Update README.md

README.md

@@ -29,7 +29,7 @@ ReadRight uses a modular setup with Gradio Spaces API and smolagents to deliver
 
 1. **Story Creation and Audio**:
    - Students enter their name, grade, and a topic they like through a simple Gradio interface.
-   - **Story Generation Agent**: Powered by Google Gemini and smolagents’ tool-calling features, this agent crafts engaging, personalized stories tailored to the student’s grade and interests. It automatically adjusts story length, vocabulary, and complexity—for example, using simple words for younger kids or richer sentences for older ones—making smart choices about content without needing extra user input.
+   - **Story Generation Agent**: Powered by LLM(can be any) and smolagents’ tool-calling features, this agent crafts engaging, personalized stories tailored to the student’s grade and interests. It automatically adjusts story length, vocabulary, and complexity—for example, using simple words for younger kids or richer sentences for older ones—making smart choices about content without needing extra user input.
    - **Audio Creation**: Hugging Face TTS (NihalGazi/Text-To-Speech-Unlimited) turns stories into natural-sounding audio to guide pronunciation.
    
    **This phase starts with user input, but the story agent works autonomously to shape the content.**
@@ -41,7 +41,8 @@ ReadRight uses a modular setup with Gradio Spaces API and smolagents to deliver
      - **Feedback Agent**: The LLM generates friendly, detailed feedback with pronunciation tips tailored to the student’s performance. It also decides when to create new stories that focus on words the student found tricky, forming a loop where it adapts content based on performance without needing extra user prompts.
    - This phase shines as a multi-step agent, with the LLM analyzing data and choosing next steps to create a personalized learning path.
 
-Together, these phases form a semi-autonomous system: story creation starts with user input but uses an agent to craft tailored content, while the feedback phase is highly agentic, dynamically adjusting to each student’s needs. This makes ReadRight a strong showcase of AI-driven education with smolagents.
+Together, these phases form a semi-autonomous system: story creation starts with user input but uses an agent to craft tailored content, while the feedback phase is highly agentic, dynamically adjusting to each student’s needs. 
+
 
 ## 🎥 Demo
 📺 [Watch the ReadRight Demo Video](#) *(Link to be added)*