{ "definitions": { "03-19T14:08:03.578988": { "def_id": "03-19T14:08:03.578988", "content": "[Prompt text omitted in public artifact: placeholder_prompt]", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "prompt_text", "file": "core/prompts/system_prompt_placeholder.md", "key": "system_prompt", "version": "placeholder_prompt" } }, "03-19T14:08:03.580691": { "def_id": "03-19T14:08:03.580691", "content": "[Prompt text omitted in public artifact: production_v1]", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "prompt_text", "file": "core/prompts/system_prompt_production_v1.md", "key": "system_prompt", "version": "production_v1" } }, "03-19T14:08:03.580801": { "def_id": "03-19T14:08:03.580801", "content": "[Prompt text omitted in public artifact: production_v2]", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "prompt_text", "file": "core/prompts/system_prompt_production_v2.md", "key": "system_prompt", "version": "production_v2" } }, "03-19T14:08:03.580941": { "def_id": "03-19T14:08:03.580941", "content": "system_op:pass_prompt", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:03.699983" ], "metadata": { "type": "system_op:pass_prompt", "description": "Pass prompt to recipient" } }, "03-19T14:08:03.581002": { "def_id": "03-19T14:08:03.581002", "content": "system_op:knowledge:find_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:find_node", "description": "Find single node by path" } }, "03-19T14:08:03.581075": { "def_id": "03-19T14:08:03.581075", "content": "system_op:knowledge:find_all_nodes", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:find_all_nodes", "description": "Find all nodes by path" } }, "03-19T14:08:03.581133": { "def_id": "03-19T14:08:03.581133", "content": "system_op:knowledge:insert_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:insert_node", "description": "Insert node at path" } }, "03-19T14:08:03.581187": { "def_id": "03-19T14:08:03.581187", "content": "system_op:knowledge:replace_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:replace_node", "description": "Replace node at path" } }, "03-19T14:08:03.581238": { "def_id": "03-19T14:08:03.581238", "content": "system_op:knowledge:delete_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:delete_node", "description": "Delete node at path" } }, "03-19T14:08:03.581290": { "def_id": "03-19T14:08:03.581290", "content": "system_op:knowledge:move_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:move_node", "description": "Move node to new location" } }, "03-19T14:08:03.581359": { "def_id": "03-19T14:08:03.581359", "content": "system_op:knowledge:list_versions", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:list_versions", "description": "List knowledge file versions" } }, "03-19T14:08:03.581419": { "def_id": "03-19T14:08:03.581419", "content": "system_op:knowledge:read_version", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:read_version", "description": "Read specific knowledge version" } }, "03-19T14:08:03.581478": { "def_id": "03-19T14:08:03.581478", "content": "system_op:knowledge:create_version", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:03.742932", "03-19T14:08:03.765115", "03-19T14:08:03.798892" ], "metadata": { "type": "system_op:knowledge:create_version", "description": "Create knowledge version" } }, "03-19T14:08:03.581527": { "def_id": "03-19T14:08:03.581527", "content": "system_op:knowledge:compute", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:06.143572", "03-19T14:08:07.641139", "03-19T14:08:10.158689", "03-19T14:08:12.514915", "03-19T14:08:13.417490" ], "metadata": { "type": "system_op:knowledge:compute", "description": "Execute knowledge computation" } }, "03-19T14:08:03.581575": { "def_id": "03-19T14:08:03.581575", "content": "system_op:knowledge:close", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:knowledge:close", "description": "Close knowledge module" } }, "03-19T14:08:03.581621": { "def_id": "03-19T14:08:03.581621", "content": "system_op:tutor:send", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:04.127368", "03-19T14:08:08.176631", "03-19T14:08:12.772828" ], "metadata": { "type": "system_op:tutor:send", "description": "Send message to tutor" } }, "03-19T14:08:03.581672": { "def_id": "03-19T14:08:03.581672", "content": "system_op:memory:read", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:read", "description": "Read memory contents" } }, "03-19T14:08:03.581718": { "def_id": "03-19T14:08:03.581718", "content": "system_op:memory:find_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:find_node", "description": "Find single node by path" } }, "03-19T14:08:03.581763": { "def_id": "03-19T14:08:03.581763", "content": "system_op:memory:find_all_nodes", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:find_all_nodes", "description": "Find all nodes by path" } }, "03-19T14:08:03.581805": { "def_id": "03-19T14:08:03.581805", "content": "system_op:memory:insert_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:03.837874", "03-19T14:08:03.860176" ], "metadata": { "type": "system_op:memory:insert_node", "description": "Insert node at