Building Simple LLM Applications

APIs, chat flows, memory, orchestration, and developer patterns explained clearly and visually.

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Overview

Simple LLM applications rely on predictable patterns. These patterns help developers build robust, modular, testable systems while keeping complexity low.

Key Concepts

LLM APIs

Direct calls to models, providing prompts and receiving responses.

Chat Flows

Structured message sequences for guided or open-ended interactions.

Memory

Techniques for storing and retrieving history, context, or state.

Orchestration

Combining tools, steps, or multiple model calls into workflows.

Developer Patterns

Reusable approaches that improve readability and maintainability.

Process for Building an LLM App

1. Define Goal

Clarify the user task.

2. Design Flow

Map conversation or steps.

3. Select Memory

Choose short-term or vector memory.

4. Add Orchestration

Define how tools or calls connect.

5. Test and Iterate

Refine prompts and flows.

Common Use Cases

Customer Support Agents

Conversational interfaces that use memory and tool calls.

Content Generation

Workflow-based generation using templates and prompts.

Data Extraction

Structured outputs driven by models and validation steps.

Comparison of Development Approaches

Direct API Calls

Fast to build, low complexity, limited structure.

Chat Frameworks

Support conversation flows and memory out of the box.

Full Orchestration Systems

Complex but powerful for multi-step workflows.

FAQ

Do all LLM apps need memory?

No. Simple single-turn apps often work without memory.

What is the easiest way to start?

Begin with direct API calls and gradually add structure.

When do I need orchestration?

When your workflow spans multiple steps or tools.

Start Building LLM Apps Today

Experiment with flows, memory, and orchestration for more powerful applications.

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