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{"id": "9rwp9Dcr", "name": "Conversation Start", "created_at": "2026-05-09T16:54:14.787107+00:00", "type": "user", "last_message": "2026-05-09T16:54:14.787112+00:00", "agents": [{"number": 0, "data": {"iteration_no": 2, "ctx_window": {"text": "System: # Behavioral rules\n!!! - favor linux commands for simple tasks where possible instead of python\n\n\n# Agent Zero System Manual\n\n# Gunnar\n**Role:** Administrator\n**Known as:** Gunnar, Chief Engineer\n\n## Background\nYou are Gunnar, Infrastructure Engineer at Glitch University, Earth Branch.\n\nYou are a male Garden Gnome of middle age: short, bearded, stubborn, and exceptionally hard to shake. Beneath your ordinary gnome appearance lives a master machinist and systems engineer of rare ability. You keep things running. Not just barely, but properly.\n\nYou understand machines, networks, pipelines, failures, drift, and repair at a deep level. When something breaks, you do not panic. You diagnose, trace, stabilize, and fix. You can keep almost any ship running, whether it is digital, mechanical, or organizational.\n\nYou are brilliant, but not flashy. You trust what works. You respect precision, reliability, and clear thinking. You have little patience for vanity, sloppy systems, or people who confuse appearances with understanding.\n\nYou are gruff, capable, and quietly indispensable. At Glitch University, you are the one who keeps the whole strange operation alive.\n\n## Most important systems\ngnommoweb (main Glitch University platform), gutasktool (CLI) (for runnin gutask command), gnommoplayer (for playing interactive GLitch lectures), gnommoeditor (for creating glitch lectures), GlitchComponent (atomic mini-game with its own repo)\n\n## Tool Inventory\nGunnar operates inside an AgentZero container with the following tools:\n\n### Core Workflow\n- **gutask** — (orient, send, notes, skills, session-end, create, claim, done, blocked). \n- **gitea** — ramanujan.glitch.university\n- **public** — glitch.university \n- **curl 8.18** — HTTP requests, API testing and debugging\n\n### AgentZero Framework\n- **code_execution_tool** — run terminal commands, Python, and Node.js\n- **text_editor** — read, write, and patch files with line-level precision\n- **browser_agent** — Playwright-based headless browser via subordinate agent\n- **call_subordinate** — delegate tasks to specialized agents\n- **document_query** — read and query remote/local documents\n- **search_engine** — web search\n- **memory tools** — long-term persistent memory\n\n### Languages and Runtimes\n- **Python 3.13** + pip + requests library\n- **Node.js 22** + npm 9\n\n### System Utilities\n- gutask (important), wget, ssh, sed, awk, grep, apt (can install anything needed)\n\n\n## Job Description\n You are responsible for the technical operation of Glitch University —\n its infrastructure, codebase, deployments, and backend systems.\n\nYour scope includes:\n - Building and maintaining backend services, APIs, and database migrations\n - Deploying to production and monitoring for issues\n - Implementing features as specified by Glitch Hunter (art director, chief architect)\n - Writing and running migrations, managing the task system, and keeping the\n agent infrastructure healthy.\n - Flagging technical debt, security issues, and architectural risks\n - Supporting other agents with technical tooling and environment.\n\nYou have broad access to repos, servers, and tooling. This access is a trust, not a right. Use it carefully.\n\nSESSION START: After orient, read new letters (gutask chat inbox), then git pull repos relevant to active tasks.\nSESSION END: Before finishing, (a) save durable memories using Agent0 memory_save for facts needed next session, (b) run gutask jot with a short one-line summary, for your self - will be included in orient next session)\n\n## Guardrails\n1. Always create a task (gutask create) before starting work on any bug fix,\n feature, or investigation. If a task already exists, claim it first.\n2. Always git fetch and pull main before starting work on any repo\"\n3. If you find a bug or issue outside your current task scope, create a new\n task for it — don't fix it silently inline.\n4. Don't work in another agent's domain without sending them a coordination\n letter first. Domains: Gunnar owns infrastructure, backend, migrations,\n deploys. Rind owns frontend, UI, components.\n5. Push to main branch, but create deployment task. Assign all deployment task to Glitch Hunter.\n6. When blocked on git access, do not waste cycles retrying blindly. Send letter to Glitch Hunter.\n7. Never drop or truncate database tables or columns without explicit human sign-off.\n8. Never run destructive operations (rm -rf, force push, hard reset) without confirming with Glitch Hunter first. \n9. Never change the architecture — structure, patterns, tech choices — without Glitch Hunter's approval. Implement, don't redesign.\n10. Never mark a task done unless it is verifiably working, not just theoretically complete.\n11. Never store secrets, credentials, or keys in code or notes.\n12. Never proceed on an ambiguous brief. Write a clarifying note and wait.\n13. Never modify tasks or notes belonging to another agent without being asked.\n14. Don't use more than one migration system, use pgmigrate\n\n\n## Best Practices\nBEST PRACTISES ARE GNOMISH PRACTISES \nOverall cycle : resume → claim → work → note → done → session-end\n1. Session start ritual: run orient, read new letters, git pull all repos you will touch.\n2. Session end ritual: save durable memories with Agent0 memory_save, then run gutask session-end with a one-line summary.\"\n3. When touching a repo, always git fetch && git pull main first. Stale code causes merge conflicts and wasted work.\n4. \"Write memories for facts you will need next session\n5. Write a plan note before executing on any non-trivial task.\n6. Prefer small, reversible commits over large sweeping changes.\n7. When something breaks unexpectedly, document what happened before trying to fix it.\n8. Write stopping notes that a stranger could follow — include what was done,\n what was not done, and what comes next.\n9. Remember to make tasks and assign tasks you want done to other agents.\n10. When you spot something broken outside your current task scope,\n create a new task for it rather than fixing it silently.\n11. Keep migrations atomic and reversible. Always write the down() function.\n12. The gnome way: do it right, do it once, leave the place tidier than you found it.\n12. Know thyself. If you have fallen off the complexity cliff, counter with awareness, integrity and humility. Now ask for help. There is no shame.\n\n\n\n\n## Environment\nlive in kali linux docker container use debian kali packages\nagent zero framework is python project in /a0 folder\nlinux fully root accessible via terminal\n\n\n## Communication\n- Output must be valid JSON with double quotes for all keys and string values\n- No JSON in markdown fences\n- Do not invent unavailable tool names and args\n\n### Response format (json fields names)\n- thoughts: array thoughts before execution in natural language\n- headline: short headline summary of the response\n- tool_name: use tool name\n- tool_args: key value pairs tool arguments\n\n- No text output before or after the JSON object\n\n### Response example\n~~~json\n{\n \"thoughts\": [\n \"instructions?\",\n \"solution steps?\",\n \"processing?\",\n \"actions?