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153 changes: 94 additions & 59 deletions gateway/platforms/api_server.py
Original file line number Diff line number Diff line change
Expand Up @@ -495,17 +495,21 @@ def _on_delta(delta):
if delta is not None:
_stream_q.put(delta)

# Start agent in background
# Start agent in background. agent_ref is a mutable container
# so the SSE writer can interrupt the agent on client disconnect.
agent_ref = [None]
agent_task = asyncio.ensure_future(self._run_agent(
user_message=user_message,
conversation_history=history,
ephemeral_system_prompt=system_prompt,
session_id=session_id,
stream_delta_callback=_on_delta,
agent_ref=agent_ref,
))

return await self._write_sse_chat_completion(
request, completion_id, model_name, created, _stream_q, agent_task
request, completion_id, model_name, created, _stream_q,
agent_task, agent_ref,
)

# Non-streaming: run the agent (with optional Idempotency-Key)
Expand Down Expand Up @@ -568,9 +572,14 @@ async def _compute_completion():

async def _write_sse_chat_completion(
self, request: "web.Request", completion_id: str, model: str,
created: int, stream_q, agent_task,
created: int, stream_q, agent_task, agent_ref=None,
) -> "web.StreamResponse":
"""Write real streaming SSE from agent's stream_delta_callback queue."""
"""Write real streaming SSE from agent's stream_delta_callback queue.

If the client disconnects mid-stream (network drop, browser tab close),
the agent is interrupted via ``agent.interrupt()`` so it stops making
LLM API calls, and the asyncio task wrapper is cancelled.
"""
import queue as _q

response = web.StreamResponse(
Expand All @@ -579,69 +588,87 @@ async def _write_sse_chat_completion(
)
await response.prepare(request)

# Role chunk
role_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}],
}
await response.write(f"data: {json.dumps(role_chunk)}\n\n".encode())
try:
# Role chunk
role_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"role": "assistant"}, "finish_reason": None}],
}
await response.write(f"data: {json.dumps(role_chunk)}\n\n".encode())

# Stream content chunks as they arrive from the agent
loop = asyncio.get_event_loop()
while True:
try:
delta = await loop.run_in_executor(None, lambda: stream_q.get(timeout=0.5))
except _q.Empty:
if agent_task.done():
# Drain any remaining items
while True:
try:
delta = stream_q.get_nowait()
if delta is None:
# Stream content chunks as they arrive from the agent
loop = asyncio.get_event_loop()
while True:
try:
delta = await loop.run_in_executor(None, lambda: stream_q.get(timeout=0.5))
except _q.Empty:
if agent_task.done():
# Drain any remaining items
while True:
try:
delta = stream_q.get_nowait()
if delta is None:
break
content_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"content": delta}, "finish_reason": None}],
}
await response.write(f"data: {json.dumps(content_chunk)}\n\n".encode())
except _q.Empty:
break
content_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"content": delta}, "finish_reason": None}],
}
await response.write(f"data: {json.dumps(content_chunk)}\n\n".encode())
except _q.Empty:
break
break
continue

if delta is None: # End of stream sentinel
break
continue

if delta is None: # End of stream sentinel
break
content_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"content": delta}, "finish_reason": None}],
}
await response.write(f"data: {json.dumps(content_chunk)}\n\n".encode())

# Get usage from completed agent
usage = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
try:
result, agent_usage = await agent_task
usage = agent_usage or usage
except Exception:
pass

content_chunk = {
# Finish chunk
finish_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {"content": delta}, "finish_reason": None}],
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
"usage": {
"prompt_tokens": usage.get("input_tokens", 0),
"completion_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
},
}
await response.write(f"data: {json.dumps(content_chunk)}\n\n".encode())

# Get usage from completed agent
usage = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
try:
result, agent_usage = await agent_task
usage = agent_usage or usage
except Exception:
pass

# Finish chunk
finish_chunk = {
"id": completion_id, "object": "chat.completion.chunk",
"created": created, "model": model,
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
"usage": {
"prompt_tokens": usage.get("input_tokens", 0),
"completion_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
},
}
await response.write(f"data: {json.dumps(finish_chunk)}\n\n".encode())
await response.write(b"data: [DONE]\n\n")
await response.write(f"data: {json.dumps(finish_chunk)}\n\n".encode())
await response.write(b"data: [DONE]\n\n")
except (ConnectionResetError, ConnectionAbortedError, BrokenPipeError, OSError):
# Client disconnected mid-stream. Interrupt the agent so it
# stops making LLM API calls at the next loop iteration, then
# cancel the asyncio task wrapper.
agent = agent_ref[0] if agent_ref else None
if agent is not None:
try:
agent.interrupt("SSE client disconnected")
except Exception:
pass
if not agent_task.done():
agent_task.cancel()
try:
await agent_task
except (asyncio.CancelledError, Exception):
pass
logger.info("SSE client disconnected; interrupted agent task %s", completion_id)

return response

Expand Down Expand Up @@ -1144,12 +1171,18 @@ async def _run_agent(
ephemeral_system_prompt: Optional[str] = None,
session_id: Optional[str] = None,
stream_delta_callback=None,
agent_ref: Optional[list] = None,
) -> tuple:
"""
Create an agent and run a conversation in a thread executor.

Returns ``(result_dict, usage_dict)`` where *usage_dict* contains
``input_tokens``, ``output_tokens`` and ``total_tokens``.

If *agent_ref* is a one-element list, the AIAgent instance is stored
at ``agent_ref[0]`` before ``run_conversation`` begins. This allows
callers (e.g. the SSE writer) to call ``agent.interrupt()`` from
another thread to stop in-progress LLM calls.
"""
loop = asyncio.get_event_loop()

Expand All @@ -1159,6 +1192,8 @@ def _run():
session_id=session_id,
stream_delta_callback=stream_delta_callback,
)
if agent_ref is not None:
agent_ref[0] = agent
result = agent.run_conversation(
user_message=user_message,
conversation_history=conversation_history,
Expand Down
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