From 06419a8ac4be73be8d1bed13448be6859edcccfc Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Thu, 12 Jun 2025 10:44:47 +0800
Subject: [PATCH 1/6] =?UTF-8?q?=E8=B0=83=E6=95=B4=E9=A1=B9=E7=9B=AE?=
=?UTF-8?q?=E7=9B=AE=E5=BD=95?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
llamacpp-embedding-rerank-server/README.md | 27 ++++++++++++++
.../docker-compose.yaml | 36 +++++++++++++++++++
.../.gitignore | 0
.../app/embedding_api.py | 0
.../app/embedding_onnx_provider.py | 0
.../app/log_config.py | 0
.../app/main.py | 0
.../app/model_service.py | 0
.../app/rerank_api.py | 0
.../app/rerank_onnx_provider.py | 0
.../requirements.txt | 0
.../run.sh | 2 +-
.../test/embedding_client.py | 0
.../test/http_client.py | 0
.../test/model_test.py | 0
.../test/rerank_client.py | 0
16 files changed, 64 insertions(+), 1 deletion(-)
create mode 100644 llamacpp-embedding-rerank-server/README.md
create mode 100644 llamacpp-embedding-rerank-server/docker-compose.yaml
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/.gitignore (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/embedding_api.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/embedding_onnx_provider.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/log_config.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/main.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/model_service.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/rerank_api.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/app/rerank_onnx_provider.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/requirements.txt (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/run.sh (69%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/test/embedding_client.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/test/http_client.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/test/model_test.py (100%)
rename {server/embedding-rerank-server => onnxruntime-embedding-rerank-server}/test/rerank_client.py (100%)
diff --git a/llamacpp-embedding-rerank-server/README.md b/llamacpp-embedding-rerank-server/README.md
new file mode 100644
index 0000000..478f3e7
--- /dev/null
+++ b/llamacpp-embedding-rerank-server/README.md
@@ -0,0 +1,27 @@
+# llama.cpp 部署 Embedding和Rerank模型
+
+## 下载模型
+
+`Embedding`: bge-m3
+
+`Rerank`: bge-reranker-v2-m3
+
+```shell
+cd /home
+mkdir models
+uv venv
+uv tool install modescope
+
+modelscope download --model gpustack/bge-m3-GGUF bge-m3-Q8_0.gguf --local_dir ./bge-m3-GGUF
+
+modescope modelscope download --model gpustack/bge-reranker-v2-m3-GGUF bge-reranker-v2-m3-Q8_0.gguf --local_dir ./bge-reranker-v2-m3-GGUF
+
+```
+
+## 部署模型
+
+```shell
+docker compose up -d
+```
+
+Embedding和Rerank模型服务支持标准OpenAI接口规范
\ No newline at end of file
diff --git a/llamacpp-embedding-rerank-server/docker-compose.yaml b/llamacpp-embedding-rerank-server/docker-compose.yaml
new file mode 100644
index 0000000..9b1b807
--- /dev/null
+++ b/llamacpp-embedding-rerank-server/docker-compose.yaml
@@ -0,0 +1,36 @@
+services:
+ llamacpp-embedding-server:
+ image: ghcr.io/ggml-org/llama.cpp:server
+ container_name: llamacpp-embedding-server
+ command: --embedding --pooling mean --verbose-prompt
+ restart: always
+ ports:
+ - 8081:8080
+ volumes:
+ - /home/models/bge-m3-GGUF:/models
+ environment:
+ LLAMA_ARG_MODEL: /models/bge-m3-Q8_0.gguf
+ LLAMA_ARG_CTX_SIZE: 8192
+ LLAMA_ARG_N_PARALLEL: 8
+ LLAMA_ARG_PORT: 8080
+ LLAMA_ARG_UBATCH: 8192
+ LLAMA_ARG_N_GPU_LAYERS_DRAFT: 0
+
+ llamacpp-rerank-server:
+ image: ghcr.io/ggml-org/llama.cpp:server
+ container_name: llamacpp-rerank-server
+ command: --reranking --pooling rank
+ restart: always
+ ports:
+ - 8082:8080
+ volumes:
+ - /home/models/bge-reranker-v2-m3-GGUF:/models
+ environment:
+ LLAMA_ARG_MODEL: /models/bge-reranker-v2-m3-Q8_0.gguf
+ LLAMA_ARG_CTX_SIZE: 8192
+ LLAMA_ARG_N_PARALLEL: 8
+ LLAMA_ARG_PORT: 8080
+ LLAMA_ARG_BATCH: 8192
+ LLAMA_ARG_UBATCH: 8192
+ LLAMA_ARG_FLASH_ATTN: enable
+ LLAMA_ARG_N_GPU_LAYERS_DRAFT: 0
diff --git a/server/embedding-rerank-server/.gitignore b/onnxruntime-embedding-rerank-server/.gitignore
similarity index 100%
rename from server/embedding-rerank-server/.gitignore
rename to onnxruntime-embedding-rerank-server/.gitignore
diff --git a/server/embedding-rerank-server/app/embedding_api.py b/onnxruntime-embedding-rerank-server/app/embedding_api.py
similarity index 100%
rename from server/embedding-rerank-server/app/embedding_api.py
rename to onnxruntime-embedding-rerank-server/app/embedding_api.py
diff --git a/server/embedding-rerank-server/app/embedding_onnx_provider.py b/onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py
similarity index 100%
rename from server/embedding-rerank-server/app/embedding_onnx_provider.py
rename to onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py
diff --git a/server/embedding-rerank-server/app/log_config.py b/onnxruntime-embedding-rerank-server/app/log_config.py
similarity index 100%
rename from server/embedding-rerank-server/app/log_config.py
rename to onnxruntime-embedding-rerank-server/app/log_config.py
diff --git a/server/embedding-rerank-server/app/main.py b/onnxruntime-embedding-rerank-server/app/main.py
similarity index 100%
rename from server/embedding-rerank-server/app/main.py
rename to onnxruntime-embedding-rerank-server/app/main.py
diff --git a/server/embedding-rerank-server/app/model_service.py b/onnxruntime-embedding-rerank-server/app/model_service.py
similarity index 100%
rename from server/embedding-rerank-server/app/model_service.py
rename to onnxruntime-embedding-rerank-server/app/model_service.py
diff --git a/server/embedding-rerank-server/app/rerank_api.py b/onnxruntime-embedding-rerank-server/app/rerank_api.py
similarity index 100%
rename from server/embedding-rerank-server/app/rerank_api.py
rename to onnxruntime-embedding-rerank-server/app/rerank_api.py
diff --git a/server/embedding-rerank-server/app/rerank_onnx_provider.py b/onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py
similarity index 100%
rename from server/embedding-rerank-server/app/rerank_onnx_provider.py
rename to onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py
diff --git a/server/embedding-rerank-server/requirements.txt b/onnxruntime-embedding-rerank-server/requirements.txt
similarity index 100%
rename from server/embedding-rerank-server/requirements.txt
rename to onnxruntime-embedding-rerank-server/requirements.txt
diff --git a/server/embedding-rerank-server/run.sh b/onnxruntime-embedding-rerank-server/run.sh
similarity index 69%
rename from server/embedding-rerank-server/run.sh
rename to onnxruntime-embedding-rerank-server/run.sh
index d05160a..851a96c 100644
--- a/server/embedding-rerank-server/run.sh
+++ b/onnxruntime-embedding-rerank-server/run.sh
@@ -1,4 +1,4 @@
-nohup python -u app/main.py > logs/app.log 2>&1 &
+nohup python -u app/main.py > app.log 2>&1 &
PID1=$!
