grabowski
1a1b62d475
Deploy web Studio / deploy (push) Successful in 3m3s
✦ Agent in the Studio's top bar opens a floating chat window. The model (any OpenAI-compatible endpoint with tool calling; default B4L's inference server, https://inference.p0.contact/v1) gets the 15 MCP tools plus two page tools (select_object, set_view) and the Studio's state (selection, level, rotation) in its system prompt. Answers and reasoning stream in; tool calls show as rows with arguments and results; object ids link to the object; Stop ends a turn; Undo takes the agent's edits back. The window moves by its title bar and resizes at its top-left corner. - studio/agent.js: shared by both front ends (waits for studio.js's isokit:studio event); MCP over /mcp or isokit.mcp in the web Studio - isokit studio: /api/agent/{config,models,chat} relay the calls on their own threads (ureq, chunked and flushed per read), so the key stays on the machine and the endpoint needs no CORS; settings from ISOKIT_LLM_URL / _KEY / _MODEL or agent.json in the user's config folder - web Studio: calls the endpoint from the page with a key kept in the browser; build_web.py --agent-url names a same-site relay as default; the deploy builds with /llm/v1, which deploy/Caddyfile forwards to the inference server (its nginx refuses the CORS preflight) - tools/mock_llm.py + tools/agent_checks.py: the agent window checks in both check_studio.py and check_web.py
19 lines
448 B
TOML
19 lines
448 B
TOML
[package]
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name = "isokit-cli"
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description = "isokit: isometric scene engine - Studio GUI, MCP server, build and export"
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version.workspace = true
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edition.workspace = true
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license.workspace = true
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[[bin]]
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name = "isokit"
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path = "src/main.rs"
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[dependencies]
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isokit-project = { workspace = true }
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serde_json = { workspace = true }
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tiny_http = { workspace = true }
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ureq = { workspace = true }
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clap = { workspace = true }
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anyhow = { workspace = true }
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