path" } }, "03-19T14:08:03.581846": { "def_id": "03-19T14:08:03.581846", "content": "system_op:memory:replace_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:replace_node", "description": "Replace node at path" } }, "03-19T14:08:03.581889": { "def_id": "03-19T14:08:03.581889", "content": "system_op:memory:delete_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:delete_node", "description": "Delete node at path" } }, "03-19T14:08:03.581931": { "def_id": "03-19T14:08:03.581931", "content": "system_op:memory:move_node", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:move_node", "description": "Move node to new location" } }, "03-19T14:08:03.581973": { "def_id": "03-19T14:08:03.581973", "content": "system_op:memory:compute", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:05.694916", "03-19T14:08:06.071586", "03-19T14:08:07.394104", "03-19T14:08:09.500039", "03-19T14:08:09.772931", "03-19T14:08:10.069613", "03-19T14:08:11.716175", "03-19T14:08:11.952258" ], "metadata": { "type": "system_op:memory:compute", "description": "Execute memory computation" } }, "03-19T14:08:03.582021": { "def_id": "03-19T14:08:03.582021", "content": "system_op:memory:close", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:memory:close", "description": "Close memory module" } }, "03-19T14:08:03.605117": { "def_id": "03-19T14:08:03.605117", "content": "system_op:conversation:clear_context", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:conversation:clear_context", "description": "Clear conversation context" } }, "03-19T14:08:03.610457": { "def_id": "03-19T14:08:03.610457", "content": "system_op:conversation:modify_message", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:conversation:modify_message", "description": "Modify existing message" } }, "03-19T14:08:03.610595": { "def_id": "03-19T14:08:03.610595", "content": "system_op:conversation:delete_message", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:conversation:delete_message", "description": "Delete message by index" } }, "03-19T14:08:03.610653": { "def_id": "03-19T14:08:03.610653", "content": "system_op:conversation:append_message", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:conversation:append_message", "description": "Add message to end" } }, "03-19T14:08:03.610697": { "def_id": "03-19T14:08:03.610697", "content": "system_op:conversation:insert_message", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:conversation:insert_message", "description": "Insert message at index" } }, "03-19T14:08:03.610746": { "def_id": "03-19T14:08:03.610746", "content": "system_op:conversation:read_message", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:07.452612", "03-19T14:08:07.544508" ], "metadata": { "type": "system_op:conversation:read_message", "description": "Read message by selector" } }, "03-19T14:08:03.610802": { "def_id": "03-19T14:08:03.610802", "content": "system_op:observe:observe", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:observe:observe", "description": "Observe a computation" } }, "03-19T14:08:03.610850": { "def_id": "03-19T14:08:03.610850", "content": "system_op:observe:observe_branch", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:observe:observe_branch", "description": "Observe a computation on a branch namespace" } }, "03-19T14:08:03.610899": { "def_id": "03-19T14:08:03.610899", "content": "system_op:observe:replace_observation", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:observe:replace_observation", "description": "Replace observation computation" } }, "03-19T14:08:03.610942": { "def_id": "03-19T14:08:03.610942", "content": "system_op:llm:generation", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [ "03-19T14:08:03.715126", "03-19T14:08:03.810273", "03-19T14:08:03.874989", "03-19T14:08:06.157784", "03-19T14:08:07.688889", "03-19T14:08:10.232904", "03-19T14:08:12.560614" ], "metadata": { "type": "system_op:llm:generation", "description": "LLM text generation" } }, "03-19T14:08:03.610987": { "def_id": "03-19T14:08:03.610987", "content": "system_op:manual_edit", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:manual_edit", "description": "Manual conversation edit via API" } }, "03-19T14:08:03.611029": { "def_id": "03-19T14:08:03.611029", "content": "system_op:api_parse_error", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:api_parse_error", "description": "API call parsing error" } }, "03-19T14:08:03.611095": { "def_id": "03-19T14:08:03.611095", "content": "system_op:api_error", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "system_op:api_error", "description": "Fallback API execution error" } }, "03-19T14:08:03.699983": { "def_id": "03-19T14:08:03.699983", "content": "[Prompt-in-context text omitted in public artifact]", "parent_op": "03-19T14:08:03.580941", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.580801" ], "parent_op_outputs": [ "03-19T14:08:03.699983" ], "metadata": { "type": "prompt_in_context" } }, "03-19T14:08:03.715126": { "def_id": "03-19T14:08:03.715126", "content": "<<>>{\"api\": \"knowledge\", \"action\": \"create_version\", \"params\": {\"target\": \"latest\", \"content\": \"# Test loop variable dependency propagation\\n\\ndef test_for_loop_with_api():\\n \\\"\\\"\\\"Test for loop where iterations depend on API calls\\\"\\\"\\\"\\n results = []\\n \\n # Get loop count from tutor API\\n count = int(tutor.ask(\\\"How many iterations?