mirror of
https://github.com/deepset-ai/haystack.git
synced 2025-07-25 09:50:14 +00:00
eb990c9688
* Removing probability field from reader and from test cases * Add switch to FARMReader to choose score/probability * Remove probability field from doc returned by doc store * Relax assertion testing joined es and dpr predictions * Use switch for confidence scores also for no_answer * Add test that checks switching to old answer scores > 10 * Normalize score in elastic doc store and reset reader.md * Scale weights of JoinDocuments to sum to 1 and adapt test case
64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
import os
|
|
|
|
import requests
|
|
import streamlit as st
|
|
|
|
API_ENDPOINT = os.getenv("API_ENDPOINT", "http://localhost:8000")
|
|
DOC_REQUEST = "query"
|
|
DOC_FEEDBACK = "feedback"
|
|
DOC_UPLOAD = "file-upload"
|
|
|
|
|
|
@st.cache(show_spinner=False)
|
|
def retrieve_doc(query, filters=None, top_k_reader=5, top_k_retriever=5):
|
|
# Query Haystack API
|
|
url = f"{API_ENDPOINT}/{DOC_REQUEST}"
|
|
req = {"query": query, "filters": filters, "top_k_retriever": top_k_retriever, "top_k_reader": top_k_reader}
|
|
response_raw = requests.post(url, json=req).json()
|
|
|
|
# Format response
|
|
result = []
|
|
answers = response_raw["answers"]
|
|
for i in range(len(answers)):
|
|
answer = answers[i]["answer"]
|
|
if answer:
|
|
context = "..." + answers[i]["context"] + "..."
|
|
meta_name = answers[i]["meta"]["name"]
|
|
relevance = round(answers[i]["score"] * 100, 2)
|
|
document_id = answers[i]["document_id"]
|
|
offset_start_in_doc = answers[i]["offset_start_in_doc"]
|
|
result.append(
|
|
{
|
|
"context": context,
|
|
"answer": answer,
|
|
"source": meta_name,
|
|
"relevance": relevance,
|
|
"document_id": document_id,
|
|
"offset_start_in_doc": offset_start_in_doc,
|
|
}
|
|
)
|
|
return result, response_raw
|
|
|
|
|
|
def feedback_doc(question, is_correct_answer, document_id, model_id, is_correct_document, answer, offset_start_in_doc):
|
|
# Feedback Haystack API
|
|
url = f"{API_ENDPOINT}/{DOC_FEEDBACK}"
|
|
req = {
|
|
"question": question,
|
|
"is_correct_answer": is_correct_answer,
|
|
"document_id": document_id,
|
|
"model_id": model_id,
|
|
"is_correct_document": is_correct_document,
|
|
"answer": answer,
|
|
"offset_start_in_doc": offset_start_in_doc,
|
|
}
|
|
response_raw = requests.post(url, json=req).json()
|
|
return response_raw
|
|
|
|
|
|
def upload_doc(file):
|
|
url = f"{API_ENDPOINT}/{DOC_UPLOAD}"
|
|
files = [("files", file)]
|
|
response_raw = requests.post(url, files=files).json()
|
|
return response_raw
|