feat: add drawing agent

pyproject.toml

@@ -17,6 +17,7 @@ dependencies = [
     "tavily-python>=0.7.9",
     "pypdf>=5.7.0",
     "pytest-playwright>=0.7.0",
+    "matplotlib>=3.10.3",
 ]
 
 [project.scripts]

src/deepengineer/deepsearch/draw_agent.py

@@ -0,0 +1,114 @@
+"""
+drawing_agent.py (rev 3)
+A smolagents‑powered CodeAgent that grants the model **full matplotlib.pyplot**
+control *plus* a single high‑level `save_fig` tool. The tool must be called at
+the end of each drawing sequence to persist the artwork, while a callback still
+captures a snapshot for chat‑time previews.
+"""
+
+from __future__ import annotations
+
+from io import BytesIO
+from time import sleep
+
+import matplotlib
+
+matplotlib.use("Agg")  # headless backend
+import matplotlib.pyplot as plt
+from PIL import Image
+
+from smolagents import CodeAgent, LiteLLMModel, tool
+from smolagents.agents import ActionStep
+
+# ---------------------------------------------------------------------------
+# Drawing tool (the *only* one): save_fig
+# ---------------------------------------------------------------------------
+
+
+@tool
+def save_fig() -> str:
+    """Save the current matplotlib figure to *path*.
+    Save fig takes no arguments. The output path is hardcoded to "figure.png".
+    """
+    path = "figure.png"
+    if not plt.get_fignums():
+        raise RuntimeError(
+            "No active figure to save; create one before calling save_fig()."
+        )
+    plt.savefig(path, bbox_inches="tight")
+    return f"Figure saved to {path}."
+
+
+# ---------------------------------------------------------------------------
+# Callback: snapshot the figure after each executed step
+# ---------------------------------------------------------------------------
+
+
+def _capture_snapshot(memory_step: ActionStep, agent: CodeAgent) -> None:
+    if not plt.get_fignums():
+        return
+
+    buf = BytesIO()
+    plt.savefig(buf, format="png", bbox_inches="tight")
+    buf.seek(0)
+    img = Image.open(buf)
+
+    for prev in agent.memory.steps:
+        if (
+            isinstance(prev, ActionStep)
+            and prev.step_number <= memory_step.step_number - 2
+        ):
+            prev.observations_images = None
+
+    memory_step.observations_images = [img.copy()]
+    buf.close()
+
+    hint = "[snapshot: matplotlib figure captured]"
+    memory_step.observations = (
+        hint
+        if memory_step.observations is None
+        else memory_step.observations + "\n" + hint
+    )
+
+
+# ---------------------------------------------------------------------------
+# Agent initialisation
+# ---------------------------------------------------------------------------
+
+model_id = "deepseek/deepseek-chat"
+model = LiteLLMModel(model_id=model_id)
+
+agent = CodeAgent(
+    tools=[save_fig],  # only one explicit tool
+    model=model,
+    additional_authorized_imports=["*"],
+    step_callbacks=[_capture_snapshot],
+    max_steps=20,
+    verbosity_level=2,
+)
+
+# ---------------------------------------------------------------------------
+# System prompt injected before every user request
+# ---------------------------------------------------------------------------
+
+matplotlib_instructions = r"""
+You may use the entire **matplotlib** API.
+Workflow
+--------
+1. Construct your figure with ordinary matplotlib calls.
+2. **Once the figure is complete, call `save_fig()` and `final_answer()`.** This is the
+   *only* external tool you have and must be invoked exactly once per final
+   graphic.
+3. Do **not** call `plt.show()`; a callback captures a PNG automatically.
+4. Keep code blocks concise and avoid GUI back‑end imports (TkAgg, Qt, etc.).
+"""
+
+# ---------------------------------------------------------------------------
+# Example CLI usage
+# ---------------------------------------------------------------------------
+if __name__ == "__main__":
+    import numpy as np
+
+    prompt = "Propose moi un schéma simplifié d'un réacteur nucléaire à eau pressurisée (PWR) avec un schéma de l'installation."
+    result = agent.run(prompt + matplotlib_instructions)
+    print("Final output:\n", result)

uv.lock

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