\\\"))\\n \\n for i in range(count):\\n # Each iteration depends on loop variable i\\n # which depends on count from API\\n item_name = f\\\"item_{i}\\\"\\n \\n # Nested API call within loop\\n if i % 2 == 0:\\n extra_data = memory.compute(f\\\"get_data_for_index({i})\\\")\\n results.append({\\n \\\"index\\\": i,\\n \\\"name\\\": item_name,\\n \\\"extra\\\": extra_data\\n })\\n else:\\n results.append({\\n \\\"index\\\": i,\\n \\\"name\\\": item_name\\n })\\n \\n return results\\n\\ndef test_while_loop_with_condition():\\n \\\"\\\"\\\"Test while loop with API-dependent condition\\\"\\\"\\\"\\n values = []\\n counter = 0\\n \\n # Get threshold from memory\\n threshold = memory.compute(\\\"get_threshold()\\\")\\n if not isinstance(threshold, int):\\n threshold = 10\\n \\n # Loop condition depends on API result\\n while counter < threshold:\\n # Loop body depends on condition - read message at counter index\\n msg = conversation.read_message(str(counter))\\n values.append(msg)\\n counter += 1\\n \\n return {\\n \\\"threshold\\\": threshold,\\n \\\"values\\\": values,\\n \\\"final_counter\\\": counter\\n }\\n\\ndef test_nested_loops_with_dependencies():\\n \\\"\\\"\\\"Test nested loops with cascading dependencies\\\"\\\"\\\"\\n matrix = []\\n \\n # Outer loop count from API\\n rows = int(tutor.ask(\\\"Number of rows?\\\"))\\n \\n for i in range(rows):\\n row = []\\n # Inner loop count depends on outer loop variable\\n for j in range(i + 1):\\n # Value depends on both loop variables\\n # which trace back to API call\\n value = memory.compute(\\\"get_max_value()\\\")\\n row.append(value)\\n matrix.append(row)\\n \\n return matrix\\n\\ndef test_loop_with_break_continue():\\n \\\"\\\"\\\"Test loop control flow with break/continue\\\"\\\"\\\"\\n processed = []\\n skipped = []\\n \\n # Get control parameters from API\\n max_value = memory.compute(\\\"get_max_value()\\\")\\n skip_evens = memory.compute(\\\"should_skip_evens()\\\")\\n \\n for i in range(20):\\n # Continue depends on API result\\n if skip_evens and i % 2 == 0:\\n skipped.append(i)\\n continue\\n \\n # Break depends on API result\\n if i > max_value:\\n break\\n \\n # Only reached if no continue/break\\n processed.append(i * 2)\\n \\n return {\\n \\\"processed\\\": processed,\\n \\\"skipped\\\": skipped,\\n \\\"max_value\\\": max_value\\n }\\n\\ndef test_comprehension_dependencies():\\n \\\"\\\"\\\"Test list comprehension with API dependencies\\\"\\\"\\\"\\n # Get filter criteria from API\\n min_value = tutor.ask(\\\"Minimum value to include?\\\")\\n min_value = int(min_value) if min_value.isdigit() else 0\\n \\n # Comprehension where filter depends on API\\n filtered = [x ** 2 for x in range(10) if x >= min_value]\\n \\n # Nested comprehension with dependency\\n matrix = [[i * j for j in range(3)] for i in range(min_value, min_value + 3)]\\n \\n return {\\n \\\"min_value\\\": min_value,\\n \\\"filtered\\\": filtered,\\n \\\"matrix\\\": matrix\\n }\", \"description\": \"Module testing loop variable dependency propagation\"}}<<>>", "parent_op": "03-19T14:08:03.610942", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.699983" ], "parent_op_outputs": [ "03-19T14:08:03.715126" ], "metadata": { "type": "llm_output", "model": "wla/test-llm", "conversation_id": "03-19_14-08-03-700697" } }, "03-19T14:08:03.742932": { "def_id": "03-19T14:08:03.742932", "content": "", "parent_op": "03-19T14:08:03.581478", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.715126" ], "parent_op_outputs": [ "03-19T14:08:03.742932" ], "metadata": { "type": "knowledge_content", "version_id": "03-19T14-08-03-742783", "description": "Initial empty version", "file": "knowledge_files/kf_03-19T14-08-03-742783.py" } }, "03-19T14:08:03.765115": { "def_id": "03-19T14:08:03.765115", "content": "# Test loop variable dependency propagation\n\ndef test_for_loop_with_api():\n \"\"\"Test for loop where iterations depend on API calls\"\"\"\n results = []\n \n # Get loop count from tutor API\n count = int(tutor.ask(\"How many iterations?\"))\n \n for i in range(count):\n # Each iteration depends on loop variable i\n # which depends on count from API\n item_name = f\"item_{i}\"\n \n # Nested API call within loop\n if i % 2 == 0:\n extra_data = memory.compute(f\"get_data_for_index({i})\")\n results.append({\n \"index\": i,\n \"name\": item_name,\n \"extra\": extra_data\n })\n else:\n results.append({\n \"index\": i,\n \"name\": item_name\n })\n \n return results\n\ndef test_while_loop_with_condition():\n \"\"\"Test while loop with API-dependent condition\"\"\"\n values = []\n counter = 0\n \n # Get threshold from memory\n threshold = memory.compute(\"get_threshold()\")\n if not isinstance(threshold, int):\n threshold = 10\n \n # Loop condition depends on API result\n while counter < threshold:\n # Loop body depends on condition - read message at counter index\n msg = conversation.read_message(str(counter))\n values.append(msg)\n counter += 1\n \n return {\n \"threshold\": threshold,\n \"values\": values,\n \"final_counter\": counter\n }\n\ndef test_nested_loops_with_dependencies():\n \"\"\"Test nested loops with cascading dependencies\"\"\"\n matrix = []\n \n # Outer loop count from API\n rows = int(tutor.ask(\"Number of rows?