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Merge branch 'main' into feature-openai-v1

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seehi 2023-12-21 12:06:12 +08:00 • committed by GitHub
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145
metagpt/config.py
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@ -2,12 +2,19 @@
# -*- coding: utf-8 -*-
"""
Provide configuration, singleton
@Modified By: mashenquan, 2023/11/27.
1. According to Section 2.2.3.11 of RFC 135, add git repository support.
2. Add the parameter `src_workspace` for the old version project path.
"""
import os
from copy import deepcopy
from enum import Enum
from pathlib import Path
from typing import Any
import yaml
from metagpt.const import PROJECT_ROOT
from metagpt.const import DEFAULT_WORKSPACE_ROOT, METAGPT_ROOT, OPTIONS
from metagpt.logs import logger
from metagpt.tools import SearchEngineType, WebBrowserEngineType
from metagpt.utils.singleton import Singleton
@ -25,6 +32,15 @@ class NotConfiguredException(Exception):
super().__init__(self.message)
class LLMProviderEnum(Enum):
OPENAI = "openai"
ANTHROPIC = "anthropic"
SPARK = "spark"
ZHIPUAI = "zhipuai"
FIREWORKS = "fireworks"
OPEN_LLM = "open_llm"
class Config(metaclass=Singleton):
"""
Regular usage method:
@ -34,29 +50,60 @@ class Config(metaclass=Singleton):
"""
_instance = None
key_yaml_file = PROJECT_ROOT / "config/key.yaml"
default_yaml_file = PROJECT_ROOT / "config/config.yaml"
home_yaml_file = Path.home() / ".metagpt/config.yaml"
key_yaml_file = METAGPT_ROOT / "config/key.yaml"
default_yaml_file = METAGPT_ROOT / "config/config.yaml"
def __init__(self, yaml_file=default_yaml_file):
self._configs = {}
self._init_with_config_files_and_env(self._configs, yaml_file)
logger.info("Config loading done.")
global_options = OPTIONS.get()
# cli paras
self.project_path = ""
self.project_name = ""
self.inc = False
self.reqa_file = ""
self.max_auto_summarize_code = 0
self._init_with_config_files_and_env(yaml_file)
self._update()
global_options.update(OPTIONS.get())
logger.debug("Config loading done.")
def get_default_llm_provider_enum(self) -> LLMProviderEnum:
for k, v in [
(self.openai_api_key, LLMProviderEnum.OPENAI),
(self.anthropic_api_key, LLMProviderEnum.ANTHROPIC),
(self.zhipuai_api_key, LLMProviderEnum.ZHIPUAI),
(self.fireworks_api_key, LLMProviderEnum.FIREWORKS),
(self.open_llm_api_base, LLMProviderEnum.OPEN_LLM), # reuse logic. but not a key
]:
if self._is_valid_llm_key(k):
if self.openai_api_model:
logger.info(f"OpenAI API Model: {self.openai_api_model}")
return v
raise NotConfiguredException("You should config a LLM configuration first")
@staticmethod
def _is_valid_llm_key(k: str) -> bool:
return k and k != "YOUR_API_KEY"
def _update(self):
# logger.info("Config loading done.")
self.global_proxy = self._get("GLOBAL_PROXY")
self.openai_api_key = self._get("OPENAI_API_KEY")
self.anthropic_api_key = self._get("Anthropic_API_KEY")
self.anthropic_api_key = self._get("ANTHROPIC_API_KEY")
self.zhipuai_api_key = self._get("ZHIPUAI_API_KEY")
if (
(not self.openai_api_key or "YOUR_API_KEY" == self.openai_api_key)
and (not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key)
and (not self.zhipuai_api_key or "YOUR_API_KEY" == self.zhipuai_api_key)
):
raise NotConfiguredException("Set OPENAI_API_KEY or Anthropic_API_KEY or ZHIPUAI_API_KEY first")
self.open_llm_api_base = self._get("OPEN_LLM_API_BASE")
self.open_llm_api_model = self._get("OPEN_LLM_API_MODEL")
self.fireworks_api_key = self._get("FIREWORKS_API_KEY")
_ = self.get_default_llm_provider_enum()
self.openai_base_url = self._get("OPENAI_BASE_URL")
self.openai_proxy = self._get("OPENAI_PROXY") or self.global_proxy
self.openai_api_type = self._get("OPENAI_API_TYPE")
self.openai_api_version = self._get("OPENAI_API_VERSION")
self.openai_api_rpm = self._get("RPM", 3)
