delete coreconfig, using the initial config instead

Author: WannaTen

metagpt/core/actions/action_graph.py

@@ -7,7 +7,7 @@
 """
 from __future__ import annotations
 
-# from metagpt.actions.action_node import ActionNode
+# from metagpt.core.actions.action_node import ActionNode
 
 
 class ActionGraph:

metagpt/core/config.py renamed to metagpt/core/config2.py

@@ -7,13 +7,21 @@
 """
 import os
 from pathlib import Path
-from typing import Dict, Iterable, Literal
+from typing import Dict, Iterable, List, Literal, Optional
 
 from pydantic import BaseModel, Field, model_validator
 
+from metagpt.core.configs.browser_config import BrowserConfig
+from metagpt.core.configs.embedding_config import EmbeddingConfig
 from metagpt.core.configs.exp_pool_config import ExperiencePoolConfig
-from metagpt.core.configs.llm_config import LLMConfig
+from metagpt.core.configs.llm_config import LLMConfig, LLMType
+from metagpt.core.configs.mermaid_config import MermaidConfig
+from metagpt.core.configs.omniparse_config import OmniParseConfig
+from metagpt.core.configs.redis_config import RedisConfig
+from metagpt.core.configs.role_custom_config import RoleCustomConfig
 from metagpt.core.configs.role_zero_config import RoleZeroConfig
+from metagpt.core.configs.s3_config import S3Config
+from metagpt.core.configs.search_config import SearchConfig
 from metagpt.core.configs.workspace_config import WorkspaceConfig
 from metagpt.core.const import CONFIG_ROOT, METAGPT_ROOT
 from metagpt.core.utils.yaml_model import YamlModel
@@ -38,23 +46,54 @@ def check_project_path(self):
         return self
 
 
-class CoreConfig(CLIParams, YamlModel):
+class Config(CLIParams, YamlModel):
     """Configurations for MetaGPT"""
 
-    workspace: WorkspaceConfig = Field(default_factory=WorkspaceConfig)
-
     # Key Parameters
     llm: LLMConfig
 
+    # RAG Embedding
+    embedding: EmbeddingConfig = EmbeddingConfig()
+
+    # omniparse
+    omniparse: OmniParseConfig = OmniParseConfig()
+
     # Global Proxy. Will be used if llm.proxy is not set
     proxy: str = ""
 
-    # Experience Pool Parameters
-    exp_pool: ExperiencePoolConfig = Field(default_factory=ExperiencePoolConfig)
+    # Tool Parameters
+    search: SearchConfig = SearchConfig()
+    enable_search: bool = False
+    browser: BrowserConfig = BrowserConfig()
+    mermaid: MermaidConfig = MermaidConfig()
+
+    # Storage Parameters
+    s3: Optional[S3Config] = None
+    redis: Optional[RedisConfig] = None
 
     # Misc Parameters
     repair_llm_output: bool = False
     prompt_schema: Literal["json", "markdown", "raw"] = "json"
+    workspace: WorkspaceConfig = Field(default_factory=WorkspaceConfig)
+    enable_longterm_memory: bool = False
+    code_validate_k_times: int = 2
+
+    # Experience Pool Parameters
+    exp_pool: ExperiencePoolConfig = Field(default_factory=ExperiencePoolConfig)
+
+    # Will be removed in the future
+    metagpt_tti_url: str = ""
+    language: str = "English"
+    redis_key: str = "placeholder"
+    iflytek_app_id: str = ""
+    iflytek_api_secret: str = ""
+    iflytek_api_key: str = ""
+    azure_tts_subscription_key: str = ""
+    azure_tts_region: str = ""
+    _extra: dict = dict()  # extra config dict
+
+    # Role's custom configuration
+    roles: Optional[List[RoleCustomConfig]] = None
 
     # RoleZero's configuration
     role_zero: RoleZeroConfig = Field(default_factory=RoleZeroConfig)
@@ -65,10 +104,10 @@ def from_home(cls, path):
         pathname = CONFIG_ROOT / path
         if not pathname.exists():
             return None
-        return CoreConfig.from_yaml_file(pathname)
+        return Config.from_yaml_file(pathname)
 
     @classmethod
-    def default(cls, reload: bool = False, **kwargs) -> "CoreConfig":
+    def default(cls, reload: bool = False, **kwargs) -> "Config":
         """Load default config
         - Priority: env < default_config_paths
         - Inside default_config_paths, the latter one overwrites the former one
@@ -78,24 +117,24 @@ def default(cls, reload: bool = False, **kwargs) -> "CoreConfig":
             CONFIG_ROOT / "config2.yaml",
         )
         if reload or default_config_paths not in _CONFIG_CACHE:
-            dicts = [dict(os.environ), *(CoreConfig.read_yaml(path) for path in default_config_paths), kwargs]
+            dicts = [dict(os.environ), *(Config.read_yaml(path) for path in default_config_paths), kwargs]
             final = merge_dict(dicts)
-            _CONFIG_CACHE[default_config_paths] = CoreConfig(**final)
+            _CONFIG_CACHE[default_config_paths] = Config(**final)
         return _CONFIG_CACHE[default_config_paths]
 
