add support for Baidu yiyan (#2049)

### What problem does this PR solve?

add support for Baidu yiyan

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

Co-authored-by: Zhedong Cen <cenzhedong2@126.com>

api/apps/llm_app.py

@@ -140,7 +140,11 @@ def add_llm():
         api_key = req.get("api_key","xxxxxxxxxxxxxxx")
     elif factory =="XunFei Spark":
         llm_name = req["llm_name"]
-        api_key = req.get("spark_api_password","") 
+        api_key = req.get("spark_api_password","xxxxxxxxxxxxxxx") 
+    elif factory == "BaiduYiyan":
+        llm_name = req["llm_name"]
+        api_key = '{' + f'"yiyan_ak": "{req.get("yiyan_ak", "")}", ' \
+                f'"yiyan_sk": "{req.get("yiyan_sk", "")}"' + '}'
     else:
         llm_name = req["llm_name"]
         api_key = req.get("api_key","xxxxxxxxxxxxxxx") 
@@ -157,7 +161,7 @@ def add_llm():
     msg = ""
     if llm["model_type"] == LLMType.EMBEDDING.value:
         mdl = EmbeddingModel[factory](
-            key=llm['api_key'] if factory in ["VolcEngine", "Bedrock","OpenAI-API-Compatible","Replicate"] else None,
+            key=llm['api_key'],
             model_name=llm["llm_name"], 
             base_url=llm["api_base"])
         try:
@@ -168,7 +172,7 @@ def add_llm():
             msg += f"\nFail to access embedding model({llm['llm_name']})." + str(e)
     elif llm["model_type"] == LLMType.CHAT.value:
         mdl = ChatModel[factory](
-            key=llm['api_key'] if factory in ["VolcEngine", "Bedrock","OpenAI-API-Compatible","Replicate","XunFei Spark"] else None,
+            key=llm['api_key'],
             model_name=llm["llm_name"],
             base_url=llm["api_base"]
         )
@@ -182,7 +186,9 @@ def add_llm():
                 e)
     elif llm["model_type"] == LLMType.RERANK:
         mdl = RerankModel[factory](
-            key=None, model_name=llm["llm_name"], base_url=llm["api_base"]
+            key=llm["api_key"], 
+            model_name=llm["llm_name"], 
+            base_url=llm["api_base"]
         )
         try:
             arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!"])
@@ -193,7 +199,9 @@ def add_llm():
                 e)
     elif llm["model_type"] == LLMType.IMAGE2TEXT.value:
         mdl = CvModel[factory](
-            key=llm["api_key"] if factory in ["OpenAI-API-Compatible"] else None, model_name=llm["llm_name"], base_url=llm["api_base"]
+            key=llm["api_key"], 
+            model_name=llm["llm_name"], 
+            base_url=llm["api_base"]
         )
         try:
             img_url = (

conf/llm_factories.json

@@ -3201,6 +3201,13 @@
             "tags": "LLM",
             "status": "1",
             "llm": []
+        },
+        {
+            "name": "BaiduYiyan",
+            "logo": "",
+            "tags": "LLM",
+            "status": "1",
+            "llm": []
         }
     ]
 }

docs/quickstart.mdx

@@ -119,7 +119,7 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
    ```
 
    :::note
-   If the above steps does not work, consider using [this workaround](https://github.com/docker/for-mac/issues/7047#issuecomment-1791912053), which employs a container and does not require manual editing of the macOS settings.
+   If the above steps do not work, consider using [this workaround](https://github.com/docker/for-mac/issues/7047#issuecomment-1791912053), which employs a container and does not require manual editing of the macOS settings.
    :::
 
   </TabItem>

rag/llm/__init__.py

@@ -43,7 +43,8 @@ EmbeddingModel = {
     "PerfXCloud": PerfXCloudEmbed,
     "Upstage": UpstageEmbed,
     "SILICONFLOW": SILICONFLOWEmbed,
-    "Replicate": ReplicateEmbed
+    "Replicate": ReplicateEmbed,
+    "BaiduYiyan": BaiduYiyanEmbed
 }
 
