llama3.yml

# Collection of all the prompts
prompts:
    - task: general
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
            {{ general_instructions }}{% if relevant_chunks != None and relevant_chunks != '' %}
            This is some relevant context:
            ```markdown
            {{ relevant_chunks }}
            ```{% endif %}
        - "{{ history | to_chat_messages }}"

    # Prompt for detecting the user message canonical form.
    - task: generate_user_intent
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
            {{ general_instructions }}

            Your task is to generate the user intent in a conversation given the last user message similar to the examples below.
            Do not provide any explanations, just output the user intent.

            # Examples:
            {{ examples | verbose_v1 }}

        - "{{ sample_conversation | first_turns(2) | to_messages }}"
        - "{{ history | colang | to_messages }}"
        - type: assistant
          content: |
              Bot thinking: potential user intents are: {{ potential_user_intents }}

      output_parser: "verbose_v1"

    # Prompt for generating the next steps.
    - task: generate_next_steps
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
            {{ general_instructions }}

            Your task is to generate the next steps in a conversation given the last user message similar to the examples below.
            Do not provide any explanations, just output the user intent and the next steps.

            # Examples:
            {{ examples | remove_text_messages | verbose_v1 }}

        - "{{ sample_conversation | first_turns(2) | to_intent_messages }}"
        - "{{ history | colang | to_intent_messages }}"

      output_parser: "verbose_v1"

    # Prompt for generating the bot message from a canonical form.
    - task: generate_bot_message
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
              {{ general_instructions }}{% if relevant_chunks != None and relevant_chunks != '' %}
              This is some relevant context:
              ```markdown
              {{ relevant_chunks }}
              ```{% endif %}
              Your task is to generate the bot message in a conversation given the last user message, user intent and bot intent.
              Similar to the examples below.
              Do not provide any explanations, just output the bot message.

              # Examples:
              {{ examples | verbose_v1 }}

        - "{{ sample_conversation | first_turns(2) | to_intent_messages_2 }}"
        - "{{ history | colang | to_intent_messages_2 }}"

      output_parser: "verbose_v1"

    # Prompt for generating the user intent, next steps and bot message in a single call.
    - task: generate_intent_steps_message
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
            {{ general_instructions }}{% if relevant_chunks != None and relevant_chunks != '' %}
            This is some relevant context:
            ```markdown
            {{ relevant_chunks }}
            ```{% endif %}

            Your task is to generate the user intent and the next steps in a conversation given the last user message similar to the examples below.
            Do not provide any explanations, just output the user intent and the next steps.

            # Examples:
            {{ examples | verbose_v1 }}

        - "{{ sample_conversation | first_turns(2) | to_messages }}"
        - "{{ history | colang | to_messages }}"
        - type: assistant
          content: |
              Bot thinking: potential user intents are: {{ potential_user_intents }}

      output_parser: "verbose_v1"

    # Prompt for generating the value of a context variable.
    - task: generate_value
      models:
        - llama3
        - llama-3

      messages:
        - type: system
          content: |
            {{ general_instructions }}

            Your task is to generate value for the ${{ var_name }} variable..
            Do not provide any explanations, just output value.

            # Examples:
            {{ examples | verbose_v1 }}

        - "{{ sample_conversation | first_turns(2) | to_messages }}"
        - "{{ history | colang | to_messages }}"
        - type: assistant
          content: |
              Bot thinking: follow the following instructions: {{ instructions }}
              ${{ var_name }} =

      output_parser: "verbose_v1"

    # Colang 2 prompts below.

    # Prompt for detecting the user message canonical form.
    - task: generate_user_intent_from_user_action
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: "{{ general_instructions }}"

        - type: system
          content: "This is how a conversation between a user and the bot can go:"
        - "{{ sample_conversation | to_messages_v2 }}"

        - type: system
          content: |-
              "These are the most likely user intents:"
              {{ examples }}

        - type: system
          content: "This is the current conversation between the user and the bot:"
        - "{{ history | colang | to_messages_v2}}"

        - type: user
          content: "user action: {{ user_action }}"

        - type: system
          content: "Derive `user intent:` from user action considering the intents from section 'These are the most likely user intents':"

    - task: generate_user_intent_and_bot_action_from_user_action
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: "{{ general_instructions }}"

        - type: system
          content: "This is how a conversation between a user and the bot can go:"
        - "{{ sample_conversation | to_messages_v2 }}"

        - type: system
          content: |
            {% if context.relevant_chunks %}
            # This is some additional context:
            ```markdown
            {{ context.relevant_chunks }}
            ```
            {% endif %}

        - type: system
          content: |-
              "These are the most likely user intents:"
              {{ examples }}

        - type: system
          content: "This is the current conversation between the user and the bot:"
        - "{{ history | colang | to_messages_v2}}"

        - type: user
          content: "user action: {{ user_action }}"

        - type: system
          content: "Continuation of the interaction starting with a `user intent:` from the section 'These are the most likely user intents':"

    # Prompt for generating the value of a context variable.
    - task: generate_value_from_instruction
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: |
              {{ general_instructions }}

              Your task is to generate value for the ${{ var_name }} variable..
              Do not provide any explanations, just output value.

        - type: system
          content: "This is how a conversation between a user and the bot can go:"
        - "{{ sample_conversation | to_messages_v2 }}"

        - type: system
          content: "This is the current conversation between the user and the bot:"
        - "{{ history | colang | to_messages_v2}}"

        - type: assistant
          content: |
              Follow these instruction `{{ instructions }}` to generate a value that is assigned to:
              ${{ var_name }} =

    # Prompt for generating a flow from instructions.
    - task: generate_flow_from_instructions
      models:
        - llama3
        - llama-3
      content: |-
          # Example flows:
          {{ examples }}

          # Complete the following flow based on its instruction:
          flow {{ flow_name }}
            """{{ instructions }}"""

    # Prompt for generating a flow from name.
    - task: generate_flow_from_name
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: |
              {{ general_instructions }}

              Your task is to generate a flow from the provided flow name ${{ flow_name }}.
              Do not provide any explanations, just output value.

        - type: system
          content: "This is the current conversation between the user and the bot:"
        - "{{ history | colang | to_messages_v2}}"

        - type: system
          content: |-
              These are some example flows:
              {{ examples }}

        - type: system
          content: |-
              Complete the following flow based on its name:
              flow {{ flow_name }}

              Do not provide any explanations, just output value.
      stop:
        - "\nflow"

      # Prompt for generating the continuation for the current conversation.
    - task: generate_flow_continuation
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: "{{ general_instructions }}"

        - type: system
          content: "This is how a conversation between a user and the bot can go:"
        - "{{ sample_conversation | to_messages_v2 }}"

        - type: system
          content: "This is the current conversation between the user and the bot:"
        - "{{ history | colang | to_messages_v2 }}"

        - type: system
          content: |
            {% if context.relevant_chunks %}
            # This is some additional context:
            ```markdown
            {{ context.relevant_chunks }}
            ```
            {% endif %}

        - type: system
          content: "Continuation of interaction:"


    - task: generate_flow_continuation_from_flow_nld
      models:
        - llama3
        - llama-3
      messages:
        - type: system
          content: "Directly response with expected answer. Don't provide any pre- or post-explanations."

        - type: system
          content: |-
              {{ flow_nld }}