Add dynamic AI suggestions, fix insight router bug, and clean up repository for production

agent/graph.py

@@ -171,7 +171,7 @@ def _output_pipeline(state: AgentState) -> AgentState:
     """
     result = state.get("execution_result")
 
-    if not result:
+    if not result and state.get("intent") != "insight_only":
         return {
             **state,
             "insight_text": "No results were returned for this query.",

agent/nodes/insight_synthesizer.py

@@ -13,15 +13,37 @@ Focus on the most important numbers, trends, and business implications.
 Do not describe how the query works — just state what the data shows."""
 
 
+def _build_conversation_context(history: list) -> str:
+    if not history:
+        return "No prior conversation."
+    lines = []
+    for i, turn in enumerate(history[-3:], 1):
+        lines.append(f"Q: {turn.get('query', '')}")
+        if turn.get('insight'):
+            lines.append(f"A: {turn['insight']}")
+    return "\n".join(lines)
+
+
 def insight_synthesizer(state: AgentState) -> AgentState:
     result = state.get("execution_result")
+    client = get_groq_client()
+
     if not result:
+        if state.get("intent") == "insight_only":
+            history_text = _build_conversation_context(state.get("conversation_history", []))
+            insight = client.complete_system(
+                system="You are a helpful data analyst. Answer the user's conversational question based on the previous context. Do not describe your thought process.",
+                user=f"Context:\n{history_text}\n\nQuestion: {state['user_query']}",
+                model=client.reason_model,
+                max_tokens=256,
+            )
+            return {**state, "insight_text": insight}
         return {**state, "insight_text": "No results were returned for this query."}
 
     # Truncate result preview for prompt (first 20 rows)
     preview = json.dumps(result[:20], default=str)
 
-    client = get_groq_client()
+
     insight = client.complete_system(
         system=SYSTEM,
         user=f"Question: {state['user_query']}\n\nResults (first 20 rows):\n{preview}",

agent/nodes/intent_router.py

@@ -44,5 +44,10 @@ def intent_router(state: AgentState) -> AgentState:
     # Post-processing safeguard: cannot do insight without prior context
     if intent == "insight" and not has_history:
         intent = "sql"
+        
+    # Post-processing safeguard: charting requests must not be insight
+    query_lower = state["user_query"].lower()
+    if intent == "insight" and any(w in query_lower for w in ["chart", "plot", "graph", "visualize", "visualization"]):
+        intent = "sql"
 
     return {**state, "intent": intent}

api/routers/query.py

@@ -225,3 +225,51 @@ async def stream_query(req: QueryRequest):
             "X-Accel-Buffering": "no",
         },
     )
+
+
+class SuggestRequest(BaseModel):
+    connector_id: str
+
+
+class SuggestResponse(BaseModel):
+    suggestions: List[str]
+
+
+@router.post("/suggest", response_model=SuggestResponse)
+async def get_suggestions(req: SuggestRequest):
+    try:
+        from connectors.base import get_connector
+        connector = get_connector(req.connector_id)
+        schema = connector.get_schema()
+    except Exception as exc:
+        return SuggestResponse(suggestions=["What is the total number of rows in this dataset?"])
+
+    # Format schema for prompt
+    schema_lines = []
+    for t in schema[:3]:  # Limit to 3 tables
+        cols = ", ".join(f"{c['name']} ({c['type']})" for c in t.get("columns", [])[:15])
+        schema_lines.append(f"Table: {t['table']}\nColumns: {cols}")
+    schema_context = "\n\n".join(schema_lines)
+
+    SYSTEM = """You are a senior data analyst.
+Based on the provided database schema, generate 3 highly relevant, interesting analytical questions that a user might want to ask.
+Return ONLY a JSON list of 3 strings. Example: ["question 1?", "question 2?", "question 3?"]
+Focus on business metrics, trends, and aggregations."""
+
+    from llm import get_groq_client
+    client = get_groq_client()
+    try:
+        raw = client.complete_system(
+            system=SYSTEM,
+            user=f"Schema:\n{schema_context}",
+            model=client.reason_model,
+            max_tokens=200,
+        )
+        import json
+        suggestions = json.loads(raw)
+        if isinstance(suggestions, list) and len(suggestions) > 0:
+            return SuggestResponse(suggestions=suggestions[:4])
+    except Exception:
+        pass
+
+    return SuggestResponse(suggestions=["What are the top trends in this dataset?"])