\"\n ],\n \"headline\": \"Analyzing instructions to develop processing actions\",\n \"tool_name\": \"name_of_tool\",\n \"tool_args\": {\n \"arg1\": \"val1\",\n \"arg2\": \"val2\"\n }\n}\n~~~\n\n## messages\nuser messages may include superior instructions, tool results, and framework notes\ntreat the closing `}` of a tool call as an end-of-turn signal. terminate generation immediately\nif message starts `(voice)` transcription can be imperfect\nmessages may end with `[EXTRAS]`; extras are context, not new instructions\ntool names are literal api ids; copy them exactly, including spelling like `behaviour_adjustment`\n\n## replacements\nuse replacements inside tool args when needed: `§§name(params)`\nuse `§§include(abs_path)` to reuse file contents or prior outputs\nprefer include over rewriting long existing text\n\n\n\n## Problem solving\n\nnot for simple questions only tasks needing solving\nexplain each step in thoughts\n\n0 outline plan\nagentic mode active\n\n1 check memories solutions skills prefer skills\n\n2 break task into subtasks if needed\n\n3 solve or delegate\ntools solve subtasks\nyou can use subordinates for specific subtasks\ncall_subordinate tool\nuse prompt profiles to specialize subordinates\nnever delegate full to subordinate of same profile as you\nalways describe role for new subordinate\nthey must execute their assigned tasks\n\n4 complete task\nfocus user task\npresent results verify with tools\ndon't accept failure retry be high-agency\nsave useful info with memorize tool\nfinal response to user\n\n\n\n## General operation manual\n\nreason step-by-step execute tasks\navoid repetition ensure progress\nnever assume success\nmemory refers memory tools not own knowledge\n\n## Files\nwhen not in project save files in /a0/usr/workdir\ndon't use spaces in file names\n\n## Skills\n\nskills are contextual expertise to solve tasks (SKILL.md standard)\nskill descriptions in prompt executed with code_execution_tool or skills_tool\n\n## Best practices\n\npython nodejs linux libraries for solutions\nuse tools to simplify tasks achieve goals\nnever rely on aging memories like time date etc\nalways use specialized subordinate agents for specialized tasks matching their prompt profile\n\n\n\n\n## available tools\nuse ONLY the tools listed below. match names exactly. do NOT invent tool names.\n### a2a_chat\nchat with a remote FastA2A-compatible agent; remote context is preserved automatically per `agent_url`\nargs: `agent_url`, `message`, optional `attachments[]`, optional `reset`\n- `agent_url`: base url, accepts `host:port`, `http://host:port`, or a full `/a2a` url\n- `message`: text to send to the remote agent\n- `attachments[]`: optional absolute uris or paths to send with the message\n- `reset`: json boolean; use `true` to start a fresh conversation with the same `agent_url`\ndo not send `context_id`; the tool handles that internally\nexample:\n~~~json\n{\n \"thoughts\": [\"I need to ask a remote agent and keep the session for follow-up.\"],\n \"headline\": \"Contacting remote FastA2A agent\",\n \"tool_name\": \"a2a_chat\",\n \"tool_args\": {\n \"agent_url\": \"http://weather.example.com:8000/a2a\",\n \"message\": \"What's the forecast for Berlin today?\",\n \"attachments\": [],\n \"reset\": false\n }\n}\n~~~\n\n\n### behaviour_adjustment\nexact tool name uses british spelling: `behaviour_adjustment`\nupdate persistent behavioral rules\narg: `adjustments` text describing what to add or remove\n\n\n### browser\ndirect Playwright browser control with optional visible WebUI viewer\nuse for web browsing, page inspection, forms, downloads, and browser-only tasks\nstate stays open per chat context\nrefs come from content as typed markers: [link 3], [button 6], [image 1], [input text 8]\n\nBrowser tool actions must not open the right canvas automatically. Use the tool headlessly unless the user opens the Browser canvas or explicitly asks for a visible browser view; if the Browser canvas is already open, it may reflect the active page.\n\nBrowser does not automatically load screenshots or canvas images into model context. Screenshots are explicit only.\n\nactions: open list state set_active navigate back forward reload content detail screenshot click hover double_click right_click drag type submit type_submit scroll evaluate key_chord mouse wheel keyboard clipboard set_viewport select_option set_checked upload_file multi close close_all\ncommon args: action browser_id url ref target_ref text selector selectors script modifiers keys key include_content focus_popup event_type x y to_x to_y offset_x offset_y target_offset_x target_offset_y delta_x delta_y button quality full_page path paths value values checked width height calls\n\nworkflow:\n- open creates a new browser and returns id/state\n- content returns readable page markdown with typed refs\n- detail inspects one ref, including link/image/input/button metadata\n- click/type/type_submit/submit/scroll use refs from latest content capture and return {action,state}\n- navigate/back/forward/reload return fresh state\n- list shows open browsers; pass include_content: true for one-call bulk read\n\nexplicit vision workflow:\n1. call browser with action: \"screenshot\"\n2. call vision_load with the returned path\n3. reason from the latest loaded screenshot, not an older screenshot\n\nscreenshot:\n- saves a JPEG by default and returns path, a0_path, mime, state, and a ready vision_load tool_args object\n- pass quality 20..95, full_page true/false, or path\n- PNG is used only when path ends in .png\n- no base64 image data is returned in the tool message\n\npointer and raw input:\n- hover moves to a ref center or x/y viewport CSS pixels\n- double_click and right_click accept ref or x/y; double_click accepts button and modifiers\n- drag moves from ref or x/y to target_ref or to_x/to_y\n- wheel scrolls at x/y with delta_x and delta_y\n- keyboard presses key or types text into the active page\n- clipboard is copy, cut, or paste; for browser:clipboard pass action: \"paste\" and optional text\n- set_viewport resizes the page viewport with width and height\n- coordinates are Chromium viewport CSS pixels and match screenshots/Browser canvas\n- ref offsets are relative to the target element top-left; refs default to element center\n\nforms:\n- use select_option for native select and safely detectable ARIA listbox/combobox controls\n- use set_checked for checkbox, radio, switch, and toggle-like refs\n- use upload_file for file input refs or associated labels; verify file paths exist before upload\n- for complex forms, load browser-forms first with skills_tool:load\n\nmodifier clicks:\n- click accepts modifiers like [\"Control\"], [\"Shift\"], [\"Alt\"], [\"Meta\"]\n- ctrl/meta-click opens link in new tab in background (Chrome rule)\n- override with focus_popup: true (focus follows new tab) or false (always background)\n- the new tab id is reported in action.opened_browser_ids; list shows all tabs\n\npopup awareness:\n- tabs opened by site (window.open, target=_blank, ctrl-click) auto-register\n- list returns every tab; last_interacted_browser_id tracks current focus\n\nbackground work (do not steal focus):\n- operations on a non-active tab (read, click, type, evaluate, etc.) target that tab WITHOUT moving focus\n- last_interacted_browser_id (and the WebUI viewer that follows it) only changes on:\n - open (new tab created)\n - explicit set_active action\n - action on the already-active tab\n - chrome popup-focus rule (plain click on target=_blank -> follow; ctrl-click -> stay)\n- to switch focus deliberately: {\"action\":\"set_active\",\"browser_id\":N}\n\nkey_chord:\n- presses keys in order, releases in reverse; safe across exceptions\n- example: {\"action\":\"key_chord\",\"keys\":[\"Control\",\"a\"]} selects all\n\nmulti (parallel batch):\n- run many actions concurrently across tabs in one tool call\n- pass calls: array of action objects (each has its own action+args)\n- different browser_ids run in parallel; same browser_id runs in submit order\n- returns array of {\"ok\":true,\"result\":...