mirror of
https://github.com/supermemoryai/supermemory.git
synced 2026-09-07 08:26:15 +00:00
fix(docs): fix and verify all code snippets across documentation
- Rename client.memories to client.documents throughout - Fix bulkDelete -> deleteBulk (TS) and bulk_delete -> delete_bulk (Python) - Fix search method: client.search() -> client.search.memories() - Fix Python f-string syntax for 3.10 compatibility - Remove non-existent fetchMemoryTool from integrations - Fix filters format from JSON.stringify to object - Fix uploadFile parameters and containerTags usage - Fix response field access patterns - Verify all snippets work against live API Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Dhravya Shah
parent
f9075bc5c1
commit
d114ddb86e
29 changed files with 246 additions and 276 deletions
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@ -116,7 +116,7 @@ To completely replace a document's content (not append), use `memories.update()`
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```typescript
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// Replace the entire document content
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await client.memories.update("doc_id_123", {
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await client.documents.update("doc_id_123", {
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content: "Completely new content replacing everything",
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metadata: { version: 2 }
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});
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@ -153,7 +153,7 @@ Upload PDFs, images, and documents directly.
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```typescript
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import fs from 'fs';
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await client.memories.uploadFile({
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await client.documents.uploadFile({
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file: fs.createReadStream('document.pdf'),
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containerTags: 'user_123'
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});
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@ -162,7 +162,7 @@ Upload PDFs, images, and documents directly.
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<Tab title="Python">
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```python
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with open('document.pdf', 'rb') as file:
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client.memories.upload_file(
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client.documents.upload_file(
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file=file,
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container_tags='user_123'
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)
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@ -275,7 +275,7 @@ When you add content, Supermemory:
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Track progress with `GET /v3/documents/{id}`:
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```typescript
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const doc = await client.memories.get("abc123");
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const doc = await client.documents.get("abc123");
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console.log(doc.status); // "queued" | "processing" | "done"
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```
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@ -342,12 +342,12 @@ console.log(doc.status); // "queued" | "processing" | "done"
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<Accordion title="Delete Content">
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**Single delete:**
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```typescript
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await client.memories.delete("doc_id_123");
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await client.documents.delete("doc_id_123");
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```
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**Bulk delete by IDs:**
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```typescript
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await client.memories.bulkDelete({
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await client.documents.deleteBulk({
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ids: ["doc_1", "doc_2", "doc_3"]
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});
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```
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@ -355,7 +355,7 @@ console.log(doc.status); // "queued" | "processing" | "done"
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**Bulk delete by container tag:**
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```typescript
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// Delete all content for a user
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await client.memories.bulkDelete({
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await client.documents.deleteBulk({
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containerTags: ["user_123"]
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});
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```
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@ -14,7 +14,7 @@ Extract text from PDFs with OCR support.
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```typescript TypeScript
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const file = fs.createReadStream('document.pdf');
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const response = await client.memories.uploadFile({
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const response = await client.documents.uploadFile({
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file: file,
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containerTags: 'documents'
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});
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@ -25,7 +25,7 @@ console.log(response.id);
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```python Python
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with open('document.pdf', 'rb') as file:
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response = client.memories.upload_file(
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response = client.documents.upload_file(
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file=file,
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container_tags='documents'
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)
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@ -54,7 +54,7 @@ Extract text from images.
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```typescript TypeScript
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const image = fs.createReadStream('screenshot.png');
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await client.memories.uploadFile({
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await client.documents.uploadFile({
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file: image,
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containerTags: 'images'
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});
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@ -62,7 +62,7 @@ await client.memories.uploadFile({
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```python Python
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with open('screenshot.png', 'rb') as file:
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client.memories.upload_file(
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client.documents.upload_file(
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file=file,
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container_tags='images'
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)
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@ -134,7 +134,7 @@ Batch upload with rate limiting.
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for (const file of files) {
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const stream = fs.createReadStream(file);
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await client.memories.uploadFile({
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await client.documents.uploadFile({
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file: stream,
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containerTags: 'batch'
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});
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@ -149,7 +149,7 @@ import time
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for file_path in files:
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with open(file_path, 'rb') as file:
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client.memories.upload_file(
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client.documents.upload_file(
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file=file,
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container_tags='batch'
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)
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@ -156,14 +156,14 @@ Upload files directly for processing.
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<CodeGroup>
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```typescript TypeScript
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await client.memories.uploadFile({
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await client.documents.uploadFile({
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file: fileStream,
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containerTag: "project"
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});
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```
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```python Python
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client.memories.upload_file(
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client.documents.upload_file(
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file=open('file.pdf', 'rb'),
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container_tags='project'
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)
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@ -187,13 +187,13 @@ Update existing document content.
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<CodeGroup>
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```typescript TypeScript
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await client.memories.update("doc_id", {
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await client.documents.update("doc_id", {
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content: "Updated content"
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});
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```
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```python Python
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client.memories.update("doc_id", {
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client.documents.update("doc_id", {
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"content": "Updated content"
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})
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```
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@ -216,7 +216,7 @@ client.add(
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### 3. Hybrid Retrieval
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```python
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# Search combines both approaches
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results = client.memories.search(
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results = client.documents.search(
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query="What phone should I recommend?",
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container_tags=["user_123"], # Gets user memories
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# Also searches general knowledge
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@ -139,7 +139,7 @@ connections.forEach(conn => {
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});
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// List synced documents (memories) using SDK
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const memories = await client.memories.list({
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const memories = await client.documents.list({
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containerTags: ['user-123', 'workspace-alpha']
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});
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@ -165,7 +165,7 @@ for conn in connections:
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print(f'Created: {conn.created_at}')
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# List synced documents (memories) using SDK
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memories = client.memories.list(container_tags=['user-123', 'workspace-alpha'])
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memories = client.documents.list(container_tags=['user-123', 'workspace-alpha'])
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print(f'Synced {len(memories.memories)} documents')
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# Output: Synced 45 documents
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@ -93,7 +93,7 @@ A customer support bot that:
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async getCustomerHistory(customerId: string, limit: number = 10) {
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try {
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const memories = await client.memories.list({
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const memories = await client.documents.list({
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containerTags: [this.getContainerTag(customerId)],
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limit,
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sort: 'updatedAt',
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@ -170,8 +170,8 @@ A customer support bot that:
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try {
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// Note: In a real implementation, you'd update the memory
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// For now, we'll add a status update
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const memory = await client.memories.get(issueId)
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const customerId = memory.containerTag.replace('customer_', '')
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const memory = await client.documents.get(issueId)
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const customerId = memory.containerTags?.[0]?.replace('customer_', '') || ''
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const updateContent = `ISSUE UPDATE: ${memory.metadata?.subject}\nStatus changed to: ${status}${resolution ? `\nResolution: ${resolution}` : ''}`
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@ -253,7 +253,7 @@ A customer support bot that:
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def get_customer_history(self, customer_id: str, limit: int = 10) -> List[Dict]:
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"""Get customer interaction history"""
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try:
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memories = self.client.memories.list(
