Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| from langchain.document_loaders import OnlinePDFLoader | |
| from langchain.text_splitter import CharacterTextSplitter | |
| from langchain.llms import HuggingFaceHub | |
| from langchain.embeddings import HuggingFaceHubEmbeddings | |
| from langchain.vectorstores import Chroma | |
| from langchain.chains import RetrievalQA | |
| import os | |
| #os.environ["HUGGINGFACEHUB_API_TOKEN"] = "" | |
| def file_upload_click(pdf_doc): | |
| loader = OnlinePDFLoader(pdf_doc.name) | |
| documents = loader.load() | |
| text_splitter = CharacterTextSplitter(chunk_size=300, chunk_overlap=0) | |
| texts = text_splitter.split_documents(documents) | |
| embeddings = HuggingFaceHubEmbeddings() | |
| db = Chroma.from_documents(texts, embeddings) | |
| retriever = db.as_retriever() | |
| llm = HuggingFaceHub(repo_id="OpenAssistant/oasst-sft-1-pythia-12b", model_kwargs={"temperature":0.1, "max_new_tokens":250}) | |
| global qa | |
| qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True) | |
| return "Ready" | |
| def add_text(history, text): | |
| history = history + [(text, None)] | |
| return history, "" | |
| def bot(history): | |
| query=history[-1][0] | |
| response = qa({"query": query}) | |
| history[-1][1] = response['result'] | |
| return history | |
| with gr.Blocks() as demo: | |
| status_label = gr.Label(value='Start') | |
| file_upload = gr.File(label="Uplaod pdf", file_types=['.pdf'], type="file") | |
| file_upload_button= gr.Button('upload file') | |
| chatbot = gr.Chatbot([], elem_id="chatbot").style(height=350) | |
| question = gr.Textbox(label="Question", placeholder="Type your question and click submit") | |
| submit_btn = gr.Button("Send message") | |
| file_upload_button.click(file_upload_click, inputs=[file_upload], outputs=[status_label], queue=False) | |
| submit_btn.click(add_text, [chatbot, question], [chatbot, question], queue=False).then( | |
| bot, chatbot, chatbot | |
| ) | |
| demo.queue() | |
| demo.launch() |