> For the complete documentation index, see [llms.txt](https://skylar-1.gitbook.io/skylar/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://skylar-1.gitbook.io/skylar/introduction.md).

# Introduction

**Skylar** is an intuitive AI platform designed for users to create, customize, and deploy **AI agents** with ease. Whether you're looking to automate tasks, answer queries, or enhance user experiences, Skylar leverages **conversational AI** (such as GPT-like technology) to build agents tailored to your specific needs.

Skylar is designed to help users create **autonomous AI agents** that can be deployed across various platforms to perform tasks, answer queries, and provide engaging user experiences. Unlike conventional business-focused tools, Skylar allows for the creation of AI agents tailored to a wide range of personal, creative, or technical use cases.

These AI agents are powered by **advanced conversational models** (like GPT technology), allowing them to engage in meaningful, natural conversations with users. Whether you're an individual creating a fun assistant or a team building a customer service bot, Skylar provides the tools to get the job done with minimal setup and technical knowledge.

When a user sends a request, the server extracts the **user’s input** (i.e., the query or task) and the **personality type** (such as "playful", "friendly", or "sarcastic") from the incoming JSON data. The server then uses this information to generate a personalized response, creating the bot— and adjusting it to the preference of the user. This allows the AI to dynamically tailor its responses to different user preferences and interactions.

```python
@app.route("/ask", methods=["POST"])
def ask():
    user_input = request.json.get("user_input")
    personality_type = request.json.get("personality", "playful")
```

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