add algo descartes(01AI) (#490)

* add algo descartes(01AI)

* Remove the link to Descartes and add it back after the product is released in the future.

* add link to descartes

* Using the GitHub：https://github.com/xiaoming-01ai/descartes.git

.github/workflows/benchmarks.yml

@@ -33,6 +33,7 @@ jobs:
           - balltree
           - bruteforce
           - ckdtree
+          - descartes
           - diskann
           - dolphinnpy
           - elasticsearch

README.md

@@ -46,6 +46,7 @@ Evaluated
 * [pgvector](https://github.com/pgvector/pgvector) ![https://img.shields.io/github/stars/pgvector/pgvector?style=social](https://img.shields.io/github/stars/pgvector/pgvector?style=social)
 * [RediSearch](https://github.com/redisearch/redisearch) ![https://img.shields.io/github/stars/redisearch/redisearch?style=social](https://img.shields.io/github/stars/redisearch/redisearch?style=social)
   * [pg_embedding](https://github.com/neondatabase/pg_embedding) ![https://img.shields.io/github/stars/pg_embedding/pg_embedding?style=social](https://img.shields.io/github/stars/neondatabase/pg_embedding?style=social)
+* [Descartes(01AI)](https://github.com/xiaoming-01ai/descartes)
 
 Data sets
 =========

ann_benchmarks/algorithms/descartes/Dockerfile

@@ -0,0 +1,9 @@
+FROM ann-benchmarks
+
+RUN apt update
+RUN apt install -y git cmake g++ python3 python3-setuptools python3-pip libblas-dev liblapack-dev
+RUN pip3 install wheel pybind11==2.5.0
+
+WORKDIR /home/app
+RUN git clone https://github.com/xiaoming-01ai/descartes.git
+RUN pip3 install descartes/descartes-*-linux_x86_64.whl

ann_benchmarks/algorithms/descartes/config.yml

@@ -0,0 +1,19 @@
+float:
+  any:
+  - base_args: ['@metric']
+    constructor: fng
+    disabled: false
+    docker_tag: ann-benchmarks-descartes
+    module: ann_benchmarks.algorithms.descartes
+    name: descartes(01AI)
+    run_groups:
+      FNG:
+        args:
+          M: [32, 64, 96, 128]
+          L: [128, 256, 320, 384, 448]
+          S: [1, 2, 3]
+        query_args: 
+          [
+            [0, 1, 2, 3],
+            [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 350, 400, 500, 600]
+          ]

ann_benchmarks/algorithms/descartes/module.py

@@ -0,0 +1,40 @@
+import py01ai
+import numpy as np
+from ..base.module import BaseANN
+import logging
+
+class fng(BaseANN):
+    def __init__(self, metric, method_param):
+        self.metric = {"angular": "angular", "euclidean": "square_l2"}[metric]
+        self.method_param = method_param
+        self.name = "01ai (%s)" % (self.method_param)
+
+    def fit(self, X):
+        self.index = py01ai.FNGIndex(metric=self.metric, dimension=len(X[0]))
+        self.index.init(count=len(X), 
+                        m=self.method_param["M"], 
+                        s=self.method_param["S"],
+                        l=self.method_param["L"])
+        try: 
+            self.index.add_vector(input=np.asarray(X))
+        except Exception as e:
+            print(str(e))
+
+    def set_query_arguments(self, ex, ef):
+        self.search_ef = ef
+        self.search_ex = ex
+        self.index.set_query_param(ef=ef, ex=ex)
+
+    def query(self, v, n):
+        return self.index.search(query=v, topk=n)
+
+    def freeIndex(self):
+        del self.index
+
+    def __str__(self):
+        m  = self.method_param['M']
+        s  = self.method_param['S']
+        l  = self.method_param['L']
+        ef = self.search_ef
+        ex = self.search_ex
+        return "01ai(M=%s S=%s L=%s EF=%s EX=%s)" % (m, s, l, ef, ex)