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feat: Qdrant Vector Search Support (#684)

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* feat: Qdrant vector search support

Signed-off-by: Anush008 <anushshetty90@gmail.com>

* chore: Review updates

Signed-off-by: Anush008 <anushshetty90@gmail.com>

---------

Signed-off-by: Anush008 <anushshetty90@gmail.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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Anush
2025-11-11 17:05:00 +05:30
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README.md
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@@ -183,10 +183,10 @@ SEARCH_API=tavily
### Private Knowledgebase
DeerFlow support private knowledgebase such as ragflow and vikingdb, so that you can use your private documents to answer questions.
DeerFlow supports private knowledgebase such as RAGFlow, Qdrant, Milvus, and VikingDB, so that you can use your private documents to answer questions.
- **[RAGFlow](https://ragflow.io/docs/dev/)**：open source RAG engine
```
- **[RAGFlow](https://ragflow.io/docs/dev/)**: open source RAG engine
```bash
# examples in .env.example
RAG_PROVIDER=ragflow
RAGFLOW_API_URL="http://localhost:9388"
@@ -195,6 +195,19 @@ DeerFlow support private knowledgebase such as ragflow and vikingdb, so that you
RAGFLOW_CROSS_LANGUAGES=English,Chinese,Spanish,French,German,Japanese,Korean
```
- **[Qdrant](https://qdrant.tech/)**: open source vector database
```bash
# Using Qdrant Cloud or self-hosted
RAG_PROVIDER=qdrant
QDRANT_LOCATION=https://xyz-example.eu-central.aws.cloud.qdrant.io:6333
QDRANT_API_KEY=your_qdrant_api_key
QDRANT_COLLECTION=documents
QDRANT_EMBEDDING_PROVIDER=openai
QDRANT_EMBEDDING_MODEL=text-embedding-ada-002
QDRANT_EMBEDDING_API_KEY=your_openai_api_key
QDRANT_AUTO_LOAD_EXAMPLES=true
```
## Features
### Core Capabilities
@@ -215,7 +228,9 @@ DeerFlow support private knowledgebase such as ragflow and vikingdb, so that you
- 📃 **RAG Integration**
- Supports mentioning files from [RAGFlow](https://github.com/infiniflow/ragflow) within the input box. [Start up RAGFlow server](https://ragflow.io/docs/dev/).
- Supports multiple vector databases: [Qdrant](https://qdrant.tech/), [Milvus](https://milvus.io/), [RAGFlow](https://github.com/infiniflow/ragflow), VikingDB, MOI, and Dify
- Supports mentioning files from RAG providers within the input box
- Easy switching between different vector databases through configuration
- 🔗 **MCP Seamless Integration**
- Expand capabilities for private domain access, knowledge graph, web browsing and more