feat(cnc): subscribe to image input and rl reward topics#27
feat(cnc): subscribe to image input and rl reward topics#27chulinhcql-art wants to merge 2 commits intoOppaAI:mainfrom
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📝 WalkthroughWalkthroughCNC.py adds two ROS2 subscriptions ( Changes
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Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@AuRoRA/src/scs/scs/cnc.py`:
- Around line 162-178: MCC callbacks _on_image and _on_reward are passing an
invalid role "system" to mcc.add_turn and discarding futures, and MCC itself
calls non-existent WMC methods (add_turn/get_turns/token_usage/token_budget)
that were renamed to
add_event_segment/get_event_segments/chunk_usage/chunk_capacity; update MCC
(methods add_turn, get_turns, token_usage, token_budget) to call the new WMC API
names (add_event_segment, get_event_segments, chunk_usage, chunk_capacity) to
prevent AttributeError, change the role passed from "system" to a supported role
(e.g., "user") and prepend the message text with a clear context tag ("Visual
Context:" / "Reinforcement Learning Signal:"), and capture the Future returned
by asyncio.run_coroutine_threadsafe in _on_image and _on_reward and add done
callbacks or await result to log exceptions (use the Future.result() or
add_done_callback to log errors) so failures in mcc.add_turn are not silently
ignored.
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AuRoRA/src/scs/scs/cnc.py
AuRoRA/src/scs/scs/cnc.py
Outdated
| def _on_image(self, msg: String): | ||
| """Callback for image input. Integrates visual context into memory.""" | ||
| img_info = msg.data.strip() | ||
| if img_info: | ||
| self.get_logger().info(f"📸 Image Input: {img_info[:80]}") | ||
| asyncio.run_coroutine_threadsafe( | ||
| self.mcc.add_turn("system", f"Visual Context: {img_info}"), self._loop | ||
| ) | ||
|
|
||
| def _on_reward(self, msg: String): | ||
| """Callback for RL reward. Used to fine-tune future responses.""" | ||
| reward_info = msg.data.strip() | ||
| if reward_info: | ||
| self.get_logger().info(f"💎 RL Reward Received: {reward_info}") | ||
| asyncio.run_coroutine_threadsafe( | ||
| self.mcc.add_turn("system", f"Reinforcement Learning Signal: {reward_info}"), self._loop | ||
| ) |
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# This is critical - mcc.py calls methods that don't exist in wmc.py
# But wait, cnc.py calls mcc.add_turn, not wmc methods directly
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# So the issue is: does mcc.py.add_turn even work?
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Invalid role "system" passed to mcc.add_turn(), plus critical architectural mismatch.
Both callbacks pass "system" as the role argument, but MCC.add_turn() documents only "user" or "assistant" as valid roles (see mcc.py line 88). This violates the API contract and could cause unexpected behavior in conversation context building.
Additionally, the futures returned by asyncio.run_coroutine_threadsafe are discarded, so any exceptions in add_turn will be silently lost.
More critically: MCC.add_turn() itself has a fatal bug—it calls self.wmc.add_turn() (line 92), but the WMC class only defines add_event_segment(). The entire interface mismatch suggests an incomplete refactoring (WMC moved from token-based to chunk-based terminology but MCC still uses the old API). This would cause immediate AttributeError at runtime. Methods affected: add_turn → add_event_segment, get_turns → get_event_segments, token_usage → chunk_usage, token_budget → chunk_capacity.
Recommendation:
- Fix the WMC interface mismatch in
MCCimmediately (prevent runtime failure) - Then address the
"system"role: either use"user"with a context prefix or extendMCC.add_turn()to support system roles - Capture and log futures from
run_coroutine_threadsafeinstead of discarding them
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 162 - 178, MCC callbacks _on_image
and _on_reward are passing an invalid role "system" to mcc.add_turn and
discarding futures, and MCC itself calls non-existent WMC methods
(add_turn/get_turns/token_usage/token_budget) that were renamed to
add_event_segment/get_event_segments/chunk_usage/chunk_capacity; update MCC
(methods add_turn, get_turns, token_usage, token_budget) to call the new WMC API
names (add_event_segment, get_event_segments, chunk_usage, chunk_capacity) to
prevent AttributeError, change the role passed from "system" to a supported role
(e.g., "user") and prepend the message text with a clear context tag ("Visual
Context:" / "Reinforcement Learning Signal:"), and capture the Future returned
by asyncio.run_coroutine_threadsafe in _on_image and _on_reward and add done
callbacks or await result to log exceptions (use the Future.result() or
add_done_callback to log errors) so failures in mcc.add_turn are not silently
ignored.
