Tool Components

Tool components connect external search, databases, HTTP APIs, email sending, document generation, financial queries, and web content extraction capabilities to Agents. When building Agents, first understand each tool's purpose and security boundaries.

In the tables below, No means manual input is optional; keep any default shown. Conditions are stated in the description. Replace bracketed placeholders with your own settings; Leave blank is an instruction, not text to enter.

Tool Selection Suggestions

Tool Category	Typical Components	Use Case
Web search	Tavily, Google, DuckDuckGo, SearXNG, Keenable, Sofya, Search1API	Retrieve web pages, news, public information, or content from specified sites.
Academic search	Google Scholar, ArXiv, PubMed, BGPT	Retrieve papers, medical literature, and research materials.
Data and financial queries	Execute SQL, Yahoo Finance, WenCai	Query databases, market data, or financial screening results.
Content output	Email, Document Generator	Send emails or generate downloadable documents.

Web Page and Information Retrieval

Tavily Search

Tavily is a web search service for LLMs. It is suitable for retrieving general web information, news, and content that needs to be limited to specific domains. Keep queries focused on a single topic and avoid overly long natural-language questions.

Parameter Description

Parameter	Type	Required	Default Value	Description
Query	string	Yes	Current user input	Search keywords.
Topic	string	No	general	Search type. Options are `general` or `news`.
Include Domains	array[string]	No	Empty list	Keep only results from these domains, such as `www.nasa.gov`.
Exclude Domains	array[string]	No	Empty list	Exclude results from these domains.
API Key	string	Conditional	Empty	Enter a Tavily key unless your administrator has configured one for the service.
Search Depth	string	No	basic	Search depth. Options are `basic` or `advanced`.
Max Results	integer	No	6	Maximum number of results.
Days	integer	No	14	Time range in days for news retrieval.
Include Answer	boolean	No	false	Whether to request Tavily's answer field.

Supported Parameter Values

Parameter	Supported Value	Description
Topic	general	General web search.
Topic	news	News retrieval.
Search Depth	basic	Basic search.
Search Depth	advanced	Deep search.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow knowledge retrieval
Topic	general
Search Depth	basic
Max Results	6
API Key	`<Tavily API key>`

Output Result

The output usually contains search result titles, links, and snippets. formalized_content is commonly passed to the Agent to generate answers, while JSON is used by subsequent nodes to read structured fields.

For a simple search workflow, connect Begin → Tavily Search → Agent → Message. Use sys.query as Query, insert Tavily Search's formalized_content into the Agent's user prompt, and insert the Agent's content into Message. Ask a focused question and check that the search output contains relevant sources before assessing the final answer.

Tavily Search

Tavily Extract

Tavily Extract reads the body content of one or more known URLs. A common workflow is to use Tavily Search to obtain links, then pass those links to this component to extract page content.

Parameter Description

Parameter	Type	Required	Default Value	Description
URLs	array[string]	Yes	Empty list	URL list to extract. If input is a string, it is split by English commas.
Extract Depth	string	No	basic	`advanced` can extract more tables and embedded content, with higher cost and latency.
Format	string	No	markdown	Extraction result format. Options are `markdown` or `text`.
API Key	string	Conditional	Empty	Enter a Tavily key unless your administrator has configured one for the service.

Supported Parameter Values

Parameter	Supported Value	Description
Extract Depth	basic	Basic extraction.
Extract Depth	advanced	Extracts more tables and embedded content, with higher latency and cost.
Format	markdown	Markdown format.
Format	text	Plain text format.

Configuration Example

Configuration Item	Example Value
URLs	`["https://www.ragflow.io/docs/dev/"]`
Extract Depth	basic
Format	markdown
API Key	`<your API key>`

Output Result

The output json contains the extracted page results. Select the required page content from json and pass it to the Agent prompt.

Tavily Extract

Querit Search

Querit Search finds web pages for a query. Configure API Key and Query, then adjust these options as needed:

Setting	Description
Result count	Maximum number of documents. Defaults to `10`.
Chunks per document	Number of content chunks requested for each document.
Sites to include / Sites to exclude	Limit results to selected sites or exclude them.
Time range	Restrict results by date.
Countries to include / Languages to include	Restrict results by country or language.

