Moved agent components into the agent folder (#5496)

### What problem does this PR solve? ### Type of change - [x] Documentation Update
2025-12-08 20:42:30 +08:00 · 2025-02-28 19:27:57 +08:00
parent 6a71314d70
commit e61da33672
15 changed files with 26 additions and 30 deletions
--- a/docs/guides/agent/agent_component_reference/_category_.json
+++ b/docs/guides/agent/agent_component_reference/_category_.json
@ -0,0 +1,8 @@
+{
+  "label": "Agent Components",
+  "position": 20,
+  "link": {
+    "type": "generated-index",
+    "description": "A complete reference for RAGFlow's agent components."
+  }
+}
--- a/docs/guides/agent/agent_component_reference/begin.mdx
+++ b/docs/guides/agent/agent_component_reference/begin.mdx
@ -0,0 +1,74 @@
+---
+sidebar_position: 1
+slug: /begin_component
+---
+
+# Begin component
+
+The starting component in a workflow.
+
+---
+
+The **Begin** component sets an opening greeting or accepts inputs from the user. It is automatically populated onto the canvas when you create an agent, whether from a template or from scratch (from a blank template). There should be only one **Begin** component in the workflow.
+
+## Scenarios
+
+A **Begin** component is essential in all cases. Every agent includes a **Begin** component, which cannot be deleted.
+
+## Configurations
+
+Click the component to display its **Configuration** window. Here, you can set an opening greeting and the input parameters (global variables) for the agent.
+
+### ID
+
+The ID is the unique identifier for the component within the workflow. Unlike the IDs of other components, the ID of the **Begin** component *cannot* be changed.
+
+### Opening greeting
+
+An opening greeting is the agent's first message to the user. It can be a welcoming remark or an instruction to guide the user forward.
+
+### Global variables
+
+You can set global variables within the **Begin** component, which can be either required or optional. Once established, users will need to provide values for these variables when interacting or chatting with the agent. Click **+ Add variable** to add a global variable, each with the following attributes:
+
+- **Key**: *Required*  
+  The unique variable name.
+- **Name**: *Required*  
+  A descriptive name providing additional details about the variable.  
+  For example, if **Key** is set to `lang`, you can set its **Name** to `Target language`.
+- **Type**: *Required*  
+  The type of the variable:  
+  - **line**: Accepts a single line of text without line breaks.
+  - **paragraph**: Accepts multiple lines of text, including line breaks.
+  - **options**: Requires the user to select a value for this variable from a dropdown menu. And you are required to set *at least* one option for the dropdown menu.
+  - **file**: Requires the user to upload one or multiple files.
+  - **integer**: Accepts an integer as input.
+  - **boolean**: Requires the user to toggle between on and off.
+- **Optional**: A toggle indicating whether the variable is optional. 
+
+## Examples
+
+As mentioned earlier, the **Begin** component is indispensable for an agent. Still, you can take a look at our three-step interpreter agent template, where the **Begin** component takes two global variables:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Interpreter** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Begin** component to display its **Configuration** window.
+
+## Frequently asked questions
+
+### Is the uploaded file in a knowledge base?
+
+No. Files uploaded to an agent as input are not stored in a knowledge base and will not be chunked using RAGFlow's built-in chunk methods. However, RAGFlow's built-in OSR, DLR, and TSR models will still be applied to process the document.
+
+### How to upload a webpage or file from a URL?
+
+If you set the type of a variable as **file**, your users will be able to upload a file either from their local device or from an accessible URL. For example:
+
+![upload_file](https://github.com/user-attachments/assets/7ad2a352-0807-4b74-b8d1-d09e5cd37997)
+
+### File size limit for an uploaded file
+
+The maximum file size for each uploaded file is determined by the variable `MAX_CONTENT_LENGTH` in `/docker/.env`. It defaults to 128 MB. If you change the default file size, ensure you also update the value of `client_max_body_size` in `/docker/nginx/nginx.conf` accordingly.
+
--- a/docs/guides/agent/agent_component_reference/categorize.mdx
+++ b/docs/guides/agent/agent_component_reference/categorize.mdx
@ -0,0 +1,111 @@
+---
+sidebar_position: 5
+slug: /categorize_component
+---
+
+# Categorize component
+
+A component that classifies user inputs and applies strategies accordingly. 
