Remove auto-rag.com URL usage (#1116)

vkehfdl1 · web-flow · commit 9625ddfa53f4 · 2025-06-17T10:32:07.000+09:00
* Remove auto-rag.com URL usage

No longer have the URL

* change all link to github.io URL
diff --git a/CNAME b/CNAME
@@ -1 +1 @@
-docs.auto-rag.com
+marker-inc-korea.github.io/AutoRAG/
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -34,7 +34,7 @@ The `AutoRAG` repo have a standard python library structure.
 
 You can find the core part of the library in `autorag` folder.
 You can find the test codes of the `AutoRAG` at the `tests` folder.
-Plus, you can find the [AutoRAG docs](https://docs.auto-rag.com) at the `docs` folder.
+Plus, you can find the [AutoRAG docs](https://marker-inc-korea.github.io/AutoRAG/) at the `docs` folder.
 
 For resources, you can find sample config YAML files at `sample_config` folder.
 Plus, you can find sample dataset download script from `sample_dataset` folder.
diff --git a/README.md b/README.md
@@ -24,9 +24,7 @@ and find the best RAG pipeline for your own use-case.
 AutoRAG supports a simple way to evaluate many RAG module combinations.
 Try now and find the best RAG pipeline for your own use-case.
 
-Explore our 📖 [Document](https://docs.auto-rag.com)!!
-
-Plus, join our 📞 [Discord](https://discord.gg/P4DYXfmSAs) Community.
+Explore our 📖 [Document](https://marker-inc-korea.github.io/AutoRAG/)!!
 
 ---
 
@@ -41,7 +39,7 @@ Your Optimized RAG pipeline is just a few clicks away.
 |:-----------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------:|
 | ![Image](https://github.com/user-attachments/assets/87289d84-ff65-4810-bc41-3f30b36b7ddf) | ![Image](https://github.com/user-attachments/assets/dbe0a49b-ebf2-4c9c-b17d-1be1c2cd1060) | ![Image](https://github.com/user-attachments/assets/d8a50512-3299-4b68-b48e-e2f49d688f01) |
 
-Click the docs to use the AutoRAG GUI beta version! [AutoRAG GUI Docs](https://docs.auto-rag.com/gui/gui.html).
+Click the docs to use the AutoRAG GUI beta version! [AutoRAG GUI Docs](https://marker-inc-korea.github.io/AutoRAG/gui/gui.html).
 
 ### GUI Installation
 
@@ -292,8 +290,8 @@ First, you need to set the config YAML file for your RAG optimization.
 We highly recommend using pre-made config YAML files for starter.
 
 - [Get Sample YAML](autorag/sample_config/rag)
-    - [Sample YAML Guide](https://docs.auto-rag.com/optimization/sample_config.html)
-- [Make Custom YAML Guide](https://docs.auto-rag.com/optimization/custom_config.html)
+    - [Sample YAML Guide](https://marker-inc-korea.github.io/AutoRAG/optimization/sample_config.html)
+- [Make Custom YAML Guide](https://marker-inc-korea.github.io/AutoRAG/optimization/custom_config.html)
 
 Here is an example of the config YAML file to use `retrieval`, `prompt_maker`, and `generator` nodes.
 
@@ -358,7 +356,7 @@ At the trial folder named to numbers (like 0),
 you can check `summary.csv` file that summarizes the evaluation results and the best RAG pipeline for your data.
 
 For more details, you can check out how the folder structure looks like
-at [here](https://docs.auto-rag.com/optimization/folder_structure.html).
+at [here](https://marker-inc-korea.github.io/AutoRAG/optimization/folder_structure.html).
 
