open-webui/backend/apps/rag/main.py
2024-01-07 00:57:10 -08:00

144 lines
3.7 KiB
Python

from fastapi import (
FastAPI,
Request,
Depends,
HTTPException,
status,
UploadFile,
File,
Form,
)
from fastapi.middleware.cors import CORSMiddleware
from chromadb.utils import embedding_functions
from langchain.document_loaders import WebBaseLoader, TextLoader, PyPDFLoader
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
from config import 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):
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]
collection = CHROMA_CLIENT.create_collection(
name=collection_name, embedding_function=EMBEDDING_FUNC
)
collection.add(
documents=texts, metadatas=metadatas, ids=[str(uuid.uuid1()) for _ in texts]
)
@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):
collection = CHROMA_CLIENT.get_collection(
name=collection_name,
)
result = collection.query(query_texts=[query], n_results=k)
return result
@app.post("/web")
def store_web(form_data: StoreWebForm):
# "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}
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: str = Form(...), file: UploadFile = File(...)):
# "https://www.gutenberg.org/files/1727/1727-h/1727-h.htm"
file.filename = f"{uuid.uuid4()}-{file.filename}"
print(dir(file))
print(file.content_type)
if file.content_type not in ["application/pdf", "text/plain"]:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.FILE_NOT_SUPPORTED,
)
try:
filename = file.filename
file_path = f"./data/{filename}"
contents = file.file.read()
with open(file_path, "wb") as f:
f.write(contents)
f.close()
if file.content_type == "application/pdf":
loader = PyPDFLoader(file_path)
elif file.content_type == "text/plain":
loader = TextLoader(file_path)
data = loader.load()
store_data_in_vector_db(data, collection_name)
return {"status": True, "collection_name": collection_name}
except Exception as e:
print(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e),
)
def reset_vector_db():
CHROMA_CLIENT.reset()
return {"status": True}