![]() ![]() With ngrok installed, run ngrok http 5000 in a new terminal tab in the directory your code is in. Now, your Flask app will need to be visible from the web so Twilio can send requests to it. Configure a Twilio Number for the SMS Chatbot On the command line, run python app.py to start the Flask app. LOCAL_resp = askQs(LOCAL_vector_store, chain, inb_msg) LOCAL_vector_store = makeEmbeddings(LOCAL_cdocs) ![]() LOCAL_cdocs = splitDoc(LOCAL_ldocs) #chunked Inb_msg = ().strip() #get inbound text body Llm=HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs=)Ĭhain = load_qa_chain(llm, chain_type="stuff") Resp = n(input_documents=similar_docs, question=q) Similar_docs = vector_store.similarity_search(q) Vector_store = om_documents(chunked_docs, embedder) # Create embeddings and store them in a FAISS vector store Splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=10)Ĭhunked_docs = splitter.split_documents(loaded_docs) With open(output_file, "w", encoding='utf-8') as file: ngrok, a handy utility to connect the development version of our Python application running on your machine to a public URL that Twilio can access.įrom langchain.document_loaders import TextLoaderįrom langchain.text_splitter import CharacterTextSplitterįrom langchain.embeddings import HuggingFaceEmbeddingsįrom _answering import load_qa_chainįrom flask import Flask, request, redirectįrom _response import MessagingResponseĭef loadFileFromURL(text_file_url): #param:.Python installed - download Python here.Hugging Face Account – make a Hugging Face Account here.A Twilio phone number with SMS capabilities - learn how to buy a Twilio Phone Number here.A Twilio account - sign up for a free Twilio account here.This could be useful, for example, if you have to prepare for a test and wish to ask the machine about things you didn’t understand. Picture feeding a PDF or maybe multiple PDF files to a machine and then asking it questions about those files. LangChain makes it easy to perform question-answering of those documents. It is the easiest way (if not one of the easiest ways) to interact with LLMs and build applications around LLMs. LangChain is an open-source tool that wraps around many large language models (LLMs) and tools. Read on to learn how to build a generative question-answering SMS chatbot that reads a document containing Lou Gehrig's Farewell Speech using LangChain, Hugging Face, and Twilio in Python. With Natural Language Processing (NLP), you can chat with your own documents, such as a text file, a PDF, or a website. ![]()
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