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Fix typos (#4662)

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### What problem does this PR solve?

Fix typos in the documents

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com>
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2
CONTRIBUTING.md
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@ -1,6 +1,6 @@
# Contribution guidelines
This document offers guidlines and major considerations for submitting your contributions to RAGFlow.
This document offers guidelines and major considerations for submitting your contributions to RAGFlow.
- To report a bug, file a [GitHub issue](https://github.com/infiniflow/ragflow/issues/new/choose) with us.
- For further questions, you can explore existing discussions or initiate a new one in [Discussions](https://github.com/orgs/infiniflow/discussions).

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README.md
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@ -41,7 +41,7 @@
</h4>
<details open>
<summary></b>📕 Table of Contents</b></summary>
<summary><b>📕 Table of Contents</b></summary>
- 💡 [What is RAGFlow?](#-what-is-ragflow)
- 🎮 [Demo](#-demo)
@ -180,11 +180,11 @@ releases! 🌟
```
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
| ----------------- | --------------- | --------------------- | ------------------------ |
|-------------------|-----------------|-----------------------|--------------------------|
| v0.15.1 | &approx;9 | :heavy_check_mark: | Stable release |
| v0.15.1-slim | &approx;2 | ❌ | Stable release |
| v0.15.1-slim | &approx;2 | ❌ | Stable release |
| nightly | &approx;9 | :heavy_check_mark: | _Unstable_ nightly build |
| nightly-slim | &approx;2 | ❌ | _Unstable_ nightly build |
| nightly-slim | &approx;2 | ❌ | _Unstable_ nightly build |
4. Check the server status after having the server up and running:

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docs/configurations.md
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@ -138,7 +138,7 @@ If you cannot download the RAGFlow Docker image, try the following mirrors.
### MacOS
- `MACOS`
Optimizations for MacOS. It is disabled by default. You can uncomment this line if your OS is MacOS.
Optimizations for macOS. It is disabled by default. You can uncomment this line if your OS is macOS.
## Service configuration
@ -168,7 +168,7 @@ If you cannot download the RAGFlow Docker image, try the following mirrors.
The OAuth configuration for signing up or signing in to RAGFlow using a third-party account. It is disabled by default. To enable this feature, uncomment the corresponding lines in **service_conf.yaml.template**.
- `github`: The GitHub authentication settings for your application. Visit the [Github Developer Settings](https://github.com/settings/developers) page to obtain your client_id and secret_key.
- `github`: The GitHub authentication settings for your application. Visit the [GitHub Developer Settings](https://github.com/settings/developers) page to obtain your client_id and secret_key.
### `user_default_llm`

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docs/guides/accelerate_question_answering.mdx
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@ -38,7 +38,7 @@ Please note that some of your settings may consume a significant amount of time.
| Check LLM | Time to validate the specified LLM. |
| Create retriever | Time to create a chunk retriever. |
| Bind embedding | Time to initialize an embedding model instance. |
| Bind LLM | Time to intialize an LLM instance. |
| Bind LLM | Time to initialize an LLM instance. |
| Tune question | Time to optimize the user query using the context of the mult-turn conversation. |
| Bind reranker | Time to initialize an reranker model instance for chunk retrieval. |
| Generate keywords | Time to extract keywords from the user query. |

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docs/guides/agent/agent_introduction.md
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@ -43,27 +43,27 @@ We also provide templates catered to different business scenarios. You can eithe
![workflow_editor](https://github.com/user-attachments/assets/47b4d5ce-b35a-4d6b-b483-ba495a75a65d)
4. General speaking, now you can do the following:
3. General speaking, now you can do the following:
- Drag and drop a desired component to your workflow,
- Select the knowledge base to use,
- Update settings of specific components,
- Update LLM settings
- Sets the input and output for a specific component, and more.
