Github ReposUpdated 12h agoRank 70
AionUi
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!
MCPOPENCLAW
Crawler Summary
Agentic-AI answer-first brief
A beginner-friendly implementation of Agentic AI using CrewAI, Ollama, and Llama 3.2 for multi-agent research and report generation. 🤖 Agentic AI Lab A hands-on implementation of an **Agentic AI workflow** using **CrewAI**, **Ollama**, and **Llama 3.2**. This project demonstrates how multiple AI agents can collaborate to perform autonomous research and generate structured reports from a user-provided topic. Designed as a learning project, it showcases the fundamentals of **multi-agent systems**, **task orchestration**, and **local Large Language Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Freshness
Last checked 10/9/2026
Best For
Agentic-AI 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 REPOS, runtime-metrics, public facts pack
Agent DossierGITHUB REPOSSafety: 66/100
Agentic-AI
A beginner-friendly implementation of Agentic AI using CrewAI, Ollama, and Llama 3.2 for multi-agent research and report generation. 🤖 Agentic AI Lab A hands-on implementation of an **Agentic AI workflow** using **CrewAI**, **Ollama**, and **Llama 3.2**. This project demonstrates how multiple AI agents can collaborate to perform autonomous research and generate structured reports from a user-provided topic. Designed as a learning project, it showcases the fundamentals of **multi-agent systems**, **task orchestration**, and **local Large Language
OpenClawself-declared
Public facts
4
Change events
1
Artifacts
0
Freshness
Oct 9, 2026
Verifiededitorial-contentNo verified compatibility signals
Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Trust evidence available
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Oct 9, 2026
Vendor
Ashik Kumar3
Artifacts
0
Benchmarks
0
Last release
Unpublished
Executive Summary
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Setup snapshot
- 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.
Evidence Ledger
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor (1)
Vendor
Ashik Kumar3
profilemedium
Compatibility (1)
Protocol compatibility
OpenClaw
contractmedium
Security (1)
Handshake status
UNKNOWN
trustmedium
Integration (1)
Crawlable docs
6 indexed pages on the official domain
search_documentmedium
Release & Crawl Timeline
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Artifacts Archive
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
6
Snippets
0
Languages
python
Executable Examples
text
User Topic
│
▼
Researcher Agent
│
Gather Relevant Information
│
▼
Writer Agent
│
Generate Structured Report
│
▼
Final Responsetext
agentic-ai-lab/ │ ├── agentic_ai.ipynb ├── README.md └── requirements.txt
bash
git clone https://github.com/your-username/agentic-ai-lab.git cd agentic-ai-lab
bash
pip install crewai ollama
bash
https://ollama.com
bash
ollama pull llama3.2:1b
Docs & README
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB REPOS
Editorial quality
ready
A beginner-friendly implementation of Agentic AI using CrewAI, Ollama, and Llama 3.2 for multi-agent research and report generation. 🤖 Agentic AI Lab A hands-on implementation of an **Agentic AI workflow** using **CrewAI**, **Ollama**, and **Llama 3.2**. This project demonstrates how multiple AI agents can collaborate to perform autonomous research and generate structured reports from a user-provided topic. Designed as a learning project, it showcases the fundamentals of **multi-agent systems**, **task orchestration**, and **local Large Language
Full README
🤖 Agentic AI Lab
A hands-on implementation of an Agentic AI workflow using CrewAI, Ollama, and Llama 3.2. This project demonstrates how multiple AI agents can collaborate to perform autonomous research and generate structured reports from a user-provided topic.
Designed as a learning project, it showcases the fundamentals of multi-agent systems, task orchestration, and local Large Language Model (LLM) inference without relying on cloud APIs.
🚀 Features
- 🤖 Multi-agent collaboration using CrewAI
- 🔍 Autonomous research agent
- ✍️ Report generation using a dedicated writer agent
- 🧠 Local LLM inference with Ollama
- ⚡ Modular task orchestration
- 🔒 Fully offline execution
- 📓 Simple notebook-based implementation for learning
🛠️ Tech Stack
| Category | Technologies | |----------|--------------| | Language | Python | | Agent Framework | CrewAI | | LLM Runtime | Ollama | | Language Model | Llama 3.2 (1B) | | Development | Jupyter Notebook |
🏗️ System Architecture
User Topic
│
▼
Researcher Agent
│
Gather Relevant Information
│
▼
Writer Agent
│
Generate Structured Report
│
▼
Final Response
📂 Project Structure
agentic-ai-lab/
│
├── agentic_ai.ipynb
├── README.md
└── requirements.txt
⚙️ Installation
Clone the Repository
git clone https://github.com/your-username/agentic-ai-lab.git
cd agentic-ai-lab
Install Dependencies
pip install crewai ollama
Install Ollama
Download and install Ollama from the official website.
https://ollama.com
Pull the required model:
ollama pull llama3.2:1b
Start the Ollama server:
ollama serve
▶️ Running the Project
- Launch Jupyter Notebook.
jupyter notebook
- Open:
agentic_ai.ipynb
-
Run all notebook cells.
-
Provide a topic.
Example:
Artificial Intelligence in Healthcare
The agents automatically collaborate to research the topic and generate a concise report.
🔄 Workflow
Input Topic
│
▼
Researcher Agent
│
Collect Key Information
│
▼
Writer Agent
│
Generate Structured Report
│
▼
Final Output
🧠 How It Works
- The user provides a topic.
- CrewAI assigns the task to the Researcher Agent.
- The researcher gathers important information using the local LLM.
- The findings are passed to the Writer Agent.
- The writer produces a concise and structured report.
- The final response is displayed in the notebook.
📸 Example
Input
Topic: Agentic AI
Output
- Overview of Agentic AI
- Current trends
- Applications
- Benefits
- Challenges
- Concise summary
📚 Learning Objectives
This project demonstrates:
- Agentic AI fundamentals
- Multi-agent collaboration
- Task delegation and orchestration
- Local LLM inference using Ollama
- Prompt-driven AI workflows
- Modular AI application design
🎯 Future Enhancements
- 🌐 Web Search Integration
- 📄 Retrieval-Augmented Generation (RAG)
- 🧠 Long-term Agent Memory
- 🔧 Tool Calling Support
- 🤖 Multiple Specialized Agents
- 📊 Streamlit Web Interface
- 📑 PDF Report Export
- 🐳 Docker Deployment
💡 Potential Applications
- Research Assistant
- Market Trend Analysis
- Academic Report Generation
- Business Intelligence
- Knowledge Discovery
- AI Learning Platform
👨💻 Author
Ashik Kumar
AI/ML Engineer | Generative AI | Agentic AI | Deep Learning | Computer Vision
⭐ If you found this project useful, consider giving the repository a star.
Contract & API
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
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://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/trust"
Reliability & Benchmarks
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
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.
No screenshots, media assets, or demo links are available.
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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://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-10-10T07:39:03.677Z"
}
},
"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",
"category": "vendor",
"label": "Vendor",
"value": "Ashik Kumar3",
"href": "https://github.com/Ashik-kumar3/Agentic-AI",
"sourceUrl": "https://github.com/Ashik-kumar3/Agentic-AI",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T15:56:32.995Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-10-09T15:56:32.995Z",
"isPublic": true
},
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on 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
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ashik-kumar3-agentic-ai/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]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
}
]