feat(api): add pagination to messages endpoint and improve chat API robustness

- Add pagination support to /api/conversations/[id]/messages with limit and before query params, returning hasMore and cursor for efficient message fetching
- Enhance /api/ollama/chat by adding non-blocking Ollama availability check and conditionally disabling debug logging in production环境下Featured

app/api/conversations/[id]/messages/route.ts

@@ -10,12 +10,21 @@ export async function GET(
 ) {
   try {
     const { id } = await params;
+    const url = new URL(request.url);
+    const limitParam = url.searchParams.get("limit");
+    const beforeParam = url.searchParams.get("before");
+
+    const limit = Math.min(Math.max(Number(limitParam) || 0, 1), 200) || 50;
+    const beforeTs = beforeParam ? Number(beforeParam) : undefined;
+
     const db = getDatabase();
     const messageRepo = new MessageRepository(db);
 
-    const messages = messageRepo.findByConversation(id);
+    const messages = messageRepo.findByConversationPaged(id, limit, beforeTs);
+    const hasMore = messages.length === limit;
+    const cursor = messages.length > 0 ? messages[0].timestamp : null;
 
-    return NextResponse.json(messages);
+    return NextResponse.json({ messages, hasMore, cursor });
   } catch (error) {
     console.error("Erro ao buscar mensagens:", error);
     return NextResponse.json(

app/api/ollama/chat/route.ts

@@ -1,5 +1,5 @@
 import { NextRequest } from "next/server";
-import { chatWithStream } from "@/lib/ollama";
+import { chatWithStream, ensureOllamaAvailable } from "@/lib/ollama";
 import { convertToOllamaMessages } from "@/lib/chat";
 import { detectModelCapabilities } from "@/lib/services/model-capabilities";
 import { MCPExecutor } from "@/lib/services/mcp-executor";
@@ -97,24 +97,30 @@ export async function POST(req: NextRequest) {
         };
 
         try {
+          // Garantir disponibilidade com timeout curto (não bloquear)
+          ensureOllamaAvailable({ timeoutMs: 2000 }).catch(() => {});
           const ollamaMessages = convertToOllamaMessages(messages);
-          console.log("🗣️  [CHAT] Messages ->", ollamaMessages);
+          if (process.env.NODE_ENV !== "production") {
+            console.log("🗣️  [CHAT] Messages ->", ollamaMessages);
+          }
 
           // Merge system prompt com tools prompt
           const finalSystemPrompt = toolsPrompt
             ? `${system || ""}\n\n${toolsPrompt}`
             : system;
-          if (toolsPrompt) console.log("🧩 [CHAT] Tools prompt injected");
+          if (toolsPrompt && process.env.NODE_ENV !== "production") console.log("🧩 [CHAT] Tools prompt injected");
 
           // Preparar parâmetros para chat
           const chatParams = capabilities.supportsNativeTools ? { tools } : {};
-          if (capabilities.supportsNativeTools) {
-            console.log(
-              "🧰 [CHAT] Native tools enabled:",
-              tools?.map((t: any) => t.function?.name)
-            );
-          } else {
-            console.log("🧰 [CHAT] Prompt-engineering tools mode");
+          if (process.env.NODE_ENV !== "production") {
+            if (capabilities.supportsNativeTools) {
+              console.log(
+                "🧰 [CHAT] Native tools enabled:",
+                tools?.map((t: any) => t.function?.name)
+              );
+            } else {
+              console.log("🧰 [CHAT] Prompt-engineering tools mode");
+            }
           }
 
           const response = await chatWithStream(
@@ -124,7 +130,7 @@ export async function POST(req: NextRequest) {
             finalSystemPrompt,
             capabilities.supportsNativeTools ? tools : undefined
           );
-          console.log("🌊 [CHAT] Streaming started for model:", model);
+          if (process.env.NODE_ENV !== "production") console.log("🌊 [CHAT] Streaming started for model:", model);
 
           const normalizeParameters = (params: any) => {
             try {
@@ -149,7 +155,7 @@ export async function POST(req: NextRequest) {
           };
 
