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- import re
- import uuid
- from core.constant import llm_constant
- from models.account import Account
- from services.dataset_service import DatasetService
- from services.errors.account import NoPermissionError
- class AppModelConfigService:
- @staticmethod
- def is_dataset_exists(account: Account, dataset_id: str) -> bool:
- # verify if the dataset ID exists
- dataset = DatasetService.get_dataset(dataset_id)
- if not dataset:
- return False
- if dataset.tenant_id != account.current_tenant_id:
- return False
- return True
- @staticmethod
- def validate_model_completion_params(cp: dict, model_name: str) -> dict:
- # 6. model.completion_params
- if not isinstance(cp, dict):
- raise ValueError("model.completion_params must be of object type")
- # max_tokens
- if 'max_tokens' not in cp:
- cp["max_tokens"] = 512
- if not isinstance(cp["max_tokens"], int) or cp["max_tokens"] <= 0 or cp["max_tokens"] > \
- llm_constant.max_context_token_length[model_name]:
- raise ValueError(
- "max_tokens must be an integer greater than 0 and not exceeding the maximum value of the corresponding model")
- # temperature
- if 'temperature' not in cp:
- cp["temperature"] = 1
- if not isinstance(cp["temperature"], (float, int)) or cp["temperature"] < 0 or cp["temperature"] > 2:
- raise ValueError("temperature must be a float between 0 and 2")
- # top_p
- if 'top_p' not in cp:
- cp["top_p"] = 1
- if not isinstance(cp["top_p"], (float, int)) or cp["top_p"] < 0 or cp["top_p"] > 2:
- raise ValueError("top_p must be a float between 0 and 2")
- # presence_penalty
- if 'presence_penalty' not in cp:
- cp["presence_penalty"] = 0
- if not isinstance(cp["presence_penalty"], (float, int)) or cp["presence_penalty"] < -2 or cp["presence_penalty"] > 2:
- raise ValueError("presence_penalty must be a float between -2 and 2")
- # presence_penalty
- if 'frequency_penalty' not in cp:
- cp["frequency_penalty"] = 0
- if not isinstance(cp["frequency_penalty"], (float, int)) or cp["frequency_penalty"] < -2 or cp["frequency_penalty"] > 2:
- raise ValueError("frequency_penalty must be a float between -2 and 2")
- # Filter out extra parameters
- filtered_cp = {
- "max_tokens": cp["max_tokens"],
- "temperature": cp["temperature"],
- "top_p": cp["top_p"],
- "presence_penalty": cp["presence_penalty"],
- "frequency_penalty": cp["frequency_penalty"]
- }
- return filtered_cp
- @staticmethod
- def validate_configuration(account: Account, config: dict, mode: str) -> dict:
- # opening_statement
- if 'opening_statement' not in config or not config["opening_statement"]:
- config["opening_statement"] = ""
- if not isinstance(config["opening_statement"], str):
- raise ValueError("opening_statement must be of string type")
- # suggested_questions
- if 'suggested_questions' not in config or not config["suggested_questions"]:
- config["suggested_questions"] = []
- if not isinstance(config["suggested_questions"], list):
- raise ValueError("suggested_questions must be of list type")
- for question in config["suggested_questions"]:
- if not isinstance(question, str):
- raise ValueError("Elements in suggested_questions list must be of string type")
- # suggested_questions_after_answer
- if 'suggested_questions_after_answer' not in config or not config["suggested_questions_after_answer"]:
- config["suggested_questions_after_answer"] = {
- "enabled": False
- }
- if not isinstance(config["suggested_questions_after_answer"], dict):
- raise ValueError("suggested_questions_after_answer must be of dict type")
- if "enabled" not in config["suggested_questions_after_answer"] or not config["suggested_questions_after_answer"]["enabled"]:
- config["suggested_questions_after_answer"]["enabled"] = False
- if not isinstance(config["suggested_questions_after_answer"]["enabled"], bool):
- raise ValueError("enabled in suggested_questions_after_answer must be of boolean type")
- # more_like_this
- if 'more_like_this' not in config or not config["more_like_this"]:
- config["more_like_this"] = {
- "enabled": False
- }
- if not isinstance(config["more_like_this"], dict):
- raise ValueError("more_like_this must be of dict type")
- if "enabled" not in config["more_like_this"] or not config["more_like_this"]["enabled"]:
- config["more_like_this"]["enabled"] = False
- if not isinstance(config["more_like_this"]["enabled"], bool):
- raise ValueError("enabled in more_like_this must be of boolean type")
- # model
- if 'model' not in config:
- raise ValueError("model is required")
- if not isinstance(config["model"], dict):
- raise ValueError("model must be of object type")
- # model.provider
- if 'provider' not in config["model"] or config["model"]["provider"] != "openai":
- raise ValueError("model.provider must be 'openai'")
- # model.name
- if 'name' not in config["model"]:
- raise ValueError("model.name is required")
- if config["model"]["name"] not in llm_constant.models_by_mode[mode]:
- raise ValueError("model.name must be in the specified model list")
- # model.completion_params
- if 'completion_params' not in config["model"]:
- raise ValueError("model.completion_params is required")
