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ac2020e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | """Display components for LegisQA"""
import streamlit as st
from legisqa_local.utils.text import escape_markdown, replace_legis_ids_with_urls
from legisqa_local.utils.usage import display_api_usage
from legisqa_local.utils.formatting import render_retrieved_chunks
from legisqa_local.config.models import PROVIDER_MODELS
def render_example_queries():
"""Render example queries in an expander"""
with st.expander("Example Queries"):
st.write(
"""
```
What are the themes around artificial intelligence?
```
```
Write a well cited 3 paragraph essay on food insecurity.
```
```
Create a table summarizing major climate change ideas with columns legis_id, title, idea.
```
```
Write an action plan to keep social security solvent.
```
```
Suggest reforms that would benefit the Medicaid program.
```
"""
)
def render_response(
response: dict,
model_info: dict,
provider: str,
should_escape_markdown: bool,
should_add_legis_urls: bool,
tag: str | None = None,
):
"""Render a RAG response with usage information and retrieved chunks"""
response_text = response["aimessage"].content
if should_escape_markdown:
response_text = escape_markdown(response_text)
if should_add_legis_urls:
response_text = replace_legis_ids_with_urls(response_text)
with st.container(border=True):
if tag is None:
st.write("Response")
else:
st.write(f"Response ({tag})")
st.info(response_text)
display_api_usage(response["aimessage"], model_info, provider, tag=tag)
render_retrieved_chunks(response["docs"], tag=tag)
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