Bases: BaseReader
Rayyan reader. Reads articles from a Rayyan review.
Parameters:
| Name |
Type |
Description |
Default |
credentials_path
|
str
|
|
required
|
rayyan_url
|
str
|
Rayyan URL. Defaults to https://rayyan.ai.
Set to an alternative URL if you are using a non-production Rayyan instance.
|
'https://rayyan.ai'
|
Source code in llama-index-integrations/readers/llama-index-readers-rayyan/llama_index/readers/rayyan/base.py
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112 | class RayyanReader(BaseReader):
"""Rayyan reader. Reads articles from a Rayyan review.
Args:
credentials_path (str): Rayyan credentials path.
rayyan_url (str, optional): Rayyan URL. Defaults to https://rayyan.ai.
Set to an alternative URL if you are using a non-production Rayyan instance.
"""
def __init__(
self, credentials_path: str, rayyan_url: str = "https://rayyan.ai"
) -> None:
"""Initialize Rayyan reader."""
from rayyan import Rayyan
from rayyan.user import User
logging.debug("Initializing Rayyan reader...")
self.rayyan = Rayyan(credentials_path, url=rayyan_url)
user = User(self.rayyan).get_info()
logging.info(f"Signed in successfully to Rayyan as: {user['displayName']}!")
def load_data(self, review_id: str, filters: dict = {}) -> List[Document]:
"""Load articles from a review.
Args:
review_id (int): Rayyan review ID.
filters (dict, optional): Filters to apply to the review. Defaults to None. Passed to
the Rayyan review results method as is.
Returns:
List[Document]: List of documents.
"""
from tenacity import (
retry,
stop_after_attempt,
stop_after_delay,
stop_all,
wait_random_exponential,
)
from tqdm import tqdm
from rayyan.review import Review
rayyan_review = Review(self.rayyan)
my_review = rayyan_review.get(review_id)
logging.info(
f"Working on review: '{my_review['title']}' with {my_review['total_articles']} total articles."
)
result_params = {"start": 0, "length": 100}
result_params.update(filters)
@retry(
wait=wait_random_exponential(min=1, max=10),
stop=stop_all(stop_after_attempt(3), stop_after_delay(30)),
)
def fetch_results_with_retry():
logging.debug("Fetch parameters: %s", result_params)
return rayyan_review.results(review_id, result_params)
articles = []
logging.info("Fetching articles from Rayyan...")
total = my_review["total_articles"]
with tqdm(total=total) as pbar:
while len(articles) < total:
# retrieve articles in batches
review_results = fetch_results_with_retry()
fetched_articles = review_results["data"]
articles.extend(fetched_articles)
# update total in case filters are applied
if total != review_results["recordsFiltered"]:
total = review_results["recordsFiltered"]
pbar.total = total
result_params["start"] += len(fetched_articles)
pbar.update(len(fetched_articles))
results = []
for article in articles:
# iterate over all abstracts
abstracts = ""
if article["abstracts"] is not None:
abstracts_arr = [
abstract["content"] for abstract in article["abstracts"]
]
if len(abstracts_arr) > 0:
# map array into a string
abstracts = "\n".join(abstracts_arr)[0:1024].strip()
title = article["title"]
if title is not None:
title = title.strip()
body = f"{title}\n{abstracts}"
if body.strip() == "":
continue
extra_info = {"id": article["id"], "title": title}
results.append(
Document(
text=body,
extra_info=extra_info,
)
)
return results
|
load_data
load_data(review_id: str, filters: dict = {}) -> List[Document]
Load articles from a review.
Parameters:
| Name |
Type |
Description |
Default |
review_id
|
int
|
|
required
|
filters
|
dict
|
Filters to apply to the review. Defaults to None. Passed to
the Rayyan review results method as is.
|
{}
|
Returns:
| Type |
Description |
List[Document]
|
List[Document]: List of documents.
|
Source code in llama-index-integrations/readers/llama-index-readers-rayyan/llama_index/readers/rayyan/base.py
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112 | def load_data(self, review_id: str, filters: dict = {}) -> List[Document]:
"""Load articles from a review.
Args:
review_id (int): Rayyan review ID.
filters (dict, optional): Filters to apply to the review. Defaults to None. Passed to
the Rayyan review results method as is.
Returns:
List[Document]: List of documents.
"""
from tenacity import (
retry,
stop_after_attempt,
stop_after_delay,
stop_all,
wait_random_exponential,
)
from tqdm import tqdm
from rayyan.review import Review
rayyan_review = Review(self.rayyan)
my_review = rayyan_review.get(review_id)
logging.info(
f"Working on review: '{my_review['title']}' with {my_review['total_articles']} total articles."
)
result_params = {"start": 0, "length": 100}
result_params.update(filters)
@retry(
wait=wait_random_exponential(min=1, max=10),
stop=stop_all(stop_after_attempt(3), stop_after_delay(30)),
)
def fetch_results_with_retry():
logging.debug("Fetch parameters: %s", result_params)
return rayyan_review.results(review_id, result_params)
articles = []
logging.info("Fetching articles from Rayyan...")
total = my_review["total_articles"]
with tqdm(total=total) as pbar:
while len(articles) < total:
# retrieve articles in batches
review_results = fetch_results_with_retry()
fetched_articles = review_results["data"]
articles.extend(fetched_articles)
# update total in case filters are applied
if total != review_results["recordsFiltered"]:
total = review_results["recordsFiltered"]
pbar.total = total
result_params["start"] += len(fetched_articles)
pbar.update(len(fetched_articles))
results = []
for article in articles:
# iterate over all abstracts
abstracts = ""
if article["abstracts"] is not None:
abstracts_arr = [
abstract["content"] for abstract in article["abstracts"]
]
if len(abstracts_arr) > 0:
# map array into a string
abstracts = "\n".join(abstracts_arr)[0:1024].strip()
title = article["title"]
if title is not None:
title = title.strip()
body = f"{title}\n{abstracts}"
if body.strip() == "":
continue
extra_info = {"id": article["id"], "title": title}
results.append(
Document(
text=body,
extra_info=extra_info,
)
)
return results
|
