Obsoleted dev and dev-slim (#3930)
Browse files### What problem does this PR solve?
Obsoleted dev and dev-slim
### Type of change
- [x] Documentation Update
- .github/workflows/tests.yml +12 -11
- README.md +14 -18
- README_id.md +13 -15
- README_ja.md +12 -8
- README_ko.md +14 -8
- README_zh.md +14 -9
- docker/.env +10 -10
- docker/README.md +8 -8
- docs/configurations.md +8 -8
- docs/guides/develop/build_docker_image.mdx +3 -3
- docs/guides/upgrade_ragflow.mdx +11 -11
- docs/quickstart.mdx +14 -7
- docs/references/faq.md +3 -3
- docs/release_notes.md +3 -3
- helm/values.yaml +4 -4
.github/workflows/tests.yml
CHANGED
@@ -55,28 +55,29 @@ jobs:
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with:
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version: ">=0.8.2"
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-
- name: Build ragflow:
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run: |
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RUNNER_WORKSPACE_PREFIX=${RUNNER_WORKSPACE_PREFIX:-$HOME}
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sudo docker pull ubuntu:22.04
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-
sudo docker build --progress=plain --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:
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-
- name: Build ragflow:
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run: |
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sudo docker build --progress=plain --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:
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-
- name: Start ragflow:
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run: |
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sudo docker compose -f docker/docker-compose.yml up -d
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-
- name: Stop ragflow:
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if: always() # always run this step even if previous steps failed
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run: |
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sudo docker compose -f docker/docker-compose.yml down -v
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-
- name: Start ragflow:
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run: |
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echo "RAGFLOW_IMAGE=infiniflow/ragflow:
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sudo docker compose -f docker/docker-compose.yml up -d
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- name: Run sdk tests against Elasticsearch
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@@ -100,12 +101,12 @@ jobs:
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cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
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-
- name: Stop ragflow:
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if: always() # always run this step even if previous steps failed
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run: |
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sudo docker compose -f docker/docker-compose.yml down -v
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-
- name: Start ragflow:
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run: |
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sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml up -d
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@@ -129,7 +130,7 @@ jobs:
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done
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cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
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-
- name: Stop ragflow:
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if: always() # always run this step even if previous steps failed
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run: |
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sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml down -v
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with:
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version: ">=0.8.2"
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+
- name: Build ragflow:nightly-slim
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run: |
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RUNNER_WORKSPACE_PREFIX=${RUNNER_WORKSPACE_PREFIX:-$HOME}
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sudo docker pull ubuntu:22.04
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sudo docker build --progress=plain --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
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+
- name: Build ragflow:nightly
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run: |
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sudo docker build --progress=plain --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly .
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- name: Start ragflow:nightly-slim
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run: |
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echo "RAGFLOW_IMAGE=infiniflow/ragflow:nightly-slim" >> docker/.env
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sudo docker compose -f docker/docker-compose.yml up -d
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+
- name: Stop ragflow:nightly-slim
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if: always() # always run this step even if previous steps failed
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run: |
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sudo docker compose -f docker/docker-compose.yml down -v
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+
- name: Start ragflow:nightly
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run: |
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echo "RAGFLOW_IMAGE=infiniflow/ragflow:nightly" >> docker/.env
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sudo docker compose -f docker/docker-compose.yml up -d
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- name: Run sdk tests against Elasticsearch
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cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
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+
- name: Stop ragflow:nightly
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if: always() # always run this step even if previous steps failed
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run: |
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sudo docker compose -f docker/docker-compose.yml down -v
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+
- name: Start ragflow:nightly
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run: |
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sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml up -d
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done
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cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
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+
- name: Stop ragflow:nightly
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if: always() # always run this step even if previous steps failed
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run: |
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sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml down -v
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README.md
CHANGED
@@ -165,29 +165,25 @@ releases! 🌟
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$ git clone https://github.com/infiniflow/ragflow.git
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```
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3.
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-
> The command below downloads the
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-
Docker images do not include embedding models or Python libraries and hence are approximately
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```bash
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$ cd ragflow/docker
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$ docker compose -f docker-compose.yml up -d
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```
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`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`. After making this change, rerun the command above to initiate the
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download.
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> **NOTE:** A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size
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and may take significantly longer time to load.
