From 1edbd36baf1c30e8b67d2264e0b42b95d367a2a3 Mon Sep 17 00:00:00 2001
From: KevinHuSh <kevinhu.sh@gmail.com>
Date: Fri, 22 Mar 2024 15:35:06 +0800
Subject: [PATCH] add help info (#142)
---
.../components/similarity-slider/index.tsx | 10 +-
.../knowledge-setting/category-panel.tsx | 6 +-
.../knowledge-setting/configuration.tsx | 14 +--
.../components/knowledge-setting/utils.ts | 113 ++++++++++++------
.../testing-control/index.tsx | 5 +-
.../assistant-setting.tsx | 10 +-
.../model-setting.tsx | 16 +--
.../prompt-engine.tsx | 11 +-
.../setting-model/api-key-modal/index.tsx | 2 +-
.../system-model-setting-modal/index.tsx | 22 ++--
.../user-setting/setting-profile/index.tsx | 6 -
11 files changed, 131 insertions(+), 84 deletions(-)
diff --git a/web/src/components/similarity-slider/index.tsx b/web/src/components/similarity-slider/index.tsx
index 7f60199..a70dfcb 100644
--- a/web/src/components/similarity-slider/index.tsx
+++ b/web/src/components/similarity-slider/index.tsx
@@ -15,7 +15,10 @@ const SimilaritySlider = ({ isTooltipShown = false }: IProps) => {
<Form.Item<FieldType>
label="Similarity threshold"
name={'similarity_threshold'}
- tooltip={isTooltipShown && 'coming soon'}
+ tooltip={isTooltipShown && `We use hybrid similarity score to evaluate distance between two lines of text.
+ It\'s weighted keywords similarity and vector cosine similarity.
+ If the similarity between query and chunk is less than this threshold, the chunk will be filtered out.`
+ }
initialValue={0.2}
>
<Slider max={1} step={0.01} />
@@ -24,7 +27,10 @@ const SimilaritySlider = ({ isTooltipShown = false }: IProps) => {
label="Vector similarity weight"
name={'vector_similarity_weight'}
initialValue={0.3}
- tooltip={isTooltipShown && 'coming soon'}
+ tooltip={isTooltipShown && `We use hybrid similarity score to evaluate distance between two lines of text.
+ It\'s weighted keywords similarity and vector cosine similarity.
+ The sum of both weights is 1.0.
+ `}
>
<Slider max={1} step={0.01} />
</Form.Item>
diff --git a/web/src/pages/add-knowledge/components/knowledge-setting/category-panel.tsx b/web/src/pages/add-knowledge/components/knowledge-setting/category-panel.tsx
index 84af184..8b6168e 100644
--- a/web/src/pages/add-knowledge/components/knowledge-setting/category-panel.tsx
+++ b/web/src/pages/add-knowledge/components/knowledge-setting/category-panel.tsx
@@ -33,16 +33,16 @@ const CategoryPanel = ({ chunkMethod }: { chunkMethod: string }) => {
{imageList.length > 0 ? (
<>
<Title level={5} className={styles.topTitle}>
- {item.title} Category
+ "{item.title}" Chunking Method Description
</Title>
<p
dangerouslySetInnerHTML={{
__html: item.description,
}}
></p>
- <Title level={5}>{item.title} Image Examples</Title>
+ <Title level={5}>"{item.title}" Examples</Title>
<Text>
- We've prepared detailed visual guides to make understanding easier
+ This visual guides is in order to make understanding easier
for you.
