forked from phoenix-oss/llama-stack-mirror
314ee09ae3
llama-models should have extremely minimal cruft. Its sole purpose should be didactic -- show the simplest implementation of the llama models and document the prompt formats, etc. This PR is the complement to https://github.com/meta-llama/llama-models/pull/279 ## Test Plan Ensure all `llama` CLI `model` sub-commands work: ```bash llama model list llama model download --model-id ... llama model prompt-format -m ... ``` Ran tests: ```bash cd tests/client-sdk LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/ LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/ LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/ ``` Create a fresh venv `uv venv && source .venv/bin/activate` and run `llama stack build --template fireworks --image-type venv` followed by `llama stack run together --image-type venv` <-- the server runs Also checked that the OpenAPI generator can run and there is no change in the generated files as a result. ```bash cd docs/openapi_generator sh run_openapi_generator.sh ```
120 lines
2.9 KiB
Python
120 lines
2.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# top-level folder for each specific model found within the models/ directory at
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# the top-level of this source tree.
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from llama_models.datatypes import (
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BuiltinTool,
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StopReason,
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ToolCall,
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)
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from .prompt_templates import (
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BuiltinToolGenerator,
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JsonCustomToolGenerator,
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ToolResponseGenerator,
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)
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INSTRUCTION = "You are a helpful assistant."
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def system_message_builtin_tools_only():
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return {
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"builtin_tools": BuiltinToolGenerator().data_examples()[0],
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"custom_tools": [],
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"instruction": INSTRUCTION,
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}
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def system_message_builtin_code_only():
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return {
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"builtin_tools": BuiltinToolGenerator().data_examples()[1],
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"custom_tools": [],
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"instruction": "",
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}
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def system_message_custom_tools_only():
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return {
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"builtin_tools": [],
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"custom_tools": JsonCustomToolGenerator().data_examples()[0],
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"instruction": INSTRUCTION,
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}
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def system_message_builtin_and_custom_tools():
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return {
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"builtin_tools": BuiltinToolGenerator().data_examples()[0],
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"custom_tools": JsonCustomToolGenerator().data_examples()[0],
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"instruction": INSTRUCTION,
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}
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def system_default():
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return {
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"builtin_tools": [],
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"custom_tools": [],
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"instruction": INSTRUCTION,
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}
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def tool_success():
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return ToolResponseGenerator().data_examples()[0]
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def tool_failure():
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return ToolResponseGenerator().data_examples()[1]
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def assistant_builtin_tool_call():
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return {
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"content": "",
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"tool_call": ToolCall(
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call_id="uuid",
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tool_name=BuiltinTool.brave_search,
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arguments={
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"query": "Who won NBA in 2024?",
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},
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),
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"stop_reason": StopReason.end_of_message,
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}
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def assistant_custom_tool_call():
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return {
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"content": "",
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"tool_call": ToolCall(
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call_id="uuid",
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tool_name="trending_songs",
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arguments={"country": "US", "n": 10},
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),
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"stop_reason": StopReason.end_of_turn,
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}
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def assistant_default():
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return {
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"content": "Hi, I am a helpful assistant. What can I help you with today?",
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"tool_call": None,
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"stop_reason": StopReason.end_of_turn,
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}
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def user_default():
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return {"content": "Please tell me how to plan a trip to New York"}
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def user_images():
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return {"content": "<|image|><|image|>What do these images depict?"}
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def user_interleaved_images():
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return {"content": "<|image|>Describe the image in one sentence.<|image|>Write a haiku about these images"}
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