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‎docs/zh/docs/dak/data-analysis/qa-quality.md

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## 查看问答质量详情
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1. 在 **数据分析** 栏中点击 **问答质量** ,找到需要查看的问答,点击该问答记录可进入详情页面。
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1. 在 **数据分析** 栏中点击 **问答质量** ，找到需要查看的问答，点击该问答记录可进入详情页面。
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![详情菜单](images/qa-quality.jpg)
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‎docs/zh/docs/dak/data-analysis/shard-hit-ratio.md

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## 查看分片命中率详情
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1. 在 **数据分析** 栏中点击 **分片命中率** ，通过 **搜索** 找到您关注的分片,点击该分片可进入详情页面，可查看该分片被引用的详细情况。
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1. 在 **数据分析** 栏中点击 **分片命中率** ，通过 **搜索** 找到您关注的分片，点击该分片可进入详情页面，可查看该分片被引用的详细情况。
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![选择详情](images/shard-hit-ratio.jpg)
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2. 可以查看以下内容：
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- 分片的基本信息：包括文本分片ID以及具体的分片内容。
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- 详细信息：该分片被问题命中的问题内容、应用名称、提问人以及提问时间。
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‎docs/zh/docs/dak/user-guide/app-center/create-app.md

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本页介绍如何在应用中心创建一个应用。
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<!-- <div class="video-container">
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<iframe width="560" height="315" src="https://harbor-test2.cn-sh2.ufileos.com/drun/deploy-qa.mp4" title="部署应用教学" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
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</div> -->
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### 创建 RAG 应用，具体步骤如下
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## 创建 RAG 应用
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1. 在 **应用中心** 页面中，点击 **创建** 按钮，选择创建 RAG 应用
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![发布应用](images/publish-app.jpg)
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### 创建全文阅读应用，具体步骤如下
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## 创建全文阅读应用
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1. 在 **应用中心** 页面中，点击 **创建** 按钮，选择创建 **全文阅读** 应用
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![创建全文阅读应用](../../images/create-read.jpg)
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### 创建组合应用，具体步骤如下
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## 创建组合应用
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1. 在 **应用中心** 页面中，点击 **创建** 按钮，选择创建 **组合应用**
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- 点击 **发布** 按钮，应用将会被发布到应用中心，用户可以在应用中心中找到并使用您的应用。
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![创建组合应用](../../images/create-combined.jpg)
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![创建组合应用](../../images/create-combined.jpg)

‎docs/zh/docs/en/dak/data-analysis/number-of-qa.md

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---
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# Number of Q&As
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d.run supports recording the number of Q&As created in this workspace.
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When users engage in Q&As, the records will be saved under the workspace where the app was created. Click the **Refresh** button in the upper right corner to view the latest Q&A count data.
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![Refresh](images/refresh-number-of-qa.png)
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You can summarize the Q&A counts of all users in this workspace into a table for export.
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1. On the **Number of Q&As** page, click the **Export** button in the upper right corner.
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<!-- ![Export](images/export-number-of-qa.jpg) -->
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2. The Q&A counts of all users in this workspace will be compiled into a xlsx file for download.

‎docs/zh/docs/en/dak/data-analysis/qa-quality.md

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# Q&A Quality
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d.run supports statistics on user feedback regarding the quality of Q&A, displaying it in reports and also allows data to be exported to xlsx format.
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## View Q&A Quality Details
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1. In the **Data Analysis** section, click **Q&A Quality** to find the Q&A you wish to view. Click the Q&A record to enter the details page.
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<!-- ![Details Menu](images/qa-quality.jpg) -->
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2. You can view the following content:
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- User's question, including the name of the user who asked.
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- App's answer: the answer generated by the app in response to the user's question.
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- The prompt used for the question.
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<!-- ![View Details](images/qa-quality-detail.jpg) -->
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3. When new Q&As are generated, you can click the **Refresh** button in the upper right corner to view the latest Q&A details.
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<!-- ![Refresh](images/refresh-qa-quality.jpg) -->
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## Export Q&A Quality
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You can summarize all user feedback on Q&A quality within this workspace into a table for export.
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1. On the **Q&A Quality** page, click the **Export** button in the upper right corner.
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<!-- ![Export](images/export-qa-quality.jpg) -->
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2. Click **Export Records** to view the exported Q&A quality records. Select the records you need to download and export them as an Excel file.
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<!-- ![Export](images/export-qa-records.jpg) -->