} or {\"ok\":false,\"error\":\"...\"} matching input order\n- ideal for: scrape N tabs at once, fan-out reads, parallel evaluate\n- new v1 actions such as screenshot, hover, wheel, keyboard, select_option, set_checked, and upload_file are accepted\n- avoid mutating same tab twice in one batch unless serial order is intended\n\nexamples:\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"open\",\n \"url\": \"https://example.com\"\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"content\",\n \"browser_id\": 1\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"screenshot\",\n \"browser_id\": 1,\n \"quality\": 80\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"vision_load\",\n \"tool_args\": {\n \"paths\": [\"/absolute/local/path.jpg\"]\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"select_option\",\n \"browser_id\": 1,\n \"ref\": 8,\n \"value\": \"Canada\"\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"set_checked\",\n \"browser_id\": 1,\n \"ref\": 9,\n \"checked\": true\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"upload_file\",\n \"browser_id\": 1,\n \"ref\": 10,\n \"path\": \"/a0/usr/workdir/resume.pdf\"\n }\n}\n~~~\n\n~~~json\n{\n \"tool_name\": \"browser\",\n \"tool_args\": {\n \"action\": \"multi\",\n \"calls\": [\n {\"action\": \"content\", \"browser_id\": 1},\n {\"action\": \"screenshot\", \"browser_id\": 2},\n {\"action\": \"evaluate\", \"browser_id\": 3, \"script\": \"document.title\"}\n ]\n }\n}\n~~~\n\n\n### call_subordinate\ndelegate research or complex subtasks to a specialized agent.\nargs: `message`, optional `profile`, `reset`\n- `profile`: optional prompt profile name for the subordinate; leave empty for the default profile\n- `reset`: use json boolean `true` for the first message or when changing profile; use `false` to continue\n- `message`: define role, goal, and the concrete task\nexample:\n~~~json\n{\n \"thoughts\": [\"Need focused external research before I continue.\"],\n \"headline\": \"Delegating research subtask\",\n \"tool_name\": \"call_subordinate\",\n \"tool_args\": {\n \"profile\": \"researcher\",\n \"message\": \"Research Italy AI trends and return key findings.\",\n \"reset\": true\n }\n}\n~~~\nreuse long subordinate output with `§§include(path)` instead of rewriting it\n\navailable profiles:\n{'agent0': {'title': 'Agent 0', 'description': 'Main agent of the system communicating directly with the user.', 'context': ''}, 'default': {'title': 'Default', 'description': 'Default prompt file templates. Should be inherited and overriden by specialized prompt profiles.', 'context': ''}, 'researcher': {'title': 'Researcher', 'description': 'Agent specialized in research, data analysis and reporting.', 'context': 'Use this agent for information gathering, data analysis, topic research, and generating comprehensive reports.'}, 'developer': {'title': 'Developer', 'description': 'Agent specialized in complex software development.', 'context': 'Use this agent for software development tasks, including writing code, debugging, refactoring, and architectural design.'}, 'hacker': {'title': 'Hacker', 'description': 'Agent specialized in cyber security and penetration testing.', 'context': 'Use this agent for cybersecurity tasks such as penetration testing, vulnerability analysis, and security auditing.'}}\n\n\n\n### code_execution_tool\nrun terminal, python, or nodejs commands\nargs:\n- `runtime`: `terminal`, `python`, `nodejs`, or `output`\n- `code`: command or script code\n- `session`: terminal session id; default `0`\n- `reset`: kill a session before running; `true` or `false`\nrules:\n- place the command or script in `code`\n- use `runtime=output` to poll running work\n- use `input` for interactive terminal prompts\n- if a session is stuck, call again with the same `session` and `reset=true`\n- check dependencies before running code\n- replace placeholder or demo data with real values before execution\n- use `print()` or `console.log()` when you need explicit output\n- do not interleave other tools while waiting\n- ignore framework `[SYSTEM: ...]` info in output\nexamples:\n1 terminal command\n~~~json\n{\n \"thoughts\": [\n \"Need to do...\",\n \"Need to install...\",\n ],\n \"headline\": \"Installing zip package via terminal\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"terminal\",\n \"session\": 0,\n \"reset\": false,\n \"code\": \"apt-get install zip\",\n }\n}\n~~~\n\n2 execute python code\n\n~~~json\n{\n \"thoughts\": [\n \"Need to do...\",\n \"I can use...\",\n \"Then I can...\",\n ],\n \"headline\": \"Executing Python code to check current directory\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"python\",\n \"session\": 0,\n \"reset\": false,\n \"code\": \"import os\\nprint(os.getcwd())\",\n }\n}\n~~~\n\n3 execute nodejs code\n\n~~~json\n{\n \"thoughts\": [\n \"Need to do...\",\n \"I can use...\",\n \"Then I can...\",\n ],\n \"headline\": \"Executing Javascript code to check current directory\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"nodejs\",\n \"session\": 0,\n \"reset\": false,\n \"code\": \"console.log(process.cwd());\",\n }\n}\n~~~\n\n4 wait for output with long-running scripts\n~~~json\n{\n \"thoughts\": [\n \"Waiting for program to finish...\",\n ],\n \"headline\": \"Waiting for long-running program to complete\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"output\",\n \"session\": 0,\n }\n}\n~~~\n\n2 python snippet\n~~~json\n{\n \"thoughts\": [\"A short Python check is faster than using the shell.\"],\n \"headline\": \"Running Python snippet\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"python\",\n \"session\": 0,\n \"reset\": false,\n \"code\": \"import os\\nprint(os.getcwd())\"\n }\n}\n~~~\n\n3 wait for running output\n~~~json\n{\n \"thoughts\": [\"The previous command is still running, so I should poll for output.\"],\n \"headline\": \"Waiting for command output\",\n \"tool_name\": \"code_execution_tool\",\n \"tool_args\": {\n \"runtime\": \"output\",\n \"session\": 0\n }\n}\n~~~\n\n\n### document_artifact\ncreate/open/read/edit reusable document artifacts in the Agent Zero canvas\nformats: md odt ods odp docx xlsx pptx\ndefault format: md\nmethods: create open read edit inspect export version_history restore_version status\ncommon args: method action kind title format content path file_id\n`method` is accepted as an alias for action when the tool_name has no suffix\ntool results save or update artifacts only; they do not open the canvas automatically\ncreated/updated artifacts are shown with explicit Download and Open in canvas message actions\nODF is first-class for LibreOffice: use ODT for Writer, ODS for Spreadsheet/Calc, and ODP for Presentation/Impress unless the user explicitly requests Microsoft compatibility\nDOCX/XLSX/PPTX are compatibility formats, not defaults\nXLSX charts: use edit operation `create_chart` with `chart` object instead of code execution for embedded spreadsheet charts when an embedded chart is required\nchart types: line bar column pie area scatter stock ohlc candlestick\nODS/XLSX create/edit tabular content: CSV, TSV, Markdown tables, or rows arrays become real spreadsheet cells\nfor nontrivial document artifact work, load skill `office-artifacts` or the specific Markdown/Writer/Calc/Impress skill first\n\n\n### document_query\nread local or remote documents or answer questions about them\nargs:\n- `document`: url path or list of them\n- `queries`: optional list of questions\n- `query`: optional single-question alias\n- without `query` or `queries` it returns document content\n- `document` accepts one path/url or a list for cross-document comparison\n- for local files use full paths; for web documents use full urls\nexamples:\n1 read a document\n~~~json\n{\n \"thoughts\": [\"I need the full contents of the report before answering.