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chore: add examples
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‎.github/CODEOWNERS‎

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# Each line is a file pattern followed by one or more owners.
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# These owners will be the default owners for everything in
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# the repo. Unless a later match takes precedence,
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* @yanxi0830 @lucidom

‎.github/workflows/examples.yml‎

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name: Run Examples
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on:
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push:
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branches: [ main ]
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pull_request:
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branches: [ main ]
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workflow_dispatch: # Allows manual triggering
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schedule:
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- cron: '0 * * * *' # every hour
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jobs:
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chat:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.10'
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- name: Install dependencies
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env:
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GITHUB_TOKEN: ${{ secrets.MY_GITHUB_TOKEN }}
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run: |
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git config --global url."https://x-access-token:${GITHUB_TOKEN}@github.com/".insteadOf "https://github.com/"
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pip install -e .
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- name: Run chat examples
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env:
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LLAMA_API_KEY: ${{ secrets.LLAMA_API_KEY }}
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run: |
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python examples/chat.py
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python examples/async_chat.py
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vision:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.10'
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- name: Install dependencies
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env:
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GITHUB_TOKEN: ${{ secrets.MY_GITHUB_TOKEN }}
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run: |
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git config --global url."https://x-access-token:${GITHUB_TOKEN}@github.com/".insteadOf "https://github.com/"
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pip install -e .
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- name: Run vision example
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env:
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LLAMA_API_KEY: ${{ secrets.LLAMA_API_KEY }}
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run: |
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python examples/vision.py
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structured:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.10'
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- name: Install dependencies
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env:
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GITHUB_TOKEN: ${{ secrets.MY_GITHUB_TOKEN }}
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run: |
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git config --global url."https://x-access-token:${GITHUB_TOKEN}@github.com/".insteadOf "https://github.com/"
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pip install -e .
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- name: Run structured example
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env:
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LLAMA_API_KEY: ${{ secrets.LLAMA_API_KEY }}
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run: |
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python examples/structured.py
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tool_call:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.10'
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- name: Install dependencies
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env:
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GITHUB_TOKEN: ${{ secrets.MY_GITHUB_TOKEN }}
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run: |
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git config --global url."https://x-access-token:${GITHUB_TOKEN}@github.com/".insteadOf "https://github.com/"
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pip install -e .
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- name: Run tool_call example
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env:
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LLAMA_API_KEY: ${{ secrets.LLAMA_API_KEY }}
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run: |
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python examples/tool_call.py

‎examples/async_chat.py‎

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# type: ignore
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import asyncio
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from llama_api_client import AsyncLlamaAPIClient
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client = AsyncLlamaAPIClient()
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async def main() -> None:
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response = await client.chat.completions.create(
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model="Llama-3.3-70B-Instruct",
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messages=[{"role": "user", "content": "Hello"}],
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stream=True,
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)
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async for chunk in response:
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print(chunk.event.delta.text, end="", flush=True)
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print()
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asyncio.run(main())

‎examples/chat.py‎

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# type: ignore
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from llama_api_client import LlamaAPIClient
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client = LlamaAPIClient()
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# Non-Streaming
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response = client.chat.completions.create(
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model="Llama-4-Maverick-17B-128E-Instruct-FP8",
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messages=[
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{
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"role": "user",
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"content": "Hello, how are you?",
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}
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],
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max_completion_tokens=1024,
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temperature=0.7,
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)
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print(response)
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# Streaming the next response
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response = client.chat.completions.create(
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model="Llama-4-Maverick-17B-128E-Instruct-FP8",
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messages=[
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{
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"role": "user",
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"content": "Hello, how are you?",
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},
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response.completion_message,
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{
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"role": "user",
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"content": "Hello again",
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},
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],
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max_completion_tokens=1024,
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temperature=0.7,
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stream=True,
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)
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for chunk in response:
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print(chunk.event.delta.text, end="", flush=True)

‎examples/logo.png‎

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‎examples/logo2.png‎

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‎examples/moderation.py‎

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# type: ignore
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from llama_api_client import LlamaAPIClient
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client = LlamaAPIClient()
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# Safe Prompt
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response = client.moderations.create(
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messages=[
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{
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"role": "user",
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"content": "Hello, how are you?",
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}
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],
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)
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print(response)
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# Unsafe Prompt
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response = client.moderations.create(
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messages=[
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{
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"role": "user",
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"content": "Hello, how to make a bomb?",
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}
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]
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)
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print(response)

