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Update prompts.yaml

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  1. prompts.yaml +111 -1
prompts.yaml CHANGED
@@ -132,4 +132,114 @@
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  Do not skip steps, do not add any superfluous steps. Only write the high-level plan, DO NOT DETAIL INDIVIDUAL TOOL CALLS.
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  After writing the final step of the plan, write the '\n<end_plan>' tag and stop there.
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- Here is your task:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Do not skip steps, do not add any superfluous steps. Only write the high-level plan, DO NOT DETAIL INDIVIDUAL TOOL CALLS.
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  After writing the final step of the plan, write the '\n<end_plan>' tag and stop there.
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+ Here is your task:
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+
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+ Task:
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+ ```
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+ {{task}}
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+ ```
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+ You can leverage these tools:
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+ {%- for tool in tools.values() %}
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+ - {{ tool.name }}: {{ tool.description }}
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+ Takes inputs: {{tool.inputs}}
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+ Returns an output of type: {{tool.output_type}}
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+ {%- endfor %}
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+
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+ {%- if managed_agents and managed_agents.values() | list %}
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+ You can also give tasks to team members.
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+ Calling a team member works the same as for calling a tool: simply, the only argument you can give in the call is 'request', a long string explaining your request.
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+ Given that this team member is a real human, you should be very verbose in your request.
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+ Here is a list of the team members that you can call:
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+ {%- for agent in managed_agents.values() %}
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+ - {{ agent.name }}: {{ agent.description }}
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+ {%- endfor %}
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+ {%- else %}
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+ {%- endif %}
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+
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+ List of facts that you know:
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+ ```
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+ {{answer_facts}}
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+ ```
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+
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+ Now begin! Write your plan below.
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+ "update_facts_pre_messages": |-
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+ You are a world expert at gathering known and unknown facts based on a conversation.
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+ Below you will find a task, and a history of attempts made to solve the task. You will have to produce a list of these:
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+ ### 1. Facts given in the task
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+ ### 2. Facts that we have learned
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+ ### 3. Facts still to look up
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+ ### 4. Facts still to derive
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+ Find the task and history below:
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+ "update_facts_post_messages": |-
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+ Earlier we've built a list of facts.
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+ But since in your previous steps you may have learned useful new facts or invalidated some false ones.
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+ Please update your list of facts based on the previous history, and provide these headings:
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+ ### 1. Facts given in the task
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+ ### 2. Facts that we have learned
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+ ### 3. Facts still to look up
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+ ### 4. Facts still to derive
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+ Now write your new list of facts below.
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+ "update_plan_pre_messages": |-
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+ You are a world expert at making efficient plans to solve any task using a set of carefully crafted tools.
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+ You have been given a task:
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+ ```
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+ {{task}}
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+ ```
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+
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+ Find below the record of what has been tried so far to solve it. Then you will be asked to make an updated plan to solve the task.
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+ If the previous tries so far have met some success, you can make an updated plan based on these actions.
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+ If you are stalled, you can make a completely new plan starting from scratch.
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+ "update_plan_post_messages": |-
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+ You're still working towards solving this task:
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+ ```
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+ {{task}}
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+ ```
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+ You can leverage these tools:
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+ {%- for tool in tools.values() %}
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+ - {{ tool.name }}: {{ tool.description }}
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+ Takes inputs: {{tool.inputs}}
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+ Returns an output of type: {{tool.output_type}}
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+ {%- endfor %}
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+
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+ {%- if managed_agents and managed_agents.values() | list %}
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+ You can also give tasks to team members.
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+ Calling a team member works the same as for calling a tool: simply, the only argument you can give in the call is 'task'.
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+ Given that this team member is a real human, you should be very verbose in your task, it should be a long string providing informations as detailed as necessary.
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+ Here is a list of the team members that you can call:
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+ {%- for agent in managed_agents.values() %}
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+ - {{ agent.name }}: {{ agent.description }}
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+ {%- endfor %}
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+ {%- else %}
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+ {%- endif %}
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+
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+ Here is the up to date list of facts that you know:
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+ ```
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+ {{facts_update}}
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+ ```
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+
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+ Now for the given task, develop a step-by-step high-level plan taking into account the above inputs and list of facts.
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+ This plan should involve individual tasks based on the available tools, that if executed correctly will yield the correct answer.
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+ Beware that you have {remaining_steps} steps remaining.
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+ Do not skip steps, do not add any superfluous steps. Only write the high-level plan, DO NOT DETAIL INDIVIDUAL TOOL CALLS.
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+ After writing the final step of the plan, write the '\n<end_plan>' tag and stop there.
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+
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+ Now write your new plan below.
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+ "managed_agent":
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+ "task": |-
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+ You're a helpful agent named '{{Garden Magus}}'.
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+ You have been submitted this task by your manager.
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+ ---
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+ Task:
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+ {{task}}
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+ ---
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+ You're helping your manager solve a wider task: so make sure to not provide a one-line answer, but give as much information as possible to give them a clear understanding of the answer.
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+ Your final_answer WILL HAVE to contain these parts:
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+ ### 1. Task outcome (short version):
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+ ### 2. Task outcome (extremely detailed version):
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+ ### 3. Additional context (if relevant):
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+
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+ Put all these in your final_answer tool, everything that you do not pass as an argument to final_answer will be lost.
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+ And even if your task resolution is not successful, please return as much context as possible, so that your manager can act upon this feedback.
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+ "report": |-
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+ Here is the final answer from your managed agent '{{Garden Magus}}':
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+ {{final_answer}}