0c8d407793* Rename cli/ to unsloth_cli/ to fix namespace collision with stringzilla stringzilla installs a namespace package at cli/ (cli/split.py, cli/wc.py) in site-packages without an __init__.py. When unsloth is installed as an editable package (pip install -e .), the entry point script does `from cli import app` which finds stringzilla's namespace cli/ first and fails with `ImportError: cannot import name 'app' from 'cli'`. Non-editable installs happened to work because unsloth's cli/__init__.py overwrites the namespace directory, but this is fragile and breaks if stringzilla is installed after unsloth. Renaming to unsloth_cli/ avoids the collision entirely and fixes both editable and non-editable install paths. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update stale cli/ references in comments and license files --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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import sys
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from typing import Optional
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import typer
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def inference(
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model: str = typer.Argument(..., help = "HF model id or local path."),
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prompt: str = typer.Argument(..., help = "Prompt to send to the model."),
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hf_token: Optional[str] = typer.Option(
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None, "--hf-token", envvar = "HF_TOKEN", help = "Hugging Face token if needed."
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),
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temperature: float = typer.Option(0.7, "--temperature"),
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top_p: float = typer.Option(0.9, "--top-p"),
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top_k: int = typer.Option(40, "--top-k"),
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max_new_tokens: int = typer.Option(256, "--max-new-tokens"),
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repetition_penalty: float = typer.Option(1.1, "--repetition-penalty"),
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system_prompt: str = typer.Option(
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"",
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"--system-prompt",
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help = "Optional system prompt to prepend.",
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),
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max_seq_length: int = typer.Option(2048, "--max-seq-length"),
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load_in_4bit: bool = typer.Option(True, "--load-in-4bit/--no-load-in-4bit"),
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):
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"""Run a single inference using the specified model."""
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from studio.backend.core import ModelConfig, get_inference_backend
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inference_backend = get_inference_backend()
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model_config = ModelConfig.from_ui_selection(
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dropdown_value = model, search_value = None, hf_token = hf_token, is_lora = False
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)
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if not model_config:
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typer.echo("Could not resolve model config", err = True)
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raise typer.Exit(code = 1)
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if not inference_backend.load_model(
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config = model_config,
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max_seq_length = max_seq_length,
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load_in_4bit = load_in_4bit,
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hf_token = hf_token,
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):
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typer.echo("Model load failed", err = True)
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raise typer.Exit(code = 1)
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messages = [{"role": "user", "content": prompt}]
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stream = inference_backend.generate_chat_response(
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messages = messages,
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system_prompt = system_prompt,
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temperature = temperature,
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top_p = top_p,
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top_k = top_k,
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max_new_tokens = max_new_tokens,
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repetition_penalty = repetition_penalty,
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)
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typer.echo("Assistant:", nl = True)
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previous = ""
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for chunk in stream:
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delta = chunk[len(previous) :]
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if delta:
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sys.stdout.write(delta)
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sys.stdout.flush()
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previous = chunk
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sys.stdout.write("\n")
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sys.stdout.flush()
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