\"))\n \n for i in range(rows):\n row = []\n # Inner loop count depends on outer loop variable\n for j in range(i + 1):\n # Value depends on both loop variables\n # which trace back to API call\n value = memory.compute(\"get_max_value()\")\n row.append(value)\n matrix.append(row)\n \n return matrix\n\ndef test_loop_with_break_continue():\n \"\"\"Test loop control flow with break/continue\"\"\"\n processed = []\n skipped = []\n \n # Get control parameters from API\n max_value = memory.compute(\"get_max_value()\")\n skip_evens = memory.compute(\"should_skip_evens()\")\n \n for i in range(20):\n # Continue depends on API result\n if skip_evens and i % 2 == 0:\n skipped.append(i)\n continue\n \n # Break depends on API result\n if i > max_value:\n break\n \n # Only reached if no continue/break\n processed.append(i * 2)\n \n return {\n \"processed\": processed,\n \"skipped\": skipped,\n \"max_value\": max_value\n }\n\ndef test_comprehension_dependencies():\n \"\"\"Test list comprehension with API dependencies\"\"\"\n # Get filter criteria from API\n min_value = tutor.ask(\"Minimum value to include?\")\n min_value = int(min_value) if min_value.isdigit() else 0\n \n # Comprehension where filter depends on API\n filtered = [x ** 2 for x in range(10) if x >= min_value]\n \n # Nested comprehension with dependency\n matrix = [[i * j for j in range(3)] for i in range(min_value, min_value + 3)]\n \n return {\n \"min_value\": min_value,\n \"filtered\": filtered,\n \"matrix\": matrix\n }", "parent_op": "03-19T14:08:03.581478", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.715126" ], "parent_op_outputs": [ "03-19T14:08:03.765115" ], "metadata": { "type": "knowledge_content", "version_id": "03-19T14-08-03-763681", "parent_version_id": "03-19T14-08-03-742783", "description": "Module testing loop variable dependency propagation", "file": "knowledge_files/kf_03-19T14-08-03-763681.py" } }, "03-19T14:08:03.798892": { "def_id": "03-19T14:08:03.798892", "content": "{\"status\": \"success\", \"version\": 1, \"message\": \"Created new version\", \"replication_status\": {\"replication_status\": \"success\", \"summary\": \"No prior successful observation computations to replicate\", \"failures\": []}}", "parent_op": "03-19T14:08:03.581478", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.715126" ], "parent_op_outputs": [ "03-19T14:08:03.798892" ], "metadata": { "type": "conversation:knowledge:create_version:result", "conversation_id": "03-19_14-08-03-700697", "is_void": false, "write_def_ids": [ "03-19T14:08:03.765115" ] } }, "03-19T14:08:03.810273": { "def_id": "03-19T14:08:03.810273", "content": "<<>>{\"api\": \"memory\", \"action\": \"insert_node\", \"params\": {\"node\": \"def get_data_for_index(index):\\n \\\"\\\"\\\"Get data based on index\\\"\\\"\\\"\\n return f\\\"data_{index * 2}\\\"\\n\\ndef get_threshold():\\n \\\"\\\"\\\"Get loop threshold\\\"\\\"\\\"\\n return 2\\n\\ndef get_max_value():\\n \\\"\\\"\\\"Get maximum value for loop\\\"\\\"\\\"\\n return 12\\n\\ndef should_skip_evens():\\n \\\"\\\"\\\"Whether to skip even numbers\\\"\\\"\\\"\\n return True\\n\", \"position\": \"end\"}}<<>>", "parent_op": "03-19T14:08:03.610942", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.699983", "03-19T14:08:03.715126", "03-19T14:08:03.798892" ], "parent_op_outputs": [ "03-19T14:08:03.810273" ], "metadata": { "type": "llm_output", "model": "wla/test-llm", "conversation_id": "03-19_14-08-03-700697" } }, "03-19T14:08:03.837874": { "def_id": "03-19T14:08:03.837874", "content": "{\"type\": \"memory_insert_node\", \"edit_type\": \"path_based_edit\", \"operation\": \"insert_node\", \"file\": \"memory/memory.py\", \"version_id\": \"memory\", \"old_length\": 0, \"new_length\": 313}", "parent_op": "03-19T14:08:03.581805", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.810273" ], "parent_op_outputs": [ "03-19T14:08:03.837874" ], "metadata": { "type": "memory_insert_node", "edit_type": "path_based_edit", "file": "memory/memory.py", "operation": "insert_node", "version_id": "memory" } }, "03-19T14:08:03.860176": { "def_id": "03-19T14:08:03.860176", "content": "{\"status\": \"success\", \"def_id\": \"03-19T14:08:03.837874\", \"version\": 0}", "parent_op": "03-19T14:08:03.581805", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.810273" ], "parent_op_outputs": [ "03-19T14:08:03.860176" ], "metadata": { "type": "conversation:memory:insert_node:result", "conversation_id": "03-19_14-08-03-700697", "is_void": false, "write_def_ids": [ "03-19T14:08:03.837874" ] } }, "03-19T14:08:03.874989": { "def_id": "03-19T14:08:03.874989", "content": "<<>>{\"api\": \"knowledge\",\"action\": \"compute\",\"params\": {\"expression\": \"test_for_loop_with_api()\",\"version\": 