Plan Execute#

Source: examples/patterns/plan_execute.py

Introduction#

Plan-and-Solve and ReAct both separate planning from execution to reduce reasoning drift, while AutoGen shows how these roles can be modularized across components. This example encodes planner-executor separation with tool-backed execution and deterministic trace artifacts.

Note

This example’s checked-in local LlamaCppServerLLMClient config uses a Qwen3-4B GGUF model. On lower-RAM machines, swap in a smaller local model or start with Ollama Local Client.

Technical Implementation#

  1. Configure Tracer with JSONL + console output so each run emits machine-readable traces and lifecycle logs.

  2. Build the runtime surface (public APIs only) and execute PlanExecutePattern.run(...) with a fixed request_id.

  3. Configure and invoke Toolbox integrations (core/script/MCP/callable) before assembling the final payload.

  4. Print a compact JSON payload including trace_info for deterministic tests and docs examples.

        flowchart LR
    A["Input prompt or scenario"] --> B["main(): runtime wiring"]
    B --> C["PlanExecutePattern.run(...)"]
    C --> D["Planner and executor phases share tool/runtime state"]
    C --> E["Tracer JSONL + console events"]
    D --> F["ExecutionResult/payload"]
    E --> F
    F --> G["Printed JSON output"]
    
 1from __future__ import annotations
 2
 3import json
 4from pathlib import Path
 5
 6import design_research_agents as drag
 7
 8# This checked-in local config uses a Qwen3-4B GGUF model to exercise a richer
 9# multi-step path. On lower-RAM machines, swap in a smaller local model or
10# start with the lighter Ollama local client example first.
11_EXAMPLE_LLAMA_CLIENT_KWARGS = {
12    "model": "Qwen_Qwen3-4B-Instruct-2507-Q4_K_M.gguf",
13    "hf_model_repo_id": "bartowski/Qwen_Qwen3-4B-Instruct-2507-GGUF",
14    "api_model": "qwen3-4b-instruct-2507-q4km",
15    "context_window": 8192,
16    "startup_timeout_seconds": 240.0,
17    "request_timeout_seconds": 240.0,
18}
19
20
21def main() -> None:
22    """Run planner-executor orchestration with tracing."""
23    # Fixed request ids keep trace paths and sample output stable for docs/tests.
24    request_id = "example-workflow-plan-execute-design-001"
25    tracer = drag.Tracer(
26        enabled=True,
27        trace_dir=Path("artifacts/examples/traces"),
28        enable_jsonl=True,
29        enable_console=True,
30    )
31    # Run the planner/executor pattern using public runtime surfaces. Using this with statement will
32    # automatically shut down the managed client and tool runtime when the example is done.
33    with drag.Toolbox() as tool_runtime, drag.LlamaCppServerLLMClient(**_EXAMPLE_LLAMA_CLIENT_KWARGS) as llm_client:
34        executor_delegate = drag.MultiStepAgent(
35            mode="json",
36            llm_client=llm_client,
37            tool_runtime=tool_runtime,
38            max_steps=3,
39            allowed_tools=("text.word_count",),
40            tracer=tracer,
41        )
42        workflow = drag.PlanExecutePattern(
43            llm_client=llm_client,
44            tool_runtime=tool_runtime,
45            executor_delegate=executor_delegate,
46            max_iterations=1,
47            tracer=tracer,
48        )
49        result = workflow.run(
50            prompt=(
51                "Create and execute a one-step plan that uses text.word_count to count the words "
52                "in the phrase 'design system research workflow', then return only word_count."
53            ),
54            request_id=request_id,
55        )
56
57    # Print the results
58    summary = result.summary()
59    print(json.dumps(summary, ensure_ascii=True, indent=2, sort_keys=True))
60
61
62if __name__ == "__main__":
63    main()

Expected Results#

Run Command

PYTHONPATH=src python3 examples/patterns/plan_execute.py

Example output shape (values vary by run):

{
  "success": true,
  "final_output": "<example-specific payload>",
  "terminated_reason": "<string-or-null>",
  "error": null,
  "trace": {
    "request_id": "<request-id>",
    "trace_dir": "artifacts/examples/traces",
    "trace_path": "artifacts/examples/traces/run_<timestamp>_<request_id>.jsonl"
  }
}

References#