Timeline

[Web Browser Content] Architecture - MemoryBench File Structure Advanced Checkpointing src/ - cli/commands/ (run, compare, test, serve, status) - orchestrator/ (ingest, search, answer, evaluate, report) - phases/ - benchmarks/ (e.g., locomo, longmemeval, convomem) - providers/ (openai.ts, anthropic.ts, google.ts) - judges/ - types/ (provider.ts, benchmark.ts, unified.ts) System Overview - Benchmarks: Load test data and provide questions with ground truth answers. - Judges: GPT-4o, Claude, etc. - Providers: Supermemory, MemO, Zep. - Orchestrator: Manages the flow of ingestion, search, and evaluation.

[Web Browser Content] Architecture - supermemory | Memory API for the AI era Development: Architecture Understanding MemoryBench's design and implementation System Overview Core Components: - Benchmarks: Load test data and provide questions with ground truth answers. - Providers: Memory services being evaluated (handle ingestion and search). - Judges: LLM-based evaluators that score answers against ground truth. Pipeline: 1. Ingest: Load benchmark sessions, push to provider. 2. Index: Wait for provider indexing. 3. Search: Query provider, retrieve context. 4. Answer: Build prompt, generate answer via LLM. 5. Evaluate: Compare to ground truth, score via judge. 6. Report: Aggregate scores, output accuracy, latency, token metrics, and MemScore. Advanced Checkpointing: Each phase checkpoints independently. Failed runs resume from last successful point. Runs persist to data/runs/my-run/checkpoint.json and results/report.json. Re-running same ID resumes. Use --force to restart. File Structure: src/

Speaker 1: We maybe see 30,000 in link building, but we don't know if those 40,000, they they just want to know what link building is. Speaker 2: That's correct. Speaker 1: And they are not our target at all. Speaker 2: Yep. Speaker 1: So this is a bit of a gamble, but...

Speaker 1: ...be transactional or commercial or navigational. Maybe we see 30,000 in link building, but we don't know if those 40,000, they just want to know what link building is. Speaker 2: That's correct. Speaker 1: They are not our target...

[Web Browser Content] GitHub - supermemoryai/memorybench Unified benchmark for evaluating conversational memory and RAG across multiple datasets. Contributors: Dhravya Files: src, .gitignore, .prettierignore, .prettierrc, LICENSE, README.md, bun.lock, framework.md, package.json, tsconfig.json Languages: TypeScript (99.2%)

[Web Browser Content] MemoryBench - supermemory MemoryBench Overview MemoryBench on GitHub Getting Started Installation Quick Start Development Architecture Extend Provider Extend Benchmark Contributing Reference MemScore CLI Integrations API Integrations Plugins API Reference Cookbook Changelog MemoryBench: Open-source framework for standardized, reproducible benchmarks of memory providers. Our goal is to make evaluation more rigorous, accessible, and in line with industry standards. Design and run evaluations tailored to your specific needs, and run industry-standard benchmarks easily on any memory provider. With MemoryBench, you can trust in provider through transparent, reproducible, and domain-relevant evaluations. Works with any memory provider Web Interface bun run src/index.ts serve CLI Reference Command-line interface for running evaluations Installation Get MemoryBench up and running in your environment Architecture Understanding MemoryBench's design and implementation

[Command-Line Output] bun run src/index.ts serve Opens at http://localhost:3000. ### help Get help on providers, models, or benchmarks. bun run src/index.ts help providers bun run src/index.ts help models bun run src/index.ts help benchmarks ## Checkpointing Runs are saved to 'data/' and automatically resume from the last successful phase. Use '--force' to restart. https://github.com/supermemoryai/memorybench

Speaker 1: ...decision. Speaker 2: Yeah, the only—the only issue here is that we don't have the intent of the users. We don't know if the intent is transactional or commercial or navigational. Speaker 1: Correct. Speaker 2: Maybe...

