Groq

export GROQ_API_KEY="gsk_..."
export GROQ_BASE_URL="https://api.groq.com"  # Optional

from upsonic import infer_model

model = infer_model("groq/llama-3.3-70b-versatile")

from upsonic.models.groq import GroqModel, GroqModelSettings

settings = GroqModelSettings(
    max_tokens=2048,
    temperature=0.7
)

model = GroqModel(
    model_name="llama-3.3-70b-versatile",
    settings=settings
)

from upsonic import Agent, Task, infer_model

model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(model=model)

task = Task("Explain quantum computing")
result = agent.do(task)

from upsonic import Agent, Task, infer_model

# Groq is exceptionally fast at streaming
model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(model=model)

task = Task("Write a story about space exploration")

# Notice the speed!
async for chunk in agent.do_stream(task):
    print(chunk, end="", flush=True)

from upsonic import Agent, Task, infer_model
from upsonic.tools.builtin_tools import WebSearchTool

# Built-in web search for all models
model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(
    model=model,
    builtin_tools=[WebSearchTool()]
)

task = Task("What are the latest AI news today?")
result = agent.do(task)

from upsonic.models.groq import GroqModel, GroqModelSettings

# Control reasoning output format
settings = GroqModelSettings(
    max_tokens=4096,
    temperature=0.3,
    groq_reasoning_format="parsed"  # 'hidden', 'raw', or 'parsed'
)

model = GroqModel(
    model_name="qwen-qwq-32b",  # Reasoning model
    settings=settings
)

agent = Agent(model=model)
task = Task("Solve this complex problem: ...")
result = agent.do(task)

from upsonic import Agent, Task, infer_model

def calculate(expression: str) -> float:
    """Evaluate a mathematical expression."""
    return eval(expression)

model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(model=model, tools=[calculate])

task = Task("What is 456 * 789?")
result = agent.do(task)

from upsonic import Agent, Task, infer_model
from upsonic.messages import ImageUrl

model = infer_model("groq/llama-3.2-90b-vision-preview")
agent = Agent(model=model)

task = Task(
    description="Describe this image",
    attachments=[
        ImageUrl(url="https://example.com/image.jpg")
    ]
)

result = agent.do(task)

from upsonic import Agent, Task, infer_model
from upsonic.storage.memory import Memory
from upsonic.storage.providers.in_memory import InMemoryStorage

storage = InMemoryStorage()
memory = Memory(storage=storage, session_id="session-123")

model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(model=model, memory=memory)

from upsonic.models.groq import GroqModel, GroqModelSettings

settings = GroqModelSettings(
    max_tokens=4096,
    temperature=0.7,
    top_p=0.9,
    seed=42,
    presence_penalty=0.1,
    frequency_penalty=0.1,
    parallel_tool_calls=True,
    groq_reasoning_format="parsed"
)

model = GroqModel(
    model_name="llama-3.3-70b-versatile",
    settings=settings
)

import time
from upsonic import Agent, Task, infer_model

model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(model=model)

task = Task("Write a detailed explanation of neural networks")

start = time.time()
result = agent.do(task)
elapsed = time.time() - start

print(f"Generated in {elapsed:.2f}s")
# Typically 1-3 seconds for long responses!

from upsonic import Agent, Task, infer_model
from upsonic.tools.builtin_tools import WebSearchTool

model = infer_model("groq/llama-3.3-70b-versatile")
agent = Agent(
    model=model,
    builtin_tools=[WebSearchTool()]
)

# Automatically searches the web
task = Task("What's happening in the tech world today?")
result = agent.do(task)