+
+---
+
+A **Categorize** component is usually the downstream of the **Interact** component.
+
+## Scenarios
+
+A **Categorize** component is essential when you need the LLM to help you identify user intentions and apply appropriate processing strategies.
+
+## Configurations
+
+### Input
+
+The **Categorize** component relies on input variables to specify its data inputs (queries). Click **+ Add variable** in the **Input** section to add the desired input variables. There are two types of input variables: **Reference** and **Text**.
+
+- **Reference**: Uses a component's output or a user input as the data source. You are required to select from the dropdown menu:
+  - A component ID under **Component Output**, or 
+  - A global variable under **Begin input**, which is defined in the **Begin** component.
+- **Text**: Uses fixed text as the query. You are required to enter static text.
+
+### Model
+
+Click the dropdown menu of **Model** to show the model configuration window.
+
+- **Model**: The chat model to use.  
+  - Ensure you set the chat model correctly on the **Model providers** page.
+  - You can use different models for different components to increase flexibility or improve overall performance.
+- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.  
+  This parameter has three options:  
+  - **Improvise**: Produces more creative responses.
+  - **Precise**: (Default) Produces more conservative responses.
+  - **Balance**: A middle ground between **Improvise** and **Precise**.
+- **Temperature**: The randomness level of the model's output.  
+  Defaults to 0.1.  
+  - Lower values lead to more deterministic and predictable outputs.
+  - Higher values lead to more creative and varied outputs.
+  - A temperature of zero results in the same output for the same prompt.
+- **Top P**: Nucleus sampling.  
+  - Reduces the likelihood of generating repetitive or unnatural text by setting a threshold *P* and restricting the sampling to tokens with a cumulative probability exceeding *P*.
+  - Defaults to 0.3.
+- **Presence penalty**: Encourages the model to include a more diverse range of tokens in the response.  
+  - A higher **presence penalty** value results in the model being more likely to generate tokens not yet been included in the generated text.
+  - Defaults to 0.4.
+- **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
+  - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
+  - Defaults to 0.7.
+- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
+  - Defaults to 512. 
+  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
+
+:::tip NOTE
+- It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.
+- If you are uncertain about the mechanism behind **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**, simply choose one of the three options of **Preset configurations**.
+:::
+
+### Message window size
+
+An integer specifying the number of previous dialogue rounds to input into the LLM. For example, if it is set to 12, the tokens from the last 12 dialogue rounds will be fed to the LLM. This feature consumes additional tokens.
+
+Defaults to 1.
+
+:::tip IMPORTANT
+This feature is used for multi-turn dialogue *only*. If your **Categorize** component is not part of a multi-turn dialogue (i.e., it is not in a loop), leave this field as-is.
+:::
+
+### Category name
+
+A **Categorize** component must have at least two categories. This field sets the name of the category. Click **+ Add Item** to include the intended categories. 
+
+:::tip NOTE
+You will notice that the category name is auto-populated. No worries. Each category is assigned a random name upon creation. Feel free to change it to a name that is understandable to the LLM.
+:::
+
+#### Description
+
+Description of this category.  
+
+You can input criteria, situation, or information that may help the LLM determine which inputs belong in this category.
+
+#### Examples
+
+Additional examples that may help the LLM determine which inputs belong in this category.
+
+:::danger IMPORTANT
+Examples are more helpful than the description if you want the LLM to classify particular cases into this category.
+:::
+
+#### Next step
+
+Specifies the downstream component of this category.
+
+- Once you specify the ID of the downstream component, a link is established between this category and the corresponding component.
+- If you manually link this category to a downstream component on the canvas, the ID of that component is auto-populated.
+
+## Examples
+
+You can explore our customer service agent template, where a **Categorize** component (component ID: **Question Categorize**) has four defined categories and takes data inputs from an **Interact** component (component ID: **Interface**):
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Interpreter** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+
--- a/docs/guides/agent/agent_component_reference/concentrator.mdx
+++ b/docs/guides/agent/agent_component_reference/concentrator.mdx
@ -0,0 +1,26 @@
+---
+sidebar_position: 10
+slug: /concentrator_component
+---
+
+# Concentrator component
+
+A component that directs execution flow to multiple downstream components.
