Xpersona

Crawler Summary

agentic-ai-learning-series answer-first brief

A 7-part practical notebook series exploring LLMs, RAG, LangChain, CrewAI, LlamaIndex & real-time multi-agent systems. 🚀 **Agentic AI Learning Series** *A complete 7-part practical notebook series on LLMs, RAG, LangChain, CrewAI & Multi-Agent Systems.* <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue" /> <img src="https://img.shields.io/badge/Google%20Gemini-API-orange" /> <img src="https://img.shields.io/badge/LangChain-Framework-green" /> <img src="https://img.shields.io/badge/LangGraph-Workflows-purpl Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 4/16/2026.

Freshness

Last checked 4/16/2026

Best For

agentic-ai-learning-series is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGitHubSafety: 66/100

agentic-ai-learning-series

A 7-part practical notebook series exploring LLMs, RAG, LangChain, CrewAI, LlamaIndex & real-time multi-agent systems. 🚀 **Agentic AI Learning Series** *A complete 7-part practical notebook series on LLMs, RAG, LangChain, CrewAI & Multi-Agent Systems.* <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue" /> <img src="https://img.shields.io/badge/Google%20Gemini-API-orange" /> <img src="https://img.shields.io/badge/LangChain-Framework-green" /> <img src="https://img.shields.io/badge/LangGraph-Workflows-purpl

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Apr 16, 2026

Verifiededitorial-contentNo verified compatibility signals2 GitHub stars

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 4/16/2026.

2 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 16, 2026

Vendor

Narasimha Kambham

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 4/16/2026.

View Source

Setup snapshot

git clone https://github.com/Narasimha-kambham/agentic-ai-learning-series.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 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.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Narasimha Kambham

profilemedium
Observed Apr 16, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 16, 2026Source linkProvenance
Adoption (1)

Adoption signal

2 GitHub stars

profilemedium
Observed Apr 16, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

1

Snippets

0

Languages

python

Executable Examples

bash

git clone https://github.com/your-username/agentic-ai-learning-series.git
cd agentic-ai-learning-series

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

A 7-part practical notebook series exploring LLMs, RAG, LangChain, CrewAI, LlamaIndex & real-time multi-agent systems. 🚀 **Agentic AI Learning Series** *A complete 7-part practical notebook series on LLMs, RAG, LangChain, CrewAI & Multi-Agent Systems.* <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue" /> <img src="https://img.shields.io/badge/Google%20Gemini-API-orange" /> <img src="https://img.shields.io/badge/LangChain-Framework-green" /> <img src="https://img.shields.io/badge/LangGraph-Workflows-purpl

Full README

🚀 Agentic AI Learning Series

A complete 7-part practical notebook series on LLMs, RAG, LangChain, CrewAI & Multi-Agent Systems.

<p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue" /> <img src="https://img.shields.io/badge/Google%20Gemini-API-orange" /> <img src="https://img.shields.io/badge/LangChain-Framework-green" /> <img src="https://img.shields.io/badge/LangGraph-Workflows-purple" /> <img src="https://img.shields.io/badge/CrewAI-Multi--Agent-red" /> <img src="https://img.shields.io/badge/LlamaIndex-RAG-lightgrey" /> <img src="https://img.shields.io/badge/ChromaDB-Vector%20DB-yellow" /> <img src="https://img.shields.io/badge/Firecrawl-Web%20Search%20%26%20Scrape-brightgreen" /> </p>

A fully hands-on notebook collection designed to help you learn, build, and experiment with modern AI tools and agentic workflows. From basic LLM calls → to RAG → to multi-agent orchestration → to real-time news pipelines, this series offers a clear progression of concepts and real applications.

📘 📚 Notebook Series Overview

| No. | Notebook Title | Description | | ----- | ------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | | 1 | Gemini + LangChain Essentials | Learn LLM calls, prompts, output parsers, chains, and a mini-RAG workflow. | | 2 | RAG Essentials | Build RAG from scratch: loading PDFs, chunking, embeddings, ChromaDB, RetrievalQA. | | 3 | LangChain + LangGraph Agents | Tools, search, multi-step reasoning, memory, chatbot flows & agent pipelines. | | 4 | Career Agent (Project) | Resume parsing → job search → job–candidate matching → cover letter generation. | | 5 | LlamaIndex Basics | A lightweight intro to LlamaIndex concepts + 5-line RAG demo. | | 6 | CrewAI Essentials | Multi-agent systems, tasks, memory, variables, custom embedders & sequential crews. | | 7 | NewsVista – Real-Time Information Extraction System | Firecrawl search → scrape → summarize using structured multi-agent workflows. (Most advanced & practical notebook.) |

