mirror of
https://github.com/supermemoryai/supermemory.git
synced 2026-05-19 07:42:43 +00:00
Merge branch 'main' of github.com:supermemoryai/supermemory
This commit is contained in:
Dhravya Shah
commit
8931c43295
6 changed files with 55 additions and 230 deletions
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@ -194,7 +194,7 @@ export function LandingPage() {
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</li>
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<li>
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<a
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href="https://discord.gg/supermemory"
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href="https://discord.gg/b3BgKWpbtR"
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target="_blank"
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className="hover:text-white"
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rel="noreferrer"
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@ -131,10 +131,6 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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// Pre-compute the vector similarity expression
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const vectorSimilarity = sql<number>`1 - (embeddings <=> ${JSON.stringify(embedding[0])}::vector)`;
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const textSearchRank = sql<number>`ts_rank_cd(
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to_tsvector('english', coalesce(${chunk.textContent}, '')),
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plainto_tsquery('english', ${queryText})
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)`;
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// Get matching chunks with document info
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const matchingChunks = await db
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@ -145,7 +141,6 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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orderInDocument: chunk.orderInDocument,
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metadata: chunk.metadata,
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similarity: vectorSimilarity,
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textRank: textSearchRank,
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// Document fields
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docId: documents.id,
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docUuid: documents.uuid,
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@ -159,16 +154,10 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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.from(chunk)
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.innerJoin(documents, eq(chunk.documentId, documents.id))
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.where(
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and(eq(documents.userId, user.id), sql`${vectorSimilarity} > 0.5`)
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and(eq(documents.userId, user.id), sql`${vectorSimilarity} > 0.3`)
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)
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.orderBy(
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desc(sql<number>`(
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0.6 * ${vectorSimilarity} +
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0.25 * ${textSearchRank} +
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0.15 * (1.0 / (1.0 + extract(epoch from age(${documents.updatedAt})) / (90 * 24 * 60 * 60)))
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)::float`)
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)
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.limit(15);
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.orderBy(desc(vectorSimilarity))
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.limit(25);
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// Get unique document IDs from matching chunks
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const uniqueDocIds = [
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@ -201,9 +190,9 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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const docChunks = chunksByDocument.get(match.documentId) || [];
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const matchIndex = docChunks.findIndex((c) => c.id === match.chunkId);
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// Get surrounding chunks (1 before and 1 after)
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const start = Math.max(0, matchIndex - 1);
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const end = Math.min(docChunks.length, matchIndex + 2);
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// Get surrounding chunks (2 before and 2 after for more context)
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const start = Math.max(0, matchIndex - 2);
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const end = Math.min(docChunks.length, matchIndex + 3);
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const relevantChunks = docChunks.slice(start, end);
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return {
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@ -224,34 +213,23 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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};
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});
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// Remove duplicates based on document ID
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const uniqueResults = contextualResults.reduce(
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(acc, current) => {
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const existingDoc = acc.find((doc) => doc.id === current.id);
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if (!existingDoc) {
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acc.push(current);
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} else if (current.similarity > existingDoc.similarity) {
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// Replace if current match is better
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const index = acc.findIndex((doc) => doc.id === current.id);
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acc[index] = current;
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}
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return acc;
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},
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[] as typeof contextualResults
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);
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// Sort by similarity and take top results
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const topResults = contextualResults
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.sort((a, b) => b.similarity - a.similarity)
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.slice(0, 10);
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data.appendMessageAnnotation(uniqueResults);
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data.appendMessageAnnotation(topResults);
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if (lastUserMessage) {
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lastUserMessage.content =
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typeof lastUserMessage.content === "string"
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? lastUserMessage.content +
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`<context>${JSON.stringify(uniqueResults)}</context>`
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`<context>${JSON.stringify(topResults)}</context>`
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: [
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...lastUserMessage.content,
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{
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type: "text",
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text: `<context>${JSON.stringify(uniqueResults)}</context>`,
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text: `<context>${JSON.stringify(topResults)}</context>`,
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},
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];
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coreMessages[coreMessages.length - 1] = lastUserMessage;
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@ -310,7 +288,7 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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role: "assistant",
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content:
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completion.text +
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`<context>[${JSON.stringify(uniqueResults)}]</context>`,
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`<context>[${JSON.stringify(topResults)}]</context>`,
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},
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];
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@ -602,14 +580,10 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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);
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}
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// Pre-compute the vector similarity expression to avoid multiple calculations
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// Pre-compute the vector similarity expression
