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import os | |
import sys | |
import logging | |
import pandas as pd | |
from json import JSONDecodeError | |
from pathlib import Path | |
import streamlit as st | |
from annotated_text import annotation | |
from markdown import markdown | |
import random | |
from utils import haystack_is_ready, query, send_feedback, upload_doc, haystack_version, get_backlink | |
# Adjust to a question that you would like users to see in the search bar when they load the UI: | |
DEFAULT_QUESTION_AT_STARTUP = os.getenv("DEFAULT_QUESTION_AT_STARTUP", "Who is Laura Palmer?") | |
DEFAULT_ANSWER_AT_STARTUP = os.getenv("DEFAULT_ANSWER_AT_STARTUP", "") | |
# Sliders | |
DEFAULT_DOCS_FROM_RETRIEVER = int(os.getenv("DEFAULT_DOCS_FROM_RETRIEVER", 3)) | |
DEFAULT_NUMBER_OF_ANSWERS = int(os.getenv("DEFAULT_NUMBER_OF_ANSWERS", 3)) | |
top_k_retriever=7 | |
top_k_reader=5 | |
# Labels for the evaluation | |
EVAL_LABELS = os.getenv("EVAL_FILE", Path(__file__).parent / "eval_labels_example.csv") | |
# Whether the file upload should be enabled or not | |
DISABLE_FILE_UPLOAD = True | |
def set_state_if_absent(key, value): | |
if key not in st.session_state: | |
st.session_state[key] = value | |
def main(): | |
st.set_page_config(page_title='Who killed Laura Palmer?', page_icon="https://haystack.deepset.ai/img/HaystackIcon.png") | |
# Persistent state | |
set_state_if_absent('question', DEFAULT_QUESTION_AT_STARTUP) | |
set_state_if_absent('answer', DEFAULT_ANSWER_AT_STARTUP) | |
set_state_if_absent('results', None) | |
set_state_if_absent('raw_json', None) | |
set_state_if_absent('random_question_requested', False) | |
# Small callback to reset the interface in case the text of the question changes | |
def reset_results(*args): | |
st.session_state.answer = None | |
st.session_state.results = None | |
st.session_state.raw_json = None | |
# page_bg_img = """ | |
# <style> | |
# .reportview-container { | |
# background: url("https://upload.wikimedia.org/wikipedia/it/3/39/Twin-peaks-1990.jpg") | |
# } | |
# .sidebar .sidebar-content { | |
# background: url("https://upload.wikimedia.org/wikipedia/it/3/39/Twin-peaks-1990.jpg") | |
# } | |
# </style> | |
# """ | |
# st.markdown(page_bg_img, unsafe_allow_html=True) | |
# st.image("https://upload.wikimedia.org/wikipedia/it/3/39/Twin-peaks-1990.jpg") | |
# Title | |
st.write("# Who killed Laura Palmer?") | |
st.write("### The first Twin Peaks Question Answering system!") | |
st.markdown("""<br/> | |
Ask any question on Twin Peaks and see if the systsem can find the correct answer to your query! | |
*Note: do not use keywords, but full-fledged questions.* | |
""", unsafe_allow_html=True) | |
# Sidebar | |
st.sidebar.header("Who killed Laura Palmer?") | |
st.sidebar.image("https://upload.wikimedia.org/wikipedia/it/3/39/Twin-peaks-1990.jpg") | |
st.sidebar.markdown("#### Twin Peaks Question Answering system") | |
# top_k_reader = st.sidebar.slider( | |
# "Max. number of answers", | |
# min_value=1, | |
# max_value=10, | |
# value=DEFAULT_NUMBER_OF_ANSWERS, | |
# step=1, | |
# on_change=reset_results) | |
# top_k_retriever = st.sidebar.slider( | |
# "Max. number of documents from retriever", | |
# min_value=1, | |
# max_value=10, | |
# value=DEFAULT_DOCS_FROM_RETRIEVER, | |
# step=1, | |
# on_change=reset_results) | |
# eval_mode = st.sidebar.checkbox("Evaluation mode") | |
# debug = st.sidebar.checkbox("Show debug info") | |
# # File upload block | |
# if not DISABLE_FILE_UPLOAD: | |
# st.sidebar.write("## File Upload:") | |
# data_files = st.sidebar.file_uploader("", type=["pdf", "txt", "docx"], accept_multiple_files=True) | |
# for data_file in data_files: | |
# # Upload file | |
# if data_file: | |
# raw_json = upload_doc(data_file) | |
# st.sidebar.write(str(data_file.name) + " β ") | |
# if debug: | |
# st.subheader("REST API JSON response") | |
# st.sidebar.write(raw_json) | |
# hs_version = "" | |
# try: | |
# hs_version = f" <small>(v{haystack_version()})</small>" | |
# except Exception: | |
# pass | |
st.sidebar.markdown(f""" | |