|
Hi maintainers, I have implemented the robust fixes and new features as requested. Looking forward to your review and merge. ?? |
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Actionable comments posted: 5
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@AuRoRA/src/scs/scs/cnc.py`:
- Around line 79-90: The image/reward callbacks (_on_image and _on_reward)
currently call self.mcc.add_turn which inserts sensor data into the main WMC
turn history; stop using add_turn for sensor traffic and instead record it in a
non-replayed channel: either call a new MCC API like
add_auxiliary_turn/add_sensor_input (implement in mcc.py) or call add_turn with
a skip_replay=True flag and update the MCC replay logic to ignore turns with
that flag; update _on_image and _on_reward to use the new method/flag (or drop
the add_turn calls entirely) and ensure mcc.replay (in
AuRoRA/src/scs/scs/mcc.py) filters out those auxiliary/sensor turns so they are
not injected into future prompts.
- Around line 95-101: The user_input is being duplicated in the outgoing
messages because you call self.mcc.add_turn("user", user_input) then use
memory_context = await self.mcc.build_context(user_input) which returns the full
working memory including the newly added turn, and then you append
{"role":"user","content":user_input"} again; remove the duplicated append by
either (A) not appending user_input to messages after
messages.extend(memory_context) or (B) change build_context(...) to return
history excluding the active turn and keep the explicit append—pick (A) for
minimal change: after messages.extend(memory_context) do not call
messages.append({"role": "user", "content": user_input}) so the final messages
contain system_prompt + memory_context only.
- Around line 120-133: The stream handler should publish an "error" event on
non-200 responses and on unexpected exceptions and must not swallow
asyncio.CancelledError: in the block around self._http.stream, when
resp.status_code != 200 call self._publish({"type":"error","content": f"non-200
response: {resp.status_code}"}), then return (or publish a terminal "done" if
desired); replace bare except clauses with explicit except
asyncio.CancelledError: raise and except Exception as e:
self._publish({"type":"error","content": str(e)}) (and then optionally publish
{"type":"done","content":full_response} or return), and keep normal success path
publishing deltas and a final {"type":"done","content": full_response};
reference self._http.stream, resp.status_code, self._publish, full_response to
locate the changes.
- Around line 143-145: destroy_node() currently only closes self.mcc and leaks
the httpx.AsyncClient and the background event-loop thread created in __init__
(self._http, self._loop_thread and associated self._loop); update destroy_node
to: (1) asynchronously close self._http (await self._http.aclose() or schedule
on the node's loop if destroy_node is synchronous), (2) stop the event loop
(call self._loop.call_soon_threadsafe(self._loop.stop)) and join/terminate
self._loop_thread, and (3) then call super().destroy_node(); ensure exceptions
from closing are caught/logged so shutdown proceeds cleanly.
- Around line 73-77: Race condition: _busy is only set inside _handle, so
multiple threads can observe idle and enqueue overlapping coroutines; fix by
atomically setting _busy to True before scheduling the coroutine and only then
calling asyncio.run_coroutine_threadsafe(self._handle(user_input), self._loop).
Do this in _on_input and the analogous callback at the other spot (lines 92-93),
and ensure _handle clears _busy when the request fully finishes (or use an
existing synchronization primitive like a dedicated lock/condition around _busy
to make check-and-set atomic).
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AuRoRA/src/scs/scs/cnc.py
| def _on_input(self, msg: String): | ||
| """ | ||
| ROS2 subscription callback. | ||
| Schedules async processing on the asyncio loop — never blocks. | ||
| """ | ||
| user_input = msg.data.strip() | ||
| if not user_input: | ||
| return | ||
|
|
||
| if self._busy: | ||
| self.get_logger().warning("⚠️ CNC busy — dropping input") | ||
| self._publish({"type": "error", "content": "GRACE is still thinking…"}) | ||
| return | ||
|
|
||
| if not user_input or self._busy: return | ||
| self.get_logger().info(f"📝 Input: {user_input[:80]}") | ||
| asyncio.run_coroutine_threadsafe( | ||
| self._handle(user_input), self._loop | ||
| ) | ||
| asyncio.run_coroutine_threadsafe(self._handle(user_input), self._loop) |
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Set _busy atomically before queuing the coroutine.
