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DOC: Miscellaneous UI and editorial updates (#7324)

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### What problem does this PR solve?



### Type of change


- [x] Documentation Update
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writinwaters
2025-04-27 11:44:08 +08:00
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@ -26,6 +26,38 @@ The "garbage in garbage out" status quo remains unchanged despite the fact that
---
### Differences between RAGFlow full edition and RAGFlow slim edition?
Each RAGFlow release is available in two editions:
- **Slim edition**: excludes built-in embedding models and is identified by a **-slim** suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0-slim`
- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0`
---
### Which embedding models can be deployed locally?
RAGFlow offers two Docker image editions, `v0.18.0-slim` and `v0.18.0`:
- `infiniflow/ragflow:v0.18.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.18.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`
- `maidalun1020/bce-embedding-base_v1`
- `maidalun1020/bce-reranker-base_v1`
- Embedding models that will be downloaded once you select them in the RAGFlow UI:
- `BAAI/bge-base-en-v1.5`
- `BAAI/bge-large-en-v1.5`
- `BAAI/bge-small-en-v1.5`
- `BAAI/bge-small-zh-v1.5`
- `jinaai/jina-embeddings-v2-base-en`
- `jinaai/jina-embeddings-v2-small-en`
- `nomic-ai/nomic-embed-text-v1.5`
- `sentence-transformers/all-MiniLM-L6-v2`
---
### Where to find the version of RAGFlow? How to interpret it?
You can find the RAGFlow version number on the **System** page of the UI:
@ -55,6 +87,14 @@ Where:
---
### Differences between demo.ragflow.io and a locally deployed open-source RAGFlow service?
demo.ragflow.io demonstrates the capabilities of RAGFlow Enterprise. Its DeepDoc models are pre-trained using proprietary data and it offers much more sophisticated team permission controls. Essentially, demo.ragflow.io serves as a preview of RAGFlow's forthcoming SaaS (Software as a Service) offering.
You can deploy an open-source RAGFlow service and call it from a Python client or through RESTful APIs. However, this is not supported on demo.ragflow.io.
---
### Why does it take longer for RAGFlow to parse a document than LangChain?
We put painstaking effort into document pre-processing tasks like layout analysis, table structure recognition, and OCR (Optical Character Recognition) using our vision models. This contributes to the additional time required.
@ -73,29 +113,6 @@ We officially support x86 CPU and nvidia GPU. While we also test RAGFlow on ARM6
---
### Which embedding models can be deployed locally?
RAGFlow offers two Docker image editions, `v0.18.0-slim` and `v0.18.0`:
- `infiniflow/ragflow:v0.18.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.18.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`
- `maidalun1020/bce-embedding-base_v1`
- `maidalun1020/bce-reranker-base_v1`
- Embedding models that will be downloaded once you select them in the RAGFlow UI:
- `BAAI/bge-base-en-v1.5`
- `BAAI/bge-large-en-v1.5`
- `BAAI/bge-small-en-v1.5`
- `BAAI/bge-small-zh-v1.5`
- `jinaai/jina-embeddings-v2-base-en`
- `jinaai/jina-embeddings-v2-small-en`
- `nomic-ai/nomic-embed-text-v1.5`
- `sentence-transformers/all-MiniLM-L6-v2`
---
### Do you offer an API for integration with third-party applications?
The corresponding APIs are now available. See the [RAGFlow HTTP API Reference](./references/http_api_reference.md) or the [RAGFlow Python API Reference](./references/python_api_reference.md) for more information.