Your AI agent loops don't know when to stop. LoopGain does.

# amber stripe = the lines you add or change. everything else is your existing loop.
from loopgain import LoopGainlg = LoopGain(target_error=0.1, max_iterations=20)
while lg.should_continue():    errors = your_verifier(output)        # your existing code
    lg.observe(errors, output=output)    output = your_refiner(output, errors)  # your existing code

result = lg.result# result.outcome      → "converged" · "oscillating" · "diverged" · "stalled" · "max_iterations"
# result.best_output  → argmin(E(n)) — the actual best draft, not the last# result.gain_margin  → 1 / max(Aβ_smooth) — > 1 means stable headroom

# amber stripe = the lines you add or change. pip install 'loopgain[langgraph]'
from loopgain import LoopGainfrom loopgain.integrations import LangGraphAdapter
graph = build_verify_revise_graph().compile()
lg = LoopGain(target_error=0.1, max_iterations=20)adapter = LangGraphAdapter(
    lg=lg,
    error_fn=lambda update: len(update.get("verifier", {}).get("errors", [])),
)final_state = adapter.run(graph, {"draft": initial})
# adapter.stream() yields each step if you want the full trace.
# adapter.arun() / adapter.astream() are the async counterparts.

# amber stripe = the lines you add or change. pip install 'loopgain[crewai]'
from loopgain import LoopGainfrom loopgain.integrations import CrewAIAdapter
crew = Crew(agents=[writer_agent, verifier_agent], tasks=[task])
lg = LoopGain(target_error=0.1, max_iterations=20)adapter = CrewAIAdapter(
    lg=lg,
    task_error_fn=lambda task_output: count_failed_checks(task_output.raw),
)with adapter:               # installs callbacks; uninstalls on exit    adapter.install(crew)    result = crew.kickoff()

# Observations land on `lg.result` — same shape as the raw API.
# Existing callbacks you had installed are chained, not clobbered.

# amber stripe = the lines you add or change. pip install 'loopgain[autogen]'
from autogen_agentchat.teams import RoundRobinGroupChat
from loopgain import LoopGainfrom loopgain.integrations import AutoGenAdapter
team = RoundRobinGroupChat(participants=[generator, verifier])
lg = LoopGain(target_error=0.1, max_iterations=20)adapter = AutoGenAdapter(
    lg=lg,
    error_fn=lambda msg: parse_verifier_score(msg.content),
    observe_sources={"verifier"},      # only verifier drives observe()
)result = await adapter.run(team, task="draft, verify, revise")
# Legacy v0.2 ConversableAgent.initiate_chat is not supported.

# amber stripe = the lines you add or change. pip install 'loopgain[langchain]'
from langchain.agents import create_agent
from loopgain import LoopGainfrom loopgain.integrations import LangChainAdapter
agent = create_agent(model="gpt-5-nano", tools=[get_weather])
lg = LoopGain(target_error=0.0, max_iterations=20)adapter = LangChainAdapter(
    lg=lg,
    error_fn=lambda chunk: count_unresolved_tool_calls(chunk),
)final = adapter.run(
    agent,
    {"messages": [{"role": "user", "content": prompt}]},
    stream_mode="updates", version="v2",
)
# Duck-typed: also drives the legacy AgentExecutor.stream() shape.

# amber stripe = the lines you add or change. pip install 'loopgain[openai-agents]'
from agents import Agent
from loopgain import LoopGainfrom loopgain.integrations import OpenAIAgentsAdapter
agent = Agent(name="Refiner", instructions="...", tools=[verify_tool])
lg = LoopGain(target_error=0.0, max_iterations=20)adapter = OpenAIAgentsAdapter(
    lg=lg,
    error_fn=lambda event: parse_verifier_failures(event),
)result = await adapter.run(agent, input="Fix the bug.")
# Defaults to run_item_stream_event; cancels the stream at terminal state.
# adapter.run_sync(...) wraps the async path with asyncio.run.

# amber stripe = the lines you add or change. pip install 'loopgain[claude-agent-sdk]'
from claude_agent_sdk import ClaudeAgentOptions, TextBlock
from loopgain import LoopGainfrom loopgain.integrations import ClaudeAgentSDKAdapter
lg = LoopGain(target_error=0.0, max_iterations=20)adapter = ClaudeAgentSDKAdapter(
    lg=lg,
    error_fn=lambda msg: count_fail_markers(msg),
)result = await adapter.run(
    prompt="Write a haiku about feedback loops.",
    options=ClaudeAgentOptions(system_prompt="Self-verify each draft."),
)
# Default filter: only AssistantMessage reaches error_fn.
# Also accepts message_iterator=client.receive_messages() for ClaudeSDKClient.