userType: external

gitBranch: claude/zealous-liskov

slug: jaunty-zooming-globe

type: user

role: user

content:
Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions.
This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing development work without losing context.

Before providing your final summary, wrap your analysis in <analysis> tags to organize your thoughts and ensure you've covered all necessary points. In your analysis process:

1. Chronologically analyze each message and section of the conversation. For each section thoroughly identify:
   - The user's explicit requests and intents
   - Your approach to addressing the user's requests
   - Key decisions, technical concepts and code patterns
   - Specific details like:
     - file names
     - full code snippets
     - function signatures
     - file edits
  - Errors that you ran into and how you fixed them
  - Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
2. Double-check for technical accuracy and completeness, addressing each required element thoroughly.

Your summary should include the following sections:

1. Primary Request and Intent: Capture all of the user's explicit requests and intents in detail
2. Key Technical Concepts: List all important technical concepts, technologies, and frameworks discussed.
3. Files and Code Sections: Enumerate specific files and code sections examined, modified, or created. Pay special attention to the most recent messages and include full code snippets where applicable and include a summary of why this file read or edit is important.
4. Errors and fixes: List all errors that you ran into, and how you fixed them. Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
5. Problem Solving: Document problems solved and any ongoing troubleshooting efforts.
6. All user messages: List ALL user messages that are not tool results. These are critical for understanding the users' feedback and changing intent.
6. Pending Tasks: Outline any pending tasks that you have explicitly been asked to work on.
7. Current Work: Describe in detail precisely what was being worked on immediately before this summary request, paying special attention to the most recent messages from both user and assistant. Include file names and code snippets where applicable.
8. Optional Next Step: List the next step that you will take that is related to the most recent work you were doing. IMPORTANT: ensure that this step is DIRECTLY in line with the user's most recent explicit requests, and the task you were working on immediately before this summary request. If your last task was concluded, then only list next steps if they are explicitly in line with the users request. Do not start on tangential requests or really old requests that were already completed without confirming with the user first.
                       If there is a next step, include direct quotes from the most recent conversation showing exactly what task you were working on and where you left off. This should be verbatim to ensure there's no drift in task interpretation.

Here's an example of how your output should be structured:

<example>
<analysis>
[Your thought process, ensuring all points are covered thoroughly and accurately]
</analysis>

<summary>
1. Primary Request and Intent:
   [Detailed description]

2. Key Technical Concepts:
   - [Concept 1]
   - [Concept 2]
   - [...]

3. Files and Code Sections:
   - [File Name 1]
      - [Summary of why this file is important]
      - [Summary of the changes made to this file, if any]
      - [Important Code Snippet]
   - [File Name 2]
      - [Important Code Snippet]
   - [...]

4. Errors and fixes:
    - [Detailed description of error 1]:
      - [How you fixed the error]
      - [User feedback on the error if any]
    - [...]

5. Problem Solving:
   [Description of solved problems and ongoing troubleshooting]

6. All user messages:
    - [Detailed non tool use user message]
    - [...]

7. Pending Tasks:
   - [Task 1]
   - [Task 2]
   - [...]

8. Current Work:
   [Precise description of current work]

9. Optional Next Step:
   [Optional Next step to take]

</summary>
</example>

Please provide your summary based on the conversation so far, following this structure and ensuring precision and thoroughness in your response.

There may be additional summarization instructions provided in the included context. If so, remember to follow these instructions when creating the above summary. Examples of instructions include:
<example>
## Compact Instructions
When summarizing the conversation focus on typescript code changes and also remember the mistakes you made and how you fixed them.
</example>

<example>
# Summary instructions
When you are using compact - please focus on test output and code changes. Include file reads verbatim.
</example>

IMPORTANT: Do NOT use any tools. You MUST respond with ONLY the <summary>...</summary> block as your text output.


type: message

role: assistant

type: text

text:
<analysis>
Let me chronologically analyze the entire conversation, which is a continuation of a previous session that ran out of context.

**Previous Session Context (from summary):**
- Built Sunaiva AI Memory product - sovereign memory-as-a-service
- Created landing page, docker-compose stack, pipeline API
- Key decisions: $47/$97/$197 pricing, FalkorDB + Graphiti MCP on Elestio, stealth approach, Claude format first
- Deployed to Elestio VPS at 152.53.201.221
- MCP endpoint verified at http://152.53.201.221:8001/mcp (Graphiti Agent Memory v1.21.0)
- FalkorDB Browser at https://sunaiva-memory-u50607.vm.elestio.app
- Created Gemini CLI Upgrade Spec
- Audited Genesis Powerhouse CLI, fixed AIVA violations
- Antigravity IDE rejected by user in favor of Gemini CLI with Turbo Mode

**This Session's Work:**

1. **First action**: Created todo list, continued from previous session context. Started verifying CLI main.py for remaining AIVA references.

