freemo 61fc70d84b fix(cli): pass decision tree and influence edges to CorrectionService in plan correct handler (#639)
## Summary

Fixes the `plan correct` CLI handler which never passes the decision tree or influence edges to `CorrectionService`, producing single-node impact analysis regardless of the plan's actual decision structure.

Closes #606

## Root Cause

The `correct_decision()` handler in `plan.py` created a bare `CorrectionService()` and called `analyze_impact()` and `execute_correction()` without passing `decision_tree` or `influence_edges`. Both parameters default to `None` -> empty dicts, causing `_compute_affected_subtree()` BFS to return only the single target decision, ignoring all descendants and influence-DAG dependents.

## Changes

### Production Fix (`src/cleveragents/cli/commands/plan.py`)
- Resolve `DecisionService` via `get_container()` (following the pattern used by `plan explain` and `plan tree`)
- Build structural tree adjacency list from `decision_svc.list_decisions(plan_id)` using `parent_decision_id` relationships
- Fetch influence edges from `decision_svc.get_influence_edges(plan_id)`
- Pass both `decision_tree` and `influence_edges` to `svc.analyze_impact()` and `svc.execute_correction()`

### Existing Test Fixups
- Updated 4 step definition files that mock `CorrectionService` to also mock the new `DecisionService` resolution path

### New Tests
- **Behave BDD**: 3 scenarios verifying tree/edge forwarding (dry-run subtree, execution subtree, leaf node)
- **Robot Framework**: 3 integration smoke tests
- **ASV Benchmark**: Tree building and analyze_impact overhead benchmarks

## Quality Gates

- `nox -s lint` — PASSED
- `nox -s typecheck` — 0 errors
- `nox -s unit_tests` — 9,109 scenarios, 0 failures
- `nox -s coverage_report` — 97%

ISSUES CLOSED: #606

Reviewed-on: cleveragents/cleveragents-core#639
Co-authored-by: Jeffrey Phillips Freeman <jeffrey.freeman@cleverthis.com>
Co-committed-by: Jeffrey Phillips Freeman <jeffrey.freeman@cleverthis.com>
2026-03-08 23:28:05 +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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Python 76%
Gherkin 18.4%
RobotFramework 5.5%