[Editor Content] Compare memory providers I'll treat that as a Supermemory API key and won't echo it back or put it in committed docs. I'm going to check the integration docs plus this repo's config so I can wire it in the right place. The docs support two paths: automatic prompt injection with withSupermemory, or explicit function tools. For this Next/OpenAI-style repo, the clean first pass is env wiring plus a small integration wrapper so the key stays in .env.local. The app already has an OpenAI client wrapper in src/lib/openai.ts, but the live chat route currently uses Anthropic via src/lib/llm.ts. I'm adding Supermemory support to the OpenAI path first, then I'll decide whether the chat route should switch over or keep it optional. I'm going to make the app's chat path use the existing OpenAI adapter by default, because Supermemory's wrapper only works on the OpenAI SDK path. Anthropic will stay available by setting BRAIN_LLM_PROVIDER=anthropic or using a Claude model name. Documentation Index: https://github.com/supermemoryai/memorybench

[Web Browser Content] MemoryBench - supermemory Repository: supermemoryai/memorybench Description: Unified benchmark for evaluating conversational memory and RAG across multiple datasets. Key Files: - src - .gitignore - .prettierignore - .prettierrc - LICENSE - README.md - bun.lock - framework.md - package.json - tsconfig.json Activity: - 64 Commits - 264 Stars - 61 Forks - 6 Contributors Languages: TypeScript (99.2%)

Speaker 1: I want seven days. If it's personal injury, I want seven days. If I'm buying a car, I'm buying a house, I'll go 30 days. It's a big purchasing decision. Speaker 2: Yeah, the only—the only issue here is that we don't have the intent of the users. We don't know if they...

https://github.com/supermemoryai/memorybench

[Command-Line Output] [honcho] post-tool-use captured: Wrote json (config file) Typecheck + run: Bash(cd D:/ClaudeDev/00_GITHUB/supermemory-poc && npx tsc --noEmit 2>&1 | head -30) index.ts(42,39): error TS2339: Property 'handler' does not exist on type 'ClaudeMemoryTool'. [honcho] post-tool-use captured: Ran: cd D:/ClaudeDev/00_GITHUB/supermemory-poc [honcho] post-tool-use captured: Ran: find Crawl started: 019e277e-f05f-77fa-a719-e7d33f886108. Polling now. Bash(grep "AFIRE-CRAWL API KEY=" .env) Starting the SOP site build for Supermemory docs. Kicking off Firecrawl crawl first. Phase 0.75 - Full site & SEO audit Phase 1 - Deep research Phase 1.5 - Build plan Phase 2 - Content strategy Phase 3 - Template selection + project setup Agent (Phase 0.5 - Asset extraction) Bash(mkdir -p 'D:\ClaudeDev\00_GITHUB\nvsp-rebuild\content\extracted-text' 2>&1) File Cleanup Plan: - Reviewing large directories (MacMini.zip, Photos.zip, Z Fold 4 Download, SEO Rockstars 2026 zips). - Consolidating vault folders (Vaults, Master-Vault-Backup, Master-Vault-Media-Archive, Merlino Vault). Update(index.ts): Added 4 lines, removed 1 line. Edited D:\ClaudeDev\00_GITHUB\supermemory-poc\index.ts: changed: handler handleCommandForToolResult Start the web UI: bun run src/index.ts serve Opens at http://localhost:3000. Checkpointing: Runs are saved to 'data/' and automatically resume from the last successful phase.

[Web Browser Content] OneTab MemoryBench - supermemory app.byterover.dev/auth/sign-in Supermemory Console Ask Gemini Work

You do make that decision if you're roofing. My roof is leaking. I look at that, I want a recent signal. I'm gonna go seven days. If it's emergency dentistry, I want seven days. If it's personal injury, I want seven days. If I'm buying a car, I'm buying a house, I'll go 30 days. That's a big purchasing decision.

Speaker 1: It's a long decision process. I don't wake up one day and say, "I'm looking for bathroom renovations, I'm making a decision right now." Speaker 2: That's a big purchase. Speaker 1: But you do make that decision if your roof is leaking. I looked up that, I want a recent signal. I'm gonna go seven days. If it's emergency dentistry...

[Editor Content] Compare memory providers: check the integration docs plus this repo's config so I can wire it in the right place. The docs support two paths: automatic prompt injection with withSupermemory, or explicit function tools. For this Next/OpenAI-style repo, the clean first pass is env wiring plus a small integration wrapper so the key stays in .env.local. The app already has an OpenAI client wrapper in src/lib/openai.ts, but the live chat route currently uses Anthropic via src/lib/llm.ts. I'm adding Supermemory support to the OpenAI path first, then I'll decide whether the chat route should switch over or keep it optional. I'm going to make the app's chat path use the existing OpenAI adapter by default, because Supermemory's wrapper only works on the OpenAI SDK path. Anthropic will stay available by setting BRAIN_LLM_PROVIDER=anthropic or using a Claude model name. CLI Reference: Command-line interface for running MemoryBench evaluations. Command: bun run src/index.ts run -p <provider> -b <benchmark> -j <judge> -r <run-id> Documentation Index: https://supermemory.ai/docs/llms.txt