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4. Check the server status after having the server up and running:
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@@ -267,12 +263,12 @@ RAGFlow uses Elasticsearch by default for storing full text and vectors. To swit
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## 🔧 Build a Docker image without embedding models
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-
This image is approximately
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔧 Build a Docker image including embedding models
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔨 Launch service from source for development
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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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+
> The command below downloads the v0.14.1 version Docker image for RAGFlow slim (`v0.14.1-slim`). Note that RAGFlow slim
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+
Docker images do not include embedding models or Python libraries and hence are approximately 2 GB in size.
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```bash
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$ cd ragflow/docker
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$ docker compose -f docker-compose.yml up -d
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```
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+
| RAGFLOW_IMAGE tag in docker/.env | size | Including embedding models and related Python packages? | comments |
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| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
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+
| v0.14.1 | ~9 GB | YES | stable release |
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+
| v0.14.1-slim | ~2 GB | NO | stable release |
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+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
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+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
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+
| nightly | ~9 GB | YES | unstable nightly build |
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| nightly-slim | ~2 GB | NO | unstable nightly build |
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4. Check the server status after having the server up and running:
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## 🔧 Build a Docker image without embedding models
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+
This image is approximately 2 GB in size and relies on external LLM and embedding services.
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
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```
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## 🔧 Build a Docker image including embedding models
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:nightly .
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```
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## 🔨 Launch service from source for development
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README_id.md
CHANGED
@@ -160,7 +160,7 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
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3. Bangun image Docker pre-built dan jalankan server:
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-
> Perintah di bawah ini akan mengunduh versi
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tidak termasuk model embedding atau library Python dan berukuran sekitar 1GB.
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```bash
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@@ -168,18 +168,16 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
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$ docker compose -f docker-compose.yml up -d
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```
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> **CATATAN:** Image Docker RAGFlow yang mencakup model embedding dan library Python berukuran sekitar 9GB
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-
dan mungkin memerlukan waktu lebih lama untuk dimuat.
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4. Periksa status server setelah server aktif dan berjalan:
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## 🔧 Membangun Docker Image tanpa Model Embedding
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Image ini berukuran sekitar
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔧 Membangun Docker Image Termasuk Model Embedding
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔨 Menjalankan Aplikasi dari untuk Pengembangan
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3. Bangun image Docker pre-built dan jalankan server:
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> Perintah di bawah ini akan mengunduh versi v0.14.1 dari Docker image RAGFlow slim (`v0.14.1-slim`). Image RAGFlow slim
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tidak termasuk model embedding atau library Python dan berukuran sekitar 1GB.
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```bash
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$ docker compose -f docker-compose.yml up -d
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```
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+
| RAGFLOW_IMAGE tag in docker/.env | size | Including embedding models and related Python packages? | comments |
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+
| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
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+
| v0.14.1 | ~9 GB | YES | stable release |
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+
| v0.14.1-slim | ~2 GB | NO | stable release |
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+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
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+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
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+
| nightly | ~9 GB | YES | unstable nightly build |
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+
| nightly-slim | ~2 GB | NO | unstable nightly build |
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4. Periksa status server setelah server aktif dan berjalan:
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## 🔧 Membangun Docker Image tanpa Model Embedding
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Image ini berukuran sekitar 2 GB dan bergantung pada aplikasi LLM eksternal dan embedding.
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
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```
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## 🔧 Membangun Docker Image Termasuk Model Embedding
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:nightly .
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```
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## 🔨 Menjalankan Aplikasi dari untuk Pengembangan
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README_ja.md
CHANGED
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3. ビルド済みの Docker イメージをビルドし、サーバーを起動する:
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> 以下のコマンドは、RAGFlow slim(`
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```bash
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$ cd ragflow/docker
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$ docker compose -f docker-compose.yml up -d
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```
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4. サーバーを立ち上げた後、サーバーの状態を確認する:
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔧 ソースコードをコンパイルしたDockerイメージ(埋め込みモデルを含む)
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔨 ソースコードからサービスを起動する方法
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3. ビルド済みの Docker イメージをビルドし、サーバーを起動する:
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> 以下のコマンドは、RAGFlow slim(`v0.14.1-slim`)の開発版Dockerイメージをダウンロードします。RAGFlow slimのDockerイメージには、埋め込みモデルやPythonライブラリが含まれていないため、サイズは約1GBです。
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```bash
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$ cd ragflow/docker
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$ docker compose -f docker-compose.yml up -d
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```
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+
| RAGFLOW_IMAGE tag in docker/.env | size | Including embedding models and related Python packages? | comments |
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+
| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
|
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+
| v0.14.1 | ~9 GB | YES | stable release |
|
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+
| v0.14.1-slim | ~2 GB | NO | stable release |
|
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+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
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+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
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+
| nightly | ~9 GB | YES | unstable nightly build |
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+
| nightly-slim | ~2 GB | NO | unstable nightly build |
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+
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4. サーバーを立ち上げた後、サーバーの状態を確認する:
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
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```
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## 🔧 ソースコードをコンパイルしたDockerイメージ(埋め込みモデルを含む)
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build -f Dockerfile -t infiniflow/ragflow:nightly .
