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chore: expurgo de blobs excedentes e realinhamento de estado
release.yml (push) Invalid workflow file
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Evandro Fonseca Junior committed 2026-02-22 14:06:01 -03:00
1 parent 593efd42e0
commit a7cbd1a3b4
114 files changed
+20716 -4258
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hooks/use-deep-research.ts
+95 -70
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@@ -23,7 +23,7 @@ export interface DeepResearchLog {
timestamp: number;
input: string;
rawOutput?: string;
parsedOutput?: any;
parsedOutput?: unknown;
error?: string;
}
@@ -47,7 +47,7 @@ function logStep(message: string) {
log.info(message);
}
function logData(label: string, data: any) {
function logData(label: string, data: unknown) {
if (typeof data === 'string' && data.length > 500) {
log.info(`${label}: ${data.substring(0, 500)}... [truncated, ${data.length} chars total]`);
} else if (typeof data === 'object') {
@@ -57,7 +57,7 @@ function logData(label: string, data: any) {
}
}
function logError(message: string, error?: any) {
function logError(message: string, error?: unknown) {
log.error(`❌ ERROR: ${message}${error ? ` - ${error}` : ''}`);
}
@@ -75,17 +75,17 @@ function extractQueriesFromResponse(raw: string): string[] {
logData('Raw response', raw);
// 1. Strip markdown code blocks (```json ... ``` or ``` ... ```)
let cleaned = raw
const cleaned = raw
.replace(/```json\s*/gi, '')
.replace(/```\s*/g, '')
.trim();
// 2. Try to parse as JSON
let parsed: any;
let parsed: unknown;
try {
parsed = JSON.parse(cleaned);
logStep('Direct JSON parse successful');
} catch (e) {
} catch {
logStep('Direct JSON parse failed, trying to extract JSON from string...');
// If JSON parse fails, try to find JSON-like content in the string
const jsonMatch = cleaned.match(/\[[\s\S]*\]|\{[\s\S]*\}/);
@@ -93,7 +93,7 @@ function extractQueriesFromResponse(raw: string): string[] {
try {
parsed = JSON.parse(jsonMatch[0]);
logStep('Extracted JSON from string successfully');
} catch (e2) {
} catch {
logError('Could not extract JSON from response');
throw new Error('Could not extract JSON from response');
}
@@ -105,7 +105,7 @@ function extractQueriesFromResponse(raw: string): string[] {
// 3. Handle different formats
if (Array.isArray(parsed)) {
const result = parsed.filter(item => typeof item === 'string' && item.trim().length > 0);
const result = (parsed as unknown[]).filter(item => typeof item === 'string' && (item as string).trim().length > 0) as string[];
logSuccess(`Parsed as plain array: ${result.length} queries`);
return result;
}
@@ -113,17 +113,19 @@ function extractQueriesFromResponse(raw: string): string[] {
// 4. Check common object keys used by different models
const commonKeys = ['queries', 'query', 'plan', 'searches', 'search_queries', 'questions'];
for (const key of commonKeys) {
if (parsed[key] && Array.isArray(parsed[key])) {
const result = parsed[key].filter((item: any) => typeof item === 'string' && item.trim().length > 0);
const obj = parsed as Record<string, unknown>;
const val = obj[key];
if (Array.isArray(val)) {
const result = (val as unknown[]).filter((item: unknown) => typeof item === 'string' && (item as string).trim().length > 0) as string[];
logSuccess(`Found queries under key "${key}": ${result.length} queries`);
return result;
}
}
// 5. Fallback: find first array value in the object
for (const val of Object.values(parsed)) {
if (Array.isArray(val) && val.length > 0 && typeof val[0] === 'string') {
const result = (val as string[]).filter((item: any) => typeof item === 'string' && item.trim().length > 0);
for (const val of Object.values(parsed as Record<string, unknown>)) {
if (Array.isArray(val) && val.length > 0 && typeof (val as unknown[])[0] === 'string') {
const result = (val as unknown[]).filter((item: unknown) => typeof item === 'string' && (item as string).trim().length > 0) as string[];
logSuccess(`Found queries in object value: ${result.length} queries`);
return result;
}
@@ -151,29 +153,19 @@ export function useDeepResearch() {
logData('Prompt length', `${prompt.length} chars`);
try {
const response = await fetch('http://localhost:11434/api/generate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model,
prompt,
stream: false,
const { invoke } = await import('@tauri-apps/api/core');
const response = await invoke<string>('generate_completion', {
model,
prompt,
options: {
temperature: 0.2,
num_predict: 2048,
format: json ? 'json' : undefined,
options: {
temperature: 0.2,
num_predict: 2048,
},
}),
},
});
if (!response.ok) {
logError(`LLM API returned status ${response.status}`);
throw new Error('Failed to call LLM');
}
const data = await response.json();
logSuccess(`LLM response received (${data.response?.length || 0} chars)`);