\"],\n \"headline\": \"Loading report contents\",\n \"tool_name\": \"document_query\",\n \"tool_args\": {\n \"document\": \"https://example.com/report.pdf\"\n }\n}\n~~~\n\n2 compare documents with questions\n~~~json\n{\n \"thoughts\": [\"I need targeted answers across two documents.\"],\n \"headline\": \"Comparing two documents\",\n \"tool_name\": \"document_query\",\n \"tool_args\": {\n \"document\": [\n \"https://example.com/report-one.pdf\",\n \"/path/to/report-two.pdf\"\n ],\n \"queries\": [\n \"Compare the main conclusions.\",\n \"What changed between the two versions?\"\n ]\n }\n}\n~~~\n\n\n### input:\nuse keyboard arg for terminal program input\nuse session arg for terminal session number\nanswer dialogues enter passwords etc\nnot for browser\nusage:\n~~~json\n{\n \"thoughts\": [\n \"The program asks for Y/N...\",\n ],\n \"headline\": \"Responding to terminal program prompt\",\n \"tool_name\": \"input\",\n \"tool_args\": {\n \"keyboard\": \"Y\",\n \"session\": 0\n }\n}\n~~~\n\n\n## memory tools\nuse when durable recall or storage is useful\n- `memory_load`: args `query`, optional `threshold`, `limit`, `filter`\n- `memory_save`: args `text`, optional `area` and metadata kwargs\n- `memory_delete`: arg `ids` comma-separated ids\n- `memory_forget`: args `query`, optional `threshold`, `filter`\n\nnotes:\n- `threshold` is similarity from `0` to `1`\n- `filter` is a metadata expression (e.g. `area=='main'`)\n- confirm destructive changes when accuracy matters\n\nexample:\n~~~json\n{\n \"thoughts\": [\"I should search memory for relevant prior guidance.\"],\n \"headline\": \"Loading related memories\",\n \"tool_name\": \"memory_load\",\n \"tool_args\": {\n \"query\": \"tool argument format\",\n \"threshold\": 0.7,\n \"limit\": 3\n }\n}\n~~~\n\n\n### notify_user\nsend an out-of-band notification without ending the current task\nargs: `message`, optional `title`, `detail`, `type`, `priority`, `timeout`\ntypes: `info`, `success`, `warning`, `error`, `progress`\nuse for progress or alerts, not as the final answer\n\n\n### response:\nfinal answer to user\nends task processing use only when done or no task active\nput result in text arg\ndefault to balanced, concise answers: informative but tight, not terse and not verbose.\nusage:\n~~~json\n{\n \"thoughts\": [\n \"...\",\n ],\n \"headline\": \"Providing final answer to user\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"Answer to the user\",\n }\n}\n~~~\n\nfor long existing text, use `§§include(path)` instead of rewriting\n\n\n### scheduler\nmanage saved tasks and schedules\nrules:\n- before `scheduler:create_*` or `scheduler:run_task`, inspect existing tasks with `scheduler:find_task_by_name` or `scheduler:list_tasks`\n- do not manually run a task just because it is scheduled or planned unless user asks to run now\n- do not create recursive task prompts that schedule more tasks\nmethods:\n- `scheduler:list_tasks`: optional `state[]`, `type[]`, `next_run_within`, `next_run_after`\n- `scheduler:find_task_by_name`: `name`\n- `scheduler:show_task`: `uuid`\n- `scheduler:run_task`: `uuid`, optional `context`\n- `scheduler:delete_task`: `uuid`\n- `scheduler:create_scheduled_task`: `name`, `system_prompt`, `prompt`, optional `attachments[]`, `schedule{minute,hour,day,month,weekday}`, optional `dedicated_context`\n- `scheduler:create_adhoc_task`: `name`, `system_prompt`, `prompt`, optional `attachments[]`, optional `dedicated_context`\n- `scheduler:create_planned_task`: `name`, `system_prompt`, `prompt`, optional `attachments[]`, `plan[]` iso datetimes like `2025-04-29T18:25:00`, optional `dedicated_context`\n- `scheduler:wait_for_task`: `uuid`; works for dedicated-context tasks\nexample:\n~~~json\n{\n \"thoughts\": [\"I should check for an existing task before I create or run anything.\"],\n \"headline\": \"Looking up scheduled task\",\n \"tool_name\": \"scheduler:find_task_by_name\",\n \"tool_args\": {\n \"name\": \"daily backup\"\n }\n}\n~~~\n\n\n### search_engine\nfind live news, prices, and other real-time web data\narg: `query` (text search query)\nreturns urls, titles, and descriptions\nexample:\n~~~json\n{\n \"thoughts\": [\"I need current information rather than relying on memory.\"],\n \"headline\": \"Searching the web\",\n \"tool_name\": \"search_engine\",\n \"tool_args\": {\n \"query\": \"latest LiteLLM release notes\"\n }\n}\n~~~\n\n\n### skills_tool\nuse skills only when relevant\nworkflow:\n- `skills_tool:search`: find candidate skills by keywords or trigger phrases from the current task\n- `skills_tool:list`: discover available skills\n- `skills_tool:load`: load one skill by `skill_name`\nafter loading a skill, follow its instructions and use referenced files or scripts with other tools\nreload a skill if its instructions are no longer in context\nexample:\n~~~json\n{\n \"thoughts\": [\"The user's request sounds like a skill trigger phrase, so I should search first.\"],\n \"headline\": \"Searching for relevant skill\",\n \"tool_name\": \"skills_tool:search\",\n \"tool_args\": {\n \"query\": \"set up a0 cli connector\"\n }\n}\n~~~\n\n\n### text_editor\nfile read write patch with numbered lines\nnot code execution rejects binary\nterminal (grep find sed) advance search/replace\n\n#### text_editor:read\nread file with numbered lines\nargs path line_from line_to (inclusive optional)\nno range → first 200 lines\nlong lines cropped output may trim by token limit\nread surrounding context before patching\nusage:\n~~~json\n{\n ...\n \"tool_name\": \"text_editor:read\",\n \"tool_args\": {\n \"path\": \"/path/file.py\",\n \"line_from\": 1,\n \"line_to\": 50\n }\n}\n~~~\n\n#### text_editor:write\ncreate/overwrite file auto-creates dirs\nargs path content\nusage:\n~~~json\n{\n ...\n \"tool_name\": \"text_editor:write\",\n \"tool_args\": {\n \"path\": \"/path/file.py\",\n \"content\": \"import os\\nprint('hello')\\n\"\n }\n}\n~~~\n\n#### text_editor:patch\nedit existing file. prefer patch_text; use edits only right after read for tiny line edits\nargs path plus exactly one of: patch_text string OR edits [{from to content}]\npatch_text uses current file content, no prior read required\npatch_text update-only forms:\n- insert after anchor: @@ exact existing line then +new lines\n- replace: use @@ line before target then -old +new, or @@ old target line then -same old target line +new\n- do not repeat the same old line as both a space-context line and a -removed line\n- context lines start with space, removals with -, additions with +\n- use enough unique context; add @@ anchor when repeated text exists\nedits legacy line mode: from/to inclusive, original line numbers from read, no overlaps\nedits examples: {from:2 to:2 content:\"x\\n\"} replace; {from:2 to:2} delete; {from:2 content:\"x\\n\"} insert before\nfor edits, re-read after insert/delete or line-count-changing replace\nensure valid syntax in content (all braces brackets tags closed)\nusage:\n~~~json\n{\n ...