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```
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## 🔨 ソースコードからサービスを起動する方法
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README_ko.md
CHANGED
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3. 미리 빌드된 Docker 이미지를 생성하고 서버를 시작하세요:
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> 아래의 명령은 RAGFlow slim(
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```bash
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$ cd ragflow/docker
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$ docker compose -f docker-compose.yml up -d
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```
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4. 서버가 시작된 후 서버 상태를 확인하세요:
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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-
docker build -f Dockerfile -t infiniflow/ragflow:
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```
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## 🔨 소스 코드로 서비스를 시작합니다.
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3. 미리 빌드된 Docker 이미지를 생성하고 서버를 시작하세요:
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148 |
+
> 아래의 명령은 RAGFlow slim(v0.14.1-slim)의 개발 버전 Docker 이미지를 다운로드합니다. RAGFlow slim Docker 이미지에는 임베딩 모델이나 Python 라이브러리가 포함되어 있지 않으므로 크기는 약 1GB입니다.
|
149 |
|
150 |
```bash
|
151 |
$ cd ragflow/docker
|
152 |
$ docker compose -f docker-compose.yml up -d
|
153 |
```
|
154 |
|
155 |
+
|
156 |
+
| RAGFLOW_IMAGE tag in docker/.env | size | Including embedding models and related Python packages? | comments |
|
157 |
+
| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
|
158 |
+
| v0.14.1 | ~9 GB | YES | stable release |
|
159 |
+
| v0.14.1-slim | ~2 GB | NO | stable release |
|
160 |
+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
|
161 |
+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
|
162 |
+
| nightly | ~9 GB | YES | unstable nightly build |
|
163 |
+
| nightly-slim | ~2 GB | NO | unstable nightly build |
|
164 |
+
|
165 |
+
|
166 |
|
167 |
|
168 |
4. 서버가 시작된 후 서버 상태를 확인하세요:
|
|
|
236 |
```bash
|
237 |
git clone https://github.com/infiniflow/ragflow.git
|
238 |
cd ragflow/
|
239 |
+
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
240 |
```
|
241 |
|
242 |
## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
|
|
|
246 |
```bash
|
247 |
git clone https://github.com/infiniflow/ragflow.git
|
248 |
cd ragflow/
|
249 |
+
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
250 |
```
|
251 |
|
252 |
## 🔨 소스 코드로 서비스를 시작합니다.
|
README_zh.md
CHANGED
@@ -142,18 +142,23 @@
|
|
142 |
|
143 |
3. 进入 **docker** 文件夹,利用提前编译好的 Docker 镜像启动服务器:
|
144 |
|
145 |
-
> 运行以下命令会自动下载
|
146 |
|
147 |
```bash
|
148 |
$ cd ragflow/docker
|
149 |
$ docker compose -f docker-compose.yml up -d
|
150 |
```
|
151 |
|
152 |
-
|
153 |
-
|
154 |
-
|
155 |
-
|
156 |
-
|
|
|
|
|
|
|
|
|
|
|
157 |
4. 服务器启动成功后再次确认服务器状态:
|
158 |
|
159 |
```bash
|
@@ -230,12 +235,12 @@ RAGFlow 默认使用 Elasticsearch 存储文本和向量数据. 如果要切换
|
|
230 |
|
231 |
## 🔧 源码编译 Docker 镜像(不含 embedding 模型)
|
232 |
|
233 |
-
