Zotero example uses retired docs.generate_search_query()

[rbpasker]

I'm looking to update this gist:
https://gist.github.com/lifan0127/e34bb0cfbf7f03dc6852fd3e80b8fb19#file-paper-qa-zotero-py-L21

which uses the outdated method 'docs.generate_search_query()' to generate keywords to search ZoteroDB

the paper-qa doc here: https://github.com/Future-House/paper-qa?tab=readme-ov-file#zotero
doesnt use a generated search query, but rather a fixed one 'large language models'

I'm wondering how to get paper_qa to generate query terms that can be submitted to ZoteroDB to find and download only those papers which might be applicable, rather than a fixed set, as in the example.

[dosubot[bot]]

Hey @rbpasker! I'm here to assist you with any issues or questions you have. Let's tackle this together!

To update your paper-qa-zotero.py script for dynamic query generation, you can replace the outdated docs.generate_search_query() method with a more flexible approach using an LLM to generate keywords. Here's a basic example of how you might implement this:

from paperqa import Docs
from paperqa.contrib import ZoteroDB
from some_llm_library import generate_keywords  # Hypothetical function to generate keywords

docs = Docs()
zotero = ZoteroDB(library_type="user")  # Use "group" if it's a group library

# Generate dynamic query terms using an LLM
query_terms = generate_keywords("Enter your topic or question here")

for item in zotero.iterate(
    q=query_terms,
    qmode="everything",
    sort="date",
    direction="desc",
    limit=100,
):
    print("Adding", item.title)
    docs.add(item.pdf, docname=item.key)

In this example, generate_keywords is a placeholder for a function that would use an LLM to generate relevant keywords based on a given topic or question. You would need to implement this function using an appropriate LLM library that fits your needs. This approach allows the script to dynamically adjust the search terms based on the context or input provided, rather than using a fixed search term like "large language models" ^[1].

To continue talking to Dosu, mention @dosu.

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[rbpasker]

ok Dosu -- this generate_keywords() hypothetical function used to be in paper-qa as docs.generate_search_query()

[rbpasker]

going through the docs again, I see:

1. Paper Search | - Get candidate papers from LLM-generated keyword query
     | - Chunk, embed, and add candidate papers to state

but its not clear how to perform the "Paper Search" against the Zotero search engine

[dosubot[bot]]

To perform a "Paper Search" against the Zotero search engine using the Paper QA library, you can follow these steps:

1. Generate Keywords: Since the docs.generate_search_query() method is outdated, you need to generate keywords dynamically. You can use an LLM (Large Language Model) to generate these keywords based on your input question or topic. This involves using an external library or service that can process text and return relevant keywords.

2. Query Zotero: Use the ZoteroDB class from the Paper QA library to interact with your Zotero library. You can customize your search using the zotero.iterate() method, which allows you to specify search parameters such as q for the query, qmode for the search mode, and other options like sort and limit to refine your search results ^[1].

Here's a conceptual example of how you might implement this:

from paperqa.contrib import ZoteroDB
from some_llm_library import generate_keywords  # Hypothetical function to generate keywords

# Initialize ZoteroDB
zotero = ZoteroDB(library_type="user")  # Use "group" if it's a group library

# Generate dynamic query terms using an LLM
query_terms = generate_keywords("Enter your topic or question here")

# Perform the search in Zotero
for item in zotero.iterate(
    q=query_terms,
    qmode="everything",
    sort="date",
    direction="desc",
    limit=100,
):
    print("Found paper:", item.title)
    # You can add logic here to download or process the papers

In this example, generate_keywords is a placeholder for a function that would use an LLM to generate relevant keywords. You would need to implement this function using an appropriate LLM library. This approach allows you to dynamically adjust the search terms based on the context or input provided, enabling more relevant searches in your Zotero library.

To continue talking to Dosu, mention @dosu.

---

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