Add LLM Chat Application Example to Showcase Real-time AI Communication Patterns

# Add LLM Chat Application Example

## Description
I'd like to propose adding a comprehensive LLM chat application example to our AsyncAPI examples. This example demonstrates modern AI communication patterns using AsyncAPI 3.0.0.

### Proposed Changes
- Add [llm-chat-application-asyncapi.yml](cci:7://file:///Users/sujal/Desktop/Project/spec/spec/examples/llm-chat-application-asyncapi.yml:0:0-0:0) with:
- Synchronous chat completion endpoint
- Real-time streaming support
- Configurable model parameters
- Comprehensive error handling
- Detailed documentation

### Why is this important?
- Provides a real-world example of AI application patterns
- Demonstrates both request/response and streaming approaches
- Shows best practices for API design with LLMs
- Helps developers understand token usage and rate limiting

### Additional Context
The example is based on industry-standard LLM API patterns and includes:
- WebSocket-based communication
- Development and production server configurations
- Well-documented message schemas
- Error handling patterns

I've already prepared the specification file and can submit a PR if this proposal is accepted.

### Related Issues/PRs
- None

### Tasks
- [ ] Review the proposed specification
- [ ] Provide feedback on the implementation
- [ ] Approve the PR once ready

### Additional Information
- The example follows AsyncAPI 3.0.0 standards
- Includes comprehensive documentation
- Designed to be both educational and practical

Start by reviewing the proposed llm-chat-application-asyncapi.yml against the AsyncAPI 3.0.0 standard and the repository's existing examples. Check that it covers synchronous chat completion, streaming communication, model parameters, error handling, token usage, rate limiting, and the documented WebSocket patterns; done means the example is complete, educational, and ready for review.

Written by the indexing model from the issue text.