+
+---
+
+The **Concentrator** component acts as a "repeater" of execution flow, transmitting a flow to multiple downstream components.
+
+
+## Scenarios
+
+A **Concentrator** component enhances the current UX design. For a component originally designed to support only one downstream component, you can append a **Concentrator**, enabling it to have multiple downstream components.
+
+## Examples
+
+Explore our general-purpose chatbot agent template, featuring a **Concentrator** component (component ID: **medical**) that relays an execution flow from category 2 of the **Categorize** component to two translator components:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **General-purpose chatbot** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
--- a/docs/guides/agent/agent_component_reference/generate.mdx
+++ b/docs/guides/agent/agent_component_reference/generate.mdx
@ -0,0 +1,117 @@
+---
+sidebar_position: 2
+slug: /generate_component
+---
+
+# Generate component
+
+The component that prompts the LLM to respond appropriately.
+
+---
+
+A **Generate** component fine-tunes the LLM and sets its prompt.
+
+## Scenarios
+
+A **Generate** component is essential when you need the LLM to assist with summarizing, translating, or controlling various tasks. 
+
+## Configurations
+
+### Model
+
+Click the dropdown menu of **Model** to show the model configuration window.
+
+- **Model**: The chat model to use.  
+  - Ensure you set the chat model correctly on the **Model providers** page.
+  - You can use different models for different components to increase flexibility or improve overall performance.
+- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+  This parameter has three options:
+  - **Improvise**: Produces more creative responses.
+  - **Precise**: (Default) Produces more conservative responses.
+  - **Balance**: A middle ground between **Improvise** and **Precise**.
+- **Temperature**: The randomness level of the model's output.  
+  Defaults to 0.1.
+  - Lower values lead to more deterministic and predictable outputs.
+  - Higher values lead to more creative and varied outputs.
+  - A temperature of zero results in the same output for the same prompt.
+- **Top P**: Nucleus sampling.  
+  - Reduces the likelihood of generating repetitive or unnatural text by setting a threshold *P* and restricting the sampling to tokens with a cumulative probability exceeding *P*.
+  - Defaults to 0.3.
+- **Presence penalty**: Encourages the model to include a more diverse range of tokens in the response.  
+  - A higher **presence penalty** value results in the model being more likely to generate tokens not yet been included in the generated text.
+  - Defaults to 0.4.
+- **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
+  - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
+  - Defaults to 0.7.
+- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
+  - Defaults to 512. 
+  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
+
+:::tip NOTE
+- It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.
+- If you are uncertain about the mechanism behind **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**, simply choose one of the three options of **Preset configurations**.
+:::
+
+### System prompt
+
+Typically, you use the system prompt to describe the task for the LLM, specify how it should respond, and outline other miscellaneous requirements. We do not plan to elaborate on this topic, as it can be as extensive as prompt engineering. However, please be aware that the system prompt is often used in conjunction with keys (variables), which serve as various data inputs for the LLM. 
+
+Keys in a system prompt should be enclosed in curly braces. Below is a prompt excerpt of a **Generate** component from the **Interpreter** template (component ID: **Reflect**):
+
+```text
+Your task is to read a source text and a translation to {target_lang}, and give constructive suggestions to improve the translation. The source text and initial translation, delimited by XML tags <SOURCE_TEXT></SOURCE_TEXT> and <TRANSLATION></TRANSLATION>, are as follows:
+
+<SOURCE_TEXT>
+{source_text}
+</SOURCE_TEXT>
+
+<TRANSLATION>
+{translation_1}
+</TRANSLATION>
+
+When writing suggestions, pay attention to whether there are ways to improve the translation's fluency, by applying {target_lang} grammar, spelling and punctuation rules, and ensuring there are no unnecessary repetitions.
+- Each suggestion should address one specific part of the translation.
+- Output the suggestions only.
+```
+
+Where `{source_text}` and `{target_lang}` are global variables defined by the **Begin** component, while `{translation_1}` is the output of another **Generate** component with the component ID **Translate directly**.
