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This tutorial installs the published Python SDK, runs the shipped standalone minimal profile, and shows how to customize the same dsh profile from your own program.
git clone https://github.com/deepseek-ai/deepseek-harness.git
cd deepseek-harness
python -m venv .venv
. .venv/bin/activate
python -m pip install deepseek-harness-sdk
git clone https://github.com/deepseek-ai/deepseek-harness.git
Set-Location deepseek-harness
py -3.10 -m venv .venv
.venv\Scripts\Activate.ps1
python -m pip install deepseek-harness-sdk
The installation includes a matching native runtime wheel and the dsh command. Normal SDK execution needs no system Node.js. Repository contributors who build the artifacts should use the Python contributor workflow.
Export the credential and, when needed, a compatible proxy endpoint:
export DEEPSEEK_API_KEY=sk-your-key-here
# export DEEPSEEK_BASE_URL=http://127.0.0.1:8000/v1
$env:DEEPSEEK_API_KEY = "sk-your-key-here"
# $env:DEEPSEEK_BASE_URL = "http://127.0.0.1:8000/v1"
Run one task with explicit workspace and home paths:
python python/sdk/examples/minimal.py \
--workspace /absolute/path/to/disposable-workspace \
--dsh-home /absolute/path/to/example-dsh-home \
--session-id example-001 \
"Inspect the repository and fix the failing tests."
python python/sdk/examples/minimal.py `
--workspace C:\work\disposable-workspace `
--dsh-home C:\work\example-dsh-home `
--session-id example-001 `
"Inspect the repository and fix the failing tests."
The script prints the final assistant response. The selected home receives the generated sdk-minimal profile, installed plugins, and uncompressed JSONL session logs under sessions/. The example and SDK never silently read ~/.dsh.
from pathlib import Path
from deepseek_harness import DeepSeekHarness
workspace = Path("/absolute/path/to/disposable-workspace").resolve()
dsh_home = Path("/absolute/path/to/example-dsh-home").resolve()
with DeepSeekHarness(
provider="deepseek-official",
model="deepseek-v4-flash",
max_tokens=49_152,
cwd=str(workspace),
dsh_home=str(dsh_home),
profile="sdk-minimal",
) as harness:
result = harness.run(
"Inspect the repository and fix the failing tests.",
session_id="example-001",
)
print(result.final_response)
The SDK starts the bundled dsh --profile sdk-minimal process lazily and reuses it until context-manager exit. The profile, its persistent patch, the home patch, and any ordered patches tuple form the application configuration. There is no separate Python runtime bin or complete-config option.
Use dsh plugin for dependencies and bundle layers that should persist in this home:
export DSH_HOME=/absolute/path/to/example-dsh-home
dsh --profile sdk-minimal --dump-default-config >/dev/null
dsh plugin --profile sdk-minimal add file:/absolute/path/to/my-plugin-bundle
$env:DSH_HOME = "C:\work\example-dsh-home"
dsh --profile sdk-minimal --dump-default-config | Out-Null
dsh plugin --profile sdk-minimal add file:C:/work/my-plugin-bundle
The first command initializes the shipped standalone profile. The second forwards package management to pnpm, then records any installed package that exports a dsh.bundle layer. Install pnpm only for this management command; launching the installed SDK does not need it. Edit $DSH_HOME/profiles/sdk-minimal/cordis.patch.yml for persistent row changes, or pass patch files from Python for per-launch changes.
Another profile is valid when it includes @deepseek-ai/dsh-sdk-app or another JSON-RPC server row. Missing server rows, unresolved plugins, and invalid patches fail during startup instead of falling back to another composition.
str_replace_editorThe bundled runtime includes str_replace_editor, but sdk-minimal omits it from the default Cordis tree. To use it, save this configuration as editor.patch.yml; insert adds both the editor and the filesystem provider that the minimal profile lacks:
- insert:
- id: fs-local
name: '@deepseek-ai/dsh-fs-local'
config:
cwd: !!js process.cwd()
- id: tool-str-replace-editor
name: '@deepseek-ai/dsh-tool-str-replace-editor'
Pass patches=("/absolute/path/to/editor.patch.yml",) when constructing DeepSeekHarness(profile="sdk-minimal", ...), or put the patch in $DSH_HOME/profiles/sdk-minimal/cordis.patch.yml for persistent configuration. On the next runtime launch, model requests include str_replace_editor beside the persistent shell. The local filesystem provider uses the runtime working directory for relative paths; like the minimal shell, it does not confine access to that directory. For the standard sdk profile, insert only the editor row so it uses the existing filesystem provider and policies.
| Property | Value |
|---|---|
| System prompt | DSH_SYSTEM_PROMPT, falling back to You are a helpful software engineer assistant. |
Model in minimal.py |
--model, then DSH_MODEL, then deepseek-v4-flash |
| Model-facing tool | Persistent bash on Linux/macOS or pwsh on Windows |
| Shell timeout | 300 seconds |
| Runtime context and compaction | Absent |
| Session persistence | Uncompressed JSONL under <dsh_home>/sessions |
The profile's sole bundle inserts the complete tree over an empty root and does not include dsh-base; later base-profile tools therefore cannot appear implicitly. It contains the SDK protocol, one environment-configured DeepSeek adapter, local execution, and persistence, while filesystem tools, settings, managed credentials, telemetry, Web tools, subagents, local instruction discovery, and compaction are absent. It pins danger-full-access, so the platform-selected persistent shell can modify any path visible to the runtime; use a disposable checkout or container.
The installed wheel still packages the full web profile and frontend assets. Run dsh web against an explicit DSH_HOME when a Python SDK deployment also needs the browser application; web is a separate CLI application and cannot serve a Python SDK client.
Use a fresh home when profiles, plugins, credentials, settings, and sessions must be isolated. Use a fresh session id for independent work; reuse a harness, home, and id only to continue the same durable conversation and session-owned resources.
The bundle reference owns the exact tree, and the example reference owns the runnable program. The Python SDK reference covers lifecycle, results, notifications, and low-level behavior; the dsh CLI reference covers profile layering.