# 生成close.sh脚本，写入kill命令
diff --git a/server/embedding-rerank-server/test/embedding_client.py b/onnxruntime-embedding-rerank-server/test/embedding_client.py
similarity index 100%
rename from server/embedding-rerank-server/test/embedding_client.py
rename to onnxruntime-embedding-rerank-server/test/embedding_client.py
diff --git a/server/embedding-rerank-server/test/http_client.py b/onnxruntime-embedding-rerank-server/test/http_client.py
similarity index 100%
rename from server/embedding-rerank-server/test/http_client.py
rename to onnxruntime-embedding-rerank-server/test/http_client.py
diff --git a/server/embedding-rerank-server/test/model_test.py b/onnxruntime-embedding-rerank-server/test/model_test.py
similarity index 100%
rename from server/embedding-rerank-server/test/model_test.py
rename to onnxruntime-embedding-rerank-server/test/model_test.py
diff --git a/server/embedding-rerank-server/test/rerank_client.py b/onnxruntime-embedding-rerank-server/test/rerank_client.py
similarity index 100%
rename from server/embedding-rerank-server/test/rerank_client.py
rename to onnxruntime-embedding-rerank-server/test/rerank_client.py
From ff0407f362c80ed86b5c0947938f1d564606bc6a Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Thu, 12 Jun 2025 11:04:23 +0800
Subject: [PATCH 2/6] rag-mcp-server
---
rag-mcp-server | 1 +
1 file changed, 1 insertion(+)
create mode 160000 rag-mcp-server
diff --git a/rag-mcp-server b/rag-mcp-server
new file mode 160000
index 0000000..4da900e
--- /dev/null
+++ b/rag-mcp-server
@@ -0,0 +1 @@
+Subproject commit 4da900e3a77b9382e3eb0e8f363830571ceae1e8
From 11b9f6677bea838ecf6d397a26e8c4bf01b73dbe Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Thu, 12 Jun 2025 11:07:33 +0800
Subject: [PATCH 3/6] rag-mivus-mcp-server
---
rag-mcp-server | 1 -
rag-milvus-mcp-server/.env | 4 +
rag-milvus-mcp-server/.gitignore | 10 +
rag-milvus-mcp-server/.python-version | 1 +
rag-milvus-mcp-server/README.md | 0
.../docker-compose-milvus.yaml | 66 ++
rag-milvus-mcp-server/embedding.py | 22 +
rag-milvus-mcp-server/http_json_client.py | 31 +
rag-milvus-mcp-server/main.py | 18 +
rag-milvus-mcp-server/milvus.py | 107 +++
rag-milvus-mcp-server/pyproject.toml | 11 +
rag-milvus-mcp-server/rerank.py | 34 +
rag-milvus-mcp-server/server.py | 49 ++
rag-milvus-mcp-server/setting.py | 36 +
rag-milvus-mcp-server/test.py | 8 +
rag-milvus-mcp-server/uv.lock | 671 ++++++++++++++++++
16 files changed, 1068 insertions(+), 1 deletion(-)
delete mode 160000 rag-mcp-server
create mode 100644 rag-milvus-mcp-server/.env
create mode 100644 rag-milvus-mcp-server/.gitignore
create mode 100644 rag-milvus-mcp-server/.python-version
create mode 100644 rag-milvus-mcp-server/README.md
create mode 100644 rag-milvus-mcp-server/docker-compose-milvus.yaml
create mode 100644 rag-milvus-mcp-server/embedding.py
create mode 100644 rag-milvus-mcp-server/http_json_client.py
create mode 100644 rag-milvus-mcp-server/main.py
create mode 100644 rag-milvus-mcp-server/milvus.py
create mode 100644 rag-milvus-mcp-server/pyproject.toml
create mode 100644 rag-milvus-mcp-server/rerank.py
create mode 100644 rag-milvus-mcp-server/server.py
create mode 100644 rag-milvus-mcp-server/setting.py
create mode 100644 rag-milvus-mcp-server/test.py
create mode 100644 rag-milvus-mcp-server/uv.lock
diff --git a/rag-mcp-server b/rag-mcp-server
deleted file mode 160000
index 4da900e..0000000
--- a/rag-mcp-server
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit 4da900e3a77b9382e3eb0e8f363830571ceae1e8
diff --git a/rag-milvus-mcp-server/.env b/rag-milvus-mcp-server/.env
new file mode 100644
index 0000000..25d9931
--- /dev/null
+++ b/rag-milvus-mcp-server/.env
@@ -0,0 +1,4 @@
+
+
+# Enable or disable security authorization
+MILVUS_AUTHORIZATION_ENABLED=true
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/.gitignore b/rag-milvus-mcp-server/.gitignore
new file mode 100644
index 0000000..505a3b1
--- /dev/null
+++ b/rag-milvus-mcp-server/.gitignore
@@ -0,0 +1,10 @@
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
diff --git a/rag-milvus-mcp-server/.python-version b/rag-milvus-mcp-server/.python-version
new file mode 100644
index 0000000..e4fba21
--- /dev/null
+++ b/rag-milvus-mcp-server/.python-version
@@ -0,0 +1 @@
+3.12
diff --git a/rag-milvus-mcp-server/README.md b/rag-milvus-mcp-server/README.md
new file mode 100644
index 0000000..e69de29
diff --git a/rag-milvus-mcp-server/docker-compose-milvus.yaml b/rag-milvus-mcp-server/docker-compose-milvus.yaml
new file mode 100644
index 0000000..8896c06
--- /dev/null
+++ b/rag-milvus-mcp-server/docker-compose-milvus.yaml
@@ -0,0 +1,66 @@
+services:
+ # Milvus vector database services
+ milvus-etcd:
+ container_name: milvus-etcd
+ image: quay.io/coreos/etcd:v3.5.5
+ environment:
+ ETCD_AUTO_COMPACTION_MODE: ${ETCD_AUTO_COMPACTION_MODE:-revision}
+ ETCD_AUTO_COMPACTION_RETENTION: ${ETCD_AUTO_COMPACTION_RETENTION:-1000}
+ ETCD_QUOTA_BACKEND_BYTES: ${ETCD_QUOTA_BACKEND_BYTES:-4294967296}
+ ETCD_SNAPSHOT_COUNT: ${ETCD_SNAPSHOT_COUNT:-50000}
+ volumes:
+ - ./volumes/milvus/etcd:/etcd
+ command: etcd -advertise-client-urls=http://127.0.0.1:2379 -listen-client-urls http://0.0.0.0:2379 --data-dir /etcd
+ healthcheck:
+ test: [ 'CMD', 'etcdctl', 'endpoint', 'health' ]
+ interval: 30s
+ timeout: 20s
+ retries: 3
+ networks:
+ - milvus
+
+ milvus-minio:
+ container_name: milvus-minio
+ image: minio/minio:RELEASE.2023-03-20T20-16-18Z
+ environment:
+ MINIO_ACCESS_KEY: ${MINIO_ACCESS_KEY:-minioadmin}
+ MINIO_SECRET_KEY: ${MINIO_SECRET_KEY:-minioadmin}
+ volumes:
+ - ./volumes/milvus/minio:/minio_data
+ command: minio server /minio_data --console-address ":9001"
+ healthcheck:
+ test: [ 'CMD', 'curl', '-f', 'http://localhost:9000/minio/health/live' ]
+ interval: 30s
+ timeout: 20s
+ retries: 3
+ networks:
+ - milvus
+
+ milvus-standalone:
+ container_name: milvus-standalone
+ image: milvusdb/milvus:v2.5.0-beta
+ command: [ 'milvus', 'run', 'standalone' ]
+ environment:
+ ETCD_ENDPOINTS: ${ETCD_ENDPOINTS:-milvus-etcd:2379}
+ MINIO_ADDRESS: ${MINIO_ADDRESS:-milvus-minio:9000}
+ common.security.authorizationEnabled: ${MILVUS_AUTHORIZATION_ENABLED:-true}
+ volumes:
+ - ./volumes/milvus/milvus:/var/lib/milvus
+ healthcheck:
+ test: [ 'CMD', 'curl', '-f', 'http://localhost:9091/healthz' ]
+ interval: 30s
+ start_period: 90s
+ timeout: 20s
+ retries: 3
+ depends_on:
+ - etcd
+ - minio
+ ports:
+ - 19530:19530
+ - 9091:9091
+ networks:
+ - milvus
+
+networks:
+ milvus:
+ driver: bridge
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/embedding.py b/rag-milvus-mcp-server/embedding.py
new file mode 100644
index 0000000..bf90cf7
--- /dev/null
+++ b/rag-milvus-mcp-server/embedding.py
@@ -0,0 +1,22 @@
+from abc import ABC, abstractmethod
+from typing import Union,List
+from http_json_client import HTTPJSONClient
+
+class EmbeddingClient(ABC,HTTPJSONClient):
+
+ @abstractmethod
+ def text_embedding(self, text: Union[str,List[str]]) -> Union[List,List[List]]:
+ pass
+
+class OpenAIEmbeddingClient(EmbeddingClient):
+
+ def __init__(self,base_url: str):
+ super().__init__(base_url)
+ self.endpoint = "/v1/embeddings"
+
+ def text_embedding(self, text: Union[str,List[str]]) -> Union[List,List[List]]:
+ result = self.post(self.endpoint,data= {"input":text})
+ data = result['data']
+ if isinstance(text,List):
+ return [dd['embedding'] for dd in data]
+ return data[0]['embedding']
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/http_json_client.py b/rag-milvus-mcp-server/http_json_client.py
new file mode 100644
index 0000000..387428a
--- /dev/null
+++ b/rag-milvus-mcp-server/http_json_client.py
@@ -0,0 +1,31 @@
+from typing import Dict,Any
+import requests
+
+
+class HTTPJSONClient:
+
+ def __init__(self,base_url: str):
+ self.base_url = base_url
+ self.session = requests.Session()
+ self.session.headers.update({
+ "Content-Type": "application/json",
+ "Accept": "application/json"
+ })
+
+ def post(self, endpoint: str, data: Dict[str, Any]) -> Dict[str, Any]:
+ base_url = self.base_url
+ if endpoint.startswith("/"):
+ endpoint = endpoint[1:]
+ if base_url.endswith("/"):
+ base_url = base_url[:-1]
+
+ url = f"{base_url}/{endpoint}"
+ try:
+ response = self.session.post(url, json=data)
+ return self._handle_response(response)
+ except requests.RequestException as e:
+ raise ValueError(f"Request failed: {str(e)}")
+
+ def _handle_response(self, response: requests.Response) -> Dict[str, Any]:
+ response.raise_for_status()
+ return response.json()
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/main.py b/rag-milvus-mcp-server/main.py
new file mode 100644
