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062f9f4 a9a6418 062f9f4 a9a6418 062f9f4 a9a6418 062f9f4 a9a6418 062f9f4 a9a6418 062f9f4 a9a6418 062f9f4 | 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 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | import streamlit as st
from graph_pipeline import textdoctor_app, TextDoctorState
st.set_page_config(
page_title="TextDoctor – Multi-Agent Text Polisher",
page_icon="🩺",
layout="wide"
)
st.title("🩺 TextDoctor – Multi-Agent Text Improvement")
st.write(
"Give me your **informal / messy text**, and I’ll run it through "
"grammar, style, and clarity agents, then a reviewer agent will pick "
"the best professional version with explanations."
)
# --- Input area ---
default_example = (
"bro i need 2 more days for this, hope thats okay, "
"i had some issues so couldnt finish on time"
)
user_text = st.text_area(
"Enter your text here:",
value=default_example,
height=150
)
col1, _ = st.columns([1, 3])
with col1:
run_button = st.button("Run TextDoctor 🚀")
if run_button and user_text.strip():
with st.spinner("Running multi-agent pipeline..."):
try:
# Prepare initial state for LangGraph app
state: TextDoctorState = {"input_text": user_text}
final_state = textdoctor_app.invoke(state)
except Exception as e:
st.error(f"Something went wrong while running the pipeline: {e}")
st.stop()
review = final_state["review_result"]
final_text = review["final_text"]
st.subheader("✅ Final Professional Version")
st.success(final_text)
with st.expander("🧠 Why this version? (Reviewer Agent Explanation)", expanded=False):
st.write(review["decision_explanation"])
# --- Show intermediate steps ---
st.subheader("🔍 Agent-wise Transformations")
tab1, tab2, tab3 = st.tabs(["Grammar Agent", "Style Agent", "Clarity Agent"])
with tab1:
g_res = final_state["grammar_result"]
st.markdown("**Output:**")
st.write(g_res["corrected"])
st.markdown(f"**Agent confidence:** `{g_res.get('confidence', 'N/A')}`")
st.markdown("**Changes detected:**")
if g_res.get("changes"):
for c in g_res["changes"]:
st.write(f"- `{c.get('from')}` → `{c.get('to')}` ({c.get('type')})")
else:
st.write("No explicit changes detected or diff too small.")
with tab2:
s_res = final_state["style_result"]
st.markdown("**Output:**")
st.write(s_res["styled"])
st.markdown(f"**Agent confidence:** `{s_res.get('confidence', 'N/A')}`")
st.markdown("**Changes detected:**")
if s_res.get("changes"):
for c in s_res["changes"]:
st.write(f"- `{c.get('from')}` → `{c.get('to')}` ({c.get('type')})")
else:
st.write("No explicit changes detected or diff too small.")
with tab3:
c_res = final_state["clarity_result"]
st.markdown("**Output:**")
st.write(c_res["clarified"])
st.markdown(f"**Agent confidence:** `{c_res.get('confidence', 'N/A')}`")
st.markdown("**Changes detected:**")
if c_res.get("changes"):
for c in c_res["changes"]:
st.write(f"- `{c.get('from')}` → `{c.get('to')}` ({c.get('type')})")
else:
st.write("No explicit changes detected or diff too small.")
# --- Candidate scores table ---
st.subheader("📊 Candidate Comparison (Reviewer Agent)")
cand_rows = []
for c in review["candidates"]:
cand_rows.append({
"Candidate": c["name"],
"Score": c["score"],
"Text": c["text"],
"Notes": c["notes"]
})
st.dataframe(cand_rows)
elif run_button and not user_text.strip():
st.warning("Please enter some text before running TextDoctor.")
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