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const vectorSimilarity = sql<number>`1 - (embeddings <=> ${JSON.stringify(embeddings.data[0])}::vector)`;
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const textSearchRank = sql<number>`ts_rank_cd(
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to_tsvector('english', coalesce(${chunk.textContent}, '')),
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plainto_tsquery('english', ${query})
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)`;
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// First get the top matching chunks
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// Get matching chunks
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const results = await db
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.select({
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chunkId: chunk.id,
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@ -618,7 +592,6 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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orderInDocument: chunk.orderInDocument,
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metadata: chunk.metadata,
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similarity: vectorSimilarity,
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textRank: textSearchRank,
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// Document fields
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docUuid: documents.uuid,
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docContent: documents.content,
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@ -657,13 +630,7 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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: [])
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)
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)
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.orderBy(
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desc(sql<number>`(
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0.6 * ${vectorSimilarity} +
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0.25 * ${textSearchRank} +
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0.15 * (1.0 / (1.0 + extract(epoch from age(${documents.updatedAt})) / (90 * 24 * 60 * 60)))
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)::float`)
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)
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.orderBy(desc(vectorSimilarity))
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.limit(limit);
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// Group results by document and take the best matching chunk
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@ -679,26 +646,28 @@ const actions = fromHono(new Hono<{ Variables: Variables; Bindings: Env }>())
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}
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// Convert back to array and format response
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const finalResults = Array.from(documentResults.values()).map((r) => ({
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id: r.documentId,
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uuid: r.docUuid,
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content: r.docContent,
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type: r.docType,
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url: r.docUrl,
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title: r.docTitle,
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createdAt: r.docCreatedAt,
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updatedAt: r.docUpdatedAt,
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userId: r.docUserId,
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description: r.docDescription,
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ogImage: r.docOgImage,
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similarity: Number(r.similarity.toFixed(4)),
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matchingChunk: {
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id: r.chunkId,
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content: r.textContent,
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orderInDocument: r.orderInDocument,
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metadata: r.metadata,
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},
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}));
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const finalResults = Array.from(documentResults.values())
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.sort((a, b) => b.similarity - a.similarity)
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.map((r) => ({
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id: r.documentId,
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uuid: r.docUuid,
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content: r.docContent,
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type: r.docType,
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url: r.docUrl,
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title: r.docTitle,
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createdAt: r.docCreatedAt,
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updatedAt: r.docUpdatedAt,
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userId: r.docUserId,
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description: r.docDescription,
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ogImage: r.docOgImage,
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similarity: Number(r.similarity.toFixed(4)),
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matchingChunk: {
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id: r.chunkId,
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content: r.textContent,
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orderInDocument: r.orderInDocument,
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metadata: r.metadata,
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},
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}));
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return c.json({ results: finalResults });
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} catch (error) {
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@ -77,7 +77,10 @@ export default function Hero() {
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</Popover>
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*/}
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<a href="https://docs.supermemory.ai" className="text-gray-600 hover:text-gray-900 transition-colors">
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<a
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href="https://docs.supermemory.ai"
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className="text-gray-600 hover:text-gray-900 transition-colors"
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>
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Docs
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</a>
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</nav>
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@ -86,10 +89,16 @@ export default function Hero() {
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{/* Right section */}
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<div className="flex items-center space-x-6">
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<div className="hidden sm:flex items-center space-x-6">
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<a href="#" className="text-gray-600 hover:text-gray-900 transition-colors">
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<a
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href="https://git.new/memory"
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className="text-gray-600 hover:text-gray-900 transition-colors"
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>
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<GithubIcon className="h-6 w-6" />
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</a>
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<a href="#" className="text-gray-600 hover:text-gray-900 transition-colors">
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<a
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href="https://discord.gg/b3BgKWpbtR"
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className="text-gray-600 hover:text-gray-900 transition-colors"
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>
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<DiscordIcon className="h-6 w-6" />
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</a>
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</div>
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@ -1,5 +1,7 @@
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import { LoaderFunctionArgs, redirect } from "@remix-run/cloudflare";
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export async function loader({ context }: LoaderFunctionArgs) {
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return redirect("https://chromewebstore.google.com/detail/supermemory/afpgkkipfdpeaflnpoaffkcankadgjfc?hl=en");
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return redirect(
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"https://chromewebstore.google.com/detail/supermemory/afpgkkipfdpeaflnpoaffkcankadgjfc?hl=en",
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);
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}
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@ -48,84 +48,6 @@ export default function Onboarding() {
