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content/blog/A Simple Honcho Primer.md
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@ -53,12 +53,12 @@ But it's not intuitive for a few reasons:
Still, when interacting with an AI app, there's a sense that it *should* be getting to know us. In fact, we're often surprised when we realize it's not learning about us over time. And probably annoyed at having to start over.
Think about personalization here as more like the experience of close human companionship or white glove services than the attention hacking mechanisms of TikTok[^2]. There's [[Announcing Honcho's Private Beta#^xb6ef1|enormous potenial]] for more positive-sum use of user data and for aligning AI applications more closely with user needs and preferences.
Think about personalization here as more like the experience of close human companionship or white glove services than the attention hacking mechanisms of TikTok. There's [[Announcing Honcho's Private Beta#^xb6ef1|enormous potenial]] for more positive-sum use of user data and for aligning AI applications more closely with user needs and preferences[^2].
## How to Use Honcho
^cd2d3c
Honcho is first and foremost a **storage** framework. Think of it like an open source version of the OpenAI Assistants API. User `sessions` store both user and AI generated `messages` as well as any intermediate inferences you might want to store as `metamessages`.
Honcho is first and foremost a **storage** framework. Think of it like an open source version of the OpenAI Assistants API. User `sessions` store both user and AI generated `messages` as well as any intermediate inferences you might want to store as `metamessages`:
```python
user_input = "Here's a message!"
@ -68,21 +68,21 @@ session.create_message(is_user=True, content=user_input)
session.create_message(is_user=False, content=ai_response)
```
But what about vectorDBs? Don't worry, Honcho has you covered there too. You can embed data and store them as `documents` in per-user vector DBs called `collections`.
But what about vectorDBs? Don't worry, Honcho has you covered there too. You can embed data and store them as `documents` in per-user vector DBs called `collections`:
```python
collection.create_document(content="The user is interested in AI")
```
Using Honcho as a storage mechanism allows you to **retrieve** rich insights via the user profiles it's building and managing on the backend. Your application's LLM can access them via the *[[Introducing Honcho's Dialectic API|dialectic]]* API.
Using Honcho as a storage mechanism allows you to **retrieve** rich insights via the user profiles it's building and managing on the backend. Your application's LLM can access [[Loose theory of mind imputations are superior to verbatim response predictions|theory-of-mind]] inference over those profiles via the *[[Introducing Honcho's Dialectic API|dialectic]]* API.
It's simple: just query in natural language using the `session.chat()` method.
It's simple: just query in natural language using the `session.chat()` method:
```python
session.chat("What are the user's interests?")
```
There are a [[Introducing Honcho's Dialectic API#How It Works|ton of ways]] to use this, and the current product only scratches the surface[^3].
There are a [[Introducing Honcho's Dialectic API#How It Works|ton of ways]] to use Honcho, this primer only scratches the surface[^3].
## What's Next for Honcho?
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@ -91,7 +91,7 @@ Beyond improving our internal AI models so they can get to know users as richly
1. [[Announcing Honcho's Private Beta#^x2dd3b|Monitoring & Evaluation]] - developer tools to understand & assess the impact of personalization + machine learning tools to build personalized datasets
2. [[Announcing Honcho's Private Beta#^a84f44|User-Facing Controls]] - chat with *your* Honcho to direct how it manages & shares data + authenticate with Honcho to sign-in to AI apps
3. [[Announcing Honcho's Private Beta#^ebf071|A Honcho Application Ecosystem]] - a network of apps contributing to & sharing Honcho data, user-owned & stored in confidential environments
3. [[Announcing Honcho's Private Beta#^ebf071|Honcho Application Ecosystem]] - a network of apps contributing to & sharing Honcho data, user-owned & stored in confidential environments
And in just a few weeks, we'll be launching a demo platform where anyone can interact with (& eventually build) Honcho powered apps.