Fix thread safety in MetricsCollector and parent process metrics registry

METRICS.md

@@ -33,6 +33,7 @@ The Conductor Python SDK includes built-in metrics collection using Prometheus t
 | `task_result_size` | Gauge | `taskType` | Size of task result payload (bytes) |
 | `task_execution_queue_full_total` | Counter | `taskType` | Number of times execution queue was full |
 | `task_paused_total` | Counter | `taskType` | Number of polls while worker paused |
+| `worker_restart_total` | Counter | `taskType` | Number of times TaskHandler restarted a worker subprocess |
 | `external_payload_used_total` | Counter | `taskType`, `payloadType` | External payload storage usage count |
 | `workflow_input_size` | Gauge | `workflowType`, `version` | Workflow input payload size (bytes) |
 | `workflow_start_error_total` | Counter | `workflowType`, `exception` | Workflow start error count |

docs/WORKER.md

@@ -259,12 +259,64 @@ workers = [
     )
 ]
 
-# If there are decorated workers in your application, scan_for_annotated_workers should be set
-# default value of scan_for_annotated_workers is False
+# TaskHandler scans for @worker_task decorated workers by default.
+# Set scan_for_annotated_workers=False if you want to disable auto-discovery.
 with TaskHandler(workers, configuration, scan_for_annotated_workers=True) as task_handler:
     task_handler.start_processes()
 ```
 
+### Resilience: auto-restart and health checks
+
+If you run workers as a long-lived service (e.g., alongside FastAPI/Uvicorn), you can optionally enable process
+supervision so the `TaskHandler` monitors worker processes and restarts them if they exit unexpectedly:
+
+```python
+with TaskHandler(
+    workers,
+    configuration,
+    scan_for_annotated_workers=True,
+    # Enabled by default. Set to False to disable supervision.
+    monitor_processes=True,
+    restart_on_failure=True,
+) as task_handler:
+    task_handler.start_processes()
+```
+
+For a `/healthcheck` endpoint, you can use:
+
+```python
+task_handler.is_healthy()
+task_handler.get_worker_process_status()
+```
+
+To disable restarts/monitoring (e.g., for local debugging), set:
+
+```python
+TaskHandler(..., monitor_processes=False, restart_on_failure=False)
+```
+
+### Mitigation for intermittent HTTP/2 connection termination
+
+The SDK uses `httpx` for outbound calls to the Conductor/Orkes server. By default, it enables HTTP/2 for these calls.
+In some environments (certain proxies/load balancers/NATs), long-lived HTTP/2 connections may be terminated, which can
+surface as errors like `httpcore.RemoteProtocolError: <ConnectionTerminated ...>`.
+
+The SDK automatically attempts to recover by recreating the underlying HTTP client and retrying the request once.
+If your environment is still unstable with HTTP/2, you can force the SDK to use HTTP/1.1 instead via an environment
+variable.
+
+#### `CONDUCTOR_HTTP2_ENABLED`
+
+- **What it does**: Controls whether the Conductor Python SDK uses HTTP/2 for outbound requests to the Conductor server.
+- **Default**: `true` (HTTP/2 enabled).
+- **Scope**: Affects all SDK clients (workers, `OrkesClients`, sync + async). It does *not* change your FastAPI/Uvicorn
+  server behavior; it only changes how the SDK talks to Conductor.
+- **Values**: `false|0|no|off` disables HTTP/2. Anything else enables it.
+
+```shell
+export CONDUCTOR_HTTP2_ENABLED=false
+```
+
 If you paste the above code in a file called main.py, you can launch the workers by running:
 ```shell
 python3 main.py

examples/README.md

@@ -25,6 +25,7 @@ python examples/workers_e2e.py
 |------|-------------|-----|
 | **workers_e2e.py** | ⭐ Start here - sync + async workers | `python examples/workers_e2e.py` |
 | **worker_example.py** | Comprehensive patterns (None returns, TaskInProgress) | `python examples/worker_example.py` |
+| **fastapi_worker_service.py** | FastAPI exposing a workflow as an API (+ workers) | `uvicorn examples.fastapi_worker_service:app --port 8081 --workers 1` |
 | **worker_configuration_example.py** | Hierarchical configuration (env vars) | `python examples/worker_configuration_example.py` |
 | **task_context_example.py** | Task context (logs, poll_count, task_id) | `python examples/task_context_example.py` |
 | **task_workers.py** | Task worker patterns with dataclasses | `python examples/task_workers.py` |
@@ -416,4 +417,4 @@ export conductor.worker.all.thread_count=20
 ---
 