 
@@ -101,7 +102,8 @@ ChatModel = {
     "01.AI": YiChat,
     "Replicate": ReplicateChat,
     "Tencent Hunyuan": HunyuanChat,
-    "XunFei Spark": SparkChat
+    "XunFei Spark": SparkChat,
+    "BaiduYiyan": BaiduYiyanChat
 }
 
 
@@ -115,7 +117,8 @@ RerankModel = {
     "OpenAI-API-Compatible": OpenAI_APIRerank,
     "cohere": CoHereRerank,
     "TogetherAI": TogetherAIRerank,
-    "SILICONFLOW": SILICONFLOWRerank
+    "SILICONFLOW": SILICONFLOWRerank,
+    "BaiduYiyan": BaiduYiyanRerank
 }
 
 

rag/llm/chat_model.py

@@ -1185,3 +1185,69 @@ class SparkChat(Base):
         }
         model_version = model2version[model_name]
         super().__init__(key, model_version, base_url)
+
+
+class BaiduYiyanChat(Base):
+    def __init__(self, key, model_name, base_url=None):
+        import qianfan
+        
+        key = json.loads(key)
+        ak = key.get("yiyan_ak","")
+        sk = key.get("yiyan_sk","")
+        self.client = qianfan.ChatCompletion(ak=ak,sk=sk)
+        self.model_name = model_name.lower()
+        self.system = ""
+
+    def chat(self, system, history, gen_conf):
+        if system:
+            self.system = system
+        gen_conf["penalty_score"] = (
+            (gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty", 0)) / 2
+        ) + 1
+        if "max_tokens" in gen_conf:
+            gen_conf["max_output_tokens"] = gen_conf["max_tokens"]
+        ans = ""
+        
+        try:
+            response = self.client.do(
+                model=self.model_name, 
+                messages=history, 
+                system=self.system,
+                **gen_conf
+            ).body
+            ans = response['result']
+            return ans, response["usage"]["total_tokens"]
+            
+        except Exception as e:
+            return ans + "\n**ERROR**: " + str(e), 0
+
+    def chat_streamly(self, system, history, gen_conf):
+        if system:
+            self.system = system
+        gen_conf["penalty_score"] = (
+            (gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty", 0)) / 2
+        ) + 1
+        if "max_tokens" in gen_conf:
+            gen_conf["max_output_tokens"] = gen_conf["max_tokens"]
+        ans = ""
+        total_tokens = 0
+        
+        try:
+            response = self.client.do(
+                model=self.model_name, 
+                messages=history, 
+                system=self.system,
+                stream=True,
+                **gen_conf
+            )
+            for resp in response:
+                resp = resp.body
+                ans += resp['result']
+                total_tokens = resp["usage"]["total_tokens"]
+
+                yield ans
+
+        except Exception as e:
+            return ans + "\n**ERROR**: " + str(e), 0
+
+        yield total_tokens

rag/llm/embedding_model.py

@@ -32,6 +32,7 @@ import asyncio
 from api.utils.file_utils import get_home_cache_dir
 from rag.utils import num_tokens_from_string, truncate
 import google.generativeai as genai 
+import json
 
 class Base(ABC):
     def __init__(self, key, model_name):
@@ -591,11 +592,34 @@ class ReplicateEmbed(Base):
         self.client = Client(api_token=key)
 
     def encode(self, texts: list, batch_size=32):
-        from json import dumps
+        res = self.client.run(self.model_name, input={"texts": json.dumps(texts)})
-
-        res = self.client.run(self.model_name, input={"texts": dumps(texts)})
         return np.array(res), sum([num_tokens_from_string(text) for text in texts])
 
