Update app.py

app.py

@@ -94,7 +94,6 @@ def fmt_currency(x: float) -> str:
 # =============================
 @dataclass
 class LLMConfig:
-    provider: str = os.getenv("LLM_PROVIDER", "openai").lower()
     base_url: Optional[str] = os.getenv("OPENAI_BASE_URL")
     api_key: Optional[str] = (
         os.getenv("OPENAI_API_KEY")
@@ -126,7 +125,7 @@ class UniversalLLMClient:
     def _base_url(self) -> str:
         return (self.cfg.base_url or "https://api.openai.com/v1").rstrip("/")
 
-    def _smoke_test(self):
+    def _smoke_test(self) -> None:
         try:
             _ = self.chat([{"role": "user", "content": "ping"}], max_tokens=4)
         except Exception as e:
@@ -279,7 +278,6 @@ class ProcurementAnalytics:
         g['total_spend'] = g['total_spend'].round(2)
         return g.sort_values('total_spend', ascending=False)
 
-    # helper: top N with shares
     def top_n_categories(self, n: int = 3) -> List[Tuple[str, float]]:
         cat = self.category_spend()
         total = float(cat['order_value'].sum()) or 1.0
@@ -316,33 +314,34 @@ class UniversalProcurementAgent:
             "top_categories": top_cats,
             "top_vendors": top_vens,
         }
-messages = [
-    {
-        "role": "system",
-        "content": (
-            "You are a senior procurement analyst. Use bullet points, be concise, "
-            "and always use the ₹ symbol. "
-            "When summarizing, include top categories and vendors with percentages, "
-            "then 2-3 quantified actions."
-        )
-    },
-    {
-        "role": "user",
-        "content": (
-            f"Executive summary. Format amounts with commas (e.g., ₹12,34,567).\n\n"
-            f"Data: {json.dumps(data_summary)}"
-        )
-    },
-]
+        messages = [
+            {
+                "role": "system",
+                "content": (
+                    "You are a senior procurement analyst. Use bullet points, be concise, "
+                    "and always use the ₹ symbol. When summarizing, include top categories "
+                    "and vendors with percentages, then 2-3 quantified actions."
+                ),
+            },
+            {
+                "role": "user",
+                "content": (
+                    "Executive summary. Format amounts with commas (e.g., ₹12,34,567).
 
-try:
-    return (
-        "🧠 **[AI-Powered Analysis]**\n\n"
-        + self.llm.chat(messages, max_tokens=550)
-    )
-except Exception as e:
-    return self._rule_summary() + f"\n\n*AI fallback due to: {e}*"
+"
+                    + f"Data: {json.dumps(data_summary)}"
+                ),
+            },
+        ]
+        try:
+            return (
+                "🧠 **[AI-Powered Analysis]**
 
+"
+                + self.llm.chat(messages, max_tokens=550)
+            )
+        except Exception as e:
+            return self._rule_summary() + f"
 
 *AI fallback due to: {e}*"
 
@@ -355,15 +354,15 @@ except Exception as e:
         return (
             "🤖 **[Rule-Based Summary]**
 "
-            f"• Total spend: {fmt_currency(k['total_spend'])} across {len(self.po_data):,} POs
+            + f"• Total spend: {fmt_currency(k['total_spend'])} across {len(self.po_data):,} POs
 "
-            f"• On-time delivery: {k['on_time_rate']*100:.1f}% | Avg quality: {k['quality_avg']:.1f}/10
+            + f"• On-time delivery: {k['on_time_rate']*100:.1f}% | Avg quality: {k['quality_avg']:.1f}/10
 "
-            f"• Top categories: {topc_str}
+            + f"• Top categories: {topc_str}
 "
-            f"• Top vendors: {topv_str}
+            + f"• Top vendors: {topv_str}
 "
-            "Actions: Consolidate long tail; multi-year terms with top vendors; auto-approve low-value POs."
+            + "Actions: Consolidate long tail; multi-year terms with top vendors; auto-approve low-value POs."
         )
 
     def chat_with_data(self, question: str) -> str:
@@ -395,9 +394,12 @@ Context: {json.dumps(context)}
 {style_rules}"},
         ]
         try:
-            return "🧠 **[AI Response]**
+            return (
+                "🧠 **[AI Response]**
 
