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docs: update prompt_format.md for llama4 (#2035)
torchrun --nproc_per_node=8 scripts/generate_prompt_format.py meta-llama/Llama-4-Scout-17B-16E-Instruct ~/local/checkpoints/<path>/ llama_stack.models.llama.llama4.prompts llama_stack/models/llama/llama4/prompt_format.md Co-authored-by: Eric Huang <erichuang@fb.com>
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2 changed files with 54 additions and 48 deletions
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@ -9,6 +9,10 @@ from io import BytesIO
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from pathlib import Path
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from typing import List
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from llama_stack.models.llama.llama4.prompt_templates.system_prompts import (
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PythonListCustomToolGenerator,
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)
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from ..datatypes import RawMediaItem, RawMessage, RawTextItem
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from ..prompt_format import (
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Llama4UseCase,
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@ -177,39 +181,9 @@ def usecases(base_model: bool = False) -> List[UseCase | str]:
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[
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RawMessage(
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role="system",
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content="""You are an expert in composing functions. You are given a question and a set of possible functions.
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Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
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If none of the function can be used, point it out. If the given question lacks the parameters required by the function,
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also point it out. You should only return the function call in tools call sections.
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If you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]
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You SHOULD NOT include any other text in the response.
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Here is a list of functions in JSON format that you can invoke.
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[
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{
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"name": "get_weather",
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"description": "Get weather info for places",
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"parameters": {
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"type": "dict",
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"required": [
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"city"
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],
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"properties": {
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"city": {
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"type": "string",
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"description": "The name of the city to get the weather for"
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},
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"metric": {
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"type": "string",
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"description": "The metric for weather. Options are: celsius, fahrenheit",
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"default": "celsius"
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}
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}
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}
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}
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""",
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content=PythonListCustomToolGenerator()
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.gen(PythonListCustomToolGenerator().data_examples()[0])
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.render(),
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),
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RawMessage(
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role="user",
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