For example, set Query to RAGFlow knowledge retrieval, Result count to 5, and leave the optional filters empty. If the component API key is empty, the server uses QUERIT_API_KEY when configured.

The outputs are formalized_content for downstream prompts and json for the raw response.

Querit Contents

Querit Contents retrieves content from known URLs. Pass links from a search component or enter them directly.

Setting	Description
API Key	Querit API key. Uses the server's `QUERIT_API_KEY` if empty.
URLs	One to ten absolute HTTP or HTTPS URLs.
Format	`markdown` (default), `text`, or `html`.
Crawl timeout	Per-page timeout in seconds. Defaults to `10`.
Include page metadata	Request additional page metadata.

For example, use https://www.ragflow.io as the URL and keep Format set to markdown. The output is json, containing the raw response. Select the required content from that response before passing it to an Agent.

Google

Google Search obtains Google organic search results through SerpApi. It is suitable for web retrieval that requires country and language targeting.

Parameter Description

Parameter	Type	Required	Default Value	Description
Query	string	Yes	Current user input	Search keywords.
Start	integer	No	0	Result offset. In document semantics, this is the pagination starting point.
Num	integer	No	6	Number of requested results.
API Key	string	Yes	Empty	SerpApi API key.
Country	string	No	cn	Google region code, such as `cn`, `us`, or `jp`.
Language	string	No	en	Google interface/result language code, such as `zh-CN` or `en`.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow official documentation
Start	0
Num	6
API Key	`<your API key>`
Country	cn
Language	en

Output Result

The output contains search result titles, links, and summaries. The organized text can be passed to the Agent for summarization, or subsequent nodes can read the link list from JSON.

Google Search

DuckDuckGo

DuckDuckGo is a privacy-focused search engine component. It does not require a separate API key and can be used for general web and news retrieval.

Parameter Description

Parameter	Type	Required	Default Value	Description
Query	string	Yes	Current user input	Search keywords.
Channel	string	No	text	Select `text` for web pages or `news` for news results.
Top N	integer	No	10	Maximum number of returned results.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow open source
Channel	text
Top N	10

Output Result

The output contains titles, links, and summaries returned by DuckDuckGo. It can be used for web material summarization, news lead organization, or subsequent page extraction.

DuckDuckGo results displayed in Message

SearXNG

SearXNG is a self-hostable privacy-oriented meta-search engine. This component calls a user-provided SearXNG instance and is suitable for scenarios that need control over retrieval sources or internal search deployment.

Parameter Description

Parameter	Type	Required	Default Value	Description
Query	string	Yes	Current user input	Search keywords.
SearXNG URL	string	Yes	Empty	SearXNG instance base URL, such as `https://searxng.example.com`.
Top N	integer	No	10	Maximum number of results.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow documentation
SearXNG URL	`https://<your-searxng-host>`
Top N	10

Output Result

The output contains titles, links, summaries, and source information returned by SearXNG. Before use, configure a reachable SearXNG service address and pass the system security checks.

Keenable

Keenable is a web search API for AI Agents. By default, it supports a public free path without a key. After configuring a key, you can increase the limit and enable low-latency realtime mode.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Search keywords.
site	string	No	Empty	Limit results to a single domain, such as `techcrunch.com`.
api_key	string	Conditional	Empty	Optional in pro mode; required in realtime mode.
mode	string	No	pro	`pro` for deeper retrieval or `realtime` for low latency. `realtime` requires an API key.
top_n	integer	No	10	Maximum number of results.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow Agent workflow
Site	github.com
API Key	Leave blank for pro mode
Mode	pro
Top N	10

Output Result

The output contains search entries, summaries, and links returned by Keenable. It can be summarized by the Agent or passed to subsequent retrieval or extraction nodes. Do not set realtime for keyless trial runs.

Keenable Search

Sofya

Sofya is a web search API for AI Agents. It returns the text of the result pages, not only a snippet, so results can be used without a separate fetch step. An API key is required and can be created at sofya.co.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Search keywords.
topic	string	No	general	`general` for web search or `news` for current events.
freshness	string	No	any	Limit results by recency: `day`, `week`, `month`, `year`, or `any`.
api_key	string	Yes	Empty	Sofya API key.
search_depth	string	No	basic	`basic` returns the content of the result pages. `snippets` returns search snippets only, which is faster and cheaper.
top_n	integer	No	10	Maximum number of results, up to 20.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow release
API Key	`<your-sofya-api-key>`
Search Depth	basic
Top N	10

Output Result

The output contains titles, links, and page content returned by Sofya. Results whose page could not be read fall back to the search snippet. It can be summarized by the Agent or passed to subsequent nodes.