     @classmethod
     def from_llm_config(cls, llm_config: dict):
         """user config llm
         example:
         llm_config = {"api_type": "xxx", "api_key": "xxx", "model": "xxx"}
-        gpt4 = CoreConfig.from_llm_config(llm_config)
+        gpt4 = Config.from_llm_config(llm_config)
         A = Role(name="A", profile="Democratic candidate", goal="Win the election", actions=[a1], watch=[a2], config=gpt4)
         """
         llm_config = LLMConfig.model_validate(llm_config)
         dicts = [dict(os.environ)]
         dicts += [{"llm": llm_config}]
         final = merge_dict(dicts)
-        return CoreConfig(**final)
+        return Config(**final)
 
     def update_via_cli(self, project_path, project_name, inc, reqa_file, max_auto_summarize_code):
         """update config via cli"""
@@ -110,6 +149,26 @@ def update_via_cli(self, project_path, project_name, inc, reqa_file, max_auto_su
         self.reqa_file = reqa_file
         self.max_auto_summarize_code = max_auto_summarize_code
 
+    @property
+    def extra(self):
+        return self._extra
+
+    @extra.setter
+    def extra(self, value: dict):
+        self._extra = value
+
+    def get_openai_llm(self) -> Optional[LLMConfig]:
+        """Get OpenAI LLMConfig by name. If no OpenAI, raise Exception"""
+        if self.llm.api_type == LLMType.OPENAI:
+            return self.llm
+        return None
+
+    def get_azure_llm(self) -> Optional[LLMConfig]:
+        """Get Azure LLMConfig by name. If no Azure, raise Exception"""
+        if self.llm.api_type == LLMType.AZURE:
+            return self.llm
+        return None
+
 
 def merge_dict(dicts: Iterable[Dict]) -> Dict:
     """Merge multiple dicts into one, with the latter dict overwriting the former"""
@@ -120,3 +179,4 @@ def merge_dict(dicts: Iterable[Dict]) -> Dict:
 
 
 _CONFIG_CACHE = {}
+config = Config.default()

metagpt/core/configs/browser_config.py

@@ -0,0 +1,31 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/4 19:06
+@Author  : alexanderwu
+@File    : browser_config.py
+"""
+from enum import Enum
+from typing import Literal
+
+from metagpt.core.utils.yaml_model import YamlModel
+
+
+class WebBrowserEngineType(Enum):
+    PLAYWRIGHT = "playwright"
+    SELENIUM = "selenium"
+    CUSTOM = "custom"
+
+    @classmethod
+    def __missing__(cls, key):
+        """Default type conversion"""
+        return cls.CUSTOM
+
+
+class BrowserConfig(YamlModel):
+    """Config for Browser"""
+
+    engine: WebBrowserEngineType = WebBrowserEngineType.PLAYWRIGHT
+    browser_type: Literal["chromium", "firefox", "webkit", "chrome", "firefox", "edge", "ie"] = "chromium"
+    """If the engine is Playwright, the value should be one of "chromium", "firefox", or "webkit". If it is Selenium, the value
+    should be either "chrome", "firefox", "edge", or "ie"."""

metagpt/core/configs/embedding_config.py

@@ -0,0 +1,54 @@
+from enum import Enum
+from typing import Optional
+
+from pydantic import field_validator
+
+from metagpt.core.utils.yaml_model import YamlModel
+
+
+class EmbeddingType(Enum):
+    OPENAI = "openai"
+    AZURE = "azure"
+    GEMINI = "gemini"
+    OLLAMA = "ollama"
+
+
+class EmbeddingConfig(YamlModel):
+    """Config for Embedding.
+
+    Examples:
+    ---------
+    api_type: "openai"
+    api_key: "YOU_API_KEY"
+    dimensions: "YOUR_MODEL_DIMENSIONS"
+
+    api_type: "azure"
+    api_key: "YOU_API_KEY"
+    base_url: "YOU_BASE_URL"
+    api_version: "YOU_API_VERSION"
+    dimensions: "YOUR_MODEL_DIMENSIONS"
+
+    api_type: "gemini"
+    api_key: "YOU_API_KEY"
+
+    api_type: "ollama"
+    base_url: "YOU_BASE_URL"
+    model: "YOU_MODEL"
+    dimensions: "YOUR_MODEL_DIMENSIONS"
+    """
+
+    api_type: Optional[EmbeddingType] = None
+    api_key: Optional[str] = None
+    base_url: Optional[str] = None
+    api_version: Optional[str] = None
+
+    model: Optional[str] = None
+    embed_batch_size: Optional[int] = None
+    dimensions: Optional[int] = None  # output dimension of embedding model
+
+    @field_validator("api_type", mode="before")
+    @classmethod
+    def check_api_type(cls, v):
+        if v == "":
+            return None
+        return v

