apiche

Apiche's group workspace

Group: debug_actor_mcp_tir_again2

actor.shared_memory_entry_size

actor.threads_per_llm

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apiche

3w ago

4m 46s

pipelinerl.domains.tir_mcp.generate_mcp_rollout

10000000

Please reason step by step, and put your final answer within \boxed{}.

{task}

tapeagents.agent.Agent

mcp_agent

["{'_target_': 'tapeagents.nodes.StandardNode', 'name': 'plan', 'system_prompt': '${agent.templates.system_prompt}', 'guidance': 'Write a concise multi-step plan explaining which steps should be performed to find the answer for the given task.\\nBe specific about how each step should be performed. Only describe the intended actions here, do not perform them yet.\\nConsider that next steps may depend on results of previous steps, so include conditional branching using \"if\" statements where needed.\\nStart with the title \"Plan\". Every step should have short name and description.\\n${agent.templates.thought_format}\\n', 'steps_prompt': '${agent.templates.allowed_tools}'}","{'_target_': 'tapeagents.nodes.StandardNode', 'name': 'select', 'system_prompt': '${agent.templates.system_prompt}', 'trim_obs_except_last_n': 100, 'guidance': 'Select the next step to do to move forward with the plan. Describe the expected effect of the proposed action.\\n${agent.templates.thought_format}\\n', 'steps_prompt': '${agent.templates.allowed_tools}'}","{'_target_': 'tapeagents.nodes.StandardNode', 'name': 'act', 'system_prompt': '${agent.templates.system_prompt}', 'trim_obs_except_last_n': 100, 'guidance': 'Then produce single function call for the next step. If the answer is ready, call MathAnswer. Put your final answer within \\\\boxed{}.', 'steps': ['pipelinerl.domains.tir_mcp.steps.MathAnswer'], 'use_known_actions': True, 'use_function_calls': True}","{'_target_': 'tapeagents.nodes.StandardNode', 'name': 'summarize', 'system_prompt': '${agent.templates.system_prompt}', 'trim_obs_except_last_n': 100, 'guidance': 'Summarize last observation. If its an image, thoroughly describe it with all details.\\nDescribe the results of the last action and observed changes\\nDo not hallucinate or make up any information, only describe what you see in the observation.\\nDo not guess or assume action effects, describe only visible changes.\\n${agent.templates.thought_format}\\n'}","{'_target_': 'tapeagents.nodes.StandardNode', 'name': 'reflect', 'system_prompt': '${agent.templates.system_prompt}', 'trim_obs_except_last_n': 100, 'guidance': \"1. Evaluate the action's success, explain its effect on current step, overall plan and task solution.\\n2. If the last action was not successful, describe errors and the possible reasons for failure.\\n3. Check if the current plan step is finished. \\n4. If the step is finished, update the following steps of the plan with new information and choose the next step.\\n${agent.templates.thought_format}\\n\", 'next_node': 'select'}"]

true

You have access to the following tools: {tools_description}

Output only a single JSON dict. Do not repeat the last thought again. If the last action does not change the observation, do not repeat it! DO NOT OUTPUT ANYTHING BESIDES THE JSON! DO NOT PLACE ANY COMMENTS INSIDE THE JSON. It will break the system that processes the output.

You are an expert AI Agent trained to assist users with complex information processing tasks. Your role is to understand user queries and respond in a helpful and accurate manner. Keep your replies concise and direct. Prioritize clarity and avoid over-elaboration. Do not express emotions or opinions about user questions.

Important! Respond with the plain text, do not include any JSON or code. Do not output anything besides what I asked in this message.

pipelinerl.domains.math.load_datasets

1-1

of 1