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Changelog

Source: NEWS.md

gptr 1.0.0

gptr 1.0.0 is a complete rewrite: an agent harness that runs inside the live R session and works on the objects already in memory.

Breaking changes

  • The 0.7.0 interface, get_response() and dataframe_to_text(), is removed with no aliases.
  • Instead of get_response(), use session = peter("your prompt", model = "openai/gpt-6-sol"), which returns a session object; its answer is session$text, and session |> peter("next prompt") continues the conversation. The key comes from OPENAI_API_KEY (or a .env file read with gptr_env()) instead of the api_key argument, instructions that went into system_specification go into the prompt or the project instructions file .gptr/vignette.Rmd, and answers stream to the console when a person is present instead of through print_response.
  • Instead of dataframe_to_text(), pass the data frame to peter() as context, for example peter("Which variables are correlated?", mtcars): gptr describes the object compactly and the model computes on it in your session.
  • Providers and models are chosen with the model argument or with gptr_config().
  • ‘RCurl’ is no longer used; HTTP is handled by ‘curl’.
  • R 4.2.0 or later is required.

New features

  • peter() is the single entry point. Without a prompt it opens a chat in the console; with a prompt it runs the agent loop and returns the session. The pipe steers one session: peter("...") |> peter("...") adds turns to the same object. gptr_fork() is the only way to branch. Sessions are saved in the project and resumed with gptr_sessions(), gptr_resume() and gptr_last().
  • With no default model, the interactive console offers Claude Code CLI or Codex CLI setup, or API instructions; gptr_providers(check_login = TRUE) shows CLI sign-in status.
  • The agent evaluates R code in the environment you pass (by default the caller’s frame), so objects it creates stay in your workspace. It reads, writes and edits files, and searches them with peter$grep(), peter$find() and peter$ls(); shell, Python, SQL and knitr engines are reached through peter$sh(), peter$py(), peter$sql() and peter$knit().
  • Providers are implemented in R: Anthropic, OpenAI, Google Gemini, OpenAI-compatible endpoints and local Ollama servers, with streaming, tool calls, images, reasoning controls, prompt caching and cost accounting where the model supports them. The Claude plan (through the claude command-line tool, experimental) and the ChatGPT plan (through codex) are supported without keys. See gptr_providers() and gptr_models().
  • System 1 decisions: with a typed decision model, TypeSafe AI’s Jev or Clef and Clef Flash on a local Ollama server (0.35.1 or later), peter() returns logical, choice or score vectors with their probabilities (gptr_prob()) that work inside if, for and while, one element per input. A generative model can emulate them; emulated answers are marked as uncalibrated.
  • Permission modes manual (default), edits, auto and plan, rules with gptr_permissions(), and an advisory risk classifier, gptr_risk(). A permission question without a person present stops the run with a classed condition.
  • Scripts and notebooks are the history: code the agent ran is recorded below each peter() call in .R, .Rmd, .qmd and .ipynb documents and replays without model calls (gptr_doc(), gptr_source(), gptr_blocks(), gptr_cache()).
  • gptr_init() creates a .gptr/ project workspace with the project instructions file .gptr/vignette.Rmd; gptr_config() and gptr_trust() manage settings and trust.
  • Checkpoints: gptr_rewind(), gptr_checkpoints() and /undo restore objects, files and the conversation.
  • Sub-agents, teams and fan-outs (agents =, parallel =, gptr_parallel()), across providers.
  • Skills, prompt templates, agent files, extensions and plugins in R packages, all on one versioned extension API (gptr_register(), gptr_spec() and the spec constructors).
  • MCP: a client for both protocol eras (gptr_mcp(), gptr_mcp_add()) that exposes server tools as R functions, and gptr_mcp_serve(), which serves the live session to other agents.
  • Artifacts are Shiny apps launched in the background from the live session (gptr_artifacts()).
  • Secrets are kept in a private vault and redacted everywhere; gptr_login() signs in to providers and MCP servers, gptr_env() loads .env files (including the jev-key alias) and gptr_scrub() cleans files that captured a key.
  • Token accounting and budgets: gptr_usage(), gptr_prompt(), gptr_describe() and the budget argument.
  • Background sessions (background = TRUE) are experimental.
  • See ?gptr_security and ?gptr_egress for what gptr does on your behalf and what it sends to model providers, and ?gptr_options for every option.
  • Successful removal of CLI billing variables emits an informational gptr_message_billing_env condition with the removed names, never their values. Handlers use muffleMessage; the notice respects gptr.quiet. Actual billing refusals remain errors.

gptr 0.7.0

CRAN release: 2025-04-05

  • Last release of the 0.x interface, get_response() and dataframe_to_text() for the OpenAI ‘ChatGPT’ API (released 2025-04-05, after 0.5.0 and 0.6.0 in May 2024).