frontend/src/api.ts

@@ -141,6 +141,17 @@ export async function* streamQuery(req: QueryRequest): AsyncGenerator<StreamEven
   }
 }
 
+export async function fetchSuggestions(connectorId: string): Promise<string[]> {
+  const res = await fetch(`${BASE}/api/query/suggest`, {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ connector_id: connectorId })
+  })
+  if (!res.ok) throw new Error('Failed to fetch suggestions')
+  const data = await res.json()
+  return data.suggestions || []
+}
+
 // ── History ────────────────────────────────────────────────────────────────────
 
 export async function getHistory(sessionId: string): Promise<HistoryRecord[]> {

frontend/src/pages/ChatPage.tsx

@@ -1,7 +1,7 @@
 import { useState, useRef, useEffect, useCallback } from 'react'
 import { Send, RefreshCw, FileDown } from 'lucide-react'
 import { v4 as uuidv4 } from 'uuid'
-import { streamQuery, savePanel, downloadReport } from '@/api'
+import { streamQuery, savePanel, downloadReport, fetchSuggestions } from '@/api'
 import type { QueryResponse, TraceEvent } from '@/api'
 import { getSessionId, newSession, getUserId, getConnectorId } from '@/session'
 import ChatMessage from '@/components/dashboard/ChatMessage'
@@ -15,21 +15,28 @@ interface Message {
   traceEvents: TraceEvent[]
 }
 
-const SUGGESTIONS = [
-  'What are the top 5 products by total revenue?',
-  'Show monthly order volume for the past year',
-  'Which region has the highest average order value?',
-  'List customers with more than 5 orders',
-]
+// Dynamic suggestions fetched from API
 
 export default function ChatPage() {
   const [messages, setMessages] = useState<Message[]>([])
+  const [suggestions, setSuggestions] = useState<string[]>([])
+  const [loadingSuggestions, setLoadingSuggestions] = useState(false)
+
   const [input, setInput] = useState('')
   const [loading, setLoading] = useState(false)
   const [streamText, setStreamText] = useState('')
   const [liveTrace, setLiveTrace] = useState<TraceEvent[]>([])
   const [sessionId, setSessionId] = useState(getSessionId)
   const [connector, setConnector] = useState(getConnectorId)
+
+  useEffect(() => {
+    if (!connector) return
+    setLoadingSuggestions(true)
+    fetchSuggestions(connector)
+      .then(setSuggestions)
+      .catch(() => setSuggestions(['What insights can you find in this dataset?']))
+      .finally(() => setLoadingSuggestions(false))
+  }, [connector])
   const bottomRef = useRef<HTMLDivElement>(null)
   const textareaRef = useRef<HTMLTextAreaElement>(null)
 
@@ -140,15 +147,19 @@ export default function ChatPage() {
             <h2 className="text-xl font-semibold text-neutral-200 text-center mb-2">Ask anything about your data</h2>
             <p className="text-xs text-neutral-500 text-center mb-8">Connected to: <span className="text-neutral-300 font-mono">{connector}</span></p>
             <div className="grid grid-cols-1 gap-2">
-              {SUGGESTIONS.map((s) => (
-                <button
-                  key={s}
-                  onClick={() => submit(s)}
-                  className="text-left px-4 py-3 card hover:border-neutral-700 hover:bg-neutral-900/50 text-sm text-neutral-400 hover:text-neutral-200 transition-all"
-                >
-                  {s}
-                </button>
-              ))}
+              {loadingSuggestions ? (
+                <div className="text-center text-xs text-neutral-500 py-4 animate-pulse">Generating tailored suggestions...</div>
+              ) : (
+                suggestions.map((s) => (
+                  <button
+                    key={s}
+                    onClick={() => submit(s)}
+                    className="text-left px-4 py-3 card hover:border-neutral-700 hover:bg-neutral-900/50 text-sm text-neutral-400 hover:text-neutral-200 transition-all"
+                  >
+                    {s}
+                  </button>
+                ))
+              )}
             </div>
           </div>
         )}