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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">What is MoA Chat?</h2>
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  <p class="mb-4 text-lg">
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- <strong>MoA (Model of Agents)</strong> is a method that lets multiple AI agents (different LLMs) collaborate to generate a higher-quality response than a single model could.
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  </p>
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  <p class="mb-4">
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- MoA Chat implements a simple version of this architecture by:
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  </p>
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  <ul class="list-disc ml-6 text-lg">
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- <li>Querying several different models (LLM-A, LLM-B, LLM-C) at once.</li>
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- <li>Combining their answers using another model (LLM-D, the aggregator).</li>
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- <li>Delivering a smart, single, structured reply to the user.</li>
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  </ul>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">How MoA Works (Visual)</h2>
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  <p class="mb-4 text-center">
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- <img src="https://raw.githubusercontent.com/togethercomputer/MoA/main/assets/moa_pipeline.png" alt="MoA Architecture" class="mx-auto rounded shadow-md">
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  </p>
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- <p class="text-center text-sm opacity-70">Source: Together MoA Architecture Concept</p>
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  </section>
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  <section class="mb-10">
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- <h2 class="text-2xl font-semibold mb-4 text-blue">How to Use</h2>
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  <ol class="list-decimal ml-6 text-lg">
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- <li>Click ⚙️ to open the configuration panel.</li>
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  <li>Select your preferred models for LLM-A, LLM-B, LLM-C, and Aggregator (LLM-D).</li>
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- <li>Type your message in the input box.</li>
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- <li>Press <strong>Send</strong>.</li>
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- <li>Watch multiple models collaborate for the best response!</li>
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  </ol>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">Features</h2>
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  <ul class="list-disc ml-6 text-lg">
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- <li>Parallel querying of multiple free or premium models (via OpenRouter, Together, Grok, etc.).</li>
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- <li>Structured prompts for each model to encourage quality responses.</li>
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- <li>Aggregator model intelligently fuses outputs into one reply.</li>
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- <li>Dynamic Light/Dark mode (Gruvbox Material Theme).</li>
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- <li>Minimal, fast, and secure frontend with no API keys exposed.</li>
 
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  </ul>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">Deployment</h2>
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  <p class="mb-4 text-lg">
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- MoA Chat is optimized to run on <strong>Hugging Face Spaces</strong> or any platform that supports Python 3.11+, Flask, and Docker-based containers.
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  </p>
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  <p class="text-lg">
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- Requires setting your API keys via Hugging Face's Secrets system (never expose them to the frontend).
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  </p>
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  </section>
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@@ -75,22 +75,31 @@
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  <h2 class="text-2xl font-semibold mb-4 text-blue">File Structure</h2>
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  <ul class="list-disc ml-6 text-lg">
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  <li><code>app.py</code> — Flask backend server.</li>
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- <li><code>llm/agents.py</code> — Query and aggregation logic for MoA system.</li>
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- <li><code>llm/model_config.json</code> — Define available models and providers.</li>
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  <li><code>templates/</code> — Contains <code>index.html</code> and <code>docs.html</code>.</li>
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  <li><code>static/</code> — Contains <code>style.css</code> and <code>script.js</code>.</li>
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  </ul>
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  </section>
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  <section class="mb-10">
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- <h2 class="text-2xl font-semibold mb-4 text-blue">Credits</h2>
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- <p class="text-lg">Made with ❤️ in Panamá by Until Dot. Inspired by Together's MoA architecture.</p>
 
 
 
 
 
 
 
 
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  </section>
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  </div>
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- <div class="text-center mt-8">
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  <a href="/" class="px-6 py-2 bg-blue text-fg0 rounded hover:bg-purple transition text-lg font-semibold">← Back to Chat</a>
 
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  </div>
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  <script>
 
