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Tales Of Puran

Project Description: Puran Story to Animation Generator This project is an AI-powered storytelling and animation system that transforms user prompts into narrated mythological stories and animated videos based on Hindu Puranic texts. The system uses a local Large Language Model (LLM) to generate context-aware stories with references from curated Puran datasets. It then converts these stories into visual scenes, generates images, adds voice narration, and compiles everything into a video animation. Key Features: 🧠 Domain-specific LLM trained on Hindu Purans πŸ” Semantic search (embeddings + vector DB) for accurate context retrieval ✍️ Story generation with citations 🎬 Automatic scene breakdown from story 🎨 AI-based image generation for each scene πŸ”Š Text-to-speech narration πŸŽ₯ Video creation using generated visuals + audio πŸ’» Interactive UI using Streamlit 🧩 Tech Stack: LLM: Local models via Ollama Embeddings: Sentence Transformers Vector DB: ChromaDB Image Generation: Diffusers (or Stable Diffusion) Audio: pyttsx3 / TTS Video: FFmpeg UI: Streamlit 🎯 Workflow: User Prompt β†’ Retrieve Context β†’ Generate Story β†’ Split into Scenes β†’ Generate Images β†’ Generate Voice β†’ Combine β†’ Video Output πŸ’‘ Purpose: The project aims to: Make ancient Puranic knowledge more engaging Combine AI + storytelling + visualization Provide an interactive learning and entertainment tool Project Description: Puran Story to Animation Generator This project is an AI-powered storytelling and animation system that transforms user prompts into narrated mythological stories and animated videos based on Hindu Puranic texts. The system uses a local Large Language Model (LLM) to generate context-aware stories with references from curated Puran datasets. It then converts these stories into visual scenes, gener

AIRAGchatbotpython

Rank

43

Safety

79

Updated

Oct 9, 2026

Source

GitLab

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor
Gitlabvendor Β· observed Oct 9, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/gitlab-public-projects-nir-p-parikh-group-tales-of-puran/snapshot"

Documentation

GitLab

1,506 characters of source documentation, loaded on request.

Machine-readable data

The same record, as JSON, for agents and crawlers.

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      "category": "vendor",
      "label": "Vendor",
      "value": "Gitlab",
      "href": "https://gitlab.com/nir.p.parikh-group/tales-of-puran",
      "sourceUrl": "https://gitlab.com/nir.p.parikh-group/tales-of-puran",
      "sourceType": "profile",
      "confidence": "medium",
      "observedAt": "2026-10-09T01:20:57.442Z",
      "isPublic": true
    },
    {
      "factKey": "handshake_status",
      "category": "security",
      "label": "Handshake status",
      "value": "UNKNOWN",
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      "sourceUrl": "https://www.xpersona.co/api/v1/agents/gitlab-public-projects-nir-p-parikh-group-tales-of-puran/trust",
      "sourceType": "trust",
      "confidence": "medium",
      "observedAt": null,
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  ],
  "events": []
}

Record generated Oct 9, 2026.

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