self.openai_api_model = self._get("OPENAI_API_MODEL", "gpt-4")
self.openai_api_model = self._get("OPENAI_API_MODEL", "gpt-4-1106-preview")
self.max_tokens_rsp = self._get("MAX_TOKENS", 2048)
self.deployment_name = self._get("DEPLOYMENT_NAME", "gpt-4")
@ -66,7 +113,10 @@ class Config(metaclass=Singleton):
self.domain = self._get("DOMAIN")
self.spark_url = self._get("SPARK_URL")
self.claude_api_key = self._get("Anthropic_API_KEY")
self.fireworks_api_base = self._get("FIREWORKS_API_BASE")
self.fireworks_api_model = self._get("FIREWORKS_API_MODEL")
self.claude_api_key = self._get("ANTHROPIC_API_KEY")
self.serpapi_api_key = self._get("SERPAPI_API_KEY")
self.serper_api_key = self._get("SERPER_API_KEY")
self.google_api_key = self._get("GOOGLE_API_KEY")
@ -81,6 +131,7 @@ class Config(metaclass=Singleton):
logger.warning("LONG_TERM_MEMORY is True")
self.max_budget = self._get("MAX_BUDGET", 10.0)
self.total_cost = 0.0
self.code_review_k_times = 2
self.puppeteer_config = self._get("PUPPETEER_CONFIG", "")
self.mmdc = self._get("MMDC", "mmdc")
@ -90,13 +141,33 @@ class Config(metaclass=Singleton):
self.mermaid_engine = self._get("MERMAID_ENGINE", "nodejs")
self.pyppeteer_executable_path = self._get("PYPPETEER_EXECUTABLE_PATH", "")
self.prompt_format = self._get("PROMPT_FORMAT", "markdown")
self.repair_llm_output = self._get("REPAIR_LLM_OUTPUT", False)
self.prompt_schema = self._get("PROMPT_FORMAT", "json")
self.workspace_path = Path(self._get("WORKSPACE_PATH", DEFAULT_WORKSPACE_ROOT))
self._ensure_workspace_exists()
def _init_with_config_files_and_env(self, configs: dict, yaml_file):
def update_via_cli(self, project_path, project_name, inc, reqa_file, max_auto_summarize_code):
"""update config via cli"""
# Use in the PrepareDocuments action according to Section 2.2.3.5.1 of RFC 135.
if project_path:
inc = True
project_name = project_name or Path(project_path).name
self.project_path = project_path
self.project_name = project_name
self.inc = inc
self.reqa_file = reqa_file
self.max_auto_summarize_code = max_auto_summarize_code
def _ensure_workspace_exists(self):
self.workspace_path.mkdir(parents=True, exist_ok=True)
logger.debug(f"WORKSPACE_PATH set to {self.workspace_path}")
def _init_with_config_files_and_env(self, yaml_file):
"""Load from config/key.yaml, config/config.yaml, and env in decreasing order of priority"""
configs.update(os.environ)
configs = dict(os.environ)
for _yaml_file in [yaml_file, self.key_yaml_file]:
for _yaml_file in [yaml_file, self.key_yaml_file, self.home_yaml_file]:
if not _yaml_file.exists():
continue
@ -105,11 +176,13 @@ class Config(metaclass=Singleton):
yaml_data = yaml.safe_load(file)
if not yaml_data:
continue
os.environ.update({k: v for k, v in yaml_data.items() if isinstance(v, str)})
configs.update(yaml_data)
OPTIONS.set(configs)
def _get(self, *args, **kwargs):
return self._configs.get(*args, **kwargs)
@staticmethod
def _get(*args, **kwargs):
i = OPTIONS.get()
return i.get(*args, **kwargs)
def get(self, key, *args, **kwargs):
"""Search for a value in config/key.yaml, config/config.yaml, and env; raise an error if not found"""
@ -118,5 +191,33 @@ class Config(metaclass=Singleton):
raise ValueError(f"Key '{key}' not found in environment variables or in the YAML file")
return value
def __setattr__(self, name: str, value: Any) -> None:
OPTIONS.get()[name] = value
def __getattr__(self, name: str) -> Any:
i = OPTIONS.get()
return i.get(name)
def set_context(self, options: dict):
"""Update current config"""
if not options:
return
opts = deepcopy(OPTIONS.get())
opts.update(options)
OPTIONS.set(opts)
self._update()
@property
def options(self):
"""Return all key-values"""
return OPTIONS.get()
def new_environ(self):
"""Return a new os.environ object"""
env = os.environ.copy()
i = self.options
env.update({k: v for k, v in i.items() if isinstance(v, str)})
return env
CONFIG = Config()