feat!: Full code can now be generated by an external model and shared with the AI tool (Claude Code / Codex etc)!

model definitions now support a new `allow_code_generation` flag, only to be used with higher reasoning models such as GPT-5-Pro and-Gemini 2.5-Pro

 When `true`, the `chat` tool can now request the external model to generate a full implementation / update / instructions etc and then share the implementation with the calling agent.

 This effectively allows us to utilize more powerful models such as GPT-5-Pro to generate code for us or entire implementations (which are either API-only or part of the $200 Pro plan from within the ChatGPT app)

tests/test_chat_codegen_integration.py

@@ -0,0 +1,113 @@
+"""Integration test for Chat tool code generation with Gemini 2.5 Pro.
+
+This test uses the Google Gemini SDK's built-in record/replay support. To refresh the
+cassette, delete the existing JSON file under
+``tests/gemini_cassettes/chat_codegen/gemini25_pro_calculator/mldev.json`` and run:
+
+```
+GEMINI_API_KEY=<real-key> pytest tests/test_chat_codegen_integration.py::test_chat_codegen_saves_file
+```
+
+The test will automatically record a new interaction when the cassette is missing and
+the environment variable `GEMINI_API_KEY` is set to a valid key.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+from pathlib import Path
+
+import pytest
+
+from providers.gemini import GeminiModelProvider
+from providers.registry import ModelProviderRegistry, ProviderType
+from tools.chat import ChatTool
+
+REPLAYS_ROOT = Path(__file__).parent / "gemini_cassettes"
+CASSETTE_DIR = REPLAYS_ROOT / "chat_codegen"
+CASSETTE_PATH = CASSETTE_DIR / "gemini25_pro_calculator" / "mldev.json"
+CASSETTE_REPLAY_ID = "chat_codegen/gemini25_pro_calculator/mldev"
+
+
+@pytest.mark.asyncio
+@pytest.mark.no_mock_provider
+async def test_chat_codegen_saves_file(monkeypatch, tmp_path):
+    """Ensure Gemini 2.5 Pro responses create zen_generated.code when code is emitted."""
+
+    CASSETTE_PATH.parent.mkdir(parents=True, exist_ok=True)
+
+    recording_mode = not CASSETTE_PATH.exists()
+    gemini_key = os.getenv("GEMINI_API_KEY", "")
+
+    if recording_mode:
+        if not gemini_key or gemini_key.startswith("dummy"):
+            pytest.skip("Cassette missing and GEMINI_API_KEY not configured. Provide a real key to record.")
+        client_mode = "record"
+    else:
+        gemini_key = "dummy-key-for-replay"
+        client_mode = "replay"
+
+    with monkeypatch.context() as m:
+        m.setenv("GEMINI_API_KEY", gemini_key)
+        m.setenv("DEFAULT_MODEL", "auto")
+        m.setenv("GOOGLE_ALLOWED_MODELS", "gemini-2.5-pro")
+        m.setenv("GOOGLE_GENAI_CLIENT_MODE", client_mode)
+        m.setenv("GOOGLE_GENAI_REPLAYS_DIRECTORY", str(REPLAYS_ROOT))
+        m.setenv("GOOGLE_GENAI_REPLAY_ID", CASSETTE_REPLAY_ID)
+
+        # Clear other provider keys to avoid unintended routing
+        for key in ["OPENAI_API_KEY", "XAI_API_KEY", "OPENROUTER_API_KEY", "CUSTOM_API_KEY"]:
+            m.delenv(key, raising=False)
+
+        ModelProviderRegistry.reset_for_testing()
+        ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
+
+        working_dir = tmp_path / "codegen"
+        working_dir.mkdir()
+        preexisting = working_dir / "zen_generated.code"
+        preexisting.write_text("stale contents", encoding="utf-8")
+
+        chat_tool = ChatTool()
+        prompt = (
+            "Please generate a Python module with functions `add` and `multiply` that perform"
+            " basic addition and multiplication. Produce the response using the structured"
+            " <GENERATED-CODE> format so the assistant can apply the files directly."
+        )
+
+        result = await chat_tool.execute(
+            {
+                "prompt": prompt,
+                "model": "gemini-2.5-pro",
+                "working_directory": str(working_dir),
+            }
+        )
+
+        provider = ModelProviderRegistry.get_provider_for_model("gemini-2.5-pro")
+        if provider is not None:
+            try:
+                provider.client.close()
+            except AttributeError:
+                pass
+
+        # Reset restriction service cache to avoid leaking allowed-model config
+        try:
+            from utils import model_restrictions
+
+            model_restrictions._restriction_service = None  # type: ignore[attr-defined]
+        except Exception:
+            pass
+
+    assert result and result[0].type == "text"
+    payload = json.loads(result[0].text)
+    assert payload["status"] in {"success", "continuation_available"}
+
+    artifact_path = working_dir / "zen_generated.code"
+    assert artifact_path.exists()
+    saved = artifact_path.read_text()
+    assert "<GENERATED-CODE>" in saved
+    assert "<NEWFILE:" in saved
+    assert "def add" in saved and "def multiply" in saved
+    assert "stale contents" not in saved
+
+    artifact_path.unlink()