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import streamlit as st |
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import numpy as np |
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import pandas as pd |
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import os |
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from run_eval import run_generate |
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default_value = "summarize: Nick: Opinions required! Gas ya induction hob? Ben: Bahut time se ek induction hob use kar raha huu, mai convinced nahi huu.. Ruth: induction- bahut sleek hai jadi garam ho jaata hai! Ben: but voh constant temperature maintain nahi karta! Kya saare induction aise hee hai yaa maine purana waala liya tha? Ruth: they pulse agar proper pans nahi use karte hum Ben: proper se tumhara kya matlab? Kya tumhara matlab better aur bhari? Ruth: yeah, simply suitable Ben: and mujhe lagta hai mujhe usse chalana seekhna padega.. Ruth: yeah, yeh gas se alag hai Christian: gas, bina kisi saval ke- aur koi cheez tumhe control nahi deti! Nick: Mai usme interested huu jisme mujhe mere hissab se consistent heat mile Mary: with induction tumhe usse shuru aur band karna padega to regulate temperature.. Kate: induction- yes, gas- no kyuki paani ubalne mein sadiyaan lag jaati hai! Tim: tum jaante ho naa tum ek electric kettle use kar sakte ho? Kate: haha! Yeh funny nahi hai! Kate: yeh saaf karne mein bhi aasan hai. Harry: mai induction lunga kyuki voh khaana banane ke baad bhi usse garam rakhta hai Tom: Induction! 100% Susan: humara induction bahut ganda tha I think it s common! Emma: induction ke liye ek aur vote! Ruth: All chefs seem to say gas! Tom: mai gas se zyaada induction hobs bechta huu! yeh popular hota jaa raha hai aur mai dekh ssakta huu kyu! Emma: humne humara waala John Lewis outlet se liya so it was ex display aur isliye bahut sasta tha! Nick: tumhari raaye ke liye thanks! Great talk! Mujhe lagta hai mai Induction lunga." |
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st.write("# GupShup") |
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st.write("## Summarizing Open-Domain Code-Switched Conversations - [https://github.com/midas-research/gupshup](https://github.com/midas-research/gupshup)") |
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task_type = st.sidebar.selectbox( |
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"Task type", ["Hinglish to English", "English to English"] |
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) |
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model_name = st.sidebar.selectbox( |
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"Model", ["mBart", "Pegasus", "Bart", "T5"] |
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) |
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src_form = st.sidebar.form(key="src_form") |
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src_ip = src_form.text_input(label="Please enter path to conversastion/source file") |
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tar_ip = src_form.text_input( |
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label="Please enter path to summary/target file. [optional]" |
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) |
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src_submit_button = src_form.form_submit_button(label="Submit") |
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st.sidebar.markdown("<h1 style='text-align: center;'>OR</h1>", unsafe_allow_html=True) |
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conv_form = st.sidebar.form(key="conv_form") |
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conv_ip = conv_form.text_input(label="Please enter the conversastion", value=default_value) |
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conv_submit_button = conv_form.form_submit_button(label="Submit") |
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st.write("### Task Type:", task_type) |
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st.write("### Model:", model_name) |
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x = "fg" |
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src_file = None |
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tar_file = None |
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gen_file = "generated_summary.txt" |
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score_file = None |
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if conv_submit_button: |
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if conv_ip == "": |
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st.write("Pls enter non empty conversastion") |
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else: |
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st.write("### Summarizing below Conversastion") |
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st.write(conv_ip) |
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src_file = "conversastion.txt" |
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src_fp = open(src_file, "w") |
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src_fp.write(conv_ip) |
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src_fp.close() |
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if src_submit_button: |
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if src_ip == "": |
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st.write("### Please enter path to conversastion file") |
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elif os.path.isfile(src_ip) == False: |
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st.write("### Path to conversastion file is invalid") |
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else: |
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src_file = src_ip |
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st.write("summarizing conversastion stored in ", src_file) |
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if tar_ip != "" and os.path.isfile(tar_ip): |
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tar_file = tar_ip |
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score_file = "scores.txt" |
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else: |
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st.write( |
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"Target file is not provided or invalid, score will not be calculated" |
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) |
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st.write(" src and tar") |
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st.write(src_ip) |
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st.write(tar_ip) |
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tt = "h2e" |
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if task_type == "English to English": |
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tt = "e2e" |
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elif task_type == "Hinglish to English": |
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tt = "h2e" |
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model_name_path = "midas/gupshup_" + str(tt) + "_" + str(model_name).lower() |
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if src_file == None or os.path.isfile(src_file) == False: |
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st.write("##### Hit the submit button on the left with the default conversation or enter your own conversation if you don't have the source files.") |
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else: |
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result = run_generate( |
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verbose=True, |
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model_name_path=model_name_path, |
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src_txt=src_file, |
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tar_txt=tar_file, |
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gen_path=gen_file, |
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scor_path=score_file, |
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batch_size=8, |
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) |
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if conv_submit_button: |
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st.write("summary:") |
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fp = open(gen_file, "r") |
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summary = fp.readlines() |
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fp.close() |
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st.write(summary) |
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if src_submit_button and result!=None: |
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if tar_file != None: |
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st.write("scores: ", result) |
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st.write("summary is stored in ", gen_file) |
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