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memories = self.client.documents.list(
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container_tags=[self._get_container_tag(customer_id)],
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limit=limit,
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sort='updatedAt',
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@ -330,8 +330,8 @@ Status: {issue['status']}"""
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"""Update the status of a support issue"""
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try:
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# Get original issue
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memory = self.client.memories.get(issue_id)
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customer_id = memory.container_tag.replace('customer_', '')
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memory = self.client.documents.get(issue_id)
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customer_id = (memory.container_tags[0] if memory.container_tags else '').replace('customer_', '')
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update_content = f"ISSUE UPDATE: {memory.metadata.get('subject', 'Unknown')}\nStatus changed to: {status}"
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if resolution:
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@ -91,7 +91,7 @@ A document Q&A system that:
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async getDocumentStatus(documentId: string) {
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try {
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const memory = await client.memories.get(documentId)
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const memory = await client.documents.get(documentId)
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return {
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id: memory.id,
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status: memory.status,
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@ -106,7 +106,7 @@ A document Q&A system that:
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async listDocuments(collection: string) {
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try {
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const memories = await client.memories.list({
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const memories = await client.documents.list({
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containerTags: [collection],
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limit: 50,
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sort: 'updatedAt',
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@ -148,15 +148,10 @@ A document Q&A system that:
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return NextResponse.json({ error: 'No file provided' }, { status: 400 })
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}
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// Convert File to Buffer for Supermemory
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const bytes = await file.arrayBuffer()
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const buffer = Buffer.from(bytes)
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const result = await client.memories.uploadFile({
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file: buffer,
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filename: file.name,
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containerTags,
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metadata
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const result = await client.documents.uploadFile({
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file: file,
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containerTags: JSON.stringify(containerTags),
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metadata: JSON.stringify(metadata)
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})
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return NextResponse.json({
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@ -180,6 +175,7 @@ A document Q&A system that:
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```python document_processor.py
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from supermemory import Supermemory
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import os
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import json
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from typing import Dict, List, Any, Optional
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import requests
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from datetime import datetime
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@ -195,15 +191,15 @@ A document Q&A system that:
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try:
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with open(file_path, 'rb') as file:
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result = self.client.memories.upload_file(
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result = self.client.documents.upload_file(
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file=file,
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container_tags=[collection],
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metadata={
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container_tags=collection,
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metadata=json.dumps({
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'originalName': os.path.basename(file_path),
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'fileType': os.path.splitext(file_path)[1],
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'uploadedAt': datetime.now().isoformat(),
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**metadata
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}
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})
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)
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return result
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except Exception as e:
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@ -234,7 +230,7 @@ A document Q&A system that:
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def get_document_status(self, document_id: str) -> Dict:
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"""Check document processing status"""
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try:
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memory = self.client.memories.get(document_id)
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memory = self.client.documents.get(document_id)
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return {
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'id': memory.id,
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'status': memory.status,
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@ -248,7 +244,7 @@ A document Q&A system that:
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def list_documents(self, collection: str) -> List[Dict]:
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"""List all documents in a collection"""
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try:
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memories = self.client.memories.list(
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memories = self.client.documents.list(
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container_tags=[collection],
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limit=50,
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sort='updatedAt',
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@ -307,7 +303,6 @@ A document Q&A system that:
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includeFullDocs: false,
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includeSummary: true,
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onlyMatchingChunks: false,
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documentThreshold: 0.6,
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chunkThreshold: 0.7
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})
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@ -432,7 +427,6 @@ If the question cannot be answered from the provided documents, respond with: "I
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include_full_docs=False,
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include_summary=True,
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only_matching_chunks=False,
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document_threshold=0.6,
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chunk_threshold=0.7
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)
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@ -803,7 +803,7 @@ client = Supermemory(api_key=os.getenv("SUPERMEMORY_API_KEY"))
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user_id = "your_user_id_here"
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container_tag = f"user_{user_id}"
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memories = client.memories.list(
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memories = client.documents.list(
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container_tags=[container_tag],
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limit=20,
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sort="updatedAt",
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@ -812,7 +812,7 @@ memories = client.memories.list(
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print(f"Found {len(memories.memories)} memories:")
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for i, memory in enumerate(memories.memories):
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full = client.memories.get(id=memory.id)
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full = client.documents.get(id=memory.id)
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print(f"\n{i + 1}. {full.content}")
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```
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@ -19,7 +19,7 @@ Retrieve paginated documents with filtering.
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containerTags: ["user_123"]
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});
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documents.forEach(d => {
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documents.memories.forEach(d => {
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console.log(d.id, d.title, d.status);
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});
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```
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@ -104,12 +104,12 @@ Retrieve paginated documents with filtering.
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```typescript
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const documents = await client.documents.list({
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containerTags: ["user_123"],
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filters: JSON.stringify({
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filters: {
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AND: [
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{ key: "status", value: "reviewed" },
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{ key: "priority", value: "high" }
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{ key: "status", value: "reviewed", negate: false },
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{ key: "priority", value: "high", negate: false }
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]
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})
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}
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});
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```
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</Accordion>
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@ -197,7 +197,7 @@ Update a document's content or metadata. Triggers reprocessing.
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</Tab>
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<Tab title="cURL">
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```bash
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curl -X PUT "https://api.supermemory.ai/v3/documents/doc_abc123" \
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curl -X PATCH "https://api.supermemory.ai/v3/documents/doc_abc123" \
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-H "Authorization: Bearer $SUPERMEMORY_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{"content": "Updated content here", "metadata": {"version": 2}}'
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@ -218,12 +218,12 @@ Permanently remove documents.
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await client.documents.delete("doc_abc123");
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// Bulk delete by IDs
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await client.documents.bulkDelete({
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await client.documents.deleteBulk({
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ids: ["doc_1", "doc_2", "doc_3"]
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});
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// Bulk delete by container tag (delete all for a user)
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await client.documents.bulkDelete({
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await client.documents.deleteBulk({
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containerTags: ["user_123"]
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});
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```
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@ -234,10 +234,10 @@ Permanently remove documents.
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client.documents.delete("doc_abc123")
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# Bulk delete by IDs
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client.documents.bulk_delete(ids=["doc_1", "doc_2", "doc_3"])
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client.documents.delete_bulk(ids=["doc_1", "doc_2", "doc_3"])
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# Bulk delete by container tag
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client.documents.bulk_delete(container_tags=["user_123"])
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client.documents.delete_bulk(container_tags=["user_123"])
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```
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</Tab>
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<Tab title="cURL">
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@ -247,7 +247,7 @@ Permanently remove documents.
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-H "Authorization: Bearer $SUPERMEMORY_API_KEY"
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# Bulk delete by IDs
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curl -X POST "https://api.supermemory.ai/v3/documents/bulk-delete" \
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curl -X DELETE "https://api.supermemory.ai/v3/documents/bulk" \
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-H "Authorization: Bearer $SUPERMEMORY_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{"ids": ["doc_1", "doc_2", "doc_3"]}'
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@ -268,12 +268,14 @@ Check documents currently being processed.
