open-webui/backend/apps/rag/main.py
Marclass aa1d386042 Allow any file to be used for RAG.
Changed RAG parser to prefer file extensions over MIME content types. If the type of file is not recognized assume it's a text file.
2024-01-18 20:41:14 -07:00

250 lines
6.8 KiB
Python

from fastapi import (
FastAPI,
Request,
Depends,
HTTPException,
status,
UploadFile,
File,
Form,
)
from fastapi.middleware.cors import CORSMiddleware
import os, shutil
# from chromadb.utils import embedding_functions
from langchain_community.document_loaders import (
WebBaseLoader,
TextLoader,
PyPDFLoader,
CSVLoader,
Docx2txtLoader,
UnstructuredWordDocumentLoader,
UnstructuredMarkdownLoader,
UnstructuredXMLLoader,
)
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.vectorstores import Chroma
from langchain.chains import RetrievalQA
from pydantic import BaseModel
from typing import Optional
import uuid
import time
from utils.misc import calculate_sha256
from utils.utils import get_current_user
from config import UPLOAD_DIR, EMBED_MODEL, CHROMA_CLIENT, CHUNK_SIZE, CHUNK_OVERLAP
from constants import ERROR_MESSAGES
# EMBEDDING_FUNC = embedding_functions.SentenceTransformerEmbeddingFunction(
# model_name=EMBED_MODEL
# )
app = FastAPI()
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
class CollectionNameForm(BaseModel):
collection_name: Optional[str] = "test"
class StoreWebForm(CollectionNameForm):
url: str
def store_data_in_vector_db(data, collection_name) -> bool:
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=CHUNK_SIZE, chunk_overlap=CHUNK_OVERLAP
)
docs = text_splitter.split_documents(data)
texts = [doc.page_content for doc in docs]
metadatas = [doc.metadata for doc in docs]
try:
collection = CHROMA_CLIENT.create_collection(name=collection_name)
collection.add(
documents=texts, metadatas=metadatas, ids=[str(uuid.uuid1()) for _ in texts]
)
return True
except Exception as e:
print(e)
if e.__class__.__name__ == "UniqueConstraintError":
return True
return False
@app.get("/")
async def get_status():
return {"status": True}
@app.get("/query/{collection_name}")
def query_collection(
collection_name: str,
query: str,
k: Optional[int] = 4,
user=Depends(get_current_user),
):
try:
collection = CHROMA_CLIENT.get_collection(
name=collection_name,
)
result = collection.query(query_texts=[query], n_results=k)
return result
except Exception as e:
print(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e),
)
@app.post("/web")
def store_web(form_data: StoreWebForm, user=Depends(get_current_user)):
# "https://www.gutenberg.org/files/1727/1727-h/1727-h.htm"
try:
loader = WebBaseLoader(form_data.url)
data = loader.load()
store_data_in_vector_db(data, form_data.collection_name)
return {
"status": True,
"collection_name": form_data.collection_name,
"filename": form_data.url,
}
except Exception as e:
print(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e),
)
@app.post("/doc")
def store_doc(
collection_name: Optional[str] = Form(None),
file: UploadFile = File(...),
user=Depends(get_current_user),
):
# "https://www.gutenberg.org/files/1727/1727-h/1727-h.htm"
print(file.content_type)
text_xml=["xml"]
octet_markdown=["md"]
known_source_ext=[
"go", "py", "java", "sh", "bat", "ps1", "cmd", "js",
"css", "cpp", "hpp","h", "c", "cs", "sql", "log", "ini",
"pl" "pm", "r", "dart", "dockerfile", "env", "php", "hs",
"hsc", "lua", "nginxconf", "conf", "m", "mm", "plsql", "perl",
"rb", "rs", "db2", "scala", "bash", "swift", "vue", "svelte"
]
docx_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
known_doc_ext=["doc","docx"]
file_ext=file.filename.split(".")[-1].lower()
known_type=True
try:
filename = file.filename
file_path = f"{UPLOAD_DIR}/{filename}"
contents = file.file.read()
with open(file_path, "wb") as f:
f.write(contents)
f.close()
f = open(file_path, "rb")
if collection_name == None:
collection_name = calculate_sha256(f)[:63]
f.close()
if file_ext=="pdf":
loader = PyPDFLoader(file_path)
elif (file.content_type ==docx_type or file_ext in known_doc_ext):
loader = Docx2txtLoader(file_path)
elif file_ext=="csv":
loader = CSVLoader(file_path)
elif file_ext in text_xml:
loader=UnstructuredXMLLoader(file_path)
elif file_ext in known_source_ext or file.content_type.find("text/")>=0:
loader = TextLoader(file_path)
elif file_ext in octet_markdown:
loader = UnstructuredMarkdownLoader(file_path)
else:
loader = TextLoader(file_path)
known_type=False
data = loader.load()
result = store_data_in_vector_db(data, collection_name)
if result:
return {
"status": True,
"collection_name": collection_name,
"filename": filename,
"known_type":known_type,
}
else:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=ERROR_MESSAGES.DEFAULT(),
)
except Exception as e:
print(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e),
)
@app.get("/reset/db")
def reset_vector_db(user=Depends(get_current_user)):
if user.role == "admin":
CHROMA_CLIENT.reset()
else:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
)
@app.get("/reset")
def reset(user=Depends(get_current_user)) -> bool:
if user.role == "admin":
folder = f"{UPLOAD_DIR}"
for filename in os.listdir(folder):
file_path = os.path.join(folder, filename)
try:
if os.path.isfile(file_path) or os.path.islink(file_path):
os.unlink(file_path)
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
except Exception as e:
print("Failed to delete %s. Reason: %s" % (file_path, e))
try:
CHROMA_CLIENT.reset()
except Exception as e:
print(e)
return True
else:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
)