index 0000000..c65a573
--- /dev/null
+++ b/rag-milvus-mcp-server/main.py
@@ -0,0 +1,18 @@
+import argparse
+from dotenv import load_dotenv
+from server import mcp
+
+def parse_arguments():
+ # 解析命令行参数
+ parser = argparse.ArgumentParser(description="Rag-Mcp-Server")
+ parser.add_argument("--transport", choices=["stdio", "sse"], default="sse")
+
+ return parser.parse_args()
+
+if __name__ == "__main__":
+ # 加载.env文件
+ load_dotenv()
+ # 解析命令行参数
+ args = parse_arguments()
+ mcp.run(transport=args.transport)
+
diff --git a/rag-milvus-mcp-server/milvus.py b/rag-milvus-mcp-server/milvus.py
new file mode 100644
index 0000000..7c862c2
--- /dev/null
+++ b/rag-milvus-mcp-server/milvus.py
@@ -0,0 +1,107 @@
+from pymilvus import DataType, MilvusClient
+from pydantic import BaseModel
+from pymilvus.milvus_client import IndexParams
+from pymilvus.orm.schema import CollectionSchema
+from typing import Any, Optional,Dict,List
+from setting import MilvusSettings,RagSettings
+from embedding import EmbeddingClient
+
+Metadata = Dict[str, Any]
+
+class Entry(BaseModel):
+
+ content: str
+ metadata: Optional[Metadata] = None
+
+class MilvusConnector:
+ def __init__(self,
+ milvus_settings: MilvusSettings,
+ embedding_client: EmbeddingClient,
+ rag_settings: Optional[RagSettings] = None):
+ # 创建MilvusClient
+ self.client = MilvusClient(uri=milvus_settings.uri,
+ user=milvus_settings.user,
+ password=milvus_settings.password,
+ token=milvus_settings.token,
+ db_name=milvus_settings.db_name)
+
+ self.embedding_client = embedding_client
+ self.collection_name = rag_settings.collection_name
+ if rag_settings and not self.has_collection(rag_settings.collection_name):
+ # 定义schema,默认已存在id,vector字段,这里只需要定义document字段
+ schema = CollectionSchema()
+ schema.add_field("document", DataType.VARCHAR)
+ schema.add_field("metadata", DataType.JSON, nullable=True)
+ # 定义index
+ index_params = IndexParams()
+ index_params.add_index("vector","AUTOINDEX","vector_index")
+ self.create_collection(collection=rag_settings.collection_name,
+ dim=rag_settings.vector_dim,
+ schema= schema,
+ index_params=index_params
+ )
+
+ async def has_collection(self,collection_name: str) -> list[str]:
+ """查询是否存在collection"""
+ try:
+ return self.client.has_collection(collection_name)
+ except Exception as e:
+ raise ValueError(f"Failed to list collections: {str(e)}")
+
+ async def create_collection(self, collection_name: str, dim: int = 128, schema: Optional[CollectionSchema] = None, index_params: Optional[IndexParams] = None,) -> bool:
+ """从指定的schema创建collection"""
+ try:
+ # 检查collection是否已存在
+ if self.has_collection(collection_name):
+ raise ValueError(f"Collection '{collection_name}' already exists")
+ # 创建collection
+ self.client.create_collection(
+ collection_name=collection_name,
+ dimension=dim,
+ auto_id=True,
+ schema=schema,
+ index_params = index_params,
+ consistency_level = "Strong",
+ )
+ return True
+ except Exception as e:
+ raise ValueError(f"Failed to create collection: {str(e)}")
+
+ async def insert_data(self, entry: Entry) -> dict[str, Any]:
+ """插入数据到collection中"""
+ try:
+ vector = self.embedding_client.text_embedding(entry.content)
+ data = {
+ "document": entry.content,
+ "metadata": entry.metadata,
+ "vector": vector
+ }
+ return self.client.insert(collection_name=self.collection_name, data=data)
+ except Exception as e:
+ raise ValueError(f"Insert failed: {str(e)}")
+
+ async def search_collection(self, query_text: str, top_n: int = 5, score:float = 0.3) -> list[dict]:
+ """指定collection进行文本搜索"""
+ search_params = {"metric_type": "COSINE", "params": {"nprobe": 10}}
+ vector_data = self.embedding_client.text_embedding(query_text)
+ try:
+ result:List[List[dict]] = self.client.search(
+ collection_name=self.collection_name,
+ data=vector_data,
+ anns_field="vector",
+ search_params=search_params,
+ limit=20,
+ output_fields=["document"],
+ )
+ except Exception as e:
+ raise ValueError(f"Vector search failed: {str(e)}")
+
+ @classmethod
+ async def from_settings(cls,milvus_settings: MilvusSettings,rag_settings: RagSettings):
+ return cls(
+
+ )
+
+class MilvusContext:
+ def __init__(self, connector: MilvusConnector):
+ self.connector = connector
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/pyproject.toml b/rag-milvus-mcp-server/pyproject.toml
new file mode 100644
index 0000000..bc2fd35
--- /dev/null
+++ b/rag-milvus-mcp-server/pyproject.toml
@@ -0,0 +1,11 @@
+[project]
+name = "rag-mcp-server"
+version = "0.1.0"
+description = "MCP server for retrieving context from a milvus vector database"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+ "mcp[cli]>=1.9.3",
+ "pymilvus>=2.5.10",
+ "requests>=2.32.3",
+]
diff --git a/rag-milvus-mcp-server/rerank.py b/rag-milvus-mcp-server/rerank.py
new file mode 100644
index 0000000..63ecbd3
--- /dev/null
+++ b/rag-milvus-mcp-server/rerank.py
@@ -0,0 +1,34 @@
+from abc import ABC, abstractmethod
+from typing import Dict,Any,List
+from http_json_client import HTTPJSONClient
+
+class RerankClient(ABC,HTTPJSONClient):
+
+ @abstractmethod
+ def documents_rerank(self, query:str, documents: List[str], min_score:float) -> List[Dict[str, Any]]:
+ pass
+
+class OpenAIRerankClient(RerankClient):
+
+ def __init__(self,base_url: str):
+ super().__init__(base_url)
+ self.endpoint = "/v1/rerank"
+
+ def documents_rerank(self, query:str, documents: List[str]) -> List[Dict[str, Any]]:
+
+ result = self.post(self.endpoint,data= {"query": query, "documents": documents})
+ return result['results']
+
+"""
+{
+ 'model': 'gpt-3.5-turbo',
+ 'object': 'list',
+ 'usage': {'prompt_tokens': 246, 'total_tokens': 246},
+ 'results': [
+ {'index': 0, 'relevance_score': -3.395951271057129},
+ {'index': 1, 'relevance_score': -1.8673471212387085},
+ {'index': 2, 'relevance_score': 8.277612686157227},
+ {'index': 3, 'relevance_score': -11.033196449279785}
+ ]
+}
+"""
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/server.py b/rag-milvus-mcp-server/server.py
new file mode 100644
index 0000000..b6868f3
--- /dev/null
+++ b/rag-milvus-mcp-server/server.py
@@ -0,0 +1,49 @@
+import json
+from typing import AsyncIterator, Optional, List
+from contextlib import asynccontextmanager
+from mcp.server.fastmcp import Context, FastMCP
+from milvus import MilvusContext,MilvusConnector,Metadata,Entry
+from setting import TOOL_STORE_DESCRIPTION,TOOL_SEARCH_DESCRIPTION
+
+@asynccontextmanager
+async def server_lifespan(server: FastMCP) -> AsyncIterator[MilvusContext]:
+ """Milvus 连接 生命周期管理"""
+ config = server.config
+
+ connector = MilvusConnector(
+ uri=config.get("milvus_uri", "http://localhost:19530"),
+ token=config.get("milvus_token"),
+ db_name=config.get("db_name", "default"),
+ )
+
+ try:
+ yield MilvusContext(connector)
+ finally:
+ pass
+
+mcp = FastMCP("Rag-Mcp-Server", lifespan=server_lifespan)
+
+@mcp.tool(name="milvus-store", description=TOOL_STORE_DESCRIPTION)
+async def store(ctx: Context, information: str, metadata: Optional[Metadata] = None,) -> str:
+ connector:MilvusConnector = ctx.request_context.lifespan_context.connector
+ entry = Entry(content=information, metadata=metadata)
+ connector.insert_data(entry)
+ return f"Remembered: {information}"
+
+
+@mcp.tool(name="milvus-search", description=TOOL_SEARCH_DESCRIPTION)
+async def search(ctx: Context, query: str, top_n: int = 5, score:float = 0.3) -> List[str]:
+ connector:MilvusConnector = ctx.request_context.lifespan_context.connector
+
+ entries = connector.search_collection(query, top_n, score)
+ if not entries and len(entries) > 0:
+ return [f"No information searched for the query '{query}'"]
+
+ content = [f"Results for the query '{query}':"]
+ for entry in entries:
+ # 生成一个xml格式的结果，让LLM模型更容易解析
+ entry_metadata = json.dumps(entry.metadata) if entry.metadata else ""
+ content.append(f"{entry.content}{entry_metadata}")
+ return content
+
+
diff --git a/rag-milvus-mcp-server/setting.py b/rag-milvus-mcp-server/setting.py
new file mode 100644
index 0000000..cea66fe
--- /dev/null
+++ b/rag-milvus-mcp-server/setting.py
@@ -0,0 +1,36 @@
+from pydantic import Field
+from pydantic_settings import BaseSettings
+from typing import Optional
+
+TOOL_STORE_DESCRIPTION = """
+将文档存储到Milvus以供后续检索。
+
+输入参数：
+1. 'information' 参数应包含自然语言的文档内容，文本长度小于8000。
+2. 'metadata' 参数是一个Python字典，键为字符串，可以存储与该文档相关的元数据。
+"""
+
+TOOL_SEARCH_DESCRIPTION = """
+从Milvus中使用自然语言形式的文本来搜索相似性文档。
+
+输入参数：
+1. 'query' 参数应该描述你正在寻找的内容，文本长度小于8000，该工具将返回最相关的文档。
+2. 'top_n' 参数：要返回相似度最高的前n个文档，字段类型是int，默认值：5。
+2. 'score' 参数：要返回相似度大于或等于score的文档，字段类型是float，默认值：0.3。
+"""
+
+class MilvusSettings(BaseSettings):
+ """
+ Configuration for Tablestore.