</Text>
<Row gutter={[10, 10]} className={styles.imageRow}>
diff --git a/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx b/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx
index f69f631..fc8d056 100644
--- a/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx
+++ b/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx
@@ -83,7 +83,7 @@ const ConfigurationForm = ({ form }: { form: FormInstance }) => {
<Form.Item
name="permission"
label="Permissions"
- tooltip="coming soon"
+ tooltip="If the permission is 'Team', all the team member can manipulate the knowledgebase."
rules={[{ required: true }]}
>
<Radio.Group>
@@ -93,22 +93,22 @@ const ConfigurationForm = ({ form }: { form: FormInstance }) => {
</Form.Item>
<Form.Item
name="embd_id"
- label="Embedding Model"
+ label="Embedding model"
rules={[{ required: true }]}
- tooltip="xx"
+ tooltip="The embedding model used to embedding chunks. It's unchangable once the knowledgebase has chunks. You need to delete all the chunks if you want to change it."
>
<Select
- placeholder="Please select a country"
+ placeholder="Please select a embedding model"
options={embeddingModelOptions}
></Select>
</Form.Item>
<Form.Item
name="parser_id"
label="Chunk method"
- tooltip="xx"
+ tooltip="The instruction is at right."
rules={[{ required: true }]}
>
- <Select placeholder="Please select a country">
+ <Select placeholder="Please select a chunk method">
{parserList.map((x) => (
<Option value={x.value} key={x.value}>
{x.label}
@@ -122,7 +122,7 @@ const ConfigurationForm = ({ form }: { form: FormInstance }) => {
if (parserId === 'naive') {
return (
- <Form.Item label="Max token number" tooltip="xxx">
+ <Form.Item label="Token number" tooltip="It determine the token number of a chunk approximately.">
<Flex gap={20} align="center">
<Flex flex={1}>
<Form.Item
diff --git a/web/src/pages/add-knowledge/components/knowledge-setting/utils.ts b/web/src/pages/add-knowledge/components/knowledge-setting/utils.ts
index 4edda9c..9cb8cd0 100644
--- a/web/src/pages/add-knowledge/components/knowledge-setting/utils.ts
+++ b/web/src/pages/add-knowledge/components/knowledge-setting/utils.ts
@@ -7,78 +7,117 @@ export const ImageMap = {
book: getImageName('book', 4),
laws: getImageName('law', 4),
manual: getImageName('manual', 4),
- media: getImageName('media', 2),
+ picture: getImageName('picture', 2),
naive: getImageName('naive', 2),
paper: getImageName('paper', 2),
presentation: getImageName('presentation', 2),
qa: getImageName('qa', 2),
resume: getImageName('resume', 2),
table: getImageName('table', 2),
+ one: getImageName('one', 2),
};
export const TextMap = {
book: {
title: '',
- description: `Supported file formats are docx, excel, pdf, txt.
+ description: `<p>Supported file formats are <b>DOCX</b>, <b>PDF</b>, <b>TXT</b>.</p><p>
Since a book is long and not all the parts are useful, if it's a PDF,
- please setup the page ranges for every book in order eliminate negative effects and save computing time for analyzing.`,
+ please setup the <i>page ranges</i> for every book in order eliminate negative effects and save computing time for analyzing.</p>`,
},
laws: {
title: '',
- description: `Supported file formats are docx, pdf, txt.`,
+ description: `<p>Supported file formats are <b>DOCX</b>, <b>PDF</b>, <b>TXT</b>.</p><p>
+ Legal documents have a very rigorous writing format. We use text feature to detect split point.
+ </p><p>
+ The chunk granularity is consistent with 'ARTICLE', and all the upper level text will be included in the chunk.
+ </p>`,
},
- manual: { title: '', description: `Only pdf is supported.` },
- media: { title: '', description: '' },
+ manual: { title: '', description: `<p>Only <b>PDF</b> is supported.</p><p>
+ We assume manual has hierarchical section structure. We use the lowest section titles as pivots to slice documents.
+ So, the figures and tables in the same section will not be sliced apart, and chunk size might be large.
+ </p>` },
naive: {
title: '',
- description: `Supported file formats are docx, pdf, txt.
- This method apply the naive ways to chunk files.
- Successive text will be sliced into pieces using 'delimiter'.
