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AbhaykoulΒ 
posted an update 1 day ago
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91
Shipped v0.1.2 of vtx β€” a minimalist coding agent for the terminal.

Most agentic CLIs ship 10k+ token system prompts. Vtx is ~2,200. Less prompt overhead means more room for your code in the model's context window.

Vtx is a from-scratch Python implementation of the design philosophy behind pi-mono β€” same principles, pure Python, no transpiled runtime.

What ships out of the box:

β†’ Textual TUI + headless CLI (vtx -p "fix the failing test")
β†’ 49 LLM provider gateways, all declared in a single provider.yaml
β†’ 5 core tools (read / edit / write / bash / find) plus web search and fetch
β†’ Session tree with compaction, handoff, and resume
β†’ AGENTS.md / CLAUDE.md auto-discovery
β†’ Skills system β€” drop SKILL.md files in .agents/skills/ and they become slash commands
β†’ Two OAuth flows (GitHub Copilot device flow, OpenAI Codex PKCE)
β†’ Two-mode permissions: prompt (default) or auto, with a safe-command allowlist

This release adds a proper extension system. Register new LLM-callable tools, intercept tool calls, hook lifecycle events, and add slash commands from a single register(api) function in a Python file under ~/.vtx/agent/extensions/. Extensions can override built-in tools by name and chain handler logic across subscribers.

Apache 2.0. uv tool install vtx-coding-agent and you're running.

GitHub: https://github.com/OEvortex/vtx-coding-agent
PyPI: https://pypi.org/project/vtx-coding-agent

Built in the open. Feedback, extensions, and PRs welcome.
AbhaykoulΒ 
posted an update 9 months ago
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3434
πŸš€ Ever dreamed of training your own Large Language Model from scratch? What if I told you it doesn't require a supercomputer or PhD in ML? 🀯

Introducing LLM Trainer - the educational framework that makes LLM training accessible to EVERYONE! Whether you're on a CPU-only laptop or scaling to distributed GPUs, we've got you covered. πŸ’»βž‘οΈπŸ–₯️

Why LLM Trainer? Because existing tools are either too simplistic (hiding the magic) or too complex (requiring expert knowledge). We bridge the gap with:

πŸŽ“ Educational transparency - every component built from scratch with clear code
πŸ’» CPU-first approach - start training immediately, no GPU needed
πŸ”§ Full customization - modify anything you want
πŸ“ˆ Seamless scaling - from laptop to cluster without code changes
🀝 HuggingFace integration - works with existing models & tokenizers

Key highlights:
βœ… Built-in tokenizers (BPE, WordPiece, HF wrappers)
βœ… Complete Transformer implementation from scratch
βœ… Optimized for CPU training
βœ… Advanced features: mixed precision, gradient checkpointing, multiple generation strategies
βœ… Comprehensive monitoring & metrics

Perfect for:
- Students learning transformers
- Researchers prototyping new ideas
- Developers building domain-specific models

Ready to train your first LLM? It's easier than you think!

πŸ”— Check it out: https://github.com/HelpingAI/llm-trainer
πŸ“š Docs: Getting Started Guide
πŸ’¬ Join the community: GitHub Discussions

#AI #MachineLearning #LLM #DeepLearning #OpenSource #Python #HuggingFace #NLP

Special thanks to HuggingFace and PyTorch teams for the amazing ecosystem! πŸ™
  • 1 reply
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AbhaykoulΒ 
posted an update 11 months ago
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4180
πŸš€ Dhanishtha-2.0-preview-0825 Is Here

The Intermediate Thinking Model just leveled up again.

With sharper reasoning, better tool use, and expanded capabilities, Dhanishtha-2.0-preview-0825 is now live and ready to impress.

🧠 What Makes Dhanishtha Special?
Unlike typical CoT models that only thinks one time, Dhanishtha thinks iteratively:

> Think β†’ Answer β†’ Rethink β†’ Improve β†’ Rethink again if needed.

πŸ”— Try it now: HelpingAI/Dhanishtha-2.0-preview-0825

πŸ”ž Dhanishtha NSFW Preview

For those exploring more expressive and immersive roleplay scenarios, we’re also releasing:

HelpingAI/Dhanishtha-nsfw
A specialized version tuned for adult-themed interactions and character-driven roleplay.

πŸ”— Explore it here: HelpingAI/Dhanishtha-nsfw

πŸ’¬ You can also try all of these live at chat.helpingai.co
  • 4 replies
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AbhaykoulΒ 
posted an update 11 months ago
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3171
πŸŽ‰ Dhanishtha-2.0-preview-0725 is Now Live

The Intermediate Thinking Model just got even better.
With the new update, Dhanishtha is now sharper, smarter, and trained further on tool use

🧠 What Makes Dhanishtha Different?
Unlike standard COT models that give one-shot responses, Dhanishtha thinks in layers:

> Think β†’ Answer β†’ Rethink β†’ Improve β†’ Rethink again if needed.

