diff --git a/.gitignore b/.gitignore index 9a31fc38..ea5ccca1 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +.worktrees/ api/**/*.db api/data api/docker-compose.yml diff --git a/examples/zo/README.md b/examples/zo/README.md new file mode 100644 index 00000000..b8c8b217 --- /dev/null +++ b/examples/zo/README.md @@ -0,0 +1,148 @@ +# Honcho Memory Skill for Zo Computer + +Give your AI persistent memory across conversations using [Honcho](https://honcho.dev). + +## Features + +- **Auto-Memory**: Save user and assistant messages to Honcho with one call +- **Query Memory**: Ask natural language questions about what Honcho remembers ("What are my hobbies?") +- **Context Injection**: Retrieve conversation context formatted for direct LLM use +- **Multi-Workspace Support**: Manage separate memory spaces via `HONCHO_WORKSPACE_ID` + +## Installation + +```bash +pip install honcho-ai python-dotenv +``` + +Or with uv: + +```bash +uv add honcho-ai python-dotenv +``` + +## Environment Variables + +Create a `.env` file: + +```env +HONCHO_API_KEY=your-api-key-here +HONCHO_WORKSPACE_ID=default +``` + +Get your API key at [honcho.dev](https://honcho.dev). + +## Quick Start + +```python +from tools.save_memory import save_memory +from tools.query_memory import query_memory +from tools.get_context import get_context + +# Save a conversation turn +save_memory("alice", "I love hiking in the mountains", "user", "session-1") +save_memory("alice", "That sounds wonderful!", "assistant", "session-1") + +# Query what Honcho remembers +answer = query_memory("alice", "What are my hobbies?", "session-1") +print(answer) # "Alice enjoys hiking in the mountains." + +# Get context ready for an LLM call +messages = get_context("alice", "session-1", "assistant", tokens=4000) +# messages is a list of {"role": ..., "content": ...} dicts +``` + +## Tool Reference + +### `save_memory(user_id, content, role, session_id, assistant_id="assistant")` + +Saves a message to Honcho memory. + +| Param | Type | Description | +|---|---|---| +| `user_id` | `str` | Unique user identifier | +| `content` | `str` | Message text | +| `role` | `str` | `"user"` or `"assistant"` | +| `session_id` | `str` | Session/conversation identifier | +| `assistant_id` | `str` | Peer ID for the assistant. Defaults to `"assistant"` | + +Returns a confirmation string. + +--- + +### `query_memory(user_id, query, session_id=None)` + +Queries stored memory using Honcho's Dialectic API. + +| Param | Type | Description | +|---|---|---| +| `user_id` | `str` | Unique user identifier | +| `query` | `str` | Natural language question | +| `session_id` | `str \| None` | Optional: scope to a specific session. Defaults to `None` (global memory) | + +Returns a natural language answer. + +> **Note:** In shared workspaces, `query_memory` may return data from other peers if the queried user has no stored memory yet. The Dialectic API draws from workspace-level context as a fallback. Use unique `HONCHO_WORKSPACE_ID` values per user group in production to prevent cross-peer data leakage. + +--- + +### `get_context(user_id, session_id, assistant_id, tokens=4000)` + +Retrieves conversation context in OpenAI message format. + +| Param | Type | Description | +|---|---|---| +| `user_id` | `str` | Unique user identifier | +| `session_id` | `str` | Session/conversation identifier | +| `assistant_id` | `str` | Peer ID for the assistant | +| `tokens` | `int` | Max tokens to include (default: 4000) | + +Returns a list of `{"role": ..., "content": ...}` dicts. + +## Concept Mapping + +| Zo Computer | Honcho | +|---|---| +| Account | Workspace | +| User | Peer | +| Conversation | Session | +| Message | Message | + +## Running Tests + +Requires a running Honcho server. See the [main repo](../../README.md) for setup instructions. + +```bash +uv run pytest tests/ -v +``` + +## Submitting to the Zo Skill Marketplace + +To publish this skill to the [Zo Skills Registry](https://github.com/zocomputer/skills): + +1. **Fork** the `zocomputer/skills` repository. +2. **Copy** this directory into the `/Community` folder of your fork, naming it `honcho-memory`: + + ``` + Community/ + └── honcho-memory/ + ├── SKILL.md + ├── README.md + ├── client.py + ├── pyproject.toml + └── tools/ + ``` + +3. **Validate** your skill: + + ```bash + bun validate + ``` + +4. **Submit a pull request** to the upstream registry repository. + +Once merged, the skill will be automatically added to the Zo marketplace `manifest.json`. + +## License + +AGPL-3.0-or-later diff --git a/examples/zo/SKILL.md b/examples/zo/SKILL.md new file mode 100644 index 00000000..7c2d532b --- /dev/null +++ b/examples/zo/SKILL.md @@ -0,0 +1,118 @@ +--- +name: honcho-memory +description: 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. +license: AGPL-3.0 +compatibility: Requires Python 3.9+, honcho-ai>=2.1.0, and a Honcho API key from honcho.dev. Set HONCHO_API_KEY and optionally HONCHO_WORKSPACE_ID in your environment. +metadata: + author: plastic-labs + version: "0.1.0" + honcho-sdk: "2.1.0" +--- + +# Honcho Memory Skill + +This skill provides three tools for storing and retrieving AI memory using [Honcho](https://honcho.dev). + +## Setup + +1. Get a Honcho API key at [honcho.dev](https://honcho.dev). +2. Set environment variables: + + ``` + HONCHO_API_KEY=your-api-key + HONCHO_WORKSPACE_ID=default # optional, defaults to "default" + ``` + +3. Install dependencies: + + ``` + pip install honcho-ai python-dotenv + ``` + +## Tools + +### `save_memory` + +Saves a conversation turn (user or assistant message) to Honcho. + +**When to use:** After every message exchange to build up the user's memory. + +```python +from tools.save_memory import save_memory + +save_memory( + user_id="alice", # unique user identifier + content="I love hiking", # message text + role="user", # "user" or "assistant" + session_id="chat-1", # conversation session ID + assistant_id="assistant" # optional: assistant peer ID (default: "assistant") +) +``` + +### `query_memory` + +Asks a natural language question against stored memory using Honcho's Dialectic API. + +**When to use:** When the user asks "do you remember...?", or when you need to recall facts about the user before responding. + +```python +from tools.query_memory import query_memory + +answer = query_memory( + user_id="alice", + query="What are Alice's hobbies?", + session_id="chat-1" # optional: scope to a session +) +# Returns: "Alice enjoys hiking." +``` + +### `get_context` + +Retrieves recent conversation history formatted for direct use in an LLM API call. + +**When to use:** At the start of each LLM call to inject relevant context from past conversations. + +```python +from tools.get_context import get_context + +messages = get_context( + user_id="alice", + session_id="chat-1", + assistant_id="assistant", + tokens=4000 # max tokens to include +) +# Returns: [{"role": "user", "content": "..."}, ...] +``` + +## Concept Mapping + +| Zo Computer | Honcho | +|---|---| +| Account | Workspace | +| User | Peer | +| Conversation | Session | +| Message | Message | + +## Example: Full Conversation Flow + +```python +from tools.save_memory import save_memory +from tools.query_memory import query_memory +from tools.get_context import get_context + +user_id = "alice" +session_id = "session-1" + +# 1. Save user message +save_memory(user_id, "I'm learning Rust and love rock climbing", "user", session_id) + +# 2. Save assistant reply +save_memory(user_id, "That's great! Both require patience.", "assistant", session_id) + +# 3. In a later session, recall what you know +print(query_memory(user_id, "What does Alice do in her free time?")) +# → "Alice is learning Rust and enjoys rock climbing." + +# 4. Get context window for next LLM call +messages = get_context(user_id, session_id, "assistant", tokens=4000) +``` diff --git a/examples/zo/pyproject.toml b/examples/zo/pyproject.toml new file mode 100644 index 00000000..68c0a616 --- /dev/null +++ b/examples/zo/pyproject.toml @@ -0,0 +1,25 @@ +[project] +name = "honcho-zo-skill" +version = "0.1.0" +description = "Honcho persistent memory skill for Zo Computer" +readme = "README.md" +requires-python = ">=3.9" +dependencies = [ + "honcho-ai>=2.1.0", + "python-dotenv>=1.0.0", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.0.0", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["tools"] + +[tool.pytest.ini_options] +pythonpath = ["."] diff --git a/examples/zo/tests/test_basic.py b/examples/zo/tests/test_basic.py new file mode 100644 index 00000000..1afe00d4 --- /dev/null +++ b/examples/zo/tests/test_basic.py @@ -0,0 +1,69 @@ +"""Basic import and structure tests for honcho-zo-skill. + +These tests validate package structure and imports without requiring +a running Honcho server. +""" + +import os +import sys + +import pytest + +# Add parent directory to path so tools/ can be imported +sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + + +def test_save_memory_import(): + """Test that save_memory can be imported.""" + from tools.save_memory import save_memory + + assert callable(save_memory) + + +def test_query_memory_import(): + """Test that query_memory can be imported.""" + from tools.query_memory import query_memory + + assert callable(query_memory) + + +def test_get_context_import(): + """Test that get_context can be imported.""" + from tools.get_context import get_context + + assert callable(get_context) + + +def test_tools_package_import(): + """Test that the tools package exports all three functions.""" + import tools + + assert hasattr(tools, "save_memory") + assert hasattr(tools, "query_memory") + assert hasattr(tools, "get_context") + + +def test_tools_all_exports(): + """Test that __all__ contains expected exports.""" + import tools + + assert hasattr(tools, "__all__") + expected = ["get_context", "query_memory", "save_memory"] + for name in expected: + assert name in tools.