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<Tabs>
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<Tab title="TypeScript">
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```typescript
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const response = await fetch("https://api.supermemory.ai/v3/documents/processing", {
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headers: { "Authorization": `Bearer ${API_KEY}` }
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});
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const { documents } = await response.json();
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console.log(`${documents.length} documents processing`);
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const response = await client.documents.listProcessing();
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console.log(`${response.documents.length} documents processing`);
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```
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</Tab>
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<Tab title="Python">
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```python
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response = client.documents.list_processing()
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print(f"{len(response.documents)} documents processing")
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```
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</Tab>
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<Tab title="cURL">
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|
|
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|
|
@ -150,16 +150,6 @@ const result = await streamText({
|
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// AI will call: addMemory({ memory: "User is allergic to peanuts" })
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```
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**Fetch Memory** - Retrieve specific memory by ID:
|
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|
||||
```typescript
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const result = await streamText({
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model: openai("gpt-5"),
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||||
prompt: "Get the details of memory abc123",
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tools: supermemoryTools("API_KEY")
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})
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```
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||||
### Using Individual Tools
|
||||
|
||||
For more control, import tools separately:
|
||||
|
|
@ -167,8 +157,7 @@ For more control, import tools separately:
|
|||
```typescript
|
||||
import {
|
||||
searchMemoriesTool,
|
||||
addMemoryTool,
|
||||
fetchMemoryTool
|
||||
addMemoryTool
|
||||
} from "@supermemory/tools/ai-sdk"
|
||||
|
||||
const result = await streamText({
|
||||
|
|
@ -189,8 +178,5 @@ const result = await streamText({
|
|||
|
||||
// addMemory result
|
||||
{ success: true, memory: { id: "mem_123", ... } }
|
||||
|
||||
// fetchMemory result
|
||||
{ success: true, memory: { id: "mem_123", content: "...", ... } }
|
||||
```
|
||||
|
||||
|
|
|
|||
|
|
@ -204,30 +204,6 @@ console.log(`Added memory with ID: ${addResult.memory.id}`)
|
|||
|
||||
</CodeGroup>
|
||||
|
||||
### Fetch Memory
|
||||
|
||||
Retrieve specific memory by ID:
|
||||
|
||||
<CodeGroup>
|
||||
|
||||
```python Python
|
||||
# Fetch specific memory
|
||||
result = await tools.fetch_memory(
|
||||
memory_id="memory-id-here"
|
||||
)
|
||||
print(f"Memory content: {result.memory.content}")
|
||||
```
|
||||
|
||||
```typescript JavaScript
|
||||
// Fetch specific memory
|
||||
const fetchResult = await tools.fetchMemory({
|
||||
memoryId: "memory-id-here"
|
||||
})
|
||||
console.log(`Memory content: ${fetchResult.memory.content}`)
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
||||
## Individual Tools
|
||||
|
||||
Use tools separately for more granular control:
|
||||
|
|
@ -237,31 +213,27 @@ Use tools separately for more granular control:
|
|||
```python Python Individual Tools
|
||||
from supermemory_openai import (
|
||||
create_search_memories_tool,
|
||||
create_add_memory_tool,
|
||||
create_fetch_memory_tool
|
||||
create_add_memory_tool
|
||||
)
|
||||
|
||||
search_tool = create_search_memories_tool("your-api-key")
|
||||
add_tool = create_add_memory_tool("your-api-key")
|
||||
fetch_tool = create_fetch_memory_tool("your-api-key")
|
||||
|
||||
# Use individual tools in OpenAI function calling
|
||||
tools_list = [search_tool, add_tool, fetch_tool]
|
||||
tools_list = [search_tool, add_tool]
|
||||
```
|
||||
|
||||
```typescript JavaScript Individual Tools
|
||||
import {
|
||||
createSearchMemoriesTool,
|
||||
createAddMemoryTool,
|
||||
createFetchMemoryTool
|
||||
createAddMemoryTool
|
||||
} from "@supermemory/tools/openai"
|
||||
|
||||
const searchTool = createSearchMemoriesTool(process.env.SUPERMEMORY_API_KEY!)
|
||||
const addTool = createAddMemoryTool(process.env.SUPERMEMORY_API_KEY!)
|
||||
const fetchTool = createFetchMemoryTool(process.env.SUPERMEMORY_API_KEY!)
|
||||
|
||||
// Use individual tools
|
||||
const toolDefinitions = [searchTool, addTool, fetchTool]
|
||||
const toolDefinitions = [searchTool.definition, addTool.definition]
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
|
@ -490,7 +462,6 @@ SupermemoryTools(
|
|||
- `get_tool_definitions()` - Get OpenAI function definitions
|
||||
- `search_memories(information_to_get, limit, include_full_docs)` - Search user memories
|
||||
- `add_memory(memory)` - Add new memory
|
||||
- `fetch_memory(memory_id)` - Fetch specific memory by ID
|
||||
- `execute_tool_call(tool_call)` - Execute individual tool call
|
||||
|
||||
#### `execute_memory_tool_calls`
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ Simple memory retrieval examples for getting started with the list memories endp
|
|||
apiKey: process.env.SUPERMEMORY_API_KEY!
|
||||
});
|
||||
|
||||
const response = await client.memories.list({ limit: 10 });
|
||||
const response = await client.documents.list({ limit: 10 });
|
||||
console.log(response);
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -26,7 +26,7 @@ Simple memory retrieval examples for getting started with the list memories endp
|
|||
import os
|
||||
|
||||
client = Supermemory(api_key=os.environ.get("SUPERMEMORY_API_KEY"))
|
||||
response = client.memories.list(limit=10)
|
||||
response = client.documents.list(limit=10)
|
||||
print(response)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -45,7 +45,7 @@ Simple memory retrieval examples for getting started with the list memories endp
|
|||
<Tabs>
|
||||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
const response = await client.memories.list({
|
||||
const response = await client.documents.list({
|
||||
containerTags: ["user_123"],
|
||||
limit: 20,
|
||||
sort: "updatedAt",
|
||||
|
|
@ -57,7 +57,7 @@ Simple memory retrieval examples for getting started with the list memories endp
|
|||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
response = client.memories.list(
|
||||
response = client.documents.list(
|
||||
container_tags=["user_123"],
|
||||
limit=20,
|
||||
sort="updatedAt",
|
||||
|
|
|
|||
|
|
@ -13,12 +13,12 @@ Container tags use exact array matching - memories must have the exact same tags
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Single tag - matches memories with exactly ["user_123"]
|
||||
const userMemories = await client.memories.list({
|
||||
const userMemories = await client.documents.list({
|
||||
containerTags: ["user_123"]
|
||||
});
|
||||
|
||||
// Multiple tags - matches memories with exactly ["user_123", "project_ai"]
|
||||
const projectMemories = await client.memories.list({
|
||||
const projectMemories = await client.documents.list({
|
||||
containerTags: ["user_123", "project_ai"]
|
||||
});
|
||||
```
|
||||
|
|
@ -26,10 +26,10 @@ Container tags use exact array matching - memories must have the exact same tags
|
|||
<Tab title="Python">
|
||||
```python
|
||||
# Single tag
|
||||
user_memories = client.memories.list(container_tags=["user_123"])
|
||||
user_memories = client.documents.list(container_tags=["user_123"])
|
||||
|
||||
# Multiple tags (exact match)
|
||||
project_memories = client.memories.list(
|
||||
project_memories = client.documents.list(
|
||||
container_tags=["user_123", "project_ai"]
|
||||
)
|
||||
```
|
||||
|
|
@ -72,7 +72,7 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
<Info>
|
||||
**Filter Structure Rules:**
|
||||
- Always wrap conditions in `AND` or `OR` arrays (even single conditions)
|
||||
- Use `JSON.stringify()` to convert the filter object to a string
|
||||
- Pass the filter as an object (TypeScript/Python) or JSON string (cURL)
|
||||
- Each condition needs `key`, `value`, and `negate` properties
|
||||
- `negate: false` for normal matching, `negate: true` for exclusion
|
||||
</Info>
|
||||
|
|
@ -83,26 +83,24 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Filter by single metadata field
|
||||
const programmingMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const programmingMemories = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{ key: "category", value: "programming", negate: false }
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
import json
|
||||
|
||||
# Filter by single metadata field
|
||||
programming_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
programming_memories = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{"key": "category", "value": "programming", "negate": False}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -124,28 +122,28 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// All conditions must match
|
||||
const reactTutorials = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const reactTutorials = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{ key: "category", value: "tutorial", negate: false },
|
||||
{ key: "framework", value: "react", negate: false },
|
||||
{ key: "difficulty", value: "beginner", negate: false }
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
# All conditions must match
|
||||
react_tutorials = client.memories.list(
|
||||
filters=json.dumps({
|
||||
react_tutorials = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{"key": "category", "value": "tutorial", "negate": False},
|
||||
{"key": "framework", "value": "react", "negate": False},
|
||||
{"key": "difficulty", "value": "beginner", "negate": False}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -167,28 +165,28 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Any condition can match
|
||||
const frontendMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const frontendMemories = await client.documents.list({
|
||||
filters: {
|
||||
OR: [
|
||||
{ key: "framework", value: "react", negate: false },
|
||||
{ key: "framework", value: "vue", negate: false },
|
||||
{ key: "framework", value: "angular", negate: false }
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
# Any condition can match
|
||||
frontend_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
frontend_memories = client.documents.list(
|
||||
filters={
|
||||
"OR": [
|
||||
{"key": "framework", "value": "react", "negate": False},
|
||||
{"key": "framework", "value": "vue", "negate": False},
|
||||
{"key": "framework", "value": "angular", "negate": False}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -210,8 +208,8 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Complex logic: programming AND (react OR advanced difficulty)
|
||||
const advancedContent = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const advancedContent = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{ key: "category", value: "programming", negate: false },
|
||||
{
|
||||
|
|
@ -221,15 +219,15 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
# Complex logic: programming AND (react OR advanced difficulty)
|
||||
advanced_content = client.memories.list(
|
||||
filters=json.dumps({
|
||||
advanced_content = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{"key": "category", "value": "programming", "negate": False},
|
||||
{
|
||||
|
|
@ -239,7 +237,7 @@ The JSON structure forces explicit grouping to prevent unexpected results.
