__(name, *args, **kwargs)
-        self.language = language
+    name: str = "GenerateTable"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     async def run(self, ocr_results: list, filename: str, *args, **kwargs) -> dict[str, str]:
         """Processes OCR results, extracts invoice information, generates a table, and saves it as an Excel file.
@@ -169,9 +174,10 @@ class ReplyQuestion(Action):
 
     """
 
-    def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
-        super().__init__(name, *args, **kwargs)
-        self.language = language
+    name: str = "ReplyQuestion"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+    language: str = "ch"
 
     async def run(self, query: str, ocr_result: list, *args, **kwargs) -> str:
         """Reply to questions based on ocr results.

metagpt/actions/prepare_interview.py

@@ -19,5 +19,7 @@ Attention: Provide as markdown block as the format above, at least 10 questions.
 
 
 class PrepareInterview(Action):
+    name: str = "PrepareInterview"
+
     async def run(self, context):
         return await QUESTIONS.fill(context=context, llm=self.llm)

metagpt/actions/research.py

@@ -3,13 +3,15 @@
 from __future__ import annotations
 
 import asyncio
-from typing import Callable
+from typing import Callable, Optional, Union
 
-from pydantic import parse_obj_as
+from pydantic import Field, parse_obj_as
 
 from metagpt.actions import Action
 from metagpt.config import CONFIG
+from metagpt.llm import LLM
 from metagpt.logs import logger
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.tools.search_engine import SearchEngine
 from metagpt.tools.web_browser_engine import WebBrowserEngine, WebBrowserEngineType
 from metagpt.utils.common import OutputParser
@@ -78,17 +80,12 @@ above. The report must meet the following requirements:
 class CollectLinks(Action):
     """Action class to collect links from a search engine."""
 
-    def __init__(
-        self,
-        name: str = "",
-        *args,
-        rank_func: Callable[[list[str]], None] | None = None,
-        **kwargs,
-    ):
-        super().__init__(name, *args, **kwargs)
-        self.desc = "Collect links from a search engine."
-        self.search_engine = SearchEngine()
-        self.rank_func = rank_func
+    name: str = "CollectLinks"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+    desc: str = "Collect links from a search engine."
+    search_engine: SearchEngine = Field(default_factory=SearchEngine)
+    rank_func: Union[Callable[[list[str]], None], None] = None
 
     async def run(
         self,
@@ -178,20 +175,20 @@ class CollectLinks(Action):
 class WebBrowseAndSummarize(Action):
     """Action class to explore the web and provide summaries of articles and webpages."""
 
-    def __init__(
-        self,
-        *args,
-        browse_func: Callable[[list[str]], None] | None = None,
-        **kwargs,
-    ):
-        super().__init__(*args, **kwargs)
+    name: str = "WebBrowseAndSummarize"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+    desc = "Explore the web and provide summaries of articles and webpages."
+    browse_func = Union[Callable[[list[str]], None], None] = None
+    web_browser_engine: WebBrowserEngine = WebBrowserEngine(
+        engine=WebBrowserEngineType.CUSTOM if browse_func else None,
+        run_func=browse_func,
+    )
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
         if CONFIG.model_for_researcher_summary:
             self.llm.model = CONFIG.model_for_researcher_summary
-        self.web_browser_engine = WebBrowserEngine(
-            engine=WebBrowserEngineType.CUSTOM if browse_func else None,
-            run_func=browse_func,
-        )
-        self.desc = "Explore the web and provide summaries of articles and webpages."
 
     async def run(
         self,
@@ -247,8 +244,12 @@ class WebBrowseAndSummarize(Action):
 class ConductResearch(Action):
     """Action class to conduct research and generate a research report."""
 
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
+    name: str = "ConductResearch"
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
         if CONFIG.model_for_researcher_report:
             self.llm.model = CONFIG.model_for_researcher_report
 

metagpt/actions/write_docstring.py

@@ -22,9 +22,13 @@ This script uses the 'fire' library to create a command-line interface. It gener
 the specified docstring style and adds them to the code.
 """
 import ast
-from typing import Literal
+from typing import Literal, Optional
+
+from pydantic import Field
 
 from metagpt.actions.action import Action
+from metagpt.llm import LLM
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.utils.common import OutputParser
 from metagpt.utils.pycst import merge_docstring
 
@@ -157,9 +161,9 @@ class WriteDocstring(Action):
         desc: A string describing the action.
     """
 
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.desc = "Write docstring for code."
+    desc: str = "Write docstring for code."
+    context: Optional[str] = None
+    llm: BaseGPTAPI = Field(default_factory=LLM)
 
     async def run(
         self,

metagpt/actions/write_review.py

@@ -6,8 +6,12 @@
 """
 from typing import List
 
+from pydantic import Field
+
 from metagpt.actions import Action
 from metagpt.actions.action_node import ActionNode
+from metagpt.llm import LLM
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 
 REVIEW = ActionNode(
     key="Review",
@@ -33,5 +37,8 @@ WRITE_REVIEW_NODE = ActionNode.from_children("WRITE_REVIEW_NODE", [REVIEW, LGTM]
 class WriteReview(Action):
     """Write a review for the given context."""
 