__all__, f"{name} not in __all__" + + +def test_save_memory_raises_on_empty_content(): + """Test that save_memory raises ValueError for empty content.""" + from tools.save_memory import save_memory + + with pytest.raises(ValueError, match="content must not be empty"): + save_memory("user1", "", "user", "session1") + + +def test_query_memory_raises_on_empty_query(): + """Test that query_memory raises ValueError for empty query.""" + from tools.query_memory import query_memory + + with pytest.raises(ValueError, match="query must not be empty"): + query_memory("user1", "") diff --git a/examples/zo/tests/test_tools.py b/examples/zo/tests/test_tools.py new file mode 100644 index 00000000..00c34b78 --- /dev/null +++ b/examples/zo/tests/test_tools.py @@ -0,0 +1,199 @@ +"""Functional tests for Honcho Zo skill tools. + +These tests require a Honcho API key set in the HONCHO_API_KEY environment +variable. They run against the Honcho cloud API (honcho.dev) by default. +Set HONCHO_WORKSPACE_ID to scope tests to a specific workspace. +""" + +import os +import sys +import time +import uuid + +import pytest + +sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + +from tools.get_context import get_context +from tools.query_memory import query_memory +from tools.save_memory import save_memory + +pytestmark = pytest.mark.skipif( + not os.getenv("HONCHO_API_KEY"), + reason="HONCHO_API_KEY not set — skipping integration tests", +) + + +@pytest.fixture(autouse=True) +def rate_limit_delay(): + """Pause between tests to stay under the Honcho API rate limit (5 req/sec).""" + yield + time.sleep(0.5) + + +def unique_id(prefix: str) -> str: + """Generate a unique ID with a prefix to avoid test state leakage.""" + return f"{prefix}_{uuid.uuid4().hex[:8]}" + + +class TestSaveMemory: + """Tests for save_memory tool.""" + + def test_returns_confirmation_string(self): + """Test that save_memory returns a non-empty confirmation string.""" + result = save_memory(unique_id("user"), "Hello, I love hiking!", "user", unique_id("session")) + + assert isinstance(result, str) + assert len(result) > 0 + + def test_saves_user_message(self): + """Test saving a user-role message.""" + user_id = unique_id("user") + result = save_memory(user_id, "I enjoy Python programming", "user", unique_id("session")) + + assert isinstance(result, str) + assert "user" in result.lower() or user_id in result + + def test_saves_assistant_message(self): + """Test saving an assistant-role message.""" + result = save_memory(unique_id("user"), "That sounds great!", "assistant", unique_id("session")) + + assert isinstance(result, str) + assert len(result) > 0 + + def test_saves_multiple_turns(self): + """Test saving multiple turns in the same session.""" + user_id = unique_id("user") + session_id = unique_id("session") + + result1 = save_memory(user_id, "I love mountains", "user", session_id) + result2 = save_memory(user_id, "That's wonderful!", "assistant", session_id) + + assert isinstance(result1, str) and len(result1) > 0 + assert isinstance(result2, str) and len(result2) > 0 + + def test_non_assistant_role_treated_as_user(self): + """Test that any role other than 'assistant' is treated as user.""" + result = save_memory(unique_id("user"), "Testing role fallback", "human", unique_id("session")) + + assert isinstance(result, str) + assert len(result) > 0 + + def test_custom_assistant_id(self): + """Test that a custom assistant_id is accepted.""" + result = save_memory( + unique_id("user"), "Hello!", "assistant", unique_id("session"), assistant_id="my-bot" + ) + + assert isinstance(result, str) + assert len(result) > 0 + + +class TestQueryMemory: + """Tests for query_memory tool.""" + + def test_returns_string(self): + """Test that query_memory returns a string response.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "I love pizza and Italian food", "user", session_id) + + result = query_memory(user_id, "What does the user enjoy?") + + assert isinstance(result, str) + assert len(result) > 0 + + def test_returns_string_with_session_scope(self): + """Test query_memory scoped to a specific session.