deepseek-agent 0.4.0

Developer-focused DeepSeek command line tools

DeepSeek CLI

This CLI is open source at https://github.com/PDFSage/deepseek_cli – collaborators and maintainers are welcome! Submit ideas, issues, or pull requests to help the project grow.

https://pypi.org/project/deepseek-agent/

Developer-focused command line tools for working with DeepSeek models. The CLI packages both an interactive chat shell and an agentic coding assistant with repository-aware tooling, plus configuration helpers and transcript logging.

Features

• Agent mode (deepseek agent) orchestrates tool-aware coding sessions with the DeepSeek API, optional read-only mode, transcripts, and workspace controls.
• Auto-detects likely project test commands and reminds the agent to run them, keeping changes validated against the repo's real workflows.
• Chat mode (deepseek chat) supports single-response or interactive conversations with streaming output and transcript capture.
• Completions mode (deepseek completions) mirrors Codex-style code/text completions with optional streaming renderers and file output.
• Embeddings mode (deepseek embeddings) batches text snippets and renders vectors as JSON, tabular previews, or plain values for quick inspection.
• Models view (deepseek models) enumerates the available DeepSeek API models with rich filtering or JSON export for automation.
• Config mode (deepseek config) manages stored defaults while respecting environment variable overrides.
• Interactive mode now launches a colourful Rich-powered shell that surfaces / and @ command shortcuts, streams the agent's thought process, and lets you update the stored API key without leaving the session.
• Ships as a Python package with an executable entry point and Homebrew formula for distribution flexibility.

Requirements

• Python 3.9 or newer.
• A DeepSeek API key exported as DEEPSEEK_API_KEY or stored via deepseek config.
• pip 23+ is recommended. Create a virtual environment for isolated installs.

Installation

From PyPI (recommended once released)

python -m pip install --upgrade pip
python -m pip install deepseek-agent

To update later, run python -m pip install --upgrade deepseek-agent.

From GitHub

Install the latest commit directly from GitHub:

python -m pip install "git+https://github.com/PDFSage/deepseek_cli.git@main"

Specify a tag (for example v0.2.0) to pin a release:

python -m pip install "git+https://github.com/PDFSage/deepseek_cli.git@v0.2.0"

From a local clone

git clone https://github.com/PDFSage/deepseek_cli.git
cd deepseek_cli
python -m venv .venv
source .venv/bin/activate  # On Windows use: .venv\\Scripts\\activate
python -m pip install --upgrade pip
python -m pip install -e .  # or `python -m pip install .` for a standard install

The editable install (-e) keeps the CLI synced with local source changes while developing.

Configuration

The CLI resolves settings in the following order:

1. Command line flags (--api-key, --base-url, --model, etc.).
2. Environment variables: DEEPSEEK_API_KEY, DEEPSEEK_BASE_URL, DEEPSEEK_MODEL, DEEPSEEK_SYSTEM_PROMPT, DEEPSEEK_CHAT_MODEL, DEEPSEEK_COMPLETION_MODEL, DEEPSEEK_EMBEDDING_MODEL, DEEPSEEK_CHAT_STREAM_STYLE.
3. Stored configuration file at ~/.config/deepseek-cli/config.json.

Helpful commands:

deepseek config init        # Guided prompt to store your API key
deepseek config show        # Display the current configuration (API key redacted)
deepseek config show --raw  # Show the API key in plain text
deepseek config set model deepseek-reasoner  # Update an individual field
deepseek config set completion_model deepseek-coder
deepseek config set chat_stream_style markdown
deepseek config unset model

If the config directory is unwritable, fall back to environment variables.

Usage

Interactive agent (default)

Running deepseek with no arguments launches the interactive coding agent, now presented through a colourful Rich-powered shell. A command palette is displayed on start so you can see the available /, @, or : shortcuts at a glance (for example @workspace, @model, @read-only, @transcript, @help, and @api). Exit with @quit or Ctrl+C. Each request runs as soon as you press Enter—include follow-up guidance in your initial prompt. The assistant appends internal follow-ups that run automated tests and regression checks until they succeed or a clear justification is provided. Use @global on when you need to edit files outside the active workspace. During execution the shell streams the agent's thought process prefixed with ▌, so you can follow what tools are being invoked in real time. Tool outputs are still truncated if they exceed the configured limits; narrow the scope or request additional reads for more detail.

