From a827396d07e62195729c6292f48b0440961f14ab Mon Sep 17 00:00:00 2001 From: CaptainB Date: Tue, 17 Dec 2024 12:50:24 +0800 Subject: [PATCH] feat: Gemini Image understand model --- .../gemini_model_provider/credential/image.py | 64 +++++++++++++++++++ .../gemini_model_provider.py | 43 ++++++++++--- .../impl/gemini_model_provider/model/image.py | 24 +++++++ 3 files changed, 121 insertions(+), 10 deletions(-) create mode 100644 apps/setting/models_provider/impl/gemini_model_provider/credential/image.py create mode 100644 apps/setting/models_provider/impl/gemini_model_provider/model/image.py diff --git a/apps/setting/models_provider/impl/gemini_model_provider/credential/image.py b/apps/setting/models_provider/impl/gemini_model_provider/credential/image.py new file mode 100644 index 000000000..33cc60bbd --- /dev/null +++ b/apps/setting/models_provider/impl/gemini_model_provider/credential/image.py @@ -0,0 +1,64 @@ +# coding=utf-8 +import base64 +import os +from typing import Dict + +from langchain_core.messages import HumanMessage + +from common import forms +from common.exception.app_exception import AppApiException +from common.forms import BaseForm, TooltipLabel +from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode + +class GeminiImageModelParams(BaseForm): + temperature = forms.SliderField(TooltipLabel('温度', '较高的数值会使输出更加随机，而较低的数值会使其更加集中和确定'), + required=True, default_value=0.7, + _min=0.1, + _max=1.0, + _step=0.01, + precision=2) + + max_tokens = forms.SliderField( + TooltipLabel('输出最大Tokens', '指定模型可生成的最大token个数'), + required=True, default_value=800, + _min=1, + _max=100000, + _step=1, + precision=0) + + + +class GeminiImageModelCredential(BaseForm, BaseModelCredential): + api_key = forms.PasswordInputField('API Key', required=True) + + def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], provider, + raise_exception=False): + model_type_list = provider.get_model_type_list() + if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))): + raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持') + + for key in ['api_key']: + if key not in model_credential: + if raise_exception: + raise AppApiException(ValidCode.valid_error.value, f'{key} 字段为必填字段') + else: + return False + try: + model = provider.get_model(model_type, model_name, model_credential) + res = model.stream([HumanMessage(content=[{"type": "text", "text": "你好"}])]) + for chunk in res: + print(chunk) + except Exception as e: + if isinstance(e, AppApiException): + raise e + if raise_exception: + raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}') + else: + return False + return True + + def encryption_dict(self, model: Dict[str, object]): + return {**model, 'api_key': super().encryption(model.get('api_key', ''))} + + def get_model_params_setting_form(self, model_name): + return GeminiImageModelParams() diff --git a/apps/setting/models_provider/impl/gemini_model_provider/gemini_model_provider.py b/apps/setting/models_provider/impl/gemini_model_provider/gemini_model_provider.py index b6dd442ca..a9acd40cf 100644 --- a/apps/setting/models_provider/impl/gemini_model_provider/gemini_model_provider.py +++ b/apps/setting/models_provider/impl/gemini_model_provider/gemini_model_provider.py @@ -11,24 +11,47 @@ import os from common.util.file_util import get_file_content from setting.models_provider.base_model_provider import IModelProvider, ModelProvideInfo, ModelInfo, ModelTypeConst, \ ModelInfoManage +from setting.models_provider.impl.gemini_model_provider.credential.image import GeminiImageModelCredential from setting.models_provider.impl.gemini_model_provider.credential.llm import GeminiLLMModelCredential +from setting.models_provider.impl.gemini_model_provider.model.image import GeminiImage from setting.models_provider.impl.gemini_model_provider.model.llm import GeminiChatModel from smartdoc.conf import PROJECT_DIR gemini_llm_model_credential = GeminiLLMModelCredential() +gemini_image_model_credential = GeminiImageModelCredential() -gemini_1_pro = ModelInfo('gemini-1.0-pro', '最新的Gemini 1.0 Pro模型，随Google更新而更新', - ModelTypeConst.LLM, - gemini_llm_model_credential, - GeminiChatModel) +model_info_list = [ + ModelInfo('gemini-1.0-pro', '最新的Gemini 1.0 Pro模型，随Google更新而更新', + ModelTypeConst.LLM, + gemini_llm_model_credential, + GeminiChatModel), + ModelInfo('gemini-1.0-pro-vision', '最新的Gemini 1.0 Pro Vision模型，随Google更新而更新', + ModelTypeConst.LLM, + gemini_llm_model_credential, + GeminiChatModel), +] -gemini_1_pro_vision = ModelInfo('gemini-1.0-pro-vision', '最新的Gemini 1.0 Pro Vision模型，随Google更新而更新', - ModelTypeConst.LLM, - gemini_llm_model_credential, - GeminiChatModel) +model_image_info_list = [ + ModelInfo('gemini-1.5-flash', '最新的Gemini 1.5 Flash模型，随Google更新而更新', + ModelTypeConst.IMAGE, + gemini_image_model_credential, + GeminiImage), + ModelInfo('gemini-1.5-pro', '最新的Gemini 1.5 Flash模型，随Google更新而更新', + ModelTypeConst.IMAGE, + gemini_image_model_credential, + GeminiImage), +] -model_info_manage = ModelInfoManage.builder().append_model_info(gemini_1_pro).append_model_info( - gemini_1_pro_vision).append_default_model_info(gemini_1_pro).build() + + +model_info_manage = ( + ModelInfoManage.builder() + .append_model_info_list(model_info_list) + .append_model_info_list(model_image_info_list) + .append_default_model_info(model_info_list[0]) + .append_default_model_info(model_image_info_list[0]) + .build() +) class GeminiModelProvider(IModelProvider): diff --git a/apps/setting/models_provider/impl/gemini_model_provider/model/image.py b/apps/setting/models_provider/impl/gemini_model_provider/model/image.py new file mode 100644 index 000000000..2e48a81b2 --- /dev/null +++ b/apps/setting/models_provider/impl/gemini_model_provider/model/image.py @@ -0,0 +1,24 @@ +from typing import Dict + +from langchain_google_genai import ChatGoogleGenerativeAI + +from common.config.tokenizer_manage_config import TokenizerManage +from setting.models_provider.base_model_provider import MaxKBBaseModel + + +def custom_get_token_ids(text: str): + tokenizer = TokenizerManage.get_tokenizer() + return tokenizer.encode(text) + + +class GeminiImage(MaxKBBaseModel, ChatGoogleGenerativeAI): + + @staticmethod + def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs): + optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs) + return GeminiImage( + model=model_name, + google_api_key=model_credential.get('api_key'), + streaming=True, + **optional_params, + )