from functools import partial
import anyio
import streamlit as st
from architxt.bucket import TreeBucket
from architxt.llm import get_chat_model
from architxt.simplification.llm import llm_rewrite
from architxt.simplification.tree_rewriting import rewrite
from architxt.ui.utils import get_forest, update_metrics
def _render_rule_based_simplification(forest: TreeBucket) -> None:
c1, c2 = st.columns(2)
tau = c1.number_input('Tau (Similarity)', 0.0, 1.0, 0.8)
decay = c2.number_input('Decay', min_value=0.0, value=2.0)
min_support = c1.number_input('Min Support', min_value=1, value=10)
epoch = c2.number_input('Epochs', min_value=1, value=50)
schema_similarity = st.selectbox("Compute similarity on", ('instance', 'schema'), index=0)
if st.button("Apply Rule-Based Simplification"):
with st.spinner("Simplifying..."):
rewrite(
forest,
tau=tau,
decay=decay,
epoch=epoch,
min_support=min_support,
schema_similarity=schema_similarity == 'schema',
)
update_metrics()
def _render_llm_based_simplification(forest: TreeBucket) -> None:
st.warning("LLM Simplification requires extra dependencies and an LLM provider.")
local: bool = st.session_state.get("llm_local", False)
c1, c2 = st.columns(2)
model_provider = c1.text_input("Provider", "huggingface", disabled=local)
model_name = c2.text_input("Model", value="deepseek-ai/DeepSeek-V3")
with st.expander("Advanced LLM Settings"):
c1, c2, c3 = st.columns(3)
temperature = c1.number_input("Temperature", 0.0, 1.0, 0.2)
max_tokens = c2.number_input("Max Tokens", min_value=256, value=4096, step=128)
refining_steps = c3.number_input("Refining Steps", min_value=0, value=3)
tau = c1.number_input('Tau (Similarity)', 0.0, 1.0, 0.8)
decay = c2.number_input('Decay', min_value=0.0, value=2.0)
min_support = c3.number_input('Min Support', min_value=1, value=10)
if st.button("Apply LLM Simplification"):
with st.status("Simplifying..."):
st.write("Loading LLM...")
llm = get_chat_model(
model_provider,
model_name,
max_tokens=max_tokens,
temperature=temperature,
local=local,
openvino=st.session_state.get("llm_openvino", False),
)
transform = partial(
llm_rewrite,
llm=llm,
max_tokens=max_tokens,
tau=tau,
decay=decay,
min_support=min_support,
refining_steps=refining_steps,
)
st.write("Simplifying...")
anyio.run(transform, forest)
update_metrics()
TRANSFORMER = {
"Default (rule-based)": _render_rule_based_simplification,
"LLM": _render_llm_based_simplification,
}
[docs]
@st.fragment
def simplification() -> None:
st.header("Simplify")
forest = get_forest()
if len(forest) == 0:
st.info("No data loaded. Please import data using the top menu.")
else:
method = st.selectbox("Method", TRANSFORMER.keys())
TRANSFORMER[method](forest)