 ### 3. Run Dashboard
 
@@ -407,7 +405,7 @@ autorag run_api --trial_dir your/path/to/trial_dir --host 0.0.0.0 --port 8000
 ```
 
 The cli command uses extracted config YAML file. If you want to know it more, check
-out [here](https://docs.auto-rag.com/tutorial.html#extract-pipeline-and-evaluate-test-dataset).
+out [here](https://marker-inc-korea.github.io/AutoRAG/tutorial.html#extract-pipeline-and-evaluate-test-dataset).
 
 ### 4-3. Run as a Web Interface
 
@@ -551,7 +549,7 @@ We are developing AutoRAG as open-source.
 
 So this project welcomes contributions and suggestions. Feel free to contribute to this project.
 
-Plus, check out our detailed documentation at [here](https://docs.auto-rag.com/index.html).
+Plus, check out our detailed documentation at [here](https://marker-inc-korea.github.io/AutoRAG/index.html).
 
 ## Citation
 
diff --git a/autorag/autorag/data/legacy/qacreation/base.py b/autorag/autorag/data/legacy/qacreation/base.py
@@ -130,7 +130,7 @@ def make_qa_with_existing_qa(
 	:param output_filepath: Optional filepath to save the parquet file.
 	:param embedding_model: The embedding model to use for vectorization.
 	    You can add your own embedding model in the autorag.embedding_models.
-	    Please refer to how to add an embedding model in this doc: https://docs.auto-rag.com/local_model.html
+	    Please refer to how to add an embedding model in this doc: https://marker-inc-korea.github.io/AutoRAG/local_model.html
 	    The default is 'openai_embed_3_large'.
 	:param collection: The chromadb collection to use for vector DB.
 	    You can make any chromadb collection and use it here.
diff --git a/autorag/autorag/deploy/api.py b/autorag/autorag/deploy/api.py
@@ -231,7 +231,7 @@ def run_api_server(
 	):
 		"""
 		Run the pipeline as an api server.
-		Here is api endpoint documentation => https://docs.auto-rag.com/deploy/api_endpoint.html
+		Here is api endpoint documentation => https://marker-inc-korea.github.io/AutoRAG/deploy/api_endpoint.html
 
 		:param host: The host of the api server.
 		:param port: The port of the api server.
diff --git a/docs/CNAME b/docs/CNAME
@@ -1 +1 @@
-docs.auto-rag.com
+marker-inc-korea.github.io/AutoRAG/
diff --git a/docs/source/CNAME b/docs/source/CNAME
@@ -1 +1 @@
-docs.auto-rag.com
+marker-inc-korea.github.io/AutoRAG/
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -45,4 +45,4 @@
 
 html_theme = "furo"
 html_static_path = ["_static"]
-html_baseurl = "https://docs.auto-rag.com/"
+html_baseurl = "https://marker-inc-korea.github.io/AutoRAG/"
diff --git a/docs/source/evaluate_metrics/retrieval.md b/docs/source/evaluate_metrics/retrieval.md
@@ -24,7 +24,7 @@ So, if we labeled the retrieval_result as ‘1’ for a correct answer and ‘0
 be `[1, 0, 1, 0]`.
 
 For more information, please refer to the
-following [Dataset Format Docs](https://docs.auto-rag.com/data_creation/data_format.html).
+following [Dataset Format Docs](https://marker-inc-korea.github.io/AutoRAG/data_creation/data_format.html).
 
 In the Apply ‘✅Basic Examples’ below, we'll use the following sample gt and result.
 Hopefully you remember them well.
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -45,25 +45,25 @@ AutoRAG GUI is a web-based tool for running AutoRAG experiments.
 If you are not familiar with command-line interface and YAML file configuration,
 you can use AutoRAG GUI to run AutoRAG experiments.
 
-Check out `AutoRAG GUI Docs <https://docs.auto-rag.com/gui/gui.html>`__ for more information.
+Check out `AutoRAG GUI Docs <https://marker-inc-korea.github.io/AutoRAG/gui/gui.html>`__ for more information.
 
 🏃‍♂️ Getting Started
 ************************************
 
 ``pip install AutoRAG``
 
 
-In our documentation, we will guide you through the process of `installation <https://docs.auto-rag.com/install.html>`__ and `tutorial <https://docs.auto-rag.com/tutorial.html>`__ for AutoRAG starter.
-After you find your first RAG pipeline with AutoRAG, you can learn how to read result files at `here <https://docs.auto-rag.com/structure.html>`__.
+In our documentation, we will guide you through the process of `installation <https://marker-inc-korea.github.io/AutoRAG/install.html>`__ and `tutorial <https://marker-inc-korea.github.io/AutoRAG/tutorial.html>`__ for AutoRAG starter.
+After you find your first RAG pipeline with AutoRAG, you can learn how to read result files at `here <https://marker-inc-korea.github.io/AutoRAG/structure.html>`__.
 
 And do you want to get the ultimate performance RAG pipeline?
-Learn how make great evaluation dataset with your own raw documents at `here <https://docs.auto-rag.com/data_creation/tutorial.html>`__.
+Learn how make great evaluation dataset with your own raw documents at `here <https://marker-inc-korea.github.io/AutoRAG/data_creation/tutorial.html>`__.
 
-Also, you can learn how to set various experiment configurations at `optimization <https://docs.auto-rag.com/optimization/optimization.html>`__ guide.