⚙️ Tech Stack Used

  • Python
  • LangChain
  • LangGraph
  • CrewAI
  • LlamaIndex
  • Gemini API
  • Groq / OpenAI (Optional)
  • SentenceTransformer Embeddings
  • ChromaDB
  • Firecrawl Search & Scrape Tools

🔧 How to Use the Notebooks

1. Clone the Repository

git clone https://github.com/your-username/agentic-ai-learning-series.git
cd agentic-ai-learning-series

2. Open in Google Colab or Jupyter

All notebooks are .ipynb, so you can run them in:

  • Google Colab
  • Jupyter Notebook
  • VS Code (Jupyter extension)

Each notebook includes its own dependencies inside the first cell.

🔑 API Keys Required

Depending on the notebook, you may need:

  • Gemini API Key
  • Tavily Search API Key
  • (Optional) Groq or OpenAI key for model switching
  • (Optional) HuggingFace key, but only if using HF inference (most notebooks use local embeddings)

🧠 What You Will Learn Across This Series

  • LLM prompting & structured outputs
  • RAG pipelines & vector databases
  • Tool calling & agent reasoning
  • LangGraph workflows & memory states
  • CrewAI multi-agent orchestration
  • Real-world automation pipelines
  • Using search engines & scrapers with LLMs
  • Building production-like AI systems

🧩 Projects Built Using This Series

Here are practical projects you can build (or extend) using the concepts from these notebooks:

🔹 1. NewsVista – Real-Time Information Extraction System

A multi-agent pipeline using Firecrawl tools to search → scrape → summarize articles.

🔹 2. Career Agent – AI Job Assistant

Parses resumes, searches job listings, matches candidate profiles, and generates personalized cover letters.

🔹 3. Mini RAG Chatbot

Using Notebook 1 & 2:

  • Load PDFs
  • Embed with Gemini
  • Build a RetrievalQA chatbot

🔹 4. Multi-Agent Writer System

Using CrewAI:

  • Research agent → Writer agent → Editor agent
  • Great for blogs, reports, and newsletters.

🔹 5. Document Insights Engine

Using RAG + LangGraph:

  • Upload any document
  • Retrieve sections
  • Summarize per section
  • Multi-step reasoning

🔹 6. Custom Tool Calling Agent

Using LangChain Agent + Tavily Search:

  • Search → Filter → Answer
  • Useful for fact-checking and research assistants.

🏆 Why This Series Exists

This entire notebook series was created as part of a learning journey — breaking down complex AI concepts into practical, runnable code examples, making it easier for anyone to understand modern AI engineering.

If you're a beginner or intermediate developer, these notebooks will help you:

  • Understand HOW everything works
  • See WHY certain patterns are used
  • Build your own agentic workflows step by step

❤️ Final Note

If you’ve taken the time to read through these notebooks — thank you for your patience and curiosity.

Learning agentic AI takes time and experimentation. Take a moment and pat yourself on the back. You earned it.

These notebooks are meant to be understood, not blindly copy–pasted. Take small snippets, try them in your own apps, ask your favorite AI model (ChatGPT, Gemini, Perplexity, Groq), and keep exploring.

If you ever want to go beyond code-based agents, try no-code agent tools like n8n, Zapier, Make, or Flowise.

Keep building. The best things are in front of you. 🚀

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/snapshot"
curl -s "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/contract"
curl -s "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Agent hubMore from this sourceOpenClaw agents
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T00:05:19.794Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "label": "Vendor",
    "value": "Narasimha Kambham",
    "category": "vendor",
    "href": "https://github.com/Narasimha-kambham/agentic-ai-learning-series",
    "sourceUrl": "https://github.com/Narasimha-kambham/agentic-ai-learning-series",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:53.884Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:53.884Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "traction",
    "label": "Adoption signal",
    "value": "2 GitHub stars",
    "category": "adoption",
    "href": "https://github.com/Narasimha-kambham/agentic-ai-learning-series",
    "sourceUrl": "https://github.com/Narasimha-kambham/agentic-ai-learning-series",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:53.884Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-narasimha-kambham-agentic-ai-learning-series/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true,
    "metadata": {}
  }
]

Sponsored

Ads related to agentic-ai-learning-series and adjacent AI workflows.