|
|||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -265,8 +263,8 @@ Filter memories that contain specific values in array fields like participants,
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Find memories where john.doe participated
|
||||
const meetingMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const meetingMemories = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{
|
||||
key: "participants",
|
||||
|
|
@ -275,15 +273,15 @@ Filter memories that contain specific values in array fields like participants,
|
|||
negate: false
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
# Find memories where john.doe participated
|
||||
meeting_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
meeting_memories = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{
|
||||
"key": "participants",
|
||||
|
|
@ -292,7 +290,7 @@ Filter memories that contain specific values in array fields like participants,
|
|||
"negate": False
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -314,8 +312,8 @@ Filter memories that contain specific values in array fields like participants,
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Find memories that don't include a specific team member
|
||||
const filteredMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const filteredMemories = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{
|
||||
key: "reviewers",
|
||||
|
|
@ -330,15 +328,15 @@ Filter memories that contain specific values in array fields like participants,
|
|||
negate: false
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
# Find memories that don't include a specific team member
|
||||
filtered_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
filtered_memories = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{
|
||||
"key": "reviewers",
|
||||
|
|
@ -353,7 +351,7 @@ Filter memories that contain specific values in array fields like participants,
|
|||
"negate": False
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -375,8 +373,8 @@ Filter memories that contain specific values in array fields like participants,
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Find memories involving any of several team leads
|
||||
const leadershipMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const leadershipMemories = await client.documents.list({
|
||||
filters: {
|
||||
OR: [
|
||||
{
|
||||
key: "attendees",
|
||||
|
|
@ -394,7 +392,7 @@ Filter memories that contain specific values in array fields like participants,
|
|||
filterType: "array_contains"
|
||||
}
|
||||
]
|
||||
}),
|
||||
},
|
||||
sort: "updatedAt",
|
||||
order: "desc"
|
||||
});
|
||||
|
|
@ -403,8 +401,8 @@ Filter memories that contain specific values in array fields like participants,
|
|||
<Tab title="Python">
|
||||
```python
|
||||
# Find memories involving any of several team leads
|
||||
leadership_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
leadership_memories = client.documents.list(
|
||||
filters={
|
||||
"OR": [
|
||||
{
|
||||
"key": "attendees",
|
||||
|
|
@ -422,7 +420,7 @@ Filter memories that contain specific values in array fields like participants,
|
|||
"filterType": "array_contains"
|
||||
}
|
||||
]
|
||||
}),
|
||||
},
|
||||
sort="updatedAt",
|
||||
order="desc"
|
||||
)
|
||||
|
|
@ -447,14 +445,14 @@ Filter memories that contain specific values in array fields like participants,
|
|||
<Tabs>
|
||||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
const filteredMemories = await client.memories.list({
|
||||
const filteredMemories = await client.documents.list({
|
||||
containerTags: ["user_123"],
|
||||
filters: JSON.stringify({
|
||||
filters: {
|
||||
AND: [
|
||||
{ key: "category", value: "tutorial", negate: false },
|
||||
{ key: "framework", value: "react", negate: false }
|
||||
]
|
||||
}),
|
||||
},
|
||||
sort: "updatedAt",
|
||||
order: "desc",
|
||||
limit: 50
|
||||
|
|
@ -463,14 +461,14 @@ Filter memories that contain specific values in array fields like participants,
|
|||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
filtered_memories = client.memories.list(
|
||||
filtered_memories = client.documents.list(
|
||||
container_tags=["user_123"],
|
||||
filters=json.dumps({
|
||||
filters={
|
||||
"AND": [
|
||||
{"key": "category", "value": "tutorial", "negate": False},
|
||||
{"key": "framework", "value": "react", "negate": False}
|
||||
]
|
||||
}),
|
||||
},
|
||||
sort="updatedAt",
|
||||
order="desc",
|
||||
limit=50
|
||||
|
|
@ -495,9 +493,9 @@ Filter memories that contain specific values in array fields like participants,
|
|||
|
||||
<Warning>
|
||||
**Common Mistakes:**
|
||||
- Using bare condition objects: `{"key": "category", "value": "programming"}`
|
||||
- Forgetting JSON.stringify: passing objects instead of strings
|
||||
- Using bare condition objects: `{"key": "category", "value": "programming"}` without wrapping in `AND` or `OR`
|
||||
- Missing negate property: always include `"negate": false` or `"negate": true`
|
||||
- For cURL requests: forgetting to properly escape the JSON string
|
||||
</Warning>
|
||||
|
||||
<Note>
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
<Tabs>
|
||||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
const response = await client.memories.list({ limit: 100 });
|
||||
const response = await client.documents.list({ limit: 100 });
|
||||
|
||||
const statusCounts = response.memories.reduce((acc: any, memory) => {
|
||||
acc[memory.status] = (acc[memory.status] || 0) + 1;
|
||||
|
|
@ -22,7 +22,7 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
response = client.memories.list(limit=100)
|
||||
response = client.documents.list(limit=100)
|
||||
|
||||
status_counts = {}
|
||||
for memory in response.memories:
|
||||
|
|
@ -48,7 +48,7 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
<Tabs>
|
||||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
const response = await client.memories.list({ limit: 100 });
|
||||
const response = await client.documents.list({ limit: 100 });
|
||||
|
||||
const processing = response.memories.filter(m =>
|
||||
['queued', 'extracting', 'chunking', 'embedding', 'indexing'].includes(m.status)
|
||||
|
|
@ -59,7 +59,7 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
response = client.memories.list(limit=100)
|
||||
response = client.documents.list(limit=100)
|
||||
|
||||
processing_statuses = ['queued', 'extracting', 'chunking', 'embedding', 'indexing']
|
||||
processing = [m for m in response.memories if m.status in processing_statuses]
|
||||
|
|
@ -83,21 +83,22 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
<Tabs>
|
||||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
const failedMemories = await client.memories.list({
|
||||
filters: "status:failed",
|
||||
limit: 50
|
||||
});
|
||||
const response = await client.documents.list({ limit: 100 });
|
||||
|
||||
failedMemories.memories.forEach(memory => {
|
||||
const failedMemories = response.memories.filter(m => m.status === 'failed');
|
||||
|
||||
failedMemories.forEach(memory => {
|
||||