Search1API

Search1API searches the web or the news through one API and lets you choose the search service, such as Google, Bing, Baidu, GitHub, arXiv, Reddit, YouTube, Hacker News, or Reuters. When it is added to an Agent as a tool, the node settings are only defaults: the Agent can pick the channel and the search service for each call, for example GitHub for code questions or Reuters for news. An API key is required and can be created at app.s1.dev. See the Search1API documentation for details.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Search keywords.
channel	string	No	general	`general` for web search or `news` for news search. The Agent can override the node value.
search_service	string	No	google	The search service to query. The Agent can override the node value with any service the channel supports.
time_range	string	No	any	Limit results by recency: `day`, `week`, `month`, `year`, or `any`.
api_key	string	Yes	Empty	Search1API API key.
top_n	integer	No	10	Maximum number of results, up to 50.

Supported Parameter Values

Channel	Supported Search Services
general	google, bing, bingcn, duckduckgo, yahoo, yandex, youtube, x, reddit, github, arxiv, wechat, bilibili, imdb, wikipedia, baidu, 360, quark
news	google, bing, duckduckgo, yahoo, hackernews, reuters

If the Agent switches to a channel that does not offer the node's search service, the search uses Search1API's default service for that channel.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow release
API Key	`<your-search1api-api-key>`
Channel	general
Search Service	google
Top N	10

Output Result

The output contains titles, links, and snippets returned by Search1API. formalized_content is commonly used as Agent context, while json preserves the raw result list.

Search1API Crawl

Search1API Crawl reads one web page and returns its title and full content. A common workflow is to use Search1API to find links, then let the Agent read the most relevant page with this component. It uses the same API key as Search1API.

Parameter Description

Field	Type	Required	Default Value	Description
url	string	Yes	Empty	The absolute HTTP or HTTPS URL of the page to read. As an Agent tool, the Agent supplies the URL.
api_key	string	Yes	Empty	Search1API API key.

Configuration Example

Configuration Item	Example Value
URL	`https://ragflow.io/docs/dev/`
API Key	`<your-search1api-api-key>`

Output Result

json contains the page title, link, content, and any metadata returned by Search1API.

Wikipedia

The Wikipedia component searches encyclopedia entries and extracts entry summaries. It is suitable for querying clear entities, concepts, and historical events. Query terms should be as close as possible to the entry title.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Specific entry topic or keyword.
top_n	integer	No	10	Maximum number of search entries.
language	string	No	en	Wikipedia language code, such as `zh`, `en`, or `ja`.

Configuration Example

Configuration Item	Example Value
Query	culture
Top N	10
Language	en

Output Result

The output contains the titles, summaries, and page links of matching entries. It is suitable for generating concept explanations or background descriptions with the Agent.

Wikipedia

GitHub

The GitHub component searches repositories through the GitHub Repository Search API and sorts by popularity by default. It is suitable for finding open-source projects, reference implementations, and technology ecosystems.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	GitHub repository search syntax or keywords.
top_n	integer	No	10	Maximum number of returned repositories.

Configuration Example

Configuration Item	Example Value
Query	RAGFlow
Top N	10

Output Result

The output contains matching repository names, links, descriptions, and star counts.

GitHub repository search component

Academic Literature Retrieval

Google Scholar

Google Scholar is used to retrieve papers, dissertations, books, abstracts, and other academic materials. It is suitable for preliminary literature discovery before a research review, but should not replace verification of original texts and citation information.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Paper topic or keyword.
top_n	integer	No	12	Maximum number of papers.
sort_by	string	No	relevance	Sorting method: `date` or `relevance`.
year_low	integer/null	No	Unset	Earliest publication year.
year_high	integer/null	No	Unset	Latest publication year.
patents	boolean	No	true	Whether to include patents.