2. **Read handoff_tools.py**: Found AIVA imports but they use lazy loading with try/except - gracefully degrade, safe as-is.

3. **Fixed CLI main.py**:
   - Changed status table from "AIVA (Local)" → "Sovereign Memory" with LIVE status
   - Replaced the `sync` command from AIVA REST calls to sovereign MCP endpoint health check using urllib

4. **Updated powerhouse_profile.sh**: Changed `alias aiva` to `alias logs`, updated command help text

5. **Updated tui.py**: Changed agent panel from "Antigravity/Claude Code/AIVA" to "Gemini CLI/Claude Code/Sovereign Memory"

6. **Tested MCP endpoint**: Confirmed Graphiti Agent Memory v1.21.0 still operational

7. **Saved first memories to sovereign MCP**:
   - Discovered correct field names: `name` + `episode_body` (NOT `content`)
   - Discovered `group_ids` is an array (NOT `group_id` string)
   - Discovered tool name is `search_memory_facts` (NOT `search_facts`)
   - Successfully saved 3 episodes to `genesis-kinan` group
   - Episodes are processed asynchronously by OpenAI for graph extraction

8. **Built memory_bridge.py**: Reusable Python MCP client for both Claude Code and Gemini CLI

9. **Updated pipeline main.py**: Fixed `store_memory_via_graphiti` to use correct MCP field names and session-based protocol

10. **Updated local decision log**: Added infrastructure details, MCP API reference, Gemini CLI decision, updated next steps

11. **User said "lets not even use their api just stick to mcp"**: Dropped Supermemory API entirely. MCP only going forward.

12. **Before that, saved 5 documents to Supermemory** using new `/v3/documents` endpoint (API changed from `/v3/memories` with 308 redirect). But user then said to drop Supermemory.

13. **Added sovereign-memory MCP to Claude Code settings**: Added `"sovereign-memory": {"type": "url", "url": "http://152.53.201.221:8001/mcp"}` to `.claude/settings.json`

14. **Created .gemini/settings.json**: Same MCP endpoint for Gemini CLI

15. **Wrote Gemini CLI handoff prompt**: `GEMINI_HANDOFF_PROMPT.md` with exact instructions for Gemini to build its own execution engine

16. **User Zero Test**:
    - Created `test_user_zero.py` script
    - Parsed current session's .jsonl (4.2MB, 849 messages, 107 chunks)
    - Successfully saved 5/5 test episodes to sovereign memory
    - Pipeline confirmed working

17. **User pivoted to George's demo**: "lets pause that and get Georges website and chatbot demo going as he is coming here soon"

18. **Researched George Bunker / Bunker FNQ**:
    - George Bunker, Bunker FNQ, underground bunker builder in Cairns/FNQ
    - Website: bunkerfnq.com.au (blocked automated requests)
    - GHL Location: Tradie Chatbots, ID: SWdaQpAVAtRigYcMfder
    - API Token: pit-a15ad83c-841a-4b04-a9f8-fc365a31d407
    - Webchat workflow B-008-WF-1.1 in DRAFT status

19. **User's final detailed request**: "when he comes ideally I will show him the powerpoint and audit-html file, then show him the locally hosted website with chat widget. he would like the chatbot to collect job details, ask the customer to send a site photo if possible, job request description and he will call back by end of the day, sometimes early evening at the latest and get back to them personally."

20. **Built bunker-fnq-demo-site.html**: Full demo site with custom intake chatbot that:
    - Collects: Name, Phone, Job Type (options), Description, Site Photo (or skip), Address/Suburb
    - Promises George calls back by end of day / early evening
    - Submits lead to GHL as contact with tags and notes
    - Matches Bunker FNQ branding (navy/red/green from audit HTML)

Key files in BUNKER FINAL folder:
- `bunker-fnq-audit.html` - existing audit report
- `Bunker_FNQ_Digital_Audit.pptx` - existing PowerPoint
- `bunker-fnq-demo-site.html` - NEW demo site with chatbot (just created)
</analysis>

<summary>
1. Primary Request and Intent:

   This session continues from a massive previous session focused on building the **Sunaiva AI Memory** product (sovereign memory-as-a-service) and the **Genesis CLI infrastructure**. The session had multiple phases:

   **Phase 1 — CLI Security & Memory Integration**: Verify and fix remaining AIVA references in the Genesis CLI, replace AIVA sync with sovereign MCP sync, update TUI/profiles.