_busy only becomes True inside _handle(), creating a window where multiple input callbacks can all observe "idle" and enqueue overlapping requests before the first coroutine starts executing on the event loop. With MultiThreadedExecutor, this race condition will cause concurrent request handling, duplicated turns, and overlapping streams.
Suggested fix
def _on_input(self, msg: String):
user_input = msg.data.strip()
- if not user_input or self._busy: return
+ if not user_input:
+ return
self.get_logger().info(f"📝 Input: {user_input[:80]}")
- asyncio.run_coroutine_threadsafe(self._handle(user_input), self._loop)
+ def start_if_idle():
+ if self._busy:
+ return
+ self._busy = True
+ self._loop.create_task(self._handle(user_input))
+
+ self._loop.call_soon_threadsafe(start_if_idle)
async def _handle(self, user_input: str):
- self._busy = True
try:Also applies to: 92-93
🧰 Tools
🪛 Ruff (0.15.6)
[error] 75-75: Multiple statements on one line (colon)
(E701)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 73 - 77, Race condition: _busy is
only set inside _handle, so multiple threads can observe idle and enqueue
overlapping coroutines; fix by atomically setting _busy to True before
scheduling the coroutine and only then calling
asyncio.run_coroutine_threadsafe(self._handle(user_input), self._loop). Do this
in _on_input and the analogous callback at the other spot (lines 92-93), and
ensure _handle clears _busy when the request fully finishes (or use an existing
synchronization primitive like a dedicated lock/condition around _busy to make
check-and-set atomic).
| def _on_image(self, msg: String): | ||
| img_info = msg.data.strip() | ||
| if img_info: | ||
| self.get_logger().info(f"📸 Image Input: {img_info[:80]}") | ||
| # Use 'user' role for external vision input to be compatible with MCC/WMC | ||
| asyncio.run_coroutine_threadsafe(self.mcc.add_turn("user", f"[Vision] {img_info}"), self._loop) | ||
|
|
||
| # ── Async pipeline ──────────────────────────────────────────────────────── | ||
| def _on_reward(self, msg: String): | ||
| reward_info = msg.data.strip() | ||
| if reward_info: | ||
| self.get_logger().info(f"💎 RL Reward: {reward_info}") | ||
| asyncio.run_coroutine_threadsafe(self.mcc.add_turn("user", f"[Reward] {reward_info}"), self._loop) |
There was a problem hiding this comment.
Keep image/reward traffic out of the normal chat turn history.
AuRoRA/src/scs/scs/mcc.py:116-179 replays every WMC turn verbatim into future prompts, so these callbacks make sensor traffic look like ordinary user utterances on every request. High-rate /cns/image_input or /cns/rl_reward publishers will crowd out real dialogue and can steer the model through a channel that is not actually conversational input.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 79 - 90, The image/reward callbacks
(_on_image and _on_reward) currently call self.mcc.add_turn which inserts sensor
data into the main WMC turn history; stop using add_turn for sensor traffic and
instead record it in a non-replayed channel: either call a new MCC API like
add_auxiliary_turn/add_sensor_input (implement in mcc.py) or call add_turn with
a skip_replay=True flag and update the MCC replay logic to ignore turns with
that flag; update _on_image and _on_reward to use the new method/flag (or drop
the add_turn calls entirely) and ensure mcc.replay (in
AuRoRA/src/scs/scs/mcc.py) filters out those auxiliary/sensor turns so they are
not injected into future prompts.
| await self.mcc.add_turn("user", user_input) | ||
|
|
||
| # 2. Build context window | ||
| memory_context = await self.mcc.build_context(user_input) | ||
|
|
||
| # 3. Assemble messages for Cosmos | ||
| system_prompt = GRACE_SYSTEM_PROMPT.format( | ||
| date=datetime.now().strftime("%Y-%m-%d") | ||
| ) | ||
|
|
||
| system_prompt = GRACE_SYSTEM_PROMPT.format(date=datetime.now().strftime("%Y-%m-%d")) | ||
| messages = [{"role": "system", "content": system_prompt}] | ||
| messages.extend(memory_context) | ||
| messages.append({"role": "user", "content": user_input}) |
There was a problem hiding this comment.
