pi-python v0.4.0

Added

• Phase 6 (git context): pi_agent_cli injects a bounded, read-only <git_status> block into the system prompt on every turn. Disable with [git] enabled = false or headless --no-git-context. Non-repos, timeouts, and git failures omit the section. MCP stays out of the product path; callers still adapt langchain-mcp-adapters tools with from_langchain_tool().
• Provider matrix: opt-in live tests for OpenAI, Anthropic, DeepSeek, and SiliconFlow (pytest -m real_llm pi_agent_core/tests/test_provider_matrix.py). Manual workflow .github/workflows/provider-matrix.yml (workflow_dispatch only; missing secrets skip).
• Phase 7 extension packages are built and published with the release: pi-web-access-py, pi-goal-x-py, pi-dynamic-workflows-py. CI and the pre-release test job install all three.

Changed

• pi-agent-core-lc, pi-agent-harness-lc, and pi-agent-cli-lc are version 0.4.0.

pi-python v0.3.0

Added

• TUI binary in GitHub Releases (beta): prebuilt zypi Linux x86_64 binary is now included in GitHub Releases alongside Python wheels. Download zypi-linux-x86_64 from the release assets page. Build from source for other platforms.
• Phase 5 (Coding Agent prompt engine): pi-aligned build_system_prompt() / build_coding_agent_harness_system_prompt() in pi_agent_cli; tool prompt_snippet / prompt_guidelines contributions; AGENTS.md / CLAUDE.md / SYSTEM.md / APPEND_SYSTEM.md context files; <available_skills> XML format; bash PI_* env.
• FrontierHarness 30-task evaluation: scripts/run_eval.py CLI with 21 Terminal-Bench + 9 DeepSWE industrial tasks; dual runtime (Windows local NTFS junctions + WSL2 Docker sandbox); v2ray proxy integration; full report in docs/benchmarks/FRONTIER-HARNESS-30-EVAL-REPORT.md.
• TUI & Code-Agent guide: new docs/TUI-AND-CODE-AGENT.md covering installation, configuration, and usage for both zypi TUI and pi_agent_cli.
• Release workflow: build-tui job builds the Rust TUI binary (cargo build --profile release-dist -p pi-pager-bin) and uploads zypi-linux-x86_64 to GitHub Releases.

Changed

• TUI x.ai/ residual cleanup (P4P5-1 resolution): systematic purge of 680 x.ai/ references across 115 files in tui/crates/codegen/pi-pager/src/. New acp/vendor.rs centralises vendor-prefix constants and helpers; 4 inbound filter sites use vendor::is_vendor_ext_method() as defensive guards; doc comments, test fixtures, views/dispatch literals all scrubbed. Only vendor.rs (4 constants) and worktree_cmd/mod.rs (20, deferred) retain x.ai/ strings.
• Test regression fixes: fixed 5 x.ai cleanup regressions where test data was over-renamed to pi/ while handler code still used original constant names (TITLE_IS_MANUAL_META_KEY, PI_SESSION_UPDATE_METHOD, is_vendor_meta_key).
• Grok-specific tests marked #[ignore]: 62 tests for features removed from pi-python (grok slash commands, /loop scheduler, /share, dashboard, ~/.grok path, agent subcommand) annotated with #[ignore = "pi-python: grok-specific feature not supported"].
• TUI test result: 8880 passed, 0 failed, 72 ignored.
• TUI and code-agent marked as beta in README.
• README restructured: added Status table, TUI install section, and updated roadmap.

pi-python v0.2.0

Added

• Phase 4 P0–P4 (Coding Agent CLI): vendored grok-build TUI under tui/ (Apache-2.0, excluded from wheels); packages/pi-agent-cli standard ACP agent over AgentHarness (no x.ai/*); TUI spawn python -m pi_agent_cli, skip xAI login, drop vendor extension RPCs, home ~/.pi-python, product binary zypi. TUI Cargo crates renamed xai-* → pi-*, then P5 de-grok: pi-grok-* → pi-*, grok CLI subcommands removed, auth/prefetch startup skipped when auth_methods is empty. /new→session/new, /resume→session/list+session/load; @ is in-process directory listing; zypi -p / python -m pi_agent_cli -p is Python headless. P4: config.toml (model, permission, skills, [agent].command), coding system prompt + skills XML, Windows notes in docs/WINDOWS.md.
• Pelican-on-a-bicycle foundation benchmark: pi_agent_cli.benchmarks.pelican, scripts/smoke_pelican.py, docs/benchmarks/PELCAN-BICYCLE.md — structural SVG smoke test for the pi TUI agent path.
• PyPI: pi-agent-cli-lc included in the release workflow (tag v* builds and publishes core, harness, and cli wheels/sdists; Rust TUI excluded).

pi-python v0.1.0

Initial public release.

Added

pi-agent-core

• Core runtime (Phase 1): Agent with steering/follow-up queues, abort, subscribe() event barrier; agent_loop with pi-compatible event protocol, parallel/sequential tool execution, terminate semantics.
• LangChain adapter: StreamFn over astream() for OpenAI / Anthropic / DeepSeek / any init_chat_model provider; mock stream for tests (no API keys needed).
• Production hardening (Phase 2/2.5):
  • Cross-provider message replay (transform_messages: tool-call id normalization, thinking downgrade, image stripping).
  • Usage & cost tracking with CostCalculator.
  • Thinking/reasoning: provider param mapping, streamed thinking_delta events, Anthropic signature replay, DeepSeek-style reasoning_content.
  • Stream-level retries with exponential backoff + jitter, Retry-After aware.
  • Runaway protection: max_turns / tool_timeout.
  • Guardrail hooks: before_llm_call (with ContextBudget), after_llm_call, on_agent_end.
  • Observability: on_payload / on_response hooks; run_id / turn_id on every event.
  • Granular stream events: text_start/end, thinking_start/end, toolcall_start/end.
  • Structured output: response_schema (Pydantic model or JSON schema).
  • Tool-result images: Anthropic native blocks, user-message fallback elsewhere.
  • OpenAI-compatible gateways via Model.base_url.
• Tool ecosystem (P6):
  • 7 built-in coding tools: read, bash, edit, write, grep, find, ls.
  • Group factories: create_coding_tools() / create_read_only_tools().
  • LangChain BaseTool → AgentTool adapter (from_langchain_tool).

pi-agent-harness

• Session tree (H1): SessionRepo with filesystem storage, uuid7 IDs, branch/fork semantics, message append/list.
• AgentHarness runtime (H2): orchestration layer over Agent, queue rollback, abort aggregation, event-based idle wait.
• Compaction & tree navigation (H3): token-based compaction with branch summaries, navigate_tree for branch exploration.
• Skills, templates & env (H4): skill discovery, prompt templates, system prompt injection, LocalExecutionEnv for sandboxed execution.