feat: deep-agent canvas, live observability, and multi-environment tooling

Self-hosted platform for building, testing, and shipping LangChain/LangGraph agents. Deep-agent sub-agents on the canvas, a live tracing/observability timeline, auto-provisioned built-in tools with import/export, per-environment tool variables, streamed evaluations, and per-user auth token forwarding.
2026-07-28 01:49:19 +05:30
commit ae67bff5a3
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+"""Regression: ToolRuntime must be injected into materialized REST/GraphQL tools.
+
+Two historical failure modes (both caused by `from __future__ import annotations`
+in forge/tools/rest.py):
+1. compile time - NameError("ToolRuntime") when create_agent resolved the string
+   annotation against module globals where ToolRuntime wasn't imported.
+2. call time - "_call() missing 1 required positional argument: 'runtime'":
+   langchain_core's StructuredTool detects injectable params via
+   inspect.signature(fn) (raw, unevaluated annotations), so a string annotation
+   made the runtime arg invisible and it was stripped during validation.
+
+These tests exercise the real create_agent → ToolNode → StructuredTool path with a
+scripted model that actually calls the tool.
+"""
+
+import itertools
+
+import pytest
+from langchain_core.language_models.fake_chat_models import GenericFakeChatModel
+from langchain_core.messages import AIMessage
+
+from forge.engine.context import CompileContext
+from forge.tools import rest
+
+REST_CFG = {
+    "name": "get_thing",
+    "description": "Fetch a thing.",
+    "kind": "rest_api",
+    "request": {
+        "method": "GET",
+        "url_template": "https://api.example.dev/things/{thing_id}",
+        "fields": [
+            {"path": "thing_id", "type": "string", "in": "path", "required": True, "llm_visible": True},
+        ],
+    },
+    "response": {},
+}
+
+
+@pytest.fixture()
+def captured_exec(monkeypatch):
+    """Stub execute_rest and capture what the tool coroutine passes through."""
+    captured: dict = {}
+
+    async def fake_exec(cfg, kwargs, *, tenant_id, project_id, context=None, auth_resolver=None, stream_writer=None, client=None, egress_policy=None):
+        captured["kwargs"] = kwargs
+        captured["context"] = context
+        captured["tenant_id"] = tenant_id
+        return {"raw": {"ok": True}, "projected": {"ok": True}, "status": 200, "latency_ms": 1}
+
+    monkeypatch.setattr(rest, "execute_rest", fake_exec)
+    return captured
+
+
+def test_runtime_param_is_visible_to_langchain():
+    """The injected-arg detection must see `runtime` as a real ToolRuntime class."""
+    tool = rest.build_rest_tool(REST_CFG, CompileContext(tenant_id="t", project_id="p"))
+    assert tool._injected_args_keys == frozenset({"runtime"}), (
+        "StructuredTool can't see the runtime param - string annotations strike again "
+        "(check for `from __future__ import annotations` in forge/tools/rest.py)"
+    )
+    # The model-facing schema must NOT advertise runtime as an input.
+    assert "runtime" not in (tool.tool_call_schema.model_json_schema().get("properties") or {})
+
+
+async def test_zero_field_tool_executes_without_injection(captured_exec):
+    """Tools with NO llm-visible fields (empty args schema) hit langchain_core's empty-schema
+    short-circuit, which drops even injected args - the coroutine must tolerate runtime=None."""
+    from langchain.agents import create_agent
+
+    cfg = {
+        "name": "get_weather",
+        "description": "Fetch current weather.",
+        "kind": "rest_api",
+        "request": {"method": "GET", "url_template": "https://api.example.dev/weather", "fields": []},
+        "response": {},
+    }
+
+    class ScriptedModel(GenericFakeChatModel):
+        def bind_tools(self, tools=None, **kwargs):  # noqa: ANN001
+            return self
+
+    script = itertools.cycle(
+        [
+            AIMessage(content="", tool_calls=[{"name": "get_weather", "args": {}, "id": "c1", "type": "tool_call"}]),
+            AIMessage(content="done"),
+        ]
+    )
+    tool = rest.build_rest_tool(cfg, CompileContext(tenant_id="t", project_id="p"))
+    agent = create_agent(model=ScriptedModel(messages=script), tools=[tool])
+
+    out = await agent.ainvoke({"messages": [{"role": "user", "content": "weather?"}]})
+
+    assert captured_exec["kwargs"] == {}
+    tool_msgs = [m for m in out["messages"] if getattr(m, "type", "") == "tool"]
+    assert tool_msgs and "ok" in str(tool_msgs[-1].content)
+
+
+async def test_agent_tool_call_injects_runtime(captured_exec):
+    """Full loop: agent's model emits a tool call; ToolNode must inject runtime."""
+    from langchain.agents import create_agent
+
+    class ScriptedModel(GenericFakeChatModel):
+        def bind_tools(self, tools=None, **kwargs):  # noqa: ANN001
+            return self
+
+    script = itertools.cycle(
+        [
+            AIMessage(content="", tool_calls=[{"name": "get_thing", "args": {"thing_id": "42"}, "id": "c1", "type": "tool_call"}]),
+            AIMessage(content="done"),
+        ]
+    )
+    tool = rest.build_rest_tool(REST_CFG, CompileContext(tenant_id="t", project_id="p"))
+    agent = create_agent(model=ScriptedModel(messages=script), tools=[tool])
+
+    out = await agent.ainvoke({"messages": [{"role": "user", "content": "get thing 42"}]})
+
+    # The tool actually executed (no TypeError about 'runtime') with the model's args.
+    assert captured_exec["kwargs"] == {"thing_id": "42"}
+    tool_msgs = [m for m in out["messages"] if getattr(m, "type", "") == "tool"]
+    assert tool_msgs, "tool result message missing from agent transcript"
+    assert "ok" in str(tool_msgs[-1].content)