本 Docker 镜像大小约
|
234 |
|
235 |
```bash
|
236 |
git clone https://github.com/infiniflow/ragflow.git
|
237 |
cd ragflow/
|
238 |
-
docker build --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:
|
239 |
```
|
240 |
|
241 |
## 🔧 源码编译 Docker 镜像(包含 embedding 模型)
|
@@ -245,7 +250,7 @@ docker build --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t in
|
|
245 |
```bash
|
246 |
git clone https://github.com/infiniflow/ragflow.git
|
247 |
cd ragflow/
|
248 |
-
docker build --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:
|
249 |
```
|
250 |
|
251 |
## 🔨 以源代码启动服务
|
|
|
142 |
|
143 |
3. 进入 **docker** 文件夹,利用提前编译好的 Docker 镜像启动服务器:
|
144 |
|
145 |
+
> 运行以下命令会自动下载 v0.14.1 版的 RAGFlow slim Docker 镜像(`v0.14.1-slim`),该镜像并不包含 embedding 模型以及一些 Python 库,因此镜像大小约 1GB。
|
146 |
|
147 |
```bash
|
148 |
$ cd ragflow/docker
|
149 |
$ docker compose -f docker-compose.yml up -d
|
150 |
```
|
151 |
|
152 |
+
| RAGFLOW_IMAGE tag in docker/.env | 尺寸 | 内置 embedding 模型和相关 Python 库? | 描述 |
|
153 |
+
| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
|
154 |
+
| v0.14.1 | ~9 GB | YES | stable release |
|
155 |
+
| v0.14.1-slim | ~2 GB | NO | stable release |
|
156 |
+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
|
157 |
+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
|
158 |
+
| nightly | ~9 GB | YES | unstable nightly build |
|
159 |
+
| nightly-slim | ~2 GB | NO | unstable nightly build |
|
160 |
+
|
161 |
+
|
162 |
4. 服务器启动成功后再次确认服务器状态:
|
163 |
|
164 |
```bash
|
|
|
235 |
|
236 |
## 🔧 源码编译 Docker 镜像(不含 embedding 模型)
|
237 |
|
238 |
+
本 Docker 镜像大小约 2 GB 左右并且依赖外部的大模型和 embedding 服务。
|
239 |
|
240 |
```bash
|
241 |
git clone https://github.com/infiniflow/ragflow.git
|
242 |
cd ragflow/
|
243 |
+
docker build --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
244 |
```
|
245 |
|
246 |
## 🔧 源码编译 Docker 镜像(包含 embedding 模型)
|
|
|
250 |
```bash
|
251 |
git clone https://github.com/infiniflow/ragflow.git
|
252 |
cd ragflow/
|
253 |
+
docker build --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly .
|
254 |
```
|
255 |
|
256 |
## 🔨 以源代码启动服务
|
docker/.env
CHANGED
@@ -80,13 +80,13 @@ REDIS_PASSWORD=infini_rag_flow
|
|
80 |
SVR_HTTP_PORT=9380
|
81 |
|
82 |
# The RAGFlow Docker image to download.
|
83 |
-
# Defaults to the
|
84 |
-
RAGFLOW_IMAGE=infiniflow/ragflow:
|
85 |
#
|
86 |
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
|
87 |
-
# RAGFLOW_IMAGE=infiniflow/ragflow:
|
88 |
#
|
89 |
-
# The Docker image of the
|
90 |
# - Built-in embedding models:
|
91 |
# - BAAI/bge-large-zh-v1.5
|
92 |
# - BAAI/bge-reranker-v2-m3
|
@@ -107,13 +107,13 @@ RAGFLOW_IMAGE=infiniflow/ragflow:dev
|
|
107 |
|
108 |
# If you cannot download the RAGFlow Docker image:
|
109 |
#
|
110 |
-
# - For the `
|
111 |
-
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
112 |
-
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
113 |
#
|
114 |
-
# - For the `
|
115 |
-
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
116 |
-
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
117 |
|
118 |
# The local time zone.
|
119 |
TIMEZONE='Asia/Shanghai'
