feat: harden agent verification and runtime contracts
Introduce two-gate checker settlement, explicit graph visibility and checkpoints, structured LLM reliability, centralized action specifications, and corresponding tests and design documentation.
This commit is contained in:
somew1nd committed
1 parent
ddfa420945
commit
cbe8f4f0c6
106 files changed
+11542
-4445
No files matched your search
@@ -49,9 +49,11 @@ from artemis.controllers.unified_controller import UnifiedMobileController
|
||||
from artemis.data_engine.trace import trace
|
||||
from artemis.graph.perception import _check_injected_instruction_file
|
||||
from artemis.graph.state import State
|
||||
from artemis.llm.structured import ParseFailure, parse_structured
|
||||
from artemis.mcp.action_executor import McpActionExecutor
|
||||
from artemis.services.llm import (
|
||||
RobustChatModelWrapper,
|
||||
acomplete,
|
||||
get_google_llm,
|
||||
get_llm,
|
||||
invoke_llm_with_timeout_message,
|
||||
@@ -182,20 +184,23 @@ class FlashRunner:
|
||||
# Check for real-time injected instructions
|
||||
if self.ctx.data_engine and self.ctx.data_engine.base_dir:
|
||||
try:
|
||||
injected_instruction = await asyncio.to_thread(
|
||||
injected_payload = await asyncio.to_thread(
|
||||
_check_injected_instruction_file,
|
||||
str(self.ctx.data_engine.base_dir),
|
||||
)
|
||||
if injected_instruction:
|
||||
messages.append(
|
||||
HumanMessage(
|
||||
content=(
|
||||
"[REAL-TIME INJECTED INSTRUCTION from user]:"
|
||||
f" {injected_instruction}\nYou MUST immediately follow"
|
||||
" this instruction and adjust your plan/actions."
|
||||
)
|
||||
)
|
||||
if injected_payload and injected_payload.get("instruction"):
|
||||
injected_text = (
|
||||
"[REAL-TIME INJECTED INSTRUCTION from user]:"
|
||||
f" {injected_payload['instruction']}\nYou MUST immediately"
|
||||
" follow this instruction and adjust your plan/actions."
|
||||
)
|
||||
if injected_payload.get("release_loop"):
|
||||
injected_text += (
|
||||
"\nThe user has explicitly authorized stopping any"
|
||||
" ongoing monitoring loop; you may now wrap up and"
|
||||
" complete the task."
|
||||
)
|
||||
messages.append(HumanMessage(content=injected_text))
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to check injected instruction in FlashRunner: {e}")
|
||||
|
||||
@@ -224,61 +229,12 @@ class FlashRunner:
|
||||
# Bind active tools
|
||||
bound_llm = llm.bind_tools(current_tools)
|
||||
|
||||
# Invoke Model with Streaming & Retry
|
||||
response = None
|
||||
max_retries = 3
|
||||
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
stream_exec_id = uuid.uuid4()
|
||||
|
||||
async def run_stream():
|
||||
full_response = None
|
||||
async for chunk in bound_llm.astream(messages):
|
||||
if full_response is None:
|
||||
full_response = chunk
|
||||
else:
|
||||
full_response += chunk
|
||||
|
||||
# Real-time token streaming to DataEngine for live UI display
|
||||
if (
|
||||
getattr(self, "ctx", None)
|
||||
and getattr(self.ctx, "data_engine", None)
|
||||
and getattr(chunk, "content", None)
|
||||
):
|
||||
text_to_stream = ""
|
||||
thinking_to_stream = ""
|
||||
if isinstance(chunk.content, str):
|
||||
text_to_stream = chunk.content
|
||||
elif isinstance(chunk.content, list):
|
||||
for item in chunk.content:
|
||||
if isinstance(item, str):
|
||||
text_to_stream += item
|
||||
elif isinstance(item, dict):
|
||||
if item.get("type") == "text":
|
||||
text_to_stream += item.get("text", "")
|
||||
elif item.get("type") == "thinking":
|
||||
thinking_to_stream += item.get("thinking", "")
|
||||
if text_to_stream:
|
||||
self.ctx.data_engine.stream_output(
|
||||
stream_exec_id, text_to_stream, is_thinking=False
|
||||
)
|
||||
if thinking_to_stream:
|
||||
self.ctx.data_engine.stream_output(
|
||||
stream_exec_id, thinking_to_stream, is_thinking=True
|
||||
)
|
||||
return full_response
|
||||
|
||||
response = await invoke_llm_with_timeout_message(
|
||||
run_stream(), timeout_seconds=10, hard_timeout=180
|
||||
)
|
||||
if response:
|
||||
break
|
||||
except Exception as e:
|
||||
logger.warning(f"FlashRunner LLM turn failed on attempt {attempt + 1}: {e}")
|
||||
if attempt == max_retries - 1:
|
||||
raise e
|
||||
await asyncio.sleep(2.0**attempt)
|
||||
# Invoke Model. Streaming, live-token UI deltas, classified
|
||||
# retries, and pause/resume are all owned by the LLM gateway
|
||||
# (acomplete); a typed LLMCallError propagates if it gives up.
|
||||
response = await invoke_llm_with_timeout_message(
|
||||
acomplete(bound_llm, messages), timeout_seconds=10, hard_timeout=180
|
||||
)
|
||||
|
||||
if response is None:
|
||||
break
|
||||
@@ -372,19 +328,20 @@ class FlashRunner:
|
||||
|
||||
# Fallback text parsing if tool_calls not parsed natively
|
||||
if not tool_calls and "```json" in raw_text:
|
||||
try:
|
||||
snippet = raw_text.split("```json")[1].split("```")[0].strip()
|
||||
parsed = json.loads(snippet)
|
||||
if isinstance(parsed, dict) and "name" in parsed:
|
||||
tool_calls = [
|
||||
{
|
||||
"name": parsed["name"],
|
||||
"args": parsed.get("args", {}),
|
||||
"id": str(uuid.uuid4()),
|
||||
}
|
||||
]
|
||||
except Exception:
|
||||
pass
|
||||
parsed = parse_structured(raw_text)
|
||||
if isinstance(parsed, ParseFailure):
|
||||
logger.warning(
|
||||
"FlashRunner response contained a JSON block that could"
|
||||
f" not be parsed: {parsed.error}"
|
||||
)
|
||||
elif isinstance(parsed, dict) and "name" in parsed:
|
||||
tool_calls = [
|
||||
{
|
||||
"name": parsed["name"],
|
||||
"args": parsed.get("args", {}),
|
||||
"id": str(uuid.uuid4()),
|
||||
}
|
||||
]
|
||||
|
||||
if not tool_calls:
|
||||
logger.info(
|
||||
|
||||
Reference in new issue
Block a user