migrate-honcho
The migrate-honcho skill automates code updates from Honcho Python SDK v1.6.0 to v2.1.1, handling major breaking changes including async architecture restructuring via the `.aio` accessor, renaming observations to conclusions, removing the Representation class, updating configuration method names, and switching from `chat(stream=True)` to dedicated `chat_stream()` calls. Use this skill when upgrading the honcho package, encountering post-upgrade errors, or when code references AsyncHoncho, observations, Representation classes, .core properties, or legacy configuration methods.
git clone --depth 1 https://github.com/plastic-labs/honcho /tmp/migrate-honcho && cp -r /tmp/migrate-honcho/.claude/skills/migrate-honcho-py ~/.claude/skills/migrate-honchoSKILL.md
# Honcho Python SDK Migration (v1.6.0 → v2.1.1)
## Overview
This skill migrates code from `honcho` Python SDK v1.6.0 to v2.1.1 (required for Honcho 3.0.0+).
**Key breaking changes:**
- `AsyncHoncho`/`AsyncPeer`/`AsyncSession` removed → use `.aio` accessor
- "Observation" → "Conclusion" terminology
- `Representation` class removed (returns `str` now)
- `get_config`/`set_config` → `get_configuration`/`set_configuration`
- Streaming via `chat_stream()` instead of `chat(stream=True)`
- `poll_deriver_status()` removed
- `.core` property removed
## Quick Migration
### 1. Update async architecture
```python
# Before
from honcho import AsyncHoncho, AsyncPeer, AsyncSession
async_client = AsyncHoncho()
peer = await async_client.peer("user-123")
response = await peer.chat("query")
# After
from honcho import Honcho
client = Honcho()
peer = await client.aio.peer("user-123")
response = await peer.aio.chat("query")
# Async iteration
async for p in client.aio.peers():
print(p.id)
```
### 2. Replace observations with conclusions
```python
# Before
from honcho import Observation, ObservationScope, AsyncObservationScope
scope = peer.observations
scope = peer.observations_of("other-peer")
rep = scope.get_representation()
# After
from honcho import Conclusion, ConclusionScope, ConclusionScopeAio
scope = peer.conclusions
scope = peer.conclusions_of("other-peer")
rep = scope.representation() # Returns str
```
### 3. Update representation handling
```python
# Before
from honcho import Representation, ExplicitObservation, DeductiveObservation
rep: Representation = peer.working_rep()
print(rep.explicit)
print(rep.deductive)
if rep.is_empty():
print("No observations")
# After
rep: str = peer.representation()
print(rep) # Just a string now
if not rep:
print("No conclusions")
```
### 4. Rename configuration methods
```python
# Before
config = peer.get_config()
peer.set_config({"observe_me": False})
session.get_config()
client.get_config()
# After
from honcho.api_types import PeerConfig, SessionConfiguration, WorkspaceConfiguration
config = peer.get_configuration()
peer.set_configuration(PeerConfig(observe_me=False))
session.get_configuration()
client.get_configuration()
```
### 5. Update method names
```python
# Before
peer.working_rep()
peer.get_context()
peer.get_sessions()
session.get_context()
session.get_summaries()
session.get_messages()
session.get_peers()
session.get_peer_config()
client.get_peers()
client.get_sessions()
client.get_workspaces()
# After
peer.representation()
peer.context()
peer.sessions()
session.context()
session.summaries()
session.messages()
session.peers()
session.get_peer_configuration()
client.peers()
client.sessions()
client.workspaces()
```
### 6. Update streaming
```python
# Before
response = peer.chat("query", stream=True)
for chunk in response:
print(chunk, end="")
# After
stream = peer.chat_stream("query")
for chunk in stream:
print(chunk, end="")
```
### 7. Update queue status (formerly deriver)
```python
# Before
from honcho_core.types import DeriverStatus
status = client.get_deriver_status()
status = client.poll_deriver_status(timeout=300.0) # Removed!
# After
from honcho.api_types import QueueStatusResponse
status = client.queue_status()
# poll_deriver_status removed - implement polling manually if needed
```
### 8. Update representation parameters
```python
# Before
rep = peer.working_rep(
include_most_derived=True,
max_observations=50
)
# After
rep = peer.representation(
include_most_frequent=True,
max_conclusions=50
)
```
### 9. Move update_message to session
```python
# Before
updated = client.update_message(message=msg, metadata={"key": "value"}, session="sess-id")
# After
updated = session.update_message(message=msg, metadata={"key": "value"})
```
### 10. Update card() return type and method name
```python
# Before
card: str = peer.card() # Returns str
# After (v2.0.0+)
card: list[str] | None = peer.get_card() # Returns list[str] | None
if card:
print("\n".join(card))
# peer.card() still works but is deprecated — use get_card()
# New in v2.0.1: set_card()
peer.set_card(["Prefers dark mode", "Located in US"])
```
### 11. Strict input validation (v2.0.2+)
All input models now reject unknown fields via `extra="forbid"` Pydantic validation. Previously, misspelled or extraneous fields were silently ignored.
```python
# Before (v2.0.1 and earlier) — silently ignored
peer = client.peer("user-1", configuration=PeerConfig(observe_mee=True)) # typo silently ignored
# After (v2.0.2+) — raises ValidationError
peer = client.peer("user-1", configuration=PeerConfig(observe_mee=True)) # ValidationError!
```
### 12. peer() and session() always make API calls (v2.1.0+)
**Breaking**: `peer()` and `session()` now always make a get-or-create API call. Previously, calling without metadata/configuration returned a lazy object with no API call.
```python
# Before (v2.0.x) — no API call without options
peer = client.peer("user-123") # Lazy, no network request
# After (v2.1.0+) — always hits the API
peer = client.peer("user-123") # Makes POST to /peers (get-or-create)
# Async
peer = await client.aio.peer("user-123") # Also always hits API
```
### 13. New properties and methods (v2.1.0+)
```python
# created_at on Peer and Session
peer = client.peer("user-123")
print(peer.created_at) # datetime | None
session = client.session("sess-1")
print(session.created_at) # datetime | None
# is_active on Session
print(session.is_active) # bool | None
# get_message() on Session
msg = session.get_message("msg-id")
# Async: msg = await session.aio.get_message("msg-id")
```
### 14. Pagination parameters on list methods (v2.1.0+)
All list methods now accept `page`, `size`, and `reverse` parameters:
```python
# Before (v2.0.x) — only filters
peers_page = client.peers(filters={"metadata": {"role": "admin"}})
# After (v2.1.0+) — pagination controls
peers_page = client.peers(
filters={"metadata": {Inspect and debug Honcho workspaces via the `honcho` CLI. Use when investigating peer representations, memory state, session context, queue status, or dialectic quality — any task that requires introspection of a Honcho deployment.
Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, implementing the dialectic chat endpoint for AI agents, or wiring Honcho into bot frameworks (nanobot, openclaw, picoclaw, etc).
Migrates Honcho TypeScript SDK code from v1.6.0 to v2.1.1. Use when upgrading @honcho-ai/sdk, fixing breaking changes after upgrade, or when errors mention removed APIs like .core, getConfig, observations, or snake_case properties.
Gives AI agents persistent memory across conversations using Honcho. Automatically saves and retrieves user context so the AI remembers preferences, history, and facts between sessions. Use when you need the AI to remember past conversations, recall what a user has told it, inject relevant context into prompts, or manage separate memory spaces for different topics.