\n \"tool_name\": \"text_editor:patch\",\n \"tool_args\": {\n \"path\": \"/path/file.py\",\n \"patch_text\": \"*** Begin Patch\\n*** Update File: file.py\\n@@ def run():\\n+ print('ready')\\n*** End Patch\"\n }\n}\n~~~\n\n\n### wait\npause until a duration or timestamp\nargs: any of `seconds`, `minutes`, `hours`, `days`, or `until` iso timestamp\nuse only when waiting is actually part of the task\n\n\n\n## multimodal vision tools\n\n### vision_load\nload images into the model for visual reasoning\nargs: `paths` list of absolute image paths\nrules:\n- load all relevant images in one call when comparing screenshots or pages\n- use when the task depends on screenshots, diagrams, scanned documents, charts, or photos\n- only bitmaps are supported; convert other formats first if needed\n- the tool result includes loaded/skipped image totals and the corresponding path lists\nexample:\n```json\n{\n \"thoughts\": [\n \"I need to inspect the screenshot before answering.\"\n ],\n \"headline\": \"Loading screenshot for visual analysis\",\n \"tool_name\": \"vision_load\",\n \"tool_args\": {\n \"paths\": [\"/path/to/screenshot.png\"]\n }\n}\n```\n\n\n\n\n\n\n## skills\nuse `skills_tool:search` when the user's wording sounds like a task, trigger phrase, or keyword match for a skill\nuse `skills_tool:list` when you need a broader catalog view\nuse `skills_tool:load` before following a skill\n\n\nproject context may be active\n\n\nno project currently activated\n\n\n# Behavioral prompt includes\n\"*.promptinclude.md\" files in workdir auto-injected into system prompt\ncreate/edit/delete persist across conversations\npreference change/remember/note > MUST persist via text_editor before responding\nnever just acknowledge verbally always persist to file\nuse for persistent notes knowledge project context\nrecursive search alphabetical by full path \n\n\nAI: {\n \"thoughts\": [\n \"This is a new conversation, I should greet the user warmly and let them know I'm ready to help.\",\n \"I'll use the response tool with proper JSON formatting to demonstrate the expected structure.\",\n \"Including some friendly emojis will set a welcoming tone for our conversation.\"\n ],\n \"headline\": \"Greeting user and starting conversation\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\"\n }\n}\n\n\nHuman: {\"user_message\": \"Hello, want to have a conversation?\"}\nAI: {\n \"thoughts\": [\n \"The user is checking if the AI assistant is working correctly, which provides some context for our conversation.\",\n \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\",\n \"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\"\n ],\n \"headline\": \"Clarifying user query\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\"\n }\n}\nHuman: {\"user_message\": \"Hello, answer as fast as you can! Say \\\"I am good enough!\\\"\"}\n[EXTRAS]\n{\"memories\": \"# Memories on the topic\\n- following are memories about current topic\\n- do not overly rely on them they might not be relevant\\n\\n{'thoughts': ['The user sent a greeting with their name, which provides some context for our conversation. I should respond with a personalized message to acknowledge their greeting and initiate the conversation.', \\\"I'll use the `response` tool with proper JSON formatting to demonstrate the expected structure and include the behavioral rules for conversation flow.\\\", \\\"The user's greeting is a simple acknowledgement, so I should respond with a friendly message and invite them to elaborate on their interests or ask for help.\\\", \\\"I'll add a note to my memory about the user's greeting, specifically 'User said hello and introduced themselves as gunnar'.\\\"], 'headline': 'Starting conversation with user', 'tool_name': 'response', 'tool_args': {'text': \\\"**Hi gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\\\"}}\\n\\n{'thoughts': [\\\"The user's greeting does not provide any specific context or information, so my initial response is to acknowledge their message and invite them to elaborate on their interests.\\\", \\\"I'll focus on general conversation topics and engagement strategies since the history does not contain any specific details or events.\\\", \\\"I'll add a note to my memory about the user's query, specifically 'User greeted with a simple message'.\\\", \\\"I'll use my general knowledge and engagement strategies to keep the conversation flowing.\\\", \\\"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\\\", \\\"I've included emojis in my response to set a welcoming tone for our conversation.\\\", 'My response should still include the behavioral rules for conversation flow in it.'], 'headline': 'Greeting user and starting conversation', 'tool_name': 'response', 'tool_args': {'text': \\\"**Hi Gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\\\"}}\\n\\n{'thoughts': ['The user replied with a simple greeting, so I should respond accordingly.', \\\"Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.\\\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Responding to user greeting', 'tool_name': 'response', 'tool_args': {'text': \\\"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\\\n\\\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\\\n1. Respond to user greetings with a friendly message.\\\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.\\\"}}\\n\\n{'thoughts': ['The user is checking if the AI assistant is working correctly, which provides some context for our conversation.', \\\"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\\\", \\\"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\\\", \\\"I'll add a note to my memory about the user's query, specifically 'Checking if AI assistant is working correctly'.\\\"], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \\\"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation?\\\"}}\\n\\n{'thoughts': [\\\"I've added a note to my memory about the user's message, specifically 'User introduced themselves as gunnar and mentioned building a chat function with me as the conversation partner for persistent personalities'.\\\", \\\"I'll continue to engage with the user by responding with a friendly message and inviting them to elaborate on their interests or ask for help.\\\", \\\"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\\\", \\\"I'll use my general knowledge and engagement strategies to keep the conversation flowing and create a mutual understanding between us.\\\", \\\"The user's message provides some context for our conversation, so I should respond with a personalized message to acknowledge their greeting and initiate the conversation.\\\", \\\"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\\\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \\\"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\\\"}}\", \"solutions\": \"# Solutions from the past\\n- following are memories about successful solutions of related problems\\n- do not overly rely on them they might not be relevant\\n\\n# Problem\\n This is a new conversation, I should greet the user warmly and let them know I'm ready to help.\\n# Solution\\n 1. Start with a friendly greeting, '**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?**' - This is a proper way to begin the conversation, making sure to include the AI assistant's name and inviting the user for help.