- Next, these successive pieces are merge into chunks whose token number is no more than 'Max token number'.`,
+ description: `<p>Supported file formats are <b>DOCX, EXCEL, PPT, IMAGE, PDF, TXT</b>.</p>
+ <p>This method apply the naive ways to chunk files: </p>
+ <p>
+ <li>Successive text will be sliced into pieces using vision detection model.</li>
+ <li>Next, these successive pieces are merge into chunks whose token number is no more than 'Token number'.</li></p>`,
},
paper: {
title: '',
- description: `Only pdf is supported.
- The special part is that, the abstract of the paper will be sliced as an entire chunk, and will not be sliced partly.`,
+ description: `<p>Only <b>PDF</b> file is supported.</p><p>
+ If our model works well, the paper will be sliced by it's sections, like <i>abstract, 1.1, 1.2</i>, etc. </p><p>
+ The benefit of doing this is that LLM can better summarize the content of relevant sections in the paper,
+ resulting in more comprehensive answers that help readers better understand the paper.
+ The downside is that it increases the context of the LLM conversation and adds computational cost,
+ so during the conversation, you can consider reducing the â€<b>topN</b>’ setting.</p>`,
},
presentation: {
title: '',
- description: `The supported file formats are pdf, pptx.
- Every page will be treated as a chunk. And the thumbnail of every page will be stored.
- PPT file will be parsed by using this method automatically, setting-up for every PPT file is not necessary.`,
+ description: `<p>The supported file formats are <b>PDF</b>, <b>PPTX</b>.</p><p>
+ Every page will be treated as a chunk. And the thumbnail of every page will be stored.</p><p>
+ <i>All the PPT files you uploaded will be chunked by using this method automatically, setting-up for every PPT file is not necessary.</i></p>`,
},
qa: {
title: '',
- description: `Excel and csv(txt) format files are supported.
- If the file is in excel format, there should be 2 column question and answer without header.
+ description: `<p><b>EXCEL</b> and <b>CSV/TXT</b> files are supported.</p><p>
+ If the file is in excel format, there should be 2 columns question and answer without header.
And question column is ahead of answer column.
- And it's O.K if it has multiple sheets as long as the columns are rightly composed.
+ And it's O.K if it has multiple sheets as long as the columns are rightly composed.</p><p>
- If it's in csv format, it should be UTF-8 encoded. Use TAB as delimiter to separate question and answer.
+ If it's in csv format, it should be UTF-8 encoded. Use TAB as delimiter to separate question and answer.</p><p>
- All the deformed lines will be ignored.
- Every pair of Q&A will be treated as a chunk.`,
+ <i>All the deformed lines will be ignored.
+ Every pair of Q&A will be treated as a chunk.</i></p>`,
},
resume: {
title: '',
- description: `The supported file formats are pdf, docx and txt.`,
+ description: `<p>The supported file formats are <b>DOCX</b>, <b>PDF</b>, <b>TXT</b>.
+ </p><p>
+ The résumé comes in a variety of formats, just like a person’s personality, but we often have to organize them into structured data that makes it easy to search.
+ </p><p>
+ Instead of chunking the résumé, we parse the résumé into structured data. As a HR, you can dump all the résumé you have,
+ the you can list all the candidates that match the qualifications just by talk with <i>'RagFlow'</i>.
+ </p>
+ `,
},
table: {
title: '',
- description: `Excel and csv(txt) format files are supported.
- For csv or txt file, the delimiter between columns is TAB.
- The first line must be column headers.
- Column headers must be meaningful terms inorder to make our NLP model understanding.
- It's good to enumerate some synonyms using slash '/' to separate, and even better to
- enumerate values using brackets like 'gender/sex(male, female)'.