- config["model"]["completion_params"] = AppModelConfigService.validate_model_completion_params(
- config["model"]["completion_params"],
- config["model"]["name"]
- )
- # user_input_form
- if "user_input_form" not in config or not config["user_input_form"]:
- config["user_input_form"] = []
- if not isinstance(config["user_input_form"], list):
- raise ValueError("user_input_form must be a list of objects")
- variables = []
- for item in config["user_input_form"]:
- key = list(item.keys())[0]
- if key not in ["text-input", "select"]:
- raise ValueError("Keys in user_input_form list can only be 'text-input' or 'select'")
- form_item = item[key]
- if 'label' not in form_item:
- raise ValueError("label is required in user_input_form")
- if not isinstance(form_item["label"], str):
- raise ValueError("label in user_input_form must be of string type")
- if 'variable' not in form_item:
- raise ValueError("variable is required in user_input_form")
- if not isinstance(form_item["variable"], str):
- raise ValueError("variable in user_input_form must be of string type")
- pattern = re.compile(r"^(?!\d)[\u4e00-\u9fa5A-Za-z0-9_\U0001F300-\U0001F64F\U0001F680-\U0001F6FF]{1,100}$")
- if pattern.match(form_item["variable"]) is None:
- raise ValueError("variable in user_input_form must be a string, "
- "and cannot start with a number")
- variables.append(form_item["variable"])
- if 'required' not in form_item or not form_item["required"]:
- form_item["required"] = False
- if not isinstance(form_item["required"], bool):
- raise ValueError("required in user_input_form must be of boolean type")
- if key == "select":
- if 'options' not in form_item or not form_item["options"]:
- form_item["options"] = []
- if not isinstance(form_item["options"], list):
- raise ValueError("options in user_input_form must be a list of strings")
- if "default" in form_item and form_item['default'] \
- and form_item["default"] not in form_item["options"]:
- raise ValueError("default value in user_input_form must be in the options list")
- # pre_prompt
- if "pre_prompt" not in config or not config["pre_prompt"]:
- config["pre_prompt"] = ""
- if not isinstance(config["pre_prompt"], str):
- raise ValueError("pre_prompt must be of string type")
- template_vars = re.findall(r"\{\{(\w+)\}\}", config["pre_prompt"])
- for var in template_vars:
- if var not in variables:
- raise ValueError("Template variables in pre_prompt must be defined in user_input_form")
- # agent_mode
- if "agent_mode" not in config or not config["agent_mode"]:
- config["agent_mode"] = {
- "enabled": False,
- "tools": []
- }
- if not isinstance(config["agent_mode"], dict):
- raise ValueError("agent_mode must be of object type")
- if "enabled" not in config["agent_mode"] or not config["agent_mode"]["enabled"]:
- config["agent_mode"]["enabled"] = False
- if not isinstance(config["agent_mode"]["enabled"], bool):
- raise ValueError("enabled in agent_mode must be of boolean type")
- if "tools" not in config["agent_mode"] or not config["agent_mode"]["tools"]:
- config["agent_mode"]["tools"] = []
- if not isinstance(config["agent_mode"]["tools"], list):
- raise ValueError("tools in agent_mode must be a list of objects")
- for tool in config["agent_mode"]["tools"]:
- key = list(tool.keys())[0]
- if key not in ["sensitive-word-avoidance", "dataset"]:
- raise ValueError("Keys in agent_mode.tools list can only be 'sensitive-word-avoidance' or 'dataset'")
- tool_item = tool[key]
- if "enabled" not in tool_item or not tool_item["enabled"]:
- tool_item["enabled"] = False
- if not isinstance(tool_item["enabled"], bool):
- raise ValueError("enabled in agent_mode.tools must be of boolean type")
- if key == "sensitive-word-avoidance":
- if "words" not in tool_item or not tool_item["words"]:
- tool_item["words"] = ""
- if not isinstance(tool_item["words"], str):
- raise ValueError("words in sensitive-word-avoidance must be of string type")
- if "canned_response" not in tool_item or not tool_item["canned_response"]:
- tool_item["canned_response"] = ""
- if not isinstance(tool_item["canned_response"], str):
- raise ValueError("canned_response in sensitive-word-avoidance must be of string type")
- elif key == "dataset":
- if 'id' not in tool_item:
- raise ValueError("id is required in dataset")
- try:
- uuid.UUID(tool_item["id"])
- except ValueError:
- raise ValueError("id in dataset must be of UUID type")
- if not AppModelConfigService.is_dataset_exists(account, tool_item["id"]):
- raise ValueError("Dataset ID does not exist, please check your permission.")
- # Filter out extra parameters
- filtered_config = {
- "opening_statement": config["opening_statement"],
- "suggested_questions": config["suggested_questions"],
- "suggested_questions_after_answer": config["suggested_questions_after_answer"],
- "more_like_this": config["more_like_this"],
- "model": {
- "provider": config["model"]["provider"],
- "name": config["model"]["name"],
- "completion_params": config["model"]["completion_params"]
- },
- "user_input_form": config["user_input_form"],
- "pre_prompt": config["pre_prompt"],
- "agent_mode": config["agent_mode"]
- }
- return filtered_config
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