streamlit pages

pages/config.py

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+import json
+
+import streamlit as st
+from pydantic import ValidationError
+
+from pages.navigation import show_stepper
+from src.schemas.requests import SampleInput
+
+show_stepper("Configuration")
+
+SAMPLE_INPUT = json.dumps(
+    [
+        {
+            "id": 0,
+            "text": "Google had solid Q4 2025 earnings but Microsoft's were not great.",
+            "entities": [
+                {
+                    "entity_id": 0,
+                    "entity_text": "Google",
+                    "entity_type": "company",
+                    "positions": [
+                        {"position_text": "Google", "length": 6, "offset": 0}
+                    ],
+                },
+                {
+                    "entity_id": 1,
+                    "entity_text": "Microsoft",
+                    "entity_type": "company",
+                    "positions": [
+                        {"position_text": "Microsoft", "length": 9, "offset": 40}
+                    ],
+                },
+            ],
+        }
+    ],
+    indent=2,
+)
+
+st.header("Configuration")
+
+endpoint = st.selectbox(
+    "Endpoint",
+    options=["predict", "predict-all-models"],
+    index=0,
+)
+st.session_state.endpoint = endpoint
+
+st.subheader("Input samples (JSON)")
+default = st.session_state.get("input_json", SAMPLE_INPUT)
+input_json = st.text_area("Paste your JSON input here:", value=default, height=300)
+st.session_state.input_json = input_json
+
+col1, col2 = st.columns(2)
+with col1:
+    if st.button("Previous", use_container_width=True):
+        st.switch_page("pages/welcome.py")
+with col2:
+    if st.button("Run prediction", use_container_width=True):
+        try:
+            parsed = json.loads(input_json)
+            if not isinstance(parsed, list):
+                raise ValueError("Input must be a JSON array of samples.")
+            for item in parsed:
+                SampleInput(**item)
+            st.switch_page("pages/result.py")
+        except json.JSONDecodeError as e:
+            st.error(f"Invalid JSON: {e}")
+        except (ValueError, ValidationError) as e:
+            st.error(f"Invalid input: {e}")

pages/navigation.py

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+import streamlit as st
+
+PAGES = [
+    ("Welcome", "pages/welcome.py"),
+    ("Configuration", "pages/config.py"),
+    ("Results", "pages/result.py"),
+]
+
+
+def show_stepper(current: str):
+    """Render a horizontal step indicator. `current` is the page title."""
+    cols = st.columns(len(PAGES))
+    for i, (title, path) in enumerate(PAGES):
+        with cols[i]:
+            if title == current:
+                st.markdown(
+                    f"<div style='text-align:center; padding:8px 0; "
+                    f"border-bottom:3px solid #ff4b4b; font-weight:700;'>"
+                    f"{i + 1}. {title}</div>",
+                    unsafe_allow_html=True,
+                )
+            else:
+                st.markdown(
+                    f"<div style='text-align:center; padding:8px 0; "
+                    f"border-bottom:3px solid #444; color:#888;'>"
+                    f"{i + 1}. {title}</div>",
+                    unsafe_allow_html=True,
+                )
+    st.write("")

pages/result.py

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+import json
+
+import streamlit as st
+
+from pages.navigation import show_stepper
+from src.fe_handler import call_predict, call_predict_all
+
+show_stepper("Results")
+
+st.header("Results")
+
+input_json = st.session_state.get("input_json")
+
+if not input_json:
+    st.warning("No input provided. Go back and provide samples.")
+    if st.button("Back to config", use_container_width=True):
+        st.switch_page("pages/config.py")
+    st.stop()
+
+try:
+    parsed = json.loads(input_json)
+except (json.JSONDecodeError, ValueError) as e:
+    st.error(f"Invalid input: {e}")
+    if st.button("Back to config", use_container_width=True):
+        st.switch_page("pages/config.py")
+    st.stop()
+
+endpoint = st.session_state.get("endpoint", "predict")
+
+try:
+    with st.spinner("Running prediction..."):
+        if endpoint == "predict":
+            results = call_predict(parsed)
+            _single = True
+        else:
+            results = call_predict_all(parsed)
+            _single = False
+
+    if _single:
+        for sample in results:
+            st.markdown(f"**Sample {sample['id']}**")
+            for entity in sample["entities"]:
+                color = {"positive": "green", "neutral": "gray", "negative": "red"}.get(
+                    entity["classification"], "gray"
+                )
+                st.markdown(f"- {entity['entity_text']}: :{color}[{entity['classification']}]")
+    else:
+        tabs = st.tabs(list(results.keys()))
+        for tab, (mode, preds) in zip(tabs, results.items()):
+            with tab:
+                for sample in preds:
+                    st.markdown(f"**Sample {sample['id']}**")
+                    for entity in sample["entities"]:
+                        color = {"positive": "green", "neutral": "gray", "negative": "red"}.get(
+                            entity["classification"], "gray"
+                        )
+                        st.markdown(f"- {entity['entity_text']}: :{color}[{entity['classification']}]")
+except Exception as e:
+    st.error(f"Prediction failed: {e}")
+
+st.write("")
+if st.button("Back to config", use_container_width=True):
+    st.switch_page("pages/config.py")

pages/welcome.py

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+import streamlit as st
+
+from pages.navigation import show_stepper
+from src.fe_handler import check_health
+
+show_stepper("Welcome")
+
+st.header("Entity Sentiment Classification")
+st.write(
+    "This tool classifies sentiment (positive, neutral, negative) "
+    "for specific entities mentioned in text articles."
+)
+st.subheader("Available endpoints")
+st.markdown(
+    "- **`/predict`** — classify entities using a single model (marker)\n"
+    "- **`/predict-all-models`** — classify entities using all available models "
+    "and compare their results side by side"
+)
+
+if check_health():
+    st.success("Backend is running.")
+else:
+    st.error("Backend is not reachable. Make sure the FastAPI server is running.")
+
+st.write("")
+if st.button("Next", use_container_width=True):
+    st.switch_page("pages/config.py")