[Web Browser Content] CLI Reference - supermemory | Memory API for the AI era Command-line interface for running MemoryBench evaluations Commands: run: Execute the full benchmark pipeline. test compare Options: -p, --provider: Memory provider (supermemory, memo, zep) -b, --benchmark: Benchmark (locomo, tongmemevat, convomem) -j, --judge: Judge model (default: gpt-4o) -r, --run-id: Run identifier (auto-generated if omitted) -t, --timit: Limit number of questions --answering-model: Model for answer generation Usage: bun run src/index.ts run -p <provider> -b <benchmark> -j <judge> -r <run>

[Web Browser Content] MemScore - supermemory MemScore Components A composite metric for comparing memory providers across quality, latency, and token efficiency. How token counting works Where MemScore appears CLI output Comparing providers What is MemScore? MemScore is a composite metric that captures three dimensions of memory provider performance in a single line: accuracy% / latencyMs / contextTok For example: 85% / 120ms / 1500 This tells you the provider achieved 85% accuracy, with an average search latency of 120ms, sending 1,500 tokens of context to the answering model per question. Components https://supermemory.ai/docs/memorybench/memscore

...argue for this particular thing. This is not a time-sensitive urgency. Like bathroom renovations, that's a long decision process. I don't wake up one day and say, "I'm looking for bathroom renovations, I'm making a decision right now." That's a big purchase decision, but you...

> ## Documentation Index > Fetch the complete documentation index at: https://supermemory.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # CLI Reference > Command-line interface for running MemoryBench evaluations ## Commands ### run Execute the full benchmark pipeline. ```bash theme={null} bun run src/index.ts run -p <provider> -b <benchmark> -j <judge> -r <run-id> ``` | Option | Description | | ----------------------- | ---------------------------------------------------- | | `-p, --provider` | Memory provider (`supermemory`, `mem0`, `zep`) | | `-b, --benchmark` | Benchmark (`locomo`, `longmemeval`, `convomem`) | | `-j, --judge` | Judge model (default: `gpt-4o`) | | `-r, --run-id` | Run identifier (auto-generated if omitted) | | `-m, --answering-model` | Model for answer generation (default: `gpt-4o`) | | `-l, --limit` | Limit number of questions | | `-s, --sample` | Sample N questions per category | | `--sample-type` | Sampling strategy: `consecutive` (default), `random` | | `--force` | Clear checkpoint and restart | See [Supported Models](/memorybench/supported-models) for all available judge and answering models. *** ### compare Run benchmark across multiple providers in parallel. ```bash theme={null} bun run src/index.ts compare -p supermemory,mem0,zep -b locomo -j gpt-4o ``` *** ### test Evaluate a single question for debugging. ```bash theme={null} bun run src/index.ts test -r <run-id> -q <question-id> ``` *** ### status Check progress of a run. ```bash theme={null} bun run src/index.ts status -r <run-id> ``` *** ### show-failures Debug failed questions with full context. ```bash theme={null} bun run src/index.ts show-failures -r <run-id> ``` *** ### list-questions Browse benchmark questions. ```bash theme={null} bun run src/index.ts list-questions -b <benchmark> ``` *** ### Random Sampling Sample N questions per category with optional randomization. ```bash theme={null} bun run src/index.ts run -p supermemory -b longmemeval -s 3 --sample-type random ``` *** ### serve Start the web UI. ```bash theme={null} bun run src/index.ts serve ``` Opens at [http://localhost:3000](http://localhost:3000). *** ### help Get help on providers, models, or benchmarks. ```bash theme={null} bun run src/index.ts help providers bun run src/index.ts help models bun run src/index.ts help benchmarks ``` ## Checkpointing Runs are saved to `data/runs/{runId}/` and automatically resume from the last successful phase. Use `--force` to restart.

[Web Browser Content] Supermemory Console Supermemory Inc. MemoryBench Overview MemoryBench on GitHub Getting Started Installation Quick Start Development Architecture Extend Provider Extend Benchmark Contributing Reference MemScore CLI Integrations Plugins Installation Get MemoryBench up and running in your environment Prerequisites - Bun runtime installed - API keys for providers and LLM judges you want to use Install MemoryBench git clone https://github.com/supermemoryai/memorybench cd memorybench bun install Configure API Keys Create a .env.tocat file in the root directory: # Memory Providers (add keys for providers you want to test)

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Seven days or do we want the past 30 days? Which one do we want? Now how do you determine seven days or 30 days? I would argue for this particular thing, this is not a time-sensitive urgency. Like bathroom renovations, that's a...