+    name: str = "WriteReview"
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+
     async def run(self, context):
         return await WRITE_REVIEW_NODE.fill(context=context, llm=self.llm, schema="json")

metagpt/actions/write_tutorial.py

@@ -9,8 +9,12 @@
 
 from typing import Dict
 
+from pydantic import Field
+
 from metagpt.actions import Action
+from metagpt.llm import LLM
 from metagpt.prompts.tutorial_assistant import CONTENT_PROMPT, DIRECTORY_PROMPT
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.utils.common import OutputParser
 
 
@@ -22,9 +26,9 @@ class WriteDirectory(Action):
         language: The language to output, default is "Chinese".
     """
 
-    def __init__(self, name: str = "", language: str = "Chinese", *args, **kwargs):
-        super().__init__(name, *args, **kwargs)
-        self.language = language
+    name: str = "WriteDirectory"
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+    language: str = "Chinese"
 
     async def run(self, topic: str, *args, **kwargs) -> Dict:
         """Execute the action to generate a tutorial directory according to the topic.
@@ -49,10 +53,10 @@ class WriteContent(Action):
         language: The language to output, default is "Chinese".
     """
 
-    def __init__(self, name: str = "", directory: str = "", language: str = "Chinese", *args, **kwargs):
-        super().__init__(name, *args, **kwargs)
-        self.language = language
-        self.directory = directory
+    name: str = "WriteContent"
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+    directory: str = ""
+    language: str = "Chinese"
 
     async def run(self, topic: str, *args, **kwargs) -> str:
         """Execute the action to write document content according to the directory and topic.

metagpt/roles/customer_service.py

@@ -29,8 +29,4 @@ class CustomerService(Sales):
     name: str = "Xiaomei"
     profile: str = "Human customer service"
     desc: str = DESC
-
     store: Optional[str] = None
-
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)

metagpt/roles/invoice_ocr_assistant.py

@@ -7,11 +7,13 @@
 @File    : invoice_ocr_assistant.py
 """
 
+from typing import Optional
+
 import pandas as pd
 
 from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, ReplyQuestion
 from metagpt.prompts.invoice_ocr import INVOICE_OCR_SUCCESS
-from metagpt.roles import Role
+from metagpt.roles.role import Role, RoleReactMode
 from metagpt.schema import Message
 
 
@@ -28,21 +30,18 @@ class InvoiceOCRAssistant(Role):
         language: The language in which the invoice table will be generated.
     """
 
-    def __init__(
-        self,
-        name: str = "Stitch",
-        profile: str = "Invoice OCR Assistant",
-        goal: str = "OCR identifies invoice files and generates invoice main information table",
-        constraints: str = "",
-        language: str = "ch",
-    ):
-        super().__init__(name, profile, goal, constraints)
-        self._init_actions([InvoiceOCR])
-        self.language = language
-        self.filename = ""
-        self.origin_query = ""
-        self.orc_data = None
-        self._set_react_mode(react_mode="by_order")
+    name: str = "Stitch"
+    profile: str = "Invoice OCR Assistant"
+    goal: str = "OCR identifies invoice files and generates invoice main information table"
+    constraints: str = ""
+    language: str = "ch"
+    filename: str = ""
+    origin_query: str = ""
+    orc_data: Optional[list] = None
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._set_react_mode(react_mode=RoleReactMode.BY_ORDER.value)
 
     async def _act(self) -> Message:
         """Perform an action as determined by the role.

metagpt/roles/researcher.py

@@ -13,7 +13,7 @@ from metagpt.actions import Action, CollectLinks, ConductResearch, WebBrowseAndS
 from metagpt.actions.research import get_research_system_text
 from metagpt.const import RESEARCH_PATH
 from metagpt.logs import logger
-from metagpt.roles import Role
+from metagpt.roles.role import Role, RoleReactMode
 from metagpt.schema import Message
 
 
@@ -25,21 +25,20 @@ class Report(BaseModel):
 
 
 class Researcher(Role):
-    def __init__(
-        self,
-        name: str = "David",
-        profile: str = "Researcher",
-        goal: str = "Gather information and conduct research",
-        constraints: str = "Ensure accuracy and relevance of information",
-        language: str = "en-us",
-        **kwargs,
-    ):
-        super().__init__(name, profile, goal, constraints, **kwargs)
-        self._init_actions([CollectLinks(name), WebBrowseAndSummarize(name), ConductResearch(name)])
-        self._set_react_mode(react_mode="by_order")
-        self.language = language
-        if language not in ("en-us", "zh-cn"):
-            logger.warning(f"The language `{language}` has not been tested, it may not work.")
+    name: str = "David"
+    profile: str = "Researcher"
+    goal: str = "Gather information and conduct research"
+    constraints: str = "Ensure accuracy and relevance of information"
+    language: str = "en-us"
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._init_actions(
+            [CollectLinks(name=self.name), WebBrowseAndSummarize(name=self.name), ConductResearch(name=self.name)]
+        )
+        self._set_react_mode(react_mode=RoleReactMode.BY_ORDER.value)
+        if self.language not in ("en-us", "zh-cn"):
+            logger.warning(f"The language `{self.language}` has not been tested, it may not work.")
 
