vector search demo

app.py

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+import os
+
+import cohere
+import gradio as gr
+import pinecone
+
+co = cohere.Client(os.environ.get('COHERE_API', ''))
+pinecone.init(
+    api_key=os.environ.get('PINECONE_API', ''),
+    environment=os.environ.get('PINECONE_ENV', '')
+)
+
+def list_me(matches):
+    result = ''
+    for match in matches:
+        result += '<li><a target="_blank" href="https://reddit.com/r/AskNYC/comments/' + match['id'] + '">'
+        result += match['metadata']['question']
+        result += '</a></li>'
+    return result
+
+
+def query(question):
+    response = co.embed(
+        model='large',
+        texts=[question],
+    )
+    index = pinecone.Index("gptnyc")
+    closest = index.query(
+        top_k=2,
+        include_metadata=True,
+        vector=response.embeddings[0],
+    )
+
+    return '<ul>' + list_me(closest['matches']) + '</ul>'
+
+
+iface = gr.Interface(
+    fn=query,
+    inputs="text",
+    outputs="html"
+)
+iface.launch()

requirements.txt

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+cohere==3.10.0
+pinecone-client==2.2.1