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feat: Implement Milvus retriver for RAG (#516)

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* feat: Implement MilvusRetriever with embedding model and resource management

* chore: Update configuration and loader files for consistency

* chore: Clean up test_milvus.py for improved readability and organization

* feat: Add tests for DashscopeEmbeddings query and document embedding methods

* feat: Add tests for embedding model initialization and example file loading in MilvusProvider

* chore: Remove unused imports and clean up test_milvus.py for better readability

* chore: Clean up test_milvus.py for improved readability and organization

* chore: Clean up test_milvus.py for improved readability and organization

* fix: replace print statements with logging in recursion limit function

* Implement feature X to enhance user experience and optimize performance

* refactor: clean up unused imports and comments in AboutTab component

* Implement feature X to enhance user experience and fix bug Y in module Z

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
This commit is contained in:
CHANGXUBO
2025-09-12 22:20:55 +08:00
committed by GitHub
parent eec8e4dd60
commit dd9af1eb50
15 changed files with 1875 additions and 43 deletions
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23
.env.example
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@@ -41,6 +41,29 @@ TAVILY_API_KEY=tvly-xxx
# RAGFLOW_RETRIEVAL_SIZE=10
# RAGFLOW_CROSS_LANGUAGES=English,Chinese,Spanish,French,German,Japanese,Korean # Optional. To use RAGFlow's cross-language search, please separate each language with a single comma
# RAG_PROVIDER: milvus (using free milvus instance on zilliz cloud: https://docs.zilliz.com/docs/quick-start )
# RAG_PROVIDER=milvus
# MILVUS_URI=<endpoint_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_USER=<username_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_PASSWORD=<password_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_COLLECTION=documents
# MILVUS_EMBEDDING_PROVIDER=openai # support openai,dashscope
# MILVUS_EMBEDDING_BASE_URL=
# MILVUS_EMBEDDING_MODEL=
# MILVUS_EMBEDDING_API_KEY=
# MILVUS_AUTO_LOAD_EXAMPLES=true
# RAG_PROVIDER: milvus (using milvus lite on Mac or Linux)
# RAG_PROVIDER=milvus
# MILVUS_URI=./milvus_demo.db
# MILVUS_COLLECTION=documents
# MILVUS_EMBEDDING_PROVIDER=openai # support openai,dashscope
# MILVUS_EMBEDDING_BASE_URL=
# MILVUS_EMBEDDING_MODEL=
# MILVUS_EMBEDDING_API_KEY=
# MILVUS_AUTO_LOAD_EXAMPLES=true
# Optional, volcengine TTS for generating podcast
VOLCENGINE_TTS_APPID=xxx
VOLCENGINE_TTS_ACCESS_TOKEN=xxx