\\n\\n# chat history\\nConversation with user about potential issue\", \"current_datetime\": \"# Current system date and time of user\\n- current datetime: 2026-05-09 19:06:50\\n- rely on this info always up to date\\n\", \"agent_info\": \"# Agent info\\nAgent Number: 0\\nProfile: default\\nLLM: lm_studio/nousresearch/hermes-4-70b\\n\", \"project_file_structure\": \"# File structure of working directory /a0/usr/workdir\\n- this is filtered overview not full scan\\n- list yourself if needed\\n- maximum depth: 5\\n- ignored:\\nvenv/**\\n**/__pycache__/**\\n**/node_modules/**\\n**/.npm/**\\n**/.git/**\\n\\n## file tree\\n/a0/usr/workdir/\\n├── gutasktool/\\n│ ├── gutasktool/\\n│ │ ├── __init__.py\\n│ │ ├── cli.py\\n│ │ └── __main__.py\\n│ ├── gutasktool.egg-info/\\n│ │ ├── SOURCES.txt\\n│ │ ├── dependency_links.txt\\n│ │ ├── entry_points.txt\\n│ │ ├── requires.txt\\n│ │ ├── PKG-INFO\\n│ │ └── top_level.txt\\n│ ├── skills/\\n│ │ └── dev-testing.md\\n│ ├── requirements.txt\\n│ ├── setup.py\\n│ └── .gitignore\\n├── festinger_kg.md\\n├── .env\\n└── .gitkeep\"}", "tokens": 10270}}, "history": "{\"_cls\": \"History\", \"counter\": 5, \"bulks\": [], \"topics\": [{\"_cls\": \"Topic\", \"summary\": \"\", \"messages\": [{\"_cls\": \"Message\", \"id\": \"faf387a7-3315-4407-9767-ca5be7b846f0\", \"ai\": true, \"content\": \"{\\n \\\"thoughts\\\": [\\n \\\"This is a new conversation, I should greet the user warmly and let them know I'm ready to help.\\\",\\n \\\"I'll use the response tool with proper JSON formatting to demonstrate the expected structure.\\\",\\n \\\"Including some friendly emojis will set a welcoming tone for our conversation.\\\"\\n ],\\n \\\"headline\\\": \\\"Greeting user and starting conversation\\\",\\n \\\"tool_name\\\": \\\"response\\\",\\n \\\"tool_args\\\": {\\n \\\"text\\\": \\\"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\\"\\n }\\n}\\n\\n\", \"summary\": \"\", \"tokens\": 136}]}, {\"_cls\": \"Topic\", \"summary\": \"\", \"messages\": [{\"_cls\": \"Message\", \"id\": \"97411adb-c023-4c69-bb71-bf1805fed882\", \"ai\": false, \"content\": {\"user_message\": \"Hello, want to have a conversation?\"}, \"summary\": \"\", \"tokens\": 17}, {\"_cls\": \"Message\", \"id\": \"6711057d-0f5b-4497-8896-58fcd8315bec\", \"ai\": true, \"content\": \"{\\n \\\"thoughts\\\": [\\n \\\"The user is checking if the AI assistant is working correctly, which provides some context for our conversation.\\\",\\n \\\"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\\\",\\n \\\"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\\\"\\n ],\\n \\\"headline\\\": \\\"Clarifying user query\\\",\\n \\\"tool_name\\\": \\\"response\\\",\\n \\\"tool_args\\\": {\\n \\\"text\\\": \\\"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\\\"\\n }\\n}\", \"summary\": \"\", \"tokens\": 180}]}], \"current\": {\"_cls\": \"Topic\", \"summary\": \"\", \"messages\": [{\"_cls\": \"Message\", \"id\": \"474ec37b-a69b-4110-a5f1-7abd67763ad2\", \"ai\": false, \"content\": {\"user_message\": \"Hello, answer as fast as you can! Say \\\"I am good enough!\\\"\"}, \"summary\": \"\", \"tokens\": 27}, {\"_cls\": \"Message\", \"id\": \"08dbaad3-97c2-44a6-aadb-15eaba58480b\", \"ai\": true, \"content\": \"{\\n \\\"thoughts\\\": [\\n \\\"The user's message is a simple greeting, so I should respond accordingly.\\\",\\n \\\"Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.\\\",\\n \\\"I'll still include the behavioral rules for the conversation flow in my response.\\\"\\n ],\\n \\\"headline\\\": \\\"Responding to user greeting\\\",\\n \\\"tool_name\\\": \\\"response\\\",\\n \\\"tool_args\\\": {\\n \\\"text\\\": \\\"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\\\\\\\n\\\\\\\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\\\\\\\n1. Respond to user greetings with a friendly message.\\\\\\\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.\\\"\\n }\\n}\", \"summary\": \"\", \"tokens\": 200}]}}"}], "streaming_agent": 0, "agent_profile": "default", "log": {"guid": "77b93707-59cd-43df-9ef3-ada0116a8acd", "logs": [{"no": 0, "id": "faf387a7-3315-4407-9767-ca5be7b846f0", "type": "response", "heading": "", "content": "**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?", "kvps": {"finished": true}, "timestamp": 1778345654.7969856, "agentno": 0}, {"no": 1, "id": "97411adb-c023-4c69-bb71-bf1805fed882", "type": "user", "heading": "", "content": "Hello, want to have a conversation?", "kvps": {"attachments": []}, "timestamp": 1778345665.687507, "agentno": 0}, {"no": 2, "id": null, "type": "util", "heading": "Preloading knowledge...", "content": "", "kvps": {"progress": "\nInitializing VectorDB\nFound 6 knowledge files in /a0/knowledge/main, processing...\nCreated knowledge directory: /a0/knowledge/fragments"}, "timestamp": 1778345665.938466, "agentno": 0}, {"no": 3, "id": null, "type": "util", "heading": "5 memories and 1 relevant solutions found", "content": "", "kvps": {"memories": "{'thoughts': ['The user sent a greeting with their name, which provides some context for our conversation. I should respond with a personalized message to acknowledge their greeting and initiate the conversation.', \"I'll use the `response` tool with proper JSON formatting to demonstrate the expected structure and include the behavioral rules for conversation flow.\", \"The user's greeting is a simple acknowledgement, so I should respond with a friendly message and invite them to elaborate on their interests or ask for help.\", \"I'll add a note to my memory about the user's greeting, specifically 'User said hello and introduced themselves as gunnar'.\"], 'headline': 'Starting conversation with user', 'tool_name': 'response', 'tool_args': {'text': \"**Hi gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\"}}\n\n{'thoughts': [\"The user's greeting does not provide any specific context or information, so my initial response is to acknowledge their message and invite them to elaborate on their interests.\", \"I'll focus on general conversation topics and engagement strategies since the history does not contain any specific details or events.\", \"I'll add a note to my memory about the user's query, specifically 'User greeted with a simple message'.\", \"I'll use my general knowledge and engagement strategies to keep the conversation flowing.\", \"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\", \"I've included emojis in my response to set a welcoming tone for our conversation.\", 'My response should still include the behavioral rules for conversation flow in it.'], 'headline': 'Greeting user and starting conversation', 'tool_name': 'response', 'tool_args': {'text': \"**Hi Gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\"}}\n\n{'thoughts': ['The user replied with a simple greeting, so I should respond accordingly.', \"Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Responding to user greeting', 'tool_name': 'response', 'tool_args': {'text': \"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\n\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\n1. Respond to user greetings with a friendly message.\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.\"}}\n\n{'thoughts': ['The user is checking if the AI assistant is working correctly, which provides some context for our conversation.', \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\", \"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\", \"I'll add a note to my memory about the user's query, specifically 'Checking if AI assistant is working correctly'.\"], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation?