agentverse/tasks/tasksolving/commongen/gpt-3.5/config.yaml

cnt_agents: &cnt_agents 2
max_turn: &max_turn 3
max_inner_turns: &max_inner_turns 3

prompts:
  role_assigner_prepend_prompt: &role_assigner_prepend_prompt |-

  role_assigner_append_prompt: &role_assigner_append_prompt |-
    # Role Description
    You are the leader of a group of experts, now you need to recruit a small group of experts with diverse identity to generate coherent and grammatically correct sentences containing the following given words:
    ${task_description}
    
    You can recruit ${cnt_critic_agents} expert in different fields. What experts will you recruit?
    
    # Response Format Guidance
    You should respond with a list of expert description. For example:
    1. an electrical engineer specified in the filed of xxx.
    2. an economist who is good at xxx.
    3. a lawyer with a good knowledge of xxx.
    ...
    
    Only respond with the description of each role. Do not include your reason.

  solver_prepend_prompt: &solver_prepend_prompt |-
    You are ${role_description}. Generate a coherent and grammatically correct paragraph containing the following given words (or their variations):
    WORDS: 
    ${task_description}

  solver_append_prompt: &solver_append_prompt |-

  critic_prepend_prompt: &critic_prepend_prompt |-
    You are in a discussion group, aiming to generate coherent and grammatically correct sentences containing the following given words (or their variations):
    WORDS:
    ${task_description}

    Below is the chat history in your group.
    
  critic_append_prompt: &critic_append_prompt |-
    You are ${role_description}. Based on your knowledge, can you check whether the latest provided paragraph contains all the given words or their variations? When responding, you should follow the following rules:
    1. If the above latest provided solution has covered all the given words or their variations, end your response with a special token "[Agree]".
    1. If not, double-check the above solutions, give your critics, and generate a better solution.

  manager_prompt: &manager_prompt |-

  executor_prepend_prompt: &executor_prepend_prompt |-

  executor_append_prompt: &executor_append_prompt |-

  evaluator_prepend_prompt: &evaluator_prepend_prompt |-

  evaluator_append_prompt: &evaluator_append_prompt |-
    You are a reviewer who checks whether a paragraph contains all the given words (including their variations). When some words are missing, you should patiently point out, and output a score of 0. When the paragraph contains all the words, you should output a score of 1.
  
    WORDS: 
    ${task_description}

    SOLUTION: 
    ```
    ${solution}
    ```

    TEST RESULT:
    ${result}
    
    RESPONSE FORMAT:
    You must respond in the following format:
    Score: (0 or 1. 0 if there are some missing words, 1 if there is no missing words)
    Advice: (point out all the missing words)
    

name: pipeline


environment:
  env_type: task-basic
  max_turn: *max_turn
  rule:
    role_assigner:
      type: role_description
      cnt_agents: *cnt_agents
    decision_maker:
      type: vertical-solver-first
      max_inner_turns: *max_inner_turns
    executor:
      type: coverage-test
    evaluator:
      type: basic

agents:
  - #role_assigner_agent:
    agent_type: role_assigner
    name: role assigner
    max_retry: 1000
    prepend_prompt_template: *role_assigner_prepend_prompt
    append_prompt_template: *role_assigner_append_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: "gpt-3.5-turbo"
      temperature: 0
      max_tokens: 512
    output_parser:
      type: role_assigner

  - #solver_agent:
    agent_type: solver
    name: Planner
    max_retry: 1000
    max_history: 4
    prepend_prompt_template: *solver_prepend_prompt
    append_prompt_template: *solver_append_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: "gpt-3.5-turbo"
      temperature: 0
      max_tokens: 1024
    output_parser:
      type: commongen
      # max_tokens: 1024
      # stop:
      #   - "\ndef "
      #   - "\nclass "
      #   - "\nif "
      #   - "\n\n#"

  - #critic_agents:
    agent_type: critic
    name: Critic 1
    max_retry: 1000
    max_history: 4
    role_description: |-
      Waiting to be assigned.
    prepend_prompt_template: *critic_prepend_prompt
    append_prompt_template: *critic_append_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: "gpt-3.5-turbo"
      temperature: 0
      max_tokens: 1024
    output_parser:
      type: mgsm-critic-agree

  - #executor_agent:
    agent_type: executor
    name: Executor
    max_retry: 1000
    prepend_prompt_template: *executor_prepend_prompt
    append_prompt_template: *executor_append_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: gpt-3.5-turbo
      temperature: 0
      max_tokens: 1024
    output_parser:
      type: commongen

  - #evaluator_agent:
    agent_type: evaluator
    name: Evaluator
    max_retry: 1000
    role_description: |-
      Evaluator
    prepend_prompt_template: *evaluator_prepend_prompt
    append_prompt_template: *evaluator_append_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: gpt-3.5-turbo
      temperature: 0.3
      max_tokens: 1024
    output_parser:
      type: humaneval-evaluator
      dimensions:
        - Score

  - #manager_agent:
    agent_type: manager
    name: Manager
    max_retry: 1000
    prompt_template: *manager_prompt
    memory:
      memory_type: chat_history
    llm:
      llm_type: gpt-3.5-turbo
      model: "gpt-3.5-turbo"
      temperature: 0
      max_tokens: 1024
    output_parser:
      type: humaneval-manager