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https://github.com/deepset-ai/haystack.git
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29e140196b
* [pipeline] Allow for batch indexing when using Pipelines fix #1168 * [pipeline] Test case fixed fix #1168 * [file_converter] Path.suffix updated #1168 * [file_converter] meta can be one of these three cases: A single dict that is applied to all files One dict for each file being converted None #1168 * [file_converter] mypy error fixed. * [file_converter] mypy error fixed. * [rest_api] batch file upload introduced in indexing API. * [test_case] Test_api file upload parameter name updated. * [ui] Streamlit file upload parameter updated.
64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
import os
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import requests
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import streamlit as st
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API_ENDPOINT = os.getenv("API_ENDPOINT", "http://localhost:8000")
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DOC_REQUEST = "query"
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DOC_FEEDBACK = "feedback"
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DOC_UPLOAD = "file-upload"
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@st.cache(show_spinner=False)
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def retrieve_doc(query, filters=None, top_k_reader=5, top_k_retriever=5):
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# Query Haystack API
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url = f"{API_ENDPOINT}/{DOC_REQUEST}"
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req = {"query": query, "filters": filters, "top_k_retriever": top_k_retriever, "top_k_reader": top_k_reader}
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response_raw = requests.post(url, json=req).json()
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# Format response
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result = []
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answers = response_raw["answers"]
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for i in range(len(answers)):
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answer = answers[i]["answer"]
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if answer:
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context = "..." + answers[i]["context"] + "..."
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meta_name = answers[i]["meta"]["name"]
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relevance = round(answers[i]["probability"] * 100, 2)
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document_id = answers[i]["document_id"]
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offset_start_in_doc = answers[i]["offset_start_in_doc"]
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result.append(
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{
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"context": context,
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"answer": answer,
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"source": meta_name,
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"relevance": relevance,
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"document_id": document_id,
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"offset_start_in_doc": offset_start_in_doc,
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}
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)
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return result, response_raw
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def feedback_doc(question, is_correct_answer, document_id, model_id, is_correct_document, answer, offset_start_in_doc):
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# Feedback Haystack API
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url = f"{API_ENDPOINT}/{DOC_FEEDBACK}"
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req = {
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"question": question,
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"is_correct_answer": is_correct_answer,
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"document_id": document_id,
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"model_id": model_id,
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"is_correct_document": is_correct_document,
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"answer": answer,
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"offset_start_in_doc": offset_start_in_doc,
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}
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response_raw = requests.post(url, json=req).json()
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return response_raw
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def upload_doc(file):
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url = f"{API_ENDPOINT}/{DOC_UPLOAD}"
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files = [("files", file)]
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response_raw = requests.post(url, files=files).json()
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return response_raw
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