   **Phase 2 — Sovereign Memory Activation**: Save first real memories to the deployed Graphiti MCP endpoint, discover correct API field names, build a reusable Python MCP client (`memory_bridge.py`), and configure both Claude Code and Gemini CLI to use the sovereign MCP endpoint.

   **Phase 3 — User Zero Test**: Test the conversation digestion pipeline by feeding Kinan's actual Claude conversation data (4.2MB, 849 messages) into the sovereign memory endpoint.

   **Phase 4 — George's Demo (URGENT, MOST RECENT)**: User pivoted urgently to prepare a demo for George Bunker (Bunker FNQ, underground bunker builder in Cairns). User wants to show George: (1) a PowerPoint audit, (2) the audit HTML, and (3) a locally hosted demo website with a custom intake chatbot. The chatbot must collect job details, ask for site photos, get job description, and promise George will call back by end of day / early evening at latest.

   **Key user directive**: "lets not even use their api just stick to mcp" — Supermemory API dropped entirely, sovereign MCP only.

2. Key Technical Concepts:
   - **MCP Streamable HTTP Transport**: Requires `Accept: application/json, text/event-stream` header, session-based (initialize first, use `Mcp-Session-Id` header for subsequent calls)
   - **Graphiti Agent Memory v1.21.0**: Tools use `name` + `episode_body` (NOT `content`), `group_ids` (array, NOT singular), `search_memory_facts` (NOT `search_facts`)
   - **Sovereign Memory Stack**: FalkorDB + Graphiti MCP on Elestio Docker VPS (152.53.201.221)
   - **MCP Memory Bridge Pattern**: Python client that handles session init, tool calls, SSE parsing
   - **GHL (GoHighLevel) API**: Contact creation, tags, notes via REST API with Bearer token auth
   - **Custom Intake Chatbot**: Step-based conversation flow with options, photo upload, and GHL submission
   - **Async Episode Processing**: Graphiti queues episodes for background OpenAI-powered entity/relationship extraction
   - **Supermemory API Change**: `/v3/memories` now 308 redirects to `/v3/documents` (discovered but then user said to drop Supermemory entirely)

3. Files and Code Sections:

   - **`E:/genesis-system/genesis_v2/cli/main.py`**
     - Updated status table: `"AIVA (Local)"` → `"Sovereign Memory"` with LIVE status pointing to `152.53.201.221:8001/mcp`
     - Replaced entire `sync()` command from AIVA REST client to sovereign MCP health check using `urllib.request` with proper MCP initialize handshake

   - **`E:/genesis-system/genesis_v2/core/powerhouse_profile.sh`**
     - Changed `alias aiva="tail -f $GENESIS_ROOT/genesis_v2.log"` to `alias logs="tail -f ..."`
     - Updated help text from `aiva` to `logs`

   - **`E:/genesis-system/genesis_v2/core/tui.py`**
     - Changed agent panel from `{"Antigravity", "Claude Code", "AIVA"}` to `{"Gemini CLI", "Claude Code", "Sovereign Memory"}`
     - Sovereign Memory shows hardcoded `"● LIVE"` status

   - **`E:/genesis-system/genesis_v2/core/memory_bridge.py`** (NEW)
     - Complete MCP client class `MemoryBridge` with methods: `save()`, `search()`, `search_facts()`, `get_episodes()`, `health()`
     - Handles session initialization, SSE response parsing, structured content extraction
     - Global convenience instance: `memory = MemoryBridge()`
     - Key pattern: Each `_call_tool()` gets a fresh session since sessions expire after tool calls

   - **`E:/genesis-system/sunaiva/ai-memory/deploy/pipeline/main.py`**
     - Rewrote `store_memory_via_graphiti()` to use MCP session-based protocol
     - Step 1: Initialize session (get `mcp-session-id` header)
     - Step 2: Call `add_memory` with `name` + `episode_body` (NOT `content`)
     - Added SSE response parsing for `event: message\ndata: {...}` format
     - Updated `process_upload()` to pass `name=f"Conversation-{i+1}-of-{len(all_memories)}"` to memory function

   - **`E:/genesis-system/.claude/settings.json`**
     - Added sovereign-memory MCP server: `"sovereign-memory": {"type": "url", "url": "http://152.53.201.221:8001/mcp"}`

   - **`E:/genesis-system/.gemini/settings.json`** (NEW)
     - Same MCP endpoint config for Gemini CLI integration