5. Click **Save** to apply changes to your agent and **Run** to test it.
4. Click **Save** to apply changes to your agent and **Run** to test it.
## Components
Please review the flowing description of the RAG-specific components before you proceed:
| Component | Description |
| -------------- | ------------------------------------------------------------ |
| **Retrieval** | A component that retrieves information from specified knowledge bases and returns 'Empty response' if no information is found. Ensure the correct knowledge bases are selected. |
| **Generate** | A component that prompts the LLM to generate responses. You must ensure the prompt is set correctly. |
| **Interact** | A component that serves as the interface between human and the bot, receiving user inputs and displaying the agent's responses. |
| Component | Description |
|----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Retrieval** | A component that retrieves information from specified knowledge bases and returns 'Empty response' if no information is found. Ensure the correct knowledge bases are selected. |
| **Generate** | A component that prompts the LLM to generate responses. You must ensure the prompt is set correctly. |
| **Interact** | A component that serves as the interface between human and the bot, receiving user inputs and displaying the agent's responses. |
| **Categorize** | A component that uses the LLM to classify user inputs into predefined categories. Ensure you specify the name, description, and examples for each category, along with the corresponding next component. |
| **Message** | A component that sends out a static message. If multiple messages are supplied, it randomly selects one to send. Ensure its downstream is **Interact**, the interface component. |
| **Rewrite** | A component that rewrites a user query from the **Interact** component, based on the context of previous dialogues. |
| **Keyword** | A component that extracts keywords from a user query, with TopN specifying the number of keywords to extract. |
| **Message** | A component that sends out a static message. If multiple messages are supplied, it randomly selects one to send. Ensure its downstream is **Interact**, the interface component. |
| **Rewrite** | A component that rewrites a user query from the **Interact** component, based on the context of previous dialogues. |
| **Keyword** | A component that extracts keywords from a user query, with TopN specifying the number of keywords to extract. |
:::caution NOTE
@ -75,9 +75,9 @@ Please review the flowing description of the RAG-specific components before you
## Basic operations
| Operation | Description |
| ------------------------- | ------------------------------------------------------------ |
| Add a component | Drag and drop the desired component from the left panel onto the canvas. |
| Delete a component | On the canvas, hover over the three dots (...) of the component to display the delete option, then select it to remove the component. |
| Operation | Description |
|---------------------------|------------------------------------------------------------------------------------------------------------------------------------------|
| Add a component | Drag and drop the desired component from the left panel onto the canvas. |
| Delete a component | On the canvas, hover over the three dots (...) of the component to display the delete option, then select it to remove the component. |
| Copy a component | On the canvas, hover over the three dots (...) of the component to display the copy option, then select it to make a copy the component. |
| Update component settings | On the canvas, click the desired component to display the component settings. |
| Update component settings | On the canvas, click the desired component to display the component settings. |

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docs/guides/configure_knowledge_base.md
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@ -22,7 +22,7 @@ _Each time a knowledge base is created, a folder with the same name is generated
## Configure knowledge base
The following screen shot shows the configuration page of a knowledge base. A proper configuration of your knowledge base is crucial for future AI chats. For example, choosing the wrong embedding model or chunk method would cause unexpected semantic loss or mismatched answers in chats.
The following screenshot shows the configuration page of a knowledge base. A proper configuration of your knowledge base is crucial for future AI chats. For example, choosing the wrong embedding model or chunk method would cause unexpected semantic loss or mismatched answers in chats.