Configuration Example

Configuration Item	Example Value
Query	retrieval augmented generation evaluation
Top N	12
Sort By	relevance
Year Low	Leave blank
Year High	Leave blank
Patents	true

Output Result

The output contains academic retrieval entries such as paper titles, authors, abstracts, source links, and citation information. It is suitable for literature reviews or research lead organization.

Google Scholar

ArXiv

ArXiv is used to retrieve open preprints across fields such as computer science, mathematics, physics, and quantitative finance. ArXiv papers may not have undergone peer review, so mark their preprint nature when using the results.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Retrieval keywords.
top_n	integer	No	12	Maximum number of returned papers.
sort_by	string	No	submittedDate	Sorting method: `submittedDate`, `lastUpdatedDate`, or `relevance`.

Configuration Example

Configuration Item	Example Value
Query	large language model agents
Top N	12
Sort By	submittedDate

Output Result

The output contains paper titles, authors, abstracts, publication times, categories, and paper links. It can be used by the Agent to generate paper summaries or research comparisons.

PubMed

PubMed is used to retrieve life science and biomedical literature. The component queries through NCBI E-utilities and returns titles, authors, journals, DOIs, abstracts, and other information.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	PubMed search term. Medical subject headings or Boolean retrieval expressions are supported.
top_n	integer	No	12	Maximum number of papers.
email	string	No	`A.N.Other@example.com`	NCBI Entrez contact email. Replace it with a real maintainer email in production.

Configuration Example

Configuration Item	Example Value
Query	COVID-19 vaccine effectiveness
Top N	12
Email	`A.N.Other@example.com`

Output Result

The output contains medical literature titles, authors, journals, abstracts, publication dates, and PubMed links. It is suitable for medical literature retrieval scenarios.

PubMed

BGPT

BGPT retrieves scientific papers and returns structured evidence, including research methods, sample sizes, results, limitations, conflicts of interest, data availability, and falsifiability tips. It is suitable for evaluating scientific claims, not only for finding paper abstracts.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Natural-language scientific retrieval question.
top_n	integer	No	10	Maximum number of results.
api_key	string	No	Empty	Optional API key. If not configured, the public service path is used.
days_back	integer/null	No	Unset	Optional. Limits retrieval to content from the most recent number of days.

Configuration Example

Configuration Item	Example Value
Query	Does sleep deprivation impair working memory in adults?
Top N	10
API Key	Leave blank (optional)
Days Back	Leave blank

Output Result

The output contains biomedical knowledge retrieval results and summaries, which can be further summarized, compared, or used to generate research explanations by subsequent Agents.

BGPT

Data and Financial Queries

Execute SQL

Execute SQL connects to an external database and executes SQL statements. The result is formatted as text or table content.

Use a database address that the RAGFlow server can reach. If the connection is rejected, check the address, credentials, and network access settings.

Parameter Description

Field	Type	Required	Default Value	Description
sql	string	Yes	`{sys.query}`	SQL to execute. Canvas variables can be included.
db_type	string	Yes	mysql	Supports `mysql`, `postgres`, `mariadb`, `mssql`, `trino`, and `oceanbase`.
database	string	Yes	Empty	Database name. Trino uses `catalog.schema` or `catalog`.
username	string	Yes	Empty	Database account.
host	string	Yes	Empty	Database address reachable from the RAGFlow server.
port	integer	Yes	3306	Database port.
password	string	Conditionally required	Empty	Database password. It can be empty for Trino.
max_records	integer	No	1024	Maximum number of records returned per statement.

Supported Values

Parameter	Supported Value	Description
Database Type	mysql	MySQL
Database Type	postgres	PostgreSQL
Database Type	mariadb	MariaDB
Database Type	mssql	Microsoft SQL Server
Database Type	trino	Trino
Database Type	oceanbase	OceanBase

Configuration Example

Ask your administrator to prepare a MySQL test database named demo_sql with a products table containing id, name, and stock. Use two sample rows: (1, Model A, 12) and (2, Model B, 0). The account needs permission to read this table.

Configuration Item	Example Value
SQL	`SELECT id, name FROM products WHERE stock > 0 ORDER BY id;`
Database Type	mysql
Database	demo_sql
Username	ragflow_reader
Host	`<host>`
Port	3306
Password	`<read-only database account password>`
Max Records	10

Replace <host>, the username, and the password with your test database connection details; change demo_sql if your database has a different name.

