wip: snapshot das alterações não commitadas (2026-10-20)

Origem: D:/Documents/Github/LocalAiApp
Arquivos omitidos (segredos, bancos de dados, logs, >50 MB): 0

services/webSearchLogger.ts

@@ -0,0 +1,190 @@
+/**
+ * webSearchLogger.ts
+ * Centralized structured logger for the web search pipeline on the client side.
+ * Outputs consistently formatted, emoji-tagged logs to the React Native / Metro console.
+ */
+
+type LogLevel = 'INFO' | 'WARN' | 'ERROR' | 'DEBUG';
+
+const ICONS: Record<LogLevel, string> = {
+    INFO: 'ℹ️ ',
+    WARN: '⚠️ ',
+    ERROR: '❌',
+    DEBUG: '🔍',
+};
+
+function formatMeta(meta?: Record<string, any>): string {
+    if (!meta) return '';
+    try {
+        return '\n  ' + JSON.stringify(meta, null, 2).replace(/\n/g, '\n  ');
+    } catch {
+        return '';
+    }
+}
+
+function log(level: LogLevel, phase: string, message: string, meta?: Record<string, any>) {
+    const ts = new Date().toISOString();
+    const metaStr = formatMeta(meta);
+    const prefix = `[${ts}] ${ICONS[level]} [WebSearch/${phase}]`;
+    const fullMsg = `${prefix} ${message}${metaStr}`;
+
+    switch (level) {
+        case 'ERROR':
+            console.error(fullMsg);
+            break;
+        case 'WARN':
+            console.warn(fullMsg);
+            break;
+        default:
+            console.log(fullMsg);
+    }
+}
+
+function logSection(title: string) {
+    const border = '─'.repeat(55);
+    console.log(`\n${border}`);
+    console.log(`  ${title}`);
+    console.log(`${border}`);
+}
+
+/** Rough tokens estimate (~4 chars per token) */
+function estimateTokens(text: string): number {
+    return Math.ceil(text.length / 4);
+}
+
+// ─── Public API ────────────────────────────────────────────────────────────────
+
+export const WebSearchLogger = {
+    pipelineStart(query: string, searchEndpoint: string) {
+        logSection(`🚀 Web Search Pipeline Started`);
+        log('INFO', 'Init', `New search initiated`, {
+            query,
+            searchEndpoint,
+            timestamp: new Date().toISOString(),
+        });
+    },
+
+    endpointResolved(host: string, port: number, searchEndpoint: string) {
+        log('INFO', 'Endpoint', `Search service URL resolved`, {
+            lmStudioHost: host,
+            lmStudioPort: port,
+            searchServiceEndpoint: searchEndpoint,
+        });
+    },
+
+    requestSent(query: string, maxContextLength: number, timeoutMs = 30000) {
+        log('INFO', 'Request', `Sending search request to local service`, {
+            query,
+            maxContextLength,
+            estimatedTokenBudget: estimateTokens('x'.repeat(maxContextLength)),
+            timeoutMs,
+        });
+    },
+
+    requestFailed(status: number, statusText: string) {
+        log('ERROR', 'Request', `Search service returned error`, {
+            httpStatus: status,
+            statusText,
+        });
+    },
+
+    serviceUnreachable(error: unknown, isTimeout = false) {
+        const err = error instanceof Error ? error : new Error(String(error));
+        const isConnectionRefused =
+            err.message.includes('Network request failed') ||
+            err.message.includes('ECONNREFUSED') ||
+            err.message.includes('Connection refused');
+
+        const message = isTimeout
+            ? `Search service timeout (30s) — service may be overloaded or unreachable`
+            : isConnectionRefused
+            ? `Search service is NOT running — connection refused`
+            : `Cannot reach local search service`;
+
+        log('ERROR', 'Request', message, {
+            error: err.message,
+            isTimeout,
+            isConnectionRefused,
+            diagnosis: isConnectionRefused
+                ? 'The local-search-service Node.js process is not running on this machine'
+                : isTimeout
+                ? 'Service is running but not responding within 30s (SearXNG may be slow)'
+                : 'Unknown network error',
+            hint: 'Run: cd local-search-service && npx ts-node server.ts',
+        });
+    },
+
+    contextReceived(
+        context: string,
+        sources: Array<{ title: string; url: string }>,
+        meta?: {
+            requestId?: string;
+            totalLatencyMs?: number;
+            finalContextChars?: number;
+            finalContextEstimatedTokens?: number;
+            sourcesKept?: number;
+            sourcesDropped?: number;
+            pruned?: boolean;
+        },
+    ) {
+        logSection(`✅ Context Received from Search Service`);
+        log('INFO', 'Context', `Web search context ready`, {
+            contextChars: context.length,
+            estimatedTokens: estimateTokens(context),
+            sourcesReceived: sources.length,
+            sourceTitles: sources.map((s) => s.title.substring(0, 60)),
+            sourceUrls: sources.map((s) => s.url),
+            ...(meta ?? {}),
+        });
+    },
+
+    contextAnalysis(systemPromptChars: number, historyChars: number, searchContextChars: number) {
+        logSection(`🧠 Context Window Analysis`);
+        const totalChars = systemPromptChars + historyChars + searchContextChars;
+        const totalTokens = estimateTokens('x'.repeat(totalChars));
+        log('INFO', 'Analysis', `Total context before sending to LLM`, {
+            systemPromptChars,
+            systemPromptTokens: estimateTokens('x'.repeat(systemPromptChars)),
+            chatHistoryChars: historyChars,
+            chatHistoryTokens: estimateTokens('x'.repeat(historyChars)),
+            searchContextChars,
+            searchContextTokens: estimateTokens('x'.repeat(searchContextChars)),
+            totalChars,
+            estimatedTotalTokens: totalTokens,
+            note: 'Token estimates are approximate (~4 chars/token). Actual tokenization varies by model.',
+        });
+    },
+
+    llmRequestStart(model: string, messageCount: number) {
+        logSection(`🤖 LLM Request`);
+        log('INFO', 'LLM', `Sending messages to LM Studio`, {
+            model,
+            totalMessages: messageCount,
+            streamingEnabled: true,
+        });
+    },
+
+    llmStreamComplete(assistantMessageId: string, chunkCount?: number) {
+        log('INFO', 'LLM', `Stream complete — response generated`, {
+            assistantMessageId,
+            ...(chunkCount !== undefined ? { chunkCount } : {}),
+        });
+    },
+
+    llmError(error: Error) {
+        log('ERROR', 'LLM', `LLM stream error`, {
+            error: error.message,
+            stack: error.stack?.split('\n').slice(0, 3).join(' | '),
+        });
+    },
+
+    pipelineComplete(query: string, totalLatencyMs: number, withSearch: boolean) {
+        logSection(`🏁 Pipeline Complete`);
+        log('INFO', 'Done', `Full request cycle finished`, {
+            query,
+            totalLatencyMs,
+            webSearchUsed: withSearch,
+        });
+        console.log('─'.repeat(55) + '\n');
+    },
+};