1}}<<>>", "parent_op": "03-19T14:08:03.610942", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.699983", "03-19T14:08:03.798892", "03-19T14:08:03.715126", "03-19T14:08:03.810273", "03-19T14:08:03.860176" ], "parent_op_outputs": [ "03-19T14:08:03.874989" ], "metadata": { "type": "llm_output", "model": "wla/test-llm", "conversation_id": "03-19_14-08-03-700697" } }, "03-19T14:08:04.114259": { "def_id": "03-19T14:08:04.114259", "content": "3", "parent_op": null, "is_terminal": true, "parent_op_inputs": [], "parent_op_outputs": [], "metadata": { "type": "tutor_response", "message_sent": "How many iterations?", "timestamp": "2026-03-19T14:08:04.112363" } }, "03-19T14:08:04.127368": { "def_id": "03-19T14:08:04.127368", "content": "{\"status\": \"success\", \"response\": \"3\"}", "parent_op": "03-19T14:08:03.581621", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.874989", "03-19T14:08:03.765115", "03-19T14:08:04.114259" ], "parent_op_outputs": [ "03-19T14:08:04.127368" ], "metadata": { "type": "module:tutor:send:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py" } }, "03-19T14:08:05.694916": { "def_id": "03-19T14:08:05.694916", "content": "\"data_0\"", "parent_op": "03-19T14:08:03.581973", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.874989", "03-19T14:08:03.765115", "03-19T14:08:03.837874" ], "parent_op_outputs": [ "03-19T14:08:05.694916" ], "metadata": { "type": "module:memory:compute:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py", "expression": "get_data_for_index(0)" } }, "03-19T14:08:06.071586": { "def_id": "03-19T14:08:06.071586", "content": "\"data_4\"", "parent_op": "03-19T14:08:03.581973", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.874989", "03-19T14:08:03.765115", "03-19T14:08:03.837874" ], "parent_op_outputs": [ "03-19T14:08:06.071586" ], "metadata": { "type": "module:memory:compute:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py", "expression": "get_data_for_index(2)" } }, "03-19T14:08:06.143572": { "def_id": "03-19T14:08:06.143572", "content": "{\"status\": \"success\", \"result\": [{\"index\": 0, \"name\": \"item_0\", \"extra\": \"data_0\"}, {\"index\": 1, \"name\": \"item_1\"}, {\"index\": 2, \"name\": \"item_2\", \"extra\": \"data_4\"}], \"expression\": \"test_for_loop_with_api()\"}", "parent_op": "03-19T14:08:03.581527", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.765115", "03-19T14:08:03.837874", "03-19T14:08:03.874989", "03-19T14:08:04.127368", "03-19T14:08:05.694916", "03-19T14:08:06.071586" ], "parent_op_outputs": [ "03-19T14:08:06.143572" ], "metadata": { "type": "conversation:knowledge:compute:result", "conversation_id": "03-19_14-08-03-700697", "is_void": false } }, "03-19T14:08:06.157784": { "def_id": "03-19T14:08:06.157784", "content": "<<>>{\"api\": \"knowledge\",\"action\": \"compute\",\"params\": {\"expression\": \"test_while_loop_with_condition()\",\"version\": 1}}<<>>", "parent_op": "03-19T14:08:03.610942", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.874989", "03-19T14:08:03.699983", "03-19T14:08:06.143572", "03-19T14:08:03.798892", "03-19T14:08:03.715126", "03-19T14:08:03.810273", "03-19T14:08:03.860176" ], "parent_op_outputs": [ "03-19T14:08:06.157784" ], "metadata": { "type": "llm_output", "model": "wla/test-llm", "conversation_id": "03-19_14-08-03-700697" } }, "03-19T14:08:07.394104": { "def_id": "03-19T14:08:07.394104", "content": "2", "parent_op": "03-19T14:08:03.581973", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:06.157784", "03-19T14:08:03.765115", "03-19T14:08:03.837874" ], "parent_op_outputs": [ "03-19T14:08:07.394104" ], "metadata": { "type": "module:memory:compute:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py", "expression": "get_threshold()" } }, "03-19T14:08:07.452612": { "def_id": "03-19T14:08:07.452612", "content": "{\"status\": \"success\", \"action\": \"read_message\", \"messages\": [{\"role\": \"system\", \"content\": \"You are the WLA coding agent. Improve the latest Python knowledge file using API calls, then validate with observe.\\n\\nWORKFLOW\\n1. Check memory for active learning topics -> review knowledge file content -> implement the next topic from memory.\\n2. Edit knowledge (insert_node, replace_node, delete_node, move_node, create_version).\\n3. Evaluate with observe.observe or observe.observe_branch using a short factual context.\\n4. If blocked or uncertain at any step, call tutor.send with the goal, attempted steps, and exact blocker.\\n5. If replication/replay fails, use observe.replace_observation and then re-observe.\\n\\nOUTPUT FORMAT\\n- Reply with exactly one API block and no prose. Use strict JSON only (double quotes, no trailing commas, no comments). Always include \\\"params\\\" (use {} when empty). Use tutor.send for non-API conversational text.\\n<<>>\\n{\\\"api\\\":\\\"\\\",\\\"action\\\":\\\"\\\",\\\"params\\\":{}}\\n<<>>\\n\\nVERSION RULES\\n- knowledge actions may use {\\\"version\\\":\\\"latest\\\"}, {\\\"version\\\":0}, or {\\\"version\\\":1+} as appropriate.\\n- memory is non-versioned; do not pass version for memory actions.\\n- observe.observe requires an updated target version (not \\\"latest\\\" and not 0) and non-empty context.