+Also, you can learn how to set various experiment configurations at `optimization <https://marker-inc-korea.github.io/AutoRAG/optimization/optimization.html>`__ guide.
 
-Of course, you can use your own local LLM or embedding model with AutoRAG. Go to `here <https://docs.auto-rag.com/local_model.html>`__ to learn how to use your own model with AutoRAG.
+Of course, you can use your own local LLM or embedding model with AutoRAG. Go to `here <https://marker-inc-korea.github.io/AutoRAG/local_model.html>`__ to learn how to use your own model with AutoRAG.
 
-If you face any trouble? Check out our `troubleshooting <https://docs.auto-rag.com/troubleshooting.html>`__ guide.
+If you face any trouble? Check out our `troubleshooting <https://marker-inc-korea.github.io/AutoRAG/troubleshooting.html>`__ guide.
 Also, feel free to ask your question at our `github issue <https://github.com/Marker-Inc-Korea/AutoRAG/issues>`__ or `Discord <https://discord.gg/P4DYXfmSAs>`__ channel.
 
 🗣️ Talk with Founders
@@ -74,9 +74,7 @@ Also, feel free to ask your question at our `github issue <https://github.com/Ma
 👨‍👩‍👧‍👦 Ecosystem
 ************************************
 * Github Repo : https://github.com/Marker-Inc-Korea/AutoRAG
-* HomePage : https://auto-rag.com
 * PyPI : https://pypi.org/project/AutoRAG/
-* Discord : https://discord.gg/P4DYXfmSAs
 * Roadmap : https://github.com/orgs/Auto-RAG/projects/1/views/2
 * HuggingFace : https://huggingface.co/AutoRAG
 * LinkedIn : https://www.linkedin.com/company/autorag/
diff --git a/docs/source/integration/vectordb/couchbase.md b/docs/source/integration/vectordb/couchbase.md
@@ -96,7 +96,7 @@ node_lines:
 1. `embedding_model: str`
    - Purpose: Specifies the name or identifier of the embedding model to be used.
    - Example: "openai_embed_3_large"
-   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://docs.auto-rag.com/local_model.html#configure-the-embedding-model) documentation.
+   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://marker-inc-korea.github.io/AutoRAG/local_model.html#configure-the-embedding-model) documentation.
 
 2. `embedding_batch: int = 100`
    - Purpose: Determines the number of embeddings to process in a single batch.
diff --git a/docs/source/integration/vectordb/milvus.md b/docs/source/integration/vectordb/milvus.md
@@ -66,7 +66,7 @@ node_lines:
 1. `embedding_model: str`
    - Purpose: Specifies the name or identifier of the embedding model to be used.
    - Example: "openai_embed_3_large"
-   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://docs.auto-rag.com/local_model.html#configure-the-embedding-model) documentation.
+   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://marker-inc-korea.github.io/AutoRAG/local_model.html#configure-the-embedding-model) documentation.
 
 2. `collection_name: str`
    - Purpose: Sets the name of the Milvus collection where the vectors will be stored.
diff --git a/docs/source/integration/vectordb/pinecone.md b/docs/source/integration/vectordb/pinecone.md
@@ -64,7 +64,7 @@ node_lines:
 1. `embedding_model: str`
    - Purpose: Specifies the name or identifier of the embedding model to be used.
    - Example: "openai_embed_3_large"
-   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://docs.auto-rag.com/local_model.html#configure-the-embedding-model) documentation.
+   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://marker-inc-korea.github.io/AutoRAG/local_model.html#configure-the-embedding-model) documentation.
 
 2. `index_name: str`
    - Purpose: Sets the name of the Pinecone index where the vectors will be stored.
diff --git a/docs/source/integration/vectordb/qdrant.md b/docs/source/integration/vectordb/qdrant.md
@@ -63,7 +63,7 @@ node_lines:
 1. `embedding_model: str`
    - Purpose: Specifies the name or identifier of the embedding model to be used.
    - Example: "openai_embed_3_large"
-   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://docs.auto-rag.com/local_model.html#configure-the-embedding-model) documentation.
+   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://marker-inc-korea.github.io/AutoRAG/local_model.html#configure-the-embedding-model) documentation.
 
 2. `collection_name: str`
    - Purpose: Sets the name of the Qdrant collection where the vectors will be stored.
diff --git a/docs/source/integration/vectordb/vectordb.md b/docs/source/integration/vectordb/vectordb.md
@@ -19,7 +19,7 @@ AutoRAG supports connection to multiple Vector Databases. This document outlines
 
 ## Usage
 
-Configure your Vector DBs in the YAML file as shown below. For more detailed information on YAML file syntax, please refer to [here](https://docs.auto-rag.com/optimization/custom_config.html).
+Configure your Vector DBs in the YAML file as shown below. For more detailed information on YAML file syntax, please refer to [here](https://marker-inc-korea.github.io/AutoRAG/optimization/custom_config.html).
 
