feat: brotli compression on parquer file, add auth passwd

app.py

@@ -11,20 +11,15 @@ from openai.embeddings_utils import get_embedding, cosine_similarity
 
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
+passwd = os.getenv("PASSWD_SECRET")
+
 title = "Confidential forensics tool with ChatGPT"
 examples = ["Who is Phillip Allen?", "What the project in Austin is about?", "Give me more details about the real estate project"]
 
 index = GPTSimpleVectorIndex.load_from_disk('email.json')
 
 dat_fr = pd.DataFrame({"Documents loaded": ["email.json", "email_200.parquet"]})
-
 df = pd.read_parquet("email_200.parquet")
-# df["embedding"] = [get_embedding(x) forW x in df.body.values]
-# df.to_parquet("email_50.parquet")
-
-# df = pd.read_csv("email_ok.csv", nrows=50)
-# df["embedding"] = [get_embedding(x) for x in df.body.values]
-# df.to_parquet("email_50.parquet")
 
 def search_emails(opt, message, n=3):
  "Outputs the top n emails that match the most the pattern"
@@ -137,4 +132,4 @@ with gr.Blocks(title=title) as demo:
  btn_send2.click(search_emails, [opt, msg2], [opt, msg2])
  
 if __name__ == "__main__":
- demo.launch()
+ demo.launch(auth=("mithril", passwd))

email_200.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:689f185923970ee7a8da61eb63ae2116d75af0a473dd2735c0848bc87b505135
-size 8670196
+oid sha256:059c095bad18d8c299ab701ca19ac1d938e82bba28af7d6e9a333bd20a35586a
+size 3098469