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Update prompts.yaml
Browse files- prompts.yaml +16 -26
prompts.yaml
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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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- 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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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:
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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
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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
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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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update_plan_pre_messages: |
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update_plan_post_messages: |
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Write a revised
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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
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---
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{{task}}
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---
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### 1. Task outcome (short version)
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### 2. Task outcome (detailed
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### 3. Additional context (if
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report: |
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Final
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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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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}}
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