‎docs/zh/docs/en/dak/data-analysis/shard-hit-ratio.md

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# Shard Hit Ratio
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d.run tracks user interactions with shard data, ranking shards by hit count. It supports viewing shard content and exporting shard usage statistics to a xlsx file.
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## View Shard Hit Ratio Details
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1. In the **Data Analysis** section, click **Shard Hit Ratio**. Use the **Search** function to find the shard you are interested in. Click the shard to enter the details page, where you can view detailed information about how this shard has been referenced.
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<!-- ![Select Details](images/shard-hit-ratio.jpg) -->
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2. You can view the following content:
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- Basic information about the shard: including the text shard ID and specific shard content.
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- Detailed information: the questions that hit this shard, app name, questioner, and the time the question was asked.
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<!-- ![View Details](images/shard-hit-ratio-detail.png) -->
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3. When new Q&As are generated, you can click the **Refresh** button in the upper right corner to view the latest shard hit ratio results.
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<!-- ![Refresh](images/refresh-shard-hit-ratio-1.jpg) -->
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You can also **Refresh** in the shard hit ratio details to see the latest results.
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<!-- ![Refresh Results](images/refresh-shard-hit-ratio-2.png) -->
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## Export Shard Hit Ratio
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1. On the **Shard Hit Ratio** page, click the **Export** button in the upper right corner.
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<!-- ![Export](images/export-shard-hit-ratio.jpg) -->
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2. This will export the shards created in this workspace and compile feedback on these shard usage statistics into a xlsx file for download.

‎docs/zh/docs/en/dak/data-analysis/shard-quality.md

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# Shard Quality
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A shard refers to dividing larger data into multiple segments, which facilitates model training by making it easier to locate and hit the data.
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d.run supports viewing the quality of shards. The specific steps are as follows:
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1. In the **Data Analysis** section, click **Shard Quality**, and use the **Search** function to find the shard you are interested in. Click the shard to enter the details page, where you can view detailed information about this shard.
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<!-- ![Select Details Menu Item](images/shard-quality.jpg) -->
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2. You can view the following content:
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- Corpus: Which corpus the shard belongs to.
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- Update Time: The last update time of the shard file.
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- Shard ID: The unique identification code of the shard.
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- Shard Content: The specific content of the shard after slicing.
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- Additional Information: Additional content related to this shard.
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<!-- ![View Details](images/shard-quality-detail.jpg) -->
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3. When new shard files are evaluated, you can click the **Refresh** button in the upper right corner to view the latest shard files.
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<!-- ![Refresh](images/refresh-shard-quality.png) -->

