docs(tutorials): add comprehensive tutorial for Vectara Chat (#462)

[sergioprica]

Closes #462
/claim #462

Summary

Adds a comprehensive, original developer tutorial for Vectara Chat (tutorials/en/crafting-a-comprehensive-tutorial-for-vectara-chat.mdx) following all requirements in #462 and the lablab.ai Tutorial Guidelines.

Sections Covered

• Introduction to Vectara Chat: Grounded Generation architecture, native multi-turn conversational memory (conversationId / turnId), and comparison against stateless RAG pipelines.
• Getting Started with Vectara Chat: Workspace & corpus setup, metadata filter attributes, environment setup, and Python document indexing script (/v1/index).
• Building a Chatbot with Vectara: Complete VectaraChatClient implementation with multi-turn session persistence, context window configuration, and inline citation extraction (/v1/query).
• Enhancing Chatbot Intelligence: Hybrid search lexical interpolation (lambda), Maximal Marginal Relevance (rerankerId: 272725718, diversityBias), and hallucination detection via the Hughes Hallucination Evaluation Model (HHEM) / Factual Consistency Score (factualConsistencyScore: True).
• Deploying and Testing Chatbots: Interactive Streamlit application with live retrieval/grounding controls plus an automated multi-turn & FCS smoke test suite.
• Conclusion and Tips for Hackathon Participants on Use Cases for the Models: Practical advice for lablab.ai hackathon teams and links to both required Vectara tutorials (Vectara Beginner App Tutorial and Vectara Advanced App Tutorial).