+ """
+
+ uri: Optional[str] = Field(default= 'http://localhost:19530',validation_alias="MILVUS_URI")
+ user: Optional[str] = Field(default= '',validation_alias="MILVUS_USER")
+ password: Optional[str] = Field(default= '',validation_alias="MILVUS_PASSWORD")
+ token: Optional[str] = Field(default= '',validation_alias="MILVUS_TOKEN")
+ db_name: Optional[str] = Field(default= 'default',validation_alias="MILVUS_DB_NAME")
+
+class RagSettings(BaseSettings):
+ collection_name: str = Field(default="rag_mcp_server", validation_alias="RAG_COLLECTION_NAME")
+ vector_dim: int = Field(default=768, validation_alias="RAG_VECTOR_DIMENSION")
+
\ No newline at end of file
diff --git a/rag-milvus-mcp-server/test.py b/rag-milvus-mcp-server/test.py
new file mode 100644
index 0000000..e23cfd9
--- /dev/null
+++ b/rag-milvus-mcp-server/test.py
@@ -0,0 +1,8 @@
+from embedding import EmbeddingClient,OpenAIEmbeddingClient
+
+client:EmbeddingClient = OpenAIEmbeddingClient("http://192.168.0.160:8081")
+
+if __name__ == "__main__":
+ text = ["Hello World","China"]
+ res = client.text_embedding(text)
+ print(res)
diff --git a/rag-milvus-mcp-server/uv.lock b/rag-milvus-mcp-server/uv.lock
new file mode 100644
index 0000000..1b139ab
--- /dev/null
+++ b/rag-milvus-mcp-server/uv.lock
@@ -0,0 +1,671 @@
+version = 1
+revision = 2
+requires-python = ">=3.12"
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://repo.huaweicloud.com/repository/pypi/simple" }
+sdist = { url = "https://repo.huaweicloud.com/repository/pypi/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89" }
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+[[package]]
+name = "anyio"
+version = "4.9.0"
+source = { registry = "https://repo.huaweicloud.com/repository/pypi/simple" }
+dependencies = [
+ { name = "idna" },
+ { name = "sniffio" },
+ { name = "typing-extensions", marker = "python_full_version < '3.13'" },
+]
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+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/9f/76/2a63409fc05d34dd7d929357b7a45e3a2c96f22b4225cd74becd2ba6c4cb/ujson-5.10.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:621e34b4632c740ecb491efc7f1fcb4f74b48ddb55e65221995e74e2d00bbff0" },
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/45/ed/582c4daba0f3e1688d923b5cb914ada1f9defa702df38a1916c899f7c4d1/ujson-5.10.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b9500e61fce0cfc86168b248104e954fead61f9be213087153d272e817ec7b4f" },
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/d7/0c/9837fece153051e19c7bade9f88f9b409e026b9525927824cdf16293b43b/ujson-5.10.0-cp313-cp313-win32.whl", hash = "sha256:4c4fc16f11ac1612f05b6f5781b384716719547e142cfd67b65d035bd85af165" },
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/d7/72/6cb6728e2738c05bbe9bd522d6fc79f86b9a28402f38663e85a28fddd4a0/ujson-5.10.0-cp313-cp313-win_amd64.whl", hash = "sha256:4573fd1695932d4f619928fd09d5d03d917274381649ade4328091ceca175539" },
+]
+
+[[package]]
+name = "urllib3"
+version = "2.4.0"
+source = { registry = "https://repo.huaweicloud.com/repository/pypi/simple" }
+sdist = { url = "https://repo.huaweicloud.com/repository/pypi/packages/8a/78/16493d9c386d8e60e442a35feac5e00f0913c0f4b7c217c11e8ec2ff53e0/urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466" }
+wheels = [
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/6b/11/cc635220681e93a0183390e26485430ca2c7b5f9d33b15c74c2861cb8091/urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813" },
+]
+
+[[package]]
+name = "uvicorn"
+version = "0.34.3"
+source = { registry = "https://repo.huaweicloud.com/repository/pypi/simple" }
+dependencies = [
+ { name = "click" },
+ { name = "h11" },
+]
+sdist = { url = "https://repo.huaweicloud.com/repository/pypi/packages/de/ad/713be230bcda622eaa35c28f0d328c3675c371238470abdea52417f17a8e/uvicorn-0.34.3.tar.gz", hash = "sha256:35919a9a979d7a59334b6b10e05d77c1d0d574c50e0fc98b8b1a0f165708b55a" }
+wheels = [
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/6d/0d/8adfeaa62945f90d19ddc461c55f4a50c258af7662d34b6a3d5d1f8646f6/uvicorn-0.34.3-py3-none-any.whl", hash = "sha256:16246631db62bdfbf069b0645177d6e8a77ba950cfedbfd093acef9444e4d885" },
+]
From c453551b869540b82b1d1dfa36b2054e98ef605c Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Wed, 18 Jun 2025 10:55:45 +0800
Subject: [PATCH 4/6] =?UTF-8?q?llama.cpp=E6=A8=A1=E5=9E=8B=E9=83=A8?=
=?UTF-8?q?=E7=BD=B2=E6=9E=84=E5=BB=BA?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
llamacpp-embedding-rerank-server/README.md | 113 ++++++++++++++++++++-
1 file changed, 110 insertions(+), 3 deletions(-)
diff --git a/llamacpp-embedding-rerank-server/README.md b/llamacpp-embedding-rerank-server/README.md
index 478f3e7..88dee9c 100644
--- a/llamacpp-embedding-rerank-server/README.md
+++ b/llamacpp-embedding-rerank-server/README.md
@@ -1,5 +1,72 @@
# llama.cpp 部署 Embedding和Rerank模型
+## ARM架构下编译llama.cpp
+
+1. 下载llama.cpp源码
+```shell
+cd /home
+git clone https://github.com/ggml-org/llama.cpp.git
+```
+
+2. 拉取``ubuntu:22.04``镜像
+
+```shell
+docker pull ubuntu:22.04
+docker run -itd -v /home/llama.cpp:/home/llama.cpp ubuntu:22.04 --name ubuntu_llamacpp
+
+docker exec -it ubuntu_llamacpp /bin/bash
+```
+
+3. 容器内编译
+
+```shell
+apt-get update
+apt-get install -y git cmake libcurl4-openssl-dev build-essential
+cmake -B build
+cmake --build build --config Release -j 8
+```
+
+4. 宿主机上构建llama.cpp镜像
+
+经过在上面容器内编译的步骤，``/home/llama.cpp``下新增``build``文件夹，里面就是基于``ubuntu:22.04``镜像环境编译的llama.cpp的库文件。下面就可根据这些文件再基于``ubuntu:22.04``构建``llama.cpp-arm64:server``镜像。
+
+```shell
+cd /home/llama.cpp
+mkdir -p docker/lib
+cp -r ../build/bin/*.so ./docker/lib/
+cp ../build/bin/llama-server ./docker/llama-server
+vi Dockerfile
+```
+
+``Dockerfile``内容
+
+```shell
+FROM ubuntu:22.04
+
+RUN apt-get update \
+ && apt-get install -y libgomp1 curl \
+ && apt autoremove -y \
+ && apt clean -y \
+ && rm -rf /tmp/* /var/tmp/* \
+ && find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
+ && find /var/cache -type f -delete
+
+COPY lib/ /app
+COPY llama-server /app
+
+ENV LLAMA_ARG_HOST=0.0.0.0
+
+WORKDIR /app
+
+ENTRYPOINT ["/app/llama-server"]
+```
+
+构建镜像
+
+```shell
+docker build -t llama.cpp-arm64:server .
