Implementation Plan: Gradio Agent Chat (LangGraph)

Branch: 033-gradio-agent-chat | Date: 2026-06-08 | Updated: 2026-06-30 | Spec: spec.md

Summary

Gradio agent backend + Svelte frontend via @gradio/client submit(). LangGraph create_react_agent() + static interrupt_before + PostgresSaver. Hybrid keyword+embedding tool router (keyword primary <1ms, embedding fallback 5-20ms). Negation guard for fast-track HITL. Smart dashboard prefetch trigger. Structured JSON metadata streaming. No REST confirmations, no custom WebSocket, no deprecated assistant tool registry for agent runtime.

Current Implementation Snapshot (2026-06-30)

/agent works through SvelteKit AgentChat.svelte and AgentChatModel.svelte.ts, connecting with @gradio/client to ${window.location.origin}/api/agent/gradio.
DEV_MODE=true ./run.sh wires BACKEND_URL, GRADIO_URL, and GRADIO_SERVER_PORT; backend/src/agent/run.py allows port fallback only with GRADIO_ALLOW_PORT_FALLBACK=true.
backend/src/agent/tools.py contains 24 native LangChain @tool functions and get_tools_for_query() for hybrid intent-based subset selection.
backend/src/agent/_embedding_router.py provides embedding-based tool similarity fallback (cosine similarity via paraphrase-multilingual-MiniLM-L12-v2).
fast_confirmation_tool() includes negation guard (\bне\b, \bno\b) to bypass fast-track for negated requests.
Dashboard prefetch uses intent-aware trigger (excludes creation/diagnostic patterns).
run_llm_validation uses /api/validation-tasks; Git, maintenance, migration, backup, and documentation tools call their existing FastAPI REST endpoints with dual identity headers.
HITL resume path recreates the agent with interrupt_before=[], preventing repeated guardrail cards after confirm.
/agent exposes debug info: conv_id, pending thread_id, connection/streaming state, env/user, message count, last message id, active tool calls, and error.
Verified: backend agent tests 375 passed; frontend AgentChatModel.test.ts 73 passed; frontend build passed.

Technical Context

Language: Python 3.9+/TypeScript Svelte 5 runes Key Dependencies: gradio>=5.0, langgraph>=0.2, langchain-core>=0.3, langchain-openai>=0.3, langgraph-checkpoint-postgres, pdfplumber, openpyxl (back); @gradio/client (front) Storage: PostgreSQL 16 (persistence + checkpoints via langgraph-checkpoint-postgres) Testing: pytest (back), vitest L1 model + L2 UX (front) Frontend: SvelteKit SPA, model-first (AgentChatModel.svelte.ts C4), runes-only Performance: First token <1.5s, streaming 60fps, file upload ≤10MB

Constitution Check — Passed

All 8 principles satisfied: semantic contracts, decision memory, external orchestrator, module discipline, RBAC, Svelte 5 runes, test-driven C3+, attention-optimized.

Project Structure

New/Changed Files

backend/src/agent/         — app.py, langgraph_setup.py, tools.py, _embedding_router.py, middleware.py, document_parser.py
backend/src/api/routes/    — agent_conversations.py, auth.py
backend/src/models/        — agent.py
backend/src/schemas/       — agent.py
frontend/src/lib/models/   — AgentChatModel.svelte.ts (rewritten)
frontend/src/lib/components/agent/ — AgentChat.svelte
frontend/src/lib/components/assistant/ — ConversationList, ToolCallCard, ConfirmationCard, ConnectionIndicator
frontend/src/routes/agent/ — +page.svelte
frontend/src/types/        — agent.ts
docker/                    — Dockerfile.agent, docker-compose.yml updated, nginx.conf updated

Deprecated

backend/src/api/routes/assistant/_tool_registry.py → @DEPRECATED Tombstone (FR-022).

Runtime Context-Budget Rule

The runtime MUST use the hybrid router: keyword primary + embedding fallback. Tool subset is 5-10 tools (50-75% token reduction vs full 24-tool catalog). Embedding model (paraphrase-multilingual-MiniLM-L12-v2) lazy-loaded on first fallback call; graceful degradation to keyword-only if sentence-transformers unavailable. Dashboard-prefetched requests MUST avoid adding search_dashboards to the tool schema (prefetch data already in context). #endregion (plan summary)

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