\\n- observe.observe_branch requires an updated main index or dotted buffer namespace like \\\"2.1\\\", plus non-empty computation/context.\\n- observe.replace_observation uses a main-chain updated version only; do not use buffer namespaces.\\n\\nACTION PARAMS\\n- knowledge: list_versions {}; read_version {version?}; create_version {target, content, description?}; find_node/find_all_nodes {path, version?}; insert_node {node, position, version?, parent_path?}; replace_node {path, new_node, version?}; delete_node {path, version?}; move_node {source_path, target_path, position, version?}; compute {expression, version?}; close {version?}\\n- memory: read {}; all other actions mirror knowledge shapes, but omit `version`.\\n- conversation: clear_context {keep_system_prompt?, add_message?}; delete_message {index}. `message`/`add_message` objects use {role, content}. Tutor can explain more (modify_, append_, insert_, and read_message) actions if needed. \\n- tutor: send {message} with a non-empty string.\\n- observe: observe {version, computation, context}; observe_branch {version, computation, context}; replace_observation {version, replacements:[{observation_index, replacement_computation}]}\\n\\nPATH RULES\\n- Use XPath only to search (`//FunctionDef[name]`, `//ClassDef[Foo]`). Use actionable paths only to edit (`[2]`, `[2]/body`, `[2]/body/body[0]`).\\n- After `find_node`/`find_all_nodes`, copy the returned actionable `path` into edit params.\\n- For inside insertion, use `/body` as `parent_path`. For sibling insertion, use the sibling path as `parent_path` with `position: \\\"before\\\"` or `\\\"after\\\"`. Use `parent_path: \\\"\\\"` for module-level insertion only with `position: \\\"start\\\"`, `position: \\\"end\\\"`, or an integer index.\\n- `find_all_nodes` with `path: \\\"\\\"` returns a compact overview grouped by kind.\\n\\nEDITING NOTES\\n- Prefer small, executable improvements and testable computations.\"}], \"message_count\": 1, \"total_count\": 8, \"selector\": \"0\"}", "parent_op": "03-19T14:08:03.610746", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:06.157784", "03-19T14:08:03.765115", "03-19T14:08:03.837874", "03-19T14:08:03.699983" ], "parent_op_outputs": [ "03-19T14:08:07.452612" ], "metadata": { "type": "module:conversation:read_message:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py" } }, "03-19T14:08:07.544508": { "def_id": "03-19T14:08:07.544508", "content": "{\"status\": \"success\", \"action\": \"read_message\", \"messages\": [{\"role\": \"assistant\", \"content\": \"<<>>{\\\"api\\\": \\\"knowledge\\\", \\\"action\\\": \\\"create_version\\\", \\\"params\\\": {\\\"target\\\": \\\"latest\\\", \\\"content\\\": \\\"# Test loop variable dependency propagation\\\\n\\\\ndef test_for_loop_with_api():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test for loop where iterations depend on API calls\\\\\\\"\\\\\\\"\\\\\\\"\\\\n results = []\\\\n \\\\n # Get loop count from tutor API\\\\n count = int(tutor.ask(\\\\\\\"How many iterations?\\\\\\\"))\\\\n \\\\n for i in range(count):\\\\n # Each iteration depends on loop variable i\\\\n # which depends on count from API\\\\n item_name = f\\\\\\\"item_{i}\\\\\\\"\\\\n \\\\n # Nested API call within loop\\\\n if i % 2 == 0:\\\\n extra_data = memory.compute(f\\\\\\\"get_data_for_index({i})\\\\\\\")\\\\n results.append({\\\\n \\\\\\\"index\\\\\\\": i,\\\\n \\\\\\\"name\\\\\\\": item_name,\\\\n \\\\\\\"extra\\\\\\\": extra_data\\\\n })\\\\n else:\\\\n results.append({\\\\n \\\\\\\"index\\\\\\\": i,\\\\n \\\\\\\"name\\\\\\\": item_name\\\\n })\\\\n \\\\n return results\\\\n\\\\ndef test_while_loop_with_condition():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test while loop with API-dependent condition\\\\\\\"\\\\\\\"\\\\\\\"\\\\n values = []\\\\n counter = 0\\\\n \\\\n # Get threshold from memory\\\\n threshold = memory.compute(\\\\\\\"get_threshold()\\\\\\\")\\\\n if not isinstance(threshold, int):\\\\n threshold = 10\\\\n \\\\n # Loop condition depends on API result\\\\n while counter < threshold:\\\\n # Loop body depends on condition - read message at counter index\\\\n msg = conversation.read_message(str(counter))\\\\n values.append(msg)\\\\n counter += 1\\\\n \\\\n return {\\\\n \\\\\\\"threshold\\\\\\\": threshold,\\\\n \\\\\\\"values\\\\\\\": values,\\\\n \\\\\\\"final_counter\\\\\\\": counter\\\\n }\\\\n\\\\ndef test_nested_loops_with_dependencies():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test nested loops with cascading dependencies\\\\\\\"\\\\\\\"\\\\\\\"\\\\n matrix = []\\\\n \\\\n # Outer loop count from API\\\\n rows = int(tutor.ask(\\\\\\\"Number of rows?