+
+
+:::danger IMPORTANT
+A **Generate** component relies on keys (variables) to specify its data inputs. Its immediate upstream component is *not* necessarily its data input, and the arrows in the workflow indicate *only* the processing sequence.
+:::
+
+![variable_settings](https://github.com/user-attachments/assets/cb024c9e-264a-43ff-9ee7-8649afd571b0)
+
+Keys in a **Generate** component are used in conjunction with the system prompt to specify data inputs for the LLM. Use a forward slash `/` to show the keys to use.
+
+### Cite 
+
+This toggle sets whether to cite the original text as reference. 
+
+
+:::tip NOTE
+This feature is used for multi-turn dialogue *only* and is applicable *only* when the original documents are uploaded to a knowledge base and have finished file parsing.
+:::
+
+
+### Message window size
+
+An integer specifying the number of previous dialogue rounds to input into the LLM. For example, if it is set to 12, the tokens from the last 12 dialogue rounds will be fed to the LLM. This feature consumes additional tokens.
+
+:::tip IMPORTANT
+This feature is used for multi-turn dialogue *only*.
+:::
+
+
+## Examples
+
+You can explore our three-step interpreter agent template, where a **Generate** component (component ID: **Reflect**) takes three global variables:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Interpreter** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on component **Reflect**, to display its **Configuration** window, where:
+   - `{target_lang}` and `{source_text}` are defined in the **Begin** component and require user input.
+   - `{translation_1}` is the output from the upstream component **Translate directly**.
--- a/docs/guides/agent/agent_component_reference/interact.mdx
+++ b/docs/guides/agent/agent_component_reference/interact.mdx
@ -0,0 +1,21 @@
+---
+sidebar_position: 3
+slug: /interact_component
+---
+
+# Interact component
+
+A component that accepts user inputs and displays responses.
+
+---
+
+An **Interact** component serves as the interface between human and bot, receiving user inputs and displaying the agent's responses.
+
+
+## Scenarios
+
+An **Interact** component is essential where you need to display the agent's responses or require user-computer interaction.
+
+## Examples
+
+You can explore our three-step interpreter agent template, where the **Interact** component is used to display the final translation, or our customer service agent template, where the **Interact** component is the immediate downstream of **Begin** and is used to display multi-turn dialogue between the user and the agent.
--- a/docs/guides/agent/agent_component_reference/iteration.mdx
+++ b/docs/guides/agent/agent_component_reference/iteration.mdx
@ -0,0 +1,77 @@
+---
+sidebar_position: 12
+slug: /iteration_component
+---
+
+# Iteration component
+
+A component that splits text input into text segments and iterates a predefined workflow for each one.
+
+---
+
+An **Interaction** component can divide text input into text segments and apply its built-in component workflow to each segment. 
+
+
+## Scenario
+
+An **Iteration** component is essential when a workflow loop is required and the loop count is *not* fixed but depends on number of segments created from the output of specific agent components. 
+
+- If, for instance, you plan to feed several paragraphs into an LLM for content generation, each with its own focus, and feeding them to the LLM all at once could create confusion or contradictions, then you can use an **Iteration** component, which encapsulates a **Generate** component, to repeat the content generation process for each paragraph.
+- Another example: If you wish to use the LLM to translate a lengthy paper into a target language without exceeding its token limit, consider using an **Iteration** component, which encapsulates a **Generate** component, to break the paper into smaller pieces and repeat the translation process for each one.
+
+## Internal components
+
+### IterationItem
+
+Each **Iteration** component includes an internal **IterationItem** component. The **IterationItem** component serves as both the starting point and input node of the workflow within the **Iteration** component. It manages the loop of the workflow for all text segments created from the input.
+
+:::tip NOTE
+The **IterationItem** component is visible *only* to the components encapsulated by the current **Iteration** components.
+:::
+
+![Iterationitem](https://github.com/user-attachments/assets/97117ceb-76c4-432e-aa86-48f253bcb886)
+
+### Build an internal workflow 
+
+You are allowed to pull other components into the **Iteration** component to build an internal workflow, and these "added internal components" are no longer visible to components outside of the current **Iteration** component.