console.log(`Failed: ${memory.id} - ${memory.title || 'Untitled'}`);
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Python">
|
||||
```python
|
||||
failed_memories = client.memories.list(filters="status:failed", limit=50)
|
||||
response = client.documents.list(limit=100)
|
||||
|
||||
for memory in failed_memories.memories:
|
||||
failed_memories = [m for m in response.memories if m.status == 'failed']
|
||||
|
||||
for memory in failed_memories:
|
||||
title = memory.title or 'Untitled'
|
||||
print(f"Failed: {memory.id} - {title}")
|
||||
```
|
||||
|
|
@ -107,8 +108,8 @@ Monitor memory processing status and track completion rates using the list endpo
|
|||
curl -X POST "https://api.supermemory.ai/v3/documents/list" \
|
||||
-H "Authorization: Bearer $SUPERMEMORY_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{"filters": "status:failed", "limit": 50}' | \
|
||||
jq '.memories[] | {id, title, status}'
|
||||
-d '{"limit": 100}' | \
|
||||
jq '.memories[] | select(.status == "failed") | {id, title, status}'
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
|
|
|||
|
|
@ -11,13 +11,13 @@ Handle large memory collections efficiently using pagination to process data in
|
|||
<Tab title="TypeScript">
|
||||
```typescript
|
||||
// Get first page
|
||||
const page1 = await client.memories.list({
|
||||
const page1 = await client.documents.list({
|
||||
limit: 20,
|
||||
page: 1
|
||||
});
|
||||
|
||||
// Get next page
|
||||
const page2 = await client.memories.list({
|
||||
const page2 = await client.documents.list({
|
||||
limit: 20,
|
||||
page: 2
|
||||
});
|
||||
|
|
@ -29,10 +29,10 @@ Handle large memory collections efficiently using pagination to process data in
|
|||
<Tab title="Python">
|
||||
```python
|
||||
# Get first page
|
||||
page1 = client.memories.list(limit=20, page=1)
|
||||
page1 = client.documents.list(limit=20, page=1)
|
||||
|
||||
# Get next page
|
||||
page2 = client.memories.list(limit=20, page=2)
|
||||
page2 = client.documents.list(limit=20, page=2)
|
||||
|
||||
print(f"Page 1: {len(page1.memories)} memories")
|
||||
print(f"Page 2: {len(page2.memories)} memories")
|
||||
|
|
@ -64,7 +64,7 @@ Handle large memory collections efficiently using pagination to process data in
|
|||
let hasMore = true;
|
||||
|
||||
while (hasMore) {
|
||||
const response = await client.memories.list({
|
||||
const response = await client.documents.list({
|
||||
page: currentPage,
|
||||
limit: 50
|
||||
});
|
||||
|
|
@ -82,7 +82,7 @@ Handle large memory collections efficiently using pagination to process data in
|
|||
has_more = True
|
||||
|
||||
while has_more:
|
||||
response = client.memories.list(page=current_page, limit=50)
|
||||
response = client.documents.list(page=current_page, limit=50)
|
||||
|
||||
print(f"Page {current_page}: {len(response.memories)} memories")
|
||||
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ Retrieve paginated memories with filtering and sorting options from your Superme
|
|||
apiKey: process.env.SUPERMEMORY_API_KEY!
|
||||
});
|
||||
|
||||
const memories = await client.memories.list({ limit: 10 });
|
||||
const memories = await client.documents.list({ limit: 10 });
|
||||
console.log(memories);
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -28,7 +28,7 @@ Retrieve paginated memories with filtering and sorting options from your Superme
|
|||
import os
|
||||
|
||||
client = Supermemory(api_key=os.environ.get("SUPERMEMORY_API_KEY"))
|
||||
memories = client.memories.list(limit=10)
|
||||
memories = client.documents.list(limit=10)
|
||||
print(f"Found {len(memories.memories)} memories")
|
||||
```
|
||||
</Tab>
|
||||
|
|
|
|||
|
|
@ -168,7 +168,7 @@ curl --location 'https://api.supermemory.ai/v3/documents' \
|
|||
```
|
||||
|
||||
```typescript Typescript
|
||||
await client.memories.create({
|
||||
await client.documents.create({
|
||||
content: "quarterly planning meeting discussion",
|
||||
metadata: {
|
||||
participants: ["john.doe", "sarah.smith", "mike.wilson"]
|
||||
|
|
@ -177,7 +177,7 @@ await client.memories.create({
|
|||
```
|
||||
|
||||
```python Python
|
||||
client.memories.create(
|
||||
client.documents.create(
|
||||
content="quarterly planning meeting discussion",
|
||||
metadata={
|
||||
"participants": ["john.doe", "sarah.smith", "mike.wilson"]
|
||||
|
|
|
|||
|
|
@ -205,7 +205,7 @@ const client = new Supermemory({
|
|||
})
|
||||
|
||||
// Method 1: Using SDK uploadFile method (RECOMMENDED)
|
||||
const result = await client.memories.uploadFile({
|
||||
const result = await client.documents.uploadFile({
|
||||
file: fs.createReadStream('/path/to/document.pdf'),
|
||||
containerTags: 'research_project' // String, not array!
|
||||
})
|
||||
|
|
@ -234,7 +234,7 @@ from supermemory import Supermemory
|
|||
client = Supermemory(api_key="your_api_key")
|
||||
|
||||
# Method 1: Using SDK upload_file method (RECOMMENDED)
|
||||
result = client.memories.upload_file(
|
||||
result = client.documents.upload_file(
|
||||
file=open('document.pdf', 'rb'),
|
||||
container_tags='research_project' # String parameter name
|
||||
)
|
||||
|
|
|
|||
|
|
@ -78,7 +78,7 @@ from supermemory import Supermemory
|
|||
|
||||
client = Supermemory()
|
||||
|
||||
client.memories.upload_file(
|
||||
client.documents.upload_file(
|
||||
file=Path("/path/to/file"),
|
||||
)
|
||||
```
|
||||
|
|
@ -146,7 +146,7 @@ client = Supermemory(
|
|||
)
|
||||
|
||||
# Or, configure per-request:
|
||||
client.with_options(max_retries=5).memories.add(
|
||||
client.with_options(max_retries=5).documents.add(
|
||||
content="This is a detailed article about machine learning concepts...",
|
||||
)
|
||||
```
|
||||
|
|
@ -171,7 +171,7 @@ client = Supermemory(
|
|||
)
|
||||
|
||||
# Override per-request:
|
||||
client.with_options(timeout=5.0).memories.add(
|
||||
client.with_options(timeout=5.0).documents.add(
|
||||
content="This is a detailed article about machine learning concepts...",
|
||||
)
|
||||
```
|
||||
|
|
@ -214,12 +214,12 @@ The "raw" Response object can be accessed by prefixing `.with_raw_response.` to
|
|||
from supermemory import Supermemory
|
||||
|
||||
client = Supermemory()
|
||||
response = client.memories.with_raw_response.add(
|
||||
response = client.documents.with_raw_response.add(
|
||||
content="This is a detailed article about machine learning concepts...",
|
||||
)
|
||||
print(response.headers.get('X-My-Header'))
|
||||
|
||||
memory = response.parse() # get the object that `memories.add()` would have returned
|
||||
memory = response.parse() # get the object that `documents.add()` would have returned
|
||||
print(memory.id)
|
||||
```
|
||||
|
||||
|
|
@ -234,7 +234,7 @@ The above interface eagerly reads the full response body when you make the reque
|
|||
To stream the response body, use `.with_streaming_response` instead, which requires a context manager and only reads the response body once you call `.read()`, `.text()`, `.json()`, `.iter_bytes()`, `.iter_text()`, `.iter_lines()` or `.parse()`. In the async client, these are async methods.
