### 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"
/>