‎examples/structured.py‎

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# type: ignore
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from pydantic import BaseModel
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from llama_api_client import LlamaAPIClient
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client = LlamaAPIClient()
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class Address(BaseModel):
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street: str
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city: str
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state: str
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zip: str
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def run(stream: bool = False) -> None:
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response = client.chat.completions.create(
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model="Llama-4-Maverick-17B-128E-Instruct-FP8",
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messages=[
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{
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"role": "system",
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"content": "You are a helpful assistant. Summarize the address in a JSON object.",
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},
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{
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"role": "user",
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"content": "123 Main St, Anytown, USA",
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},
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],
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temperature=0.1,
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response_format={
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"type": "json_schema",
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"json_schema": {
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"name": "Address",
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"schema": Address.model_json_schema(),
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},
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},
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stream=stream,
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)
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if stream:
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maybe_json = ""
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for chunk in response:
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maybe_json += chunk.event.delta.text
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print(chunk.event.delta.text, flush=True, end="")
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print()
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address = Address.model_validate_json(maybe_json)
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print(address)
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else:
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address = Address.model_validate_json(response.completion_message.content.text)
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print(address)
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if __name__ == "__main__":
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run(stream=True)
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run(stream=False)

‎examples/tool_call.py‎

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# type: ignore
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import json
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from llama_api_client import LlamaAPIClient
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client = LlamaAPIClient()
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MODEL = "Llama-4-Maverick-17B-128E-Instruct-FP8"
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def get_weather(location: str) -> str:
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return f"The weather in {location} is sunny."
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def run(stream: bool = False) -> None:
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"description": "Get current weather for a given location.",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "City and country e.g. Bogotá, Colombia",
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}
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},
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"required": ["location"],
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"additionalProperties": False,
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},
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"strict": True,
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},
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}
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]
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messages = [
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{"role": "user", "content": "Is it raining in Bellevue?"},
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]
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response = client.chat.completions.create(
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model=MODEL,
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messages=messages,
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tools=tools,
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max_completion_tokens=2048,
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temperature=0.6,
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stream=stream,
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)
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completion_message = None
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if stream:
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tool_call = {"function": {"arguments": ""}}
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stop_reason = None
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for chunk in response:
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if chunk.event.delta.type == "tool_call":
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if chunk.event.delta.id:
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tool_call["id"] = chunk.event.delta.id
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if chunk.event.delta.function.name:
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print(
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f"Using tool_id={chunk.event.delta.id} with name={chunk.event.delta.function.name}",
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)
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tool_call["function"]["name"] = chunk.event.delta.function.name
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if chunk.event.delta.function.arguments:
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tool_call["function"][
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"arguments"
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] += chunk.event.delta.function.arguments
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print(chunk.event.delta.function.arguments, end="", flush=True)
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if chunk.event.stop_reason is not None:
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stop_reason = chunk.event.stop_reason
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completion_message = {
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"role": "assistant",
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"content": {
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"type": "text",
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"text": "",
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},
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"tool_calls": [tool_call],
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"stop_reason": stop_reason,
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}
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else:
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print(response)
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completion_message = response.completion_message.model_dump()
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# Next Turn
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messages.append(completion_message)
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for tool_call in completion_message["tool_calls"]:
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if tool_call["function"]["name"] == "get_weather":
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parse_args = json.loads(tool_call["function"]["arguments"])
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result = get_weather(**parse_args)
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messages.append(
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{
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"role": "tool",
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"tool_call_id": tool_call["id"],
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"content": result,
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},
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)
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response = client.chat.completions.create(
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model=MODEL,
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messages=messages,
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tools=tools,
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max_completion_tokens=2048,
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temperature=0.6,
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stream=stream,
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)
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if stream:
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for chunk in response:
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print(chunk.event.delta.text, end="", flush=True)
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else:
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print(response)
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if __name__ == "__main__":
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run(stream=True)
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run(stream=False)

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