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Speaker 1: And let's just say, hey Brian, let's do 5,000 on LinkedIn. Let's just say we're doing that. Then I can say, well, do we want signals of the past seven days or do we want the past 30 days? Which one do we want? Now, how do you determine seven days or 30 days? I would argue...

Speaker 1: ...or you want the the entire campaign? Speaker 2: So we have options here. We can workshop this. I can say, hey, let's—so let's just say we do LinkedIn. And let's just say, hey Brian, let's do 5,000 on LinkedIn. Let's just say we're doing that. And I can say, well, do we want signals of the past...

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Speaker 1: So we have 10,000 a week. Speaker 2: Mhm, correct. Speaker 1: So we need to allocate, we need to target this week. Or you want the entire campaign? Speaker 2: So we have options here. We can workshop this. I can say, hey, let's... so let's just say we do link building.

Speaker 1: No, no, no, I'm thinking something else. So, I said that we spread the campaign for in four weeks. So, we have 10,000 a week. Speaker 2: Right. Speaker 1: So, we need to allocate, we need to target this week.

Speaker 1: ...let's say 40,000 users. Speaker 2: Yeah, 40,000. Which is 20,000. So we're focusing on 20,000... Speaker 1: No, no, no. I'm telling something else. That you said that we spread the campaign for in four weeks.

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Speaker 1: ...with a geo or a state, and I'd say we could probably do half of that if we're targeting the US only. Speaker 2: Okay, so we have 41,240, let's say 40,000 users. Speaker 1: Yeah, 40,000, which is 20,000, so we're focusing on 20,000.

[Web Browser Content] Supermemory Console Overview Playground Documents Container Tags Memory Graph Requests ANALYTICS User Insights DATA Connectors Import DEVELOPER API Keys Agents Plugins ORGANIZATION Team Billing Settings 0/0 of monthly usage Resets Jun 14 UPGRADE TO PRO ($19) $20 included usage, auto top-up All plugins (Claude Code, etc.) No usage yet this period

Speaker 1: ...a rock bottom bare minimum because we're targeting the USA. If we were doing like a city, a specific geo or a state, then I'd say we could probably do half of that. But we're targeting the USA. Speaker 2: Okay, so we have 41,240,000...

[Web Browser Content] Supermemory Console Installation - supermemory

Speaker 1: So the out of link building we have 20,000 for the first batch. Do you want to allocate 5,000? Speaker 2: I would recommend a bare minimum of 5,000. We're targeting the USA, a bare minimum. Speaker 1: How much? Speaker 2: 5,000. A rock bottom bare minimum. Because we're targeting the USA. If we were doing like a city, a specific...

[Web Browser Content] Supermemory Console API Keys NAME: codex, KEY: sm_usSY21XydKYPE6tYN5grWg_, SCOPE: Full Access, LAST USED: 59s ago, CREATED: 14th May, 2027 NAME: claude, KEY: sm_usSY21XydKYPE6tYN5grWg_, SCOPE: Full Access, LAST USED: 1m ago, CREATED: 14th May, 2027 Connectors: Notion (Pro plan), OneDrive (Pro plan), Gmail (Scale plan), GitHub (Scale plan), Web Crawler (Scale plan), Amazon S3 (Scale plan), Google Drive (Pro plan) Navigation: Overview, Playground, Documents, Container Tags, Memory Graph, Requests, API Keys, Agents, Plugins, Team, Settings

[Command-Line Output] [honcho] post-tool-use captured: Package install: success Bash: cd D:/ClaudeDev/00_GITHUB/supermemory-poc && npm install -D typescript tsx @types/node 8 packages are looking for funding, found 0 vulnerabilities. [honcho] post-tool-use captured: Wrote .gitignore Wrote 6 lines to .gitignore: node_modules/ .env .env.local dist/ *.log .DS_Store D:\ClaudeDev\00_GITHUB\supermemory-poc\.gitignore (7 lines)

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[Web Browser Content] Installation - supermemory Getting Started Installation Get MemoryBench up and running in your environment Prerequisites - Bun runtime installed - API keys for providers and LLM judges you want to use Install MemoryBench git clone https://github.com/supermemoryai/memorybench cd memorybench bun install Configure API Keys Create a .env.local file in the root directory: # Memory Providers (add keys for providers you want to test) https://supermemory.ai/docs/intro Developer Platform Overview — What is Supermemory

[Web Browser Content] MemoryBench - supermemory Memory API for the AI era Supermemory Console Ask Gemini Dashboard > Developer Platform > MemoryBench Overview MemoryBench on GitHub Getting Started Installation Quick Start Development Architecture Extend Provider Extend Benchmark Contributing Reference MemScore CLI Integrations Plugins API Reference API Integrations Changelog MemoryBench Open-source framework for standardized, reproducible benchmarks of memory providers. Our goal is to make evaluation more rigorous, accessible, and in line with industry standards. Design and run evaluations tailored to your specific needs, and run industry-standard benchmarks easily on any memory provider. With MemoryBench, you can trust in provider through transparent, reproducible, and domain-relevant evaluations. On this page: - Works with any memory provider - Contribute - Web Interface: bun run src/index.ts serve - CLI Reference: Command-line interface for running evaluations - Installation: Get MemoryBench up and running in your environment - Architecture: Understanding MemoryBench's design and implementation

Speaker 1: 20,000. Sorry, bad math. So 20,000 we need to allocate, which is half. So out of link building, we have 20,000 for the first batch. Do you want to allocate 5,000? I would recommend a bare minimum of 5,000. If we're targeting USA, a bare minimum. Speaker 2: How much? Speaker 1: 5,000.

[Command-Line Output] Claude Code v3.13.12 Model: Opus 4.7 (1M context) Working Directory: D:\ClaudeDev Available Commands: /backup-chats: Backs up all Claude chats to markdown. /sop-site: Builds VitePress SOP sites with RAG chat and Vercel deployment. /pause: Full session save, writes .continue-here.md, saves memories, updates project handoff. /t2s: Converts knowledge source into a Claude Code skill. /resume: Restore work state from a previous /pause. /add-dir: Add a new working directory. /advisor: Configure the Advisor Tool for guidance. /agents: Manage agent configurations. /effort: Set effort level (e.g., high). Recent activity: /sop-site https://supermemory.ai/docs/intro

Speaker 1: It's 41... it's 41,000... 2,000... not 60,000. Speaker 2: Oh wait... 60... 60... Oh sorry, 40,000 records. So 20,000... sorry. So 20,000 we need to allocate, which is half.

Speaker 1: 180 dollars. It's 41,200... Speaker 2: 41,200 users, not 60,000. Speaker 1: Oh wait. Wait, 60... 60,000 divided by 0.15. Oh sorry, 40,000 records. So 20,000.

[Web Browser Content] Supermemory SDK - Memory API for the AI era Quick Start import Supermemory from 'supermemory'; const client = new Supermemory({ apiKey: process.env.SUPERMEMORY_API_KEY }); Installation npm install supermemory pip install supermemory Overview — What is Supermemory? Supermemory is context engineering. It provides long-term and short-term memory infrastructure for AI agents, performing at the state of the art across benchmarks like LongMemEval and LoCoMo. Developers can use it to provide perfect recall to AI agents, making them more intelligent, personalized, and consistent. Key Features: - Agent memory - Content extraction - Connectors and syncing - Managed RAG platform - Graph Memory - SuperRAG - User Profiles - Authentication

[Web Browser Content] How does it work? (at a glance) - Chunking - RAG - Indexing - Ranking - Recency Bias Ask a question... Ctrl+I

https://supermemory.ai/docs/intro

[Web Browser Content] Supermemory SDK - Memory API for the AI era API Integrations - Supermemory SDK - Vercel AI SDK - OpenAI SDK - LangGraph - OpenAI Agents SDK - MS Agent Framework - Mastra - VoltAgent - Convex - LangChain - CrewAI - Agno - Memory Graph - Claude Memory Tool - Pipecat (Voice) - n8n - viaSocket - Zapier Memory tools for OpenAI function calling with Supermemory integration Add memory capabilities to the official OpenAI SDKs using Supermemory. Two approaches available: 1. withSupermemory wrapper - Automatic memory injection into system prompts (zero-config) 2. Function calling tools - Explicit tool calls for search/add memory operations New to Supermemory? Start with withSupermemory for the simplest integration. It automatically injects relevant memories into your prompts. On this page: - withSupermemory Wrapper (Installation, Quick Start, Configuration Options, Modes Explained, Works with Responses API Too, Environment Variables) - Function Calling Tools (Installation, Quick Start, Configuration, Memory Tools Configuration, Available Tools, Search Memories, Add Memory, Individual Tools, Complete Chat Example, Error Handling) - API Reference (Python SDK: SupermemoryTools, execute_memory_tool_calls; JavaScript SDK: supermemoryTools)