stmnk
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Duplicate from stmnk/mlrefkws
Browse files- .gitattributes +34 -0
- README.md +13 -0
- app.py +39 -0
.gitattributes
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README.md
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---
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title: Mlrefkws
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emoji: 💻
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colorFrom: purple
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colorTo: green
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sdk: streamlit
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sdk_version: 1.17.0
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app_file: app.py
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pinned: false
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duplicated_from: stmnk/mlrefkws
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import os; import json; import requests
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import streamlit as st
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ES_URL = os.environ.get("ES_URL")
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question = 'What is the capital of Netherlands?'
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query_text = 'Query used for keyword search (you can also edit, and experiment with the responses)'
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written_question = st.text_input(query_text, question)
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if written_question:
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question = written_question
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if st.button('Run keyword search'):
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if question:
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try:
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url = f"{ES_URL}/document/_search?pretty"
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# payload = json.dumps({"query":{"match":{"content":"moldova"}}})
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payload = json.dumps({"query": {
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"more_like_this": { "like": question, # "What is the capital city of Netherlands?"
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"fields": ["content"], "min_term_freq": 1.9, "min_doc_freq": 4, "max_query_terms": 50
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}}})
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headers = {'Content-Type': 'application/json'}
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response = requests.request("GET", url, headers=headers, data=payload)
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kws_result = response.json() # print(response.text)
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# qa_result = pipe_exqa(question=question, context=paragraph)
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except Exception as e:
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qa_result = str(e)
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top_5_hits = kws_result['hits']['hits'][:5] # print("First 5 results:")
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top_5_text = [{'text': hit['_source']['content'][:500],
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'confidence': hit['_score']} for hit in top_5_hits ]
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for i, doc_hit in enumerate(top_5_text):
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st.subheader(f'Search result #{i+1} (and score):')
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st.write(f'<em>{doc_hit["text"]}...</em>', unsafe_allow_html = True)
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st.markdown(f'> (*confidence score*: **{format(doc_hit["confidence"], ".3f")}**)')
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st.write(f'Answer JSON: '); st.write(top_5_text) # st.write(qa_result)
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else:
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st.write('Write a query to submit your keyword search'); st.stop()
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