|
|
|
80 |
SVR_HTTP_PORT=9380
|
81 |
|
82 |
# The RAGFlow Docker image to download.
|
83 |
+
# Defaults to the v0.14.1-slim edition, which is the RAGFlow Docker image without embedding models.
|
84 |
+
RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim
|
85 |
#
|
86 |
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
|
87 |
+
# RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1
|
88 |
#
|
89 |
+
# The Docker image of the v0.14.1 edition includes:
|
90 |
# - Built-in embedding models:
|
91 |
# - BAAI/bge-large-zh-v1.5
|
92 |
# - BAAI/bge-reranker-v2-m3
|
|
|
107 |
|
108 |
# If you cannot download the RAGFlow Docker image:
|
109 |
#
|
110 |
+
# - For the `nightly-slim` edition, uncomment either of the following:
|
111 |
+
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim
|
112 |
+
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim
|
113 |
#
|
114 |
+
# - For the `nightly` edition, uncomment either of the following:
|
115 |
+
# RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly
|
116 |
+
# RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly
|
117 |
|
118 |
# The local time zone.
|
119 |
TIMEZONE='Asia/Shanghai'
|
docker/README.md
CHANGED
@@ -75,8 +75,8 @@ The [.env](./.env) file contains important environment variables for Docker.
|
|
75 |
- `RAGFLOW-IMAGE`
|
76 |
The Docker image edition. Available editions:
|
77 |
|
78 |
-
- `infiniflow/ragflow:
|
79 |
-
- `infiniflow/ragflow:
|
80 |
- Built-in embedding models:
|
81 |
- `BAAI/bge-large-zh-v1.5`
|
82 |
- `BAAI/bge-reranker-v2-m3`
|
@@ -95,12 +95,12 @@ The [.env](./.env) file contains important environment variables for Docker.
|
|
95 |
> [!TIP]
|
96 |
> If you cannot download the RAGFlow Docker image, try the following mirrors.
|
97 |
>
|
98 |
-
> - For the `
|
99 |
-
> - `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
100 |
-
> - `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
101 |
-
> - For the `
|
102 |
-
> - `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
103 |
-
> - `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
104 |
|
105 |
### Timezone
|
106 |
|
|
|
75 |
- `RAGFLOW-IMAGE`
|
76 |
The Docker image edition. Available editions:
|
77 |
|
78 |
+
- `infiniflow/ragflow:v0.14.1-slim` (default): The RAGFlow Docker image without embedding models.
|
79 |
+
- `infiniflow/ragflow:v0.14.1`: The RAGFlow Docker image with embedding models including:
|
80 |
- Built-in embedding models:
|
81 |
- `BAAI/bge-large-zh-v1.5`
|
82 |
- `BAAI/bge-reranker-v2-m3`
|
|
|
95 |
> [!TIP]
|
96 |
> If you cannot download the RAGFlow Docker image, try the following mirrors.
|
97 |
>
|
98 |
+
> - For the `nightly-slim` edition:
|
99 |
+
> - `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim` or,
|
100 |
+
> - `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim`.
|
101 |
+
> - For the `nightly` edition:
|
102 |
+
> - `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly` or,
|
103 |
+
> - `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly`.
|
104 |
|
105 |
### Timezone
|
106 |
|
docs/configurations.md
CHANGED
@@ -93,8 +93,8 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
|
|
93 |
- `RAGFLOW-IMAGE`
|
94 |
The Docker image edition. Available editions:
|
95 |
|
96 |
-
- `infiniflow/ragflow:
|
97 |
-
- `infiniflow/ragflow:
|
98 |
- Built-in embedding models:
|
99 |
- `BAAI/bge-large-zh-v1.5`
|
100 |
- `BAAI/bge-reranker-v2-m3`
|
@@ -113,12 +113,12 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
|
|
113 |
:::tip NOTE
|
114 |
If you cannot download the RAGFlow Docker image, try the following mirrors.
|
115 |
|
116 |
-
- For the `
|
117 |
-
- `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
118 |
-
- `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
119 |
-
- For the `
|
120 |
-
- `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:
|
121 |
-
- `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:
|
122 |
:::
|
123 |
|
124 |
### Timezone
|
|
|
93 |
- `RAGFLOW-IMAGE`
|
94 |
The Docker image edition. Available editions:
|
95 |
|
96 |
+
- `infiniflow/ragflow:v0.14.1-slim` (default): The RAGFlow Docker image without embedding models.
|
97 |
+
- `infiniflow/ragflow:v0.14.1`: The RAGFlow Docker image with embedding models including:
|
98 |
- Built-in embedding models:
|
99 |
- `BAAI/bge-large-zh-v1.5`
|
100 |
- `BAAI/bge-reranker-v2-m3`
|
|
|
113 |
:::tip NOTE
|
114 |
If you cannot download the RAGFlow Docker image, try the following mirrors.
|
115 |
|
116 |
+
- For the `nightly-slim` edition:
|
117 |
+
- `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly-slim` or,
|
118 |
+
- `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly-slim`.
