tg131
commited on
Commit
·
9f6ab40
1
Parent(s):
edfac63
application ready
Browse files- app.py +178 -0
- requirements.txt +2 -0
app.py
ADDED
@@ -0,0 +1,178 @@
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+
import pinecone
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import streamlit as st
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from sentence_transformers import SentenceTransformer
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from transformers import BartTokenizer, BartForConditionalGeneration
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class BartGenerator:
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def __init__(self, model_name):
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self.tokenizer = BartTokenizer.from_pretrained(model_name)
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self.generator = BartForConditionalGeneration.from_pretrained(model_name)
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def tokenize(self, query, max_length=1024):
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inputs = self.tokenizer([query], max_length=max_length, return_tensors="pt")
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return inputs
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def generate(self, query, min_length=20, max_length=40):
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inputs = self.tokenize(query)
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ids = self.generator.generate(inputs["input_ids"], num_beams=1, min_length=int(min_length), max_length=int(max_length), temperature=int(temperature))
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answer = self.tokenizer.batch_decode(ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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return answer
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@st.experimental_singleton
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def init_models():
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retriever = SentenceTransformer("flax-sentence-embeddings/all_datasets_v3_mpnet-base") #("multi-qa-mpnet-base-cos-v1") ("flax-sentence-embeddings/all_datasets_v3_mpnet-base")
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generator = BartGenerator("vblagoje/bart_lfqa")
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return retriever, generator
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PINECONE_KEY = st.secrets["PINECONE_KEY"]
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@st.experimental_singleton
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def init_pinecone():
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pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
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return pinecone.Index("history-qa")
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retriever, generator = init_models()
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index = init_pinecone()
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def display_answer(answer):
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return st.markdown(f"""
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<div class="container-fluid">
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<div class="row align-items-start">
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<div class="col-md-12 col-sm-12">
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<span style="color: #808080;">
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{answer}
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</span>
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</div>
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</div>
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</div>
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""", unsafe_allow_html=True)
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def display_context(title, context, url):
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return st.markdown(f"""
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<div class="container-fluid">
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<div class="row align-items-start">
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<div class="col-md-12 col-sm-12">
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<a href={url}>{title}</a>
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<br>
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<span style="color: #808080;">
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<small>{context}</small>
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</span>
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</div>
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</div>
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</div>
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""", unsafe_allow_html=True)
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hide_streamlit_style = """
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<style>
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#MainMenu {visibility: hidden;}
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footer {visibility: hidden;}
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</style>
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"""
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st.markdown(hide_streamlit_style, unsafe_allow_html=True)
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st.write("""
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# Jua Historia Yetu
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### An AI Powered Search Engine for East African History and Tourism!
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This is an AI powered system designed to help learn about our history, heroes, cultures and tourist destinations.
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The system generates a Human-like response to questions asked and points users to where they
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can get more information on what they would like to know.
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It is intended to act as a one-stop search engine for all things East Africa including the people, history, culture, wildlife and tourist destinations.
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It can be of use to locals, tourists, students or anyone who would like to learn about The East African Community.
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The data is to be sourced from the EAC e-resourse database, member nations' meuseums, archives and relevant tourism bodies.
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Once queried, the system generates a short answer that the user can quickly read through and also points the user to
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some resources they might find usefull. The user can click on the links to learn more.
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""")
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st.markdown("""
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
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""", unsafe_allow_html=True)
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def format_query(query, context):
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context = [f"<P> {m['metadata']['passage_text']}" for m in context]
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context = " ".join(context)
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query = f"question: {query} context: {context}"
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return query
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# set parameters
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top_k = 5
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min_length = 1
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max_length = 150
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temperature = 3.5
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st.sidebar.write("""
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## Here are some questions you can try out:
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### Copy and paste to test
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who was the first person on the moon?\n
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Which was the first radio station at Auburn University\n
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where is Damastown located\n
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What is the Lohanipur Torso \n
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when was The Coliseum Theatre opened\n
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Who invented the tatoo machine\n
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whats th erecipe for Corn chowder\n
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when was the Tamil Methodist Church built\n
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when was the first electric power system built?\n
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How was the first wireless message sent?\n
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what was the war of currents?\n
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what was NASAs most expensive project?\n
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What brands of smokoing paper are manufactured by Miguel y Costas\n
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what influenced the naming Holy Forty Martyrs Church\n
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When was the world first power system built\n
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which is the largest island within the Halifax Harbour\n
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Who was Joseph Monier\n
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who were the Karadjordjevic dynasty\n
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how many royal tombs were excavated at Tillia Tepe\n
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What did the HEICO company manufacture\n
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tell me about The Battle of Antietam\n
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Which was the smallest microbrewery in the United States\n
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when did queen marie recieve the bran castle\n
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Whe was York Township founded\n
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When did the United Nations Security Council reform the security sector\n
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When was Magandang Umaga Po first aired\n
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when was Mae Lan District formed\n
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what is Voice over Internet Protocol\n
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When was InfluxDB developed\n
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When was the Semanário Económico newspaper started\n
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who owned Kasteln Castle\n
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when was The Steinbach Haus built\n
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when was the Guerrero ship in Africa\n
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tell me about the Guerrero ship\n
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When was the Companhia Paulista de Trens Metropolitanos rilway built\n
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When was the lincoln mall demolished\n
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where is Damastown located\n
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when was solo diving first practiced\n
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when was Consumers Credit Union History Consumers Credit Union was founded\n
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Who built the castle of Daroynk\n
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What is the prime meridian\n
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Which was the first radio station at Auburn University\n
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What are the origins of feminist music\n
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What were the earliest insecticides to be used\n
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who were the Drevlians\n
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Who were the founders of A.F.C. Euro Kickers\n
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when was the camera-on-a-chip developed\n
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""")
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st.write("If you encounter an error, search again.")
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query = st.text_input("Search!", "")
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if query != "":
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with st.spinner(text="Wait a sec 🚀🚀🚀"):
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xq = retriever.encode([query]).tolist()
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xc = index.query(xq, top_k=int(top_k), include_metadata=True)
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query = format_query(query, xc["matches"])
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with st.spinner(text="Just a minute ✍️✍️✍️"):
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answer = generator.generate(query, min_length=min_length, max_length=max_length)
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st.write("#### System generated response:")
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display_answer(answer)
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st.write("#### Here are some resources you might find relevant:")
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for m in xc["matches"]:
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title = m["metadata"]["article_title"]
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url = "https://en.wikipedia.org/wiki/" + title.replace(" ", "_")
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context = m["metadata"]["passage_text"]
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display_context(title, context, url)
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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pinecone-client
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2 |
+
sentence-transformers
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