+```
+
## 下载模型
`Embedding`: bge-m3
@@ -7,15 +74,55 @@
`Rerank`: bge-reranker-v2-m3
```shell
+pip config set global.index-url https://repo.huaweicloud.com/repository/pypi/simple
+pip install modelscope
cd /home
mkdir models
-uv venv
-uv tool install modescope
+cd models
+modelscope download --model gpustack/bge-reranker-v2-m3-GGUF bge-reranker-v2-m3-Q8_0.gguf --local_dir ./bge-reranker-v2-m3-GGUF
modelscope download --model gpustack/bge-m3-GGUF bge-m3-Q8_0.gguf --local_dir ./bge-m3-GGUF
+```
-modescope modelscope download --model gpustack/bge-reranker-v2-m3-GGUF bge-reranker-v2-m3-Q8_0.gguf --local_dir ./bge-reranker-v2-m3-GGUF
+## 编制docker-compose文件
+
+```shell
+services:
+ llamacpp-embedding-server:
+ image: llama.cpp-arm64:server
+ container_name: llamacpp-embedding-server
+ command: --embedding --pooling mean --verbose-prompt
+ restart: always
+ ports:
+ - 8081:8080
+ volumes:
+ - /home/models/bge-m3-GGUF:/models
+ environment:
+ LLAMA_ARG_MODEL: /models/bge-m3-Q8_0.gguf
+ LLAMA_ARG_CTX_SIZE: 8192
+ LLAMA_ARG_N_PARALLEL: 8
+ LLAMA_ARG_PORT: 8080
+ LLAMA_ARG_UBATCH: 8192
+ LLAMA_ARG_N_GPU_LAYERS_DRAFT: 0
+ llamacpp-rerank-server:
+ image: llama.cpp-arm64:server
+ container_name: llamacpp-rerank-server
+ command: --reranking --pooling rank
+ restart: always
+ ports:
+ - 8082:8080
+ volumes:
+ - /home/models/bge-reranker-v2-m3-GGUF:/models
+ environment:
+ LLAMA_ARG_MODEL: /models/bge-reranker-v2-m3-Q8_0.gguf
+ LLAMA_ARG_CTX_SIZE: 8192
+ LLAMA_ARG_N_PARALLEL: 8
+ LLAMA_ARG_PORT: 8080
+ LLAMA_ARG_BATCH: 8192
+ LLAMA_ARG_UBATCH: 8192
+ LLAMA_ARG_FLASH_ATTN: enable
+ LLAMA_ARG_N_GPU_LAYERS_DRAFT: 0
```
## 部署模型
From 55b4719afd44f1252b5e8fcb81c88e386d8cdeb4 Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Mon, 23 Jun 2025 09:19:12 +0800
Subject: [PATCH 5/6] =?UTF-8?q?=E9=80=82=E9=85=8D=E6=96=B0=E7=89=88?=
=?UTF-8?q?=E7=9A=84transformer?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
.../.python-version | 1 +
onnxruntime-embedding-rerank-server/README.md | 0
.../app/download_model.py | 19 +
.../app/embedding_api.py | 13 +-
.../app/embedding_onnx_provider.py | 5 +-
.../app/log_config.py | 52 --
.../app/main.py | 73 +-
.../app/rerank_api.py | 9 +-
.../app/rerank_onnx_provider.py | 6 +-
.../pyproject.toml | 14 +
.../requirements.txt | 4 -
onnxruntime-embedding-rerank-server/run.sh | 2 +-
onnxruntime-embedding-rerank-server/stop.sh | 2 +
onnxruntime-embedding-rerank-server/uv.lock | 660 ++++++++++++++++++
14 files changed, 742 insertions(+), 118 deletions(-)
create mode 100644 onnxruntime-embedding-rerank-server/.python-version
create mode 100644 onnxruntime-embedding-rerank-server/README.md
create mode 100644 onnxruntime-embedding-rerank-server/app/download_model.py
delete mode 100644 onnxruntime-embedding-rerank-server/app/log_config.py
create mode 100644 onnxruntime-embedding-rerank-server/pyproject.toml
delete mode 100644 onnxruntime-embedding-rerank-server/requirements.txt
create mode 100644 onnxruntime-embedding-rerank-server/stop.sh
create mode 100644 onnxruntime-embedding-rerank-server/uv.lock
diff --git a/onnxruntime-embedding-rerank-server/.python-version b/onnxruntime-embedding-rerank-server/.python-version
new file mode 100644
index 0000000..e4fba21
--- /dev/null
+++ b/onnxruntime-embedding-rerank-server/.python-version
@@ -0,0 +1 @@
+3.12
diff --git a/onnxruntime-embedding-rerank-server/README.md b/onnxruntime-embedding-rerank-server/README.md
new file mode 100644
index 0000000..e69de29
diff --git a/onnxruntime-embedding-rerank-server/app/download_model.py b/onnxruntime-embedding-rerank-server/app/download_model.py
new file mode 100644
index 0000000..3a72245
--- /dev/null
+++ b/onnxruntime-embedding-rerank-server/app/download_model.py
@@ -0,0 +1,19 @@
+import os
+from modelscope import snapshot_download
+
+# 当前文件的绝对路径
+filepath = os.path.abspath(__file__)
+models_dir = os.path.join(os.path.dirname(os.path.dirname(filepath)), "models")
+os.makedirs(models_dir, exist_ok=True)
+
+def download_embedding_models():
+ embedding_dir = os.path.join(models_dir,"bce-embedding-base_v1")
+ if not os.path.exists(embedding_dir):
+ snapshot_download(model_id='netease-youdao/bce-embedding-base_v1',local_dir = embedding_dir)
+ return embedding_dir
+
+def download_rerank_models():
+ reranker_dir = os.path.join(models_dir,"bce-reranker-base_v1")
+ if not os.path.exists(reranker_dir):
+ snapshot_download(model_id='netease-youdao/bce-reranker-base_v1',local_dir = reranker_dir)
+ return reranker_dir
\ No newline at end of file
diff --git a/onnxruntime-embedding-rerank-server/app/embedding_api.py b/onnxruntime-embedding-rerank-server/app/embedding_api.py
index a0e54fd..0f29493 100644
--- a/onnxruntime-embedding-rerank-server/app/embedding_api.py
+++ b/onnxruntime-embedding-rerank-server/app/embedding_api.py
@@ -1,10 +1,13 @@
-from fastapi import APIRouter, Request, HTTPException
-from typing import List,Union,Optional
-from pydantic import BaseModel,Field
-from uuid import uuid4
-from log_config import logger
+from fastapi import APIRouter, Request
+from typing import List,Union
+from pydantic import BaseModel
from model_service import EmbeddingService
import time
+import logging
+
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
embedding_router = APIRouter(tags=['Embedding'])
diff --git a/onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py b/onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py
index 73438d6..57aed74 100644
--- a/onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py
+++ b/onnxruntime-embedding-rerank-server/app/embedding_onnx_provider.py
@@ -1,8 +1,7 @@
from onnxruntime import InferenceSession
-from transformers import AutoTokenizer
+from transformers import XLMRobertaTokenizer
from concurrent.futures import ThreadPoolExecutor
from typing import List
-from log_config import logger
import numpy as np
import os
@@ -13,7 +12,7 @@ def __init__(self,embed_path:str,**kwargs):
if not os.path.isfile(embed_model_path):
raise ValueError(f"{embed_model_path} 文件不存在")
self.workers = kwargs.get('workers', 8)
- self._tokenizer = AutoTokenizer.from_pretrained(embed_path)
+ self._tokenizer = XLMRobertaTokenizer.from_pretrained(embed_path)
providers = ['CPUExecutionProvider']
self._session = InferenceSession(embed_model_path, providers=providers)
self.thread_pool = ThreadPoolExecutor(max_workers=self.workers)
diff --git a/onnxruntime-embedding-rerank-server/app/log_config.py b/onnxruntime-embedding-rerank-server/app/log_config.py
deleted file mode 100644
index e310faa..0000000
--- a/onnxruntime-embedding-rerank-server/app/log_config.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import os
-import logging
-import logging.config
-from typing import Any
-
-LOG_PATH = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "logs")
-os.makedirs(LOG_PATH, exist_ok=True)
-
-LOGGING_CONFIG: dict[str, Any] = {
- "version": 1,
- "disable_existing_loggers": False,
- "formatters": {
- "default": {
- "()": "uvicorn.logging.DefaultFormatter",
- "fmt": "%(asctime)s %(levelprefix)s %(message)s",
- "use_colors": None,
- },
- "access": {
- "()": "uvicorn.logging.AccessFormatter",
- "fmt": '%(asctime)s %(levelprefix)s %(client_addr)s - "%(request_line)s" %(status_code)s',
- },
- },
- "handlers": {
- "default": {
- "formatter": "default",
- "class": "logging.StreamHandler",
- "stream": "ext://sys.stderr",
- },
- "access": {
- "formatter": "access",
- "class": "logging.StreamHandler",
- "stream": "ext://sys.stdout",
- },
- # "file": {
- # "formatter": "default",
- # "encoding": "utf-8",
- # "class": "logging.handlers.RotatingFileHandler",
- # "filename": os.path.join(LOG_PATH, "server_info.log"),
