ExtraltodeusandClaude Opus 4.8
4bc7c8005e
- scripts/jwash_mcp.py: MCP server (FastMCP/stdio), an HTTP client of the running J-Wash server so an external LLM can drive an already-loaded model. Tools: generate, find_token, list_layers, scale_token/replace_token (pure-weights, layers required), set_intensity, list_edits/reset_edits. - api/app.py + ui: /api/generate now records the last exchange (surfaced in /api/status) and broadcasts on /ws when done; the UI shows a "generated via API/MCP" panel at the top of the chat and an Options "API monitor" toggle that swaps the 2s status poll for an event-driven refresh. - sampling: repetition penalty (default 1.0, applied in model_manager._sample), exposed as a "rep" field in the chat controls; intentionally not exposed through the MCP. - ui: remove the redundant "md" chat toggle (already available in Options). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
import os
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent
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HOST = "127.0.0.1"
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PORT = 8381
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# HF cache root. Default: the shared Hugging Face cache (a pre-set HF_HOME, else
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# the standard ~/.cache/huggingface — the same one other HF tools use). Pass
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# `run.py --hf-cache PATH` (e.g. ./hf_cache) for an isolated, project-local cache;
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# run.py sets HF_HOME from that argument before this module is imported.
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_DEFAULT_HF_HOME = Path(os.environ.get("XDG_CACHE_HOME") or (Path.home() / ".cache")) / "huggingface"
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HF_CACHE = Path(os.environ.get("HF_HOME") or _DEFAULT_HF_HOME)
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# Runtime data root (SQLite history, frames, presets, edits, masks). Overridable
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# so several instances can run side by side; run.py sets it from --data-dir.
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DATA_DIR = Path(os.environ.get("JWASH_DATA_DIR") or (ROOT / "data"))
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LENSES_DIR = ROOT / "lenses"
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UI_DIST = ROOT / "ui" / "dist"
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LOCAL_MODELS_ROOT = ROOT
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DTYPES = ("bf16", "fp16")
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QUANTS = ("int8", "nf4")
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DEFAULT_DTYPE = "bf16"
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DEFAULT_DEVICE = "cuda:0"
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DEFAULT_SAMPLING = {
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"temperature": 0.7,
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"top_p": 0.95,
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"top_k": 40,
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"max_tokens": 512,
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"seed": -1, # -1 = random
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"repetition_penalty": 1.0, # 1.0 = off
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}
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def setup_env():
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os.environ.setdefault("CUDA_DEVICE_ORDER", "PCI_BUS_ID")
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os.environ.setdefault("HF_HOME", str(HF_CACHE))
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os.environ.setdefault("PYTORCH_CUDA_ALLOC_CONF", "expandable_segments:True")
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_tolerant_subprocess_text()
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def _tolerant_subprocess_text():
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"""Windows: libraries (quantization backends, driver probes) spawn tools
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whose console output is localized (cp850/cp1252). Under ``-X utf8`` the
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stdlib decodes their pipes as STRICT UTF-8, and the reader thread dies
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with a noisy — though harmless — UnicodeDecodeError. Default text-mode
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pipes to ``errors="replace"`` when the caller didn't choose otherwise."""
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if os.name != "nt":
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return
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import subprocess
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if getattr(subprocess.Popen.__init__, "_jwash_tolerant", False):
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return
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orig = subprocess.Popen.__init__
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def patched(self, *args, **kwargs):
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wants_text = (
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kwargs.get("text")
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or kwargs.get("universal_newlines")
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or kwargs.get("encoding")
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)
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if wants_text and not kwargs.get("errors"):
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kwargs["errors"] = "replace"
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orig(self, *args, **kwargs)
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patched._jwash_tolerant = True
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subprocess.Popen.__init__ = patched
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