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Cookbook model workflow fixes

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pewdiepie-archdaemon
2026-06-21 11:02:35 +00:00
parent 8c46172e87
commit c504214925
38 changed files with 3042 additions and 459 deletions
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src/task_scheduler.py
+32 -13
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@@ -833,6 +833,14 @@ class TaskScheduler:
owner=task.owner,
body=run.result if output == "notification" else None,
)
elif run.status == "error":
self.add_notification(
task.name,
"error",
task_id,
owner=task.owner,
body=run.error or run.result,
)
# Log result to the assistant chat so all task activity is visible.
# Skip skipped/error rows — user shouldn't see "skipped: …" noise
@@ -1406,12 +1414,18 @@ class TaskScheduler:
)
except Exception as e:
logger.warning(f"Agent loop failed for task '{task.name}', falling back to simple call: {e}")
from src.llm_core import llm_call_async
from src.task_endpoint import task_llm_call_async
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": task.prompt},
]
result = await llm_call_async(url=endpoint_url, model=model, messages=messages, timeout=120)
result = await task_llm_call_async(
messages,
fallback_url=endpoint_url,
fallback_model=model,
owner=task.owner,
timeout=120,
)
# Strip the model's chain-of-thought before saving/delivering. Task
# output is LLM-only, so prose=True (which also removes untagged
@@ -1636,13 +1650,17 @@ class TaskScheduler:
# Honor per-task max_steps (defense against runaway agent loops).
# Falls back to 20 if not set — the historical default.
_task_max_rounds = task.max_steps if task.max_steps and task.max_steps > 0 else 20
# Tasks are background workloads — they share the Utility model's
# fallback chain (Settings → Utility Model → Fallbacks). A downed
# primary endpoint won't silently yield `(no output)` — same recipe
# chat uses but with the utility list (`utility_model_fallbacks`).
# Tasks are background workloads: use the shared task fallback chain
# behind the primary endpoint so a downed primary won't silently yield
# `(no output)`.
try:
from src.endpoint_resolver import resolve_utility_fallback_candidates
_task_fallbacks = resolve_utility_fallback_candidates(owner=task.owner or None)
from src.task_endpoint import resolve_task_candidates
_task_fallbacks = resolve_task_candidates(
fallback_url=endpoint_url,
fallback_model=model,
fallback_headers=headers,
owner=task.owner or None,
)[1:]
except Exception:
_task_fallbacks = []
async for event_str in stream_agent_loop(
@@ -1679,21 +1697,22 @@ class TaskScheduler:
# asking it to summarize what it did. Guarantees output.
if not full_text.strip():
try:
from src.llm_core import llm_call_async_with_fallback
from src.endpoint_resolver import resolve_utility_fallback_candidates
from src.task_endpoint import task_llm_call_async
grace_context = "You ran out of steps. "
if tool_results:
grace_context += "Here's what your tools returned:\n" + "\n".join(tool_results[-5:])
else:
grace_context += "No tool results were captured."
grace_context += "\n\nSummarize what you accomplished and what's still pending. Be concise."
_grace_candidates = [(endpoint_url, model, headers)] + resolve_utility_fallback_candidates(owner=task.owner or None)
full_text = await llm_call_async_with_fallback(
_grace_candidates,
full_text = await task_llm_call_async(
messages=[
{"role": "system", "content": system_content},
{"role": "user", "content": grace_context},
],
fallback_url=endpoint_url,
fallback_model=model,
fallback_headers=headers,
owner=task.owner or None,
timeout=30,
)
full_text = (full_text or "").strip()