[WIP] Semantic search endpoint

README.md

@@ -22,6 +22,10 @@ Click on each to see the parameters!
 
 * [classify](docs/classify.md) : `POST /classify/`
 
+#### Semantic search (multilingual) 🔍
+
+* [semsearch](docs/semsearch.md) : `POST /semsearch/`
+
 ## Using the API 🔥
 
 * Python:

docs/semsearch.md

@@ -0,0 +1,62 @@
+# Semantic Search
+
+Given a query sentence or paragraph, and a set of key sentences, compute probabilities of the query being similar to any of the key sentences
+http://api.vicgalle.net:5000/docs#/default/generate_semsearch_post
+
+**URL** : `/semsearch/`
+
+**Method** : `POST`
+
+**Data parameters**
+
+```json
+{
+    "query": "[string, the text to be searched in the other set]",
+    "keys": "[list of string, the key sentences separated by comma and surrounded with " "]",
+}
+```
+
+**Data example**
+
+```json
+{
+    "query": "That is a happy person",
+    "keys": ""That is a happy dog","That is a very happy person","Today is a sunny day"",
+}
+```
+
+## Success Response
+
+**Code** : `200 OK`
+
+**Content example**
+
+`scores` for the key sentences (from 0 to 1), in the same order returned by keys.
+
+```json
+{
+  "query": "That is a happy person",
+  "keys": [
+    "That is a happy dog",
+    "That is a very happy person",
+    "Today is a sunny day"
+  ],
+  "scores": [
+    0.6623498797416687,
+    0.9382339715957642,
+    0.2296333611011505
+  ]
+}
+```
+
+## Python Example
+
+```python
+import requests
+payload = { 
+    "query" : "That is a happy person", 
+    "keys" : ""That is a happy dog","That is a very happy person","Today is a sunny day""}
+response = requests.post("http://api.vicgalle.net:5000/semsearch", params=payload).json()
+print(response)
+
+```