uv add honcho-ai

bun add @honcho-ai/sdk

from honcho import Honcho
import os

honcho = Honcho(
    workspace_id="your-app-name",
    api_key=os.environ["HONCHO_API_KEY"],
    environment="production"
)

import { Honcho } from '@honcho-ai/sdk';

const honcho = new Honcho({
    workspaceId: "your-app-name",
    apiKey: process.env.HONCHO_API_KEY,
    environment: "production"
});

undefined

**TypeScript:**

```typescript
// Human users
const user = await honcho.peer("user-123");

// AI assistants - set observe_me=False
const assistant = await honcho.peer("assistant", { config: { observe_me: false } });
const supportBot = await honcho.peer("support-bot", { config: { observe_me: false } });

from honcho import SessionPeerConfig

session = honcho.session("conversation-123")

**TypeScript:**

```typescript
const session = await honcho.session("conversation-123");

await session.addPeers([
    [user, { observeMe: true, observeOthers: true }],
    [assistant, { observeMe: false, observeOthers: true }]
]);

session.add_messages([
    user.message("I'm having trouble with my account"),
    assistant.message("I'd be happy to help. What seems to be the issue?"),
    user.message("I can't reset my password")
])

await session.addMessages([
    user.message("I'm having trouble with my account"),
    assistant.message("I'd be happy to help. What seems to be the issue?"),
    user.message("I can't reset my password")
]);

import openai
from honcho import Honcho

honcho = Honcho(workspace_id="my-app", api_key=os.environ["HONCHO_API_KEY"])

response = openai.chat.completions.create(
    model="gpt-4",
    messages=messages,
    tools=[honcho_tool]
)

# Handle tool calls
if response.choices[0].message.tool_calls:
    for tool_call in response.choices[0].message.tool_calls:
        if tool_call.function.name == "query_user_context":
            import json
            args = json.loads(tool_call.function.arguments)
            result = handle_honcho_tool_call(user_id, args["query"])
            # Continue conversation with tool result...

**TypeScript (OpenAI function calling):**

```typescript
import OpenAI from 'openai';
import { Honcho } from '@honcho-ai/sdk';

const honcho = new Honcho({
    workspaceId: "my-app",
    apiKey: process.env.HONCHO_API_KEY
});

const honchoTool: OpenAI.ChatCompletionTool = {
    type: "function",
    function: {
        name: "query_user_context",
        description: "Query Honcho to retrieve relevant context about the user based on their history and preferences.",
        parameters: {
            type: "object",
            properties: {
                query: {
                    type: "string",
                    description: "A natural language question about the user"
                }
            },
            required: ["query"]
        }
    }
};

async function handleHonchoToolCall(userId: string, query: string): Promise<string> {
    const peer = await honcho.peer(userId);
    return await peer.chat(query);
}

def get_user_context_for_prompt(user_id: str) -> dict:
    """Fetch key user attributes via targeted Honcho queries."""
    peer = honcho.peer(user_id)

    return {
        "communication_style": peer.chat("What communication style does this user prefer? Be concise."),
        "expertise_level": peer.chat("What is this user's technical expertise level? Be concise."),
        "current_goals": peer.chat("What are this user's current goals or priorities? Be concise."),
        "preferences": peer.chat("What key preferences should I know about this user? Be concise.")
    }

def build_system_prompt(user_context: dict) -> str:
    return f"""You are a helpful assistant. Here's what you know about this user:

Communication style: {user_context['communication_style']}
Expertise level: {user_context['expertise_level']}
Current goals: {user_context['current_goals']}
Key preferences: {user_context['preferences']}

Tailor your responses accordingly."""

async function getUserContextForPrompt(userId: string): Promise<Record<string, string>> {
    const peer = await honcho.peer(userId);

    const [style, expertise, goals, preferences] = await Promise.all([
        peer.chat("What communication style does this user prefer? Be concise."),
        peer.chat("What is this user's technical expertise level? Be concise."),
        peer.chat("What are this user's current goals or priorities? Be concise."),
        peer.chat("What key preferences should I know about this user? Be concise.")
    ]);

    return {
        communicationStyle: style,
        expertiseLevel: expertise,
        currentGoals: goals,
        preferences: preferences
    };
}

import openai

session = honcho.session("conversation-123")
user = honcho.peer("user-123")
assistant = honcho.peer("assistant", config={"observe_me": False})

undefined

response_stream = peer.chat("What do we know about this user?", stream=True)

for chunk in response_stream.iter_text():
    print(chunk, end="", flush=True)