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Update Octoverse to README (#10859)
### Type of change - [x] Documentation Update
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Yingfeng
41
README.md
41
README.md
@ -43,7 +43,9 @@
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<a href="https://demo.ragflow.io">Demo</a>
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</h4>
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#
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<div align="center" style="margin-top:20px;margin-bottom:20px;">
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<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
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</div>
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<div align="center">
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<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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@ -175,22 +177,21 @@ releases! 🌟
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> ```bash
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> vm.max_map_count=262144
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> ```
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>
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2. Clone the repo:
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```bash
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$ git clone https://github.com/infiniflow/ragflow.git
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```
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3. Start up the server using the pre-built Docker images:
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> [!CAUTION]
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> All Docker images are built for x86 platforms. We don't currently offer Docker images for ARM64.
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> If you are on an ARM64 platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.
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> The command below downloads the `v0.21.1-slim` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.21.1-slim`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.
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> The command below downloads the `v0.21.1-slim` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.21.1-slim`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.
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```bash
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```bash
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$ cd ragflow/docker
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# Use CPU for embedding and DeepDoc tasks:
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$ docker compose -f docker-compose.yml up -d
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@ -198,16 +199,15 @@ releases! 🌟
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# To use GPU to accelerate embedding and DeepDoc tasks:
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# sed -i '1i DEVICE=gpu' .env
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# docker compose -f docker-compose.yml up -d
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```
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```
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| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
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|-------------------|-----------------|-----------------------|--------------------------|
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| v0.21.1 | ≈9 | ✔️ | Stable release |
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| v0.21.1-slim | ≈2 | ❌ | Stable release |
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| nightly | ≈2 | ❌ | _Unstable_ nightly build |
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| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
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| ----------------- | --------------- | --------------------- | -------------------------- |
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| v0.21.1 | ≈9 | ✔️ | Stable release |
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| v0.21.1-slim | ≈2 | ❌ | Stable release |
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| nightly | ≈2 | ❌ | _Unstable_ nightly build |
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> Note: Starting with `v0.22.0`, we ship only the slim edition and no longer append the **-slim** suffix to the image tag.
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> Note: Starting with `v0.22.0`, we ship only the slim edition and no longer append the **-slim** suffix to the image tag.
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4. Check the server status after having the server up and running:
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@ -230,14 +230,17 @@ releases! 🌟
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> If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network anormal`
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> error because, at that moment, your RAGFlow may not be fully initialized.
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>
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5. In your web browser, enter the IP address of your server and log in to RAGFlow.
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> With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default
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> HTTP serving port `80` can be omitted when using the default configurations.
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>
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6. In [service_conf.yaml.template](./docker/service_conf.yaml.template), select the desired LLM factory in `user_default_llm` and update
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the `API_KEY` field with the corresponding API key.
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> See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.
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>
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_The show is on!_
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@ -276,7 +279,6 @@ RAGFlow uses Elasticsearch by default for storing full text and vectors. To swit
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> `-v` will delete the docker container volumes, and the existing data will be cleared.
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2. Set `DOC_ENGINE` in **docker/.env** to `infinity`.
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3. Start the containers:
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```bash
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@ -303,7 +305,6 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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```bash
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pipx install uv pre-commit
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```
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2. Clone the source code and install Python dependencies:
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```bash
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@ -313,7 +314,6 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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uv run download_deps.py
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pre-commit install
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```
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3. Launch the dependent services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:
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```bash
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@ -325,13 +325,11 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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```
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127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
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```
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4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:
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```bash
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export HF_ENDPOINT=https://hf-mirror.com
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```
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5. If your operating system does not have jemalloc, please install it as follows:
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```bash
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@ -344,7 +342,6 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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# macOS
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sudo brew install jemalloc
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```
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6. Launch backend service:
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```bash
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@ -352,14 +349,12 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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export PYTHONPATH=$(pwd)
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bash docker/launch_backend_service.sh
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```
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7. Install frontend dependencies:
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```bash
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cd web
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npm install
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```
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8. Launch frontend service:
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```bash
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@ -369,14 +364,12 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
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_The following output confirms a successful launch of the system:_
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9. Stop RAGFlow front-end and back-end service after development is complete:
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```bash
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pkill -f "ragflow_server.py|task_executor.py"
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```
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## 📚 Documentation
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- [Quickstart](https://ragflow.io/docs/dev/)
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