Upload app.py

app.py

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+import streamlit as st
+import pandas as pd
+from core import NHMQuery, run_structured_query
+from agent import create_agent
+from io import BytesIO
+
+st.set_page_config("NHM GBIF Explorer", layout="wide")
+st.title("NHM GBIF Explorer (LangChain)")
+
+# ---------- API KEY ----------
+st.sidebar.header("OpenAI")
+
+openai_api_key = st.sidebar.text_input(
+    "OpenAI API Key",
+    type="password",
+    help="Used only for this session"
+)
+
+# ---------- STRUCTURED QUERY ----------
+st.sidebar.header("Structured Query")
+
+scientific_name = st.sidebar.text_input("Scientific name", "Quercus robur")
+country = st.sidebar.text_input("Country (ISO)", "GB")
+year = st.sidebar.text_input("Year range", "1800,1950")
+limit = st.sidebar.number_input("Limit", 1, 500, 10)
+
+if st.sidebar.button("Run Query"):
+
+    if not openai_api_key:
+        st.sidebar.error("OpenAI API key is required")
+        st.stop()
+
+    query = NHMQuery(
+        scientific_name=scientific_name,
+        country=country,
+        year=year,
+        limit=limit
+    )
+
+    result = run_structured_query(query)
+
+    st.session_state.df = result["example_records"]
+    st.session_state.summary = result["summary"]
+    st.session_state.filters = result["applied_filters"]
+    st.session_state.agent = create_agent(
+        st.session_state.df,
+        openai_api_key
+    )
+    st.session_state.chat = []
+
+# ---------- DISPLAY ----------
+if "df" in st.session_state:
+
+    st.subheader("Applied Filters")
+    st.json(st.session_state.filters)
+
+    st.subheader("Summary")
+    st.json(st.session_state.summary)
+
+    st.subheader("Records Table (Raw GBIF Data)")
+    st.dataframe(st.session_state.df)
+
+    st.subheader("Chat with the Data")
+
+    user_msg = st.chat_input("Ask about the table...")
+
+    if user_msg:
+        st.session_state.chat.append(("user", user_msg))
+        response = st.session_state.agent.run(user_msg)
+        st.session_state.chat.append(("assistant", response))
+
+    for role, msg in st.session_state.chat:
+        st.chat_message(role).write(msg)
+
+    st.subheader("Download Raw Data")
+
+    buffer = BytesIO()
+    st.session_state.df.to_excel(buffer, index=False, engine="openpyxl")
+    buffer.seek(0)
+
+    st.download_button(
+        label="Download raw GBIF data (Excel)",
+        data=buffer,
+        file_name="nhm_gbif_raw_data.xlsx",
+        mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+    )