wehub-resource-sync
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
from mlflow.deployments import get_deploy_client
|
|
|
|
|
|
def main():
|
|
client = get_deploy_client("http://localhost:7000")
|
|
|
|
print(f"PaLM endpoints: {client.list_endpoints()}\n")
|
|
print(f"PaLM completions endpoint info: {client.get_endpoint(endpoint='completions')}\n")
|
|
|
|
# Completions request
|
|
response_completions = client.predict(
|
|
endpoint="completions",
|
|
inputs={
|
|
"prompt": "What is the world record for flapjack consumption in a single sitting?",
|
|
"temperature": 0.1,
|
|
},
|
|
)
|
|
print(f"PaLM response for completions: {response_completions}")
|
|
|
|
# Embeddings request
|
|
response_embeddings = client.predict(
|
|
endpoint="embeddings",
|
|
inputs={"input": ["Do you carry the Storm Trooper costume in size 2T?"]},
|
|
)
|
|
print(f"PaLM response for embeddings: {response_embeddings}")
|
|
|
|
# Chat example
|
|
response_chat = client.predict(
|
|
endpoint="chat",
|
|
inputs={
|
|
"messages": [
|
|
{
|
|
"role": "system",
|
|
"content": "You are a talented European rapper with a background in US history",
|
|
},
|
|
{
|
|
"role": "user",
|
|
"content": "Please recite the preamble to the US Constitution as if it were "
|
|
"written today by a rapper from Reykjavík",
|
|
},
|
|
]
|
|
},
|
|
)
|
|
print(f"PaLM response for chat: {response_chat}")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|