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Add gpt-4o-mini, update examples (#253)
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@@ -255,14 +255,14 @@ async def main() -> None:
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"ReviewerAgent",
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lambda: ReviewerAgent(
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description="Code Reviewer",
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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),
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)
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await runtime.register(
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"CoderAgent",
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lambda: CoderAgent(
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description="Coder",
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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),
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)
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run_context = runtime.start()
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@@ -118,7 +118,7 @@ async def main() -> None:
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lambda: GroupChatParticipant(
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description="A data scientist",
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system_messages=[SystemMessage("You are a data scientist.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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),
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)
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agent2 = await runtime.register_and_get(
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@@ -126,7 +126,7 @@ async def main() -> None:
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lambda: GroupChatParticipant(
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description="An engineer",
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system_messages=[SystemMessage("You are an engineer.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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),
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)
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agent3 = await runtime.register_and_get(
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@@ -134,7 +134,7 @@ async def main() -> None:
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lambda: GroupChatParticipant(
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description="An artist",
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system_messages=[SystemMessage("You are an artist.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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),
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)
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@@ -117,7 +117,7 @@ async def main() -> None:
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lambda: ReferenceAgent(
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description="Reference Agent 1",
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system_messages=[SystemMessage("You are a helpful assistant that can answer questions.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo", temperature=0.1),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini", temperature=0.1),
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),
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)
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await runtime.register(
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@@ -125,7 +125,7 @@ async def main() -> None:
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lambda: ReferenceAgent(
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description="Reference Agent 2",
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system_messages=[SystemMessage("You are a helpful assistant that can answer questions.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo", temperature=0.5),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini", temperature=0.5),
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),
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)
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await runtime.register(
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@@ -133,7 +133,7 @@ async def main() -> None:
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lambda: ReferenceAgent(
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description="Reference Agent 3",
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system_messages=[SystemMessage("You are a helpful assistant that can answer questions.")],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo", temperature=1.0),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini", temperature=1.0),
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),
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)
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await runtime.register(
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@@ -145,7 +145,7 @@ async def main() -> None:
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"...synthesize these responses into a single, high-quality response... Responses from models:"
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)
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],
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model_client=get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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model_client=get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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num_references=3,
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),
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)
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@@ -214,7 +214,7 @@ async def main(question: str) -> None:
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await runtime.register(
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"MathSolver1",
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lambda: MathSolver(
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get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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neighbor_names=["MathSolver2", "MathSolver4"],
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max_round=3,
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),
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@@ -222,7 +222,7 @@ async def main(question: str) -> None:
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await runtime.register(
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"MathSolver2",
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lambda: MathSolver(
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get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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neighbor_names=["MathSolver1", "MathSolver3"],
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max_round=3,
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),
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@@ -230,7 +230,7 @@ async def main(question: str) -> None:
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await runtime.register(
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"MathSolver3",
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lambda: MathSolver(
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get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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neighbor_names=["MathSolver2", "MathSolver4"],
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max_round=3,
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),
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@@ -238,7 +238,7 @@ async def main(question: str) -> None:
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await runtime.register(
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"MathSolver4",
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lambda: MathSolver(
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get_chat_completion_client_from_envs(model="gpt-3.5-turbo"),
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get_chat_completion_client_from_envs(model="gpt-4o-mini"),
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neighbor_names=["MathSolver1", "MathSolver3"],
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max_round=3,
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),
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