- # "maxBytes": 1024 * 1024 * 50,
- # "backupCount": 5,
- # },
- },
- "loggers": {
- "uvicorn": {"handlers": ["default"], "level": "INFO", "propagate": False},
- "uvicorn.error": {"level": "INFO"},
- "uvicorn.access": {"handlers": ["access"], "level": "INFO", "propagate": False},
- "app": {"handlers": ["default"], "level": "INFO", "propagate": False},
- },
-}
-
-logging.config.dictConfig(LOGGING_CONFIG)
-logger = logging.getLogger("app")
\ No newline at end of file
diff --git a/onnxruntime-embedding-rerank-server/app/main.py b/onnxruntime-embedding-rerank-server/app/main.py
index 59397cd..3962d94 100644
--- a/onnxruntime-embedding-rerank-server/app/main.py
+++ b/onnxruntime-embedding-rerank-server/app/main.py
@@ -3,60 +3,41 @@
from model_service import EmbeddingService,RerankService
from embedding_api import embedding_router
from rerank_api import rerank_router
-from modelscope import snapshot_download,model_file_download
-from log_config import logger,LOGGING_CONFIG
+from download_model import download_embedding_models,download_rerank_models
+import logging
import os
import uvicorn
-# 当前文件的绝对路径
-filepath = os.path.abspath(__file__)
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
-def download_models():
- models_dir = os.path.join(os.path.dirname(os.path.dirname(filepath)), "models")
- os.makedirs(models_dir, exist_ok=True)
+EMBEDDING_MODEL_PATH = os.getenv("LOCAL_EMBEDDING_MODEL_PATH",download_embedding_models())
+RERANK_MODEL_PATH = os.getenv("LOCAL_RERANK_MODEL_PATH",download_rerank_models())
- # embedding model
- embedding_dir = os.path.join(models_dir,"bce_embedding_base")
- if not os.path.exists(embedding_dir):
- snapshot_download(model_id='netease-youdao/bce-embedding-base_v1',local_dir = embedding_dir)
- model_file_download(model_id='maidalun/bce-embedding-base_v1',file_path='tokenizer_config.json',local_dir=embedding_dir)
- model_file_download(model_id='maidalun/bce-embedding-base_v1',file_path='tokenizer.json',local_dir=embedding_dir)
-
- # reranker
- reranker_dir = os.path.join(models_dir,"bce_reranker_base")
- if not os.path.exists(reranker_dir):
- snapshot_download(model_id='netease-youdao/bce-reranker-base_v1',local_dir = reranker_dir)
- model_file_download(model_id='maidalun/bce-reranker-base_v1',file_path='tokenizer_config.json',local_dir=reranker_dir)
- model_file_download(model_id='maidalun/bce-reranker-base_v1',file_path='tokenizer.json',local_dir=reranker_dir)
- return embedding_dir,reranker_dir
+logger.info(f"EMBEDDING_MODEL_PATH:{EMBEDDING_MODEL_PATH}")
+logger.info(f"RERANK_MODEL_PATH:{RERANK_MODEL_PATH}")
-def create_app(embedding_dir,reranker_dir) -> FastAPI:
- @asynccontextmanager
- async def lifespan(app:FastAPI):
- """生命周期"""
- app.state.embed_engine = EmbeddingService(embedding_dir, 8)
- app.state.rerank_engine = RerankService(reranker_dir, 8)
- logger.info("应用初始化成功")
- yield
- logger.info("应用正常停止")
+@asynccontextmanager
+async def lifespan(app:FastAPI):
+ """生命周期"""
+ app.state.embed_engine = EmbeddingService(EMBEDDING_MODEL_PATH, 8)
+ app.state.rerank_engine = RerankService(RERANK_MODEL_PATH, 8)
+ logger.info("应用初始化成功")
+ yield
+ logger.info("应用正常停止")
- # 创建应用
- app = FastAPI(
- title="Embedding Inference Server",
- lifespan=lifespan,
- root_path="/v1",
- version="1.0",
- license_info={"name":"Apache License 2.0","identifier":"Apache"}
- )
+# 创建应用
+app = FastAPI(
+ title="Embedding and Reranker Inference Server",
+ lifespan=lifespan,
+ root_path="/v1",
+ version="1.0",
+ license_info={"name":"Apache License 2.0","identifier":"Apache"}
+ )
- app.include_router(embedding_router)
- app.include_router(rerank_router)
- return app
+app.include_router(embedding_router)
+app.include_router(rerank_router)
if __name__ == "__main__":
- # 下载模型
- embedding_dir,reranker_dir = download_models()
- # 创建应用
- app = create_app(embedding_dir,reranker_dir)
# 启动应用
- uvicorn.run(app, host="0.0.0.0", port=9997,log_config=LOGGING_CONFIG)
\ No newline at end of file
+ uvicorn.run(app, host="0.0.0.0", port=9997)
\ No newline at end of file
diff --git a/onnxruntime-embedding-rerank-server/app/rerank_api.py b/onnxruntime-embedding-rerank-server/app/rerank_api.py
index 95f2fb9..e68f70a 100644
--- a/onnxruntime-embedding-rerank-server/app/rerank_api.py
+++ b/onnxruntime-embedding-rerank-server/app/rerank_api.py
@@ -1,10 +1,13 @@
from fastapi import APIRouter, Request
from typing import List
-from pydantic import BaseModel,Field
+from pydantic import BaseModel
from uuid import uuid4
-from log_config import logger
from model_service import RerankService
import time
+import logging
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
rerank_router = APIRouter(tags=['Rerank'])
@@ -40,7 +43,7 @@ def text_rerank(request: Request,rerank_request:RerankRequest) -> RerankResponse
results = engine.execute(query,documents,top_n,return_documents)
# usage = Usage(prompt_tokens=len(documents),total_tokens=total_tokens)
- logger.info("请求结果:\n%s\n耗时 %.4f ms",results,(time.perf_counter() - start_time) * 1000)
+ logger.info("请求耗时 %.4f ms,返回结果:\n%s",(time.perf_counter() - start_time) * 1000, results)
rerankResult = [
RerankResult(
index = result['id'],
diff --git a/onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py b/onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py
index 1f1c98c..235deae 100644
--- a/onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py
+++ b/onnxruntime-embedding-rerank-server/app/rerank_onnx_provider.py
@@ -1,8 +1,7 @@
import onnxruntime as ort
-from transformers import AutoTokenizer
+from transformers import XLMRobertaTokenizer
from typing import List
from copy import deepcopy
-from log_config import logger
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import os
@@ -21,7 +20,7 @@ def __init__(self,rerank_path,**kwargs):
# 判断文件是否存在
if not os.path.isfile(rerank_model_path):
raise ValueError(f"{rerank_model_path} 文件不存在")
- self._tokenizer = AutoTokenizer.from_pretrained(rerank_path)
+ self._tokenizer = XLMRobertaTokenizer.from_pretrained(rerank_path)
self.sep_id = self._tokenizer.sep_token_id
self.overlap_tokens = kwargs.get('overlap_tokens', 80)
self.max_length = kwargs.get('max_length', 512)
@@ -30,7 +29,6 @@ def __init__(self,rerank_path,**kwargs):
self.session = ort.InferenceSession(rerank_model_path, providers=providers)
self.thread_pool = ThreadPoolExecutor(max_workers=self.workers)
-
def tokenize_preproc(self, query: str, passages: List[str]):
def _merge_inputs(chunk1_raw, chunk2):
diff --git a/onnxruntime-embedding-rerank-server/pyproject.toml b/onnxruntime-embedding-rerank-server/pyproject.toml
new file mode 100644
index 0000000..713e1a3
--- /dev/null
+++ b/onnxruntime-embedding-rerank-server/pyproject.toml
@@ -0,0 +1,14 @@
+[project]
+name = "onnxruntime-embedding-rerank-server"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+ "fastapi>=0.115.13",
+ "modelscope>=1.27.1",
+ "onnxruntime>=1.22.0",
+ "sentencepiece>=0.2.0",
+ "tiktoken>=0.9.0",
+ "transformers>=4.52.4",
+]
diff --git a/onnxruntime-embedding-rerank-server/requirements.txt b/onnxruntime-embedding-rerank-server/requirements.txt
deleted file mode 100644
index 7ae27e3..0000000
--- a/onnxruntime-embedding-rerank-server/requirements.txt
+++ /dev/null
@@ -1,4 +0,0 @@
-fastapi[standard]
-onnxruntime
-transformers
-modelscope
\ No newline at end of file
diff --git a/onnxruntime-embedding-rerank-server/run.sh b/onnxruntime-embedding-rerank-server/run.sh
index 851a96c..edfb7d5 100644
--- a/onnxruntime-embedding-rerank-server/run.sh
+++ b/onnxruntime-embedding-rerank-server/run.sh
@@ -1,4 +1,4 @@
-nohup python -u app/main.py > app.log 2>&1 &
+nohup uv run app/main.py > app.log 2>&1 &
PID1=$!