     async def _think(self) -> bool:
         if self._rc.todo is None:
@@ -118,7 +117,7 @@ if __name__ == "__main__":
     import fire
 
     async def main(topic: str, language="en-us"):
-        role = Researcher(topic, language=language)
+        role = Researcher(language=language)
         await role.run(topic)
 
     fire.Fire(main)

metagpt/roles/sales.py

@@ -22,7 +22,6 @@ class Sales(Role):
     " I don't know, and I won't tell you that this is from the knowledge base,"
     "but pretend to be what I know. Note that each of my replies will be replied in the tone of a "
     "professional guide"
-
     store: Optional[str] = None
 
     def __init__(self, **kwargs):

metagpt/roles/sk_agent.py

@@ -7,13 +7,16 @@
 @Modified By: mashenquan, 2023-11-1. In accordance with Chapter 2.2.1 and 2.2.2 of RFC 116, utilize the new message
         distribution feature for message filtering.
 """
+
+from pydantic import Field
 from semantic_kernel.planning import SequentialPlanner
 from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
 from semantic_kernel.planning.basic_planner import BasicPlanner
 
 from metagpt.actions import UserRequirement
 from metagpt.actions.execute_task import ExecuteTask
-from metagpt.logs import logger
+from metagpt.llm import LLM
+from metagpt.provider.base_gpt_api import BaseGPTAPI
 from metagpt.roles import Role
 from metagpt.schema import Message
 from metagpt.utils.make_sk_kernel import make_sk_kernel
@@ -30,27 +33,28 @@ class SkAgent(Role):
         constraints (str): Constraints for the SkAgent.
     """
 
-    def __init__(
-        self,
-        name: str = "Sunshine",
-        profile: str = "sk_agent",
-        goal: str = "Execute task based on passed in task description",
-        constraints: str = "",
-        planner_cls=BasicPlanner,
-    ) -> None:
+    name: str = "Sunshine"
+    profile: str = "sk_agent"
+    goal: str = "Execute task based on passed in task description"
+    constraints: str = ""
+    planner_cls: BasicPlanner = BasicPlanner
+    planner: BasicPlanner = Field(default_factory=BasicPlanner)
+    llm: BaseGPTAPI = Field(default_factory=LLM)
+
+    def __init__(self, **kwargs) -> None:
         """Initializes the Engineer role with given attributes."""
-        super().__init__(name, profile, goal, constraints)
+        super().__init__(**kwargs)
         self._init_actions([ExecuteTask()])
         self._watch([UserRequirement])
         self.kernel = make_sk_kernel()
 
         # how funny the interface is inconsistent
-        if planner_cls == BasicPlanner:
-            self.planner = planner_cls()
-        elif planner_cls in [SequentialPlanner, ActionPlanner]:
-            self.planner = planner_cls(self.kernel)
+        if self.planner_cls == BasicPlanner:
+            self.planner = self.planner_cls()
+        elif self.planner_cls in [SequentialPlanner, ActionPlanner]:
+            self.planner = self.planner_cls(self.kernel)
         else:
-            raise f"Unsupported planner of type {planner_cls}"
+            raise Exception(f"Unsupported planner of type {self.planner_cls}")
 
         self.import_semantic_skill_from_directory = self.kernel.import_semantic_skill_from_directory
         self.import_skill = self.kernel.import_skill

metagpt/roles/tutorial_assistant.py

@@ -12,7 +12,7 @@ from typing import Dict
 from metagpt.actions.write_tutorial import WriteContent, WriteDirectory
 from metagpt.const import TUTORIAL_PATH
 from metagpt.logs import logger
-from metagpt.roles import Role
+from metagpt.roles.role import Role, RoleReactMode
 from metagpt.schema import Message
 from metagpt.utils.file import File
 
@@ -28,21 +28,20 @@ class TutorialAssistant(Role):
         language: The language in which the tutorial documents will be generated.
     """
 
-    def __init__(
-        self,
-        name: str = "Stitch",
-        profile: str = "Tutorial Assistant",
-        goal: str = "Generate tutorial documents",
-        constraints: str = "Strictly follow Markdown's syntax, with neat and standardized layout",
-        language: str = "Chinese",
-    ):
-        super().__init__(name, profile, goal, constraints)
-        self._init_actions([WriteDirectory(language=language)])
-        self.topic = ""
-        self.main_title = ""
-        self.total_content = ""
-        self.language = language
-        self._set_react_mode(react_mode="by_order")
+    name: str = "Stitch"
+    profile: str = "Tutorial Assistant"
+    goal: str = "Generate tutorial documents"
+    constraints: str = "Strictly follow Markdown's syntax, with neat and standardized layout"
+    language: str = "Chinese"
+
+    topic = ""
+    main_title = ""
+    total_content = ""
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._init_actions([WriteDirectory(language=self.language)])
+        self._set_react_mode(react_mode=RoleReactMode.BY_ORDER.value)
 
     async def _handle_directory(self, titles: Dict) -> Message:
         """Handle the directories for the tutorial document.