     def encode_queries(self, text):
         res = self.client.embed(self.model_name, input={"texts": [text]})
         return np.array(res), num_tokens_from_string(text)
+
+
+class BaiduYiyanEmbed(Base):
+    def __init__(self, key, model_name, base_url=None):
+        import qianfan
+
+        key = json.loads(key)
+        ak = key.get("yiyan_ak", "")
+        sk = key.get("yiyan_sk", "")
+        self.client = qianfan.Embedding(ak=ak, sk=sk)
+        self.model_name = model_name
+
+    def encode(self, texts: list, batch_size=32):
+        res = self.client.do(model=self.model_name, texts=texts).body
+        return (
+            np.array([r["embedding"] for r in res["data"]]),
+            res["usage"]["total_tokens"],
+        )
+
+    def encode_queries(self, text):
+        res = self.client.do(model=self.model_name, texts=[text]).body
+        return (
+            np.array([r["embedding"] for r in res["data"]]),
+            res["usage"]["total_tokens"],
+        )

rag/llm/rerank_model.py

@@ -24,6 +24,7 @@ from abc import ABC
 import numpy as np
 from api.utils.file_utils import get_home_cache_dir
 from rag.utils import num_tokens_from_string, truncate
+import json
 
 def sigmoid(x):
     return 1 / (1 + np.exp(-x))
@@ -288,3 +289,25 @@ class SILICONFLOWRerank(Base):
             rank[indexs],
             response["meta"]["tokens"]["input_tokens"] + response["meta"]["tokens"]["output_tokens"],
         )
+
+
+class BaiduYiyanRerank(Base):
+    def __init__(self, key, model_name, base_url=None):
+        from qianfan.resources import Reranker
+
+        key = json.loads(key)
+        ak = key.get("yiyan_ak", "")
+        sk = key.get("yiyan_sk", "")
+        self.client = Reranker(ak=ak, sk=sk)
+        self.model_name = model_name
+
+    def similarity(self, query: str, texts: list):
+        res = self.client.do(
+            model=self.model_name,
+            query=query,
+            documents=texts,
+            top_n=len(texts),
+        ).body
+        rank = np.array([d["relevance_score"] for d in res["results"]])
+        indexs = [d["index"] for d in res["results"]]
+        return rank[indexs], res["usage"]["total_tokens"]

requirements.txt

@@ -62,6 +62,7 @@ pytest==8.2.2
 python-dotenv==1.0.1
 python_dateutil==2.8.2
 python_pptx==0.6.23
+qianfan==0.4.6
 readability_lxml==0.8.1
 redis==5.0.3
 Requests==2.32.2

requirements_arm.txt

@@ -100,6 +100,7 @@ python-docx==1.1.0
 python-dotenv==1.0.1
 python-pptx==0.6.23
 PyYAML==6.0.1
+qianfan==0.4.6
 redis==5.0.3
 regex==2023.12.25
 replicate==0.31.0

web/src/assets/svg/llm/yiyan.svg

@@ -0,0 +1 @@
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web/src/locales/en.ts

@@ -528,6 +528,11 @@ The above is the content you need to summarize.`,
       SparkModelNameMessage: 'Please select Spark model',
       addSparkAPIPassword: 'Spark APIPassword',
       SparkAPIPasswordMessage: 'please input your APIPassword',
+      yiyanModelNameMessage: 'Please input model name',
+      addyiyanAK: 'yiyan API KEY',
+      yiyanAKMessage: 'Please input your API KEY',
+      addyiyanSK: 'yiyan Secret KEY',
+      yiyanSKMessage: 'Please input your Secret KEY',
     },
     message: {
       registered: 'Registered!',

web/src/locales/zh-traditional.ts

@@ -491,6 +491,11 @@ export default {
       SparkModelNameMessage: '請選擇星火模型!',
       addSparkAPIPassword: '星火 APIPassword',
       SparkAPIPasswordMessage: '請輸入 APIPassword',
+      yiyanModelNameMessage: '輸入模型名稱',
+      addyiyanAK: '一言 API KEY',
+      yiyanAKMessage: '請輸入 API KEY',
+      addyiyanSK: '一言 Secret KEY',
+      yiyanSKMessage: '請輸入 Secret KEY',
     },
     message: {
       registered: '註冊成功',