# 生成close.sh脚本，写入kill命令
diff --git a/onnxruntime-embedding-rerank-server/stop.sh b/onnxruntime-embedding-rerank-server/stop.sh
new file mode 100644
index 0000000..4458fc9
--- /dev/null
+++ b/onnxruntime-embedding-rerank-server/stop.sh
@@ -0,0 +1,2 @@
+#!/bin/bash
+kill -9 28070
diff --git a/onnxruntime-embedding-rerank-server/uv.lock b/onnxruntime-embedding-rerank-server/uv.lock
new file mode 100644
index 0000000..c3b1a06
--- /dev/null
+++ b/onnxruntime-embedding-rerank-server/uv.lock
@@ -0,0 +1,660 @@
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+revision = 2
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+dependencies = [
+ { name = "filelock" },
+ { name = "huggingface-hub" },
+ { name = "numpy" },
+ { name = "packaging" },
+ { name = "pyyaml" },
+ { name = "regex" },
+ { name = "requests" },
+ { name = "safetensors" },
+ { name = "tokenizers" },
+ { name = "tqdm" },
+]
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+dependencies = [
+ { name = "typing-extensions" },
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+[[package]]
+name = "urllib3"
+version = "2.5.0"
+source = { registry = "https://repo.huaweicloud.com/repository/pypi/simple" }
+sdist = { url = "https://repo.huaweicloud.com/repository/pypi/packages/15/22/9ee70a2574a4f4599c47dd506532914ce044817c7752a79b6a51286319bc/urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760" }
+wheels = [
+ { url = "https://repo.huaweicloud.com/repository/pypi/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc" },
+]
From 32d578bcfe35fc7bfa34e75b70d46e35dc6c3a34 Mon Sep 17 00:00:00 2001
From: szlele <595128841@qq.com>
Date: Tue, 29 Jul 2025 15:25:24 +0800
Subject: [PATCH 6/6] =?UTF-8?q?=E6=8F=90=E4=BA=A4=E5=9F=BA=E4=BA=8Enpu?=
=?UTF-8?q?=E7=9A=84server?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
.../test/rerank_client.py | 4 +-
vllm-ascend-rerank-server/main.py | 61 ++++++
vllm-ascend-rerank-server/rerank_provider.py | 43 ++++
vllm-ascend-rerank-server/test.py | 29 +++
vllm-embedding-rerank-server/.python-version | 1 +
vllm-embedding-rerank-server/Dockerfile | 14 ++
vllm-embedding-rerank-server/README.md | 1 +
.../app/embedding_provider.py | 19 ++
vllm-embedding-rerank-server/app/main.py | 63 ++++++
vllm-embedding-rerank-server/app/models.py | 19 ++
vllm-embedding-rerank-server/app/test.py | 10 +
vllm-embedding-rerank-server/pyproject.toml | 10 +
vllm-embedding-rerank-server/uv.lock | 207 ++++++++++++++++++
13 files changed, 479 insertions(+), 2 deletions(-)
create mode 100644 vllm-ascend-rerank-server/main.py
create mode 100644 vllm-ascend-rerank-server/rerank_provider.py
create mode 100644 vllm-ascend-rerank-server/test.py
create mode 100644 vllm-embedding-rerank-server/.python-version
create mode 100644 vllm-embedding-rerank-server/Dockerfile
create mode 100644 vllm-embedding-rerank-server/README.md
create mode 100644 vllm-embedding-rerank-server/app/embedding_provider.py
create mode 100644 vllm-embedding-rerank-server/app/main.py
create mode 100644 vllm-embedding-rerank-server/app/models.py
create mode 100644 vllm-embedding-rerank-server/app/test.py
create mode 100644 vllm-embedding-rerank-server/pyproject.toml
create mode 100644 vllm-embedding-rerank-server/uv.lock
diff --git a/onnxruntime-embedding-rerank-server/test/rerank_client.py b/onnxruntime-embedding-rerank-server/test/rerank_client.py
index 106cad8..c5cb623 100644
--- a/onnxruntime-embedding-rerank-server/test/rerank_client.py
+++ b/onnxruntime-embedding-rerank-server/test/rerank_client.py
@@ -2,7 +2,7 @@
import numpy as np
import string
-client = HttpClient("http://127.0.0.1:9997/v1")
+client = HttpClient("http://115.120.51.57:11558/v1")
query = "抗生素是谁发现的？请说明发现过程和时间。"
documents = [
@@ -14,7 +14,7 @@
]
payload = {
- "model": "bce",
+ "model": "Qwen/Qwen3-Reranker-8B",
"query": query,
"documents": documents,
"top_n": 3, # 可选参数
diff --git a/vllm-ascend-rerank-server/main.py b/vllm-ascend-rerank-server/main.py
new file mode 100644
index 0000000..bc1f973
--- /dev/null
+++ b/vllm-ascend-rerank-server/main.py
@@ -0,0 +1,61 @@
+import os,uvicorn
+from pydantic import BaseModel
+from fastapi import FastAPI,Request
+from fastapi.concurrency import asynccontextmanager
+from rerank_provider import RerankProvider
+
+@asynccontextmanager
+async def lifespan(app:FastAPI):
+ app.state.rerank_engine = RerankProvider()
+ yield
+ app.state.rerank_engine.destroy()
+
+app = FastAPI(
+ title="Rerank Inference Server",
+ lifespan=lifespan,
+ root_path="/v1",
+ version="1.0",
+ license_info={"name":"Apache License 2.0","identifier":"Apache"}
+ )
+
+class RerankRequest(BaseModel):
+ model: str
+ query: str
+ top_n: int
+ return_documents: bool
+ documents: list[str]
+
+class RerankData(BaseModel):
+ index: int
+ relevance_score: float
+ document: str
+
+class RerankResponse(BaseModel):
+ model: str
+ results: list[RerankData]
+
+@app.post("/rerank", response_model=RerankResponse, summary="文本重排序")
+def text_rerank(request: Request,rerank_request:RerankRequest) -> RerankResponse:
+ query = rerank_request.query
+ documents = rerank_request.documents
+ top_n = rerank_request.top_n
+ return_documents = rerank_request.return_documents
+
+ engine:RerankProvider = request.app.state.rerank_engine
+ results = engine.rerank(query,documents,top_n,return_documents)
+
+ rerank_datas = [
+ RerankData(
+ index = result['id'],
+ relevance_score = result['score'],
+ document = result['document'],
+ )
+ for result in results
+ ]
+ return RerankResponse(
+ model = rerank_request.model,
+ results = rerank_datas
+ )
+
+if __name__ == "__main__":
+ uvicorn.run(app, host="0.0.0.0", port=8000)
\ No newline at end of file
diff --git a/vllm-ascend-rerank-server/rerank_provider.py b/vllm-ascend-rerank-server/rerank_provider.py
new file mode 100644
index 0000000..8dcff73
--- /dev/null
+++ b/vllm-ascend-rerank-server/rerank_provider.py
@@ -0,0 +1,43 @@
+import heapq
+from vllm.distributed.parallel_state import destroy_model_parallel
+from vllm import LLM
+from typing import List
+
+class RerankProvider:
+
+ def __init__(self):
+ self.prefix = '<|im_start|>system\nJudge whether the Document meets the requirements based on the Query and the Instruct provided. Note that the answer can only be "yes" or "no".<|im_end|>\n<|im_start|>user\n'
+ self.suffix = "<|im_end|>\n<|im_start|>assistant\n\n\n\n\n"
+ self.query_template = "{prefix}: Given a web search query, retrieve relevant passages that answer the query\n: {query}\n"
+ self.document_template = ": {doc}{suffix}"
+
+ self.model = LLM(
+ model='Qwen/Qwen3-Reranker-8B',
+ task="score",
+ hf_overrides={
+ "architectures": ["Qwen3ForSequenceClassification"],
+ "classifier_from_token": ["no", "yes"],
+ "is_original_qwen3_reranker": True,
+ },
+ tensor_parallel_size=1,
+ max_model_len=10000,
+ enable_prefix_caching=True,
+ gpu_memory_utilization=0.5)
+
+ def destroy():
+ destroy_model_parallel()
+
+ def rerank(self,query:str,documents:List[str],top_n:int,return_documents:bool=False):
+ query_in = self.query_template.format(prefix=self.prefix, query=query)
+ documents_in = [self.document_template.format(doc=doc, suffix=self.suffix) for doc in documents]
+ outputs = self.model.score(query_in,documents_in)
+
+ all_pairs = [
+ {'id': index, 'score': output.outputs.score, 'document': documents[index] if return_documents else ""}