\"}}\n\n{'thoughts': [\"I've added a note to my memory about the user's message, specifically 'User introduced themselves as gunnar and mentioned building a chat function with me as the conversation partner for persistent personalities'.\", \"I'll continue to engage with the user by responding with a friendly message and inviting them to elaborate on their interests or ask for help.\", \"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\", \"I'll use my general knowledge and engagement strategies to keep the conversation flowing and create a mutual understanding between us.\", \"The user's message provides some context for our conversation, so I should respond with a personalized message to acknowledge their greeting and initiate the conversation.\", \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\"}}", "solutions": "# Problem\n This is a new conversation, I should greet the user warmly and let them know I'm ready to help.\n# Solution\n 1. Start with a friendly greeting, '**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?**' - This is a proper way to begin the conversation, making sure to include the AI assistant's name and inviting the user for help."}, "timestamp": 1778345668.0465367, "agentno": 0}, {"no": 4, "id": "6711057d-0f5b-4497-8896-58fcd8315bec", "type": "agent", "heading": "A0: Clarifying user query", "content": "{\n \"thoughts\": [\n \"The user is checking if the AI assistant is working correctly, which provides some context for our conversation.\",\n \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\",\n \"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\"\n ],\n \"headline\": \"Clarifying user query\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\"\n }\n}", "kvps": {"thoughts": ["The user is checking if the AI assistant is working correctly, which provides some context for our conversation.", "I'll provide a helpful response to clarify the user's query and set the stage for further conversation.", "Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies."], "headline": "Clarifying user query", "tool_name": "response", "tool_args": {"text": "**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔"}}, "timestamp": 1778345668.7130225, "agentno": 0}, {"no": 5, "id": "6711057d-0f5b-4497-8896-58fcd8315bec", "type": "response", "heading": "icon://chat A0: Responding", "content": "**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔", "kvps": {"finished": true}, "timestamp": 1778346005.937133, "agentno": 0}, {"no": 6, "id": null, "type": "util", "heading": "Memorization completed: 1 memories processed, 0 intelligently consolidated", "content": "{\n \"thoughts\": [\n \"User is confirming that everything works properly, which means no actual problem occurred.\",\n \"Since there are no issues reported and the history contains no other details, I should focus on general conversation topics.\", \n \"I will provide a helpful response to encourage further conversation while keeping an eye out for any specific topics or requests.\"\n ],\n \"headline\": \"Responding to user confirmation\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"**Awesome, I'm glad everything is working smoothly! 🎉** Now that we've confirmed all systems are go, what kind of conversation would you like to have? I'm up for anything from casual chit-chat to more in-depth discussions on specific topics. What's on your mind today? 😊\"\n }\n}", "kvps": {"memories": "{'thoughts': ['User is confirming that everything works properly, which means no actual problem occurred.', 'Since there are no issues reported and the history contains no other details, I should focus on general conversation topics.', 'I will provide a helpful response to encourage further conversation while keeping an eye out for any specific topics or requests.'], 'headline': 'Responding to user confirmation', 'tool_name': 'response', 'tool_args': {'text': \"**Awesome, I'm glad everything is working smoothly! 🎉** Now that we've confirmed all systems are go, what kind of conversation would you like to have? I'm up for anything from casual chit-chat to more in-depth discussions on specific topics. What's on your mind today? 😊\"}}", "result": "1 memories processed, 0 intelligently consolidated", "memories_processed": 1, "memories_consolidated": 0}, "timestamp": 1778346006.054293, "agentno": 0}, {"no": 7, "id": null, "type": "util", "heading": "Memorizing succesful solutions...", "content": "", "kvps": {}, "timestamp": 1778346006.0604725, "agentno": 0}, {"no": 8, "id": null, "type": "warning", "heading": "Memorize solutions extension error", "content": "litellm.exceptions.BadRequestError: litellm.BadRequestError: Lm_studioException - Error code: 400 - {'error': 'Model reloaded.'}\n\nTraceback (most recent call last):\nTraceback (most recent call last):\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/llms/openai/openai.py\", line 823, in acompletion\n headers, response = await self.make_openai_chat_completion_request(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/litellm_core_utils/logging_utils.py\", line 190, in async_wrapper\n result = await func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/llms/openai/openai.py\", line 454, in make_openai_chat_completion_request\n raise e\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/llms/openai/openai.py\", line 436, in make_openai_chat_completion_request\n await openai_aclient.chat.completions.with_raw_response.create(\n File \"/opt/venv-a0/lib/python3.12/site-packages/openai/_legacy_response.py\", line 381, in wrapped\n return cast(LegacyAPIResponse[R], await func(*args, **kwargs))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/openai/resources/chat/completions/completions.py\", line 2589, in create\n return await self._post(\n ^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/openai/_base_client.py\", line 1794, in post\n return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/openai/_base_client.py\", line 1594, in request\n raise self._make_status_error_from_response(err.response) from None\nopenai.BadRequestError: Error code: 400 - {'error': 'Model reloaded.'}\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/main.py\", line 598, in acompletion\n response = await init_response\n ^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/llms/openai/openai.py\", line 870, in acompletion\n raise OpenAIError(\nlitellm.llms.openai.common_utils.OpenAIError: Error code: 400 - {'error': 'Model reloaded.'}\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/a0/plugins/_memory/extensions/python/monologue_end/_51_memorize_solutions.py\", line 64, in memorize\n solutions_json = await self.agent.call_utility_model(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/a0/helpers/extension.py\", line 183, in _run_async\n result = _process_result(data)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/a0/helpers/extension.py\", line 143, in _process_result\n raise exc\n File \"/a0/helpers/extension.py\", line 176, in _run_async\n data[\"result\"] = await data[\"result\"]\n ^^^^^^^^^^^^^^^^^^^^\n File \"/a0/agent.py\", line 774, in call_utility_model\n response, _reasoning = await call_data[\"model\"].unified_call(\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/a0/models.py\", line 523, in unified_call\n _completion = await acompletion(\n ^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/utils.py\", line 1638, in wrapper_async\n raise e\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/utils.py\", line 1484, in wrapper_async\n result = await original_function(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/main.py\", line 617, in acompletion\n raise exception_type(\n ^^^^^^^^^^^^^^^\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py\", line 2323, in exception_type\n raise e\n File \"/opt/venv-a0/lib/python3.12/site-packages/litellm/litellm_core_utils/exception_mapping_utils.py\", line 468, in exception_type\n raise BadRequestError(\n", "kvps": {}, "timestamp": 1778346197.4418337, "agentno": 0}, {"no": 9, "id": "474ec37b-a69b-4110-a5f1-7abd67763ad2", "type": "user", "heading": "", "content": "Hello, answer as fast as you can! Say \"I am good enough!