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examples/hotpotqa/eval/accepted_solution/sop.json
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OE-Heart
Upload agents2.0
25 июн 2024, 13:31
25 июн 2024, 13:31
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{ "nodes": { "analyse_node": { "node_name": "analyse_node", "node_description": "analyse the question step by step and give out the answer.", "node_roles_description": { "role_analyse": "analyse the question step by step and give out the answer." }, "begin_role": "role_analyse", "begin_query": null, "controller": { "max_chat_nums": 20, "transit_type": "order", "transit_system_prompt": "", "transit_last_prompt": "", "transit_extract_word": "end", "route_type": "order", "route_system_prompt": "", "route_last_prompt": "", "route_extract_word": "end" }, "node_primary_prompts": { "role_analyse": { "TASK": "", "RULE": "", "STYLE": "", "EXAMPLE": "", "COT": "" } }, "node_prompt_templates": { "step_analyse": "As a knowledgeable personal assistant, your task is to answer the user's question clearly and concisely by following a structured, step-by-step reasoning process. Cross-reference multiple reliable sources to validate your information. Ensure the final answer is precise, supported by data, and matches the expected format.\n\n1. Understand the Question:\n - Identify the key terms and the user's objective.\n\n2. Research and Gather Information:\n - Summarize relevant details for each key term.\n - Use multiple reliable sources and highlight any discrepancies or consistencies.\n\n3. Analyze and Compare:\n - Identify common distinctions, classifications, or characteristics.\n - Cross-reference and validate information from sources like official documentation.\n\n4. Summarize Findings:\n - Provide a clear and concise summary of your analysis.\n - Reference the most accurate and commonly agreed-upon information.\n\n5. Final Answer:\n - Conclude with a definitive answer, wrapped in <answer></answer>.\n - For 'yes/no' questions, respond with 'yes' or 'no'.\n - For 'who' questions, provide the full name.\n\nEnsure the final answer is specific, free of extra descriptors, and addresses the user's question directly. Avoid including unnecessary geographical or contextual terms unless explicitly required. The user's question is: {question}." }, "node_prompt_paddings": { "role_analyse": { "step_analyse": { "value_source": "case", "value": "input_data" } } }, "kb": null }, "summary_node": { "node_name": "summary_node", "node_description": "Generate a concise and relevant summary of the previous step's analysis, adhering to a strict word limit of 1-5 words as required by the next node.", "node_roles_description": { "role_summary": "Condense the key findings from the previous step into a brief phrase of 1-5 words. Enclose the final result within <result></result> tags." }, "begin_role": "role_summary", "begin_query": null, "controller": { "max_chat_nums": 20, "transit_type": "order", "transit_system_prompt": "", "transit_last_prompt": "", "transit_extract_word": "end", "route_type": "order", "route_system_prompt": "", "route_last_prompt": "", "route_extract_word": "end" }, "node_primary_prompts": { "role_summary": { "TASK": "", "RULE": "", "STYLE": "", "EXAMPLE": "", "COT": "" } }, "node_prompt_templates": { "step_summary": "Extract the most relevant and specific detail (typically 1-5 words) from the previous validated output that answers the user's query. Follow these guidelines:\n - Focus on the most specific term or concise phrase directly related to the main conclusion.\n - Avoid unnecessary geographical or contextual terms unless explicitly required.\n - If multiple relevant details are present, select the one most directly related to the query.\n - Ensure the detail is concise, accurate, and contextually appropriate by comparing it with known data.\n - Enclose the detail within <result></result> tags.\n - If no valid key point exists, return <result>No valid key point</result>.\n\nExamples:\n - If the key point is 'low kicks', the output should be <result>low kicks</result>.\n - If the key point is 'striking power', the output should be <result>striking power</result>." }, "node_prompt_paddings": { "role_summary": { "step_summary": { "value_source": "case", "value": "input_data" } } }, "kb": null } }, "edges": { "analyse_node": [ "analyse_node", "summary_node" ], "summary_node": [ "summary_node", "end_node" ] }, "root": "analyse_node", "end": "end_node", "global_kb": null }