Python SDK for the Mixgarden API
Project description
Mixgarden Python SDK
pip install mixgarden
- Use
get_models()to get a list of available models and providers. - Use
get_plugins()to get a list of available plugins. - Use
get_conversations()to get a list of available conversations. - Use
get_conversation(id)to get a specific conversation. - Use
chat(model, messages)when you’re building a conversational UI, or want the platform to maintain context for you. - Use
get_mg_completion(model, content)when you need a one-off, stateless generation enhanced by Mixgarden plugins. - Use
get_completion(model, messages)when you need a one-off, stateless generation directly from LLM (Raw LLM Output).
import os
from mixgarden import MixgardenSDK
sdk = MixgardenSDK(api_key=os.getenv("MIXGARDEN_API_KEY"))
# List available models
models = sdk.get_models()
# Stateful chat (conversation is stored server-side)
chat = sdk.chat(
model="openai/gpt-4o-mini",
# Optionally add conversationId to add to an existing conversation
# conversationId: "your-convo-id",
content="Hello mixgarden!",
pluginId="tone-pro",
pluginSettings={
"emotion-type": "neutral",
"emotion-intensity": 6,
"personality-type": "friendly",
},
)
# Other helper calls
plugins = sdk.get_plugins()
conversations = sdk.get_conversations()
conversation = sdk.get_conversation(conversations[0]["id"])
# One-shot completion (Mixgarden Enhanced)
completion = sdk.get_mg_completion(
model="openai/gpt-4o-mini",
content="hello mixgarden!",
maxTokens=100,
temperature=0.7,
pluginId="tone-pro",
pluginSettings={
"emotion-type": "neutral",
"emotion-intensity": 6,
"personality-type": "friendly"
}
)
# One-shot completion (Raw LLM Output)
completion = sdk.get_completion(
model= "openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hi there!"}],
maxTokens=100,
temperature=0.7,
)
print(chat)
print(completion)
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