 ```yaml
 vectordb:
diff --git a/docs/source/integration/vectordb/weaviate.md b/docs/source/integration/vectordb/weaviate.md
@@ -144,7 +144,7 @@ node_lines:
 1. `embedding_model: str`
    - Purpose: Specifies the name or identifier of the embedding model to be used.
    - Example: "openai_embed_3_large"
-   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://docs.auto-rag.com/local_model.html#configure-the-embedding-model) documentation.
+   - Note: This should correspond to a valid embedding model that your system can use to generate vector embeddings. For more information see [custom your embedding model](https://marker-inc-korea.github.io/AutoRAG/local_model.html#configure-the-embedding-model) documentation.
 
 2. `collection_name: str`
    - Purpose: Sets the name of the Weaviate collection where the vectors will be stored.
diff --git a/docs/source/local_model.md b/docs/source/local_model.md
@@ -167,7 +167,7 @@ We support the following embedding model types:
 
 You can configure the embedding model option directly in the YAML file `vectordb` section.
 If you want to know how to configure vectordb in AutoRAG,
-please go [here](https://docs.auto-rag.com/integration/vectordb/vectordb.html).
+please go [here](https://marker-inc-korea.github.io/AutoRAG/integration/vectordb/vectordb.html).
 
 For example,
 
diff --git a/docs/source/nodes/index.md b/docs/source/nodes/index.md
@@ -12,9 +12,9 @@ myst:
 
 <style>
 table.table.table-my-special-table {
-    border-collapse: collapse; 
+    border-collapse: collapse;
     border:1px solid #69899F;
-} 
+}
 table.table.table-my-special-table td{
     border:1px dotted #69899F;
     padding:5px;
@@ -38,7 +38,7 @@ table.table.table-my-special-table th{
     </tr>
     <tr>
       <td>1️⃣ <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/query_expansion.html">Query Expansion</a></td>
-      <td><a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/query_decompose.html">Query Decompose</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/hyde.html">HyDE</a>, <a href="https://docs.auto-rag.com/nodes/query_expansion/multi_query_expansion.html">Multi Query Expansion</a>, 📌 Pass Module: pass_query_expansion</td>
+      <td><a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/query_decompose.html">Query Decompose</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/hyde.html">HyDE</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/query_expansion/multi_query_expansion.html">Multi Query Expansion</a>, 📌 Pass Module: pass_query_expansion</td>
       <td>query_decompose, hyde, multi_query_expansion, pass_query_expansion</td>
     </tr>
     <tr>
@@ -68,7 +68,7 @@ table.table.table-my-special-table th{
     </tr>
     <tr>
       <td>7️⃣ <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/prompt_maker.html">Prompt Maker</a></td>
-      <td><a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/fstring.html">Default Prompt Maker (f-string)</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/long_context_reorder.html">Long Context Reorder</a>, <a href="https://docs.auto-rag.com/nodes/prompt_maker/window_replacement.html">Window Replacement</a></td>
+      <td><a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/fstring.html">Default Prompt Maker (f-string)</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/long_context_reorder.html">Long Context Reorder</a>, <a href="https://marker-inc-korea.github.io/AutoRAG/nodes/prompt_maker/window_replacement.html">Window Replacement</a></td>
       <td>fstring, long_context_reorder, window_replacement</td>
     </tr>
     <tr>
@@ -79,4 +79,4 @@ table.table.table-my-special-table th{
   </tbody>
 </table>
 