web/src/locales/zh.ts

@@ -508,6 +508,11 @@ export default {
       SparkModelNameMessage: '请选择星火模型！',
       addSparkAPIPassword: '星火 APIPassword',
       SparkAPIPasswordMessage: '请输入 APIPassword',
+      yiyanModelNameMessage: '请输入模型名称',
+      addyiyanAK: '一言 API KEY',
+      yiyanAKMessage: '请输入 API KEY',
+      addyiyanSK: '一言 Secret KEY',
+      yiyanSKMessage: '请输入 Secret KEY',
     },
     message: {
       registered: '注册成功',

web/src/pages/user-setting/setting-model/constant.ts

@@ -34,6 +34,7 @@ export const IconMap = {
   Replicate: 'replicate',
   'Tencent Hunyuan': 'hunyuan',
   'XunFei Spark': 'spark',
+  BaiduYiyan: 'yiyan',
 };
 
 export const BedrockRegionList = [

web/src/pages/user-setting/setting-model/hooks.ts

@@ -217,6 +217,33 @@ export const useSubmitSpark = () => {
   };
 };
 
+export const useSubmityiyan = () => {
+  const { addLlm, loading } = useAddLlm();
+  const {
+    visible: yiyanAddingVisible,
+    hideModal: hideyiyanAddingModal,
+    showModal: showyiyanAddingModal,
+  } = useSetModalState();
+
+  const onyiyanAddingOk = useCallback(
+    async (payload: IAddLlmRequestBody) => {
+      const ret = await addLlm(payload);
+      if (ret === 0) {
+        hideyiyanAddingModal();
+      }
+    },
+    [hideyiyanAddingModal, addLlm],
+  );
+
+  return {
+    yiyanAddingLoading: loading,
+    onyiyanAddingOk,
+    yiyanAddingVisible,
+    hideyiyanAddingModal,
+    showyiyanAddingModal,
+  };
+};
+
 export const useSubmitBedrock = () => {
   const { addLlm, loading } = useAddLlm();
   const {

web/src/pages/user-setting/setting-model/index.tsx

@@ -39,6 +39,7 @@ import {
   useSubmitSpark,
   useSubmitSystemModelSetting,
   useSubmitVolcEngine,
+  useSubmityiyan,
 } from './hooks';
 import HunyuanModal from './hunyuan-modal';
 import styles from './index.less';
@@ -46,6 +47,7 @@ import OllamaModal from './ollama-modal';
 import SparkModal from './spark-modal';
 import SystemModelSettingModal from './system-model-setting-modal';
 import VolcEngineModal from './volcengine-modal';
+import YiyanModal from './yiyan-modal';
 
 const LlmIcon = ({ name }: { name: string }) => {
   const icon = IconMap[name as keyof typeof IconMap];
@@ -95,7 +97,8 @@ const ModelCard = ({ item, clickApiKey }: IModelCardProps) => {
                 {isLocalLlmFactory(item.name) ||
                 item.name === 'VolcEngine' ||
                 item.name === 'Tencent Hunyuan' ||
-                item.name === 'XunFei Spark'
+                item.name === 'XunFei Spark' ||
+                item.name === 'BaiduYiyan'
                   ? t('addTheModel')
                   : 'API-Key'}
                 <SettingOutlined />
@@ -185,6 +188,14 @@ const UserSettingModel = () => {
     SparkAddingLoading,
   } = useSubmitSpark();
 
+  const {
+    yiyanAddingVisible,
+    hideyiyanAddingModal,
+    showyiyanAddingModal,
+    onyiyanAddingOk,
+    yiyanAddingLoading,
+  } = useSubmityiyan();
+
   const {
     bedrockAddingLoading,
     onBedrockAddingOk,
@@ -199,12 +210,14 @@ const UserSettingModel = () => {
       VolcEngine: showVolcAddingModal,
       'Tencent Hunyuan': showHunyuanAddingModal,
       'XunFei Spark': showSparkAddingModal,
+      BaiduYiyan: showyiyanAddingModal,
     }),
     [
       showBedrockAddingModal,
       showVolcAddingModal,
       showHunyuanAddingModal,
       showSparkAddingModal,
+      showyiyanAddingModal,
     ],
   );
 