-" + self.llm.chat(messages, max_tokens=450)
+"
+                + self.llm.chat(messages, max_tokens=450)
+            )
         except Exception as e:
             return self._rule_answer(question) + f"
 
@@ -408,7 +410,7 @@ Context: {json.dumps(context)}
         k = self.analytics.kpis()
         top_c = self.analytics.top_n_categories(3)
         top_v = self.analytics.top_n_vendors(3)
-        if "spend" in q or "spending" in q or "cost" in q:
+        if ("spend" in q) or ("spending" in q) or ("cost" in q):
             lines = [
                 f"• Total spend: {fmt_currency(k['total_spend'])}",
                 "• Top categories: " + ", ".join([f"{n} – {s:.0f}%" for n, s in top_c]),
@@ -418,7 +420,7 @@ Context: {json.dumps(context)}
             return "🤖 **[Rule-Based Spend]**
 " + "
 ".join(lines)
-        if "vendor" in q or "supplier" in q or "partner" in q:
+        if ("vendor" in q) or ("supplier" in q) or ("partner" in q):
             vp = self.po_data.groupby('vendor').agg(
                 spend=('order_value','sum'),
                 late_rate=('late_delivery','mean'),
@@ -437,7 +439,7 @@ Context: {json.dumps(context)}
             return "🤖 **[Rule-Based Vendor]**
 " + "
 ".join(lines)
-        if "risk" in q or "late" in q or "delay" in q:
+        if ("risk" in q) or ("late" in q) or ("delay" in q):
             late = float(self.po_data['late_delivery'].mean())*100
             lines = [
                 f"• Late delivery rate: {late:.1f}%",
@@ -446,13 +448,12 @@ Context: {json.dumps(context)}
             return "🤖 **[Rule-Based Risk]**
 " + "
 ".join(lines)
-        # default
         return (
             "🤖 **[Rule-Based]**
 "
-            "• I can analyze spend (top categories/vendors), vendor performance (best/worst), risk (late %), and trends.
+            + "• I can analyze spend (top categories/vendors), vendor performance (best/worst), risk (late %), and trends.
 "
-            f"• Snapshot: {fmt_currency(k['total_spend'])}, {len(self.po_data):,} POs, {self.po_data['vendor'].nunique()} vendors, on-time {k['on_time_rate']*100:.1f}%"
+            + f"• Snapshot: {fmt_currency(k['total_spend'])}, {len(self.po_data):,} POs, {self.po_data['vendor'].nunique()} vendors, on-time {k['on_time_rate']*100:.1f}%"
         )
 
 # =============================
@@ -482,13 +483,13 @@ api_status = "🟢 Connected" if status['available'] else "🔴 Not Connected"
 # Header
 # =============================
 st.markdown(
-    f"""
-<div class="main-header">
-  <h1>🤖 SAP S/4HANA Agentic AI Procurement Analytics</h1>
-  <p>Autonomous Intelligence for Procurement Excellence</p>
-  <small>LLM: {api_status} · Data: {len(st.session_state.po_df):,} POs</small>
-</div>
-""",
+    (
+        "<div class=\"main-header\">"
+        "<h1>🤖 SAP S/4HANA Agentic AI Procurement Analytics</h1>"
+        "<p>Autonomous Intelligence for Procurement Excellence</p>"
+        + f"<small>LLM: {api_status} · Data: {len(st.session_state.po_df):,} POs</small>"
+        "</div>"
+    ),
     unsafe_allow_html=True,
 )
 