Connect Begin → Execute SQL → Message. Configure Execute SQL as above, then insert its formalized_content output into Message through the variable selector. Save and click Run. The result should contain only 1, Model A, because Model B has no stock.

Output Result

The output contains SQL execution results, field names, and record content. You can pass formatted text to the Agent for explanation, or let subsequent nodes read structured results.

Execute SQL

Yahoo Finance

The Yahoo Finance component queries stock quotes, company profiles, historical market data, financial statements, and news. It returns the selected content as a Markdown report.

Parameter Description

Field	Type	Required	Default Value	Description
stock_code	string	Yes	`{sys.query}`	Stock code or company name. Use exchange-standard codes when possible.
info	boolean	No	true	Output company and quote information.
history	boolean	No	false	Output historical market data.
count	boolean	No	false	Include share-count statistics.
financials	boolean	No	false	Output earnings dates and other financial calendar events returned by Yahoo Finance.
income_stmt	boolean	No	false	Include annual and quarterly income statements.
balance_sheet	boolean	No	false	Output balance sheet and quarterly balance sheet.
cash_flow_statement	boolean	No	false	Output cash flow statement and quarterly cash flow statement.
news	boolean	No	true	Output related news.

Configuration Example

Configuration Item	Example Value
Stock Code	AAPL
Info	true
History	false
Count	false
Financials	false
Income Statement	false
Balance Sheet	false
Cash Flow Statement	false
News	true

Output Result

The output report is a Markdown report containing the selected financial information. Insert report into a downstream Agent prompt to generate a market overview or explain indicators.

WenCai

WenCai is used to screen financial data such as stocks, indices, funds, Hong Kong stocks, U.S. stocks, futures, and other instruments based on natural-language conditions.

Parameter Description

Field	Type	Required	Default Value	Description
query	string	Yes	`{sys.query}`	Stock selection or financial condition, such as "A-shares with P/E ratio below 20".
top_n	integer	No	20	Maximum number of results.
query_type	string	No	stock	Supports `stock`, `zhishu`, `fund`, `hkstock`, `usstock`, `threeboard`, `conbond`, `insurance`, `futures`, `lccp`, and `foreign_exchange`.

Supported Query Types

Type	Description
stock	A-share stocks
zhishu	Indices
fund	Funds
hkstock	Hong Kong stocks
usstock	U.S. stocks
threeboard	NEEQ
conbond	Convertible bonds
insurance	Insurance
futures	Futures
lccp	Wealth management products
foreign_exchange	Foreign exchange

Configuration Example

Configuration Item	Example Value
Query	A-shares with P/E ratio below 20 and net profit YoY growth above 20%
Top N	10
Query Type	stock

Output Result

The output contains a financial data list that matches the natural-language screening condition. It can be used for displaying stock selection results, subsequent filtering, or Agent explanation.

NOTE

Configure the WenCai query service before using this component.

Communication and External Systems

Email

The Email component sends HTML emails through SMTP. Configure the recipients, CC recipients, subject, and email body in the component.

Parameter Description

Field	Type	Required	Default Value	Description
to_email	string	Yes	`{sys.query}`	Recipient email address.
cc_email	string	No	Empty	CC email addresses. Separate multiple addresses with English commas.
content	string	No	Empty	Email body, sent as HTML content.
subject	string	No	Empty	Email subject.
smtp_server	string	Yes	Empty	SMTP server address.
smtp_port	integer	No	465	SMTP port. Port 465 uses SSL, and other ports use STARTTLS.
email	string	Yes	Empty	Sender email address.
smtp_username	string	No	Empty	SMTP login account. If empty, the sender email address is used.
password	string	Yes	Empty	SMTP authorization code or password.
sender_name	string	No	Empty	Sender display name.

NOTE

Although some SMTP fields are displayed as optional in the UI, a valid SMTP service address, sender account, and authentication information must be provided before sending email.

