refactor: support vllm embeddings image

Author: liuruibin

apps/setting/models_provider/impl/vllm_model_provider/credential/embedding.py

@@ -0,0 +1,48 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： embedding.py
+    @date：2024/7/12 16:45
+    @desc:
+"""
+from typing import Dict
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+from django.utils.translation import gettext_lazy as _
+
+
+
+class VllmEmbeddingCredential(BaseForm, BaseModelCredential):
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=True):
+        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, _('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_base', 'api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, _('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            model.embed_query('你好')
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, _('Verification failed, please check whether the parameters are correct: {error}').format(error=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', ''))}
+
+    api_base = forms.TextInputField('API Url', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)

apps/setting/models_provider/impl/vllm_model_provider/credential/image.py

@@ -0,0 +1,68 @@
+# 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
+from django.utils.translation import gettext_lazy as _
+
+class VllmImageModelParams(BaseForm):
+    temperature = forms.SliderField(TooltipLabel(_('Temperature'),
+                                                 _('Higher values make the output more random, while lower values make it more focused and deterministic')),
+                                    required=True, default_value=0.7,
+                                    _min=0.1,
+                                    _max=1.0,
+                                    _step=0.01,
+                                    precision=2)
+
+    max_tokens = forms.SliderField(
+        TooltipLabel(_('Output the maximum Tokens'),
+                     _('Specify the maximum number of tokens that the model can generate')),
+        required=True, default_value=800,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0)
+
+
+
+class VllmImageModelCredential(BaseForm, BaseModelCredential):
+    api_base = forms.TextInputField('API Url', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, 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, _('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_base', 'api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, _('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential, **model_params)
+            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, _('Verification failed, please check whether the parameters are correct: {error}').format(error=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 VllmImageModelParams()

apps/setting/models_provider/impl/vllm_model_provider/model/embedding.py

@@ -0,0 +1,23 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： embedding.py
+    @date：2024/7/12 17:44
+    @desc:
+"""
+from typing import Dict
+
+from langchain_community.embeddings import OpenAIEmbeddings
+
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+
+
+class VllmEmbeddingModel(MaxKBBaseModel, OpenAIEmbeddings):
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        return VllmEmbeddingModel(
+            model=model_name,
+            openai_api_key=model_credential.get('api_key'),
+            openai_api_base=model_credential.get('api_base'),
+        )

apps/setting/models_provider/impl/vllm_model_provider/model/image.py

@@ -0,0 +1,20 @@
+from typing import Dict
+
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_chat_open_ai import BaseChatOpenAI
+
+
+class VllmImage(MaxKBBaseModel, BaseChatOpenAI):
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
+        return VllmImage(
+            model_name=model_name,
+            openai_api_base=model_credential.get('api_base'),
+            openai_api_key=model_credential.get('api_key'),
+            # stream_options={"include_usage": True},
+            streaming=True,
+            stream_usage=True,
+            **optional_params,
+        )