   - **`E:/genesis-system/genesis_v2/GEMINI_HANDOFF_PROMPT.md`** (NEW)
     - Paste-ready prompt for Gemini CLI to build its own execution engine
     - Covers: Feature 1 (real tmux), Feature 2 (memory bridge integration), Feature 3 (track-based spawning)
     - Includes MCP API quick reference, verification commands, critical rules

   - **`E:/genesis-system/.claude/agent-memory/sunaiva-decisions-2026-02-13.md`**
     - Updated with: full infrastructure details, MCP API reference table (all 9 tools with correct field names), Gemini CLI architecture decision, updated next steps with completion checkmarks

   - **`E:/genesis-system/sunaiva/ai-memory/test_user_zero.py`** (NEW)
     - User Zero test script that reads Claude .jsonl conversation files
     - Parses messages, chunks into groups of 8, saves to MCP with fresh session per episode
     - Successfully tested: 849 messages → 107 chunks → 5/5 episodes saved

   - **`E:/genesis-system/TRADIES/BUNKER FINAL/bunker-fnq-demo-site.html`** (NEW, MOST RECENT)
     - Full demo website for Bunker FNQ with custom intake chatbot
     - Branding matches audit HTML: navy `#1a1a2e`, accent red `#e94560`, green `#27ae60`, Inter font
     - Sections: Nav, Hero, Trust Bar, Services (3 cards), CTA, Footer
     - Custom chatbot widget with step-based conversation flow:
       - Steps: greeting → name → phone → job_type (with button options: Underground Bunker, Concrete Slab/Foundation, Storage/Wine Cellar, Other) → description → photo (with skip option) → address → confirm
       - Typing indicators, fade-in animations, option buttons
       - Final confirmation shows collected data summary
       - Promise: "George will review this and give you a call back by end of today. If it's late in the arvo, early evening at the latest."
       - `submitToGHL()` function creates contact via GHL API with tags `['b-008. webchat: first entry', 'bunker-fnq-demo']` and adds a note with full job details
       - GHL API: Token `pit-a15ad83c-841a-4b04-a9f8-fc365a31d407`, Location `SWdaQpAVAtRigYcMfder`

   - **`E:/genesis-system/TRADIES/george_chatbot_embed.html`** (NEW)
     - GHL native chat widget embed code (alternative to custom chatbot)

   - **Existing demo assets for George**:
     - `E:/genesis-system/TRADIES/BUNKER FINAL/bunker-fnq-audit.html` — Digital audit report
     - `E:/genesis-system/TRADIES/BUNKER FINAL/Bunker_FNQ_Digital_Audit.pptx` — PowerPoint
     - `E:/genesis-system/TRADIES/BUNKER FNQ/Updated_Bunker_FNQ_Audit.pptx` — Updated audit
     - `E:/genesis-system/TRADIES/george_bunker_fnq_setup.py` — GHL contact setup script

4. Errors and Fixes:

   - **MCP `add_memory` wrong field names**: Used `content` field → got pydantic validation error requiring `name` and `episode_body`. Fixed by using correct field names.

   - **MCP session expiry**: After saving first memory, next call returned "Missing session ID". Fixed by getting a fresh session for each tool call (pattern built into `memory_bridge.py`).

   - **MCP `search_facts` wrong tool name**: Called `search_facts` → got "Unknown tool". Correct name is `search_memory_facts`. Discovered via `tools/list` call.

   - **MCP `group_id` vs `group_ids`**: `search_nodes` uses `group_ids` (array) not `group_id` (string). Fixed in all search calls.

   - **Supermemory API 308 redirect**: `/v3/memories` endpoint now 308 redirects to `/v3/documents`. Discovered and fixed, but then user said to drop Supermemory entirely: "lets not even use their api just stick to mcp"

   - **Episodes not appearing in search**: After saving, `get_episodes` and `search_nodes` returned empty results. This is expected — Graphiti processes episodes asynchronously via OpenAI for entity/relationship extraction. Processing can take 30-120 seconds per episode.

   - **bunkerfnq.com.au 403**: Website blocks automated requests. Worked around by using search results and existing research in TRADIES folder.

5. Problem Solving:

   **Solved — CLI AIVA Cleanup**: Replaced all AIVA references in CLI with sovereign MCP. `sync` command now does MCP health check. TUI shows "Gemini CLI" and "Sovereign Memory" instead of "Antigravity" and "AIVA".

   **Solved — MCP API Discovery**: Through trial and error, discovered the exact Graphiti v1.21.0 API: correct field names (`name`/`episode_body`), correct tool names (`search_memory_facts`), correct parameter types (`group_ids` as array), and session management pattern.