+
+:::danger IMPORTANT
+To reference the created text segments from an added internal component, simply add a **Reference** variable that equals **IterationItem** within the **Input** section of that internal component. There is no need to reference the corresponding external component, as the **IterationItem** component manages the loop of the workflow for all created text segments. 
+:::
+
+:::tip NOTE
+An added internal component can reference an external component when necessary.
+:::
+
+## Configurations
+
+### Input
+
+The **Iteration** component uses input variables to specify its data inputs, namely the texts to be segmented. You are allowed to specify multiple input sources for the **Iteration** component. Click **+ Add variable** in the **Input** section to include the desired input variables. There are two types of input variables: **Reference** and **Text**.
+
+- **Reference**: Uses a component's output or a user input as the data source. You are required to select from the dropdown menu:
+  - A component ID under **Component Output**, or 
+  - A global variable under **Begin input**, which is defined in the **Begin** component.
+- **Text**: Uses fixed text as the query. You are required to enter static text.
+
+### Delimiter
+
+The delimiter to use to split the text input into segments:
+
+- Comma (Default)
+- Line break
+- Tab
+- Underline
+- Forward slash
+- Dash
+- Semicolon
+
+## Examples
+
+Explore our research report generator agent template, where the **Iteration** component (component ID: **Sections**) takes subtitles from the **Subtitles** component and generates sections for them:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Customer service** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Iteration** component to display its **Configuration** window.
--- a/docs/guides/agent/agent_component_reference/keyword.mdx
+++ b/docs/guides/agent/agent_component_reference/keyword.mdx
@ -0,0 +1,79 @@
+---
+sidebar_position: 6
+slug: /keyword_component
+---
+
+# Keyword component
+
+A component that extracts keywords from a user query.
+
+---
+
+A **Keyword** component uses the specified LLM to extract keywords from a user query.
+
+## Scenarios
+
+A **Keyword** component is essential where you need to prepare keywords for a potential keyword search.
+
+## Configurations
+
+### Input
+
+The **Keyword** component relies on input variables to specify its data inputs (queries). Click **+ Add variable** in the **Input** section to add the desired input variables. There are two types of input variables: **Reference** and **Text**.
+
+- **Reference**: Uses a component's output or a user input as the data source. You are required to select from the dropdown menu:
+  - A component ID under **Component Output**, or 
+  - A global variable under **Begin input**, which is defined in the **Begin** component.
+- **Text**: Uses fixed text as the query. You are required to enter static text.
+
+
+### Model
+
+Click the dropdown menu of **Model** to show the model configuration window.
+
+- **Model**: The chat model to use.  
+  - Ensure you set the chat model correctly on the **Model providers** page.
+  - You can use different models for different components to increase flexibility or improve overall performance.
+- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+  This parameter has three options:
+  - **Improvise**: Produces more creative responses.
+  - **Precise**: (Default) Produces more conservative responses.
+  - **Balance**: A middle ground between **Improvise** and **Precise**.
+- **Temperature**: The randomness level of the model's output.  
+  Defaults to 0.1.
+  - Lower values lead to more deterministic and predictable outputs.
+  - Higher values lead to more creative and varied outputs.
+  - A temperature of zero results in the same output for the same prompt.
+- **Top P**: Nucleus sampling.  
+  - Reduces the likelihood of generating repetitive or unnatural text by setting a threshold *P* and restricting the sampling to tokens with a cumulative probability exceeding *P*.
+  - Defaults to 0.3.
+- **Presence penalty**: Encourages the model to include a more diverse range of tokens in the response.  
+  - A higher **presence penalty** value results in the model being more likely to generate tokens not yet been included in the generated text.
+  - Defaults to 0.4.
+- **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
+  - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
+  - Defaults to 0.7.
+- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
+  - Defaults to 512. 
+  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
+
+:::tip NOTE
+- It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.
+- If you are uncertain about the mechanism behind **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**, simply choose one of the three options of **Preset**.
+:::
+
+
+### Number of keywords
+
+An integer specifying the number of keywords to extract from the user query. Defaults to 3. Please note that the number of extracted keywords depends on the LLM's capabilities and the token count in the user query, and may *not* match the integer you set.
