app.py

from openai import OpenAI
import panel as pn
import requests
import os

pn.extension()

# format this URL with query and number of rows
API_URL = "https://api.crossref.org/works"
# API_KEY = os.environ["ELSEVIER_API_KEY"]
# URL_FMT = "https://api.elsevier.com/content/search/scopus"
DEFAULT_PROMPT_TEMPLATE = """
Here are the papers related to {query}

Help me summarize these into bullet points, readable within 2 minutes.

{items}
"""


def get_relevant_papers(query, rows):
    params = {
        "query.bibliographic": query,
        "rows": rows,
    }
    response = requests.get(API_URL, params=params)
    output = response.json()
    return output


def process_inputs(contents, user, instance):
    output = get_relevant_papers(contents, rows_input.value)
    instance.send(pn.pane.JSON(output), respond=False, user="Sources")

    items = []
    for item in output["message"]["items"]:
        abstract = item.get("abstract", "")
        title = item["title"]
        url = item["URL"]
        items.append(f"{title}({url}): {abstract}")

    prompt = prompt_template_input.value.format(
        query=contents, items=items
    )
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        stream=True,
    )
    message = ""
    for chunk in response:
        part = chunk.choices[0].delta.content
        if part is not None:
            message += part
            yield message


client = OpenAI()

# define widgets
prompt_template_input = pn.widgets.TextAreaInput(
    value=DEFAULT_PROMPT_TEMPLATE.strip(), height=500
)
rows_input = pn.widgets.IntInput(name="Number of rows", value=2)
chat_interface = pn.chat.ChatInterface(callback=process_inputs, callback_exception="verbose")

# layout
sidebar = pn.Column(prompt_template_input, rows_input)
main = pn.Column(chat_interface)
pn.template.FastListTemplate(
    sidebar=[sidebar],
    main=[main],
    title="Elsevier Summarizer",
).servable()