   **Solved — Memory Bridge**: Built `memory_bridge.py` as reusable Python client that both Claude Code and Gemini CLI can use. Handles all MCP complexity (session init, SSE parsing, error handling).

   **Solved — User Zero Test**: Successfully parsed 4.2MB Claude conversation (849 messages, 107 chunks), saved 5/5 test episodes to sovereign memory.

   **Solved — George's Demo Site**: Built complete demo website with custom intake chatbot matching Bunker FNQ branding and collecting the exact information George requested.

   **Ongoing — Episode Graph Extraction**: Episodes saved but nodes/facts not yet appearing in search. Async OpenAI processing may need more time or may have issues with the OpenAI API key/rate limits on the server.

6. All User Messages:
   - "keep going here until we hit our limits. lets keep going now."
   - "can you update supermemory again"
   - "lets not even use their api just stick to mcp"
   - "lets pause that and get Georges website and chatbot demo going as he is coming here soon. lovable cloned his site, so can we set up a chatbot on his site draft site demo clone site now? he already has ghl sub-sccount. here is the lovable clone with edit access https://lovable.dev/projects/18e1072d-13f6-4019-ada9-2847d1994a52?magic_link=mc_172856b1-693c-487b-8735-566703ff0555"
   - "when he comes ideally I will show him the powerpoint and audit-html file, then show him the locally hosted website with chat widget. he would like the chatbot to collect job details, ask the customer to send a site photo if possible, job request description and he will call back by end of the day, sometimes early evening at the latest and get back to them personally."

7. Pending Tasks:
   - **Test the demo site chatbot end-to-end** — Open `bunker-fnq-demo-site.html` locally, walk through the full chat flow, verify GHL contact creation works
   - **Activate GHL webchat workflow B-008-WF-1.1** — Currently in DRAFT, needs to be published/active for the webchat tag trigger to fire
   - **Add chatbot to Lovable clone** — User provided Lovable project link with edit access; Chrome extension wasn't connected so couldn't access directly
   - **Run full 107-chunk ingestion** for user zero (only 5/5 tested so far)
   - **Deploy pipeline container to Elestio** (SSH required)
   - **Build Gemini CLI upgrade** (6 features from spec, hand to Gemini)

8. Current Work:

   Was building **George Bunker's demo site with custom intake chatbot**. Just completed writing `E:/genesis-system/TRADIES/BUNKER FINAL/bunker-fnq-demo-site.html` — a full locally-hostable demo website with:
   - Bunker FNQ branding (navy/red theme matching audit)
   - Hero section, services, trust bar, CTA
   - Custom chatbot widget (bottom-right bubble) with step-based intake flow
   - Collects: name, phone, job type (4 options), description, site photo (or skip), suburb/area
   - Promises George calls back by end of day / early evening
   - Submits to GHL API as contact with tags and notes containing full job details

   The demo assets George will see:
   1. `BUNKER FINAL/Bunker_FNQ_Digital_Audit.pptx` — PowerPoint audit
   2. `BUNKER FINAL/bunker-fnq-audit.html` — HTML audit report
   3. `BUNKER FINAL/bunker-fnq-demo-site.html` — Demo website with chatbot (just built)

9. Optional Next Step:

   **Test the chatbot end-to-end** and potentially activate the GHL webchat workflow. The user's most recent message was: "when he comes ideally I will show him the powerpoint and audit-html file, then show him the locally hosted website with chat widget. he would like the chatbot to collect job details, ask the customer to send a site photo if possible, job request description and he will call back by end of the day, sometimes early evening at the latest and get back to them personally."

   The demo site HTML file is written but hasn't been tested in a browser yet. Next steps:
   1. Verify the chatbot flow works by opening it locally
   2. Potentially activate the GHL webchat workflow (B-008-WF-1.1, currently DRAFT)
   3. Optionally integrate with the Lovable clone if Chrome extension becomes available

   **Live Infrastructure Reference:**
   - Sovereign Memory MCP: `http://152.53.201.221:8001/mcp` (Graphiti Agent Memory v1.21.0)
   - FalkorDB Browser: `https://sunaiva-memory-u50607.vm.elestio.app` (auth: admin/Sn4iv@Adm1n!2026)
   - GHL Location: `SWdaQpAVAtRigYcMfder`, Token: `pit-a15ad83c-841a-4b04-a9f8-fc365a31d407`
   - George: Bunker FNQ, phone +61424459772, email bunker.fnq@mailbox.org
</summary>

service_tier: standard

type: assistant


type: progress

hookEvent: SubagentStop

hookName: SubagentStop

command: python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event subagent_stop