Somu Odia Vlogs

Somu Odia Vlogs This is Somu Nayak ଗାଁ ଛୁଆ, Jai Jagannath 🙏
Jai shree Ram 🙏

❤️
20/03/2026

❤️

31/01/2026

Jay jaganath reel part 5

19/01/2026

Raja ko samajh aa gaya…
power se nahi,
bhakti se hi Bhagwan aate hain 🙏

Jab sab kuch impossible lag raha tha,
tab Neel Madhab swapna mein aaye
aur sach ka raasta dikhaya.

Ye sirf ek lakdi nahi thi,
ye vishwas tha,
ye bhakti thi,
ye Jagannath ki leela thi.

Part 5 mein dekhiye —
kaise bina sena,
bina shakti,
sirf prem aur bhakti se
daru chal padi…

Jai Jagannath 🙏


[ ai, ai vlog, god vlog]

14/01/2026

❤️ Reel With God❤️😎

13/01/2026

Insaan aur haathi…
poori taakat lagayi,
phir bhi lakdi nahi hilli 😮





10/01/2026

Samudra se aayi wo lakdi…
aur raja ko mila sapne mein sandesh 😳
🌊🌳
Yeh kahani yahin nahi rukti…
Part 3 mein asli koshish shuru hoti hai.
🙏 Jai Jagannath 🔱




09/01/2026

Day 31 — LangChain starts here: from prompts to real applications.

Until now, we talked to models.
From today, we start building with them.

LangChain helps you:
• connect LLMs with your data
• manage prompts properly
• chain multiple steps together
• build real GenAI workflows

This is where GenAI moves from:
👉 “Ask a question”
to
👉 “Build a system.”

LangChain is not magic.
It’s a framework that brings structure to GenAI apps.

If you want to build:
• chatbots
• RAG systems
• AI agents
• tools around LLMs

LangChain is a good place to start.

Save this journey.
Like, share, and comment what you want to build with LangChain.

— Somu

[langchain basics, langchain introduction, genai application development, llm frameworks, building ai apps, prompt chaining, rag with langchain, ai workflows, genai developer journey, large language models, ai engineering roadmap]

08/01/2026

Jagannath Dham sirf ek mandir nahi…
yeh ek rahasya hai.
🙏
Part 2 mein pata chalega
lakdi kahan se aayi aur kyun itni khaas hai…
Jai Jagannath 🔱





❤️

07/01/2026

Day 30 — All Major AI Model Providers you should know as a GenAI Developer.

GenAI is not just one model.
It’s an ecosystem of model providers.

As a GenAI developer, you should know who provides what and why it matters.

Major model providers today:
• OpenAI → GPT models (text, vision, reasoning)
• Google → Gemini models (multimodal, search-integrated)
• Anthropic → Claude models (safety + long context)
• Meta → LLaMA models (open-source ecosystem)
• Mistral → lightweight & efficient open models
• Cohere → enterprise-focused NLP models
• Hugging Face → model hub + open research

Each provider has strengths:
• cost
• context length
• speed
• openness
• enterprise readiness

You don’t “marry” one model.
You choose based on the problem.

That’s real GenAI engineering.

Save this journey.
Like, share, and comment which model you’ve used or want to explore.

— Somu

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