RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
- Deep document understanding-based knowledge extraction from unstructured data with complicated formats.
- Finds "needle in a data haystack" of literally unlimited tokens.
- Intelligent and explainable.
- Plenty of template options to choose from.
- Visualization of text chunking to allow human intervention.
- Quick view of the key references and traceable citations to support grounded answers.
- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.
- Streamlined RAG orchestration catered to both personal and large businesses.
- Configurable LLMs as well as embedding models.
- Multiple recall paired with fused re-ranking.
- Intuitive APIs for seamless integration with business.
- 2024-04-11 Support Xinference for local LLM deployment.
- 2024-04-10 Add a new layout recognization model to the 'Laws' method.
- 2024-04-08 Support Ollama for local LLM deployment.
- 2024-04-07 Support Chinese UI.
- CPU >= 2 cores
- RAM >= 8 GB
- Docker >= 24.0.0 & Docker Compose >= v2.26.1
If you have not installed Docker on your local machine (Windows, Mac, or Linux), see Install Docker Engine.
-
Ensure
vm.max_map_count
>= 262144 (more):To check the value of
vm.max_map_count
:$ sysctl vm.max_map_count
Reset
vm.max_map_count
to a value at least 262144 if it is not.# In this case, we set it to 262144: $ sudo sysctl -w vm.max_map_count=262144
This change will be reset after a system reboot. To ensure your change remains permanent, add or update the
vm.max_map_count
value in /etc/sysctl.conf accordingly:vm.max_map_count=262144
-
Clone the repo:
$ git clone https://github.com/infiniflow/ragflow.git
-
Build the pre-built Docker images and start up the server:
$ cd ragflow/docker $ chmod +x ./entrypoint.sh $ docker compose up -d
The core image is about 9 GB in size and may take a while to load.
-
Check the server status after having the server up and running:
$ docker logs -f ragflow-server
The following output confirms a successful launch of the system:
____ ______ __ / __ \ ____ _ ____ _ / ____// /____ _ __ / /_/ // __ `// __ `// /_ / // __ \| | /| / / / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ / /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/ /____/ * Running on all addresses (0.0.0.0) * Running on http:https://127.0.0.1:9380 * Running on http:https://x.x.x.x:9380 INFO:werkzeug:Press CTRL+C to quit
-
In your web browser, enter the IP address of your server and log in to RAGFlow.
In the given scenario, you only need to enter
http:https://IP_OF_YOUR_MACHINE
(sans port number) as the default HTTP serving port80
can be omitted when using the default configurations. -
In service_conf.yaml, select the desired LLM factory in
user_default_llm
and update theAPI_KEY
field with the corresponding API key.See ./docs/llm_api_key_setup.md for more information.
The show is now on!
When it comes to system configurations, you will need to manage the following files:
- .env: Keeps the fundamental setups for the system, such as
SVR_HTTP_PORT
,MYSQL_PASSWORD
, andMINIO_PASSWORD
. - service_conf.yaml: Configures the back-end services.
- docker-compose.yml: The system relies on docker-compose.yml to start up.
You must ensure that changes to the .env file are in line with what are in the service_conf.yaml file.
The ./docker/README file provides a detailed description of the environment settings and service configurations, and you are REQUIRED to ensure that all environment settings listed in the ./docker/README file are aligned with the corresponding configurations in the service_conf.yaml file.
To update the default HTTP serving port (80), go to docker-compose.yml and change 80:80
to <YOUR_SERVING_PORT>:80
.
Updates to all system configurations require a system reboot to take effect:
$ docker-compose up -d
To build the Docker images from source:
$ git clone https://github.com/infiniflow/ragflow.git
$ cd ragflow/
$ docker build -t infiniflow/ragflow:v1.0 .
$ cd ragflow/docker
$ chmod +x ./entrypoint.sh
$ docker compose up -d
See the RAGFlow Roadmap 2024
RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our Contribution Guidelines first.