Configuration Example

Configuration Item	Example Value
To Email	receiver@example.com
CC Email	Leave blank (optional)
Content	`<p>This is a test email sent by RAGFlow.</p>`
Subject	RAGFlow email tool test
SMTP Server	`<your SMTP server>`
SMTP Port	465
Email	`<your sender email>`
SMTP Username	Leave blank to use the sender email
Password	`<your SMTP authorization code or password>`
Sender Name	Leave blank (optional)

Output Result

The output contains sending status and error information. success being true means the email was sent successfully. If sending fails, check the SMTP address, account, password, and recipient.

MCP tools

MCP connects an Agent to tools provided by a configured MCP server. Add MCP tools through the Agent component's tool selector; they are not a standalone HTTP Request node.

Open User settings > MCP > Add MCP, enter the server URL and authentication, refresh Tools available, and click Save. See Connect an external MCP server.
Open the Agent component, use its tool selector to choose the server, and select the tools to expose.
Describe when to use those tools in System prompt, then run a small test task.

The running user must have permission to use the selected server. Tool arguments and results follow each server's tool schema; downstream Agent output remains the Agent's response. If a call fails, check server access, authentication, and required arguments.

HTTP Request

The HTTP Request component calls external HTTP APIs, allowing business systems, third-party services, or self-built APIs to be connected to Agent workflows.

Configuration

Setting	Description
Url	API address. Insert canvas variables as needed.
Method	Select GET, POST, or PUT.
Timeout	Request timeout in seconds. Defaults to `60`.
Headers	Request headers as a JSON object.
Proxy	Optional proxy address.
Clean HTML	Remove HTML markup from the response.
Parameter	Click `+` to add request parameters and set their values using constants or variables.

Configuration Example

Setting	Example Value
Url	`https://httpbin.org/get`
Method	GET
Timeout	60
Headers	`{}`
Parameter	`topic` = `ragflow`

Output Result

The result output contains the response body as text. Pass the text to an Agent for summarization, or parse a JSON response body before accessing its fields.

If a URL is rejected, the output can contain _ERROR with a null result. Check for errors before consuming the response. Other request failures can surface as component execution errors.

Example: request, response, and next step

Connect Begin → HTTP Request → Message. Set URL to https://httpbin.org/get, Method to GET, and add a parameter named topic with the fixed value ragflow.

If the service is accessible from the server, its JSON response body includes:

{"args": {"topic": "ragflow"}}

The component returns that body as the string result. In Message, insert HTTP Request's result to display it. To use only args.topic, first parse result in a Code component. If the test returns _ERROR, resolve that failure before consuming the result.

HTTP Request

Content Generation and Automation

Document Generator (DocGenerator)

The Document Generator component outputs Markdown content as PDF, DOCX, TXT, Markdown, or HTML files, and stores the generated files in Agent attachment storage.

Parameter Description

Field	Type	Required	Default Value	Description
content	string	Yes	Empty	Markdown content to generate. Upstream outputs can be referenced.
output_format	string	Yes	pdf	Output format: `pdf`, `docx`, `txt`, `markdown`, or `html`.
filename	string	No	Empty	File name. If empty, it is generated automatically, and illegal file name characters are cleaned.
header_text	string	No	Empty	Header text. Applies to PDF/DOCX.
footer_text	string	No	Empty	Footer text. Applies to PDF/DOCX.
watermark_text	string	No	Empty	Watermark text. Available for PDF, DOCX, and HTML.
add_page_numbers	boolean	No	true	Whether to add page numbers. Mainly used for PDF/DOCX.
add_timestamp	boolean	No	true	Whether to add generation time.
font_size	number	No	12	Font size, which must be greater than or equal to 12.

Configuration Example

Configuration Item	Example Value
Content	`# RAGFlow Agent`
Output Format	pdf
Filename	ragflow-agent-test.pdf
Header Text	RAGFlow
Footer Text	Internal Test
Watermark Text	DRAFT
Add Page Numbers	true
Add Timestamp	true
Font Size	12

Output Result

Use download to display the generated file in a Message. The other outputs identify the file and describe its name, type, and size.

Example: generate a downloadable PDF

Connect Begin → Document Generator → Message. Begin needs no additional inputs.
In Document Generator, set Content to # Sample report, Output Format to PDF, and Filename to sample-report.pdf. Keep the other settings at their defaults.
In Message, open the variable selector and insert Document Generator's download output.
Save and click Run. The conversation should show a downloadable file named sample-report.pdf; open it to check that it contains the heading Sample report.