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LLM config via json file (EmergenceAI#95)
* move the config to a file * sample config file * refactor readme and add instructions for json file config * update example env * logging configuration for clarity * inform the user if a new system prompt was provided in config
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,6 +1,10 @@ | ||
| AUTOGEN_MODEL_NAME=PUT YOUR MODEL NAME HERE, for example: gpt-4-turbo-preview or llama3-70b-8192 | ||
| AUTOGEN_MODEL_NAME=PUT YOUR MODEL NAME HERE, for example: gpt-4-turbo, gpt-4o | ||
| AUTOGEN_MODEL_API_KEY=PUT YOUR MODEL API KEY HERE | ||
| AUTOGEN_MODEL_BASE_URL=IF YOU ARE USING OpenAI, remove this line, otherwise add the base URL, for example: https://api.groq.com/openai/v1 | ||
| OPENAI_API_KEY=If you are using the testing/benchmarking, put your openai key here otherwise remove this line | ||
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| BROWSER_STORAGE_DIR=/Users/macuser/Library/Application Support/Google/Chrome/Profile 5 | ||
| BROWSER_STORAGE_DIR=/Users/macuser/Library/Application Support/Google/Chrome/Profile 5 | ||
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| # If you want to use json file for config (see sample agents_llm_config.json and the Readme) | ||
| AGENTS_LLM_CONFIG_FILE=agents_llm_config.json | ||
| AGENTS_LLM_CONFIG_FILE_REF_KEY=The key for the config stanza to use from the file |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,161 @@ | ||
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| import json | ||
| import os | ||
| from typing import Any | ||
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| from dotenv import load_dotenv | ||
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| from ae.utils.logger import logger | ||
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| class AgentsLLMConfig: | ||
| # Mapping from environment keys to model config keys | ||
| KEY_MAPPING_ENV_MODEL: dict[str, str] = { | ||
| "AUTOGEN_MODEL_NAME": "model", | ||
| "AUTOGEN_MODEL_API_KEY": "api_key", | ||
| "AUTOGEN_MODEL_BASE_URL": "base_url", | ||
| "AUTOGEN_MODEL_API_TYPE": "api_type", | ||
| "AUTOGEN_MODEL_API_VERSION": "api_version", | ||
| } | ||
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| # Mapping from environment keys to LLM config keys | ||
| KEY_MAPPING_ENV_LLM: dict[str, str] = { | ||
| "AUTOGEN_LLM_TEMPERATURE": "temperature", | ||
| "AUTOGEN_LLM_TOP_P": "top_p", | ||
| } | ||
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| # Mapping from file keys to model config keys | ||
| KEY_MAPPING_FILE: dict[str, str] = { | ||
| "model_name": "model", | ||
| "model_api_key": "api_key", | ||
| "model_base_url": "base_url", | ||
| } | ||
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| def __init__(self, env_file_path: str = ".env") -> None: | ||
| load_dotenv(env_file_path, verbose=True, override=True) | ||
| self.config: dict[str, Any] = self._load_config() | ||
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| def _load_config(self) -> dict[str, Any]: | ||
| config_file = os.getenv("AGENTS_LLM_CONFIG_FILE") | ||
| config_file_ref_key = os.getenv("AGENTS_LLM_CONFIG_FILE_REF_KEY") | ||
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| if config_file: | ||
| try: | ||
| with open(config_file, 'r') as file: # noqa: UP015 | ||
| file_config = json.load(file) | ||
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| if config_file_ref_key: | ||
| if config_file_ref_key in file_config: | ||
| logger.info(f"Loading configuration from: {config_file} with key: {config_file_ref_key}") | ||
| raw_config = file_config[config_file_ref_key] | ||
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| # Process configurations for both planner_agent and browser_nav_agent | ||
| planner_config = self._normalize_config_from_file(raw_config.get("planner_agent", {})) | ||
| browser_nav_config = self._normalize_config_from_file(raw_config.get("browser_nav_agent", {})) | ||
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| config = { | ||
| "planner_agent": planner_config, | ||
| "browser_nav_agent": browser_nav_config, | ||
| "other_settings": {k: v for k, v in raw_config.items() if k not in ["planner_agent", "browser_nav_agent"]}, | ||
| } | ||
| logger.info(f"Using configuration key '{config_file_ref_key}' from the config file.") | ||
| else: | ||
| logger.error(f"Key '{config_file_ref_key}' not found in the configuration file.") | ||
| raise KeyError(f"Key '{config_file_ref_key}' not found in the configuration file.") | ||
| else: | ||
| logger.error("AGENTS_LLM_CONFIG_FILE_REF_KEY is not provided.") | ||