+
+
+## Examples
+
+Explore our general-purpose chatbot agent template, where the **Keyword** component (component ID: **keywords**) is used to extract keywords from financial inputs for a potential stock search in the **akshare** component:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **General-purpose chatbot** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Keyword** component to display its **Configuration** window.
--- a/docs/guides/agent/agent_component_reference/message.mdx
+++ b/docs/guides/agent/agent_component_reference/message.mdx
@ -0,0 +1,30 @@
+---
+sidebar_position: 7
+slug: /message_component
+---
+
+# Message component
+
+A component that sends out a static message.
+
+---
+
+A **Message** component sends out a static message. If multiple messages are supplied, it randomly selects one to send.
+
+## Configurations
+
+### Messages
+
+The message to send out. 
+
+Click **+ Add message** to add message options. When multiple messages are supplied, the **Message** component randomly selects one to send.
+
+## Examples
+
+Explore our customer service agent template, where the **Message** component (component ID: **What else?**) randomly sends out a message to the user interface if the user inputs is related to personal contact information:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Customer service** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Message** component to display its **Configuration** window.
--- a/docs/guides/agent/agent_component_reference/note.mdx
+++ b/docs/guides/agent/agent_component_reference/note.mdx
@ -0,0 +1,22 @@
+---
+sidebar_position: 13
+slug: /note_component
+---
+
+# Note component
+
+The component that keeps design notes.
+
+---
+
+A **note** component allows you to keep design notes, including details about an agent, the output of specific components, the rationale of a particular design, or any information that may assist you, your users, or your fellow developers understand the agent.
+
+## Examples
+
+Explore our customer service agent template, which has five **Note** components:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Customer service** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **note** component to add or update notes.
--- a/docs/guides/agent/agent_component_reference/retrieval.mdx
+++ b/docs/guides/agent/agent_component_reference/retrieval.mdx
@ -0,0 +1,75 @@
+---
+sidebar_position: 4
+slug: /retrieval_component
+---
+
+# Retrieval component
+
+A component that retrieves information from specified datasets.
+
+## Scenarios
+
+A **Retrieval** component is essential in most RAG scenarios, where information is extracted from designated knowledge bases before being sent to the LLM for content generation.
+
+## Configurations
+
+Click on a **Retrieval** component to open its configuration window.
+
+### Input
+
+The **Retrieval** component relies on input variables to specify its data inputs (queries). Click **+ Add variable** in the **Input** section to add the desired input variables. There are two types of input variables: **Reference** and **Text**.
+
+- **Reference**: Uses a component's output or a user input as the data source. You are required to select from the dropdown menu:
+  - A component ID under **Component Output**, or 
+  - A global variable under **Begin input**, which is defined in the **Begin** component.
+- **Text**: Uses fixed text as the query. You are required to enter static text.
+
+### Similarity threshold
+
+RAGFlow employs a combination of weighted keyword similarity and weighted vector cosine similarity during retrieval. This parameter sets the threshold for similarities between the user query and chunks stored in the datasets. Any chunk with a similarity score below this threshold will be excluded from the results.
+
+Defaults to 0.2.
+
+### Keyword similarity weight
+
+This parameter sets the weight of keyword similarity in the combined similarity score. The total of the two weights must equal 1.0. Its default value is 0.7, which means the weight of vector similarity in the combined search is 1 - 0.7 = 0.3.
+
+### Top N
+
+This parameter selects the "Top N" chunks from retrieved ones and feed them to the LLM.
+
+Defaults to 8.
+
+
+### Rerank model
+
+*Optional*
+
+If a rerank model is selected, a combination of weighted keyword similarity and weighted reranking score will be used for retrieval.
+
+:::caution WARNING
+Using a rerank model will *significantly* increase the system's response time.
+:::
+
+
+### Knowledge bases 
+
+*Required*
+
+You are required to select the knowledge base(s) to retrieve data from.
+
+:::danger IMPORTANT 
+If you select multiple knowledge bases, you must ensure that the knowledge bases (datasets) you select use the same embedding model; otherwise, an error message would occur.