HelpingAI/Dhanishtha-2.0-preview-0725
AbhaykoulΒ 
posted an update 12 months ago
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3127
πŸŽ‰ Dhanishtha 2.0 Preview is Now Open Source!

The world's first Intermediate Thinking Model is now available to everyone!

Dhanishtha 2.0 Preview brings revolutionary intermediate thinking capabilities to the open-source community. Unlike traditional reasoning models that think once, Dhanishtha can think, answer, rethink, answer again, and continue rethinking as needed using multiple blocks between responses.

πŸš€ Key Features
- Intermediate thinking: Think β†’ Answer β†’ Rethink β†’ Answer β†’ Rethink if needed...
- Token efficient: Uses up to 79% fewer tokens than DeepSeek R1 on similar queries
- Transparent thinking: See the model's reasoning process in real-time
- Open source: Freely available for research and development


HelpingAI/Dhanishtha-2.0-preview
https://helpingai.co/chat
  • 2 replies
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AbhaykoulΒ 
posted an update 12 months ago
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4707
Introducing Dhanishtha 2.0: World's first Intermediate Thinking Model

Dhanishtha 2.0 is the world's first LLM designed to think between the responses. Unlike other Reasoning LLMs, which think just once.

Dhanishtha can think, rethink, self-evaluate, and refine in between responses using multiple <think> blocks.
This technique makes it Hinghlt Token efficient it Uses up to 79% fewer tokens than DeepSeek R1
---

You can try our model from: https://helpingai.co/chat
Also, we're gonna Open-Source Dhanistha on July 1st.

---
For Devs:
πŸ”‘ Get your API key at https://helpingai.co/dashboard
from HelpingAI import HAI  # pip install HelpingAI==1.1.1
from rich import print

hai = HAI(api_key="hl-***********************")

response = hai.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[{"role": "user", "content": "What is the value of ∫0∞π‘₯3/π‘₯βˆ’1𝑑π‘₯ ?"}],
    stream=True,
    hide_think=False # Hide or show models thinking
)

for chunk in response:
    print(chunk.choices[0].delta.content, end="", flush=True)
  • 2 replies
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AbhaykoulΒ 
posted an update over 1 year ago
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πŸ”₯ THE WAIT IS OVER... HAI-SER IS HERE! πŸ”₯

Yo fam, this ain't just another AI dropβ€” this is the FUTURE of emotional intelligence! πŸš€

Introducing HAI-SER, powered by Structured Emotional Reasoning (SER), the next-level AI that doesn’t just understand your wordsβ€”it feels you, analyzes your emotions, and helps you navigate life’s toughest moments. πŸ’‘

πŸ’₯ What makes HAI-SER a game-changer?
πŸ”Ή Emotional Vibe Check – Gets the mood, energy, and what’s really going on 🎭
πŸ”Ή Mind-State Analysis – Breaks down your thoughts, beliefs, and patterns 🀯
πŸ”Ή Root Cause Deep-Dive – Unpacks the WHY behind your emotions πŸ’‘
πŸ”Ή Impact Check – Sees how it’s affecting your life and mental health πŸ’”
πŸ”Ή Safety Check – Prioritizes your well-being and crisis management 🚨
πŸ”Ή Healing Game Plan – Custom strategies to help you bounce back πŸ’ͺ
πŸ”Ή Growth Potential – Turns struggles into opportunities for self-improvement πŸ“ˆ
πŸ”Ή How to Approach – Teaches you and others how to communicate and heal 🀝
πŸ”Ή Personalized Response – Not just generic adviceβ€”real talk, tailored to YOU πŸ’―

No more robotic AI responses. No more surface-level advice. HAI-SER gets deep, analyzing emotions with precision and giving real, actionable support.

This ain’t just AIβ€”this is your digital therapist, life coach, and hype squad all in one. Whether it’s mental health, career struggles, relationships, or personal growth, HAI-SER has your back.

πŸš€ The future of emotionally intelligent AI is HERE.
Are you ready? πŸ”₯πŸ’―

HelpingAI/HAI-SER
  • 5 replies
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AbhaykoulΒ 
posted an update over 1 year ago
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πŸ”₯ BIG ANNOUNCEMENT: THE HELPINGAI API IS LIVE! πŸ”₯

Yo, the moment you’ve all been waiting for is here! πŸš€ The HelpingAI API is now LIVE and ready to level up your projects! πŸ”₯ We’re bringing that next-level AI goodness straight to your fingertips. πŸ’―

No more waitingβ€” it’s time to build something epic! πŸ™Œ

From now on, you can integrate our cutting-edge AI models into your own applications, workflows, and everything in between. Whether you’re a developer, a creator, or just someone looking to make some serious moves, this is your chance to unlock the full potential of emotional intelligence and adaptive AI.