<style> | |
a {{ | |
text-decoration: none; | |
}} | |
.haystack-footer {{ | |
text-align: center; | |
}} | |
.haystack-footer h4 {{ | |
margin: 0.1rem; | |
padding:0; | |
}} | |
footer {{ | |
opacity: 0; | |
}} | |
.haystack-footer img {{ | |
display: block; | |
margin-left: auto; | |
margin-right: auto; | |
width: 85%; | |
}} | |
</style> | |
<div class="haystack-footer"> | |
<p>Get it on <a href="https://github.com/deepset-ai/haystack/">GitHub</a> - | |
Built with <a href="https://github.com/deepset-ai/haystack/">Haystack</a><br/> | |
<small>Data crawled from <a href="https://twinpeaks.fandom.com/wiki/Twin_Peaks_Wiki">Twin Peaks Wiki</a>.</small> | |
</p> | |
<img src = 'https://static.wikia.nocookie.net/twinpeaks/images/e/ef/Laura_Palmer%2C_the_Queen_Of_Hearts.jpg'/> | |
<br/> | |
</div> | |
""", unsafe_allow_html=True) | |
# st.sidebar.image('https://static.wikia.nocookie.net/twinpeaks/images/e/ef/Laura_Palmer%2C_the_Queen_Of_Hearts.jpg', width=270) #use_column_width='always' | |
song_i = random.randint(1,11) | |
st.sidebar.audio(f'http://twinpeaks.narod.ru/Media/0{song_i}.mp3') | |
# Load csv into pandas dataframe | |
try: | |
df = pd.read_csv(EVAL_LABELS, sep=";") | |
except Exception: | |
st.error(f"The eval file was not found. Please check the demo's [README](https://github.com/deepset-ai/haystack/tree/master/ui/README.md) for more information.") | |
sys.exit(f"The eval file was not found under `{EVAL_LABELS}`. Please check the README (https://github.com/deepset-ai/haystack/tree/master/ui/README.md) for more information.") | |
# Search bar | |
question = st.text_input("", | |
value=st.session_state.question, | |
max_chars=100, | |
#on_change=reset_results | |
) | |
col1, col2 = st.columns(2) | |
col1.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True) | |
col2.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True) | |
# Run button | |
run_pressed = col1.button("Run") | |
# Get next random question from the CSV | |
if col2.button("Random question"): | |
reset_results() | |
new_row = df.sample(1) | |
while new_row["Question Text"].values[0] == st.session_state.question: # Avoid picking the same question twice (the change is not visible on the UI) | |
new_row = df.sample(1) | |
st.session_state.question = new_row["Question Text"].values[0] | |
st.session_state.answer = new_row["Answer"].values[0] | |
st.session_state.random_question_requested = True | |
# Re-runs the script setting the random question as the textbox value | |
# Unfortunately necessary as the Random Question button is _below_ the textbox | |
raise st.script_runner.RerunException(st.script_request_queue.RerunData(None)) | |
else: | |
st.session_state.random_question_requested = False | |
run_query = (run_pressed or question != st.session_state.question) and not st.session_state.random_question_requested | |
# Check the connection | |
with st.spinner("βοΈ Haystack is starting..."): | |
if not haystack_is_ready(): | |
st.error("π« Connection Error. Is Haystack running?") | |
run_query = False | |
