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import streamlit as st
# st.set_page_config(layout="wide")
from ring import LLM_GPT35
from ring import LLM_GPT4
from ring import LLM_GPT4o
from ring import LLM_LLAMA2
from ring import LLM_GEMINI
from ring import LLM_AI21
from ring import LLM_Claude2
from ring import LLM_Cohere
from ring import PREF_ORDER_LLMS
from ring import requires_openai_key
from ring import get_openai_api_key
from ring import generate_response
from ring import generate_panel_response
__version__ = "0.2.2"
col1, col2 = st.columns([3, 1])
with col1:
st.title("OpenWormLLM")
st.markdown("**v%s** - Note: work in progress!" % __version__)
with col2:
st.image("images/OpenWormLogo.png")
tab_free, tab_panel, tab_pubs, tab_data, tab_corpus, tab_model, tab_about = st.tabs(
[
"Individual LLMs",
"Panel discussion",
"Publications",
"Structured data",
"OpenWorm Corpus",
"Run model",
"About",
]
)
with tab_free:
st.markdown("**Ask individual LLMs questions about _C. elegans_**")
with st.form("form_free"):
text = st.text_area(
"Ask a question related to _C. elegans_:",
"What is the primary role of the C. elegans neuron AVBL?",
)
llm_ver = st.selectbox("Which LLM version should I use?", PREF_ORDER_LLMS)
temperature = st.text_input("Temperature", value=0.1)
only_celegans = st.checkbox(
"Only answer questions related to _C. elegans_", value=True, disabled=True
)
submitted = st.form_submit_button("Submit")
if requires_openai_key(llm_ver) and not get_openai_api_key():
st.info("Please add your OpenAI API key to continue.")
elif submitted:
response = generate_response(text, llm_ver, temperature, only_celegans)
st.info(response)
with tab_panel:
st.markdown("**Get a consensus answer across multiple LLMs**")
with st.form("form_panel"):
text = st.text_area(
"Ask a question related to _C. elegans_:",
"What is the typical length of the worm C. elegans?",
)
temperature = st.text_input("Temperature", value=0.1)
###Start of Kaan Changes
# Selectbox to determine which LLM becomes panel lead
st.markdown(
"<style> .stRadio> div {gap:30px;} </style>",
unsafe_allow_html=True,
)
panel_lead = st.radio(
"Which LLM would you like to lead this panel?",
PREF_ORDER_LLMS,
horizontal=True,
)
# Create checkboxes to determine which LLMs are included in the panel
st.markdown(
"<div style='text-align: left; font-size: 14px;'>Which LLMs would you like to attend the panel?</div>",
unsafe_allow_html=True,
)
options = PREF_ORDER_LLMS # [llm for llm in PREF_ORDER_LLMS if llm !=panel_lead] creates a list of options excluding the chosen panel lead
selected_options = []
#Put checkboxes into table arranged 4x2
for row in range(2): # 2 rows
cols = st.columns(4) # 4 columns in each row
for col in range(4): # Iterate over each column
index = row * 4 + col
if index < len(options):
with cols[col]:
selected = st.checkbox(options[index], key=options[index])
if selected:
selected_options.append(options[index])
submitted = st.form_submit_button("Submit")
if len(selected_options) == 1 and panel_lead in selected_options:
st.markdown("Please choose a panelist that is not the panel lead.")
elif len(selected_options) == 0:
st.markdown("Please choose a panelist to join the panel lead.")
elif requires_openai_key(llm_ver) and not get_openai_api_key():
st.info("Please add your OpenAI API key to continue.")
elif submitted:
# Create new list of LLMs that does not include panel lead
llm_panelists = [llm for llm in selected_options if llm != panel_lead]
response = generate_panel_response(
text,
llm_panelists=llm_panelists,
llm_panel_chair=panel_lead,
temperature=temperature,
)
st.info(response)
with tab_pubs:
from publications import find_basis_paper
st.markdown(
"**Find literature related to _C. elegans._** Uses: [Semantic Scholar](https://www.semanticscholar.org)"
)
with st.form("form_pubs"):
text = st.text_input("Enter a topic:", "C. elegans locomotion")
num = st.text_input("Number of results", value=10)
submitted = st.form_submit_button("Submit")
if submitted:
response = find_basis_paper(query=text, result_limit=num)
st.info(response)
with tab_data:
st.markdown("**Query structured datasets**")
with st.form("form_data"):
from datasources import DS_WORMNEUROATLAS
from datasources import FORMATS
from datasources import query_data_source
text = st.text_area("Which neuron would you like to know about?", "AVBL")
source = st.selectbox("Select data source to use:", (DS_WORMNEUROATLAS,))
format = st.selectbox("Return format:", FORMATS)
submitted = st.form_submit_button("Submit")
if submitted:
response = query_data_source(text, source, format)
st.info(response)
with tab_corpus:
from corpus_query import run_query
st.markdown(
"**Search a (small) corpus of _C. elegans_ literature** Uses: [paper-qa](https://github.com/whitead/paper-qa)"
)
with st.form("form_corpus"):
text = st.text_input(
"Enter a query:",
"What types of ion channels are present in C. elegans neurons?",
)
llm_ver = st.selectbox(
"Which LLM version should I use?", (LLM_LLAMA2, LLM_GPT4o)
)
submitted = st.form_submit_button("Submit")
if submitted:
response = run_query(query=text, llm_ver=llm_ver)
st.info(response)
with tab_model:
st.markdown("**Run a _C. elegans_ cell model**")
with st.form("form_model"):
from model import run_model
from model import MODELS
text = st.text_area("Current injection level:", "4.1 pA")
model_to_sim = st.selectbox("Model to simulate", list(MODELS.keys()))
submitted = st.form_submit_button("Submit")
if submitted:
response, traces, events = run_model(text, model_to_sim)
st.info(response)
try:
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
for key in sorted(traces.keys()):
if key != "t":
ts = traces["t"]
vs = traces[key]
ax.plot(ts, vs, label=key)
ax.legend()
plt.xlabel("Time (s)")
plt.ylabel("(SI units)")
st.pyplot(fig)
except Exception as e:
st.info("There was a problem...\n\n%s" % e)
with tab_about:
st.markdown('### About "Project Sydney"')
st.markdown(
"This is an initiative by the [OpenWorm project](https://openworm.org) to investigate the use of LLMs for interacting with scientific literature and structured datasets related to _C. elegans_."
)
st.markdown("**Work in progress!!** Subject to change/removal without notice!")
|