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Deepvista Chat

通过 deepvista 命令行与 DeepVista AI 智能体对话：+send 发送消息并以 NDJSON 流式返回回复，sessions/get 读取会话列表与元数据，delete 删除会话。发送消息属写操作，可能触发智能体创建卡片、联网检索等动作，需用户确认；认证、配置档案与全局参数依赖 deepvista-shared 技能。

jingconan
jingconan
热度 28.32
最近更新 2026-05-20 03:35:49
分类：协作依赖：代码执行 / 第三方 API应用场景：笔记整理 / 任务管理 / 工作流

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add deepvista-chat
Metadata
name
deepvista-chat
description
DeepVista Chat: Send messages to the AI agent and manage chat sessions.
metadata
{"openclaw":{"category":"service","requires":{"bins":["deepvista"],"skills":["deepvista-shared"]},"install":[{"kind":"uv","package":"deepvista-cli","bins":["deepvista"]}],"homepage":"https://cli.deepvista.ai","cliHelp":"deepvista chat --help"}}

Chat

PREREQUISITE: Read deepvista-shared for auth, profiles, and global flags.

Chat with the DeepVista AI agent. The agent can search your knowledge base, create cards, run web searches, and execute tools.

Commands

sessions

deepvista chat sessions [--limit N] [--offset N] [--search "query"]

Read-only — list chat sessions.

get

deepvista chat get <chat_id>

Read-only — returns session metadata (id, summary, created_at, status). Full message history is not returned by this endpoint.

delete

deepvista chat delete <chat_id>

[!CAUTION] Destructive command — confirm with user before executing.

+send

deepvista chat +send "your message" [--chat-id ID] [--new]

[!CAUTION] This is a write command — creates/updates chat sessions and the agent may create cards, search the web, and take other actions. Confirm with the user before executing.

Flag Required Default Description
<message> Yes — Your message to the agent
--chat-id No — Continue an existing chat session
--new No false Force start a new conversation

Output is NDJSON — one JSON object per line, streamed as the agent responds.

SSE Event Format

+send streams events in this structure. Parse page_delta events to get the agent's response text:

{"type": "chat_session", "id": "abc123", ...}
{"type": "page", "page": {"user_instruction": "...", ...}}
{"type": "page_delta", "parts": [
  {"type": "tool_result", "output": "partial response text...", "done": false}
], "page_index": 0}
{"type": "page_delta", "parts": [
  {"type": "tool_result", "output": "full response text", "done": true, "options": ["follow-up 1", "follow-up 2"]}
]}

Key fields:

  • type: "chat_session" — first event; contains the id of the session
  • type: "page_delta" — carries the streamed response
  • parts[].type: "tool_result" — the agent's text; output is the full accumulated text so far (not an incremental delta)
  • parts[].done: true — final chunk; options may contain suggested follow-up prompts

Examples

# Send a message (new conversation)
deepvista chat +send "What are my open tasks?" --new

# Continue an existing conversation
deepvista chat +send "Tell me more about the first one" --chat-id abc123

# Ask the agent to create a note
deepvista chat +send "Create a note summarizing our ML strategy discussion"

# List recent sessions
deepvista chat sessions --limit 5

# Search sessions by summary
deepvista chat sessions --search "roadmap"

See Also