reset_results() | |
# Get results for query | |
if run_query and question: | |
reset_results() | |
st.session_state.question = question | |
with st.spinner( | |
"π§ Performing neural search on documents... \n " | |
"The response may be slow because the system is running on CPU. \n" | |
"If you want to support and speed up this site, please contact me on Github. " | |
): | |
try: | |
st.session_state.results, st.session_state.raw_json = query(question, top_k_reader=top_k_reader, | |
top_k_retriever=top_k_retriever) | |
except JSONDecodeError as je: | |
st.error("π An error occurred reading the results. Is the document store working?") | |
return | |
except Exception as e: | |
logging.exception(e) | |
if "The server is busy processing requests" in str(e) or "503" in str(e): | |
st.error("π§βπΎ All our workers are busy! Try again later.") | |
else: | |
st.error("π An error occurred during the request.") | |
return | |
if st.session_state.results: | |
eval_mode=False | |
# Show the gold answer if we use a question of the given set | |
if eval_mode and st.session_state.answer: | |
st.write("## Correct answer:") | |
st.write(st.session_state.answer) | |
st.write("## Results:") | |
alert_irrelevance=True | |
for count, result in enumerate(st.session_state.results): | |
if result["answer"]: | |
if alert_irrelevance and result['relevance']<=30: | |
alert_irrelevance = False | |
st.write("<h3 style='color: red'>Attention, the following answers have low relevance:</h3>", unsafe_allow_html=True) | |
answer, context = result["answer"], result["context"] | |
start_idx = context.find(answer) | |
end_idx = start_idx + len(answer) | |
# Hack due to this bug: https://github.com/streamlit/streamlit/issues/3190 | |
st.write(markdown(context[:start_idx] + str(annotation(answer, "ANSWER", "#8ef")) + context[end_idx:]), unsafe_allow_html=True) | |
source = "" | |
url = get_backlink(result) | |
if url: | |
source = f"({result['document']['meta']['url']})" | |
else: | |
source = f"{result['source']}" | |
st.markdown(f"**Relevance:** {result['relevance']} - **Source:** {source}") | |
else: | |
st.info("π€ Haystack is unsure whether any of the documents contain an answer to your question. Try to reformulate it!") | |
st.write("**Relevance:** ", result["relevance"]) | |
if eval_mode and result["answer"]: | |
# Define columns for buttons | |
is_correct_answer = None | |
is_correct_document = None | |
button_col1, button_col2, button_col3, _ = st.columns([1, 1, 1, 6]) | |
if button_col1.button("π", key=f"{result['context']}{count}1", help="Correct answer"): | |
is_correct_answer=True | |
is_correct_document=True | |
if button_col2.button("π", key=f"{result['context']}{count}2", help="Wrong answer and wrong passage"): | |
is_correct_answer=False | |
is_correct_document=False | |
if button_col3.button("ππ", key=f"{result['context']}{count}3", help="Wrong answer, but correct passage"): | |
is_correct_answer=False | |
is_correct_document=True | |
if is_correct_answer is not None and is_correct_document is not None: | |
try: | |
send_feedback( | |
query=question, | |
answer_obj=result["_raw"], | |
is_correct_answer=is_correct_answer, | |
is_correct_document=is_correct_document, | |
document=result["document"] | |
) | |
st.success("β¨ Thanks for your feedback! β¨") | |
except Exception as e: | |
logging.exception(e) | |
st.error("π An error occurred while submitting your feedback!") | |
st.write("___") | |
# if debug: | |
# st.subheader("REST API JSON response") | |
# st.write(st.session_state.raw_json) | |
main() | |