@@ -524,24 +525,63 @@ if selected == "🏠 Dashboard":
     st.markdown("### 🧠 AI Executive Summary")
     with st.spinner('🤖 Analyzing procurement data...'):
         summary = agent.executive_summary()
-    st.markdown(f"""
-    <div class="ai-insight">
-        <h4>📊 Intelligent Analysis</h4>
-        <div style="white-space: pre-line; line-height: 1.55;">{summary}</div>
-    </div>
-    """, unsafe_allow_html=True)
+    st.markdown(
+        (
+            "<div class=\"ai-insight\">"
+            "<h4>📊 Intelligent Analysis</h4>"
+            + f"<div style=\"white-space: pre-line; line-height: 1.55;\">{summary}</div>"
+            "</div>"
+        ),
+        unsafe_allow_html=True,
+    )
 
     k = analytics.kpis()
 
     c1, c2, c3, c4 = st.columns(4)
     with c1:
-        st.markdown(f"<div class='metric-card'><h3 style='color: var(--primary-color); margin:0;'>Total Spend</h3><h2 style='margin: .5rem 0;'>{fmt_currency(k['total_spend'])}</h2><p style='color:#28a745;margin:0;'>📈 Active Portfolio</p></div>", unsafe_allow_html=True)
+        st.markdown(
+            (
+                "<div class='metric-card'>"
+                "<h3 style='color: var(--primary-color); margin:0;'>Total Spend</h3>"
+                + f"<h2 style='margin: .5rem 0;'>{fmt_currency(k['total_spend'])}</h2>"
+                "<p style='color:#28a745;margin:0;'>📈 Active Portfolio</p>"
+                "</div>"
+            ),
+            unsafe_allow_html=True,
+        )
     with c2:
-        st.markdown(f"<div class='metric-card'><h3 style='color: var(--primary-color); margin:0;'>Avg Order Value</h3><h2 style='margin: .5rem 0;'>{fmt_currency(k['avg_order_value'])}</h2><p style='color:#17a2b8;margin:0;'>📊 Order Efficiency</p></div>", unsafe_allow_html=True)
+        st.markdown(
+            (
+                "<div class='metric-card'>"
+                "<h3 style='color: var(--primary-color); margin:0;'>Avg Order Value</h3>"
+                + f"<h2 style='margin: .5rem 0;'>{fmt_currency(k['avg_order_value'])}</h2>"
+                "<p style='color:#17a2b8;margin:0;'>📊 Order Efficiency</p>"
+                "</div>"
+            ),
+            unsafe_allow_html=True,
+        )
     with c3:
-        st.markdown(f"<div class='metric-card'><h3 style='color: var(--primary-color); margin:0;'>Active Vendors</h3><h2 style='margin: .5rem 0;'>{k['active_vendors']}</h2><p style='color:#6f42c1;margin:0;'>🤝 Strategic Partners</p></div>", unsafe_allow_html=True)
+        st.markdown(
+            (
+                "<div class='metric-card'>"
+                "<h3 style='color: var(--primary-color); margin:0;'>Active Vendors</h3>"
+                + f"<h2 style='margin: .5rem 0;'>{k['active_vendors']}</h2>"
+                "<p style='color:#6f42c1;margin:0;'>🤝 Strategic Partners</p>"
+                "</div>"
+            ),
+            unsafe_allow_html=True,
+        )
     with c4:
-        st.markdown(f"<div class='metric-card'><h3 style='color: var(--primary-color); margin:0;'>On‑Time Delivery</h3><h2 style='margin: .5rem 0;'>{k['on_time_rate']*100:.1f}%</h2><p style='color:#28a745;margin:0;'>⏱ Performance</p></div>", unsafe_allow_html=True)
+        st.markdown(
+            (
+                "<div class='metric-card'>"
+                "<h3 style='color: var(--primary-color); margin:0;'>On‑Time Delivery</h3>"
+                + f"<h2 style='margin: .5rem 0;'>{k['on_time_rate']*100:.1f}%</h2>"
+                "<p style='color:#28a745;margin:0;'>⏱ Performance</p>"
+                "</div>"
+            ),
+            unsafe_allow_html=True,
+        )
 