+:::
+
+
+
+## Examples
+
+Explore our customer service agent template, where the **Retrieval** component (component ID: **Search product info**) is used to search the dataset and send the Top N results to the LLM:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Customer service** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Retrieval** component to display its **Configuration** window.
--- a/docs/guides/agent/agent_component_reference/rewrite.mdx
+++ b/docs/guides/agent/agent_component_reference/rewrite.mdx
@ -0,0 +1,82 @@
+---
+sidebar_position: 8
+slug: /rewrite_component
+---
+
+# Rewrite component
+
+A component that rewrites a user query.
+
+---
+
+A **Rewrite** component uses a specified LLM to rewrite a user query from the **Interact** component, based on the context of previous dialogues.
+
+## Scenarios
+
+A **Rewrite** component is essential when you need to optimize a user query based on the context of previous conversations. It is usually the upstream component of a **Retrieval** component.
+
+:::tip NOTE
+See also the [Keyword](./keyword.mdx) component, a similar component used for multi-turn optimization.
+:::
+
+## Configurations
+
+:::tip NOTE
+The **Rewrite** component uses the user-agent interaction from the **Interact** component as its data input. Therefore, there is no need to specify its data inputs in the Configurations.
+:::
+
+### Model
+
+Click the dropdown menu of **Model** to show the model configuration window.
+
+- **Model**: The chat model to use.  
+  - Ensure you set the chat model correctly on the **Model providers** page.
+  - You can use different models for different components to increase flexibility or improve overall performance.
+- **Preset configurations**: A shortcut to **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty** settings, indicating the freedom level of the model. From **Improvise**, **Precise**, to **Balance**, each preset configuration corresponds to a unique combination of **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**.   
+  This parameter has three options:
+  - **Improvise**: Produces more creative responses.
+  - **Precise**: (Default) Produces more conservative responses.
+  - **Balance**: A middle ground between **Improvise** and **Precise**.
+- **Temperature**: The randomness level of the model's output.  
+  Defaults to 0.1.
+  - Lower values lead to more deterministic and predictable outputs.
+  - Higher values lead to more creative and varied outputs.
+  - A temperature of zero results in the same output for the same prompt.
+- **Top P**: Nucleus sampling.  
+  - Reduces the likelihood of generating repetitive or unnatural text by setting a threshold *P* and restricting the sampling to tokens with a cumulative probability exceeding *P*.
+  - Defaults to 0.3.
+- **Presence penalty**: Encourages the model to include a more diverse range of tokens in the response.  
+  - A higher **presence penalty** value results in the model being more likely to generate tokens not yet been included in the generated text.
+  - Defaults to 0.4.
+- **Frequency penalty**: Discourages the model from repeating the same words or phrases too frequently in the generated text.  
+  - A higher **frequency penalty** value results in the model being more conservative in its use of repeated tokens.
+  - Defaults to 0.7.
+- **Max tokens**: Sets the maximum length of the model's output, measured in the number of tokens.  
+  - Defaults to 512. 
+  - If disabled, you lift the maximum token limit, allowing the model to determine the number of tokens in its responses.
+
+:::tip NOTE
+- It is not necessary to stick with the same model for all components. If a specific model is not performing well for a particular task, consider using a different one.
+- If you are uncertain about the mechanism behind **Temperature**, **Top P**, **Presence penalty**, and **Frequency penalty**, simply choose one of the three options of **Preset configurations**.
+:::
+
+
+### Message window size
+
+An integer specifying the number of previous dialogue rounds to input into the LLM. For example, if it is set to 12, the tokens from the last 12 dialogue rounds will be fed to the LLM. This feature consumes additional tokens.
+
+Defaults to 1.
+
+:::tip IMPORTANT
+This feature is used for multi-turn dialogue *only*. If your **Categorize** component is not part of a multi-turn dialogue (i.e., it is not in a loop), leave this field as-is.
+:::
+
+## Examples
+
+Explore our customer service agent template, where the **Rewrite** component (component ID: **Refine Question**) is used to optimize a product-specific user query based on context of previous dialogues before passing it on to the **Retrieval** component.
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Customer service** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Rewrite** component to display its **Configuration** window.