| raise ValueError("AGENTS_LLM_CONFIG_FILE_REF_KEY must be provided if AGENTS_LLM_CONFIG_FILE is set.") | ||
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| except Exception as e: | ||
| logger.error(f"Error loading configuration file: {e}") | ||
| raise e | ||
| else: | ||
| logger.info("Loading configuration from environment variables") | ||
| # Load configurations from environment variables | ||
| normalized_config = self._normalize_config_from_env() | ||
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| config = { | ||
| "planner_agent": normalized_config, | ||
| "browser_nav_agent": normalized_config | ||
| } | ||
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| return config | ||
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| def _normalize_config_from_file(self, agent_config: dict[str, Any]) -> dict[str, Any]: | ||
| """Normalize agent-specific config from a file, grouping keys into model_config_params, llm_config_params, and other_settings.""" | ||
| model_config = {} | ||
| llm_config_params = {} | ||
| other_settings = {} | ||
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| for k, v in agent_config.items(): | ||
| if k in self.KEY_MAPPING_FILE: | ||
| model_config[self.KEY_MAPPING_FILE[k]] = v | ||
| elif k == "llm_config_params": | ||
| llm_config_params = v # Keep llm_config_params as is | ||
| else: | ||
| other_settings[k] = v | ||
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| return { | ||
| "model_config_params": model_config, | ||
| "llm_config_params": llm_config_params, | ||
| "other_settings": other_settings, | ||
| } | ||
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| def _normalize_config_from_env(self) -> dict[str, Any]: | ||
| """Normalize config from environment variables, adding defaults for 'temperature', 'top_p', and 'seed' based on model name.""" | ||
| model_config = {} | ||
| llm_config_params = {} | ||
| other_settings = {} | ||
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| # Populate model_config_params | ||
| for original_key, mapped_key in self.KEY_MAPPING_ENV_MODEL.items(): | ||
| value = os.getenv(original_key) | ||
| if value is not None: | ||
| model_config[mapped_key] = value | ||
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| # Populate llm_config_params | ||
| for original_key, mapped_key in self.KEY_MAPPING_ENV_LLM.items(): | ||
| value = os.getenv(original_key) | ||
| if value is not None: | ||
| llm_config_params[mapped_key] = value | ||
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| # Capture other settings that start with 'AUTOGEN_MODEL' | ||
| for original_key in os.environ: | ||
| if original_key.startswith("AUTOGEN_MODEL") and original_key not in self.KEY_MAPPING_ENV_MODEL: | ||
| other_settings[original_key] = os.getenv(original_key) | ||
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| # Apply defaults for 'temperature', 'top_p', 'seed' if not present | ||
| model_name:str = model_config.get("model", "").lower() # type: ignore | ||
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| if model_name.startswith("gpt"): # type: ignore | ||
| llm_config_params.setdefault("temperature", 0.0) # type: ignore | ||
| llm_config_params.setdefault("top_p", 0.001) # type: ignore | ||
| llm_config_params.setdefault("seed", 12345) # type: ignore | ||
| else: | ||
| llm_config_params.setdefault("temperature", 0.1) # type: ignore | ||
| llm_config_params.setdefault("top_p", 0.1) # type: ignore | ||
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| return { | ||
| "model_config_params": model_config, | ||
| "llm_config_params": llm_config_params, | ||
| "other_settings": other_settings, | ||
| } | ||
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| def get_planner_agent_config(self) -> dict[str, Any]: | ||
| return self.config["planner_agent"] | ||
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| def get_browser_nav_agent_config(self) -> dict[str, Any]: | ||
| return self.config["browser_nav_agent"] | ||
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| def get_full_config(self) -> dict[str, Any]: | ||
| return self.config | ||
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| # Example usage | ||
| if __name__ == "__main__": | ||
| config = AgentsLLMConfig() | ||
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| planner_config = config.get_planner_agent_config() | ||
| browser_nav_config = config.get_browser_nav_agent_config() | ||
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| print("Planner Agent Config:", planner_config) | ||
| print("Browser Nav Agent Config:", browser_nav_config) |
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