plyngent

Single-user LLM chat and agent toolkit for the terminal.

Python 3.14+. OpenAI-compatible APIs (including DeepSeek OpenAI-compat), OpenAI Responses with optional hosted tools, SQLite session memory, workspace-scoped file/process/VCS tools, and a readline REPL with slash commands.

Requires Python 3.14+ on your PATH (or via uv / pipx).

Install

Quick try (uvx)

No permanent install — runs the published package in a temporary environment:

uvx plyngent --help
uvx plyngent chat

User tool install

Keep plyngent on your PATH as a managed tool:

# uv (recommended)
uv tool install plyngent
plyngent --help

# pipx
pipx install plyngent
plyngent --help

Upgrade later:

uv tool upgrade plyngent
# or: pipx upgrade plyngent

pip (venv or user)

python3.14 -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -U pip
pip install plyngent
plyngent --help

Or user install (if you accept that layout):

pip install --user plyngent

From a git clone (development)

pdm install          # first time
pdm sync             # after pull
pdm run plyngent --help

Dev checks (same order as CI):

pdm run ruff check .
pdm run ruff format --check .   # or: pdm run ruff format .  to apply
pdm run basedpyright .
pdm run pytest

Commit gateway (prek): runs ruff check + format and basedpyright on git commit so format is not forgotten.

uv tool install prek    # once
prek install            # once per clone (installs .git/hooks/pre-commit)
prek run --all-files    # run all hooks on demand

Config: prek.toml. CI still runs the same checks in GitHub Actions.

Basic usage

# 1) Create / open config
plyngent config path
plyngent config edit    # $VISUAL/$EDITOR, else system open (xdg-open/open/startfile)

# Minimal provider (OpenAI platform — Responses API; preset defaults to openai):
# [providers.oai]
# access_key_or_token = "sk-..."
# # models default: gpt-5.4, gpt-5.4-mini, gpt-5.4-nano
# # provider_tools default: web_search  (use provider_tools = [] to disable)

# 2) Chat
plyngent chat
plyngent chat --provider oai --model gpt-5.4-mini
plyngent chat -p "Summarize this repo" --provider oai --model gpt-5.4-mini --no-stream

# 3) List providers from config
plyngent providers

# 4) Plugins (entry-point allowlist under [plugins])
plyngent plugins list
plyngent plugins enable acme

In the REPL: type normally, use /help for slash commands, """ … """ for multiline, /markdown for Rich rendering, /quit to leave.

Configure

Default config path (platformdirs):

plyngent config path
plyngent config edit    # $VISUAL/$EDITOR (e.g. codium --wait), else system default

Copy the example and fill in a real token:

cp doc/plyngent.example.toml "$(plyngent config path)"
# then edit providers

Minimal shape:

[providers.local]
preset = "openai-compatible"
url = "https://api.openai.com/v1"
access_key_or_token = "sk-..."
# Optional HTTP timeouts (seconds). Default: connect=10, read=600.
# timeout = 120
# timeout = { connect = 10, read = 600 }

[providers.local.models]
"gpt-4o-mini" = { text = true }

[agent]
# system_prompt = persona (omit → built-in). tool_directives = tool playbook.
# system_prompt = "" / tool_directives = "" disable each part; both "" → no system.
# Or multi-line override (prefer '''...'''):
# system_prompt = '''Your custom persona...'''
# tool_directives = '''### Workspace ...'''
confirm_destructive = true
max_context_tokens = 200000
# Fold MCP server initialize ``instructions`` (usage guidance) into the
# system prompt when tools are on (default true; false ignores server text).
# mcp_instructions = true
# Static out-of-workspace pre-allow (path → read|write|exec); never prompts.
# allow_paths = { "/data/datasets" = "read", "/tmp/build" = "exec" }
# Auto-raise tool/PTY limits without prompting (same as answering yyy).
# auto_continue_limits = false
# Thinking strength: "" (provider default) | none | minimal | low | medium |
# high | xhigh | max. See "Thinking strength" below; providers and single
# models may override either value.
# reasoning_effort = "medium"
# thinking_budget_tokens = 8000   # Anthropic only; overrides the level's budget

# Optional skills (instruction directories). See doc/skills.md.
# [skills]
# enabled = true                  # false = no skill tools
# paths = ["~/team-skills"]       # explicit roots, highest priority
# discover = ["plyngent", "claude"]  # our user dir + other harnesses' dirs
# include_project_roots = true    # also <workspace>/.claude/skills
# allow_write = false             # true = skip the per-write grant prompt

# Optional plugins (entry-point names); default load none. See doc/plugins.md.
# [plugins]
# enable = ["acme"]

Per-provider timeout is passed to the HTTP session for chat/completions, Responses, and GET /models. A single number sets one timeout; { connect, read } splits TCP/TLS setup vs idle wait between response bytes (SSE can run longer than read while chunks keep arriving). Tool/process timeouts (run_argv, PTY, policy confirm) are separate.