           for await (const chunk of response) {
-            console.log("📦 [CHAT stream chunk]", JSON.stringify(chunk));
+            if (process.env.NODE_ENV !== "production") console.log("📦 [CHAT stream chunk]", JSON.stringify(chunk));
             // Verificar se há tool calls (modelos com suporte nativo)
             if (
               (chunk.message?.tool_calls &&
@@ -157,19 +163,16 @@ export async function POST(req: NextRequest) {
               (Array.isArray((chunk as any).tool_calls) &&
                 (chunk as any).tool_calls.length > 0)
             ) {
-              console.log("🔧 Model requested tool calls (native)");
+              if (process.env.NODE_ENV !== "production") console.log("🔧 Model requested tool calls (native)");
 
               const nativeCalls =
                 chunk.message?.tool_calls || (chunk as any).tool_calls || [];
               for (const toolCall of nativeCalls) {
                 const toolKey = toolCall.function.name;
                 const toolInfo = mcpToolsMap.get(toolKey);
-                console.log(
-                  "🧭 [CHAT] Native tool call:",
-                  toolKey,
-                  "->",
-                  toolInfo
-                );
+                if (process.env.NODE_ENV !== "production") {
+                  console.log("🧭 [CHAT] Native tool call:", toolKey, "->", toolInfo);
+                }
 
                 if (toolInfo) {
                   // Executar tool
@@ -185,11 +188,13 @@ export async function POST(req: NextRequest) {
 
                   if (result.success) {
                     toolExecuted = true;
-                    console.log("✅ [CHAT] Tool executed successfully", {
-                      mcpId: toolInfo.mcpId,
-                      toolName: toolInfo.toolName,
-                      executionTime: result.executionTime,
-                    });
+                    if (process.env.NODE_ENV !== "production") {
+                      console.log("✅ [CHAT] Tool executed successfully", {
+                        mcpId: toolInfo.mcpId,
+                        toolName: toolInfo.toolName,
+                        executionTime: result.executionTime,
+                      });
+                    }
                     // Enviar indicador de execução de tool
                     safeEnqueue(
                       JSON.stringify({
@@ -206,10 +211,12 @@ export async function POST(req: NextRequest) {
                       toolInfo.toolName,
                       result.result
                     );
-                    console.log(
-                      "🧩 [CHAT] Injecting tool result into context (length)",
-                      String(resultMessage).length
-                    );
+                    if (process.env.NODE_ENV !== "production") {
+                      console.log(
+                        "🧩 [CHAT] Injecting tool result into context (length)",
+                        String(resultMessage).length
+                      );
+                    }
 
                     // Fazer nova chamada ao modelo com o resultado
                     const updatedMessages = [
@@ -264,9 +271,9 @@ export async function POST(req: NextRequest) {
               extractToolCallFromResponse(accumulatedResponse);
 
             if (extractedToolCall) {
-              console.log("🔧 Model requested tool call (prompt engineering)");
+              if (process.env.NODE_ENV !== "production") console.log("🔧 Model requested tool call (prompt engineering)");
               lastExtractedToolCall = extractedToolCall;
-              console.log("🧭 [CHAT] Extracted tool call:", extractedToolCall);
+              if (process.env.NODE_ENV !== "production") console.log("🧭 [CHAT] Extracted tool call:", extractedToolCall);
 
               // Encontrar MCP e tool
               let foundToolInfo: { mcpId: string; toolName: string } | null =
@@ -339,9 +346,8 @@ export async function POST(req: NextRequest) {
                 }
               }
             } else {
-              console.log(
-                "🕵️  [CHAT] No tool call extracted from accumulated response"
-              );
+              if (process.env.NODE_ENV !== "production")
+                console.log("🕵️  [CHAT] No tool call extracted from accumulated response");
             }
           }
 

app/api/ollama/models/route.ts

@@ -10,6 +10,10 @@ import {
 
 export const dynamic = "force-dynamic";
 
