add support to uploading zip file (#62)

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Evan Carlson 2023-05-19 14:13:46 -07:00 committed by GitHub
parent 424f055ca1
commit 6d1f22a420
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5 changed files with 152 additions and 51 deletions

4
components_keys.py Normal file
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@ -0,0 +1,4 @@
"""Store streamlit component keys"""
class ComponentsKeys:
FILE_UPLOADER = "file_uploader"

183
files.py
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@ -1,21 +1,37 @@
import streamlit as st
from streamlit.runtime.uploaded_file_manager import UploadedFile, UploadedFileRec
import os
from typing import (
Any,
Union,
)
import zipfile
import streamlit as st
from streamlit.runtime.uploaded_file_manager import (
UploadedFile,
UploadedFileRec,
UploadedFileManager,
)
from streamlit.runtime.scriptrunner import get_script_run_ctx
from supabase.client import Client
from langchain.vectorstores.supabase import SupabaseVectorStore
from components_keys import ComponentsKeys
from loaders.audio import process_audio
from loaders.txt import process_txt
from loaders.csv import process_csv
from loaders.markdown import process_markdown
from loaders.html import process_html
from utils import compute_sha1_from_content
from loaders.pdf import process_pdf
from loaders.html import get_html, create_html_file, delete_tempfile
from loaders.html import (
create_html_file,
delete_tempfile,
get_html,
process_html,
)
from loaders.powerpoint import process_powerpoint
from loaders.docx import process_docx
import requests
import re
import unicodedata
import tempfile
from utils import compute_sha1_from_content
ctx = get_script_run_ctx()
manager = UploadedFileManager()
file_processors = {
".txt": process_txt,
".csv": process_csv,
@ -30,17 +46,33 @@ file_processors = {
".mpeg": process_audio,
".pdf": process_pdf,
".html": process_html,
".pptx": process_powerpoint,
".docx": process_docx
".pptx": process_powerpoint,
".docx": process_docx
}
def file_uploader(supabase, openai_key, vector_store):
def file_uploader(supabase, vector_store):
# Omit zip file support if the `st.secrets.self_hosted` != "true" because
# a zip file can consist of multiple files so the limit on 1 file uploaded
# at a time in the demo can be circumvented.
accepted_file_extensions = list(file_processors.keys())
accept_multiple_files = st.secrets.self_hosted == "true"
files = st.file_uploader("**Upload a file**", accept_multiple_files=accept_multiple_files, type=list(file_processors.keys()))
if accept_multiple_files:
accepted_file_extensions += [".zip"]
files = st.file_uploader(
"**Upload a file**",
accept_multiple_files=accept_multiple_files,
type=accepted_file_extensions,
key=ComponentsKeys.FILE_UPLOADER,
)
if st.secrets.self_hosted == "false":
st.markdown("**In demo mode, the max file size is 1MB**")
if st.button("Add to Database"):
if files is not None:
# Single file upload
if isinstance(files, UploadedFile):
filter_file(files, supabase, vector_store)
# Multiple files upload
elif isinstance(files, list):
for file in files:
filter_file(file, supabase, vector_store)
@ -49,42 +81,107 @@ def file_already_exists(supabase, file):
response = supabase.table("documents").select("id").eq("metadata->>file_sha1", file_sha1).execute()
return len(response.data) > 0
def file_to_uploaded_file(file: Any) -> Union[None, UploadedFile]:
"""Convert a file to a streamlit `UploadedFile` object.
This allows us to unzip files and treat them the same way
streamlit treats files uploaded through the file uploader.
Parameters
---------
file : Any
The file. Can be any file supported by this app.
Returns
-------
Union[None, UploadedFile]
The file converted to a streamlit `UploadedFile` object.
Returns `None` if the script context cannot be grabbed.
"""
if ctx is None:
print("script context not found, skipping uploading file:", file.name)
return
file_extension = os.path.splitext(file.name)[-1]
file_name = file.name
file_data = file.read()
# The file manager will automatically assign an ID so pass `None`
# Reference: https://github.com/streamlit/streamlit/blob/9a6ce804b7977bdc1f18906d1672c45f9a9b3398/lib/streamlit/runtime/uploaded_file_manager.py#LL98C6-L98C6
uploaded_file_rec = UploadedFileRec(None, file_name, file_extension, file_data)
uploaded_file_rec = manager.add_file(
ctx.session_id,
ComponentsKeys.FILE_UPLOADER,
uploaded_file_rec,
)
return UploadedFile(uploaded_file_rec)
def filter_zip_file(
file: UploadedFile,
supabase: Client,
vector_store: SupabaseVectorStore,
) -> None:
"""Unzip the zip file then filter each unzipped file.
Parameters
----------
file : UploadedFile
The uploaded file from the file uploader.
supabase : Client
The supabase client.
vector_store : SupabaseVectorStore
The vector store in the database.
"""
with zipfile.ZipFile(file, "r") as z:
unzipped_files = z.namelist()
for unzipped_file in unzipped_files:
with z.open(unzipped_file, "r") as f:
filter_file(f, supabase, vector_store)
def filter_file(file, supabase, vector_store):
# Streamlit file uploads are of type `UploadedFile` which has the
# necessary methods and attributes for this app to work.
if not isinstance(file, UploadedFile):
file = file_to_uploaded_file(file)
file_extension = os.path.splitext(file.name)[-1]
if file_extension == ".zip":
filter_zip_file(file, supabase, vector_store)
return True
if file_already_exists(supabase, file):
st.write(f"😎 {file.name} is already in the database.")
return False
elif file.size < 1:
if file.size < 1:
st.write(f"💨 {file.name} is empty.")
return False
else:
file_extension = os.path.splitext(file.name)[-1]
if file_extension in file_processors:
if st.secrets.self_hosted == "false":
file_processors[file_extension](vector_store, file, stats_db=supabase)
else:
file_processors[file_extension](vector_store, file, stats_db=None)
st.write(f"{file.name} ")
return True
if file_extension in file_processors:
if st.secrets.self_hosted == "false":
file_processors[file_extension](vector_store, file, stats_db=supabase)
else:
st.write(f"{file.name} is not a valid file type.")
return False
file_processors[file_extension](vector_store, file, stats_db=None)
st.write(f"{file.name} ")
return True
def url_uploader(supabase, openai_key, vector_store):
url = st.text_area("**Add an url**",placeholder="https://www.quivr.app")
button = st.button("Add the URL to the database")
st.write(f"{file.name} is not a valid file type.")
return False
if button:
if not st.session_state["overused"]:
html = get_html(url)
if html:
st.write(f"Getting content ... {url} ")
file, temp_file_path = create_html_file(url, html)
ret = filter_file(file, supabase, vector_store)
delete_tempfile(temp_file_path, url, ret)
else:
st.write(f"❌ Failed to access to {url} .")
def url_uploader(supabase, vector_store):
url = st.text_area("**Add an url**",placeholder="https://www.quivr.app")
button = st.button("Add the URL to the database")
if button:
if not st.session_state["overused"]:
html = get_html(url)
if html:
st.write(f"Getting content ... {url} ")
file, temp_file_path = create_html_file(url, html)
ret = filter_file(file, supabase, vector_store)
delete_tempfile(temp_file_path, url, ret)
else:
st.write("You have reached your daily limit. Please come back later or self host the solution.")
st.write(f"❌ Failed to access to {url} .")
else:
st.write("You have reached your daily limit. Please come back later or self host the solution.")

