Retrieve prior decisions and working context from Nowledge Mem in DeepChat, and save useful lessons for future work. It also supports requested conversation exports and connection troubleshooting while keeping operations within the selected server and Space.
中文简介正在准备中。当前显示英语简介。
Use Nowledge Mem for cross-tool startup context, recall of prior decisions, durable learnings, explicit conversation saving, and connection diagnosis. Use only the connection selected for this DeepChat agent or session.
安装前可以查看交给 AI 代理的指令内容。
Use the enabled nowledge-mem-connection MCP tools for the server configured in Plugins >
Nowledge Mem. Keep that destination, returned identity and Space for the whole operation. Never mix results from
different Mem servers or silently retry on another server.
At the beginning of related work, read Context Bundle once (read_context_bundle, source_app
deepchat) for identity, scope, rules and Working Memory. Use read_working_memory only when the
bundle tool is unavailable. An empty Working Memory is a successful empty result.
For continuation, reviews, regressions and prior decisions, search memory_search with a narrow
query and limit 5, then fetch the relevant exact IDs. Search before adding a duplicate. Distinguish
recorded facts from proposals, and keep scope returned by the server. A graph is optional; only
show one when it enforces the same identity and Space as retrieval.
Save a concise durable learning with memory_add or update an existing memory only when it is
useful beyond this conversation. State what was saved. Do not save speculative conclusions as
facts. Save complete conversations only when the user requests it: use DeepChat's conversation
export to Nowledge Mem, which uses the same verified connection as MCP. Do not
claim an export happened without a successful acknowledgement.
For configuration or failed access, direct the user to Plugins > Nowledge Mem. The host verifies
REST and MCP and stores credentials securely. Report the failing connection and operation; do not
switch to localhost after a remote error. Do not ask for keys in chat, invoke unscoped nmem, edit
~/.nowledge-mem/config.json, read local Mem database files, or install another connector. This
plugin uses DeepChat's HTTP client and does not require the CLI.
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Add an LLM provider to DeepChat by choosing a suitable API connection method, updating authentication and model configuration, and making focused source changes with tests for the affected behavior.
中文简介正在准备中。当前显示英语简介。
Create original generative art with p5.js, using code to produce patterns and motion. Receive a written artistic concept and an interactive HTML viewer with adjustable parameters, reproducible random variations, seed navigation, and PNG downloads.
中文简介正在准备中。当前显示英语简介。
Review code for readability, maintainability, security, and performance. Receive an overview, issues grouped by severity, concrete improvements with code examples, and positive feedback on parts of the implementation that work well.
中文简介正在准备中。当前显示英语简介。
Operate desktop applications through DeepChat's built-in Computer Use tools. Inspect windows, click controls, enter text, use menus, and arrange windows, checking the visible result after each action.
中文简介正在准备中。当前显示英语简介。
Use DeepChat's bundled command-line interface to compare models, generate media, transcribe audio, and extract text from images. Also inspect runtime status, artifact metadata, public settings, installed Skills, and MCP connections to external tools.
中文简介正在准备中。当前显示英语简介。
Build third-party tools to inspect, extract, migrate, or analyze DeepChat's local settings and conversations. Work through data locations, database encryption, and table relationships while favoring read-only copies and redacted output.
中文简介正在准备中。当前显示英语简介。