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">What is MoA Chat?</h2>
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  <p class="mb-4 text-lg">
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+ <strong>MoA (Model of Agents)</strong> is a method that allows multiple AI models to collaborate to generate a higher-quality response than a single model could.
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  </p>
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  <p class="mb-4">
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+ MoA Chat implements this idea by:
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  </p>
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  <ul class="list-disc ml-6 text-lg">
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+ <li>Querying several different models (LLM-A, LLM-B, LLM-C) simultaneously.</li>
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+ <li>Combining their answers using a special model (LLM-D, the aggregator).</li>
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+ <li>Delivering a smart, clear, and polished reply to the user.</li>
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  </ul>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">How MoA Works (Visual)</h2>
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  <p class="mb-4 text-center">
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+ <img src="https://raw.githubusercontent.com/togethercomputer/MoA/main/assets/moa-explained.png" alt="MoA Architecture Explained" class="mx-auto rounded shadow-md">
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  </p>
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+ <p class="text-center text-sm opacity-70">Source: Together Computer, MoA Architecture Overview</p>
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  </section>
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  <section class="mb-10">
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+ <h2 class="text-2xl font-semibold mb-4 text-blue">How to Use MoA Chat</h2>
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  <ol class="list-decimal ml-6 text-lg">
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+ <li>Click ⚙️ to open the model configuration panel.</li>
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  <li>Select your preferred models for LLM-A, LLM-B, LLM-C, and Aggregator (LLM-D).</li>
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+ <li>Type your message in the chat input box.</li>
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+ <li>Press <strong>Send</strong> and watch the system generate a unified, better answer!</li>
 
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  </ol>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">Features</h2>
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  <ul class="list-disc ml-6 text-lg">
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+ <li>Parallel querying of multiple free and premium LLMs (OpenRouter, Together, Grok, etc.).</li>
56
+ <li>Structured system prompts for consistent quality.</li>
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+ <li>Aggregator model intelligently fuses outputs into a coherent final response.</li>
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+ <li>Dynamic Light/Dark Gruvbox Material theme.</li>
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+ <li>Secure: No API keys exposed to frontend.</li>
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+ <li>Minimal, fast, mobile-friendly interface.</li>
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  </ul>
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  </section>
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  <section class="mb-10">
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  <h2 class="text-2xl font-semibold mb-4 text-blue">Deployment</h2>
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  <p class="mb-4 text-lg">
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+ MoA Chat is optimized for <strong>Hugging Face Spaces</strong> or any platform supporting Python 3.11+, Flask, and Docker containers.
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  </p>
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  <p class="text-lg">
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+ API keys should be stored securely using Hugging Face's <strong>Secrets</strong> system.
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  </p>
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  </section>
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  <h2 class="text-2xl font-semibold mb-4 text-blue">File Structure</h2>
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  <ul class="list-disc ml-6 text-lg">
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  <li><code>app.py</code> — Flask backend server.</li>
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+ <li><code>llm/agents.py</code> — Core querying and aggregation logic.</li>
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+ <li><code>llm/model_config.json</code> — Configures models and providers.</li>
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  <li><code>templates/</code> — Contains <code>index.html</code> and <code>docs.html</code>.</li>
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  <li><code>static/</code> — Contains <code>style.css</code> and <code>script.js</code>.</li>
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  </ul>
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  </section>
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  <section class="mb-10">
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+ <h2 class="text-2xl font-semibold mb-4 text-blue">Credits and License</h2>
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+ <p class="mb-4 text-lg">
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+ Inspired by <a href="https://github.com/togethercomputer/MoA" class="text-blue underline hover:text-purple" target="_blank">Together Computer's MoA project</a>.
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+ </p>
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+ <p class="mb-4 text-lg">
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+ This project is based on the concept of collaborative AI agents.
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+ </p>
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+ <p class="text-lg">
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+ Together Computer's original project is licensed under the <strong>Apache 2.0 License</strong>.
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+ </p>
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  </section>
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  </div>
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+ <div class="text-center mt-8 space-x-4">
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  <a href="/" class="px-6 py-2 bg-blue text-fg0 rounded hover:bg-purple transition text-lg font-semibold">← Back to Chat</a>
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+ <a href="https://github.com/togethercomputer/MoA" target="_blank" class="px-6 py-2 bg-blue text-fg0 rounded hover:bg-purple transition text-lg font-semibold">GitHub</a>
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  </div>
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  <script>