If no API key is detected, the CLI now prompts you to paste one on launch and safely stores it. You can update the stored key at any time with @api or via deepseek config set api_key.

Verify installation

deepseek --version
# or use the legacy alias if preferred
deepseek-cli --version

Get help for any subcommand:

deepseek --help

Chat mode

deepseek chat "Summarise the last commit"

deepseek chat --interactive --model deepseek-reasoner \
  --transcript ~/Desktop/session.jsonl

• --no-stream disables live token streaming.
• --temperature, --top-p, and --max-tokens mirror the OpenAI Chat Completions API.
• --stream-style swaps between plain, markdown, or rich streaming renderers (defaults to the stored configuration).
• Provide --transcript to log each exchange to JSONL for later review.

Completions mode

deepseek completions "def fib(n):" --max-tokens 128

deepseek completions --input-file snippet.py --stream-style rich --output completion.txt

• Matches Codex-style behaviour with --stream-style support and optional file-backed prompts (--input-file).
• --stop may be supplied multiple times to register stop sequences.
• Pipe prompts via stdin when omitting the positional prompt.

Embeddings mode

deepseek embeddings "vectorize me" "and me"

deepseek embeddings --input-file sentences.txt --format json --output embeddings.json

• Outputs tabular previews by default, with optional JSON (--format json) or whitespace-delimited vectors (--format plain).
• Supply repeated positional text values, a newline-delimited file, or stdin.
• --show-dimensions reveals the embedding length alongside previews.

Model listing

deepseek models
deepseek models --filter coder --limit 5
deepseek models --json > models.json

• Displays a rich table of available models, mirroring the Gemini/OpenAI/Claude CLIs for quick discovery.

Agent mode

deepseek agent "Refactor the HTTP client" \
  --workspace ~/code/project --max-steps 30 --transcript transcript.jsonl

• The agent uses repository-aware tools: list directories, read/write files, apply patches, run shell commands, and search text.
• Additional integrations now include a Python REPL tool and a lightweight HTTP client for fetching external resources during reasoning.
• Pass --global to permit edits outside the workspace root when you need system-wide changes.
• The agent automatically watches for regressions, replans on the fly, and fixes issues before finishing.
• Tool outputs are truncated to keep prompts within context limits; refine commands or request additional detail if necessary.
• Add --follow-up "Also add tests" for additional prompts.
• Use --read-only to prevent write operations and --quiet to suppress progress logs.

Transcripts and workspaces

• Relative transcript paths under agent mode are resolved within the selected workspace.
• Chat transcripts default to ~/.config/deepseek-cli/transcripts/ when a file name (not path) is supplied.

Legacy shim

Running python deepseek_agentic_cli.py prints a compatibility notice and forwards the call to deepseek agent, so existing automation keeps working.

Publishing to PyPI

1. Update the version in pyproject.toml and commit your changes.
2. Remove old build artifacts:

   rm -rf build dist *.egg-info
   

3. Install packaging tooling:

   python -m pip install --upgrade build twine
   

4. Build the source and wheel distributions:

   python -m build
   

5. Verify the archives:

   python -m twine check dist/*
   

6. Upload to TestPyPI (optional but recommended):

   python -m twine upload --repository testpypi dist/*
   

7. Upload to PyPI:

   python -m twine upload dist/*
   

After publishing, users can install with pip install deepseek-agent.

Development

• python -m deepseek_cli --version exercises the module entry point.
• python -m deepseek_cli chat --help shows chat-specific flags.
• python -m deepseek_cli agent --help lists agent options.
• Run ruff, pytest, or other tooling as required by your workflow.

Contributions welcome! Open issues or pull requests to extend functionality.