|
||||
|
||||
```python
|
||||
with client.memories.with_streaming_response.add(
|
||||
with client.documents.with_streaming_response.add(
|
||||
content="This is a detailed article about machine learning concepts...",
|
||||
) as response:
|
||||
print(response.headers.get("X-My-Header"))
|
||||
|
|
|
|||
|
|
@ -41,10 +41,10 @@ const client = new Supermemory({
|
|||
});
|
||||
|
||||
async function main() {
|
||||
const params: supermemory.MemoryAddParams = {
|
||||
const params: Supermemory.AddParams = {
|
||||
content: 'This is a detailed article about machine learning concepts...',
|
||||
};
|
||||
const response: supermemory.MemoryAddResponse = await client.add(params);
|
||||
const response: Supermemory.AddResponse = await client.add(params);
|
||||
}
|
||||
|
||||
main();
|
||||
|
|
@ -68,17 +68,17 @@ import Supermemory, { toFile } from 'supermemory';
|
|||
const client = new Supermemory();
|
||||
|
||||
// If you have access to Node `fs` we recommend using `fs.createReadStream()`:
|
||||
await client.memories.uploadFile({ file: fs.createReadStream('/path/to/file') });
|
||||
await client.documents.uploadFile({ file: fs.createReadStream('/path/to/file') });
|
||||
|
||||
// Or if you have the web `File` API you can pass a `File` instance:
|
||||
await client.memories.uploadFile({ file: new File(['my bytes'], 'file') });
|
||||
await client.documents.uploadFile({ file: new File(['my bytes'], 'file') });
|
||||
|
||||
// You can also pass a `fetch` `Response`:
|
||||
await client.memories.uploadFile({ file: await fetch('https://somesite/file') });
|
||||
await client.documents.uploadFile({ file: await fetch('https://somesite/file') });
|
||||
|
||||
// Finally, if none of the above are convenient, you can use our `toFile` helper:
|
||||
await client.memories.uploadFile({ file: await toFile(Buffer.from('my bytes'), 'file') });
|
||||
await client.memories.uploadFile({ file: await toFile(new Uint8Array([0, 1, 2]), 'file') });
|
||||
await client.documents.uploadFile({ file: await toFile(Buffer.from('my bytes'), 'file') });
|
||||
await client.documents.uploadFile({ file: await toFile(new Uint8Array([0, 1, 2]), 'file') });
|
||||
```
|
||||
|
||||
## Handling errors
|
||||
|
|
@ -90,7 +90,7 @@ a subclass of `APIError` will be thrown:
|
|||
|
||||
```ts
|
||||
async function main() {
|
||||
const response = await client.memories
|
||||
const response = await client.documents
|
||||
.add({ content: 'This is a detailed article about machine learning concepts...' })
|
||||
.catch(async (err) => {
|
||||
if (err instanceof supermemory.APIError) {
|
||||
|
|
@ -175,13 +175,13 @@ Unlike `.asResponse()` this method consumes the body, returning once it is parse
|
|||
```ts
|
||||
const client = new Supermemory();
|
||||
|
||||
const response = await client.memories
|
||||
const response = await client.documents
|
||||
.add({ content: 'This is a detailed article about machine learning concepts...' })
|
||||
.asResponse();
|
||||
console.debug(response.headers.get('X-My-Header'));
|
||||
console.debug(response.statusText); // access the underlying Response object
|
||||
|
||||
const { data: response, response: raw } = await client.memories
|
||||
const { data: response, response: raw } = await client.documents
|
||||
.add({ content: 'This is a detailed article about machine learning concepts...' })
|
||||
.withResponse();
|
||||
console.debug(raw.headers.get('X-My-Header'));
|
||||
|
|
|
|||
|
|
@ -105,20 +105,20 @@ Track specific document processing status.
|
|||
<CodeGroup>
|
||||
|
||||
```typescript Typescript
|
||||
const memory = await client.memories.get("doc_abc123");
|
||||
const memory = await client.documents.get("doc_abc123");
|
||||
|
||||
console.log(`Status: ${memory.status}`);
|
||||
|
||||
// Poll for completion
|
||||
while (memory.status !== 'done') {
|
||||
await new Promise(r => setTimeout(r, 2000));
|
||||
memory = await client.memories.get("doc_abc123");
|
||||
memory = await client.documents.get("doc_abc123");
|
||||
console.log(`Status: ${memory.status}`);
|
||||
}
|
||||
```
|
||||
|
||||
```python Python
|
||||
memory = client.memories.get("doc_abc123")
|
||||
memory = client.documents.get("doc_abc123")
|
||||
|
||||
print(f"Status: {memory['status']}")
|
||||
|
||||
|
|
@ -126,7 +126,7 @@ print(f"Status: {memory['status']}")
|
|||
import time
|
||||
while memory['status'] != 'done':
|
||||
time.sleep(2)
|
||||
memory = client.memories.get("doc_abc123")
|
||||
memory = client.documents.get("doc_abc123")
|
||||
print(f"Status: {memory['status']}")
|
||||
```
|
||||
|
||||
|
|
@ -178,7 +178,7 @@ async function waitForProcessing(documentId: string, maxWaitMs = 300000) {
|
|||
const pollInterval = 2000; // 2 seconds
|
||||
|
||||
while (Date.now() - startTime < maxWaitMs) {
|
||||
const doc = await client.memories.get(documentId);
|
||||
const doc = await client.documents.get(documentId);
|
||||
|
||||
if (doc.status === 'done') {
|
||||
return doc;
|
||||
|
|
@ -205,7 +205,7 @@ async function trackBatch(documentIds: string[]) {
|
|||
|
||||
// Initial check
|
||||
for (const id of documentIds) {
|
||||
const doc = await client.memories.get(id);
|
||||
const doc = await client.documents.get(id);
|
||||
statuses.set(id, doc.status);
|
||||
}
|
||||
|
||||
|
|
@ -215,7 +215,7 @@ async function trackBatch(documentIds: string[]) {
|
|||
|
||||
for (const id of documentIds) {
|
||||
if (statuses.get(id) !== 'done' && statuses.get(id) !== 'failed') {
|
||||
const doc = await client.memories.get(id);
|
||||
const doc = await client.documents.get(id);
|
||||
statuses.set(id, doc.status);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -200,7 +200,7 @@ results = client.search(
|
|||
```
|
||||
|
||||
```python Supermemory
|
||||
results = client.memories.search(
|
||||
results = client.documents.search(
|
||||
query="user preferences",
|
||||
container_tags=["user_alice"]
|
||||
)
|
||||
|
|
@ -219,7 +219,7 @@ memories = client.get_all(
|
|||
```
|
||||
|
||||
```python Supermemory
|
||||
memories = client.memories.list(
|
||||
memories = client.documents.list(
|
||||
container_tags=["user_alice"],
|
||||
limit=100
|
||||
)
|
||||
|
|
@ -236,7 +236,7 @@ client.delete(memory_id="mem_123")
|
|||
```
|
||||
|
||||
```python Supermemory
|
||||
client.memories.delete("mem_123")
|
||||
client.documents.delete("mem_123")
|
||||
```
|
||||
|
||||
</CodeGroup>
|
||||
|
|
|
|||
|
|
@ -111,7 +111,7 @@ memories = client.memory.get(session_id="user_123")
|
|||
```
|
||||
|
||||
```python Supermemory
|
||||
documents = client.memories.list({
|
||||
documents = client.documents.list({
|
||||
"containerTag": ["user_123"],
|
||||
"limit": 100
|
||||
})
|
||||
|
|
|
|||
|
|
@ -235,7 +235,7 @@ def verify_migration(api_key: str, expected_count: int):
|
|||
|
||||
try:
|
||||
# Check imported memories
|
||||
result = client.memories.list(container_tags=["imported_from_mem0"], limit=100)
|
||||
result = client.documents.list(container_tags=["imported_from_mem0"], limit=100)
|
||||
|
||||
total_imported = result["pagination"]["totalItems"]
|
||||
print(f"✅ Found {total_imported} imported memories in Supermemory")
|
||||
|
|
|
|||
|
|
@ -50,14 +50,18 @@ conversation = [
|
|||
# Get user profile + relevant memories for context
|
||||
profile = client.profile(container_tag=USER_ID, q=conversation[-1]["content"])
|
||||
|
||||
static = "\n".join(profile.profile.static)
|
||||
dynamic = "\n".join(profile.profile.dynamic)
|
||||
memories = "\n".join(r.content for r in profile.search_results.results)
|
||||
|
||||
context = f"""Static profile:
|
||||
{"\n".join(profile.profile.static)}
|
||||
{static}
|
||||
|
||||
Dynamic profile:
|
||||
{"\n".join(profile.profile.dynamic)}
|
||||
{dynamic}
|
||||
|
||||
Relevant memories:
|
||||
{"\n".join(r.content for r in profile.search_results.results)}"""
|
||||
{memories}"""
|
||||
|
||||
# Build messages with memory-enriched context
|
||||
messages = [{"role": "system", "content": f"User context:\n{context}"}, *conversation]
|
||||
|
|
|
|||
|
|
@ -20,7 +20,7 @@ Search through your memories and documents with a single API call.
