### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
This PR introduces a new Docs Generator agent component for producing
downloadable PDF, DOCX, or TXT files from Markdown content generated
within a RAGFlow workflow.
### **Key Features**
**Backend**
- New component: DocsGenerator (agent/component/docs_generator.py)
-
- Markdown → PDF/DOCX/TXT conversion
-
- Supports tables, lists, code blocks, headings, and rich formatting
-
- Configurable document style (fonts, margins, colors, page size,
orientation)
-
- Optional header logo and footer with page numbers/timestamps
-
**Frontend**
- New configuration UI for the Docs Generator
-
- Download button integrated into the chat interface
-
- Output wired to the Message component
-
- Full i18n support
**Documentation**
Added component guide:
docs/guides/agent/agent_component_reference/docs_generator.md
**Usage**
Add the Docs Generator to a workflow, connect Markdown output from an
upstream component, configure metadata/style, and feed its output into
the Message component. Users will see a document download button
directly in the chat.
**Contributor Note**
We have been following RAGFlow since more than a year and half now and
have worked extensively on personalizing the framework and integrating
it into several of our internal systems. Over the past year and a half,
we have built multiple platforms that rely on RAGFlow as a core
component, which has given us a strong appreciation for how flexible and
powerful the project is.
We also previously contributed the full Italian translation, and we were
glad to see it accepted. This new Docs Generator component was created
for our own production needs, and we believe that it may be useful for
many others in the community as well.
We want to sincerely thank the entire RAGFlow team for the remarkable
work you have done and continue to do. If there are opportunities to
contribute further, we would be glad to help whenever we have time
available. It would be a pleasure to support the project in any way we
can.
If appropriate, we would be glad to be listed among the project’s
contributors, but in any case we look forward to continuing to support
and contribute to the project.
PentaFrame Development Team
---------
Co-authored-by: PentaFrame <info@pentaframe.it>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Update some docs and comments, since 'File manager' is rename to 'File'
### Type of change
- [x] Documentation Update
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com>
### What problem does this PR solve?
Introduced gpu profile in .env
Added Dockerfile_tei
fix datrie
Removed LIGHTEN flag
### Type of change
- [x] Documentation Update
- [x] Refactoring
### What problem does this PR solve?
Feat: Support attribute filtering #8703
### Type of change
- [X] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com>
Co-authored-by: writinwaters <cai.keith@gmail.com>
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.5 to v0.21.0
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.4 to v0.20.5
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.3 to v0.20.4
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.2 to v0.20.3
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.1 to v0.20.2
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
- Update version tags in README files (including translations) from
v0.20.0 to v0.20.1
- Modify Docker image references and documentation to reflect new
version
- Update version badges and image descriptions
- Maintain consistency across all language variants of README files
### Type of change
- [x] Documentation Update
### Description
This PR introduces two new environment variables, `DOC_BULK_SIZE` and
`EMBEDDING_BATCH_SIZE`, to allow flexible tuning of batch sizes for
document parsing and embedding vectorization in RAGFlow. By making these
parameters configurable, users can optimize performance and resource
usage according to their hardware capabilities and workload
requirements.
### What problem does this PR solve?
Previously, the batch sizes for document parsing and embedding were
hardcoded, limiting the ability to adjust throughput and memory
consumption. This PR enables users to set these values via environment
variables (in `.env`, Helm chart, or directly in the deployment
environment), improving flexibility and scalability for both small and
large deployments.
- `DOC_BULK_SIZE`: Controls how many document chunks are processed in a
single batch during document parsing (default: 4).
- `EMBEDDING_BATCH_SIZE`: Controls how many text chunks are processed
in a single batch during embedding vectorization (default: 16).
This change updates the codebase, documentation, and configuration files
to reflect the new options.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
- [ ] Refactoring
- [x] Performance Improvement
- [ ] Other (please describe):
### Additional context
- Updated `.env`, `helm/values.yaml`, and documentation to describe
the new variables.
- Modified relevant code paths to use the environment variables instead
of hardcoded values.
- Users can now tune these parameters to achieve better throughput or
reduce memory usage as needed.
Before:
Default value:
<img width="643" alt="image"
src="https://github.com/user-attachments/assets/086e1173-18f3-419d-a0f5-68394f63866a"
/>
After:
10x:
<img width="777" alt="image"
src="https://github.com/user-attachments/assets/5722bbc0-0bcb-4536-b928-077031e550f1"
/>