Thinking strength (reasoning_effort) can be set on [agent], on a provider, or on a single model: the most specific layer wins, per field, so a model may override only the effort or only the budget. "" sends nothing and lets the provider apply its own default. Each API surface maps the value onto its own wire field — chat completions send reasoning_effort, Responses send reasoning.effort, and Anthropic has no effort level at all, so it sends thinking with the token budget that level maps onto (minimal 1024 … xhigh/max 32768; none disables thinking); a thinking block the model refuses is retried once with the shape it takes — adaptive thinking with the level itself as output_config.effort (from Claude 4.7 on), or no block at all where thinking cannot be turned off — and the refusal is remembered for the session, so thinking_budget_tokens is ignored on such a model. max is DeepSeek's own top level on chat completions and clamps to xhigh everywhere else. thinking_budget_tokens overrides that mapping; either way the request stays valid: the budget never drops below 1024, and when it would swallow the output limit max_tokens grows so the answer still has room. DeepSeek chat keeps thinking.type = "enabled" unless the effort is none.

[providers.deepseek]
reasoning_effort = "high"          # provider default

[providers.deepseek.models]
"deepseek-v4-pro" = { text = true, reasoning_effort = "max" }  # per-model wins

[providers.anthropic]
reasoning_effort = "medium"
thinking_budget_tokens = 16000     # explicit Anthropic thinking budget

Third-party plugins: install a package that declares project.entry-points."plyngent.tools" (and later other groups), then allowlist the entry-point name under [plugins].enable. Details: doc/plugins.md.

Skills (instruction directories with a SKILL.md): discovered under [skills].paths, our own user skills directory, and other harnesses' skill directories (~/.claude/skills, plus <workspace>/.claude/skills when include_project_roots). A session-start notice (a host notice, never a system-prompt edit) tells the model that the skill tools exist and how to use them — skill_list to see what exists, skill_read for a SKILL.md, skill_search for content — and deliberately lists nothing; skill_create / skill_edit write one behind a timed once/session/no grant ([skills].allow_write = true for a standing one; the path denylist still wins and --yes//yolo never skips it). Reading needs no grant: skill roots are read-only roots, so read_file / regex_files see them too while writes stay denied. Details: doc/skills.md.

MCP servers (Model Context Protocol over stdio): define servers under [mcp.servers.<name>] (command + args, optional env/cwd/timeout/read_only) and their tools become agent tools namespaced mcp__<server>__<tool> (LOCAL tags; read_only = true also marks them READ_ONLY, eligible for /btw --tools=read). Names in [mcp].disable stay disconnected. A server may also return optional instructions (usage guidance) in its MCP initialize response; when tools are on those are folded into the agent system prompt as MCP server <name> instructions: blocks ([agent] mcp_instructions = false disables), and /mcp previews them. In the REPL, /mcp lists per-server status and tool counts; /mcp reconnect re-reads the config file and restarts every enabled server (adopts newly added ones).

Supported provider presets today:

Model-level preset / url overrides on a catalog entry can route a single provider name to a different API (e.g. gateway + Anthropic model). DeepSeek models may also carry a per-model convention (empty = inherit the provider-level one), e.g. serve deepseek-flash over Responses while deepseek-v4-pro stays Chat Completions:

[providers.deepseek]
preset = "deepseek"
access_key_or_token = "sk-..."

[providers.deepseek.models]
"deepseek-flash" = { text = true, convention = "responses" }
"deepseek-v4-pro" = { text = true }

DeepSeek's Anthropic convention (convention = "anthropic") points at https://api.deepseek.com/anthropic by default and is fully supported by the agent's Anthropic Messages path (tools, streaming, usage). DeepSeek maps claude-opus* model ids to deepseek-v4-pro and claude-haiku* / claude-sonnet* (and unknown ids) to deepseek-flash server-side; real DeepSeek ids pass through as-is. GET /models is not documented on that base, so model selection is config-driven.