|
|||
|
||||
const client = new Supermemory();
|
||||
|
||||
const results = await client.search({
|
||||
const results = await client.search.memories({
|
||||
q: "machine learning",
|
||||
containerTag: "user_123",
|
||||
searchMode: "hybrid",
|
||||
|
|
@ -28,7 +28,7 @@ Search through your memories and documents with a single API call.
|
|||
});
|
||||
|
||||
results.results.forEach(result => {
|
||||
console.log(result.content, result.similarity);
|
||||
console.log(result.memory || result.chunk, result.similarity);
|
||||
});
|
||||
```
|
||||
</Tab>
|
||||
|
|
@ -38,7 +38,7 @@ Search through your memories and documents with a single API call.
|
|||
|
||||
client = Supermemory()
|
||||
|
||||
results = client.search(
|
||||
results = client.search.memories(
|
||||
q="machine learning",
|
||||
container_tag="user_123",
|
||||
search_mode="hybrid",
|
||||
|
|
@ -46,7 +46,7 @@ Search through your memories and documents with a single API call.
|
|||
)
|
||||
|
||||
for result in results.results:
|
||||
print(result.content, result.similarity)
|
||||
print(result.memory or result.chunk, result.similarity)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="cURL">
|
||||
|
|
@ -70,15 +70,19 @@ Search through your memories and documents with a single API call.
|
|||
"results": [
|
||||
{
|
||||
"id": "mem_xyz",
|
||||
"content": "User is interested in machine learning for product recommendations",
|
||||
"memory": "User is interested in machine learning for product recommendations",
|
||||
"similarity": 0.91,
|
||||
"metadata": { "topic": "interests" }
|
||||
"metadata": { "topic": "interests" },
|
||||
"updatedAt": "2024-01-15T10:30:00.000Z",
|
||||
"version": 1
|
||||
},
|
||||
{
|
||||
"id": "chunk_abc",
|
||||
"content": "Machine learning enables personalized experiences at scale...",
|
||||
"chunk": "Machine learning enables personalized experiences at scale...",
|
||||
"similarity": 0.87,
|
||||
"metadata": { "source": "onboarding_doc" }
|
||||
"metadata": { "source": "onboarding_doc" },
|
||||
"updatedAt": "2024-01-14T09:15:00.000Z",
|
||||
"version": 1
|
||||
}
|
||||
],
|
||||
"timing": 92,
|
||||
|
|
@ -86,6 +90,10 @@ Search through your memories and documents with a single API call.
|
|||
}
|
||||
```
|
||||
|
||||
<Info>
|
||||
In hybrid mode, results contain either a `memory` field (extracted facts) or a `chunk` field (document content), depending on the source.
|
||||
</Info>
|
||||
|
||||
---
|
||||
|
||||
## Parameters
|
||||
|
|
@ -107,14 +115,14 @@ Search through your memories and documents with a single API call.
|
|||
|
||||
```typescript
|
||||
// Hybrid: memories + document chunks (recommended)
|
||||
await client.search({
|
||||
await client.search.memories({
|
||||
q: "quarterly goals",
|
||||
containerTag: "user_123",
|
||||
searchMode: "hybrid"
|
||||
});
|
||||
|
||||
// Memories only: just extracted facts
|
||||
await client.search({
|
||||
await client.search.memories({
|
||||
q: "user preferences",
|
||||
containerTag: "user_123",
|
||||
searchMode: "memories"
|
||||
|
|
@ -128,7 +136,7 @@ await client.search({
|
|||
Filter by `containerTag` to scope results to a user or project:
|
||||
|
||||
```typescript
|
||||
const results = await client.search({
|
||||
const results = await client.search.memories({
|
||||
q: "project updates",
|
||||
containerTag: "user_123",
|
||||
searchMode: "hybrid"
|
||||
|
|
@ -138,7 +146,7 @@ const results = await client.search({
|
|||
Use `filters` for metadata-based filtering:
|
||||
|
||||
```typescript
|
||||
const results = await client.search({
|
||||
const results = await client.search.memories({
|
||||
q: "meeting notes",
|
||||
containerTag: "user_123",
|
||||
filters: {
|
||||
|
|
@ -169,7 +177,7 @@ const results = await client.search({
|
|||
Re-scores results for better relevance. Adds ~100ms latency.
|
||||
|
||||
```typescript
|
||||
const results = await client.search({
|
||||
const results = await client.search.memories({
|
||||
q: "complex technical question",
|
||||
containerTag: "user_123",
|
||||
rerank: true
|
||||
|
|
@ -182,10 +190,10 @@ Control result quality vs quantity:
|
|||
|
||||
```typescript
|
||||
// Broad search — more results
|
||||
await client.search({ q: "...", threshold: 0.3 });
|
||||
await client.search.memories({ q: "...", threshold: 0.3 });
|
||||
|
||||
// Precise search — fewer, better results
|
||||
await client.search({ q: "...", threshold: 0.8 });
|
||||
await client.search.memories({ q: "...", threshold: 0.8 });
|
||||
```
|
||||
|
||||
---
|
||||
|
|
@ -196,7 +204,7 @@ Optimal configuration for conversational AI:
|
|||
|
||||
```typescript
|
||||
async function getContext(userId: string, message: string) {
|
||||
const results = await client.search({
|
||||
const results = await client.search.memories({
|
||||
q: message,
|
||||
containerTag: userId,
|
||||
searchMode: "hybrid",
|
||||
|
|
@ -205,7 +213,7 @@ async function getContext(userId: string, message: string) {
|
|||
});
|
||||
|
||||
return results.results
|
||||
.map(r => r.content)
|
||||
.map(r => r.memory || r.chunk)
|
||||
.join('\n\n');
|
||||
}
|
||||
```
|
||||
|
|
@ -214,10 +222,12 @@ async function getContext(userId: string, message: string) {
|
|||
```typescript
|
||||
interface SearchResult {
|
||||
id: string;
|
||||
content: string; // Memory or chunk content
|
||||
memory?: string; // Present for memory results
|
||||
chunk?: string; // Present for document chunk results
|
||||
similarity: number; // 0-1
|
||||
metadata: object | null;
|
||||
updatedAt: string;
|
||||
version: number;
|
||||
}
|
||||
|
||||
interface SearchResponse {
|
||||
|
|
|
|||
|
|
@ -345,7 +345,7 @@ This is useful when:
|
|||
|
||||
```typescript TypeScript
|
||||
// Get a specific document by ID
|
||||
const document = await client.memories.get("doc_abc123");
|
||||
const document = await client.documents.get("doc_abc123");
|
||||
|
||||
console.log(document.content); // Full document content
|
||||
console.log(document.status); // Processing status
|
||||
|
|
@ -355,7 +355,7 @@ console.log(document.summary); // AI-generated summary
|
|||
|
||||
```python Python
|
||||
# Get a specific document by ID
|
||||
document = client.memories.get("doc_abc123")
|
||||
document = client.documents.get("doc_abc123")
|
||||
|
||||
print(document.content) # Full document content
|
||||
print(document.status) # Processing status
|
||||
|
|
|
|||
|
|
@ -12,14 +12,18 @@ conversation = [
|
|||
# Get user profile + relevant memories for context
|
