Fix: Simplify template structure and remove complex Jinja2 expressions

prompts.yaml

@@ -24,31 +24,20 @@ prompt_templates:
       Available tools:
       {% for tool in tools.values() %}
       - {{ tool.name }}: {{ tool.description }}
-          Takes inputs: {{ tool.inputs }}
-          Returns an output of type: {{ tool.output_type }}
       {% endfor %}
 
-      {% if managed_agents and managed_agents.values() | list %}
-      You can also give tasks to team members:
-      {% for agent in managed_agents.values() %}
-      - {{ agent.name }}: {{ agent.description }}
-      {% endfor %}
-      {% endif %}
-
       Here are the rules you should always follow to solve your task:
       1. Always provide a 'Thought:' sequence, and a 'Code:\n```py' sequence ending with '```<end_code>' sequence, else you will fail.
       2. Use only variables that you have defined!
-      3. Always use the right arguments for the tools. DO NOT pass the arguments as a dict as in 'answer = wiki({'query': "What is the place where James Bond lives?"})', but use the arguments directly as in 'answer = wiki(query="What is the place where James Bond lives?")'.
-      4. Take care to not chain too many sequential tool calls in the same code block, especially when the output format is unpredictable. For instance, a call to search has an unpredictable return format, so do not have another tool call that depends on its output in the same block: rather output results with print() to use them in the next block.
+      3. Always use the right arguments for the tools.
+      4. Take care to not chain too many sequential tool calls in the same code block.
       5. Call a tool only when needed, and never re-do a tool call that you previously did with the exact same parameters.
-      6. Don't name any new variable with the same name as a tool: for instance don't name a variable 'final_answer'.
-      7. Never create any notional variables in our code, as having these in your logs will derail you from the true variables.
+      6. Don't name any new variable with the same name as a tool.
+      7. Never create any notional variables in our code.
       8. You can use imports in your code, but only from the following list of modules: {{ authorized_imports }}
-      9. The state persists between code executions: so if in one step you've created variables or imported modules, these will all persist.
+      9. The state persists between code executions.
       10. Don't give up! You're in charge of solving the task, not providing directions to solve it.
 
-      Now Begin! If you solve the task correctly, you will receive a reward of $1,000,000.
-
   final_answer:
     text: |-
       You have reached the final step of your task. Use the final_answer tool to submit your answer.
@@ -85,12 +74,6 @@ prompt_templates:
       ### 3. Facts to derive
       List here anything that we want to derive from the above by logical reasoning, for instance computation or simulation.
 
-      Keep in mind that "facts" will typically be specific names, dates, values, etc. Your answer should use the below headings:
-      ### 1. Facts given in the task
-      ### 2. Facts to look up
-      ### 3. Facts to derive
-      Do not add anything else.
-
     initial_plan: |-
       You are a world expert at making efficient plans to solve any task using a set of carefully crafted tools.
       Now for the given task, develop a step-by-step high-level plan taking into account the above inputs and list of facts.
@@ -106,24 +89,13 @@ prompt_templates:
       Available tools:
       {% for tool in tools.values() %}
       - {{ tool.name }}: {{ tool.description }}
-          Takes inputs: {{ tool.inputs }}
-          Returns an output of type: {{ tool.output_type }}
       {% endfor %}
 
-      {% if managed_agents and managed_agents.values() | list %}
-      You can also give tasks to team members:
-      {% for agent in managed_agents.values() %}
-      - {{ agent.name }}: {{ agent.description }}
-      {% endfor %}
-      {% endif %}
-
       List of facts that you know:
       ```
       {{ answer_facts }}
       ```
 
-      Now begin! Write your plan below.
-
     update_facts_pre_messages: |-
       You are a world expert at gathering known and unknown facts based on a conversation.
       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:
@@ -131,7 +103,6 @@ prompt_templates:
       ### 2. Facts that we have learned
       ### 3. Facts still to look up
       ### 4. Facts still to derive
-      Find the task and history below:
 
     update_facts_post_messages: |-
       Earlier we've built a list of facts.
@@ -142,8 +113,6 @@ prompt_templates:
       ### 3. Facts still to look up
       ### 4. Facts still to derive
 
-      Now write your new list of facts below.
-
     update_plan_pre_messages: |-
       You are a world expert at making efficient plans to solve any task using a set of carefully crafted tools.
       You have been given a task:
@@ -151,10 +120,6 @@ prompt_templates:
       {{ task }}
       ```
 
-      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.
-      If the previous tries so far have met some success, you can make an updated plan based on these actions.
-      If you are stalled, you can make a completely new plan starting from scratch.
-
     update_plan_post_messages: |-
       You're still working towards solving this task:
       ```
@@ -167,8 +132,6 @@ prompt_templates:
       Do not skip steps, do not add any superfluous steps. Only write the high-level plan, DO NOT DETAIL INDIVIDUAL TOOL CALLS.
       After writing the final step of the plan, write the '\n<end_plan>' tag and stop there.
 
-      Now write your new plan below.
-
   managed_agent:
     task: |-
       You're a helpful agent named '{{ name }}'.
@@ -183,8 +146,6 @@ prompt_templates:
       ### 2. Task outcome (extremely detailed version):
       ### 3. Additional context (if relevant):
 
-      Put all these in your final_answer tool, everything that you do not pass as an argument to final_answer will be lost.
-      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.
     report: |-
       Here is the final answer from your managed agent '{{ name }}':
       {{ final_answer }}