‎docs/zh/docs/en/dak/data-analysis/suggestions.md

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# Suggestions
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d.run provides an entry for users to submit feedback, allowing administrators to see what issues need improvement in the apps within this workspace.
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## Handling Feedback
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1. In the **Data Analysis** section, click **Improvement Suggestions**, find the feedback that needs to be addressed, and click the **┇** button on the right.
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2. In the pop-up menu, select **Handle Feedback** (clicking the ticket information within the range will take you to the details page).
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<!-- ![Click to Handle Feedback](images/processing-feedback.jpg) -->
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3. You can view the following content:
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- User feedback on the Q&A.
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- Relevant information about the Q&A: assistant name, model name, number of citations, processing time, and Q&A details.
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<!-- ![Q&A Relevant Information](images/feedback-content.png) -->
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- Latest Citations: You can view the details of all citations referenced in the answer.
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<!-- ![Latest Citations](images/latest-quote.png) -->
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- Details of ticket processing.
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4. Click the status of the ticket marked as **Pending** to change the status to **In Progress** or **Completed**, and fill in the **Processing Description** below.
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5. Click the **OK** button in the lower right corner to modify the feedback processing status.
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<!-- ![Click Confirm](images/modify-processing-state.png) -->
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6. When new improvement suggestions are submitted, you can click the **Refresh** button in the upper right corner to view the latest suggestions.
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<!-- ![Refresh](images/refresh-improvement-suggestions.jpg) -->
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## Export Feedback
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Aggregate all Q&A details and feedback into a table for export.
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1. Click the **left side of Q&A feedback**, select the feedback you want to export, and click the **Export** button in the upper right corner.
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2. The Q&A content will be compiled into a xlsx file for download.
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<!-- ![Export](images/export-feedback.png) -->

‎docs/zh/docs/en/dak/features.md

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| Module | Features | Description |
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| Conversation | Context-Aware Intelligent Q&A | Connects application corpus to achieve context-aware intelligent Q&A functionality |
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| Conversation | Context-Aware Intelligent Q&A | Connects app corpus to achieve context-aware intelligent Q&A functionality |
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| | User Interaction Optimization | Supports users to **evaluate, copy, regenerate, delete conversations, or submit feedback** on AI responses, enhancing user experience |
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| Application Center | Application Lifecycle Management | Provides full lifecycle management from **creation, deployment, monitoring to maintenance** |
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| | Environment Isolation | Supports binding or unbinding of workspaces to achieve **environment isolation**, ensuring application security |
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| | Model Service Integration | Integrates **GLM, Llama, and other model services**, enhancing the efficiency of RAG (Retrieval-Augmented Generation) applications |
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| App Center | App Lifecycle Management | Provides full lifecycle management from **creation, deployment, monitoring to maintenance** |
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| | Environment Isolation | Supports binding or unbinding of workspaces to achieve **environment isolation**, ensuring app security |
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| | Model Service Integration | Integrates **GLM, Llama, and other model services**, enhancing the efficiency of RAG (Retrieval-Augmented Generation) apps |
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| | Diverse Configuration Options | Offers options for AI configuration, corpus association, retrieval strategies, etc., to optimize AI response quality |
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| | Application Key Support | Supports generation of **application keys** for secure access to OpenAPI conversations |
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| | Application Link Sharing | Allows **link sharing of applications** and supports H5 page display for mobile use |
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| | App Key Support | Supports generation of **app keys** for secure access to OpenAPI conversations |
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| | App Link Sharing | Allows **link sharing of apps** and supports H5 page display for mobile use |
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| | Conversation Process Viewing | Supports viewing the complete **conversation process**, enhancing user experience and troubleshooting efficiency |
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| | Combination Application Support | Supports **combination applications** for intent recognition, enhancing the ability to handle complex scenarios |
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| | Combination App Support | Supports **combination apps** for intent recognition, enhancing the ability to handle complex scenarios |
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| | Language Translation Support | Supports **translation** of user input content, improving the accuracy of corpus matching |
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| | Multilingual Response Selection | Allows users to choose the **language** of AI responses, catering to multilingual scenarios |
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| | Full Text Reading Application Support | New full text reading application, supports displaying **image content** |
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| | Full Text Reading App Support | New full text reading app, supports displaying **image content** |
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| | Support for Numbers and Chemical Formulas | Supports the display of **mathematical formulas and chemical equations**, enhancing the user experience in academic and research contexts |
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| Corpus Management | Multiple Import Methods | Supports various methods for managing the corpus, including **standard import, formatted import, manual import, and image-text import** |
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| | Intelligent Sharding | Supports **automatic sharding** by delimiter or size, with customizable sharding logic through plugins |

