From 4af966157136601e304c41cf24abc14776449e92 Mon Sep 17 00:00:00 2001 From: evelynmitchell Date: Wed, 27 Nov 2024 18:32:31 -0700 Subject: [PATCH] whitespace flake8 --- swarms/prompts/autoswarm.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/swarms/prompts/autoswarm.py b/swarms/prompts/autoswarm.py index 8ded2027..2e3096f7 100644 --- a/swarms/prompts/autoswarm.py +++ b/swarms/prompts/autoswarm.py @@ -2,13 +2,13 @@ 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. 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 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. 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 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) swarm_assembly_output = swarm_assembly_agent.run(agent_configuration_output) testing_optimization_output = testing_optimization_agent.run(swarm_assembly_output) -""" +""" # noqa: W291, W293 # Prompt for Testing and Optimization Agent 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. 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.