Honcho Python SDK
The official Python library for the Honcho conversational memory platform. Honcho provides tools for managing peers, sessions, and conversation context across multi-party interactions, enabling advanced conversational AI applications with persistent memory and theory-of-mind capabilities.
Installation
pip install honcho-ai
Quick Start
from honcho import Honcho
# Initialize client
client = Honcho(api_key="your-api-key")
# Create peers (participants in conversations)
alice = client.peer("alice")
bob = client.peer("bob")
# Create a session for group conversations
session = client.session("conversation-1")
# Add messages to the session
session.add_messages([
alice.message("Hello, Bob!"),
bob.message("Hi Alice, how are you?")
])
# Query conversation context
response = alice.chat("What did Bob say to the user?")
print(response)
Core Concepts
Peers
Peers represent participants in conversations.
# Create peers
assistant = client.peer("assistant")
user = client.peer("user-123")
# Chat with global context
response = user.chat("What did I talk about yesterday?")
# Chat with perspective of another peer
response = user.chat("Does the assistant know my preferences?", target=assistant)
Sessions
Sessions group related conversations and messages:
# Create a session
session = client.session("project-discussion")
# Add peers to session
session.add_peers([alice, bob])
# Add messages
session.add_messages([
alice.message("Let's discuss the project timeline"),
bob.message("I think we need two more weeks")
])
# Get conversation context
context = session.context()
Messages and Context
Retrieve and use conversation history:
# Get messages from a session
messages = session.messages()
# Convert to OpenAI format for further prompting
openai_messages = context.to_openai(assistant="assistant")
# Convert to Anthropic format for further prompting
anthropic_messages = context.to_anthropic(assistant="assistant")
Async Support
The SDK provides async access via the .aio accessor on any instance:
from honcho import Honcho
async def main():
client = Honcho(api_key="your-api-key")
# Async peer and session creation
peer = await client.aio.peer("user-123")
session = await client.aio.session("conversation-1")
# Async chat
response = await peer.aio.chat("What does this user prefer?")
# Async iteration
async for p in client.aio.peers():
print(p.id)
Metadata Management
# Set peer metadata
user.set_metadata({"location": "San Francisco", "preferences": {"theme": "dark"}})
# Session metadata
session.set_metadata({"topic": "project-planning", "priority": "high"})
Multi-Perspective Queries
# Alice's view of what Bob knows
response = alice.chat("Does Bob remember our discussion about the budget?", target=bob)
# Session-specific perspective
response = alice.chat("What does Bob think about this project?",
target=bob,
session=session)
Configuration
Environment Variables
export HONCHO_API_KEY="your-api-key"
export HONCHO_BASE_URL="https://api.honcho.dev" # Optional
export HONCHO_WORKSPACE_ID="your-workspace" # Optional
Client Options
client = Honcho(
api_key="your-api-key",
environment="production", # or "local"
workspace_id="custom-workspace",
base_url="https://api.honcho.dev"
)
License
Apache 2.0 - see LICENSE for details.
Support
1 maintainer
Metadata
1 maintainer
Release files for honcho-ai 2.7.0
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