- Here are some examples for headers:
- 1. supplier/vendor\tcolor(yellow, red, brown)\tgender/sex(male, female)\tsize(M,L,XL,XXL)
- 2. 姓ĺŤ/ĺŤĺ—\t电话/手机/微信\t最é«ĺ¦ĺŽ†ďĽé«ä¸ďĽŚčŚé«ďĽŚçˇ•ĺŁ«ďĽŚćś¬ç§‘，博士，ĺťä¸ďĽŚä¸ćŠ€ďĽŚä¸ä¸“，专科，专升本，MPA，MBA，EMBA）
- Every row in table will be treated as a chunk.
-
-visual:
- Image files are supported. Video is comming soon.
- If the picture has text in it, OCR is applied to extract the text as a description of it.
- If the text extracted by OCR is not enough, visual LLM is used to get the descriptions.`,
+ description: `<p><b>EXCEL</b> and <b>CSV/TXT</b> format files are supported.</p><p>
+ Here're some tips:
+ <ul>
+ <li>For csv or txt file, the delimiter between columns is <em><b>TAB</b></em>.</li>
+ <li>The first line must be column headers.</li>
+ <li>Column headers must be meaningful terms in order to make our LLM understanding.
+ It's good to enumerate some synonyms using slash <i>'/'</i> to separate, and even better to
+ enumerate values using brackets like <i>'gender/sex(male, female)'</i>.<p>
+ Here are some examples for headers:<ol>
+ <li>supplier/vendor<b>'TAB'</b>color(yellow, red, brown)<b>'TAB'</b>gender/sex(male, female)<b>'TAB'</b>size(M,L,XL,XXL)</li>
+ <li>姓ĺŤ/ĺŤĺ—<b>'TAB'</b>电话/手机/微信<b>'TAB'</b>最é«ĺ¦ĺŽ†ďĽé«ä¸ďĽŚčŚé«ďĽŚçˇ•ĺŁ«ďĽŚćś¬ç§‘，博士，ĺťä¸ďĽŚä¸ćŠ€ďĽŚä¸ä¸“，专科，专升本，MPA，MBA，EMBA）</li>
+ </ol>
+ </p>
+ </li>
+ <li>Every row in table will be treated as a chunk.</li>
+ </ul>`,
+},
+picture: {
+ title: '',
+ description: `
+ <p>Image files are supported. Video is coming soon.</p><p>
+ If the picture has text in it, OCR is applied to extract the text as its text description.
+ </p><p>
+ If the text extracted by OCR is not enough, visual LLM is used to get the descriptions.
+ </p>`,
+ },
+one: {
+ title: '',
+ description: `
+ <p>Supported file formats are <b>DOCX, EXCEL, PDF, TXT</b>.
+ </p><p>
+ For a document, it will be treated as an entire chunk, no split at all.
+ </p><p>
+ If you don't trust any chunk method and the selected LLM's context length covers the document length, you can try this method.
+ </p>`,
},
};
diff --git a/web/src/pages/add-knowledge/components/knowledge-testing/testing-control/index.tsx b/web/src/pages/add-knowledge/components/knowledge-testing/testing-control/index.tsx
index 81d9a95..138614a 100644
--- a/web/src/pages/add-knowledge/components/knowledge-testing/testing-control/index.tsx
+++ b/web/src/pages/add-knowledge/components/knowledge-testing/testing-control/index.tsx
@@ -53,9 +53,10 @@ const TestingControl = ({ form, handleTesting }: IProps) => {
>
<SimilaritySlider isTooltipShown></SimilaritySlider>
<Form.Item<FieldType>
- label="Top k"
+ label="Top K"
name={'top_k'}
- tooltip="coming soon"
+ tooltip="For the computaion cost, not all the retrieved chunk will be computed vector cosine similarity with query.
+ The bigger the 'Top K' is, the higher the recall rate is, the slower the retrieval speed is."