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "My favorite color is blue", "user", session_id) + + result = query_memory(user_id, "What is the user's favorite color?", session_id) + + assert isinstance(result, str) + assert len(result) > 0 + + def test_returns_fallback_for_unknown_user(self): + """Test that query_memory returns a non-empty string even for new users.""" + result = query_memory(unique_id("user"), "What do I like?") + + assert isinstance(result, str) + assert len(result) > 0 + + +class TestGetContext: + """Tests for get_context tool.""" + + def test_returns_list(self): + """Test that get_context returns a list.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "Hello there!", "user", session_id) + + result = get_context(user_id, session_id, "assistant") + + assert isinstance(result, list) + + def test_returns_openai_format(self): + """Test that returned messages are in OpenAI format.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "My name is Alex", "user", session_id) + save_memory(user_id, "Nice to meet you, Alex!", "assistant", session_id) + + result = get_context(user_id, session_id, "assistant") + + assert isinstance(result, list) + for msg in result: + assert "role" in msg + assert "content" in msg + assert msg["role"] in ("user", "assistant", "system") + assert isinstance(msg["content"], str) + + def test_respects_token_limit(self): + """Test that context respects the token limit parameter.""" + user_id = unique_id("user") + session_id = unique_id("session") + for i in range(5): + save_memory(user_id, f"Message number {i} with some content", "user", session_id) + + result_small = get_context(user_id, session_id, "assistant", tokens=100) + result_large = get_context(user_id, session_id, "assistant", tokens=8000) + + assert isinstance(result_small, list) + assert isinstance(result_large, list) + assert len(result_large) >= len(result_small) + + def test_empty_session_returns_list(self): + """Test that get_context returns an empty list for a session with no messages.""" + result = get_context(unique_id("user"), unique_id("session"), "assistant") + + assert isinstance(result, list) + + +class TestToolsWorkTogether: + """Integration tests using all three tools in sequence.""" + + def test_save_query_roundtrip(self): + """Test saving a message and then querying it.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "I am a software engineer who loves Rust", "user", session_id) + + result = query_memory(user_id, "What is the user's profession?", session_id) + + assert isinstance(result, str) + assert len(result) > 0 + + def test_save_then_get_context(self): + """Test that saved messages appear in context.""" + user_id = unique_id("user") + session_id = unique_id("session") + save_memory(user_id, "Hello!", "user", session_id) + save_memory(user_id, "Hi there!", "assistant", session_id) + + messages = get_context(user_id, session_id, "assistant") + + assert isinstance(messages, list) + assert len(messages) >= 1 diff --git a/examples/zo/tools/__init__.py b/examples/zo/tools/__init__.py new file mode 100644 index 00000000..4d8b4830 --- /dev/null +++ b/examples/zo/tools/__init__.py @@ -0,0 +1,7 @@ +"""Honcho memory tools for Zo Computer.""" + +from tools.get_context import get_context +from tools.query_memory import query_memory +from tools.save_memory import save_memory + +__all__ = ["get_context", "query_memory", "save_memory"] diff --git a/examples/zo/tools/client.py b/examples/zo/tools/client.py new file mode 100644 index 00000000..ad1257b2 --- /dev/null +++ b/examples/zo/tools/client.py @@ -0,0 +1,32 @@ +"""Honcho client initialization for Zo Computer skill.""" + +import os + +from dotenv import load_dotenv +from honcho import Honcho + +load_dotenv() + + +def get_client(workspace_id: str | None = None) -> Honcho: + """Initialize and return a Honcho client. + + Reads HONCHO_API_KEY and HONCHO_WORKSPACE_ID from environment variables. + The workspace_id parameter overrides the environment variable if provided. + + Args: + workspace_id: Optional workspace ID override. Falls back to the + HONCHO_WORKSPACE_ID env var, then to "default". + + Returns: + Configured Honcho client instance. + """ + api_key = os.getenv("HONCHO_API_KEY") + if not api_key: + raise ValueError( + "HONCHO_API_KEY is required. Set it in your environment or .env file." + ) + + env_workspace = os.getenv("HONCHO_WORKSPACE_ID") + resolved_workspace = workspace_id or env_workspace or "default" + return Honcho(api_key=api_key, workspace_id=resolved_workspace) diff --git a/examples/zo/tools/get_context.py b/examples/zo/tools/get_context.py new file mode 100644 index 00000000..fdf3cb10 --- /dev/null +++ b/examples/zo/tools/get_context.py @@ -0,0 +1,42 @@ +"""Retrieve conversation context from Honcho formatted for LLM use.""" + +from __future__ import annotations + +from .client import get_client + + +def get_context( + user_id: str, + session_id: str, + assistant_id: str, + tokens: int = 4000, +) -> list[dict[str, str]]: + """Retrieve conversation context ready for injection into an LLM prompt. + + Fetches recent messages from a Honcho session within the given token + budget and converts them to OpenAI-compatible message format. Use the + returned list directly as the ``messages`` parameter in an LLM API call. + + Args: + user_id: Unique identifier for the user peer. Used to ensure the + peer is registered in the session before fetching context. + session_id: Identifier for the conversation session. + assistant_id: Peer ID representing the assistant. This determines + which role is mapped to ``"assistant"`` in the output. + tokens: Maximum number of tokens to include in the context window. + Defaults to 4000. + + Returns: + A list of message dicts in OpenAI format: + ``[{"role": "user" | "assistant", "content": "..."}]``. + Returns an empty list if the session has no messages. + """ + honcho = get_client() + user_peer = honcho.peer(user_id) + assistant_peer = honcho.peer(assistant_id) + session = honcho.session(session_id) + + session.add_peers([user_peer, assistant_peer]) + + context = session.context(tokens=tokens) + return context.to_openai(assistant=assistant_id) diff --git a/examples/zo/tools/query_memory.py b/examples/zo/tools/query_memory.py new file mode 100644 index 00000000..01836a09 --- /dev/null +++ b/examples/zo/tools/query_memory.py @@ -0,0 +1,37 @@ +"""Query a user's Honcho memory using the Dialectic API.""" + +from __future__ import annotations + +from .client import get_client + + +def query_memory(user_id: str, query: str, session_id: str | None = None) -> str: + """Query stored memory for a user using Honcho's Dialectic API. + + Sends a natural language question to Honcho and returns an answer + grounded in the peer's long-term representation and stored observations. + + Args: + user_id: Unique identifier for the user peer. + query: Natural language question, e.g. "What are my hobbies?". + session_id: Optional session ID to scope the query to a specific + conversation. If omitted, the query draws from global memory. + + Returns: + A natural language answer from Honcho's Dialectic API, or a + default message if no relevant information was found. + + Raises: + ValueError: If query is empty. + """ + if not query: + raise ValueError("query must not be empty") + + honcho = get_client() + peer = honcho.peer(user_id) + + response = peer.chat(query=query, session=session_id) + + if response: + return str(response) + return "No relevant information found in memory." diff --git a/examples/zo/tools/save_memory.py b/examples/zo/tools/save_memory.py new file mode 100644 index 00000000..f7818066 --- /dev/null +++ b/examples/zo/tools/save_memory.py @@ -0,0 +1,45 @@ +"""Save a conversation message to Honcho memory.""" + +from .client import get_client + + +def save_memory( + user_id: str, + content: str, + role: str, + session_id: str, + assistant_id: str = "assistant", +) -> str: + """Save a single conversation turn to Honcho memory. + + Creates the peer and session if they do not already exist. Registers + the peer in the session on first use, then persists the message. + + Args: + user_id: Unique identifier for the user peer. + content: Text content of the message to save. + role: Either "user" or "assistant". Determines which peer sends + the message. Any value other than "assistant" is treated as "user". + session_id: Identifier for the conversation session. + assistant_id: Peer ID for the assistant. Defaults to "assistant". + + Returns: + A confirmation string describing what was saved. + + Raises: + ValueError: If content is empty. + """ + if not content: + raise ValueError("content must not be empty") + + honcho = get_client() + user_peer = honcho.peer(user_id) + assistant_peer = honcho.peer(assistant_id) + session = honcho.session(session_id) + + session.add_peers([user_peer, assistant_peer]) + + sender = assistant_peer if role == "assistant" else user_peer + session.add_messages([sender.message(content)]) + + return f"Saved {role} message to session '{session_id}' for user '{user_id}'." diff --git a/examples/zo/uv.lock b/examples/zo/uv.lock new file mode 100644 index 00000000..902f8fdd --- /dev/null +++ b/examples/zo/uv.lock @@ -0,0 +1,503 @@ +version = 1 +revision = 3 +requires-python = ">=3.9" +resolution-markers = [ + "python_full_version >= '3.10'", + "python_full_version < '3.10'", +] + +[[package]] +name = "annotated-types" +version = "0.7.0" +source = { registry = 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