![knowledge base configuration](https://github.com/infiniflow/ragflow/assets/93570324/384c671a-8b9c-468c-b1c9-1401128a9b65)
@ -39,18 +39,18 @@ This section covers the following topics:
RAGFlow offers multiple chunking template to facilitate chunking files of different layouts and ensure semantic integrity. In **Chunk method**, you can choose the default template that suits the layouts and formats of your files. The following table shows the descriptions and the compatible file formats of each supported chunk template:
| **Template** | Description | File format |
| ------------ | ------------------------------------------------------------ | ---------------------------------------------------- |
| **Template** | Description | File format |
|--------------|-----------------------------------------------------------------------|------------------------------------------------------|
| General | Files are consecutively chunked based on a preset chunk token number. | DOCX, EXCEL, PPT, PDF, TXT, JPEG, JPG, PNG, TIF, GIF |
| Q&A | | EXCEL, CSV/TXT |
| Manual | | PDF |
| Table | | EXCEL, CSV/TXT |
| Paper | | PDF |
| Book | | DOCX, PDF, TXT |
| Laws | | DOCX, PDF, TXT |
| Presentation | | PDF, PPTX |
| Picture | | JPEG, JPG, PNG, TIF, GIF |
| One | The entire document is chunked as one. | DOCX, EXCEL, PDF, TXT |
| Q&A | | EXCEL, CSV/TXT |
| Manual | | PDF |
| Table | | EXCEL, CSV/TXT |
| Paper | | PDF |
| Book | | DOCX, PDF, TXT |
| Laws | | DOCX, PDF, TXT |
| Presentation | | PDF, PPTX |
| Picture | | JPEG, JPG, PNG, TIF, GIF |
| One | The entire document is chunked as one. | DOCX, EXCEL, PDF, TXT |
You can also change the chunk template for a particular file on the **Datasets** page.
@ -82,7 +82,7 @@ While uploading files directly to a knowledge base seems more convenient, we *hi
### Parse file
File parsing is a crucial topic in knowledge base configuration. The meaning of file parsing in RAGFlow is twofold: chunking files based on file layout and building embedding and full-text (keyword) indexes on these chunks. After having selected the chunk method and embedding model, you can start parsing an file:
File parsing is a crucial topic in knowledge base configuration. The meaning of file parsing in RAGFlow is twofold: chunking files based on file layout and building embedding and full-text (keyword) indexes on these chunks. After having selected the chunk method and embedding model, you can start parsing a file:
![parse file](https://github.com/infiniflow/ragflow/assets/93570324/5311f166-6426-447f-aa1f-bd488f1cfc7b)
@ -121,8 +121,8 @@ You can add keywords to a file chunk to increase its ranking for queries contain
RAGFlow uses multiple recall of both full-text search and vector search in its chats. Prior to setting up an AI chat, consider adjusting the following parameters to ensure that the intended information always turns up in answers:
- Similarity threshold: Chunks with similarities below the threshold will be filtered. Defaultly set to 0.2.
- Vector similarity weight: The percentage by which vector similarity contributes to the overall score. Defaultly set to 0.3.
- Similarity threshold: Chunks with similarities below the threshold will be filtered. By default, it is set to 0.2.
- Vector similarity weight: The percentage by which vector similarity contributes to the overall score. By default, it is set to 0.3.
![retrieval test](https://github.com/infiniflow/ragflow/assets/93570324/c03f06f6-f41f-4b20-a97e-ae405d3a950c)

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docs/guides/deploy_local_llm.mdx
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@ -39,7 +39,7 @@ time=2024-12-02T02:20:21.360Z level=INFO source=common.go:49 msg="Dynamic LLM li
Ensure ollama is listening on all IP address:
```bash
sudo ss -tunlp|grep 11434
sudo ss -tunlp | grep 11434
tcp LISTEN 0 4096 0.0.0.0:11434 0.0.0.0:* users:(("docker-proxy",pid=794507,fd=4))
tcp LISTEN 0 4096 [::]:11434 [::]:* users:(("docker-proxy",pid=794513,fd=4))
```

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docs/references/agent_component_reference/begin.mdx
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@ -52,7 +52,7 @@ As mentioned earlier, the **Begin** component is indispensable for an agent. Sti
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 **Interperter** card and click **Use this template**.
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.

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docs/references/agent_component_reference/iteration.mdx
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@ -26,7 +26,7 @@ An **Iteration** component is essential when a workflow loop is required and the
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 comonents encapsulated by the current **Iteration** components.
