### What problem does this PR solve?
fix issues：https://github.com/infiniflow/ragflow/issues/10402
As the newly distributed embedding models support vector dimensions max
to 4096, while current OpenSearch's max dimension support is 1536.
As I tested, the 4096-dimensions vector will be treated as a float type
which is unacceptable in OpenSearch.
Besides, OpenSearch supports max to 16000 dimensions by defalut with the
vector engine(Faiss). According to:
https://docs.opensearch.org/2.19/field-types/supported-field-types/knn-methods-engines/
I added max to 10240 dimensions support for OpenSearch, as I think will
be sufficient in the future.
As I tested , it worked well on my own server (treated as knn_vector)by
using qwen3-embedding:8b as the embedding model:
<img width="1338" height="790" alt="image"
src="https://github.com/user-attachments/assets/a9b2d284-fcf6-4cea-859a-6aadccf36ace"
/>
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
By the way, I will still focus on the stuff about
Elasticsearch/Opensearch as search engines and vector databases.
Co-authored-by: 张雨豪 <zhangyh80@chinatelecom.cn>
### What problem does this PR solve?
This PR adds the support for latest OpenSearch2.19.1 as the store engine
& search engine option for RAGFlow.
### Main Benefit
1. OpenSearch2.19.1 is licensed under the [Apache v2.0 License] which is
much better than Elasticsearch
2. For search, OpenSearch2.19.1 supports full-text
search、vector_search、hybrid_search those are similar with Elasticsearch
on schema
3. For store, OpenSearch2.19.1 stores text、vector those are quite
simliar with Elasticsearch on schema
### Changes
- Support opensearch_python_connetor. I make a lot of adaptions since
the schema and api/method between ES and Opensearch differs in many
ways(especially the knn_search has a significant gap) :
rag/utils/opensearch_coon.py
- Support static config adaptions by changing:
conf/service_conf.yaml、api/settings.py、rag/settings.py
- Supprt some store&search schema changes between OpenSearch and ES:
conf/os_mapping.json
- Support OpenSearch python sdk : pyproject.toml
- Support docker config for OpenSearch2.19.1 :
docker/.env、docker/docker-compose-base.yml、docker/service_conf.yaml.template
### How to use
- I didn't change the priority that ES as the default doc/search engine.
Only if in docker/.env , we set DOC_ENGINE=${DOC_ENGINE:-opensearch}, it
will work.
### Others
Our team tested a lot of docs in our environment by using OpenSearch as
the vector database ,it works very well.
All the conifg for OpenSearch is necessary.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Yongteng Lei <yongtengrey@outlook.com>
Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com>
Co-authored-by: Yingfeng <yingfeng.zhang@gmail.com>
