db-gpt
Use DB-GPT 0.8.1 as an agentic AI data platform: install and configure provider profiles, operate its CLI and services, build agents and AWEL flows, ingest…
Skill by VectorSpaceLab
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/vectorspacelab-db-gpt
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: backend, data, ml
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/db-gpt
What's inside
- Skill name
db-gpt- Description
- Use DB-GPT 0.8.1 as an agentic AI data platform: install and configure provider profiles, operate its CLI and services, build agents and AWEL flows, ingest and retrieve data with RAG, call client/API surfaces, and execute code through explicitly bounded sandbox runtimes.
- License
- MIT
- Metadata
- disco-role: operating
- Instructions
- 74 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (39)
- SKILL.md
- configuration.md · references/
- installation.md · references/
- repo-provenance.md · references/
- repo-routing-metadata.json · references/
- troubleshooting.md · references/
- package_import_smoke.py · scripts/
- SKILL.md · sub-skills/agents-and-awel/
- agent-api-reference.md · sub-skills/agents-and-awel/references/
- awel-workflows.md · sub-skills/agents-and-awel/references/
- skills-and-tools.md · sub-skills/agents-and-awel/references/
- troubleshooting.md · sub-skills/agents-and-awel/references/
- awel_smoke.py · sub-skills/agents-and-awel/scripts/
- SKILL.md · sub-skills/apis-client-and-sandbox/
- client-api-reference.md · sub-skills/apis-client-and-sandbox/references/
- sandbox-workflows.md · sub-skills/apis-client-and-sandbox/references/
- service-endpoints.md · sub-skills/apis-client-and-sandbox/references/
- troubleshooting.md · sub-skills/apis-client-and-sandbox/references/
- sandbox_cli_wrapper.py · sub-skills/apis-client-and-sandbox/scripts/
- SKILL.md · sub-skills/data-and-rag/
- connectors-and-stores.md · sub-skills/data-and-rag/references/
- data-formats.md · sub-skills/data-and-rag/references/
- rag-api-reference.md · sub-skills/data-and-rag/references/
- troubleshooting.md · sub-skills/data-and-rag/references/
- workflows.md · sub-skills/data-and-rag/references/
- local_rag_smoke.py · sub-skills/data-and-rag/scripts/
- SKILL.md · sub-skills/models-and-serving/
- backends.md · sub-skills/models-and-serving/references/
- model-api-reference.md · sub-skills/models-and-serving/references/
- provider-and-backend-matrix.md · sub-skills/models-and-serving/references/
- serving-workflows.md · sub-skills/models-and-serving/references/
- troubleshooting.md · sub-skills/models-and-serving/references/
- model_config_check.py · sub-skills/models-and-serving/scripts/
- SKILL.md · sub-skills/setup-and-cli/
- cli-reference.md · sub-skills/setup-and-cli/references/
- configuration.md · sub-skills/setup-and-cli/references/
- installation-and-profiles.md · sub-skills/setup-and-cli/references/
- troubleshooting.md · sub-skills/setup-and-cli/references/
- inspect_config.py · sub-skills/setup-and-cli/scripts/
SKILL.md (first lines)
# DB-GPT
Use this repo skill when a task names **DB-GPT**, `dbgpt`, `dbgpt-app`,
`dbgpt-client`, `dbgpt-ext`, `dbgpt-serve`, or `dbgpt-sandbox`, or asks for an
agentic data assistant that combines models, SQL/code, files, knowledge bases,
RAG, skills, AWEL workflows, APIs, or sandboxed execution.
## Choose the route
- **Install, profiles, TOML configuration, `dbgpt` command routing, web start/stop,
knowledge/repo/app/trace/migration CLI** → [setup-and-cli](sub-skills/setup-and-cli/SKILL.md).
- **LLM/embedding/reranker providers, model TOML, controller/worker/API-server,
local models, CUDA, vLLM, llama.cpp, Ollama, or serving** →
[models-and-serving](sub-skills/models-and-serving/SKILL.md).
- **Agents, tools, skills, middleware, teams, memory/context, AWEL/DAG/flow, or
HTTP-triggered workflow construction** → [agents-and-awel](sub-skills/agents-and-awel/SKILL.md).
- **Local documents, datasource schemas, chunking, embeddings, retrieval,
knowledge indexing, vector/full-text/graph stores, or RAG** →
[data-and-rag](sub-skills/data-and-rag/SKILL.md).
- **Python client, HTTP CRUD/API routes, files/apps/flows, service integration,
or sandbox execution** →
[apis-client-and-sandbox](sub-skills/apis-client-and-sandbox/SKILL.md).
When a request spans routes, establish the runtime boundary in this order:
**configuration/provider → data or workflow construction → API/service execution**.
Do not claim that a parsed config, imported package, registry entry, or health
endpoint proves a provider, model, vector store, database, or sandbox is usable.
## Baseline installation and inspection
For the recorded 0.8.1 baseline, use a clean Python 3.10+ environment and
install the public package without relying on a source checkout:
```bash
uv pip install 'dbgpt-app==0.8.1'
dbgpt --version
python -c "import dbgpt, dbgpt_app, dbgpt_client, dbgpt_ext; print('imports ok')"
```
Use `pip` if `uv` is unavailable. Add only the extras needed by the route:
provider, RAG/parser, vector-store, database, local-model, or sandbox variants.
Read [installation](references/installation.md) before adding optional
backends, and [configuration](references/configuration.md) before writing a
profile or TOML file. The bundled [package smoke script](scripts/package_import_smoke.py)
is a read-only import/version check; it never starts a server or contacts a provider.
## Cross-cutting operating rules
1. Keep credentials in environment variables or the user's secret manager. Do
not print resolved TOML, API keys, passwords, bearer tokens, or provider
responses containing secrets.
2. Separate local/import/config validation from live provider, model, database,
vector, graph, API, and sandbox checks. Record the exact boundary and skipped
prerequisites.
3. Prefer tiny deterministic fixtures and disposable paths. Do not run a
network installer, download a model, mutate a database, launch a daemon, or
execute untrusted code as an implicit smoke test.
4. Use the installed package's live Click help and signatures when a flag or
object is version-sensitive. In particular, model command discovery may
query a controller even while rendering help; an unreachable controller is
not a successful deployment.
5. Default DB-GPT's web API is commonly `http://localhost:5670`; confirm the
actual profile, API version, route prefix, and authentication policy before
making client calls. Close async clients and clean temporary uploads/sessions.
6. Treat local sandbox execution as a weaker, explicitly opted-in boundary, not
container isolation. Container runtime/image availability and network policy
must be verified separately.
Read [cross-cutting troubleshooting](references/troubleshooting.md) for
installation/import, optional dependency, configuration, service, backend, and
safety failures. Source/version context is recorded in
[repo provenance](references/repo-provenance.md); it is not a runtime dependency.From VectorSpaceLab/AREX-Skill, MIT.
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Signals
- Stars
- 341
- Forks
- 26
- Open issues
- 0
- Last commit (this folder)
- Aug 28, 2026 (2 months ago)
- Last release
- Sep 2, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/VectorSpaceLab/AREX-Skill
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
db-gpt skill. Agent Mart. https://agentmart.dev/skills/vectorspacelab-db-gpt (last updated 2026-10-24)