     st.markdown("### 📊 Executive Dashboard")
     colA, colB = st.columns(2)
@@ -574,13 +614,16 @@ if selected == "🏠 Dashboard":
 
 elif selected == "💬 AI Chat":
     st.markdown("### 💬 Chat with Your Procurement Data")
-    st.markdown(f"""
-    <div class=\"ai-insight\">
-        <h4>🤖 Universal AI Assistant</h4>
-        <p>Ask me anything about your procurement data. I will answer with crisp bullets and actual metrics.</p>
-        <p><small>Status: {api_status} | Model: {status['model']}</small></p>
-    </div>
-    """, unsafe_allow_html=True)
+    st.markdown(
+        (
+            "<div class=\"ai-insight\">"
+            "<h4>🤖 Universal AI Assistant</h4>"
+            "<p>Ask me anything about your procurement data. I will answer with crisp bullets and actual metrics.</p>"
+            + f"<p><small>Status: {api_status} | Model: {status['model']}</small></p>"
+            "</div>"
+        ),
+        unsafe_allow_html=True,
+    )
 
     if "messages" not in st.session_state:
         st.session_state.messages = [
@@ -645,13 +688,13 @@ elif selected == "🧪 What‑If":
 
     kept_names = ", ".join(kept_vendors)
     st.markdown(
-        f"""
-        <div class='alert alert-info'>
-            <strong>Scenario:</strong> Keep top <b>{top_n}</b> vendors. Addressable share: <b>{share*100:.1f}%</b>.<br/>
-            <strong>Potential savings:</strong> <b>{est_savings*100:.1f}%</b> (heuristic).<br/>
-            <small>Kept Vendors:</small> {kept_names}
-        </div>
-        """,
+        (
+            "<div class='alert alert-info'>"
+            + f"<strong>Scenario:</strong> Keep top <b>{top_n}</b> vendors. Addressable share: <b>{share*100:.1f}%</b>.<br/>"
+            + f"<strong>Potential savings:</strong> <b>{est_savings*100:.1f}%</b> (heuristic).<br/>"
+            + f"<small>Kept Vendors:</small> {kept_names}"
+            + "</div>"
+        ),
         unsafe_allow_html=True,
     )
 
@@ -669,12 +712,12 @@ elif selected == "🎯 Recommendations":
     ]
     for i, rec in enumerate(recs, start=1):
         st.markdown(
-            f"""
-            <div class="alert alert-success">
-                <h4>Recommendation #{i}</h4>
-                <p>{rec}</p>
-            </div>
-            """,
+            (
+                "<div class=\"alert alert-success\">"
+                + f"<h4>Recommendation #{i}</h4>"
+                + f"<p>{rec}</p>"
+                + "</div>"
+            ),
             unsafe_allow_html=True,
         )
 
@@ -683,11 +726,11 @@ elif selected == "🎯 Recommendations":
 # =============================
 st.markdown("---")
 st.markdown(
-    f"""
-<div style="text-align:center; padding: 1rem; color:#666;">
-  <p>🤖 <strong>Universal AI Procurement Analytics</strong> | Crisp, metric-first answers in ₹</p>
-  <p><em>Demo with synthetic data • {len(st.session_state.po_df):,} orders • LLM {api_status}</em></p>
-</div>
-""",
+    (
+        "<div style=\"text-align:center; padding: 1rem; color:#666;\">"
+        "<p>🤖 <strong>Universal AI Procurement Analytics</strong> | Crisp, metric-first answers in ₹</p>"
+        + f"<p><em>Demo with synthetic data • {len(st.session_state.po_df):,} orders • LLM {api_status}</em></p>"
+        "</div>"
+    ),
     unsafe_allow_html=True,
 )