 **Repository**: https://github.com/conductor-oss/conductor-python
-**License**: Apache 2.0
+**License**: Apache 2.0

examples/fastapi_worker_service.py

@@ -0,0 +1,213 @@
+"""
+FastAPI + Conductor workers in one process.
+
+Install (example-only deps):
+    pip install fastapi uvicorn
+
+Run (single web worker; TaskHandler will spawn one process per Conductor worker):
+    export CONDUCTOR_SERVER_URL="http://localhost:8080/api"
+    export CONDUCTOR_AUTH_KEY="..."
+    export CONDUCTOR_AUTH_SECRET="..."
+    uvicorn examples.fastapi_worker_service:app --host 0.0.0.0 --port 8081 --workers 1
+
+Trigger the workflow via API (waits up to 10s for completion):
+    curl -s -X POST http://localhost:8081/v1/hello \\
+      -H 'content-type: application/json' \\
+      -d '{"name":"Ada","a":2,"b":3}' | jq .
+
+Notes:
+  - Do NOT run uvicorn with multiple web workers unless you explicitly want multiple independent TaskHandlers polling.
+  - TaskHandler supervision is enabled by default (monitor + restart worker subprocesses).
+"""
+
+from __future__ import annotations
+
+import os
+from contextlib import asynccontextmanager
+from typing import Optional
+
+from fastapi import FastAPI
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel, Field
+
+from conductor.client.automator.task_handler import TaskHandler
+from conductor.client.configuration.configuration import Configuration
+from conductor.client.context.task_context import get_task_context
+from conductor.client.orkes_clients import OrkesClients
+from conductor.client.worker.worker_task import worker_task
+from conductor.client.workflow.conductor_workflow import ConductorWorkflow
+from conductor.client.workflow.executor.workflow_executor import WorkflowExecutor
+
+
+# ---------------------------------------------------------------------------
+# Example worker(s)
+# ---------------------------------------------------------------------------
+
+@worker_task(
+    task_definition_name="fastapi_normalize_name",
+    poll_interval_millis=100,
+    register_task_def=True,
+    overwrite_task_def=False,
+)
+def normalize_name(name: str) -> str:
+    # This shows how to access task context safely.
+    _ = get_task_context()
+    return name.strip().title()
+
+
+@worker_task(
+    task_definition_name="fastapi_add_numbers",
+    poll_interval_millis=100,
+    register_task_def=True,
+    overwrite_task_def=False,
+)
+def add_numbers(a: int, b: int) -> int:
+    _ = get_task_context()
+    return a + b
+
+
+@worker_task(
+    task_definition_name="fastapi_build_message",
+    poll_interval_millis=100,
+    register_task_def=True,
+    overwrite_task_def=False,
+)
+def build_message(normalized_name: str, total: int) -> dict:
+    ctx = get_task_context()
+    return {
+        "message": f"Hello {normalized_name}! {total=}",
+        "normalized_name": normalized_name,
+        "total": total,
+        "task_id": ctx.get_task_id(),
+        "workflow_id": ctx.get_workflow_instance_id(),
+    }
+
+
+def _build_hello_workflow(executor: WorkflowExecutor) -> ConductorWorkflow:
+    workflow = ConductorWorkflow(executor=executor, name="fastapi_hello_workflow", version=1)
+
+    t1 = normalize_name(task_ref_name="normalize_name_ref", name=workflow.input("name"))
+    t2 = add_numbers(task_ref_name="add_numbers_ref", a=workflow.input("a"), b=workflow.input("b"))
+    t3 = build_message(
+        task_ref_name="build_message_ref",
+        normalized_name=t1.output("result"),
+        total=t2.output("result"),
+    )
+
+    workflow >> t1 >> t2 >> t3
+
+    workflow.output_parameters(
+        output_parameters={
+            "message": t3.output("message"),
+            "normalized_name": t3.output("normalized_name"),
+            "total": t3.output("total"),
+        }
+    )
+
+    return workflow
+
+
+class HelloRequest(BaseModel):
+    name: str = Field(default="World", description="Name to greet")
+    a: int = Field(default=1, description="First number")
+    b: int = Field(default=2, description="Second number")
+
+
+# ---------------------------------------------------------------------------
+# FastAPI app + TaskHandler lifecycle
+# ---------------------------------------------------------------------------