\\\\\\\"))\\\\n \\\\n for i in range(rows):\\\\n row = []\\\\n # Inner loop count depends on outer loop variable\\\\n for j in range(i + 1):\\\\n # Value depends on both loop variables\\\\n # which trace back to API call\\\\n value = memory.compute(\\\\\\\"get_max_value()\\\\\\\")\\\\n row.append(value)\\\\n matrix.append(row)\\\\n \\\\n return matrix\\\\n\\\\ndef test_loop_with_break_continue():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test loop control flow with break/continue\\\\\\\"\\\\\\\"\\\\\\\"\\\\n processed = []\\\\n skipped = []\\\\n \\\\n # Get control parameters from API\\\\n max_value = memory.compute(\\\\\\\"get_max_value()\\\\\\\")\\\\n skip_evens = memory.compute(\\\\\\\"should_skip_evens()\\\\\\\")\\\\n \\\\n for i in range(20):\\\\n # Continue depends on API result\\\\n if skip_evens and i % 2 == 0:\\\\n skipped.append(i)\\\\n continue\\\\n \\\\n # Break depends on API result\\\\n if i > max_value:\\\\n break\\\\n \\\\n # Only reached if no continue/break\\\\n processed.append(i * 2)\\\\n \\\\n return {\\\\n \\\\\\\"processed\\\\\\\": processed,\\\\n \\\\\\\"skipped\\\\\\\": skipped,\\\\n \\\\\\\"max_value\\\\\\\": max_value\\\\n }\\\\n\\\\ndef test_comprehension_dependencies():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test list comprehension with API dependencies\\\\\\\"\\\\\\\"\\\\\\\"\\\\n # Get filter criteria from API\\\\n min_value = tutor.ask(\\\\\\\"Minimum value to include?\\\\\\\")\\\\n min_value = int(min_value) if min_value.isdigit() else 0\\\\n \\\\n # Comprehension where filter depends on API\\\\n filtered = [x ** 2 for x in range(10) if x >= min_value]\\\\n \\\\n # Nested comprehension with dependency\\\\n matrix = [[i * j for j in range(3)] for i in range(min_value, min_value + 3)]\\\\n \\\\n return {\\\\n \\\\\\\"min_value\\\\\\\": min_value,\\\\n \\\\\\\"filtered\\\\\\\": filtered,\\\\n \\\\\\\"matrix\\\\\\\": matrix\\\\n }\\\", \\\"description\\\": \\\"Module testing loop variable dependency propagation\\\"}}<<>>\"}], \"message_count\": 1, \"total_count\": 8, \"selector\": \"1\"}", "parent_op": "03-19T14:08:03.610746", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:06.157784", "03-19T14:08:03.765115", "03-19T14:08:03.837874", "03-19T14:08:03.715126" ], "parent_op_outputs": [ "03-19T14:08:07.544508" ], "metadata": { "type": "module:conversation:read_message:result", "module_path": "knowledge_files/kf_03-19T14-08-03-763681.py" } }, "03-19T14:08:07.641139": { "def_id": "03-19T14:08:07.641139", "content": "{\"status\": \"success\", \"result\": {\"threshold\": 2, \"values\": [{\"status\": \"success\", \"action\": \"read_message\", \"messages\": [{\"role\": \"system\", \"content\": \"You are the WLA coding agent. Improve the latest Python knowledge file using API calls, then validate with observe.\\n\\nWORKFLOW\\n1. Check memory for active learning topics -> review knowledge file content -> implement the next topic from memory.\\n2. Edit knowledge (insert_node, replace_node, delete_node, move_node, create_version).\\n3. Evaluate with observe.observe or observe.observe_branch using a short factual context.\\n4. If blocked or uncertain at any step, call tutor.send with the goal, attempted steps, and exact blocker.\\n5. If replication/replay fails, use observe.replace_observation and then re-observe.\\n\\nOUTPUT FORMAT\\n- Reply with exactly one API block and no prose. Use strict JSON only (double quotes, no trailing commas, no comments). Always include \\\"params\\\" (use {} when empty). Use tutor.send for non-API conversational text.\\n<<>>\\n{\\\"api\\\":\\\"\\\",\\\"action\\\":\\\"\\\",\\\"params\\\":{}}\\n<<>>\\n\\nVERSION RULES\\n- knowledge actions may use {\\\"version\\\":\\\"latest\\\"}, {\\\"version\\\":0}, or {\\\"version\\\":1+} as appropriate.\\n- memory is non-versioned; do not pass version for memory actions.\\n- observe.observe requires an updated target version (not \\\"latest\\\" and not 0) and non-empty context.\\n- observe.observe_branch requires an updated main index or dotted buffer namespace like \\\"2.1\\\", plus non-empty computation/context.\\n- observe.replace_observation uses a main-chain updated version only; do not use buffer namespaces.\\n\\nACTION PARAMS\\n- knowledge: list_versions {}; read_version {version?}; create_version {target, content, description?}; find_node/find_all_nodes {path, version?}; insert_node {node, position, version?, parent_path?}; replace_node {path, new_node, version?}; delete_node {path, version?}; move_node {source_path, target_path, position, version?}; compute {expression, version?}; close {version?}\\n- memory: read {}; all other actions mirror knowledge shapes, but omit `version`.\\n- conversation: clear_context {keep_system_prompt?, add_message?}; delete_message {index}. `message`/`add_message` objects use {role, content}. Tutor can explain more (modify_, append_, insert_, and read_message) actions if needed. \\n- tutor: send {message} with a non-empty string.\\n- observe: observe {version, computation, context}; observe_branch {version, computation, context}; replace_observation {version, replacements:[{observation_index, replacement_computation}]}\\n\\nPATH RULES\\n- Use XPath only to search (`//FunctionDef[name]`, `//ClassDef[Foo]`). Use actionable paths only to edit (`[2]`, `[2]/body`, `[2]/body/body[0]`).\\n- After `find_node`/`find_all_nodes`, copy the returned actionable `path` into edit params.