mirror of
https://github.com/FoundationAgents/MetaGPT.git
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183 lines
7.2 KiB
Python
183 lines
7.2 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Provide configuration, singleton
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@Modified By: mashenquan, 2023/11/27.
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1. According to Section 2.2.3.11 of RFC 135, add git repository support.
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2. Add the parameter `src_workspace` for the old version project path.
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"""
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import datetime
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import os
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from copy import deepcopy
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from pathlib import Path
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from typing import Any
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from uuid import uuid4
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import yaml
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from metagpt.const import DEFAULT_WORKSPACE_ROOT, METAGPT_ROOT, OPTIONS
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from metagpt.logs import logger
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from metagpt.tools import SearchEngineType, WebBrowserEngineType
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from metagpt.utils.singleton import Singleton
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class NotConfiguredException(Exception):
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"""Exception raised for errors in the configuration.
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Attributes:
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message -- explanation of the error
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"""
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def __init__(self, message="The required configuration is not set"):
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self.message = message
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super().__init__(self.message)
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class Config(metaclass=Singleton):
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"""
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Regular usage method:
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config = Config("config.yaml")
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secret_key = config.get_key("MY_SECRET_KEY")
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print("Secret key:", secret_key)
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"""
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_instance = None
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home_yaml_file = Path.home() / ".metagpt/config.yaml"
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key_yaml_file = METAGPT_ROOT / "config/key.yaml"
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default_yaml_file = METAGPT_ROOT / "config/config.yaml"
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def __init__(self, yaml_file=default_yaml_file):
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self._init_with_config_files_and_env(yaml_file)
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logger.info("Config loading done.")
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self._update()
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def _update(self):
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# logger.info("Config loading done.")
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self.global_proxy = self._get("GLOBAL_PROXY")
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self.openai_api_key = self._get("OPENAI_API_KEY")
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self.anthropic_api_key = self._get("Anthropic_API_KEY")
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self.zhipuai_api_key = self._get("ZHIPUAI_API_KEY")
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if (
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(not self.openai_api_key or "YOUR_API_KEY" == self.openai_api_key)
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and (not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key)
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and (not self.zhipuai_api_key or "YOUR_API_KEY" == self.zhipuai_api_key)
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):
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val = self._get("RAISE_NOT_CONFIG_ERROR")
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if val is None or val.lower() == "true":
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raise NotConfiguredException("Set OPENAI_API_KEY or Anthropic_API_KEY or ZHIPUAI_API_KEY first")
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else: # for agent
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logger.warning("Set OPENAI_API_KEY or Anthropic_API_KEY or ZHIPUAI_API_KEY first")
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self.openai_api_base = self._get("OPENAI_API_BASE")
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self.openai_proxy = self._get("OPENAI_PROXY") or self.global_proxy
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self.openai_api_type = self._get("OPENAI_API_TYPE")
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self.openai_api_version = self._get("OPENAI_API_VERSION")
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self.openai_api_rpm = self._get("RPM", 3)
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self.openai_api_model = self._get("OPENAI_API_MODEL", "gpt-4")
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self.max_tokens_rsp = self._get("MAX_TOKENS", 2048)
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self.deployment_name = self._get("DEPLOYMENT_NAME")
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self.deployment_id = self._get("DEPLOYMENT_ID")
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self.spark_appid = self._get("SPARK_APPID")
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self.spark_api_secret = self._get("SPARK_API_SECRET")
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self.spark_api_key = self._get("SPARK_API_KEY")
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self.domain = self._get("DOMAIN")
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self.spark_url = self._get("SPARK_URL")
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self.claude_api_key = self._get("Anthropic_API_KEY")
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self.serpapi_api_key = self._get("SERPAPI_API_KEY")
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self.serper_api_key = self._get("SERPER_API_KEY")
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self.google_api_key = self._get("GOOGLE_API_KEY")
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self.google_cse_id = self._get("GOOGLE_CSE_ID")
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self.search_engine = SearchEngineType(self._get("SEARCH_ENGINE", SearchEngineType.SERPAPI_GOOGLE))
