From 7c9fb7e5b17faf217dba66ae052b01cd681505fc Mon Sep 17 00:00:00 2001
From: William Mattingly <wjbmattingly@gmail.com>
Date: Mon, 8 Apr 2024 10:30:43 -0400
Subject: [PATCH] added spacy annoy to universe

---
 website/meta/universe.json | 39 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 39 insertions(+)

diff --git a/website/meta/universe.json b/website/meta/universe.json
index 6278dd489..156677a31 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -4517,7 +4517,46 @@
                 "website": "https://redfield.ai"
             },
             "category": ["standalone"]
+        },
+        {
+            "id": "spacy-annoy",
+            "title": "Spacy Annoy",
+            "slogan": "Integrating Spacy NLP and Annoy for Semantic Text Search with spaCy linguistic tags.",
+            "description": "Spacy Annoy offers a combination of Spacy's natural language processing (NLP) capabilities and Annoy's efficient similarity search algorithms. This Python class is tailored for analyzing and querying large text corpora, delivering results based on semantic similarity. Key features include contextual window chunking and controlled overlap with preservation of original context at the Doc level, allowing access to all original Spacy properties.",
+            "github": "wjbmattingly/spacy-annoy",
+            "pip": "spacy-annoy",
+            "code_example": [
+                "from SpacyAnnoy import SpacyAnnoy",
+                "",
+                "# Initialize with a Spacy model name",
+                "sa = SpacyAnnoy('en_core_web_lg')",
+                "",
+                "texts = ['This is a text about sports', 'This is a text about dogs']*20",
+                "sa.load_docs(texts)",
+                "",
+                "sa.build_index(n_trees=10, metric='euclidean')",
+                "",
+                "# Query the index",
+                "results = sa.query_index('Dogs and cats.', depth=5)",
+                "",
+                "# Pretty print results",
+                "sa.pretty_print(results)",
+                "",
+                "# Accessing the Spacy span of the first result",
+                "first_result_span = results[0][0]"
+            ],
+            "author": "W.J.B. Mattingly",
+            "author_links": {
+                "twitter": "wjb_mattingly",
+                "github": "wjbmattingly",
+                "website": "https://wjbmattingly.com"
+            },
+            "code_language": "python",
+            "url": "https://github.com/wjbmattingly/spacy-annoy",
+            "category": ["nlp", "search", "similarity"],
+            "tags": ["spacy", "annoy", "text analysis", "semantic search"]
         }
+        
     ],
 
     "categories": [