+ for index, output in enumerate(outputs)
+ ]
+
+ if top_n is not None:
+ return heapq.nlargest(top_n, all_pairs, key=lambda x: x['score'])
+ else:
+ return all_pairs
\ No newline at end of file
diff --git a/vllm-ascend-rerank-server/test.py b/vllm-ascend-rerank-server/test.py
new file mode 100644
index 0000000..5d88deb
--- /dev/null
+++ b/vllm-ascend-rerank-server/test.py
@@ -0,0 +1,29 @@
+from requests import request
+from json import dumps
+
+url = "http://115.120.51.57:11558/v1/rerank"
+query = "抗生素是谁发现的？请说明发现过程和时间。"
+documents = [
+ "路易·巴斯德是微生物学之父，提出了巴氏杀菌法，对疫苗研发有重大贡献。" , # 不相关（无关人物）
+ "亚历山大·弗莱明于1928年偶然发现青霉素。他在实验室中发现霉菌抑制了葡萄球菌的生长，这一发现开启了抗生素时代。", # 完全相关（直接回答核心问题）
+ "抗生素的滥用可能导致耐药性细菌的产生，世界卫生组织已将其列为全球健康威胁。" , # 弱相关（提及抗生素但未回答发现者）
+ "1928年9月28日，弗莱明在伦敦圣玛丽医院记录到青霉素的抑菌效应，但未能纯化该物质。", # 中等相关（提供时间但未完整回答过程）
+ "弗莱明因发现青霉素获得1945年诺贝尔生理学或医学奖，但青霉素的大规模生产由霍华德·弗洛里和厄恩斯特·钱恩实现。", # 高度相关（补充关键细节）
+]
+
+payload = {
+ "model": "Qwen/Qwen3-Reranker-8B",
+ "query": query,
+ "documents": documents,
+ "top_n": 3, # 可选参数
+ "return_documents": True # 可选参数
+}
+response = request("post", url, json=payload)
+response.raise_for_status()
+results = response.json()
+
+print(results)
+
+'''
+{'model': 'Qwen/Qwen3-Reranker-8B', 'results': [{'index': 2, 'relevance_score': 0.999783456325531, 'document': '亚历山大·弗莱明于1928年偶然发现青霉素。他在实验室中发现霉菌抑制了葡萄球菌的生长，这一发现开启了抗生素时代。'}, {'index': 4, 'relevance_score': 0.9525741338729858, 'document': '1928年9月28日，弗莱明在伦敦圣玛丽医院记录到青霉素的抑菌效应，但未能纯化该物质。'}, {'index': 5, 'relevance_score': 0.9032942056655884, 'document': '弗莱明因发现青霉素获得1945年诺贝尔生理学或医学奖，但青霉素的大规模生产由霍华德·弗洛里和厄恩斯特·钱恩实现。'}]}
+'''
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/.python-version b/vllm-embedding-rerank-server/.python-version
new file mode 100644
index 0000000..e4fba21
--- /dev/null
+++ b/vllm-embedding-rerank-server/.python-version
@@ -0,0 +1 @@
+3.12
diff --git a/vllm-embedding-rerank-server/Dockerfile b/vllm-embedding-rerank-server/Dockerfile
new file mode 100644
index 0000000..e9d3e4e
--- /dev/null
+++ b/vllm-embedding-rerank-server/Dockerfile
@@ -0,0 +1,14 @@
+FROM quay.io/ascend/vllm-ascend:v0.9.2rc1
+
+RUN pip config set global.index-url https://repo.huaweicloud.com/repository/pypi/simple \
+ && pip install fastapi uvicorn
+
+WORKDIR /workspace
+RUN mkdir -p /root/.cache/modelscope/hub/models/Qwen
+
+COPY ./app .
+COPY /root/.cache/modelscope/hub/models/Qwen/Qwen3-Reranker-8B /root/.cache/modelscope/hub/models/Qwen/Qwen3-Reranker-8B
+
+CMD ["python","main.py"]
+
+# docker build -t vllm-qwen3-rerank-server .
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/README.md b/vllm-embedding-rerank-server/README.md
new file mode 100644
index 0000000..cec9f7a
--- /dev/null
+++ b/vllm-embedding-rerank-server/README.md
@@ -0,0 +1 @@
+### 在昇腾NPU上基于VLLM部署Qwen3-Embedding-8B和Qwen3-Rerank-8B
diff --git a/vllm-embedding-rerank-server/app/embedding_provider.py b/vllm-embedding-rerank-server/app/embedding_provider.py
new file mode 100644
index 0000000..b10b597
--- /dev/null
+++ b/vllm-embedding-rerank-server/app/embedding_provider.py
@@ -0,0 +1,19 @@
+from typing import List
+import torch
+from vllm import LLM
+from vllm.distributed.parallel_state import destroy_model_parallel
+
+class EmbeddingProvider:
+
+ def __init__(self):
+ self.task = 'Given a web search query, retrieve relevant passages that answer the query'
+ self.model = LLM(model="Qwen/Qwen3-Embedding-8B", task="embed")
+
+ def destroy():
+ destroy_model_parallel()
+
+ def embedding(self,documents:List[str]):
+ outputs = self.model.embed(documents)
+ embeddings = torch.tensor([o.outputs.embedding for o in outputs])
+ scores = (embeddings[:2] @ embeddings[2:].T)
+ return scores.tolist()
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/app/main.py b/vllm-embedding-rerank-server/app/main.py
new file mode 100644
index 0000000..f6a35ee
--- /dev/null
+++ b/vllm-embedding-rerank-server/app/main.py
@@ -0,0 +1,63 @@
+import uvicorn
+from typing import Union
+from pydantic import BaseModel
+from fastapi import FastAPI,Request
+from fastapi.concurrency import asynccontextmanager
+from embedding_provider import EmbeddingProvider
+
+@asynccontextmanager
+async def lifespan(app:FastAPI):
+ app.state.embed_engine = EmbeddingProvider()
+ yield
+ app.state.embed_engine.destroy()
+
+app = FastAPI(
+ title="Embedding Inference Server",
+ lifespan=lifespan,
+ root_path="/v1",
+ version="1.0",
+ license_info={"name":"Apache License 2.0","identifier":"Apache"}
+ )
+
+class EmbeddingRequest(BaseModel):
+ model: str
+ input: list[str]
+
+class Usage(BaseModel):
+ total_tokens: int
+
+class EmbeddingData(BaseModel):
+ embedding: list[Union[float, int]]
+
+class EmbeddingResponse(BaseModel):
+ model: str
+ data: list[EmbeddingData]
+ usage: Usage
+
+@app.post("/embeddings", response_model=EmbeddingResponse, summary="文本向量化")
+def text_embedding(request: Request,embed_request:EmbeddingRequest) -> EmbeddingResponse:
+ texts = embed_request.input
+
+ engine:EmbeddingProvider = request.app.state.embed_engine
+ results = engine.embedding(documents=texts)
+ embeddings = results[0]
+ total_tokens = results[1]
+
+ usage = Usage(total_tokens=total_tokens)
+
+ embedding_datas = [
+ EmbeddingData(
+ embedding = emb,
+ index = count,
+ )
+ for count, emb in enumerate(embeddings)
+ ]
+
+ return EmbeddingResponse(
+ model=embed_request.model,
+ data=embedding_datas,
+ usage=usage
+ )
+
+if __name__ == "__main__":
+ uvicorn.run(app, host="0.0.0.0", port=8097)
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/app/models.py b/vllm-embedding-rerank-server/app/models.py
new file mode 100644
index 0000000..551273d
--- /dev/null
+++ b/vllm-embedding-rerank-server/app/models.py
@@ -0,0 +1,19 @@
+from typing import Union
+from pydantic import BaseModel
+
+class EmbeddingRequest(BaseModel):
+ model: str
+ input: Union[str, list[str]]
+
+class Usage(BaseModel):
+ total_tokens: int
+
+class EmbeddingData(BaseModel):
+ object: str = "embedding"
+ embedding: list[Union[float, int]]
+
+class EmbeddingResponse(BaseModel):
+ model: str
+ object: str = "list"
+ data: list[EmbeddingData]
+ usage: Usage
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/app/test.py b/vllm-embedding-rerank-server/app/test.py
new file mode 100644
index 0000000..eeaae84
--- /dev/null
+++ b/vllm-embedding-rerank-server/app/test.py
@@ -0,0 +1,10 @@
+import heapq
+
+scores=[0.1,0.3,0.5]
+documents=['a','b','c']
+all_pairs = [
+ {'id': index+1, 'score': score, 'document': documents[index]}
+ for index, score in enumerate(scores)
+]
+all_pairs = heapq.nlargest(2, all_pairs, key=lambda x: x['score'])
+print(all_pairs)
\ No newline at end of file
diff --git a/vllm-embedding-rerank-server/pyproject.toml b/vllm-embedding-rerank-server/pyproject.toml
new file mode 100644
index 0000000..c6ae93e
--- /dev/null
+++ b/vllm-embedding-rerank-server/pyproject.toml
@@ -0,0 +1,10 @@
+[project]
+name = "vllm-embed-rerank-server"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+ "fastapi>=0.116.1",
+ "uvicorn>=0.35.0",
+]
diff --git a/vllm-embedding-rerank-server/uv.lock b/vllm-embedding-rerank-server/uv.lock
new file mode 100644
index 0000000..01734f0
--- /dev/null
+++ b/vllm-embedding-rerank-server/uv.lock
@@ -0,0 +1,207 @@
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+
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