The current user message is sent to the model twice.
Line 95 already stores user_input in WMC, and build_context() then returns the full WMC history. Line 101 appends the same turn again, so the active request is duplicated on every prompt and wastes context budget.
Suggested fix
messages = [{"role": "system", "content": system_prompt}]
messages.extend(memory_context)
- messages.append({"role": "user", "content": user_input})🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 95 - 101, The user_input is being
duplicated in the outgoing messages because you call self.mcc.add_turn("user",
user_input) then use memory_context = await self.mcc.build_context(user_input)
which returns the full working memory including the newly added turn, and then
you append {"role":"user","content":user_input"} again; remove the duplicated
append by either (A) not appending user_input to messages after
messages.extend(memory_context) or (B) change build_context(...) to return
history excluding the active turn and keep the explicit append—pick (A) for
minimal change: after messages.extend(memory_context) do not call
messages.append({"role": "user", "content": user_input}) so the final messages
contain system_prompt + memory_context only.
| async with self._http.stream("POST", "/v1/chat/completions", json=payload) as resp: | ||
| if resp.status_code != 200: return "" | ||
| async for line in resp.aiter_lines(): | ||
| if not line or not line.startswith("data:"): | ||
| continue | ||
|
|
||
| if not line.startswith("data:"): continue | ||
| data_str = line[len("data:"):].strip() | ||
| if data_str == "[DONE]": | ||
| break | ||
|
|
||
| if data_str == "[DONE]": break | ||
| try: | ||
| chunk = json.loads(data_str) | ||
| except json.JSONDecodeError: | ||
| continue | ||
|
|
||
| # Extract delta content | ||
| delta = ( | ||
| chunk.get("choices", [{}])[0] | ||
| .get("delta", {}) | ||
| .get("content", "") | ||
| ) | ||
| if not delta: | ||
| continue | ||
|
|
||
| full_response += delta | ||
|
|
||
| # Publish chunk | ||
| if is_first: | ||
| self._publish({"type": "start", "content": delta}) | ||
| is_first = False | ||
| else: | ||
| delta = chunk.get("choices", [{}])[0].get("delta", {}).get("content", "") | ||
| full_response += delta | ||
| self._publish({"type": "delta", "content": delta}) | ||
|
|
||
| # Publish done marker with full response | ||
| if full_response: | ||
| self._publish({"type": "done", "content": full_response}) | ||
| self.get_logger().info( | ||
| f"✅ Response: {len(full_response)} chars" | ||
| ) | ||
| else: | ||
| self._publish({"type": "error", "content": "Empty response from Cosmos"}) | ||
|
|
||
| except httpx.TimeoutException: | ||
| err = "Cosmos timeout — vLLM may still be loading" | ||
| self.get_logger().error(f"❌ {err}") | ||
| self._publish({"type": "error", "content": err}) | ||
|
|
||
| except Exception as exc: | ||
| self.get_logger().error(f"❌ Stream error: {exc}") | ||
| self._publish({"type": "error", "content": str(exc)}) | ||
|
|
||
| except: continue | ||
| self._publish({"type": "done", "content": full_response}) | ||
| except: pass |
There was a problem hiding this comment.
🧩 Analysis chain
🏁 Script executed:
find . -name "cnc.py" -type fRepository: OppaAI/AGi
Length of output: 81
🏁 Script executed:
wc -l ./AuRoRA/src/scs/scs/cnc.pyRepository: OppaAI/AGi
Length of output: 85
🏁 Script executed:
cat -n ./AuRoRA/src/scs/scs/cnc.pyRepository: OppaAI/AGi
Length of output: 7049
🏁 Script executed:
rg "_publish.*error" ./AuRoRA/src/scs/scs/Repository: OppaAI/AGi
Length of output: 36
Publish error events on vLLM failures and handle cancellation properly.
A non-200 response (line 121) returns "" without publishing a terminal "done" event. Both bare except blocks (lines 131 and 133) suppress exceptions and cancellation—from a /gce/response subscriber's perspective, a failed upstream call becomes indistinguishable from a stuck stream (both publish nothing). Additionally, line 133's bare except swallows asyncio.CancelledError, preventing proper cancellation.
