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shriyansnaik/README.md

Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio · LinkedIn · Email

I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval, and multi-agent platforms that run in production. Currently working on an agentic compliance platform at Big Language Solutions. Previously Swiggy (founding AI engineer on CREW, a chat-based concierge platform), National Stock Exchange, and Jio Platforms.

Mumbai, India.

Minions

PyPIPython versions

minion-ai is an agentic framework I wrote because every other one made me bolt observability on separately, and the good answer was always a paid hosted service. Here, tracing of every run, turn and tool call, plus per-model cost tracking, is one flag.

importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))

A tool is a plain function; its signature and docstring are the schema. Traces go to a local SQLite file you own, with a dashboard you run yourself (minion serve) and spend roll-ups across a 145-model price table. Sub-agents, parallel tool calls, and a strict JSON envelope per turn that keeps agents portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.

It runs the entire agent layer of the compliance platform at work, all 25 agents.

Docs · Quickstart · Cookbook

Currently

  • Working into the agents, evals and RL-environments side of open source, starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0

Selected work

minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.

Toolbelt

Languages Python · Go · SQL · JavaScript

LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals

Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic

Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake

Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned Loading

  1. minion-aiminion-aiPublic

    A simple agentic framework - observability, evals, memory all in one

    Python 4

  2. linkedin-feed-parserlinkedin-feed-parserPublic

    Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
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(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
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btn.textContent = 'Copy';
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navigator.clipboard.writeText(codeBlock.textContent).then(function() {
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observer.observe(document.body, { childList: true, subtree: true });
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
shriyansnaik (Shriyans Naik) · GitHub
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Highlights
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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
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var style = document.createElement('style');
style.textContent = '
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color-scheme: dark light;
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})();
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
shriyansnaik (Shriyans Naik) · GitHub
Skip to content
View shriyansnaik's full-sized avatar
6
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 · 3
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Achievements
Achievement: Pull Shark
Achievements
Achievement: Pull Shark
Highlights
  • 
Pro


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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
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if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
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var found = false;
terms.forEach(function(term) {
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found = true;
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if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
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});
});
observer.observe(document.body, { childList: true, subtree: true });
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
shriyansnaik (Shriyans Naik) · GitHub
Skip to content
View shriyansnaik's full-sized avatar
6
followers
 · 3
following

Achievements
Achievement: Pull Shark
Achievements
Achievement: Pull Shark
Highlights
  • 
Pro


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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
shriyansnaik (Shriyans Naik) · GitHub
Skip to content
View shriyansnaik's full-sized avatar
6
followers
 · 3
following

Achievements
Achievement: Pull Shark
Achievements
Achievement: Pull Shark
Highlights
  • 
Pro


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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
shriyansnaik (Shriyans Naik) · GitHub
Skip to content
View shriyansnaik's full-sized avatar
6
followers
 · 3
following

Achievements
Achievement: Pull Shark
Achievements
Achievement: Pull Shark
Highlights
  • 
Pro


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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
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A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
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function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
shriyansnaik (Shriyans Naik) · GitHub
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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
shriyansnaik (Shriyans Naik) · GitHub
Skip to content
View shriyansnaik's full-sized avatar
6
followers
 · 3
following

Achievements
Achievement: Pull Shark
Achievements
Achievement: Pull Shark
Highlights
  • 
Pro


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shriyansnaik/README.md
Shriyans Naik

AI Engineer · LLM and agentic systems

Portfolio ·
LinkedIn ·
Email
I build LLM systems end to end: QLoRA fine-tuning and vLLM serving, retrieval,
and multi-agent platforms that run in production. Currently working on an
agentic compliance platform at Big Language Solutions. Previously Swiggy
(founding AI engineer on CREW, a chat-based concierge platform), National Stock
Exchange, and Jio Platforms.
Mumbai, India.
Minions
PyPIPython versions
minion-ai is an agentic
framework I wrote because every other one made me bolt observability on
separately, and the good answer was always a paid hosted service. Here, tracing
of every run, turn and tool call, plus per-model cost tracking, is one flag.
importminionsminions.init(tracing=True, project="demo")
agent=minions.Minion(model="openai/gpt-4o", tools=[get_weather])
print(agent("Should I take a jacket in Oslo today?"))
A tool is a plain function; its signature and docstring are the schema. Traces
go to a local SQLite file you own, with a dashboard you run yourself
(minion serve) and spend roll-ups across a 145-model price table. Sub-agents,
parallel tool calls, and a strict JSON envelope per turn that keeps agents
portable across OpenAI, Anthropic, Gemini, Azure and vLLM through LiteLLM.
It runs the entire agent layer of the compliance platform at work, all 25 agents.
Docs ·
Quickstart ·
Cookbook
Currently
  • Working into the agents, evals and RL-environments side of open source,
starting with PrimeIntellect-ai/verifiers
  • Pushing Minions toward a 1.0
Selected work
minion-aiAgentic framework with tracing, cost tracking and a self-hosted dashboard. On PyPI.
multimodal_ragRAG over PDFs that indexes figures as well as text, by summarising every extracted image and embedding it alongside the prose.
linkedin-feed-parserChrome extension that turns LinkedIn job posts into structured cards via LLM extraction, and drafts the outreach email.
shribookEvent finance tracking for singing groups. React, Firebase, role-based access, live here.
google-translate-apiSelenium driver for Google Translate behind a FastAPI wrapper. Chunking, 190+ languages, no official API.
Toolbelt
Languages Python · Go · SQL · JavaScript
LLM Agentic systems · MCP · RAG · Structured outputs · Fine-tuning (QLoRA, PEFT) · Evals
Frameworks LangGraph · DSPy · LiteLLM · vLLM · Ray · PyTorch · Transformers · FastAPI · Pydantic
Data Qdrant · Milvus · Elasticsearch · PostgreSQL · MongoDB · DynamoDB · Redis · Snowflake
Infra AWS · Azure · Docker · GitHub Actions · Langfuse · Grafana · Prometheus

Pinned
Loading
  1. minion-aiminion-aiPublic
    
A simple agentic framework - observability, evals, memory all in one

    Python
4

  2. linkedin-feed-parserlinkedin-feed-parserPublic
    
Chrome extension that parses LinkedIn job posts into clean cards with LLM extraction, flip-card UI, and Gmail email drafting

    JavaScript