Netmind

Netmind AI Build AI Faster, Smarter, and More Affordably Train, Fine-tune, Run Inference, and Scale with our Global GPU Network—Your all-in-one AI Engine.

This example goes over how to use LangChain to interact with Netmind AI models.

# Querying chat models with Netmind AI
from langchain_netmind import ChatNetmind, NetmindEmbeddings

# choose from our 50+ models here: https://www.netmind.ai/
chat = ChatNetmind(
    # netmind_api_key="YOUR_API_KEY",
    model="meta-llama/Llama-3.3-70B-Instruct",
)

# stream the response back from the model
for m in chat.stream("Who are you?"):
    print(m.content, end="", flush=True)

# if you don't want to do streaming, you can use the invoke method
# chat.invoke("Who are you?")


embeddings = NetmindEmbeddings(
    # netmind_api_key="YOUR_API_KEY",
    model="nvidia/NV-Embed-v2",
)
single_vector = embeddings.embed_query("I love programming.")
print(str(single_vector)[:100])