> ## Documentation Index > Fetch the complete documentation index at: https://docs.evermind.ai/llms.txt > Use this file to discover all available pages before exploring further. # Product Updates #### Request Log Improvements: * Find requests faster with request ID filtering, custom time-range search, and pagination. * Click any entry to view its status, latency, and error messages. #### API v0 Retirement: * The v0 API is now fully replaced by v1. Calls to v0 endpoints will return an error. * Existing data is migrated automatically, so users already on v1 are unaffected. * See the "API Reference (Cloud)" for the migration guide. #### Streamlined Onboarding: * **Simpler, friendlier setup**\ A more streamlined onboarding experience that's friendlier for users of any technical level. * **Helpful tips while you wait**\ While your memory space is being set up, we share helpful tips tailored to you to get you started. * **Refreshed look**\ A cleaner, fully branded onboarding experience. #### Console UI/UX Refresh: * **Zero-setup onboarding**\ **Copy a single prompt, paste it into any agent, and you're done.** No manual install, no API key creation, all automated. * **Redesigned Get Started page**\ Switch between Prompt (for agents) and SDK setup modes, with ready-to-use `add` / `get` / `search` code samples for both Agent and User memory. * **Clearer navigation**\ Reorganized sidebar tabs so you can find what you need faster. #### Performance Improvmenets: * System-level engineering optimizations for improved speed and stability #### New Features & Updates: * **API path set to v1**\ The EverOS API has been upgraded to v1 with improved structure and new capabilities. See the "API Reference" for full details and migration guide * **Multimodal storage and retrieval (mRAG)**\ Store and query images, documents, PDFs and web contents alongside text * **Self-evolving agent memory**\ Agents can now build and refine memory through Cases and Skills primitives * **Memory Bank**\ Visualize and manage user, group, and agent memory from a single console * **Interactive Playground**\ Explore and test memory APIs directly in the console, no setup required #### New Features & Updates: * Dashboard UI updates * Performance improvements * Bug fixes and reliability improvements #### New Features & Updates: * Message timestamp validation #### Bug Fixes: * Fixed dashboard API usage chart data anomaly #### New Features & Updates: * Refactored Get Memories and Search Memories API parameters * Dashboard UI interaction improvements * Added Google and GitHub third-party login support * Restricted available LLM providers and models on cloud platform * Bug fixes This is a non-backwards-compatible change. Update your API request parameters immediately. #### New Features & Updates: * **API path set to v0**\ All endpoints are served under `/api/v0/`. Requests to any other path are not supported. #### Cloud SDK package renamed to `everos-cloud`: The Cloud Python SDK is now published as **`everos-cloud`**. Existing installations are unaffected; new installs should use the updated package name. ```bash theme={null} pip install everos-cloud ``` #### New Features & Updates: * **v1 API support**\ SDK updated to align with EverOS API v1; all endpoints are now accessible via the client.v1 namespace * **Multimodal storage and retrieval (mRAG)**\ Added multimodal support to memories.add(), enabling ingestion of images, PDFs, documents, and web content alongside text * **Self-evolving agent memory**\ Introduced Cases & Skills APIs to support structured storage and retrieval of self-evolving agent memory * **Async client**\ Added AsyncEverOS client with async/await support, with optional aiohttp backend for improved concurrency #### Bug Fixes * Fixed group\_ids parameter parsing error ```bash theme={null} pip install --upgrade evermemos ``` #### New Features & Updates: * **Core Memory Operation** * Updated memory types enum values * Search now accepts a list of group IDs * Get memories uses page-based pagination * **LLM Custom Settings** * Available provider: openrouter * Available models: qwen/qwen3-235b-a22b-2507 (recommended), openai/gpt-4.1-mini This is a non-backwards-compatible change. Update your SDK immediately. ```bash theme={null} pip install --upgrade evermemos ``` #### EverOS Python SDK v0.3.11 is now available: * Please upgrade to the latest version, as v0.3.10 and earlier are not compatible. #### Bug Fixes * **Disk usage growth**\ Fixed an issue where index fragment merges could fail, causing disk usage to grow rapidly without being reclaimed. ```bash theme={null} pip install --upgrade everos ``` #### Bug Fixes * **Agent search reliability**\ Fixed an issue where agentic search could become unavailable in certain cases. ```bash theme={null} pip install --upgrade everos ``` #### Benchmarks and Search Quality EverOS OSS v1.1.1 is a quality release focused on reproducible benchmarks and improved search accuracy. * **LoCoMo benchmark runner**\ Reproduce EverOS memory benchmark results yourself with the new runner under [`benchmarks/`](https://github.com/EverMind-AI/EverOS/tree/main/benchmarks): TOML configuration, staged ingestion / search / answer / judge phases, and result artifacts. See [`benchmarks/README.md`](https://github.com/EverMind-AI/EverOS/blob/main/benchmarks/README.md) to get started. * **Improved hybrid search**\ Heap-driven lazy expansion and global top-N competition raise retrieval quality, with