# Technology

#### Agent Logs

The agent logs page shows the real-time chain of thought and goal-based actions taken by SAG3 Agent. Agent logs are the backbone of any self-respecting AI agent. They demonstrate beyond a shadow of a doubt that the tech actually exists and works.

<figure><img src="/files/4nmTcZPfm0E9I0TnilI4" alt=""><figcaption><p>SAG3.ai <a href="https://sag3.ai/agent-logs">Agent logs</a></p></figcaption></figure>

#### Core Components

1. **Research Engine**
   * Powered by Perplexity AI's sonar-pro model
   * Capable of collecting and organizing data from multiple sources
   * Source tracking and citation management
2. **Analysis Engine**
   * Utilizes DeepSeek's R1 reasoning model (hosted in USA)&#x20;
   * Structured data processing for interpretation and attribute scoring
   * Pattern recognition for strengths and weaknesses identification
3. **Tweet Generation System**
   * AI-driven content creation for social sharing
   * Context-aware messaging that incorporates cashtags or @ mentions
   * Tone consistency and brand alignment
4. **Image Processing Pipeline**
   * Automated creation of analysis summary images
   * Optimization for social media sharing
   * Thumbnail generation
5. **Scheduling System**
   * Automated queue management for social posts
   * Time optimization algorithms
   * Retry mechanisms for failed operations

#### Architecture

* **Frontend**: React-based web application with interactive components
* **Backend**: Supabase-powered database and Privy authentication
* **Edge Functions**: Serverless functions for AI operations and social media posting
* **Data Storage**: Secure storage for analysis results and user data

#### Integration Points

* **Twitter API**: For monitoring KOLs, posting analysis reports and hot takes
* **CoinGecko API**: For price and market data integration
* **Perplexity API**: For research data collection
* **Fireworks API**: For reasoning-based analysis processing
* **OpenAi API**: For generating context-aware research images

<figure><img src="/files/z3JgpQcWVhHyyqyfDj2S" alt=""><figcaption><p>Research image generated for <a href="https://sag3.ai/analyze?s=xpz6zz">Story Protocol</a></p></figcaption></figure>


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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://docs.sag3.ai/sag3-platform/images-and-media.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.