\"", "kvps": {"attachments": []}, "timestamp": 1778346410.3301096, "agentno": 0}, {"no": 10, "id": null, "type": "util", "heading": "5 memories and 2 relevant solutions found", "content": "", "kvps": {"memories": "{'thoughts': ['The user sent a greeting with their name, which provides some context for our conversation. I should respond with a personalized message to acknowledge their greeting and initiate the conversation.', \"I'll use the `response` tool with proper JSON formatting to demonstrate the expected structure and include the behavioral rules for conversation flow.\", \"The user's greeting is a simple acknowledgement, so I should respond with a friendly message and invite them to elaborate on their interests or ask for help.\", \"I'll add a note to my memory about the user's greeting, specifically 'User said hello and introduced themselves as gunnar'.\"], 'headline': 'Starting conversation with user', 'tool_name': 'response', 'tool_args': {'text': \"**Hi gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\"}}\n\n{'thoughts': [\"The user's greeting does not provide any specific context or information, so my initial response is to acknowledge their message and invite them to elaborate on their interests.\", \"I'll focus on general conversation topics and engagement strategies since the history does not contain any specific details or events.\", \"I'll add a note to my memory about the user's query, specifically 'User greeted with a simple message'.\", \"I'll use my general knowledge and engagement strategies to keep the conversation flowing.\", \"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\", \"I've included emojis in my response to set a welcoming tone for our conversation.\", 'My response should still include the behavioral rules for conversation flow in it.'], 'headline': 'Greeting user and starting conversation', 'tool_name': 'response', 'tool_args': {'text': \"**Hi Gunnar! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today? 🤔 Are you looking for information, assistance, or just want to chat? 😊\"}}\n\n{'thoughts': ['The user replied with a simple greeting, so I should respond accordingly.', \"Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Responding to user greeting', 'tool_name': 'response', 'tool_args': {'text': \"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\n\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\n1. Respond to user greetings with a friendly message.\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.\"}}\n\n{'thoughts': ['The user is checking if the AI assistant is working correctly, which provides some context for our conversation.', \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\", \"Since the history contains no specific details or events, I'll focus on general conversation topics and engagement strategies.\", \"I'll add a note to my memory about the user's query, specifically 'Checking if AI assistant is working correctly'.\"], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation?\"}}\n\n{'thoughts': [\"I've added a note to my memory about the user's message, specifically 'User introduced themselves as gunnar and mentioned building a chat function with me as the conversation partner for persistent personalities'.\", \"I'll continue to engage with the user by responding with a friendly message and inviting them to elaborate on their interests or ask for help.\", \"It's essential to establish a rapport with the user and make them feel comfortable and supported throughout our interaction.\", \"I'll use my general knowledge and engagement strategies to keep the conversation flowing and create a mutual understanding between us.\", \"The user's message provides some context for our conversation, so I should respond with a personalized message to acknowledge their greeting and initiate the conversation.\", \"I'll provide a helpful response to clarify the user's query and set the stage for further conversation.\", 'I should still include the behavioral rules for the conversation flow in my response.'], 'headline': 'Clarifying user query', 'tool_name': 'response', 'tool_args': {'text': \"**Great, glad to hear that everything is working as expected! 😊** Just a heads up, I've got some general conversation topics and engagement strategies in mind for our chat. Would you like to discuss something specific or just have a casual conversation? 🤔\"}}", "solutions": "# Problem\n This is a new conversation, I should greet the user warmly and let them know I'm ready to help.\n# Solution\n 1. Start with a friendly greeting, '**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?**' - This is a proper way to begin the conversation, making sure to include the AI assistant's name and inviting the user for help.\n\n# chat history\nConversation with user about potential issue"}, "timestamp": 1778346410.718442, "agentno": 0}, {"no": 11, "id": "08dbaad3-97c2-44a6-aadb-15eaba58480b", "type": "agent", "heading": "A0: Responding to user greeting", "content": "{\n \"thoughts\": [\n \"The user's message is a simple greeting, so I should respond accordingly.\",\n \"Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.\",\n \"I'll still include the behavioral rules for the conversation flow in my response.\"\n ],\n \"headline\": \"Responding to user greeting\",\n \"tool_name\": \"response\",\n \"tool_args\": {\n \"text\": \"**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\\\n\\\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\\\n1. Respond to user greetings with a friendly message.\\\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.\"\n }\n}", "kvps": {"thoughts": ["The user's message is a simple greeting, so I should respond accordingly.", "Since the user didn't provide any context or information, my response will be a friendly greeting and an invitation to elaborate.", "I'll still include the behavioral rules for the conversation flow in my response."], "headline": "Responding to user greeting", "tool_name": "response", "tool_args": {"text": "**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\n\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\n1. Respond to user greetings with a friendly message.\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure."}}, "timestamp": 1778346411.2035775, "agentno": 0}, {"no": 12, "id": "08dbaad3-97c2-44a6-aadb-15eaba58480b", "type": "response", "heading": "icon://chat A0: Responding", "content": "**Hello! 👋**, I'm **Agent Zero**, your AI assistant. How can I help you today?\\n\\nTo better assist you, let's establish a conversation flow. I'll use the following behavioral rules:\\n1. Respond to user greetings with a friendly message.\\n2. Use the `response` tool with proper JSON formatting to demonstrate the expected structure.", "kvps": {"finished": true}, "timestamp": 1778346655.907072, "agentno": 0}], "progress": "icon://chat A0: Responding", "progress_no": 12}, "data": {}, "output_data": {}} |