>
<Slider marks={{ 0: 0, 2048: 2048 }} max={2048} />
</Form.Item>
diff --git a/web/src/pages/chat/chat-configuration-modal/assistant-setting.tsx b/web/src/pages/chat/chat-configuration-modal/assistant-setting.tsx
index 15b670e..bca69b6 100644
--- a/web/src/pages/chat/chat-configuration-modal/assistant-setting.tsx
+++ b/web/src/pages/chat/chat-configuration-modal/assistant-setting.tsx
@@ -55,6 +55,7 @@ const AssistantSetting = ({ show }: ISegmentedContentProps) => {
label="Language"
initialValue={'Chinese'}
tooltip="coming soon"
+ style={{display:'none'}}
>
<Select
options={[
@@ -66,22 +67,23 @@ const AssistantSetting = ({ show }: ISegmentedContentProps) => {
<Form.Item
name={['prompt_config', 'empty_response']}
label="Empty response"
- tooltip="coming soon"
+ tooltip="If nothing is retrieved with user's question in the knowledgebase, it will use this as an answer.
+ If you want LLM comes up with its own opinion when nothing is retrieved, leave this blank."
>
<Input placeholder="" />
</Form.Item>
<Form.Item
name={['prompt_config', 'prologue']}
label="Set an opener"
- tooltip="coming soon"
+ tooltip="How do you want to welcome your clients?"
initialValue={"Hi! I'm your assistant, what can I do for you?"}
>
<Input.TextArea autoSize={{ minRows: 5 }} />
</Form.Item>
<Form.Item
- label="Select one context"
+ label="Knowledgebases"
name="kb_ids"
- tooltip="coming soon"
+ tooltip="Select knowledgebases associated."
rules={[
{
required: true,
diff --git a/web/src/pages/chat/chat-configuration-modal/model-setting.tsx b/web/src/pages/chat/chat-configuration-modal/model-setting.tsx
index cf2ec45..87390ab 100644
--- a/web/src/pages/chat/chat-configuration-modal/model-setting.tsx
+++ b/web/src/pages/chat/chat-configuration-modal/model-setting.tsx
@@ -46,16 +46,16 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
<Form.Item
label="Model"
name="llm_id"
- tooltip="coming soon"
+ tooltip="Large language chat model"
rules={[{ required: true, message: 'Please select!' }]}
>
<Select options={modelOptions} showSearch />
</Form.Item>
<Divider></Divider>
<Form.Item
- label="Parameters"
+ label="Freedom"
name="parameters"
- tooltip="coming soon"
+ tooltip="'Precise' means the LLM will be conservative and answer your question cautiously. 'Improvise' means the you want LLM talk much and freely. 'Balance' is between cautiously and freely."
initialValue={ModelVariableType.Precise}
// rules={[{ required: true, message: 'Please input!' }]}
>
@@ -64,7 +64,7 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
onChange={handleParametersChange}
/>
</Form.Item>
- <Form.Item label="Temperature" tooltip={'xx'}>
+ <Form.Item label="Temperature" tooltip={'This parameter controls the randomness of predictions by the model. A lower temperature makes the model more confident in its responses, while a higher temperature makes it more creative and diverse.'}>
<Flex gap={20} align="center">
<Form.Item
name={'temperatureEnabled'}
@@ -96,7 +96,7 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
</Form.Item>
</Flex>
</Form.Item>
- <Form.Item label="Top P" tooltip={'xx'}>
+ <Form.Item label="Top P" tooltip={'Also known as “nucleus sampling,” this parameter sets a threshold to select a smaller set of words to sample from. It focuses on the most likely words, cutting off the less probable ones.'}>
