first push

app.py

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+import os
+os.system('pip install openpyxl')
+os.system('pip install sentence-transformers')
+import pandas as pd
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer('all-mpnet-base-v2') #all-MiniLM-L6-v2 #all-mpnet-base-v2
+
+df = pd.read_parquet('df_encoded.parquet')
+df.columns = [['name', 'description', 'year', 'target', 'size', 'stage', 'raised', 'tags', 'text_vector_']]
+#if parsing from a parquet, I have a list of array that does not want to get changed 
+df_knn = [x[0].tolist() for x in df['text_vector_'].values.tolist()]
+df = df.reset_index(drop=True)
+
+from sklearn.neighbors import NearestNeighbors
+import numpy as np
+import pandas as pd
+from sentence_transformers import SentenceTransformer
+
+#prepare model
+nbrs = NearestNeighbors(n_neighbors=5, algorithm='ball_tree').fit(df_knn)
+
+def search(query):
+    product = model.encode(query).tolist()
+    # product = df.iloc[0]['text_vector_'] #use one of the products as sample
+
+    distances, indices = nbrs.kneighbors([product]) #input the vector of the reference object
+
+    #print out the description of every recommended product
+    return df.iloc[list(indices)[0]][['name', 'description', 'year', 'target', 'size', 'stage', 'raised', 'tags']]
+
+#the first module becomes text1, the second module file1
+def greet(text1): 
+    return search(text1)
+
+iface = gr.Interface(fn=greet, inputs=['text'], outputs=["dataframe"])
+iface.launch(share=False)

df_encoded.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0f3ea0cc9455a2bb2a2ee793b9588e85c5df7ad4e9e04e363d45747092e93422
+size 24419137