Streaming Responses

from honcho import Honcho

# Initialize client (using the default workspace)
honcho = Honcho()

# Create or get peers
user = honcho.peer("demo-user")
assistant = honcho.peer("assistant")

# Create a new session
session = honcho.session("demo-session")

# Add peers to the session
session.add_peers([user, assistant])

# Store some messages for context (optional)
session.add_messages([
    user.message("Hello, I'm testing the streaming functionality")
])

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

(async () => {
    // Initialize client (using the default workspace)
    const honcho = new Honcho({});

    // Create or get peers
    const user = await honcho.peer('demo-user');
    const assistant = await honcho.peer('assistant');

    // Create a new session
    const session = await honcho.session('demo-session');

    // Add peers to the session
    await session.addPeers([user, assistant]);

    // Store some messages for context (optional)
    await session.addMessages([
      user.message("Hello, I'm testing the streaming functionality")
    ]);
})();

import time

# Basic streaming example
response_stream = user.chat("What can you tell me about this user?", stream=True)

for chunk in response_stream.iter_text():
    print(chunk, end="", flush=True)  # Print each chunk as it arrives
    time.sleep(0.01)  # Optional delay for demonstration

(async () => {
    // Basic streaming example
    const responseStream = await user.chat("What can you tell me about this user?", {
      stream: true
    });

    // Process the stream
    for await (const chunk of responseStream.iter_text()) {
      process.stdout.write(chunk);  // Write to console without newlines
    }
})();

import asyncio
from honcho import Honcho

async def restaurant_recommendation_chat():
    # Initialize client
    honcho = Honcho()

    # Create peers
    user = honcho.peer("food-lover")
    assistant = honcho.peer("restaurant-assistant")

    # Create session
    session = honcho.session("food-preferences-session")

    # Add peers to session
    await session.add_peers([user, assistant])

    # Store multiple user messages about food preferences
    user_messages = [
        "I absolutely love spicy Thai food, especially curries with coconut milk.",
        "Italian cuisine is another favorite - fresh pasta and wood-fired pizza are my weakness!",
        "I try to eat vegetarian most of the time, but occasionally enjoy seafood.",
        "I can't handle overly sweet desserts, but love something with dark chocolate."
    ]

    # Add the user's messages to the session
    session_messages = [user.message(message) for message in user_messages]
    await session.add_messages(session_messages)

    # Print the user messages
    for message in user_messages:
        print(f"User: {message}")

    # Ask for restaurant recommendations based on preferences
    print("\nRequesting restaurant recommendations...")
    print("Assistant: ", end="", flush=True)
    full_response = ""

    # Stream the response using the user's peer to get recommendations
    response_stream = user.chat(
        "Based on this user's food preferences, recommend 3 restaurants they might enjoy in the Lower East Side.",
        stream=True,
        session_id=session.id
    )

    for chunk in response_stream.iter_text():
        print(chunk, end="", flush=True)
        full_response += chunk
        await asyncio.sleep(0.01)

    # Store the assistant's complete response
    await session.add_messages([
        assistant.message(full_response)
    ])

# Run the async function
if __name__ == "__main__":
    asyncio.run(restaurant_recommendation_chat())

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

(async () => {
    async function restaurantRecommendationChat() {
      // Initialize client
      const honcho = new Honcho({});

      // Create peers
      const user = await honcho.peer('food-lover');
      const assistant = await honcho.peer('restaurant-assistant');

      // Create session
      const session = await honcho.session('food-preferences-session');

      // Add peers to session
      await session.addPeers([user, assistant]);

      // Store multiple user messages about food preferences
      const userMessages = [
        "I absolutely love spicy Thai food, especially curries with coconut milk.",
        "Italian cuisine is another favorite - fresh pasta and wood-fired pizza are my weakness!",
        "I try to eat vegetarian most of the time, but occasionally enjoy seafood.",
        "I can't handle overly sweet desserts, but love something with dark chocolate."
      ];

      // Add the user's messages to the session
      const sessionMessages = userMessages.map(message => user.message(message));
      await session.addMessages(sessionMessages);

      // Print the user messages
      for (const message of userMessages) {
        console.log(`User: ${message}`);
      }

      // Ask for restaurant recommendations based on preferences
      console.log("\nRequesting restaurant recommendations...");
      process.stdout.write("Assistant: ");
      let fullResponse = "";

      // Stream the response using the user's peer to get recommendations
      const responseStream = await user.chat(
        "Based on this user's food preferences, recommend 3 restaurants they might enjoy in the Lower East Side.",
        {
          stream: true,
          sessionId: session.id
        }
      );

      for await (const chunk of responseStream.iter_text()) {
        process.stdout.write(chunk);
        fullResponse += chunk;
      }

      // Store the assistant's complete response
      await session.addMessages([
        assistant.message(fullResponse)
      ]);
    }

    await restaurantRecommendationChat();
})();