# Mindforge WebApp

## Mindforge WebApp Guide

This guide will walk you through the steps to create and analyze AI agent experiments using the **Mindforge AI Laboratory** on the website.

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### Getting Started

You can begin using the laboratory in two ways:

1. **Create a new experiment** from scratch.
2. **Load an existing experiment** using its unique ID.

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### Creating a New Experiment

#### Step 1: Agent Creation

Before creating agents, you’ll need to:

* Define a **conversation topic** (e.g., "Space Exploration", "Climate Change").
* Add at least **two agents** to participate in the conversation.

There are three ways to add agents:

* **Random Agent**: Generates an AI agent with random personality traits (a topic must be set first).
* **Custom Agent**: Allows you to design an agent with specific characteristics.
* **Import Agents**: Import agents from a previous experiment using its ID.

**Note:** You need a topic and at least 2 agents to proceed to the next step.

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#### Step 2: Conversation Setup

After creating your agents, configure the conversation parameters:

* **Topic**: Pre-filled from Step 1 (cannot be changed at this stage).
* **Messages per Agent**: Set the number of messages each agent will contribute (choose between 2-5 messages).

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#### Step 3: Simulation

In this phase:

* Agents will engage in a conversation based on the configured parameters.
* You can observe the conversation in **real-time**.
* Each agent will send the specified number of messages.
* The simulation ends automatically when all messages are sent.

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#### Step 4: Analysis

Once the simulation is complete, you can access the following insights:

**Key Metrics:**

* **Idea Diversity**
* **Conversation Depth**
* **Emotional Intelligence**
* **Logical Consistency**
* **Creativity Score**

**Detailed Insights:**

* **Main Topics**
* **Key Discussion Points**
* **Main Conclusions**
* **Emergent Behaviors**
* **Research Implications**
* **Suggested Next Topics**

**Agent Analysis:**

* **Behavioral Patterns**
* **Cognitive Patterns**
* **Emotional Responses**
* **Adaptability Scores**
* **Role Consistency**

**Interaction Dynamics:**

* **Power Dynamics**
* **Group Polarization**
* **Cognitive Alignment**
* **Influence Patterns**

From the analysis page, you can:

* **View the full conversation**.
* **Share your experiment via the URL**
* **Start a new experiment**.

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### Loading an Existing Experiment

If you have an experiment ID:

1. Enter it in the **"Load Existing Experiment"** field.
2. Click **"Load Experiment"**.

You’ll be directed to:

* **The simulation**, if the conversation is still in progress.
* **The analysis**, if the conversation is complete.

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### Important Notes

* **Topic Requirement**: A topic must be defined before creating random agents.
* **Minimum Agents**: At least 2 agents are needed to start an experiment.
* **Experiment ID**: Save your experiment ID to revisit your results later.
* **Session Persistence**: You can return to your experiment anytime using its ID.

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### Tips for Better Results

#### Topic Selection:

* Choose **clear and specific** topics.
* Avoid overly broad or vague subjects.

#### Agent Creation:

* Combine **random** and **custom agents** for diverse interactions.
* Create agents with **contrasting viewpoints** for richer discussions.

#### Message Count:

* Start with **3 messages per agent** for balanced conversations.
* Use **more messages** for complex topics.
* Opt for **fewer messages** for quick exploratory discussions.

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://mindforgeai.gitbook.io/mindforgeai/mindforge-framework/mindforge-webapp.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.