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@ -9,13 +9,13 @@ from stats import add_usage
def process_file(vector_store, file, loader_class, file_suffix, stats_db=None):
documents = []
file_sha = ""
file_name = file.name
file_size = file.size
if st.secrets.self_hosted == "false":
if file_size > 1000000:
st.error("File size is too large. Please upload a file smaller than 1MB or self host.")
return
dateshort = time.strftime("%Y%m%d")
with tempfile.NamedTemporaryFile(delete=False, suffix=file_suffix) as tmp_file:
tmp_file.write(file.getvalue())
@ -24,6 +24,7 @@ def process_file(vector_store, file, loader_class, file_suffix, stats_db=None):
loader = loader_class(tmp_file.name)
documents = loader.load()
file_sha1 = compute_sha1_from_file(tmp_file.name)
os.remove(tmp_file.name)
chunk_size = st.session_state['chunk_size']
@ -39,4 +40,3 @@ def process_file(vector_store, file, loader_class, file_suffix, stats_db=None):
vector_store.add_documents(docs_with_metadata)
if stats_db:
add_usage(stats_db, "embedding", "file", metadata={"file_name": file_name,"file_type": file_suffix, "chunk_size": chunk_size, "chunk_overlap": chunk_overlap})
return

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@ -88,15 +88,15 @@ if user_choice == 'Add Knowledge':
col1, col2 = st.columns(2)
with col1:
file_uploader(supabase, openai_api_key, vector_store)
file_uploader(supabase, vector_store)
with col2:
url_uploader(supabase, openai_api_key, vector_store)
url_uploader(supabase, vector_store)
elif user_choice == 'Chat with your Brain':
# Display model and temperature selection only when asking questions
st.sidebar.title("Configuration")
st.sidebar.markdown(
"Choose your model and temperature for asking questions.")
if st.secrets.self_hosted != "false":
if self_hosted != "false":
st.session_state['model'] = st.sidebar.selectbox(
"Select Model", models, index=(models).index(st.session_state['model']))
else:
@ -120,4 +120,4 @@ elif user_choice == 'Explore':
st.sidebar.title("Configuration")
view_document(supabase)
st.markdown("---\n\n")
st.markdown("---\n\n")

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@ -3,9 +3,9 @@ import hashlib
def compute_sha1_from_file(file_path):
with open(file_path, "rb") as file:
bytes = file.read()
readable_hash = hashlib.sha1(bytes).hexdigest()
readable_hash = compute_sha1_from_content(bytes)
return readable_hash
def compute_sha1_from_content(content):
readable_hash = hashlib.sha1(content).hexdigest()
return readable_hash
return readable_hash