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refactor: remove aggressive ERROR status filter from library agent search

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The ERROR status filter was too aggressive - a single failed execution
would exclude an agent from sub-agent composition, even if it had many
successful runs. Removed the filter for now.

Future enhancement: Add quality filtering based on execution success rate
or correctness_score (stored in AgentGraphExecution stats) rather than
the binary ERROR status.
This commit is contained in:
Zamil Majdy
2026-01-30 07:45:00 -06:00
parent be7e1ad9b6
commit aef705007b
1 changed files with 8 additions and 20 deletions
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28
autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py
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@@ -6,7 +6,6 @@ import uuid
from typing import Any, TypedDict
from backend.api.features.library import db as library_db
from backend.api.features.library import model as library_model
from backend.api.features.store import db as store_db
from backend.data.graph import (
Graph,
@@ -184,52 +183,41 @@ async def get_library_agents_for_generation(
search_query: str | None = None,
exclude_graph_id: str | None = None,
max_results: int = 15,
exclude_error_status: bool = True,
) -> list[LibraryAgentSummary]:
"""Fetch user's library agents formatted for Agent Generator.
Uses search-based fetching to return relevant agents instead of all agents.
This is more scalable for users with large libraries.
Quality filtering: By default, excludes agents with ERROR status to avoid
recommending broken or draft agents for sub-agent composition.
Args:
user_id: The user ID
search_query: Optional search term to find relevant agents (user's goal/description)
exclude_graph_id: Optional graph ID to exclude (prevents circular references)
max_results: Maximum number of agents to return (default 15)
exclude_error_status: Filter out agents with ERROR status (default True)
Returns:
List of LibraryAgentSummary with schemas for sub-agent composition
Note:
Future enhancement: Add quality filtering based on execution success rate
or correctness_score from AgentGraphExecution stats. The current
LibraryAgentStatus.ERROR is too aggressive (1 failed run = ERROR).
Better approach: filter by success rate (e.g., >50% successful runs)
or require at least 1 successful execution.
"""
try:
# Fetch more than needed to account for filtered out agents
fetch_size = max_results * 2 if exclude_error_status else max_results
response = await library_db.list_library_agents(
user_id=user_id,
search_term=search_query,
page=1,
page_size=fetch_size,
page_size=max_results,
)
results: list[LibraryAgentSummary] = []
for agent in response.agents:
if len(results) >= max_results:
break
if exclude_graph_id is not None and agent.graph_id == exclude_graph_id:
continue
# Quality filter: skip agents in ERROR state (broken/draft agents)
if (
exclude_error_status
and agent.status == library_model.LibraryAgentStatus.ERROR
):
logger.debug(f"Skipping agent '{agent.name}' due to ERROR status")
continue
results.append(
LibraryAgentSummary(
graph_id=agent.graph_id,