||||
profile = client.profile(container_tag=USER_ID, q=conversation[-1]["content"])
|
||||
|
||||
static = "\n".join(profile.profile.static)
|
||||
dynamic = "\n".join(profile.profile.dynamic)
|
||||
memories = "\n".join(r.content for r in profile.search_results.results)
|
||||
|
||||
context = f"""Static profile:
|
||||
{ "\n".join(profile.profile.static)}
|
||||
{static}
|
||||
|
||||
Dynamic profile:
|
||||
{"\n".join(profile.profile.dynamic)}
|
||||
{dynamic}
|
||||
|
||||
Relevant memories:
|
||||
{"\n".join(r.content for r in profile.search_results.results)}"""
|
||||
{memories}"""
|
||||
|
||||
# Build messages with memory-enriched context
|
||||
messages = [{"role": "system", "content": f"User context:\n{context}"}, *conversation]
|
||||
|
|
|
|||
|
|
@ -20,7 +20,7 @@ const client = new Supermemory({
|
|||
});
|
||||
|
||||
// Update by memory ID
|
||||
const updated = await client.memories.update('memory_id_123', {
|
||||
const updated = await client.documents.update('memory_id_123', {
|
||||
content: 'Updated content here',
|
||||
metadata: { version: 2, updated: true }
|
||||
});
|
||||
|
|
@ -36,7 +36,7 @@ import os
|
|||
client = Supermemory(api_key=os.environ.get("SUPERMEMORY_API_KEY"))
|
||||
|
||||
# Update by memory ID
|
||||
updated = client.memories.update(
|
||||
updated = client.documents.update(
|
||||
'memory_id_123',
|
||||
content='Updated content here',
|
||||
metadata={'version': 2, 'updated': True}
|
||||
|
|
@ -165,18 +165,18 @@ Delete individual memories by their ID. This is a permanent hard delete with no
|
|||
|
||||
```typescript Typescript
|
||||
// Hard delete - permanently removes memory
|
||||
await client.memories.delete('memory_id_123');
|
||||
await client.documents.delete('memory_id_123');
|
||||
console.log('Memory deleted successfully');
|
||||
```
|
||||
|
||||
```python Python
|
||||
# Hard delete - permanently removes memory
|
||||
client.memories.delete('memory_id_123')
|
||||
client.documents.delete('memory_id_123')
|
||||
print('Memory deleted successfully')
|
||||
|
||||
# Error handling for single delete
|
||||
try:
|
||||
client.memories.delete('memory_id_123')
|
||||
client.documents.delete('memory_id_123')
|
||||
print('Delete successful')
|
||||
except NotFoundError:
|
||||
print('Memory not found or already deleted')
|
||||
|
|
@ -204,7 +204,7 @@ Delete multiple memories at once by providing an array of memory IDs. Maximum of
|
|||
|
||||
```typescript Typescript
|
||||
// Bulk delete by memory IDs
|
||||
const result = await client.memories.bulkDelete({
|
||||
const result = await client.documents.deleteBulk({
|
||||
ids: [
|
||||
'memory_id_1',
|
||||
'memory_id_2',
|
||||
|
|
@ -225,7 +225,7 @@ console.log('Bulk delete result:', result);
|
|||
|
||||
```python Python
|
||||
# Bulk delete by memory IDs
|
||||
result = client.memories.bulk_delete(
|
||||
result = client.documents.delete_bulk(
|
||||
ids=[
|
||||
'memory_id_1',
|
||||
'memory_id_2',
|
||||
|
|
@ -276,7 +276,7 @@ Delete all memories within specific container tags. This is useful for cleaning
|
|||
|
||||
```typescript Typescript
|
||||
// Delete all memories in specific container tags
|
||||
const result = await client.memories.bulkDelete({
|
||||
const result = await client.documents.deleteBulk({
|
||||
containerTags: ['user-123', 'project-old', 'archived-content']
|
||||
});
|
||||
|
||||
|
|
@ -290,7 +290,7 @@ console.log('Bulk delete by tags result:', result);
|
|||
|
||||
```python Python
|
||||
# Delete all memories in specific container tags
|
||||
result = client.memories.bulk_delete(
|
||||
result = client.documents.delete_bulk(
|
||||
container_tags=['user-123', 'project-old', 'archived-content']
|
||||
)
|
||||
|
||||
|
|
@ -329,7 +329,7 @@ For applications requiring audit trails or recovery mechanisms, implement soft d
|
|||
|
||||
```typescript Typescript
|
||||
// Soft delete pattern using metadata
|
||||
await client.memories.update('memory_id', {
|
||||
await client.documents.update('memory_id', {
|
||||
metadata: {
|
||||
deleted: true,
|
||||
deletedAt: new Date().toISOString(),
|
||||
|
|
@ -338,40 +338,40 @@ await client.memories.update('memory_id', {
|
|||
});
|
||||
|
||||
// Filter out deleted memories in searches
|
||||
const activeMemories = await client.memories.list({
|
||||
filters: JSON.stringify({
|
||||
const activeMemories = await client.documents.list({
|
||||
filters: {
|
||||
AND: [
|
||||
{ key: "deleted", value: "true", negate: true }
|
||||
]
|
||||
})
|
||||
}
|
||||
});
|
||||
|
||||
console.log('Active memories:', activeMemories.results.length);
|
||||
console.log('Active memories:', activeMemories.memories.length);
|
||||
```
|
||||
|
||||
```python Python
|
||||
from datetime import datetime
|
||||
import json
|
||||
|
||||
# Soft delete pattern using metadata
|
||||
client.memories.update('memory_id', {
|
||||
'metadata': {
|
||||
client.documents.update(
|
||||
'memory_id',
|
||||
metadata={
|
||||
'deleted': True,
|
||||
'deletedAt': datetime.now().isoformat(),
|
||||
'deletedBy': 'user_123'
|
||||
}
|
||||
})
|
||||
)
|
||||
|
||||
# Filter out deleted memories
|
||||
active_memories = client.memories.list(
|
||||
filters=json.dumps({
|
||||
active_memories = client.documents.list(
|
||||
filters={
|
||||
"AND": [
|
||||
{"key": "deleted", "value": "true", "negate": True}
|
||||
]
|
||||
})
|
||||
}
|
||||
)
|
||||
|
||||
print(f'Active memories: {len(active_memories.results)}')
|
||||
print(f'Active memories: {len(active_memories.memories)}')
|
||||
```
|
||||
|
||||
```bash cURL
|
||||
|
|
@ -407,7 +407,7 @@ async function batchDeleteMemories(memoryIds: string[], batchSize = 100) {
|
|||
console.log(`Processing batch ${Math.floor(i/batchSize) + 1} of ${Math.ceil(memoryIds.length/batchSize)}`);
|
||||
|
||||
try {
|
||||
const result = await client.memories.bulkDelete({ ids: batch });
|
||||
const result = await client.documents.deleteBulk({ ids: batch });
|
||||
results.push(result);
|
||||
|
||||
// Brief delay between batches to avoid rate limiting
|
||||
|
|
@ -446,7 +446,7 @@ def batch_delete_memories(memory_ids, batch_size=100):
|
|||
print(f'Processing batch {batch_num} of {total_batches}')
|
||||
|
||||
try:
|
||||
result = client.memories.bulk_delete(ids=batch)
|
||||
result = client.documents.delete_bulk(ids=batch)
|
||||
results.append(result)
|
||||
|
||||
# Brief delay between batches to avoid rate limiting
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue