- Published the v2.0.0 docs and a 1.4 → 2.0 migration guide so existing users have a clear upgrade path.
- Updated the four integration pages (AI SDK, OpenAI, Mastra, VoltAgent) to reflect v2 defaults and link to the migration guide.
- Added a short explainer on the two required fields (containerTag, customId) so new users aren't blocked at first integration.
**`withSupermemory`** **(AI SDK)**
- **`skipMemoryOnError`** **defaults to** **`true`**. memory errors/timeouts log and the model runs on the **original** prompt unless you set `skipMemoryOnError: false`.
- **Pre-LLM** **`/v4/profile`** **is aborted after 5s** via `AbortSigna`
**Docs**
- `packages/tools/README.md`, **`apps/docs/integrations/ai-sdk.md`**
### TL;DR
Added Python SDK for integrating Supermemory with Cartesia Line voice agents, enabling persistent memory capabilities.
### What changed?
Created a new Python SDK package (`supermemory_cartesia`) that provides:
- `SupermemoryCartesiaAgent` wrapper class that enhances Cartesia Line agents with memory capabilities
- Memory retrieval and storage functionality that integrates with the Supermemory API
- Utility functions for memory formatting, deduplication, and time formatting
- Custom exception classes for error handling
- Comprehensive documentation and type hints
The implementation includes:
- Memory enrichment for user queries
- Automatic storage of conversation history
- Configurable memory retrieval modes (profile, query, full)
- Background processing to avoid blocking the main conversation flow
### How to test?
```python
from supermemory_cartesia import SupermemoryCartesiaAgent
from line.llm_agent import LlmAgent, LlmConfig
import os
# Create base LLM agent
base_agent = LlmAgent(
model="gemini/gemini-2.5-flash-preview-09-2025",
config=LlmConfig(
system_prompt="You are a helpful assistant.",
introduction="Hello!"
)
)
# Wrap with Supermemory
memory_agent = SupermemoryCartesiaAgent(
agent=base_agent,
api_key=os.getenv("SUPERMEMORY_API_KEY"),
user_id="user-123",
)
# Use memory_agent in your Cartesia Line application
```
### Why make this change?
This SDK enables Cartesia Line voice agents to maintain persistent memory across conversations, enhancing user experience by:
1. Providing contextual awareness of past interactions
2. Remembering user preferences and important information
3. Reducing repetition in conversations
4. Creating more personalized and natural voice interactions
The integration is designed to be lightweight and non-blocking, ensuring that memory operations don't impact the responsiveness of voice interactions.
- Switch to infinite query with viewport-triggered pagination (loads more when user zooms out 3x past node bounds)
- Remove maxNodes cap so all data renders
- Remove background color and dot pattern from graph
- Make document-memory edges light grey
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
## Summary
- Fixed memory graph stuck on "Loading graph data..." caused by field name mismatch after package rewrite (`memoryEntries` vs `memories`, `type` vs `documentType`)
- Improved MCP app UI to match console-v2 design: golden derives edges (#FBBF24), edge glow pass, node hover effects, dot mode at low zoom, vertical controls with keyboard shortcuts, expandable legend
- Synced local `memory-graph` edgeDerives constant with published npm version
## Test plan
- [ ] Run `cd apps/mcp && bun run dev`, connect via Claude Desktop
- [ ] Verify graph renders with golden derives edges and blue dashed extends edges
- [ ] Verify node hover/selection glow effects
- [ ] Verify Fit (Z), Center (C), zoom (+/-) keyboard shortcuts
- [ ] Verify legend expands/collapses
- redirect to login when session is gone instead of blank screen
- show cached username while session restores so header doesn't flicker
- cleaned up redundant type casts and unused vars
