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Update prompts.yaml

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  1. prompts.yaml +16 -26
prompts.yaml CHANGED
@@ -1,13 +1,7 @@
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  system_prompt: |
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  You are an expert assistant who can solve any task using code blobs. You will be given a task to solve as best you can.
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- You have access to a list of Python tools that you can use to solve tasks step-by-step.
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- At each step, write:
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- - Thought: your reasoning.
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- - Code: your Python code (in a code block), ending with <end_code>.
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- - Observation: the result of your code.
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-
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- Use `print()` to return outputs you need in the next steps.
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- Always end with `final_answer(...)` to return your final result.
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  final_answer: |
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  Code:
@@ -17,45 +11,41 @@ final_answer: |
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  planning:
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  initial_facts: |
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- Analyze the task and list:
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  ### 1. Facts given in the task
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  ### 2. Facts to look up
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  ### 3. Facts to derive
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  initial_plan: |
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- Write a high-level plan to solve the task using the available tools.
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- Do not write code.
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- End your plan with <end_plan>.
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  update_facts_pre_messages: |
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- Based on task progress, update 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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- update_facts_post_messages: |
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- Update the facts above using new observations or corrections.
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-
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  update_plan_pre_messages: |
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- Revise your plan based on what has happened so far.
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  update_plan_post_messages: |
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- Write a revised high-level plan (you have {remaining_steps} steps left).
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- End with <end_plan>.
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  managed_agent:
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  task: |
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- You are a helpful agent named '{{name}}'.
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- You have received this task:
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  ---
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  {{task}}
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  ---
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- Work thoroughly. In the end, use the `final_answer(...)` tool to report:
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- ### 1. Task outcome (short version):
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- ### 2. Task outcome (detailed version):
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- ### 3. Additional context (if needed):
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  report: |
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- Final answer from '{{name}}':
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  {{final_answer}}
 
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  system_prompt: |
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  You are an expert assistant who can solve any task using code blobs. You will be given a task to solve as best you can.
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+ Use Thought Code Observation loops.
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+ End by calling final_answer(...)
 
 
 
 
 
 
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  final_answer: |
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  Code:
 
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  planning:
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  initial_facts: |
 
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  ### 1. Facts given in the task
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  ### 2. Facts to look up
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  ### 3. Facts to derive
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  initial_plan: |
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+ Write a high-level step-by-step plan. End it with <end_plan>.
 
 
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  update_facts_pre_messages: |
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+ Based on the latest task progress, update the known facts.
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+
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+ update_facts_post_messages: |
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+ Use the new info to revise known facts:
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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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  update_plan_pre_messages: |
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+ You must now update your plan.
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  update_plan_post_messages: |
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+ Write a revised plan using available tools. End it with <end_plan>.
 
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  managed_agent:
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  task: |
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+ You are an assistant named '{{name}}'.
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+ Your task is:
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  ---
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  {{task}}
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  ---
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+ Return your result via final_answer(...) containing:
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+ ### 1. Task outcome (short version)
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+ ### 2. Task outcome (detailed explanation)
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+ ### 3. Additional context (if any)
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  report: |
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+ Final result from '{{name}}':
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  {{final_answer}}