|
119 |
+
- For the `nightly` edition:
|
120 |
+
- `RAGFLOW_IMAGE=swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow:nightly` or,
|
121 |
+
- `RAGFLOW_IMAGE=registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow:nightly`.
|
122 |
:::
|
123 |
|
124 |
### Timezone
|
docs/guides/develop/build_docker_image.mdx
CHANGED
@@ -31,7 +31,7 @@ A guide explaining how to build a RAGFlow Docker image from its source code. By
|
|
31 |
]}>
|
32 |
<TabItem value="without">
|
33 |
|
34 |
-
This image is approximately
|
35 |
|
36 |
:::tip NOTE
|
37 |
While we also test RAGFlow on ARM64 platforms, we do not plan to maintain RAGFlow Docker images for ARM. However, you can build an image yourself on a `linux/arm64` or `darwin/arm64` host machine as well.
|
@@ -40,7 +40,7 @@ While we also test RAGFlow on ARM64 platforms, we do not plan to maintain RAGFlo
|
|
40 |
```bash
|
41 |
git clone https://github.com/infiniflow/ragflow.git
|
42 |
cd ragflow/
|
43 |
-
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:
|
44 |
```
|
45 |
|
46 |
|
@@ -56,7 +56,7 @@ While we also test RAGFlow on ARM64 platforms, we do not plan to maintain RAGFlo
|
|
56 |
```bash
|
57 |
git clone https://github.com/infiniflow/ragflow.git
|
58 |
cd ragflow/
|
59 |
-
docker build -f Dockerfile -t infiniflow/ragflow:
|
60 |
```
|
61 |
|
62 |
</TabItem>
|
|
|
31 |
]}>
|
32 |
<TabItem value="without">
|
33 |
|
34 |
+
This image is approximately 2 GB in size and relies on external LLM and embedding services.
|
35 |
|
36 |
:::tip NOTE
|
37 |
While we also test RAGFlow on ARM64 platforms, we do not plan to maintain RAGFlow Docker images for ARM. However, you can build an image yourself on a `linux/arm64` or `darwin/arm64` host machine as well.
|
|
|
40 |
```bash
|
41 |
git clone https://github.com/infiniflow/ragflow.git
|
42 |
cd ragflow/
|
43 |
+
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
44 |
```
|
45 |
|
46 |
|
|
|
56 |
```bash
|
57 |
git clone https://github.com/infiniflow/ragflow.git
|
58 |
cd ragflow/
|
59 |
+
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
60 |
```
|
61 |
|
62 |
</TabItem>
|
docs/guides/upgrade_ragflow.mdx
CHANGED
@@ -7,11 +7,11 @@ slug: /upgrade_ragflow
|
|
7 |
import Tabs from '@theme/Tabs';
|
8 |
import TabItem from '@theme/TabItem';
|
9 |
|
10 |
-
Upgrade RAGFlow to `
|
11 |
|
12 |
-
## Upgrade RAGFlow to `
|
13 |
|
14 |
-
`
|
15 |
|
16 |
To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker image:
|
17 |
|
@@ -24,22 +24,22 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
|
|
24 |
2. Update **ragflow/docker/.env**:
|
25 |
|
26 |
<Tabs
|
27 |
-
defaultValue="
|
28 |
values={[
|
29 |
-
{label: '
|
30 |
-
{label: '
|
31 |
]}>
|
32 |
-
<TabItem value="
|
33 |
|
34 |
```bash
|
35 |
-
RAGFLOW_IMAGE=infiniflow/ragflow:
|
36 |
```
|
37 |
|
38 |
</TabItem>
|
39 |
-
<TabItem value="
|
40 |
|
41 |
```bash
|
42 |
-
RAGFLOW_IMAGE=infiniflow/ragflow:
|
43 |
```
|
44 |
|
45 |
</TabItem>
|
@@ -65,7 +65,7 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
|
|
65 |
2. Switch to the latest, officially published release, e.g., `v0.14.1`:
|
66 |
|
67 |
```bash
|
68 |
-
git checkout v0.14.1
|
69 |
```
|
70 |
|
71 |
3. Update **ragflow/docker/.env** as follows:
|
|
|
7 |
import Tabs from '@theme/Tabs';
|
8 |
import TabItem from '@theme/TabItem';
|
9 |
|
10 |
+
Upgrade RAGFlow to `nightly-slim`/`nightly` or the latest, published release.