stable LoCoMo scores around 91% for hybrid search and 93% for agentic search. * **Python 3.12 and 3.13 support**\ CI coverage now includes Python 3.12 and 3.13. #### Bug Fixes * Concurrent Knowledge cascade upserts now use an atomic insert-or-update path * The OpenAPI application version stays in sync with the package version * Profile middleware re-raises inner handler exceptions instead of swallowing them * Reduced unnecessary LanceDB optimize I/O by throttling cascade optimize calls ```bash theme={null} pip install --upgrade everos ``` #### Knowledge Wiki and Reflection EverOS OSS v1.1.0 adds two major capabilities: a **Knowledge Wiki** that turns uploaded documents into searchable memory, and **Reflection** that consolidates scattered memories into clean, coherent narratives. #### Knowledge Wiki A third memory track alongside user and agent memory: upload documents (PDF, DOCX, Markdown, and more) and EverOS turns them into a searchable topic library. * **Progressive L0 → L1 → L2 structure**\ An LLM extracts each document into a category → document → topic hierarchy, so agents drill down on demand. * **Deterministic classification**\ Auto-sorted into an editable taxonomy of 20 built-in categories, predictable and overridable. * **Hybrid search, human-readable storage**\ Keyword, vector, or hybrid retrieval, with every document stored as editable Markdown and the original preserved. #### Reflection An offline background process that merges fragmented, overlapping memories into one coherent narrative. * **Cleaner memory over time**\ Related episodes merge into a single chronological narrative, resolving stale and contradictory fragments by keeping the latest state. * **Originals are never lost**\ Replaced memories are soft-archived rather than deleted, and stay fully traceable on disk. * **Off by default, you stay in control**\ Enable in `ome.toml`; runs on a weekly schedule and never touches the live conversation path. #### Getting Started ```bash theme={null} pip install --upgrade everos ``` See [Knowledge Wiki](/open-source/wiki) and [Reflection](/open-source/reflection) for full guides. #### Security release A path-traversal vulnerability in the memory-ingestion endpoint (`POST /api/v1/memory/add`) has been fixed. **All v1.0.0 users should upgrade.** * **`sender_id` path-safety validation** — `sender_id` now carries the same path-safety guard as `app_id` / `project_id`: a character whitelist plus rejection of `.` / `..`. The whitelist admits `@` and `+`, so email-style and plus-addressed identifiers still work. * **Defense-in-depth write containment** — the Markdown writer now rejects any write that resolves outside the configured memory root, before any filesystem access (covering both the write and the append read-modify-write paths). * **Severity:** High — unauthorized arbitrary `.md` file write on affected versions (≤ 1.0.0). No workaround other than upgrading. ```bash theme={null} pip install --upgrade everos ``` #### Initial Release — Agent-First Memory System EverOS OSS v1.0.0 is an agent-first, self-hosted memory system designed for full local deployment. Install with a single command — no Docker, no external databases, no infrastructure to manage. #### Markdown-First Storage * **Memory as plain Markdown files**\ Every memory record lives as a human-readable `.md` file on disk. Read, edit, version with Git, or browse in Obsidian — the data is fully yours. What you see is what is stored. * **Auditable and user-controlled**\ Memory files can be inspected and corrected directly without going through an API. Full data sovereignty. * **Lightweight embedded stack**\ Markdown (truth) + SQLite (state) + LanceDB (index). All retrieval — vector search, BM25 keyword, and scalar filtering — runs locally. Wipe `.index/` and the daemon rebuilds everything from the Markdown alone. #### Memory Classification * **Three memory tracks** — User Memory, Agent Memory, and Wiki Memory (coming soon) — organized by who owns the memory: the user, the agent, or shared world knowledge * **Multi-granularity coexistence** — episodes, atomic facts, foresight, and user profile exist side by side; the system selects the right granularity at retrieval time * **Independent memory scoping** — memory owner (`user_id` / `agent_id`), `app_id`, `project_id`, and `session_id` are orthogonal dimensions; add and search by any combination #### Self-Evolving Agent Memory * **Experience loop** — every agent execution is recorded as a case; cases are periodically clustered and distilled into reusable skills * **The system gets smarter with use** — skills generalize from individual traces into structured, retrievable knowledge about how to approach a class of task #### Online and Offline Memory Strategies * **Online strategy** — real-time memory ingestion and boundary detection during active sessions * **Offline strategy (OME)** — an in-process async engine that derives atomic facts, foresight, profile updates, and agent skills from accumulated episodes in the background * Each stage runs with configurable prompts and models #### Multimodal Support * Ingest and extract memories from: `text`, `image`, `audio`, `doc`, `pdf`, `html`, `email` * Multimodal content is processed alongside text through the same extraction pipeline #### Getting Started ```bash theme={null} pip install everos everos init # generate .env config everos server start ``` See the [OSS Quickstart](/open-source/quickstart) for a full walkthrough.