If [database] is omitted (or SQLite url is unset/empty), chat uses a durable file under the user data dir (e.g. ~/.local/share/plyngent/chat.db on Linux). Set url = ":memory:" for a true in-memory SQLite (CLI warns; no file; useful for tests).

Chat

Interactive REPL

plyngent chat
plyngent chat --provider local --model gpt-4o-mini
plyngent chat --workspace /path/to/project --new
plyngent chat --session 3

Sessions resume the most recently updated session for the current workspace unless you pass --new or --session. Each session remembers the last provider and model (restored on resume so you are not re-prompted). A session resumed by a fresh plyngent process also gets a [notice] resume: … line: the model is told that process-scoped state — PTY sessions, running commands, temporary workspaces — did not survive the restart, and that an unfinished turn may have been cut off. The notice is kept with the transcript; --quiet hides only the user-facing line.

When a tool-loop or PTY limit is hit, the prompt accepts y (continue once), n (stop), or yyy — stop asking for the rest of this turn (the next user turn prompts again). --auto-continue / [agent] auto_continue_limits = true skip the prompt for every turn.

Tool calls show progress as they run: every builtin tool prints a * Read 'src/x.py' prefix the moment the call starts, and the outcome (L1-80 (done), (exit code 0), (session 3)) is appended once the result lands; MCP tools render as * MCP <server>:<tool> (done). Plugin tools keep the [tool] … / [tool ok] … style. Piped output and --verbose print the finished line as before.

One-shot (scripts / CI)

plyngent chat -p "Summarize README.md" --provider local --model gpt-4o-mini --no-stream
echo "hello" | plyngent chat --provider local --model gpt-4o-mini

Exit codes (one-shot):

Input ergonomics

• Multiline: start a message with """, end a later line with """.
• /edit: compose a turn in $VISUAL/$EDITOR (blocking only; empty cancels).
• Tab: completes slash commands and some arguments (provider, model, on/off, export, /help targets).

Slash commands

Type /help in the REPL for the live list. Common ones:

| /retry | Retry/continue the incomplete last user turn (after error, cancel, or output limit) | | /btw [--tools read\|no\|full] [--fresh] | Side question without changing the main session (read-only tools by default; the model is told the exchange is unsaved and how its tools are scoped) | | /provider /model | Switch without restarting | | /model --persist | Save current model id into plyngent.toml catalog | | /models | List config + remote GET /models (always re-fetches) | | /models --persist | Merge remote catalog into TOML for this provider | | /todos | Todo/task stack: list (items numbered as listed), push, pop, done, clear | | /skills [list\|search\|open] | List discovered skills, regex-search them, or open one's directory in the system file manager | | /grants | Directory-access grants: list, or revoke <index\|all> | | /config | Edit plyngent.toml ($VISUAL/$EDITOR or system open); reload after blocking editor | | /quit | Leave the REPL |

User messages are saved immediately. On API error or Ctrl+C, unfinished assistant text is discarded — tool calls that already produced a result stay, so /retry does not run them again — but the user message stays so /retry works after resume. Interactive auto-retry waits 5s, 10s, 15s, 20s, then +10s each step (10 attempts); an attempt that gets a full model round back resets that budget, so a connection that recovers and drops again starts over from 5s. A round cut off at the output limit (max_tokens) is not an error: what the model had written — thinking blocks included — stays in the transcript, its tool calls are dropped (they are re-issued, not replayed), and a notice tells it where it stopped, so up to 2 further rounds carry on from there; when that budget is spent the turn ends with the partial answer kept and /retry continues it. Tool calls of one round run in parallel, but writes to the same file apply one at a time, in call order — a later edit sees the earlier one's result instead of stale text.

Ctrl+C cancels the in-flight turn, and during the auto-retry countdown it cancels the retry. Model-initiated prompts run off the event loop: a wait prompt is cancelled by Ctrl+C (the tool reports cancelled by user and the turn continues), while ask_user_* and confirm prompts ignore it with a one-line hint — answer them to continue. Ctrl+C never exits the REPL (use Ctrl+D or /quit), and MCP servers run in their own process group, so it never kills them either.