|
11 |
|
12 |
+
## Upgrade RAGFlow to `nightly-slim`/`nightly`, the most recent, tested Docker image
|
13 |
|
14 |
+
`nightly-slim` refers to the RAGFlow Docker image *without* embedding models, while `nightly` refers to the RAGFlow Docker image with embedding models. For details on their differences, see [ragflow/docker/.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env).
|
15 |
|
16 |
To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker image:
|
17 |
|
|
|
24 |
2. Update **ragflow/docker/.env**:
|
25 |
|
26 |
<Tabs
|
27 |
+
defaultValue="nightly-slim"
|
28 |
values={[
|
29 |
+
{label: 'nightly-slim', value: 'nightly-slim'},
|
30 |
+
{label: 'nightly', value: 'nightly'},
|
31 |
]}>
|
32 |
+
<TabItem value="nightly-slim">
|
33 |
|
34 |
```bash
|
35 |
+
RAGFLOW_IMAGE=infiniflow/ragflow:nightly-slim
|
36 |
```
|
37 |
|
38 |
</TabItem>
|
39 |
+
<TabItem value="nightly">
|
40 |
|
41 |
```bash
|
42 |
+
RAGFLOW_IMAGE=infiniflow/ragflow:nightly
|
43 |
```
|
44 |
|
45 |
</TabItem>
|
|
|
65 |
2. Switch to the latest, officially published release, e.g., `v0.14.1`:
|
66 |
|
67 |
```bash
|
68 |
+
git checkout -f v0.14.1
|
69 |
```
|
70 |
|
71 |
3. Update **ragflow/docker/.env** as follows:
|
docs/quickstart.mdx
CHANGED
@@ -177,20 +177,27 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
|
|
177 |
|
178 |
```bash
|
179 |
$ git clone https://github.com/infiniflow/ragflow.git
|
|
|
|
|
180 |
```
|
181 |
|
182 |
-
3.
|
183 |
|
184 |
-
> The command below downloads the
|
185 |
|
186 |
```bash
|
187 |
-
$
|
188 |
-
$ docker compose -f docker-compose.yml up -d
|
189 |
```
|
190 |
|
191 |
-
|
192 |
-
|
193 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
194 |
|
195 |
:::tip NOTE
|
196 |
A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size and may take significantly longer time to load.
|
|
|
177 |
|
178 |
```bash
|
179 |
$ git clone https://github.com/infiniflow/ragflow.git
|
180 |
+
$ cd ragflow
|
181 |
+
$ git checkout -f v0.14.1
|
182 |
```
|
183 |
|
184 |
+
3. Use the pre-built Docker images and start up the server:
|
185 |
|
186 |
+
> The command below downloads the v0.14.1 version Docker image for RAGFlow slim (`v0.14.1-slim`). Note that RAGFlow slim Docker images do not include embedding models or Python libraries and hence are approximately 2 GB in size.
|
187 |
|
188 |
```bash
|
189 |
+
$ docker compose -f docker/docker-compose.yml up -d
|
|
|
190 |
```
|
191 |
|
192 |
+
| RAGFLOW_IMAGE tag in docker/.env | size | Including embedding models and related Python packages? | comments |
|
193 |
+
| -------------------------------- | ----- | ------------------------------------------------------- | ---------------------- |
|
194 |
+
| v0.14.1 | ~9 GB | YES | stable release |
|
195 |
+
| v0.14.1-slim | ~2 GB | NO | stable release |
|
196 |
+
| v0.15.0-dev1 | ~9 GB | YES | unstable beta release |
|
197 |
+
| v0.15.0-dev1-slim | ~2 GB | NO | unstable beta release |
|
198 |
+
| nightly | ~9 GB | YES | unstable nightly build |
|
199 |
+
| nightly-slim | ~2 GB | NO | unstable nightly build |
|
200 |
+
|
201 |
|
202 |
:::tip NOTE
|
203 |
A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size and may take significantly longer time to load.
