Spaces:
Runtime error
Runtime error
import pandas as pd | |
import tiktoken | |
import os | |
import openai | |
from openai.embeddings_utils import get_embedding, cosine_similarity | |
import numpy as np | |
import streamlit as st | |
input_datapath = "fine_food_reviews_with_embeddings_1k.csv" | |
df = pd.read_csv(input_datapath, index_col=0) | |
st.title("Semanti Search") | |
#adding another column having the summary as title and the actual text as content | |
df["combined"] = ( | |
"Title: " + df.Summary.str.strip() + "; Content: " + df.Text.str.strip() | |
) | |
# embedding model parameters | |
embedding_model = "text-embedding-ada-002" | |
embedding_encoding = "cl100k_base" # this the encoding for text-embedding-ada-002 | |
max_tokens = 8000 # the maximum for text-embedding-ada-002 is 8191 | |
encoding = tiktoken.get_encoding(embedding_encoding) | |
top_n = 500 | |
# omit reviews that are too long to embed | |
df["n_tokens"] = df.combined.apply(lambda x: len(encoding.encode(x))) | |
df = df[df.n_tokens <= max_tokens].tail(top_n) | |
datafile_path = "fine_food_reviews_with_embeddings_1k.csv" | |
df = pd.read_csv(datafile_path) | |
df["embedding"] = df.embedding.apply(eval).apply(np.array) | |
prompt = input("What do you want to search for? : ") | |
top_n = int(input("How many results do you want to see? : ")) | |
print() | |
results,product = search_reviews(df, prompt, top_n) | |