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)

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docs/references/faq.md
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@ -380,7 +380,7 @@ The status of a Docker container status does not necessarily reflect the status
### How to increase the length of RAGFlow responses?
1. Right click the desired dialog to display the **Chat Configuration** window.
1. Right-click the desired dialog to display the **Chat Configuration** window.
2. Switch to the **Model Setting** tab and adjust the **Max Tokens** slider to get the desired length.
3. Click **OK** to confirm your change.
@ -414,8 +414,8 @@ See [here](../guides/deploy_local_llm.mdx) for more information.
This error occurs because there are too many chunks matching your search criteria. Try reducing the **TopN** and increasing **Similarity threshold** to fix this issue:
1. Click **Chat** in the middle top of the page.
2. Right click the desired conversation > **Edit** > **Prompt Engine**
3. Reduce the **TopN** and/or raise **Silimarity threshold**.
2. Right-click the desired conversation > **Edit** > **Prompt Engine**
3. Reduce the **TopN** and/or raise **Similarity threshold**.
4. Click **OK** to confirm your changes.
![topn](https://github.com/infiniflow/ragflow/assets/93570324/7ec72ab3-0dd2-4cff-af44-e2663b67b2fc)

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docs/references/http_api_reference.md
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@ -1256,7 +1256,7 @@ curl --request POST \
- `"vector_similarity_weight"`: (*Body parameter*), `float`
The weight of vector cosine similarity. Defaults to `0.3`. If x represents the weight of vector cosine similarity, then (1 - x) is the term similarity weight.
- `"top_k"`: (*Body parameter*), `integer`
The number of chunks engaged in vector cosine computaton. Defaults to `1024`.
The number of chunks engaged in vector cosine computation. Defaults to `1024`.
- `"rerank_id"`: (*Body parameter*), `integer`
The ID of the rerank model.
- `"keyword"`: (*Body parameter*), `boolean`

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docs/references/python_api_reference.md
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@ -688,8 +688,8 @@ A `Chunk` object contains the following attributes:
from ragflow_sdk import RAGFlow
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
dataset = rag_object.list_datasets(id="123")
dtaset = dataset[0]
datasets = rag_object.list_datasets(id="123")
dataset = datasets[0]
doc = dataset.list_documents(id="wdfxb5t547d")
doc = doc[0]
chunk = doc.add_chunk(content="xxxxxxx")
@ -859,7 +859,7 @@ The weight of vector cosine similarity. Defaults to `0.3`. If x represents the v
##### top_k: `int`
The number of chunks engaged in vector cosine computaton. Defaults to `1024`.
The number of chunks engaged in vector cosine computation. Defaults to `1024`.
##### rerank_id: `str`
@ -1325,7 +1325,7 @@ In streaming mode, not all responses include a reference, as this depends on the
##### question: `str`, *Required*
The question to start an AI-powered conversation. Defalut to `""`
The question to start an AI-powered conversation. Default to `""`
##### stream: `bool`

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docs/release_notes.md
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@ -181,7 +181,7 @@ Released on September 30, 2024.
- Enables users to remove added LLM vendors.
- Adds support for **OpenTTS** and **SparkTTS** models.
- Implements an **Excel to HTML** toggle in the **General** chunk method, allowing users to parse a spreadsheet into either HTML tables or key-value pairs by row.
- Adds agent tools **YahooFance** and **Jin10**.
- Adds agent tools **YahooFinance** and **Jin10**.
- Adds an investment advisor agent template.
### Compatibility changes
@ -242,7 +242,7 @@ Released on August 6, 2024.
### New features
- Supports GraphRAG as a chunk method.
- Introduces Agent component **Keyword** and search tools, including **Baidu**, **DduckDuckGo**, **PubMed**, **Wikipedia**, **Bing**, and **Google**.
- Introduces Agent component **Keyword** and search tools, including **Baidu**, **DuckDuckGo**, **PubMed**, **Wikipedia**, **Bing**, and **Google**.
- Supports speech-to-text recognition for audio files.
- Supports model vendors **Gemini** and **Groq**.
- Supports inference frameworks, engines, and services including **LM studio**, **OpenRouter**, **LocalAI**, and **Nvidia API**.