Workspace model

• Workspace = root for file/process/VCS tools (default cwd).
• Session = SQLite chat bound to a workspace path.
• Paths outside the workspace need a directory-access grant: the model calls request_directory_access (read / write / exec), the human approves at the requested level or another one (timed y/N, default deny; --yes//yolo auto-approve as a process-only grant), and approval lasts for the session (/grants lists/revokes). Static pre-allow lives under [agent].allow_paths. The path denylist always wins, and grants gate path-resolving tools only — they are not a sandbox (run_argv/PTY reach the whole filesystem).
• Resuming a session from another directory prompts: keep session workspace, rebind to current, or abort.

Tools (when enabled)

Default registry: file ops (including tree with a markdown bullet-list default, flat paths or classic decorated on demand; default noise-dir skips), run_argv / run_argv_batch / PTY (POSIX openpty; Windows ConPTY via pywinpty), read-only VCS (git), HTTP fetch (GET/POST/PUT/DELETE via niquests; private/loopback hosts need a human policy grant, not YOLO), human prompts (ask_user_line / ask_user_choice / ask_user_form), wait (line prompt with timeout; Enter disturbs), request_directory_access (out-of-workspace access grants), get_truncated (resume any truncated result via its truncate_token=...), skills (skill_list / skill_read / skill_search / skill_create / skill_edit), and todo stack tools (todo_list / todo_push / todo_pop / todo_update / todo_clear).

Skills are instruction directories shared with other harnesses: a folder with a SKILL.md (YAML frontmatter — name, description, … — plus a Markdown body) and optional bundled files (scripts, references). Discovery, roots, grants, and the authoring format are documented in doc/skills.md; the short version is that a session-start notice points the model at them (skill_list / skill_read / skill_search) without listing anything, so what exists (and the bodies) is read on demand rather than injected, and writing a skill is a separate grant (a timed once/session/no prompt, or [skills].allow_write) that is not a directory-access grant and is never skipped by YOLO.

Safety defaults:

• Paths stay under the workspace unless granted (request_directory_access / [agent].allow_paths); the refusal names the mode that would cover the call; optional path_denylist substrings always apply (tree also skips denylisted children by default).

• Command basename denylist (e.g. dangerous shells/utilities).

• Destructive tools (delete/move/overwrite) can require confirm (confirm_destructive; default deny in non-TTY). Override for the session with /yolo on|off|once or startup --yes (path/command denylists still apply).

• write_file refuses to replace an existing file unless overwrite=true; the confirm asks about that replacement.

• PTY sessions: caps, idle TTL, output budget; master FD is non-inheritable; sessions closed on chat exit. Prefer file tools over full-screen editors (vim/nano) for edits. read_pty sanitizes CSI/controls so tool results cannot reprogram the host TTY (no host terminal reset on exit). write_pty is literal text only; use write_pty_keys for \xHH, ctrl+x, key=esc|enter|…. For passwords/sudo/ssh prompts use ask_into_pty (human types locally; answer never returns to the model).

• Mis-typed tool arguments are answered, never guessed: a string where an array is expected (run_argv argv, ask_user_choice options, ask_user_form fields), a call that omits a required argument, or a non-numeric wait duration (numeric strings are accepted) returns an error showing the shape/names to send — the human never sees a garbage prompt, and no confirm prompt fires for a call that cannot run.

Usage / context (CLI)

• Context size prefers API prompt_tokens from the last model call; otherwise a char-based estimate (~4 chars/token).
• Turn/session usage sum billed completion usage across tool rounds (history is re-sent each round).
• Soft compact can calibrate from reported prompt_tokens. See /status.

Other commands

plyngent providers          # list configured providers
plyngent config path|edit
plyngent --log-level INFO chat ...

Architecture (short)

See doc/architecture.md and AGENTS.md for developers.

• lmproto/ — OpenAI-compatible, OpenAI Responses, Anthropic Messages, DeepSeek msgspec models and async SSE clients
• agent/ — kind-based tool loop (chat_completions / responses / messages), streaming, usage, compact
• memory/ — async SQLAlchemy sessions/messages
• tools/ — workspace tools
• cli/ — Click entry + slash registry (awaitlet bridges sync Click to async work)
• Multi-tenant web (web/) is not in scope for the single-user CLI (Phase H).

License

MIT