63 lines
1.9 KiB
Markdown
63 lines
1.9 KiB
Markdown
# iSphere AI Bridge Design
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## Objective
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Make iSphere messages usable by AI digital employees without rebuilding the full communication platform.
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## First POC
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The first POC reads recent messages, converts them into a normalized JSON model, generates draft replies, and records evidence. Send/file capabilities are part of the staged MCP tool roadmap.
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## Architecture
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```text
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iSphere / MockCloud / existing bridge
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-> source connector
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-> message adapter
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-> AI draft worker
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-> human review
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-> evidence log
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```
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## Source Connectors
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1. Local data connector: reads local databases, logs, or caches in read-only mode.
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2. Existing bridge connector: talks to `OpenClawBridge` or `XmppBridgeService` when available.
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3. UI/RPA connector: wraps the desktop client with limited actions.
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4. Network connector: wraps discovered HTTP/SOAP/XMPP/WebSocket APIs when validated.
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## Normalized Message Model
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```json
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{
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"message_id": "string",
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"conversation_id": "string",
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"conversation_name": "string",
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"conversation_type": "direct|group|system",
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"sender_id": "string",
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"sender_name": "string",
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"content_type": "text|image|file|rich|notify",
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"content_text": "string",
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"attachments": [],
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"created_at": "ISO-8601 or Unix ms",
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"received_at": "ISO-8601 or Unix ms",
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"source": "local-db|log|plugin|xmpp|http|rpa|mock",
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"raw_ref": "path/table/packet/window reference"
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}
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```
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## Write Execution Model
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- Read access and draft generation can be automated in test scope.
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- Send/file tools are staged after source discovery and connector selection.
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- Every write action records target, content or file hash, timestamp, operator, and connector.
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## Verification
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The project is successful when it can:
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1. Find at least one stable authorized message source.
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2. Extract recent messages into normalized JSON.
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3. Generate a reply draft.
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4. Produce an evidence report with exact paths, commands, and limits.
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