<Flex gap={20} align="center">
<Form.Item name={'topPEnabled'} valuePropName="checked" noStyle>
<Switch size="small" />
@@ -124,7 +124,7 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
</Form.Item>
</Flex>
</Form.Item>
- <Form.Item label="Presence Penalty" tooltip={'xx'}>
+ <Form.Item label="Presence Penalty" tooltip={'This discourages the model from repeating the same information by penalizing words that have already appeared in the conversation.'}>
<Flex gap={20} align="center">
<Form.Item
name={'presencePenaltyEnabled'}
@@ -160,7 +160,7 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
</Form.Item>
</Flex>
</Form.Item>
- <Form.Item label="Frequency Penalty" tooltip={'xx'}>
+ <Form.Item label="Frequency Penalty" tooltip={'Similar to the presence penalty, this reduces the model’s tendency to repeat the same words frequently.'}>
<Flex gap={20} align="center">
<Form.Item
name={'frequencyPenaltyEnabled'}
@@ -196,7 +196,7 @@ const ModelSetting = ({ show, form }: ISegmentedContentProps) => {
</Form.Item>
</Flex>
</Form.Item>
- <Form.Item label="Max Tokens" tooltip={'xx'}>
+ <Form.Item label="Max Tokens" tooltip={'This sets the maximum length of the model’s output, measured in the number of tokens (words or pieces of words).'}>
<Flex gap={20} align="center">
<Form.Item name={'maxTokensEnabled'} valuePropName="checked" noStyle>
<Switch size="small" />
diff --git a/web/src/pages/chat/chat-configuration-modal/prompt-engine.tsx b/web/src/pages/chat/chat-configuration-modal/prompt-engine.tsx
index 758330a..1fc6e10 100644
--- a/web/src/pages/chat/chat-configuration-modal/prompt-engine.tsx
+++ b/web/src/pages/chat/chat-configuration-modal/prompt-engine.tsx
@@ -154,7 +154,7 @@ const PromptEngine = (
<Form.Item
label="System"
rules={[{ required: true, message: 'Please input!' }]}
- tooltip="coming soon"
+ tooltip="Instructions you need LLM to follow when LLM answers questions, like charactor design, answer length and answer language etc."
name={['prompt_config', 'system']}
initialValue={`ä˝ ćŻä¸€ä¸Şć™şč˝ĺŠ©ć‰‹ďĽŚčŻ·ć€»ç»“知识库的内容来回ç”é—®é˘ďĽŚčŻ·ĺ—举知识库ä¸çš„数据详细回ç”。当所有知识库内容é˝ä¸Žé—®é˘ć— ĺ…łć—¶ďĽŚä˝ çš„ĺ›žç”必须包括“知识库ä¸ćśŞć‰ľĺ°ć‚¨č¦çš„ç”ćˇďĽâ€ťčż™ĺŹĄčŻťă€‚回ç”需č¦č€č™‘čŠĺ¤©ĺŽ†ĺŹ˛ă€‚
以下ćŻçźĄčŻ†ĺş“：
@@ -166,10 +166,10 @@ const PromptEngine = (
<Divider></Divider>
<SimilaritySlider isTooltipShown></SimilaritySlider>
<Form.Item<FieldType>
- label="Top n"
+ label="Top N"
name={'top_n'}
initialValue={8}
- tooltip={'xxx'}
+ tooltip={`Not all the chunks whose similarity score is above the 'simialrity threashold' will be feed to LLMs. LLM can only see these 'Top N' chunks.`}
>
<Slider max={30} />
</Form.Item>
@@ -178,7 +178,10 @@ const PromptEngine = (
<Col span={7} className={styles.variableAlign}>
<label className={styles.variableLabel}>
Variables
- <Tooltip title="coming soon">
+ <Tooltip title="If you use dialog APIs, the varialbes might help you chat with your clients with different strategies.
+ The variables are used to fill-in the 'System' part in prompt in order to give LLM a hint.
+ The 'knowledge' is a very special variable which will be filled-in with the retrieved chunks.
