mirror of
https://github.com/open-webui/open-webui
synced 2024-11-06 08:56:39 +00:00
144 lines
3.7 KiB
Python
144 lines
3.7 KiB
Python
from fastapi import (
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FastAPI,
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Request,
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Depends,
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HTTPException,
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status,
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UploadFile,
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File,
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Form,
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)
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from fastapi.middleware.cors import CORSMiddleware
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from chromadb.utils import embedding_functions
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from langchain.document_loaders import WebBaseLoader, TextLoader, PyPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.vectorstores import Chroma
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from langchain.chains import RetrievalQA
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from pydantic import BaseModel
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from typing import Optional
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import uuid
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from config import EMBED_MODEL, CHROMA_CLIENT, CHUNK_SIZE, CHUNK_OVERLAP
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from constants import ERROR_MESSAGES
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EMBEDDING_FUNC = embedding_functions.SentenceTransformerEmbeddingFunction(
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model_name=EMBED_MODEL
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)
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app = FastAPI()
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origins = ["*"]
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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class CollectionNameForm(BaseModel):
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collection_name: Optional[str] = "test"
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class StoreWebForm(CollectionNameForm):
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url: str
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def store_data_in_vector_db(data, collection_name):
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text_splitter = RecursiveCharacterTextSplitter(
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chunk_size=CHUNK_SIZE, chunk_overlap=CHUNK_OVERLAP
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)
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docs = text_splitter.split_documents(data)
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texts = [doc.page_content for doc in docs]
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metadatas = [doc.metadata for doc in docs]
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collection = CHROMA_CLIENT.create_collection(
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name=collection_name, embedding_function=EMBEDDING_FUNC
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)
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collection.add(
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documents=texts, metadatas=metadatas, ids=[str(uuid.uuid1()) for _ in texts]
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)
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@app.get("/")
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async def get_status():
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return {"status": True}
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@app.get("/query/{collection_name}")
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def query_collection(collection_name: str, query: str, k: Optional[int] = 4):
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collection = CHROMA_CLIENT.get_collection(
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name=collection_name,
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)
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result = collection.query(query_texts=[query], n_results=k)
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return result
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@app.post("/web")
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def store_web(form_data: StoreWebForm):
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# "https://www.gutenberg.org/files/1727/1727-h/1727-h.htm"
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try:
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loader = WebBaseLoader(form_data.url)
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data = loader.load()
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store_data_in_vector_db(data, form_data.collection_name)
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return {"status": True, "collection_name": form_data.collection_name}
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except Exception as e:
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print(e)
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.DEFAULT(e),
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)
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@app.post("/doc")
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def store_doc(collection_name: str = Form(...), file: UploadFile = File(...)):
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# "https://www.gutenberg.org/files/1727/1727-h/1727-h.htm"
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file.filename = f"{uuid.uuid4()}-{file.filename}"
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print(dir(file))
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print(file.content_type)
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if file.content_type not in ["application/pdf", "text/plain"]:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.FILE_NOT_SUPPORTED,
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)
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try:
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filename = file.filename
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file_path = f"./data/{filename}"
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contents = file.file.read()
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with open(file_path, "wb") as f:
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f.write(contents)
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f.close()
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if file.content_type == "application/pdf":
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loader = PyPDFLoader(file_path)
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elif file.content_type == "text/plain":
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loader = TextLoader(file_path)
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data = loader.load()
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store_data_in_vector_db(data, collection_name)
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return {"status": True, "collection_name": collection_name}
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except Exception as e:
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print(e)
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.DEFAULT(e),
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)
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def reset_vector_db():
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CHROMA_CLIENT.reset()
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return {"status": True}
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