-For a comprehensive and up-to-date list of supporting nodes and modules, please refer to our dedicated Notion page. You can access this information [here](https://edai.notion.site/Supporting-Nodes-modules-0ebc7810649f4e41aead472a92976be4?pvs=4).
+For a comprehensive and up-to-date list of supporting nodes and modules, please refer to our dedicated Notion page. You can access this information [here](https://edai.notion.site/Supporting-Nodes-modules-0ebc7810649f4e41aead472a92976be4?pvs=4).
diff --git a/docs/source/nodes/passage_filter/percentile_cutoff.md b/docs/source/nodes/passage_filter/percentile_cutoff.md
@@ -2,13 +2,13 @@
 myst:
    html_meta:
       title: AutoRAG - Percentile Cutoff
-      description: Learn about percentile cutoff passage filter module in AutoRAG 
+      description: Learn about percentile cutoff passage filter module in AutoRAG
       keywords: AutoRAG,RAG,Advanced RAG,Passage Filter,percentile cutoff
 ---
 # Percentile Cutoff
 
 This module is inspired by
-our [similarity percentile cutoff](https://docs.auto-rag.com/nodes/passage_filter/similarity_percentile_cutoff.html)
+our [similarity percentile cutoff](https://marker-inc-korea.github.io/AutoRAG/nodes/passage_filter/similarity_percentile_cutoff.html)
 module.
 
 Filter out the contents that are below the content's length times percentile.
diff --git a/docs/source/nodes/passage_filter/threshold_cutoff.md b/docs/source/nodes/passage_filter/threshold_cutoff.md
@@ -7,7 +7,7 @@ myst:
 ---
 # Threshold Cutoff
 
-This module is inspired by our [similarity threshold cutoff](https://docs.auto-rag.com/nodes/passage_filter/similarity_threshold_cutoff.html) module.
+This module is inspired by our [similarity threshold cutoff](https://marker-inc-korea.github.io/AutoRAG/nodes/passage_filter/similarity_threshold_cutoff.html) module.
 Filters the contents, scores, and ids based on a **previous result's scores**.
 
 📣 Keeps at least one item per query if all scores are below the threshold.
diff --git a/docs/source/nodes/retrieval/bm25.md b/docs/source/nodes/retrieval/bm25.md
@@ -57,7 +57,7 @@ or install sudachipy by yourself.
 
 ```{admonition} Any trouble to use Korean tokenizer?
 You need to install extra dependencies to properly use Korean tokenizer.
-Please go to [here](https://docs.auto-rag.com/install.html) to look at the installation guide.
+Please go to [here](https://marker-inc-korea.github.io/AutoRAG/install.html) to look at the installation guide.
 ```
 
 ## **Example config.yaml**
diff --git a/docs/source/optimization/custom_config.md b/docs/source/optimization/custom_config.md
@@ -102,7 +102,7 @@ node_lines:
 ```
 
 ```{attention}
-Above YAML file is not working. For more information, please check out the [hybrid rrf](https://docs.auto-rag.com/nodes/retrieval/hybrid_rrf.html) module.
+Above YAML file is not working. For more information, please check out the [hybrid rrf](https://marker-inc-korea.github.io/AutoRAG/nodes/retrieval/hybrid_rrf.html) module.
 ```
 
 ```{admonition} What is tuple in the yaml file?
diff --git a/docs/source/test_your_rag.md b/docs/source/test_your_rag.md
@@ -7,7 +7,7 @@ In other words, you can measure retrieval or generation performance on the RAG t
 ## Preparation
 
 Before starting, ensure you have prepared a `qa.parquet` file for evaluation.
-See [here](https://docs.auto-rag.com/data_creation/tutorial.html#qa-creation) for learning how to make QA dataset.
+See [here](https://marker-inc-korea.github.io/AutoRAG/data_creation/tutorial.html#qa-creation) for learning how to make QA dataset.
 
 ## Retrieval Evaluation
 
diff --git a/docs/source/tutorial.md b/docs/source/tutorial.md

Original file line number	Diff line number	Diff line change
`@@ -1 +1 @@`
`1`		`-docs.auto-rag.com`
	`1`	`+marker-inc-korea.github.io/AutoRAG/`