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self.web_browser_engine = WebBrowserEngineType(self._get("WEB_BROWSER_ENGINE", WebBrowserEngineType.PLAYWRIGHT))
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self.playwright_browser_type = self._get("PLAYWRIGHT_BROWSER_TYPE", "chromium")
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self.selenium_browser_type = self._get("SELENIUM_BROWSER_TYPE", "chrome")
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self.long_term_memory = self._get("LONG_TERM_MEMORY", False)
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if self.long_term_memory:
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logger.warning("LONG_TERM_MEMORY is True")
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self.max_budget = self._get("MAX_BUDGET", 10.0)
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self.total_cost = 0.0
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self.code_review_k_times = 2
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self.puppeteer_config = self._get("PUPPETEER_CONFIG", "")
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self.mmdc = self._get("MMDC", "mmdc")
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self.calc_usage = self._get("CALC_USAGE", True)
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self.model_for_researcher_summary = self._get("MODEL_FOR_RESEARCHER_SUMMARY")
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self.model_for_researcher_report = self._get("MODEL_FOR_RESEARCHER_REPORT")
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self.mermaid_engine = self._get("MERMAID_ENGINE", "nodejs")
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self.pyppeteer_executable_path = self._get("PYPPETEER_EXECUTABLE_PATH", "")
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self.prompt_format = self._get("PROMPT_FORMAT", "markdown")
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workspace_uid = (
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self._get("WORKSPACE_UID") or f"{datetime.datetime.now().strftime('%Y%m%d%H%M%S')}-{uuid4().hex[-8:]}"
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)
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self.workspace_path = Path(self._get("WORKSPACE_PATH", DEFAULT_WORKSPACE_ROOT))
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val = self._get("WORKSPACE_PATH_WITH_UID")
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if val and val.lower() == "true": # for agent
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self.workspace_path = self.workspace_path / workspace_uid
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self._ensure_workspace_exists()
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self.max_auto_summarize_code = self.max_auto_summarize_code or self._get("MAX_AUTO_SUMMARIZE_CODE", 1)
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def _ensure_workspace_exists(self):
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self.workspace_path.mkdir(parents=True, exist_ok=True)
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logger.info(f"WORKSPACE_PATH set to {self.workspace_path}")
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def _init_with_config_files_and_env(self, yaml_file):
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"""Load from config/key.yaml, config/config.yaml, and env in decreasing order of priority"""
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configs = dict(os.environ)
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for _yaml_file in [yaml_file, self.key_yaml_file, self.home_yaml_file]:
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if not _yaml_file.exists():
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continue
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# Load local YAML file
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with open(_yaml_file, "r", encoding="utf-8") as file:
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yaml_data = yaml.safe_load(file)
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if not yaml_data:
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continue
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configs.update(yaml_data)
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OPTIONS.set(configs)
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@staticmethod
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def _get(*args, **kwargs):
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m = OPTIONS.get()
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return m.get(*args, **kwargs)
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def get(self, key, *args, **kwargs):
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"""Search for a value in config/key.yaml, config/config.yaml, and env; raise an error if not found"""
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value = self._get(key, *args, **kwargs)
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if value is None:
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raise ValueError(f"Key '{key}' not found in environment variables or in the YAML file")
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return value
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def __setattr__(self, name: str, value: Any) -> None:
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OPTIONS.get()[name] = value
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def __getattr__(self, name: str) -> Any:
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m = OPTIONS.get()
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return m.get(name)
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def set_context(self, options: dict):
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"""Update current config"""
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if not options:
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return
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opts = deepcopy(OPTIONS.get())
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opts.update(options)
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OPTIONS.set(opts)
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self._update()
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@property
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def options(self):
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"""Return all key-values"""
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return OPTIONS.get()
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def new_environ(self):
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"""Return a new os.environ object"""
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env = os.environ.copy()
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m = self.options
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env.update({k: v for k, v in m.items() if isinstance(v, str)})
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return env
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CONFIG = Config()
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