mirror of
https://github.com/deepset-ai/haystack.git
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9dc89d2bd2
* Fix a path issue in Dockerfile-GPU * Fix paths in Dockerfile-GPU * Add workflow_dispatch to docker build task * Remove reference to optional component from ui/, not needed anymore * Move pytorch installation last to avoid replacing it later * Remove optional import from rest_api too, no more needed * Change path in ui/Dockerfile * ui container works again * Complete review of import paths Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
124 lines
3.9 KiB
Python
124 lines
3.9 KiB
Python
from typing import List, Dict, Any, Tuple
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import os
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import logging
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import requests
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from time import sleep
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from uuid import uuid4
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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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STATUS = "initialized"
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HS_VERSION = "hs_version"
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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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def haystack_is_ready():
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"""
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Used to show the "Haystack is loading..." message
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"""
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url = f"{API_ENDPOINT}/{STATUS}"
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try:
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if requests.get(url).status_code < 400:
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return True
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except Exception as e:
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logging.exception(e)
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sleep(1) # To avoid spamming a non-existing endpoint at startup
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return False
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@st.cache
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def haystack_version():
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"""
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Get the Haystack version from the REST API
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"""
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url = f"{API_ENDPOINT}/{HS_VERSION}"
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return requests.get(url, timeout=0.1).json()["hs_version"]
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def query(query, filters={}, top_k_reader=5, top_k_retriever=5) -> Tuple[List[Dict[str, Any]], Dict[str, str]]:
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"""
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Send a query to the REST API and parse the answer.
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Returns both a ready-to-use representation of the results and the raw JSON.
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"""
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url = f"{API_ENDPOINT}/{DOC_REQUEST}"
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params = {"filters": filters, "Retriever": {"top_k": top_k_retriever}, "Reader": {"top_k": top_k_reader}}
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req = {"query": query, "params": params}
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response_raw = requests.post(url, json=req)
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if response_raw.status_code >= 400 and response_raw.status_code != 503:
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raise Exception(f"{vars(response_raw)}")
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response = response_raw.json()
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if "errors" in response:
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raise Exception(", ".join(response["errors"]))
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# Format response
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results = []
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answers = response["answers"]
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for answer in answers:
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if answer.get("answer", None):
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results.append(
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{
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"context": "..." + answer["context"] + "...",
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"answer": answer.get("answer", None),
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"source": answer["meta"]["name"],
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"relevance": round(answer["score"] * 100, 2),
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"document": [doc for doc in response["documents"] if doc["id"] == answer["document_id"]][0],
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"offset_start_in_doc": answer["offsets_in_document"][0]["start"],
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"_raw": answer,
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}
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)
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else:
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results.append(
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{
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"context": None,
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"answer": None,
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"document": None,
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"relevance": round(answer["score"] * 100, 2),
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"_raw": answer,
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}
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)
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return results, response
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def send_feedback(query, answer_obj, is_correct_answer, is_correct_document, document) -> None:
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"""
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Send a feedback (label) to the REST API
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"""
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url = f"{API_ENDPOINT}/{DOC_FEEDBACK}"
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req = {
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"id": str(uuid4()),
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"query": query,
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"document": document,
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"is_correct_answer": is_correct_answer,
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"is_correct_document": is_correct_document,
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"origin": "user-feedback",
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"answer": answer_obj,
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}
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response_raw = requests.post(url, json=req)
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if response_raw.status_code >= 400:
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raise ValueError(f"An error was returned [code {response_raw.status_code}]: {response_raw.json()}")
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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 = requests.post(url, files=files).json()
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return response
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def get_backlink(result) -> Tuple[str, str]:
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if result.get("document", None):
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doc = result["document"]
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if isinstance(doc, dict):
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if doc.get("meta", None):
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if isinstance(doc["meta"], dict):
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if doc["meta"].get("url", None) and doc["meta"].get("title", None):
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return doc["meta"]["url"], doc["meta"]["title"]
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return None, None
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