return data.response;
logSuccess(`LLM response received (${response?.length || 0} chars)`);
return response;
} catch (e) {
const errorMsg = e instanceof Error ? e.message : String(e);
logError('LLM Call Error', errorMsg);
@@ -255,40 +247,41 @@ export function useDeepResearch() {
plan = [query];
}
// Safety Check
logStep('--- Safety Check ---');
const keywords = query.toLowerCase().split(/\s+/).filter(w => w.length > 3);
logData('Keywords from query', keywords);
const isRelevant = plan.some(q =>
keywords.some(k => q.toLowerCase().includes(k))
);
logData('Plan is relevant', isRelevant);
if (!isRelevant && keywords.length > 0) {
logError('Safety Check Failed: Plan is irrelevant to query');
logData('Generated plan', plan);
logStep('Falling back to original query');
addLog({
stage: 'decomposition',
timestamp: Date.now(),
input: prompt,
rawOutput: response,
parsedOutput: plan,
error: 'Safety Check Failed: Plan irrelevant to query'
});
plan = [query];
const isSmallModel = /(?:270m|0\.5b|1b|1\.7b|2b|mini|small|abliterated|uncensored|qwen3|llama2)/i.test(model);
if (isSmallModel) {
logStep('Safety Check bypassed for small/experimental model');
} else {
logSuccess(`Decomposition complete: ${plan.length} search queries generated`);
addLog({
stage: 'decomposition',
timestamp: Date.now(),
input: prompt,
rawOutput: response,
parsedOutput: plan,
error: parseError
});
const isRelevant = plan.some(q =>
keywords.some(k => q.toLowerCase().includes(k))
);
logData('Plan is relevant', isRelevant);
if (!isRelevant && keywords.length > 0) {
logError('Safety Check Failed: Plan is irrelevant to query');
logData('Generated plan', plan);
logStep('Falling back to original query');
addLog({
stage: 'decomposition',
timestamp: Date.now(),
input: prompt,
rawOutput: response,
parsedOutput: plan,
error: 'Safety Check Failed: Plan irrelevant to query'
});
plan = [query];
}
}
addLog({
stage: 'decomposition',
timestamp: Date.now(),
input: prompt,
rawOutput: response,
parsedOutput: plan,
error: parseError
});
logSuccess(`Decomposition complete: ${plan.length} search queries generated`);
setState(s => ({ ...s, plan }));
return plan;
@@ -303,31 +296,63 @@ export function useDeepResearch() {
// --- ADD TO KNOWLEDGE BASE ---
const addToKnowledgeBase = useCallback((query: string, sources: ScrapedContent[]) => {
logStep(`--- Adding to Knowledge Base ---`);
logSection('ADDING TO KNOWLEDGE BASE');
logData('Query', query);
logData('Sources count', sources.length);
logData('Timestamp', new Date().toISOString());
const entries: ResearchEntry[] = sources.map((src, idx) => ({
id: `${query.substring(0, 10)}-${idx}-${Date.now()}`,
query,
sourceUrl: src.url,
title: src.title,
content: src.markdown,
content: src.markdown || src.content || '',
timestamp: Date.now(),
}));
// Log detalhado de cada fonte
sources.forEach((src, idx) => {
logStep(` → Source ${idx + 1}: ${src.title} (${src.url})`);
const contentLength = src.markdown?.length || 0;
logData(` Content length`, `${contentLength} chars`);
logStep(`\n--- Source ${idx + 1}/${sources.length} ---`);
logData('Title', src.title);
logData('URL', src.url);
const contentLength = src.markdown?.length || src.content?.length || 0;
const snippetLength = src.snippet?.length || 0;
logData('Content length (markdown)', `${contentLength} chars`);
logData('Snippet length', `${snippetLength} chars`);
logData('Cached', src.cached ? 'Yes' : 'No');
if (src.markdown && contentLength > 0) {
const preview = src.markdown.substring(0, 300);
logData(` Preview`, preview + (contentLength > 300 ? '...' : ''));
// Log preview mais detalhado
const preview = src.markdown.substring(0, 500);
logData('Content preview', preview + (contentLength > 500 ? '...' : ''));
// Estatísticas do conteúdo
const wordCount = src.markdown.split(/\s+/).length;
const paragraphCount = src.markdown.split(/\n\n/).length;
logData('Word count', wordCount);
logData('Paragraph count', paragraphCount);
} else if (src.content && src.content.length > 0) {
const preview = src.content.substring(0, 500);
logData('Content preview (raw)', preview + (src.content.length > 500 ? '...' : ''));
} else {
logStep(` ⚠️ No content extracted`);
logError('No content extracted from this source');
}
// Log snippet se disponível
if (src.snippet) {
logData('Snippet', src.snippet.substring(0, 200) + (snippetLength > 200 ? '...' : ''));
}
});
// Estatísticas agregadas
const totalContentLength = entries.reduce((sum, e) => sum + e.content.length, 0);
const avgContentLength = entries.length > 0 ? totalContentLength / entries.length : 0;
logStep('\n--- Aggregated Statistics ---');
logData('Total entries', entries.length);
logData('Total content length', `${totalContentLength} chars`);
logData('Average content length', `${Math.round(avgContentLength)} chars`);
setState(s => ({
...s,