--- a/docs/guides/agent/agent_component_reference/switch.mdx
+++ b/docs/guides/agent/agent_component_reference/switch.mdx
@ -0,0 +1,61 @@
+---
+sidebar_position: 9
+slug: /switch_component
+---
+
+# Switch component
+
+A component that evaluates whether specified conditions are met and directs the follow of execution accordingly. 
+
+---
+
+A **Switch** component evaluates conditions based on the output of specific components, directing the flow of execution accordingly to enable complex branching logic.
+
+## Scenarios
+
+A **Switch** component is essential for condition-based direction of execution flow. While it shares similarities with the [Categorize](./categorize.mdx) component, which is also used in multi-pronged strategies, the key distinction lies in their approach: the evaluation of the **Switch** component is rule-based, whereas the **Categorize** component involves AI and uses an LLM for decision-making. 
+
+## Configurations
+
+### Case n
+
+A **Switch** component must have at least one case, each with multiple specified conditions and *only one* downstream component. When multiple conditions are specified for a case, you must set the logical relationship between them to either AND or OR.
+
+#### Next step
+
+Specifies the downstream component of this case.
+
+- *Once you specify the ID of the downstream component, a link is established between this case and the corresponding component.*
+- *If you manually link this case to a downstream component on the canvas, the ID of that component is auto-populated.*
+
+#### Condition
+
+Evaluates whether the output of specific components meets certain conditions, with **Component ID**, **Operator**, and **Value** together forming a conditional expression.
+
+:::danger IMPORTANT
+When you have added multiple conditions for a specific case, a **Logical operator** field appears, requiring you to set the logical relationship between these conditions as either AND or OR.
+:::
+
+- **Component ID**: The ID of the corresponding component.
+- **Operator**: The operator required to form a conditional expression.
+  - Equals
+  - Not equal
+  - Greater than
+  - Greater equal
+  - Less than
+  - Less equal
+  - Contains 
+  - Not contains 
+  - Starts with
+  - Ends with
+  - Is empty
+  - Not empty
+- **Value**: A single value, which can be an integer, float, or string.  
+  - Delimiters, multiple values, or expressions are *not* supported.
+  - Strings need not be wrapped in `""` or `''`.
+
+### ELSE 
+
+**Required**. Specifies the downstream component if none of the conditions defined above are met.
+
+*Once you specify the ID of the downstream component, a link is established between ELSE and the corresponding component.*
--- a/docs/guides/agent/agent_component_reference/template.mdx
+++ b/docs/guides/agent/agent_component_reference/template.mdx
@ -0,0 +1,49 @@
+---
+sidebar_position: 11
+slug: /template_component
+---
+
+# Template component
+
+A component that formats user inputs or the outputs of other components.
+
+---
+
+A **Template** component acts as a content formatter. It is usually the upstream component of an **Interact** component.
+
+
+## Scenarios
+
+A **Template** component is useful for organizing various sources of data or information into specific formats.
+
+## Configurations
+
+### Content 
+
+Used together with Keys to organize various data or information sources into desired formats. Example:
+
+```text
+<h2>{subtitle}</h2>
+<div>{content}</div>
+```
+
+Where `{subtitle}` and `{content}` are defined keys.
+
+### Key 
+
+A **Template** component relies on keys (variables) to specify its data or information sources. Its immediate upstream component is *not* necessarily its input, and the arrows in the workflow indicate *only* the processing sequence.
+
+Values of keys are categorized into two groups:
+
+- **Component Output**: The value of the key should be a component ID.
+- **Begin Input**: The value of the key should be the name of a global variable defined in the **Begin** component.
+
+## Examples
+
+Explore our research report generator agent template, where the **Template** component (component ID: **Article**) organizes user input and the outputs of the **Sections** component into HTML format:
+
+1. Click the **Agent** tab at the top center of the page to access the **Agent** page.
+2. Click **+ Create agent** on the top right of the page to open the **agent template** page.
+3. On the **agent template** page, hover over the **Research report generator** card and click **Use this template**.
+4. Name your new agent and click **OK** to enter the workflow editor.
+5. Click on the **Template** component to display its **Configuration** window