@@ -330,6 +343,13 @@ const UserSettingModel = () => {
         loading={SparkAddingLoading}
         llmFactory={'XunFei Spark'}
       ></SparkModal>
+      <YiyanModal
+        visible={yiyanAddingVisible}
+        hideModal={hideyiyanAddingModal}
+        onOk={onyiyanAddingOk}
+        loading={yiyanAddingLoading}
+        llmFactory={'BaiduYiyan'}
+      ></YiyanModal>
       <BedrockModal
         visible={bedrockAddingVisible}
         hideModal={hideBedrockAddingModal}

web/src/pages/user-setting/setting-model/yiyan-modal/index.tsx

@@ -0,0 +1,97 @@
+import { useTranslate } from '@/hooks/common-hooks';
+import { IModalProps } from '@/interfaces/common';
+import { IAddLlmRequestBody } from '@/interfaces/request/llm';
+import { Form, Input, Modal, Select } from 'antd';
+import omit from 'lodash/omit';
+
+type FieldType = IAddLlmRequestBody & {
+  vision: boolean;
+  yiyan_ak: string;
+  yiyan_sk: string;
+};
+
+const { Option } = Select;
+
+const YiyanModal = ({
+  visible,
+  hideModal,
+  onOk,
+  loading,
+  llmFactory,
+}: IModalProps<IAddLlmRequestBody> & { llmFactory: string }) => {
+  const [form] = Form.useForm<FieldType>();
+
+  const { t } = useTranslate('setting');
+
+  const handleOk = async () => {
+    const values = await form.validateFields();
+    const modelType =
+      values.model_type === 'chat' && values.vision
+        ? 'image2text'
+        : values.model_type;
+
+    const data = {
+      ...omit(values, ['vision']),
+      model_type: modelType,
+      llm_factory: llmFactory,
+    };
+    console.info(data);
+
+    onOk?.(data);
+  };
+
+  return (
+    <Modal
+      title={t('addLlmTitle', { name: llmFactory })}
+      open={visible}
+      onOk={handleOk}
+      onCancel={hideModal}
+      okButtonProps={{ loading }}
+      confirmLoading={loading}
+    >
+      <Form
+        name="basic"
+        style={{ maxWidth: 600 }}
+        autoComplete="off"
+        layout={'vertical'}
+        form={form}
+      >
+        <Form.Item<FieldType>
+          label={t('modelType')}
+          name="model_type"
+          initialValue={'chat'}
+          rules={[{ required: true, message: t('modelTypeMessage') }]}
+        >
+          <Select placeholder={t('modelTypeMessage')}>
+            <Option value="chat">chat</Option>
+            <Option value="embedding">embedding</Option>
+            <Option value="rerank">rerank</Option>
+          </Select>
+        </Form.Item>
+        <Form.Item<FieldType>
+          label={t('modelName')}
+          name="llm_name"
+          rules={[{ required: true, message: t('yiyanModelNameMessage') }]}
+        >
+          <Input placeholder={t('yiyanModelNameMessage')} />
+        </Form.Item>
+        <Form.Item<FieldType>
+          label={t('addyiyanAK')}
+          name="yiyan_ak"
+          rules={[{ required: true, message: t('yiyanAKMessage') }]}
+        >
+          <Input placeholder={t('yiyanAKMessage')} />
+        </Form.Item>
+        <Form.Item<FieldType>
+          label={t('addyiyanSK')}
+          name="yiyan_sk"
+          rules={[{ required: true, message: t('yiyanSKMessage') }]}
+        >
+          <Input placeholder={t('yiyanSKMessage')} />
+        </Form.Item>
+      </Form>
+    </Modal>
+  );
+};
+
+export default YiyanModal;