Sentient Foundation | Open-Source AGI

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import dspy from roma_dspy import Aggregator, Atomizer, Executor, Planner, Verifier, SubTask from roma_dspy.types import TaskType
# Optional tool that the Executor may call def get_weather(city: str) -> str: """Return a canned weather report for the city.""" return f"The weather in {city} is sunny."
# Executor geared toward ReAct with a Fireworks model executor_lm = dspy.LM( "fireworks_ai/accounts/fireworks/models/kimi-k2-instruct-0905", temperature=0.7, cache=True, ) executor = Executor( lm=executor_lm, prediction_strategy="react", tools=[get_weather], context_defaults={"track_usage": True}, )
# Atomizer decides when to branch into planning atomizer = Atomizer( lm=dspy.LM("openrouter/google/gemini-2.5-flash", temperature=0.6, cache=False), prediction_strategy="cot", context_defaults={"track_usage": True}, )
# Planner produces executable subtasks for non-atomic goals planner = Planner( lm=dspy.LM("openrouter/openai/gpt-4o-mini", temperature=0.85, cache=True), prediction_strategy="cot", context_defaults={"track_usage": True}, )
aggregator = Aggregator( lm=dspy.LM("openrouter/openai/gpt-4o-mini", temperature=0.65), prediction_strategy="cot", )
verifier = Verifier( lm=dspy.LM("openrouter/openai/gpt-4o-mini", temperature=0.0), )
def run_pipeline(goal: str) -> str: atomized = atomizer.forward(goal) if atomized.is_atomic or atomized.node_type.is_execute: execution = executor.forward(goal) candidate = execution.output else: plan = planner.forward(goal) results = [] for idx, subtask in enumerate(plan.subtasks, start=1): execution = executor.forward(subtask.goal) results.append( SubTask( goal=subtask.goal, task_type=subtask.task_type, dependencies=subtask.dependencies, ) ) aggregated = aggregator.forward(goal, results) candidate = aggregated.synthesized_result
verdict = verifier.forward(goal, candidate) if verdict.verdict: return candidate return f"Verifier flagged the output: {verdict.feedback or 'no feedback returned'}"
print(run_pipeline("Plan a weekend in Barcelona and include a packing list."))

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ROMA

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Role list: Atomizer, Planner, Executor, Aggregator, Verifier

ROMA

Reasoning & Orchestration for Machine Agents

ROMA is an open framework for building multi-agent AI systems with structured reasoning and coordination.

OML

Open, Monetizable,
Loyal Models

OML proposes a new primitive for distributing AI models that balances openness, control, and sustainability.

ODS

Open Deep Search

Open Deep Search (ODS) is a framework for building search-augmented reasoning systems using open-source models.

Open research, in public through Sentient Labs

Open AGI Summit

A space for builders, founders, and researchers to discuss the future of open-source AI

Open AGI
Summit

02.19.2026

Bringing together researchers, developers, and communities united by the shared conviction that AGI must remain open and accessible to everyone.

Research releases, announcements, and milestones from Sentient Foundation

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Sentient Foundation Launches as Global Nonprofit to Ensure AGI Remains Open-Source and Aligned with Humanity

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//Global

The new foundation aims to prevent any single entity from controlling Artificial General Intelligence, following the precedent of Linux and other transformative open-source movements.

Sentient Expands Across Asia

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//Asia

Sentient continues its expansion across Asia, building partnerships with universities, researchers, and local communities. The initiative strengthens the foundation’s mission to advance open and collaborative AGI development.

Be the Sparks, Ignite with Sentient Sparks

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//Europe

Sentient Sparks is a community-driven initiative designed to empower contributors in the Open AGI ecosystem. The program encourages experimentation, collaboration, and the exchange of bold ideas.