+// Cache leve em memória para reduzir chamadas repetidas em curto intervalo
+let __modelsCache: { ts: number; payload: any } | null = null;
+const CACHE_TTL_MS = 8000; // 8s
+
 function normalizeModel(model: any): ModelInfo {
   const name: string = model?.model || model?.name || "unknown";
   const sizeBytes: number = model?.size || 0;
@@ -30,6 +34,11 @@ function normalizeModel(model: any): ModelInfo {
 
 export async function GET() {
   try {
+    // Tentar retorno via cache recente
+    if (__modelsCache && Date.now() - __modelsCache.ts < CACHE_TTL_MS) {
+      return NextResponse.json(__modelsCache.payload);
+    }
+
     let models: any[] = [];
     // Tentar garantir disponibilidade rapidamente (não bloquear longamente a UI)
     await ensureOllamaAvailable({ timeoutMs: 3000 }).catch(() => {});
@@ -39,8 +48,12 @@ export async function GET() {
       models = await listModelsViaHttp();
     }
     const normalized = models.map((m) => normalizeModel(m));
-    return NextResponse.json({ offline: false, models: normalized });
+    const payload = { offline: false, models: normalized };
+    __modelsCache = { ts: Date.now(), payload };
+    return NextResponse.json(payload);
   } catch (e) {
-    return NextResponse.json({ offline: true, models: mockModels });
+    const payload = { offline: true, models: mockModels };
+    __modelsCache = { ts: Date.now(), payload };
+    return NextResponse.json(payload);
   }
 }

app/api/ollama/warmup/route.ts

@@ -0,0 +1,29 @@
+import { NextRequest, NextResponse } from "next/server";
+import { Ollama } from "ollama";
+import { OLLAMA_HOST } from "@/lib/ollama";
+
+export const dynamic = "force-dynamic";
+
+export async function GET(req: NextRequest) {
+  try {
+    const url = new URL(req.url);
+    const model = url.searchParams.get("model");
+    if (!model) {
+      return NextResponse.json({ error: "model required" }, { status: 400 });
+    }
+
+    const client = new Ollama({ host: OLLAMA_HOST });
+    await client.chat({
+      model,
+      messages: [{ role: "system", content: "warm" }],
+      stream: false,
+      options: { keep_alive: "5m" },
+    });
+
+    return NextResponse.json({ warmed: true });
+  } catch (e) {
+    return NextResponse.json({ warmed: false }, { status: 200 });
+  }
+}
+
+

components/chat/ChatContainer.tsx

@@ -46,6 +46,8 @@ export function ChatContainer({
   useEffect(() => {
     if (ready && prefs.selectedModel && !selectedModel) {
       setSelectedModel(prefs.selectedModel);
+      // Warmup do modelo em background
+      fetch(`/api/ollama/warmup?model=${encodeURIComponent(prefs.selectedModel)}`).catch(() => {});
     }
   }, [ready, prefs.selectedModel]);
 
@@ -64,6 +66,8 @@ export function ChatContainer({
   const handleModelChange = (modelName: string) => {
     setSelectedModel(modelName);
     update({ selectedModel: modelName }); // Salvar no Redis
+    // Disparar warmup em background
+    fetch(`/api/ollama/warmup?model=${encodeURIComponent(modelName)}`).catch(() => {});
   };
 
   // Carregar MCPs ativos do localStorage

database/repositories/message.ts

@@ -39,6 +39,21 @@ export class MessageRepository {
       .all(conversationId) as Message[];
   }
 
+  findByConversationPaged(
+    conversationId: string,
+    limit: number,
+    beforeTs?: number
+  ): Message[] {
+    const sql = beforeTs
+      ? `SELECT * FROM messages WHERE conversation_id = ? AND timestamp < ? ORDER BY timestamp DESC LIMIT ?`
+      : `SELECT * FROM messages WHERE conversation_id = ? ORDER BY timestamp DESC LIMIT ?`;
+    const rows = beforeTs
+      ? (this.db.prepare(sql).all(conversationId, beforeTs, limit) as Message[])
+      : (this.db.prepare(sql).all(conversationId, limit) as Message[]);
+    // Reverter para ascendente no retorno
+    return rows.reverse();
+  }
+
   findById(id: string): Message | null {
     return this.db
       .prepare(

lib/ollama.ts

@@ -83,7 +83,7 @@ export async function chatWithStream(
       ? [{ role: "system", content: system }, ...messages]
       : messages,
     stream: true,
-    options,
+    options: { ...(options || {}), keep_alive: "5m" },
   };
 
   // Adicionar tools se fornecidos