Example: Sequential pipeline with AutoGen [chapter] deterministic

from autogen import Agent, ConversableAgent planner = ConversableAgent( name="Planner", llm_config={"model": "gpt-4"}, system_message="You are a planner. Produce a step-by-step plan." ) executor = ConversableAgent( name="Executor", llm_config={"model": "gpt-3.5"}, system_message="You are an executor. Carry out the plan." ) planner.register_reply(executor, lambda agent, messages: planner.generate_reply(messages)) executor.register_reply(planner, lambda agent, messages: executor.generate_reply(messages)) planner.initiate_chat(executor, message="Plan a data extraction pipeline for CSV files.")

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Parallel

Source Code and Repositories

This chapter draws from the following open-source projects by DanielKliewer:

• **PersonaGen**: https://github.com/kliewerdaniel/PersonaGen
• **dynamic_persona_moe_rag**: https://github.com/kliewerdaniel/dynamic_persona_moe_rag
• **SynthInt**: https://github.com/kliewerdaniel/SynthInt
• **workflow**: https://github.com/kliewerdaniel/workflow
• **sovereign**: https://github.com/kliewerdaniel/sovereign
• **sovereignSpec**: https://github.com/kliewerdaniel/sovereignSpec

For more projects, visit https://github.com/kliewerdaniel

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