‎docs/zh/docs/en/dak/index.md

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The d.run intelligent Q&A product utilizes RAG technology to vectorize user data, and then combines a large language model with similarity search to query the user data repository, achieving knowledge-based Q&A.
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This method addresses the issues of user privacy data protection and model hallucination, resulting in more accurate and personalized responses.
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Here, you can create applications and plugins to build a corpus for AI conversations, and then optimize user experience through data analysis feedback.
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Here, you can create apps and plugins to build a corpus for AI conversations, and then optimize user experience through data analysis feedback.
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![Application Center](./images/app-center.jpg)
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![App Center](./images/app-center.jpg)
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[Register and Try d.run](https://console.d.run/){ .md-button .md-button--primary }

‎docs/zh/docs/en/dak/user-guide/app-center/conversation.md

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# App Dialogue Instructions
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**Dialogue** is the most common way to obtain information since the emergence of ChatGPT. In d.run, once an app is published, the dialogue function can be used. You can freely ask questions in the dialogue after linking to a corpus, consult historical records at any time, and the navigation bar also lists the recently used dialogues.
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## Daily Dialogue
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### RAG App
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1. In the left navigation bar, click on **App Center**, select the published RAG type app, and click the dialogue icon in the lower right corner.
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<!-- ![Click dialogue icon](../../images/chat01.jpg) -->
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2. Enter your question in the dialogue box, click **Send**, or press the Enter key to start the conversation.
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<!-- ![Chat](../../images/chat02.jpg) -->
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### Full Text Reading App
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1. In the left navigation bar, click on **App Center**, select the published **Full Text Reading** type app, and click the dialogue icon in the lower right corner.
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<!-- ![Click dialogue icon](../../images/chat03.jpg) -->
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2. Upload a file in the lower right corner of the dialogue box and ask questions based on the content of the file. Click **Send**, or press the Enter key to start the conversation.
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<!-- ![Chat](../../images/chat04.jpg) -->
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### Combination App
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1. In the left navigation bar, click on **App Center**, select the published **Combination App** type app, and click the dialogue icon in the lower right corner.
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<!-- ![Click dialogue icon](../../images/chat05.jpg) -->
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2. Enter your question in the dialogue box, click **Send**, or press the Enter key to start the conversation.
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<!-- ![Chat](../../images/chat06.jpg) -->
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## Dialogue Management
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<!-- ![manage](../images/manage.jpg) -->
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- **Pin**, **Rename**, and **Delete**: In the history pane, click the **┇** on the right side of a dialogue to pin, rename, or delete the dialogue.
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- **Clear**: In the upper left corner of the dialogue page, click the 🧹 icon to **clear** the dialogue.
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- **Link Corpus**: In the lower left corner of the input box, click the 📖 icon to link the corpus.
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Selection of corpus: The **chat app** will match the most similar corpus in the selected corpus as a reference to answer your questions. A successful operation will indicate that the corpus has been selected. You can also deselect one or more corpora.
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!!! info
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If you cannot select or change the linked corpus, you can only add a corpus. The vectorization model of the app must be consistent with the vectorization model of the corpus to be usable.
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- **Stop Dialogue**: After asking a question, click the icon on the right side of the input box to stop the dialogue, allowing the assistant to cease outputting content.
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## Some Useful Icons
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<!-- ![page-function](../images/page-function.jpg) -->
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- **Rating**: You can like 👍 or dislike 👎 a response, depending on your satisfaction with the content of the answer.
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- **Copy**: You can copy a response.
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- **Reset**: You can reset or regenerate a specific response.
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!!! info "Randomness"
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For the reset content, the administrator can adjust the model's **randomness** to control the consistency of the assistant's responses over multiple attempts.
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If the randomness is high, the assistant's responses may vary each time. If high accuracy is required, the randomness can be lowered, resulting in more consistent outputs from the assistant each time.
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- **Delete**: Click the trash can :material-delete: icon to delete a response, after which the deleted dialogue will not be remembered in the context of the assistant's conversation.
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- **Feedback**: Click the last icon :bookmark_tabs: of a response to submit feedback, providing comments based on the quality of the assistant's responses.

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