Cerebras

import os
import weave
from cerebras.cloud.sdk import Cerebras

# Initialiser le projet weave
weave.init("cerebras_speedster")

# Utiliser le SDK Cerebras normalement
api_key = os.environ["CEREBRAS_API_KEY"]
model = "llama3.1-8b"  # Modèle Cerebras

client = Cerebras(api_key=api_key)

response = client.chat.completions.create(
    model=model,
    messages=[{"role": "user", "content": "What's the fastest land animal?"}],
)

print(response.choices[0].message.content)

import os
import weave
from cerebras.cloud.sdk import Cerebras

# Initialiser le projet Weave
weave.init("cerebras_speedster")

client = Cerebras(api_key=os.environ["CEREBRAS_API_KEY"])

# Weave suivra les entrées, les sorties et le code de cette fonction
@weave.op
def animal_speedster(animal: str, model: str) -> str:
    "Find out how fast an animal can run"
    
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": f"How fast can a {animal} run?"}],
    )
    return response.choices[0].message.content

animal_speedster("cheetah", "llama3.1-8b")
animal_speedster("ostrich", "llama3.1-8b")
animal_speedster("human", "llama3.1-8b")

import os
import weave
from cerebras.cloud.sdk import Cerebras

# Initialiser le projet Weave
weave.init("cerebras_speedster")

client = Cerebras(api_key=os.environ["CEREBRAS_API_KEY"])

class AnimalSpeedModel(weave.Model):
    model: str
    temperature: float

    @weave.op
    def predict(self, animal: str) -> str:
        "Predict the top speed of an animal"        

        response = client.chat.completions.create(
            model=self.model,
            messages=[{"role": "user", "content": f"What's the top speed of a {animal}?"}],
            temperature=self.temperature
        )
        return response.choices[0].message.content

speed_model = AnimalSpeedModel(
    model="llama3.1-8b",
    temperature=0.7
)
result = speed_model.predict(animal="cheetah")
print(result)