Check out the docs πŸ”₯ and let’s get to work! πŸš€

πŸ‘‰ Check out the docs and start building (https://helpingai.co/docs)
πŸ‘‰ Visit the HelpingAI website (https://helpingai.co/)
  • 6 replies
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AbhaykoulΒ 
posted an update almost 2 years ago
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Introducing HelpingAI2-9B, an emotionally intelligent LLM.
Model Link : https://huggingface.co/OEvortex/HelpingAI2-9B
Demo Link: https://huggingface.co/spaces/Abhaykoul/HelpingAI2

This model is part of the innovative HelpingAI series and it stands out for its ability to engage users with emotional understanding.

Key Features:
-----------------

* It gets 95.89 score on EQ Bench greather than all top notch LLMs, reflecting advanced emotional recognition.
* It gives responses in empathetic and supportive manner.

Must try our demo: https://huggingface.co/spaces/Abhaykoul/HelpingAI2
  • 1 reply
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AbhaykoulΒ 
posted an update about 2 years ago
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# HelpingAI 9B: Cutting Edge Emotionally Intelligent AI

If you have ever felt that AI not understand your emotions or you not get human like fell while taking to him than this blog is for you!
In this BlogPost we will be exploring [HelpingAI 9B](https://huggingface.co/spaces/Abhaykoul/HelpingAI-9B) is an Highly Emotionally Intelligent AI which beated all top notch ai like GPT4o, GPT4, Claude3 Opus on EQ-Bench.

## What is HelpingAI 9B?
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6612aedf09f16e7347dfa7e1/FrNhr3WhMhvvD-dNplHxZ.png)
HelpingAI-9B is the fine-tuned Llama2 model crafted for emotionally intelligent conversations. This model excels in empathetic engagement, offering understanding and support through dialogue spanning various topics and situations. Its goal is to serve as a supportive AI companion, adept at resonating with users' emotions and communication requirements.

## Method
We gathered a large volume of high-quality human chat data, which was then filtered and refined to create three types of datasets:
1. DPOΒ - Initially, we trained the AI on a substantial DPO dataset to grasp human conversation patterns, enabling it to discern which types of output to generate and which to avoid.
2. AlpacaΒ - Subsequently, we trained it on an Alpaca-type dataset to enhance its human-like responses.
3. SFTΒ - Finally, once the AI fully comprehended human interactions, we trained it on an SFT dataset to broaden its knowledge base.

## Evaluation

![By/KingNish/Banchmark/png](https://cdn-uploads.huggingface.co/production/uploads/6612aedf09f16e7347dfa7e1/xvS57q5kU9f3AX-O-al0k.png)

## Conclusion:
HelpingAI is a large step toward understanding human emoions and give response like them. It can help us lot in making AI better for NLP.
Thanks!

Model Link: - https://huggingface.co/OEvortex/HelpingAI-9B

Demo link: - https://huggingface.co/spaces/Abhaykoul/HelpingAI-9B
  • 9 replies
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SharryOGΒ 
updated a model about 2 years ago
AbhaykoulΒ 
posted an update about 2 years ago
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2903
Introduction to HelpingAI-3B-v2.1 and HelpingAI-3B-v2.2

These models are designed to engage in dialogues that are not only contextually relevant but also deeply empathetic, tailoring their responses to the emotional state and context of the user. With advanced emotional understanding capabilities, they can comfort, celebrate, and address complex feelings with a level of emotional nuance that is unparalleled in the AI domain.

Emotional Intelligence Capabilities

The core of these models lies in their emotional intelligence capabilities. They exhibit several key traits that enable them to respond emotionally resonant:

- Emotion recognition and validation: The models can identify and validate the emotions expressed by the user, ensuring that their responses are grounded in understanding.
- Empathetic perspective-taking: They are capable of taking the user's perspective, understanding their feelings, and responding with empathy.
- Generating emotionally supportive language: The models can generate language that is supportive and comforting, tailored to the user's emotional state.
- Contextual emotional attunement: They can adapt their communication style to match the emotional context of the conversation, ensuring relevance and appropriateness.
- Using appropriate tone, word choice, and emotional expression**: The models are adept at using the right tone, words, and emotional expressions to convey their messages effectively.

Examples of Emotionally Intelligent Responses

Let's take a look at how these models can adapt their communication style with emotional nuance:

- Comforting someone grieving: The models can offer empathetic responses, acknowledging the user's feelings and suggesting practical ways to cope with grief.
- Celebrating positive news: They can generate responses that are joyful and supportive, encouraging the user to enjoy their positive experiences.
OEvortex/HelpingAI-3B-v2.1
OEvortex/HelpingAI-3B-v2.2
SharryOGΒ 
updated a model about 2 years ago
AbhaykoulΒ 
updated a Space about 2 years ago