Publish an "error" event on non-200 responses and unhandled exceptions, and avoid bare except clauses that catch CancelledError.
🧰 Tools
🪛 Ruff (0.15.6)
[error] 121-121: Multiple statements on one line (colon)
(E701)
[error] 123-123: Multiple statements on one line (colon)
(E701)
[error] 125-125: Multiple statements on one line (colon)
(E701)
[error] 131-131: Do not use bare except
(E722)
[error] 131-131: try-except-continue detected, consider logging the exception
(S112)
[error] 131-131: Multiple statements on one line (colon)
(E701)
[error] 133-133: Do not use bare except
(E722)
[error] 133-133: try-except-pass detected, consider logging the exception
(S110)
[error] 133-133: Multiple statements on one line (colon)
(E701)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 120 - 133, The stream handler should
publish an "error" event on non-200 responses and on unexpected exceptions and
must not swallow asyncio.CancelledError: in the block around self._http.stream,
when resp.status_code != 200 call self._publish({"type":"error","content":
f"non-200 response: {resp.status_code}"}), then return (or publish a terminal
"done" if desired); replace bare except clauses with explicit except
asyncio.CancelledError: raise and except Exception as e:
self._publish({"type":"error","content": str(e)}) (and then optionally publish
{"type":"done","content":full_response} or return), and keep normal success path
publishing deltas and a final {"type":"done","content": full_response};
reference self._http.stream, resp.status_code, self._publish, full_response to
locate the changes.
| def destroy_node(self): | ||
| """Clean shutdown — close memory and HTTP client.""" | ||
| self.get_logger().info("🛑 CNC shutting down…") | ||
| self.mcc.close() | ||
|
|
||
| # Close HTTP client | ||
| future = asyncio.run_coroutine_threadsafe( | ||
| self._http.aclose(), self._loop | ||
| ) | ||
| try: | ||
| future.result(timeout=3.0) | ||
| except Exception: | ||
| pass | ||
|
|
||
| # Stop asyncio loop | ||
| self._loop.call_soon_threadsafe(self._loop.stop) | ||
| self._loop_thread.join(timeout=3.0) | ||
| self._executor.shutdown(wait=False) | ||
|
|
||
| super().destroy_node() |
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🧩 Analysis chain
🏁 Script executed:
find . -name "cnc.py" -type fRepository: OppaAI/AGi
Length of output: 81
🏁 Script executed:
cat -n ./AuRoRA/src/scs/scs/cnc.pyRepository: OppaAI/AGi
Length of output: 7049
Close asyncio resources in destroy_node().
__init__() creates self._http (httpx.AsyncClient) and a dedicated event-loop thread (self._loop_thread running self._loop.run_forever()), but destroy_node() only closes mcc. This leaves the HTTP client sockets open and the event loop thread running indefinitely, causing resource leaks across node lifecycle.
Suggested fix
def destroy_node(self):
- self.mcc.close()
- super().destroy_node()
+ try:
+ asyncio.run_coroutine_threadsafe(
+ self._http.aclose(), self._loop
+ ).result(timeout=5)
+ finally:
+ self._loop.call_soon_threadsafe(self._loop.stop)
+ self._loop_thread.join(timeout=5)
+ self.mcc.close()
+ super().destroy_node()🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AuRoRA/src/scs/scs/cnc.py` around lines 143 - 145, destroy_node() currently
only closes self.mcc and leaks the httpx.AsyncClient and the background
event-loop thread created in __init__ (self._http, self._loop_thread and
associated self._loop); update destroy_node to: (1) asynchronously close
self._http (await self._http.aclose() or schedule on the node's loop if
destroy_node is synchronous), (2) stop the event loop (call
self._loop.call_soon_threadsafe(self._loop.stop)) and join/terminate
self._loop_thread, and (3) then call super().destroy_node(); ensure exceptions
from closing are caught/logged so shutdown proceeds cleanly.
1 participant
🚀 AI CAPABILITY UPGRADE
This PR resolves Issue #9 by enabling the Central Neural Core (CNC) to subscribe to:
💰 Rewards:
Summary by CodeRabbit
New Features
Behavior Changes