amaraditya/text2sql1

1import streamlit as st2import requests3import pandas as pd4from datetime import datetime5 6# =====================================================7# CONFIG8# =====================================================9 10API_URL = "https://boundless-underline-product.ngrok-free.dev/query"11 12st.set_page_config(13    page_title="Text2SQL Agent",14    page_icon="🧠",15    layout="wide",16    initial_sidebar_state="expanded"17)18 19# =====================================================20# CUSTOM CSS21# =====================================================22 23st.markdown("""24<style>25 26.main {27    background-color: #0E1117;28}29 30.block-container {31    padding-top: 2rem;32    padding-bottom: 2rem;33}34 35h1, h2, h3 {36    color: white;37}38 39.stTextInput > div > div > input {40    background-color: #1E1E1E;41    color: white;42    border-radius: 10px;43    border: 1px solid #444;44    padding: 12px;45}46 47.stButton>button {48    width: 100%;49    border-radius: 10px;50    height: 3em;51    background-color: #6C63FF;52    color: white;53    border: none;54    font-weight: 600;55}56 57.stButton>button:hover {58    background-color: #5A52E0;59    color: white;60}61 62.sql-box {63    background-color: #1E1E1E;64    padding: 1rem;65    border-radius: 10px;66    border: 1px solid #333;67}68 69.metric-card {70    background-color: #1A1D24;71    padding: 1rem;72    border-radius: 12px;73    border: 1px solid #2D2F36;74}75 76.success-box {77    background-color: #132A13;78    padding: 1rem;79    border-radius: 10px;80}81 82.error-box {83    background-color: #3A1111;84    padding: 1rem;85    border-radius: 10px;86}87 88</style>89""", unsafe_allow_html=True)90 91# =====================================================92# HEADER93# =====================================================94 95col1, col2 = st.columns([6,1])96 97with col1:98    st.title(" Text2SQL Agent")99 100 101 102st.markdown("""103Convert natural language questions into executable SQLite queries using a multi-agent AI pipeline.104""")105 106st.divider()107 108# =====================================================109# SIDEBAR110# =====================================================111 112with st.sidebar:113 114    st.header("⚡ Example Queries")115 116    examples = [117        "Top 5 customers by revenue",118        "Monthly sales trend",119        "Revenue by country",120        "Which artist has most tracks?",121        "Find average invoice amount by country",122        "Which year generated highest revenue?",123        "Find customers with purchases in multiple years",124        "Top genres by revenue"125    ]126 127    for ex in examples:128        if st.button(ex):129            st.session_state["example_question"] = ex130 131    st.divider()132 133    st.header("📊 System Architecture")134 135    st.markdown("""136    - Schema Retrieval137    - Planner Agent138    - SQL Generator139    - Validator Agent140    - SQLite Execution141    """)142 143    st.divider()144 145    st.header("🛠 Backend")146 147    st.success("Connected to Colab GPU")148 149# =====================================================150# INPUT SECTION151# =====================================================152 153default_question = st.session_state.get("example_question", "")154 155question = st.text_input(156    "Ask your business question",157    value=default_question,158    placeholder="Example: Show monthly revenue trend"159)160 161# =====================================================162# EXECUTE BUTTON163# =====================================================164 165run = st.button(" Generate SQL & Execute")166 167# =====================================================168# MAIN EXECUTION169# =====================================================170 171if run:172 173    if not question.strip():174 175        st.warning("Please enter a question.")176 177    else:178 179        with st.spinner("Agents are reasoning over your query..."):180 181            start_time = datetime.now()182 183            try:184 185                response = requests.post(186                    API_URL,187                    json={"question": question},188                    timeout=180189                )190 191                output = response.json()192 193            except Exception as e:194 195                st.error(f"Backend connection failed:\n{e}")196                st.stop()197 198            end_time = datetime.now()199 200            latency = round(201                (end_time - start_time).total_seconds(),202                2203            )204 205        # =================================================206        # SUCCESS207        # =================================================208 209        if output.get("status") == "PASS":210 211            st.success(" Query executed successfully")212 213            # =============================================214            # METRICS215            # =============================================216 217            c1, c2, c3 = st.columns(3)218 219            with c1:220                st.metric(221                    "Execution Time",222                    f"{latency}s"223                )224 225            with c2:226                st.metric(227                    "Rows Returned",228                    len(output["result"])229                )230 231            with c3:232                st.metric(233                    "Status",234                    "PASS"235                )236 237            st.divider()238 239            # =============================================240            # SQL241            # =============================================242 243            st.subheader(" Generated SQL")244 245            st.code(246                output["sql"],247                language="sql"248            )249 250            # =============================================251            # RESULT252            # =============================================253 254            st.subheader(" Query Result")255 256            df = pd.DataFrame(output["result"])257 258            st.dataframe(259                df,260                use_container_width=True,261                height=450262            )263 264            # =============================================265            # DOWNLOAD266            # =============================================267 268            csv = df.to_csv(index=False)269 270            st.download_button(271                label="⬇ Download Result CSV",272                data=csv,273                file_name="query_result.csv",274                mime="text/csv"275            )276 277            # =============================================278            # DEBUG SECTIONS279            # =============================================280 281            with st.expander("Planner Output"):282 283                if "plan" in output:284                    st.write(output["plan"])285 286            with st.expander("Retrieved Schema"):287 288                if "schema" in output:289                    st.write(output["schema"])290 291            with st.expander("🔍 Full Backend Output"):292 293                st.json(output)294 295        # =================================================296        # FAILURE297        # =================================================298 299        else:300 301            # st.error("Failed to generate valid SQL")302            st.error("Result not found")303 304            # if "sql" in output:305 306            #     st.subheader("Generated SQL")307 308            #     st.code(309            #         output["sql"],310            #         language="sql"311            #     )312 313            # if "error" in output:314 315            #     st.subheader("Error Details")316 317            #     st.error(output["error"])318 319            # with st.expander("🔍 Full Backend Output"):320 321            #     st.json(output)