metagpt/core/configs/models_config.py

@@ -17,7 +17,7 @@
 
 from pydantic import Field, field_validator
 
-from metagpt.config2 import merge_dict
+from metagpt.core.config2 import merge_dict
 from metagpt.core.configs.llm_config import LLMConfig
 from metagpt.core.const import CONFIG_ROOT, METAGPT_ROOT
 from metagpt.core.utils.yaml_model import YamlModel

metagpt/core/configs/omniparse_config.py

@@ -0,0 +1,7 @@
+from metagpt.core.utils.yaml_model import YamlModel
+
+
+class OmniParseConfig(YamlModel):
+    api_key: str = ""
+    base_url: str = ""
+    timeout: int = 600

metagpt/core/configs/redis_config.py

@@ -0,0 +1,26 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/4 19:06
+@Author  : alexanderwu
+@File    : redis_config.py
+"""
+from metagpt.core.utils.yaml_model import YamlModelWithoutDefault
+
+
+class RedisConfig(YamlModelWithoutDefault):
+    host: str
+    port: int
+    username: str = ""
+    password: str
+    db: str
+
+    def to_url(self):
+        return f"redis://{self.host}:{self.port}"
+
+    def to_kwargs(self):
+        return {
+            "username": self.username,
+            "password": self.password,
+            "db": self.db,
+        }

metagpt/core/configs/role_custom_config.py

@@ -0,0 +1,19 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/4/22 16:33
+@Author  : Justin
+@File    : role_custom_config.py
+"""
+from metagpt.core.configs.llm_config import LLMConfig
+from metagpt.core.utils.yaml_model import YamlModel
+
+
+class RoleCustomConfig(YamlModel):
+    """custom config for roles
+    role: role's className or role's role_id
+    To be expanded
+    """
+
+    role: str = ""
+    llm: LLMConfig

metagpt/core/configs/s3_config.py

@@ -0,0 +1,15 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/4 19:07
+@Author  : alexanderwu
+@File    : s3_config.py
+"""
+from metagpt.core.utils.yaml_model import YamlModelWithoutDefault
+
+
+class S3Config(YamlModelWithoutDefault):
+    access_key: str
+    secret_key: str
+    endpoint: str
+    bucket: str

metagpt/core/configs/search_config.py

@@ -0,0 +1,41 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/4 19:06
+@Author  : alexanderwu
+@File    : search_config.py
+"""
+from enum import Enum
+from typing import Callable, Optional
+
+from pydantic import ConfigDict, Field
+
+from metagpt.core.utils.yaml_model import YamlModel
+
+
+class SearchEngineType(Enum):
+    SERPAPI_GOOGLE = "serpapi"
+    SERPER_GOOGLE = "serper"
+    DIRECT_GOOGLE = "google"
+    DUCK_DUCK_GO = "ddg"
+    CUSTOM_ENGINE = "custom"
+    BING = "bing"
+
+
+class SearchConfig(YamlModel):
+    """Config for Search"""
+
+    model_config = ConfigDict(extra="allow")
+
+    api_type: SearchEngineType = SearchEngineType.DUCK_DUCK_GO
+    api_key: str = ""
+    cse_id: str = ""  # for google
+    search_func: Optional[Callable] = None
+    params: dict = Field(
+        default_factory=lambda: {
+            "engine": "google",
+            "google_domain": "google.com",
+            "gl": "us",
+            "hl": "en",
+        }
+    )

metagpt/core/context.py

@@ -12,7 +12,7 @@
 
 from pydantic import BaseModel, ConfigDict, Field
 
-from metagpt.core.config import CoreConfig
+from metagpt.core.config2 import Config
 from metagpt.core.configs.llm_config import LLMConfig, LLMType
 from metagpt.core.provider.base_llm import BaseLLM
 from metagpt.core.provider.llm_provider_registry import create_llm_instance
@@ -61,7 +61,7 @@ class Context(BaseModel):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     kwargs: AttrDict = AttrDict()
-    config: CoreConfig = Field(default_factory=CoreConfig.default)
+    config: Config = Field(default_factory=Config.default)
 
     cost_manager: CostManager = CostManager()