+ All the variables in 'System' should be curly bracketed.">
<QuestionCircleOutlined className={styles.variableIcon} />
</Tooltip>
</label>
diff --git a/web/src/pages/user-setting/setting-model/api-key-modal/index.tsx b/web/src/pages/user-setting/setting-model/api-key-modal/index.tsx
index fabdec4..d35186e 100644
--- a/web/src/pages/user-setting/setting-model/api-key-modal/index.tsx
+++ b/web/src/pages/user-setting/setting-model/api-key-modal/index.tsx
@@ -66,7 +66,7 @@ const ApiKeyModal = ({
<Form.Item<FieldType>
label="Api-Key"
name="api_key"
- tooltip="coming soon"
+ tooltip="The API key can be obtained by registering the corresponding LLM supplier."
rules={[{ required: true, message: 'Please input api key!' }]}
>
<Input />
diff --git a/web/src/pages/user-setting/setting-model/system-model-setting-modal/index.tsx b/web/src/pages/user-setting/setting-model/system-model-setting-modal/index.tsx
index 54ccc72..1deb482 100644
--- a/web/src/pages/user-setting/setting-model/system-model-setting-modal/index.tsx
+++ b/web/src/pages/user-setting/setting-model/system-model-setting-modal/index.tsx
@@ -43,25 +43,27 @@ const SystemModelSettingModal = ({
confirmLoading={loading}
>
<Form form={form} onValuesChange={onFormLayoutChange} layout={'vertical'}>
- <Form.Item
- label="Sequence2txt model"
- name="asr_id"
- tooltip="coming soon"
- >
- <Select options={allOptions[LlmModelType.Speech2text]} />
+
+ <Form.Item label="Chat model" name="llm_id" tooltip="The default chat LLM all the newly created knowledgebase will use.">
+ <Select options={allOptions[LlmModelType.Chat]} />
</Form.Item>
- <Form.Item label="Embedding model" name="embd_id" tooltip="coming soon">
+ <Form.Item label="Embedding model" name="embd_id" tooltip="The default embedding model all the newly created knowledgebase will use.">
<Select options={allOptions[LlmModelType.Embedding]} />
</Form.Item>
<Form.Item
label="Img2txt model"
name="img2txt_id"
- tooltip="coming soon"
+ tooltip="The default multi-module model all the newly created knowledgebase will use. It can describe a picture or video."
>
<Select options={allOptions[LlmModelType.Image2text]} />
</Form.Item>
- <Form.Item label="Chat model" name="llm_id" tooltip="coming soon">
- <Select options={allOptions[LlmModelType.Chat]} />
+
+ <Form.Item
+ label="Sequence2txt model"
+ name="asr_id"
+ tooltip="The default ASR model all the newly created knowledgebase will use. Use this model to translate voices to corresponding text."
+ >
+ <Select options={allOptions[LlmModelType.Speech2text]} />
</Form.Item>
</Form>
</Modal>
diff --git a/web/src/pages/user-setting/setting-profile/index.tsx b/web/src/pages/user-setting/setting-profile/index.tsx
index 13ea15f..bb3e3f9 100644
--- a/web/src/pages/user-setting/setting-profile/index.tsx
+++ b/web/src/pages/user-setting/setting-profile/index.tsx
@@ -110,9 +110,6 @@ const UserSettingProfile = () => {
<div>
<Space>
Your photo
- <Tooltip title="coming soon">
- <QuestionCircleOutlined />
- </Tooltip>
</Space>
<div>This will be displayed on your profile.</div>
</div>
@@ -140,7 +137,6 @@ const UserSettingProfile = () => {
<Form.Item<FieldType>
label="Color schema"
name="color_schema"
- tooltip="coming soon"
rules={[
{ required: true, message: 'Please select your color schema!' },
]}
@@ -154,7 +150,6 @@ const UserSettingProfile = () => {
<Form.Item<FieldType>
label="Language"
name="language"
- tooltip="coming soon"
rules={[{ required: true, message: 'Please input your language!' }]}
>
<Select placeholder="select your language">
@@ -166,7 +161,6 @@ const UserSettingProfile = () => {
<Form.Item<FieldType>
label="Timezone"
name="timezone"
- tooltip="coming soon"
rules={[{ required: true, message: 'Please input your timezone!' }]}
>
<Select placeholder="select your timezone" showSearch>
--
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