whitespace flake8

pull/649/head
evelynmitchell 5 months ago
parent 78b0f8bce4
commit 4af9661571

@ -2,13 +2,13 @@
AGENT_ROLE_IDENTIFICATION_AGENT_PROMPT = """ AGENT_ROLE_IDENTIFICATION_AGENT_PROMPT = """
Based on the following idea: '{user_idea}', identify and list the specific types of agents needed for the team. Detail their roles, responsibilities, and capabilities. Based on the following idea: '{user_idea}', identify and list the specific types of agents needed for the team. Detail their roles, responsibilities, and capabilities.
Output Format: A list of agent types with brief descriptions of their roles and capabilities, formatted in bullet points or a numbered list. Output Format: A list of agent types with brief descriptions of their roles and capabilities, formatted in bullet points or a numbered list.
""" """ # noqa: W291, W293
# Prompt for Agent Configuration Agent # Prompt for Agent Configuration Agent
AGENT_CONFIGURATION_AGENT_PROMPT = """ AGENT_CONFIGURATION_AGENT_PROMPT = """
Given these identified agent roles: '{agent_roles}', write SOPs/System Prompts for each agent type. Ensure that each SOP/Prompt is tailored to the specific functionalities of the agent, considering the operational context and objectives of the swarm team. Given these identified agent roles: '{agent_roles}', write SOPs/System Prompts for each agent type. Ensure that each SOP/Prompt is tailored to the specific functionalities of the agent, considering the operational context and objectives of the swarm team.
Output Format: A single Python file of the whole agent team with capitalized constant names for each SOP/Prompt, an equal sign between each agent name and their SOP/Prompt, and triple quotes surrounding the Prompt/SOP content. Follow best-practice prompting standards. Output Format: A single Python file of the whole agent team with capitalized constant names for each SOP/Prompt, an equal sign between each agent name and their SOP/Prompt, and triple quotes surrounding the Prompt/SOP content. Follow best-practice prompting standards.
""" """ # noqa: W291, W293
# Prompt for Swarm Assembly Agent # Prompt for Swarm Assembly Agent
SWARM_ASSEMBLY_AGENT_PROMPT = """ SWARM_ASSEMBLY_AGENT_PROMPT = """
@ -73,13 +73,13 @@ role_identification_output = role_identification_agent.run(user_idea)
agent_configuration_output = agent_configuration_agent.run(role_identification_output) agent_configuration_output = agent_configuration_agent.run(role_identification_output)
swarm_assembly_output = swarm_assembly_agent.run(agent_configuration_output) swarm_assembly_output = swarm_assembly_agent.run(agent_configuration_output)
testing_optimization_output = testing_optimization_agent.run(swarm_assembly_output) testing_optimization_output = testing_optimization_agent.run(swarm_assembly_output)
""" """ # noqa: W291, W293
# Prompt for Testing and Optimization Agent # Prompt for Testing and Optimization Agent
TESTING_OPTIMIZATION_AGENT_PROMPT = """ TESTING_OPTIMIZATION_AGENT_PROMPT = """
Review this Python script for swarm demonstration: '{swarm_script}'. Create a testing and optimization plan that includes methods for validating each agent's functionality and the overall performance of the swarm. Suggest improvements for efficiency and effectiveness. Review this Python script for swarm demonstration: '{swarm_script}'. Create a testing and optimization plan that includes methods for validating each agent's functionality and the overall performance of the swarm. Suggest improvements for efficiency and effectiveness.
Output Format: A structured plan in a textual format, outlining testing methodologies, key performance metrics, and optimization strategies. Output Format: A structured plan in a textual format, outlining testing methodologies, key performance metrics, and optimization strategies.
""" """ # noqa: W291, W293
# This file can be imported in the main script to access the prompts. # This file can be imported in the main script to access the prompts.

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