+
+task_handler: Optional[TaskHandler] = None
+workflow_executor: Optional[WorkflowExecutor] = None
+api_config: Optional[Configuration] = None
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    global task_handler, workflow_executor, api_config
+
+    api_config = Configuration()
+    clients = OrkesClients(configuration=api_config)
+    workflow_executor = clients.get_workflow_executor()
+
+    # scan_for_annotated_workers=True will pick up @worker_task functions in this module.
+    task_handler = TaskHandler(
+        workers=[],
+        configuration=api_config,
+        scan_for_annotated_workers=True,
+        # Defaults are already True, but keeping these explicit in the example:
+        monitor_processes=True,
+        restart_on_failure=True,
+    )
+    task_handler.start_processes()
+
+    try:
+        yield
+    finally:
+        if task_handler is not None:
+            task_handler.stop_processes()
+            task_handler = None
+        workflow_executor = None
+        api_config = None
+
+
+app = FastAPI(lifespan=lifespan)
+
+
+@app.get("/healthcheck")
+def healthcheck():
+    # 503 if worker processes aren't healthy; useful for container orchestrators.
+    if task_handler is None:
+        return JSONResponse({"ok": False, "detail": "workers_not_started"}, status_code=503)
+
+    ok = task_handler.is_healthy()
+    payload = {
+        "ok": ok,
+        "workers": task_handler.get_worker_process_status(),
+    }
+    return JSONResponse(payload, status_code=200 if ok else 503)
+
+
+@app.post("/v1/hello")
+def hello(req: HelloRequest):
+    """
+    Expose a Conductor workflow as an API:
+    - Builds an inline workflow definition with 3 SIMPLE tasks
+    - Starts it and waits up to 10 seconds for completion
+    - Returns workflow output as the HTTP response
+    """
+    if task_handler is None or workflow_executor is None or api_config is None:
+        return JSONResponse({"ok": False, "detail": "service_not_ready"}, status_code=503)
+    if not task_handler.is_healthy():
+        return JSONResponse(
+            {"ok": False, "detail": "workers_unhealthy", "workers": task_handler.get_worker_process_status()},
+            status_code=503,
+        )
+
+    workflow = _build_hello_workflow(executor=workflow_executor)
+    payload = req.model_dump() if hasattr(req, "model_dump") else req.dict()  # pydantic v2/v1
+
+    try:
+        run = workflow.execute(workflow_input=payload, wait_for_seconds=10)
+    except Exception as e:
+        return JSONResponse({"ok": False, "detail": "workflow_start_failed", "error": str(e)}, status_code=502)
+
+    response = {
+        "ok": run.status == "COMPLETED",
+        "workflow_id": run.workflow_id,
+        "status": run.status,
+        "output": run.output,
+        "ui_url": f"{api_config.ui_host}/execution/{run.workflow_id}",
+    }
+    return JSONResponse(response, status_code=200 if run.status == "COMPLETED" else 202)
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(
+        "examples.fastapi_worker_service:app",
+        host="0.0.0.0",
+        port=int(os.getenv("PORT", "8081")),
+        workers=1,
+    )

src/conductor/client/automator/json_schema_generator.py

@@ -188,11 +188,13 @@ def _type_to_json_schema(type_hint, strict_schema: bool = False) -> Optional[Dic
         if len(non_none_args) == 1:
             # Optional[T] case
             inner_schema = _type_to_json_schema(non_none_args[0], strict_schema)
-            if inner_schema:
-                # For optional, we could use oneOf or just mark as nullable
-                # Using nullable for simplicity
-                inner_schema['nullable'] = True
-                return inner_schema
+            if inner_schema is not None:
+                # Draft-07 JSON Schema does not support OpenAPI's `nullable`.
+                # Represent Optional[T] as a union with null.
+                if inner_schema == {}:
+                    # "Any" already includes null, so keep it minimal.
+                    return inner_schema
+                return {"anyOf": [inner_schema, {"type": "null"}]}
         # Multiple non-None types in Union - too complex
         return None