|
docs/references/faq.md
CHANGED
@@ -42,10 +42,10 @@ We officially support x86 CPU and nvidia GPU. While we also test RAGFlow on ARM6
|
|
42 |
|
43 |
### Which embedding models can be deployed locally?
|
44 |
|
45 |
-
RAGFlow offers two Docker image editions, `
|
46 |
|
47 |
-
- `infiniflow/ragflow:
|
48 |
-
- `infiniflow/ragflow:
|
49 |
- Built-in embedding models:
|
50 |
- `BAAI/bge-large-zh-v1.5`
|
51 |
- `BAAI/bge-reranker-v2-m3`
|
|
|
42 |
|
43 |
### Which embedding models can be deployed locally?
|
44 |
|
45 |
+
RAGFlow offers two Docker image editions, `v0.14.1-slim` and `v0.14.1`:
|
46 |
|
47 |
+
- `infiniflow/ragflow:v0.14.1-slim` (default): The RAGFlow Docker image without embedding models.
|
48 |
+
- `infiniflow/ragflow:v0.14.1`: The RAGFlow Docker image with embedding models including:
|
49 |
- Built-in embedding models:
|
50 |
- `BAAI/bge-large-zh-v1.5`
|
51 |
- `BAAI/bge-reranker-v2-m3`
|
docs/release_notes.md
CHANGED
@@ -102,11 +102,11 @@ Released on September 30, 2024.
|
|
102 |
|
103 |
As of this release, RAGFlow offers slim editions of its Docker images to improve the experience for users with limited Internet access. A slim edition of RAGFlow's Docker image does not include built-in BGE/BCE embedding models and has a size of about 1GB; a full edition of RAGFlow is approximately 9GB and includes both built-in embedding models and embedding models that will be downloaded once you select them in the RAGFlow UI.
|
104 |
|
105 |
-
The default Docker image edition is `
|
106 |
|
107 |
-
- `
|
108 |
- `v0.12.0-slim`: The slim edition of the most recent **officially released** Docker image.
|
109 |
-
- `
|
110 |
- `v0.12.0`: The full edition of the most recent **officially released** Docker image.
|
111 |
|
112 |
See [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow) for instructions on upgrading.
|
|
|
102 |
|
103 |
As of this release, RAGFlow offers slim editions of its Docker images to improve the experience for users with limited Internet access. A slim edition of RAGFlow's Docker image does not include built-in BGE/BCE embedding models and has a size of about 1GB; a full edition of RAGFlow is approximately 9GB and includes both built-in embedding models and embedding models that will be downloaded once you select them in the RAGFlow UI.
|
104 |
|
105 |
+
The default Docker image edition is `nightly-slim`. The following list clarifies the differences between various editions:
|
106 |
|
107 |
+
- `nightly-slim`: The slim edition of the most recent tested Docker image.
|
108 |
- `v0.12.0-slim`: The slim edition of the most recent **officially released** Docker image.
|
109 |
+
- `nightly`: The full edition of the most recent tested Docker image.
|
110 |
- `v0.12.0`: The full edition of the most recent **officially released** Docker image.
|
111 |
|
112 |
See [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow) for instructions on upgrading.
|
helm/values.yaml
CHANGED
@@ -27,13 +27,13 @@ env:
|
|
27 |
REDIS_PASSWORD: infini_rag_flow_helm
|
28 |
|
29 |
# The RAGFlow Docker image to download.
|
30 |
-
# Defaults to the
|
31 |
-
RAGFLOW_IMAGE: infiniflow/ragflow:
|
32 |
#
|
33 |
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
|
34 |
-
# RAGFLOW_IMAGE=infiniflow/ragflow:
|
35 |
#
|
36 |
-
# The Docker image of the
|
37 |
# - Built-in embedding models:
|
38 |
# - BAAI/bge-large-zh-v1.5
|
39 |
# - BAAI/bge-reranker-v2-m3
|
|
|
27 |
REDIS_PASSWORD: infini_rag_flow_helm
|
28 |
|
29 |
# The RAGFlow Docker image to download.
|
30 |
+
# Defaults to the v0.14.1-slim edition, which is the RAGFlow Docker image without embedding models.
|
31 |
+
RAGFLOW_IMAGE: infiniflow/ragflow:v0.14.1-slim
|
32 |
#
|
33 |
# To download the RAGFlow Docker image with embedding models, uncomment the following line instead:
|
34 |
+
# RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1
|
35 |
#
|
36 |
+
# The Docker image of the v0.14.1 edition includes:
|
37 |
# - Built-in embedding models:
|
38 |
# - BAAI/bge-large-zh-v1.5
|
39 |
# - BAAI/bge-reranker-v2-m3
|