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animate={{ opacity: 1 }}
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className="flex flex-col min-h-screen items-center pt-40 relative overflow-hidden bg-gradient-to-b from-gray-900 to-gray-800 bg-opacity-40"
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>
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{/* Neural network background pattern */}
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<div className="absolute inset-0 overflow-hidden">
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{/* Subtle gradient orbs */}
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{[...Array(4)].map((_, i) => (
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<motion.div
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key={`orb-${i}`}
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className="absolute rounded-full blur-3xl opacity-20"
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style={{
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background: `radial-gradient(circle, ${
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i % 2 === 0 ? "#3b82f6" : "#4f46e5"
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} 0%, transparent 70%)`,
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width: `${Math.random() * 300 + 200}px`,
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height: `${Math.random() * 300 + 200}px`,
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}}
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animate={{
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x: [Math.random() * window.innerWidth, Math.random() * window.innerWidth],
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y: [Math.random() * window.innerHeight, Math.random() * window.innerHeight],
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}}
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transition={{
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duration: 25,
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repeat: Infinity,
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repeatType: "reverse",
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ease: "easeInOut",
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}}
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/>
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))}
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{/* Neurons */}
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{[...Array(30)].map((_, i) => (
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<motion.div
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key={i}
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className="absolute w-3 h-3 bg-blue-400/30 rounded-full"
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initial={{
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x: Math.random() * window.innerWidth,
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y: Math.random() * window.innerHeight,
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scale: Math.random() * 0.5 + 0.5,
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}}
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animate={{
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x: Math.random() * window.innerWidth,
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y: Math.random() * window.innerHeight,
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scale: [null, 1.2, 1],
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}}
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transition={{
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duration: 10 + Math.random() * 5,
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repeat: Infinity,
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ease: "linear",
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delay: Math.random() * 2,
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}}
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/>
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))}
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{/* Synaptic connections */}
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{[...Array(40)].map((_, i) => (
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<motion.div
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key={`line-${i}`}
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className="absolute h-[1px] bg-gradient-to-r from-blue-400/20 to-transparent"
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style={{
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width: `${Math.random() * 200 + 100}px`,
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transform: `rotate(${Math.random() * 360}deg)`,
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}}
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initial={{
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x: Math.random() * window.innerWidth,
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y: Math.random() * window.innerHeight,
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opacity: 0.1,
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}}
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animate={{
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opacity: [0.1, 0.3, 0.1],
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}}
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transition={{
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duration: 4 + Math.random() * 2,
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repeat: Infinity,
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ease: "easeInOut",
|
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delay: Math.random() * 2,
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||||
}}
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/>
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))}
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</div>
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{/* Logo */}
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<motion.div
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initial={{ y: 20, opacity: 0 }}
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|
|
|
|||
|
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@ -27,83 +27,6 @@ export default function Onboarding() {
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animate={{ opacity: 1 }}
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className="flex flex-col min-h-screen items-center pt-20 relative overflow-hidden bg-gradient-to-b from-gray-900 to-gray-800 bg-opacity-40"
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||||
>
|
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{/* Neural network background pattern */}
|
||||
<div className="absolute inset-0 overflow-hidden pointer-events-none">
|
||||
{/* Subtle gradient orbs */}
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||||
{[...Array(4)].map((_, i) => (
|
||||
<motion.div
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key={`orb-${i}`}
|
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className="absolute rounded-full blur-3xl opacity-20"
|
||||
style={{
|
||||
background: `radial-gradient(circle, ${
|
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i % 2 === 0 ? "#3b82f6" : "#4f46e5"
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||||
} 0%, transparent 70%)`,
|
||||
width: `${Math.random() * 300 + 200}px`,
|
||||
height: `${Math.random() * 300 + 200}px`,
|
||||
}}
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||||
animate={{
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||||
x: [Math.random() * window.innerWidth, Math.random() * window.innerWidth],
|
||||
y: [Math.random() * window.innerHeight, Math.random() * window.innerHeight],
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||||
}}
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||||
transition={{
|
||||
duration: 25,
|
||||
repeat: Infinity,
|
||||
repeatType: "reverse",
|
||||
ease: "easeInOut",
|
||||
}}
|
||||
/>
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||||
))}
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||||
|
||||
{/* Neurons */}
|
||||
{[...Array(30)].map((_, i) => (
|
||||
<motion.div
|
||||
key={i}
|
||||
className="absolute w-3 h-3 bg-blue-400/30 rounded-full"
|
||||
initial={{
|
||||
x: Math.random() * window.innerWidth,
|
||||
y: Math.random() * window.innerHeight,
|
||||
scale: Math.random() * 0.5 + 0.5,
|
||||
}}
|
||||
animate={{
|
||||
x: Math.random() * window.innerWidth,
|
||||
y: Math.random() * window.innerHeight,
|
||||
scale: [null, 1.2, 1],
|
||||
}}
|
||||
transition={{
|
||||
duration: 10 + Math.random() * 5,
|
||||
repeat: Infinity,
|
||||
ease: "linear",
|
||||
delay: Math.random() * 2,
|
||||
}}
|
||||
/>
|
||||
))}
|
||||
|
||||
{/* Synaptic connections */}
|
||||
{[...Array(40)].map((_, i) => (
|
||||
<motion.div
|
||||
key={`line-${i}`}
|
||||
className="absolute h-[1px] bg-gradient-to-r from-blue-400/20 to-transparent"
|
||||
style={{
|
||||
width: `${Math.random() * 200 + 100}px`,
|
||||
transform: `rotate(${Math.random() * 360}deg)`,
|
||||
}}
|
||||
initial={{
|
||||
x: Math.random() * window.innerWidth,
|
||||
y: Math.random() * window.innerHeight,
|
||||
opacity: 0.1,
|
||||
}}
|
||||
animate={{
|
||||
opacity: [0.1, 0.3, 0.1],
|
||||
}}
|
||||
transition={{
|
||||
duration: 4 + Math.random() * 2,
|
||||
repeat: Infinity,
|
||||
ease: "easeInOut",
|
||||
delay: Math.random() * 2,
|
||||
}}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{/* Logo */}
|
||||
<motion.div
|
||||
|
|
|
|||
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