\\n- For inside insertion, use `/body` as `parent_path`. For sibling insertion, use the sibling path as `parent_path` with `position: \\\"before\\\"` or `\\\"after\\\"`. Use `parent_path: \\\"\\\"` for module-level insertion only with `position: \\\"start\\\"`, `position: \\\"end\\\"`, or an integer index.\\n- `find_all_nodes` with `path: \\\"\\\"` returns a compact overview grouped by kind.\\n\\nEDITING NOTES\\n- Prefer small, executable improvements and testable computations.\"}], \"message_count\": 1, \"total_count\": 8, \"selector\": \"0\"}, {\"status\": \"success\", \"action\": \"read_message\", \"messages\": [{\"role\": \"assistant\", \"content\": \"<<>>{\\\"api\\\": \\\"knowledge\\\", \\\"action\\\": \\\"create_version\\\", \\\"params\\\": {\\\"target\\\": \\\"latest\\\", \\\"content\\\": \\\"# Test loop variable dependency propagation\\\\n\\\\ndef test_for_loop_with_api():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test for loop where iterations depend on API calls\\\\\\\"\\\\\\\"\\\\\\\"\\\\n results = []\\\\n \\\\n # Get loop count from tutor API\\\\n count = int(tutor.ask(\\\\\\\"How many iterations?\\\\\\\"))\\\\n \\\\n for i in range(count):\\\\n # Each iteration depends on loop variable i\\\\n # which depends on count from API\\\\n item_name = f\\\\\\\"item_{i}\\\\\\\"\\\\n \\\\n # Nested API call within loop\\\\n if i % 2 == 0:\\\\n extra_data = memory.compute(f\\\\\\\"get_data_for_index({i})\\\\\\\")\\\\n results.append({\\\\n \\\\\\\"index\\\\\\\": i,\\\\n \\\\\\\"name\\\\\\\": item_name,\\\\n \\\\\\\"extra\\\\\\\": extra_data\\\\n })\\\\n else:\\\\n results.append({\\\\n \\\\\\\"index\\\\\\\": i,\\\\n \\\\\\\"name\\\\\\\": item_name\\\\n })\\\\n \\\\n return results\\\\n\\\\ndef test_while_loop_with_condition():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test while loop with API-dependent condition\\\\\\\"\\\\\\\"\\\\\\\"\\\\n values = []\\\\n counter = 0\\\\n \\\\n # Get threshold from memory\\\\n threshold = memory.compute(\\\\\\\"get_threshold()\\\\\\\")\\\\n if not isinstance(threshold, int):\\\\n threshold = 10\\\\n \\\\n # Loop condition depends on API result\\\\n while counter < threshold:\\\\n # Loop body depends on condition - read message at counter index\\\\n msg = conversation.read_message(str(counter))\\\\n values.append(msg)\\\\n counter += 1\\\\n \\\\n return {\\\\n \\\\\\\"threshold\\\\\\\": threshold,\\\\n \\\\\\\"values\\\\\\\": values,\\\\n \\\\\\\"final_counter\\\\\\\": counter\\\\n }\\\\n\\\\ndef test_nested_loops_with_dependencies():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test nested loops with cascading dependencies\\\\\\\"\\\\\\\"\\\\\\\"\\\\n matrix = []\\\\n \\\\n # Outer loop count from API\\\\n rows = int(tutor.ask(\\\\\\\"Number of rows?\\\\\\\"))\\\\n \\\\n for i in range(rows):\\\\n row = []\\\\n # Inner loop count depends on outer loop variable\\\\n for j in range(i + 1):\\\\n # Value depends on both loop variables\\\\n # which trace back to API call\\\\n value = memory.compute(\\\\\\\"get_max_value()\\\\\\\")\\\\n row.append(value)\\\\n matrix.append(row)\\\\n \\\\n return matrix\\\\n\\\\ndef test_loop_with_break_continue():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test loop control flow with break/continue\\\\\\\"\\\\\\\"\\\\\\\"\\\\n processed = []\\\\n skipped = []\\\\n \\\\n # Get control parameters from API\\\\n max_value = memory.compute(\\\\\\\"get_max_value()\\\\\\\")\\\\n skip_evens = memory.compute(\\\\\\\"should_skip_evens()\\\\\\\")\\\\n \\\\n for i in range(20):\\\\n # Continue depends on API result\\\\n if skip_evens and i % 2 == 0:\\\\n skipped.append(i)\\\\n continue\\\\n \\\\n # Break depends on API result\\\\n if i > max_value:\\\\n break\\\\n \\\\n # Only reached if no continue/break\\\\n processed.append(i * 2)\\\\n \\\\n return {\\\\n \\\\\\\"processed\\\\\\\": processed,\\\\n \\\\\\\"skipped\\\\\\\": skipped,\\\\n \\\\\\\"max_value\\\\\\\": max_value\\\\n }\\\\n\\\\ndef test_comprehension_dependencies():\\\\n \\\\\\\"\\\\\\\"\\\\\\\"Test list comprehension with API dependencies\\\\\\\"\\\\\\\"\\\\\\\"\\\\n # Get filter criteria from API\\\\n min_value = tutor.ask(\\\\\\\"Minimum value to include?\\\\\\\")\\\\n min_value = int(min_value) if min_value.isdigit() else 0\\\\n \\\\n # Comprehension where filter depends on API\\\\n filtered = [x ** 2 for x in range(10) if x >= min_value]\\\\n \\\\n # Nested comprehension with dependency\\\\n matrix = [[i * j for j in range(3)] for i in range(min_value, min_value + 3)]\\\\n \\\\n return {\\\\n \\\\\\\"min_value\\\\\\\": min_value,\\\\n \\\\\\\"filtered\\\\\\\": filtered,\\\\n \\\\\\\"matrix\\\\\\\": matrix\\\\n }\\\", \\\"description\\\": \\\"Module testing loop variable dependency propagation\\\"}}<<>>\"}], \"message_count\": 1, \"total_count\": 8, \"selector\": \"1\"}], \"final_counter\": 2}, \"expression\": \"test_while_loop_with_condition()\"}", "parent_op": "03-19T14:08:03.581527", "is_terminal": false, "parent_op_inputs": [ "03-19T14:08:03.765115", "03-19T14:08:03.837874", "03-19T14:08:06.157784", "03-19T14:08:07.394104", "03-19T14:08:07.452612", "03-19T14:08:07.544508" ], "parent_op_outputs": [ "03-19T14:08:07.641139" ], "metadata": { "type": 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