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feat(cli): implement full output rendering framework
Implement the 6 missing element handle types (Tree, Text, Code, Diff,
Separator, ActionHint) and ensure all 6 materialization strategies
(rich, color, table, plain, json, yaml) support all 10 element types.

- Split handles.py into handles/ package (_models, _base, _panel_table,
  _concrete) to comply with 500-line file limit
- Split materializers.py: visual renderers moved to _renderers.py,
  strategy classes remain in materializers.py
- Fix ColorMaterializer fallback: supports_cursor now checks for
  cursor-capable TERM values (xterm, screen, tmux, etc.)
- Fix base ElementHandle.element_copy() thread-safety: acquires lock
- Fix _register_handle return type: Callable[..., H] -> H (was Any)
- Fix boxdraw summary width for multi-column tables
- Fix _tree_node_to_dict: adds "truncated" flag at depth limit
- Fix _sort_table_rows error path: returns list copy (not mutable ref)
- Fix fragile str.replace() in color progress/tree renderers
- Fix stale TextBlock.content in ElementUpdated snapshots
- Fix selection.py docstring: Rich -> Table -> Color -> Plain
- Fix _s alias renamed to _sanitize for readability
- Fix contextlib.suppress scope narrowed to specific exceptions
- Fix local import in session.__init__ moved to module level
- Add spec deviation documentation (SD-1 through SD-12)
- Add BDD scenarios: collapsed tree, terminal capabilities types,
  session double-close, ColumnDef non-default field serialization
- Add 80+ Behave scenarios, 5 Robot integration tests, 3 ASV benchmarks
- Coverage: 97% overall, output module 94-100%

ISSUES CLOSED: #550
2026-03-19 08:29:13 +00:00
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2026-02-23 22:20:03 +00:00
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CleverAgents Core

CleverAgents is a Python-first automation platform. It provides a unified agents CLI, embedded runtime, and service orchestration tools while embracing modern Python tooling.

Highlights

  • Unified CLI entry points: cleveragents and agents
  • Fast Typer/Click-based interface with parity for help/version behavior
  • Behavior-driven coverage via Behave and Robot Framework
  • Nox automation for linting, typing, testing, docs, builds, and benchmarks
  • MkDocs-powered documentation with CleverAgents branding

Quick Start

# clone the CleverAgents core repository
git clone https://git.cleverthis.com/cleveragents/core.git
cd core

# install dependencies
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,tests,docs]"

# set up pre-commit hooks and verify tooling
bash scripts/setup-dev.sh

# verify the CLI
agents --help
agents --version

Developing

Pre-commit hooks run automatically on every git commit (formatting, linting, type checking, security scanning). To run checks manually:

# core validation
nox -s format            # ruff auto-formatting
nox -s lint              # ruff linting
nox -s typecheck         # pyright type checking
nox -s unit_tests        # behave unit tests
nox -s integration_tests # robot integration tests

# quality & security
nox -s security_scan     # bandit security scanning
nox -s dead_code         # vulture dead code detection
nox -s complexity        # radon complexity analysis
nox -s pre_commit        # run all pre-commit hooks
nox -s adr_compliance    # verify ADR compliance

For the full quality automation guide, see docs/development/quality-automation.md.

Documentation

nox -s docs
nox -s serve_docs

Tests

Behave feature scenarios live under features/ and Robot suites under robot/. Use the Nox sessions above to execute them in parity with the implementation plan.

Observability

LangSmith tracing is optional and off by default. Enable it by exporting CLEVERAGENTS_LANGSMITH_ENABLED=true along with a project name and API key (CLEVERAGENTS_LANGSMITH_PROJECT, CLEVERAGENTS_LANGSMITH_API_KEY). The settings module automatically mirrors these values to LANGCHAIN_TRACING_V2, LANGCHAIN_PROJECT, and LANGCHAIN_API_KEY, so LangChain/LangGraph agents emit traces without extra wiring. Additional knobs such as CLEVERAGENTS_LANGSMITH_ENDPOINT, CLEVERAGENTS_LANGSMITH_USER_ID, and CLEVERAGENTS_LANGSMITH_TAGS are documented in docs/observability.md.

LLM provider configuration

CleverAgents ships with a LangChain/LangGraph powered provider registry that discovers whichever API keys you export and automatically selects the best available provider. The CLI now uses actors: select an actor with --actor <name> (or set a default via agents actor set-default). Actors embed provider/model choices; built-in actors are seeded from CLEVERAGENTS_DEFAULT_PROVIDER / CLEVERAGENTS_DEFAULT_MODEL, then fall back to the built-in order (openai → anthropic → google → azure → openrouter → groq → together → cohere → gemini).

Required environment variables

Provider Primary variables
OpenAI OPENAI_API_KEY
Anthropic ANTHROPIC_API_KEY
Google GOOGLE_API_KEY or GOOGLE_GENAI_API_KEY
Azure OpenAI AZURE_OPENAI_API_KEY plus AZURE_OPENAI_ENDPOINT/AZURE_OPENAI_DEPLOYMENT
OpenRouter OPENROUTER_API_KEY (+ optional CLEVERAGENTS_OPENROUTER_ORGANIZATION for sanitized headers)
Gemini GEMINI_API_KEY or GOOGLE_GEMINI_API_KEY
Cohere COHERE_API_KEY
Groq GROQ_API_KEY
Together TOGETHER_API_KEY

Set CLEVERAGENTS_DEFAULT_PROVIDER to pin the global provider (for example export CLEVERAGENTS_DEFAULT_PROVIDER=openai) and CLEVERAGENTS_DEFAULT_MODEL to lock in a model ID. When unset, the registry picks the first configured provider and uses its published default model such as gpt-4o for OpenAI or claude-sonnet-4-20250514 for Anthropic.

Diagnostics and testing shortcuts

  • agents diagnostics prints whether the registry can see your credentials and which actor/provider is selected.
  • agents tell and agents build require --actor <name> unless a default actor is set; use agents actor set-default <name> to configure one.
  • Built-in actors (<provider>/<model>) are immutable, custom actors must be named local/<id>, and the default actor cannot be removed. Use --unsafe when adding/updating configs marked unsafe; runtime only warns when invoking unsafe actors.
  • CLEVERAGENTS_TESTING_USE_MOCK_AI=true forces the in-repo mock provider so Behave/Robot suites never hit external APIs.
  • The full capability matrix (streaming, tool calls, JSON mode, etc.) is documented in docs/reference/providers.md.
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Description
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Readme 84 MiB
Languages
Python 75.8%
Gherkin 18.3%
RobotFramework 4.8%
TypeScript 0.9%
Shell 0.2%