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Agentic Website Scraping using Firecrawl: How to Setup Locally? 🔥 Integrate with @LangChainAI LlamaIndex 🦙 🤖 AI Agent Integration PraisonAI 🌐 Set up locally Docker 📊 Data Processing Automation Llama 3 LLM Groq Inc 🔄 Search @yousearchengine Mendable @firecrawl_dev Subscribe: YT:

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Mervin Praison

10,733 subscribers

20,909 görüntüleme • 2 yıl önce •via X (Twitter)

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Nicolas Camara profil fotoğrafı
Nicolas Camara2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev 🔥🔥🔥

Eric Ciarla profil fotoğrafı
Eric Ciarla2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev Great work @MervinPraison!

Adam Silverman (Hiring!) 🖇️ profil fotoğrafı
Adam Silverman (Hiring!) 🖇️2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev Awesome

Happy profil fotoğrafı
Happy2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev like

Essa Mamdani profil fotoğrafı
Essa Mamdani2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev Use free opensource for crawling.

Дмитрий Суриков profil fotoğrafı
Дмитрий Суриков2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev AI + Web3 = Innovation! 🚀🌐 @magnetaixyz @din_lol_ GODIN

Igor Andreichenk profil fotoğrafı
Igor Andreichenk2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev Your AI, your profit! 💰🤖 @magnetaixyz @din_lol_ GODIN

NONAME❤️ WELL3 profil fotoğrafı
NONAME❤️ WELL32 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev ModelFi: The AI game-changer! 🎮💫 @magnetaixyz @din_lol_ GODIN

Ninew💙NOYA.ai profil fotoğrafı
Ninew💙NOYA.ai2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev 🔥 Web3Go who? It's all about DIN now! Go @din_lol_ $ARCA

Mercury.fi profil fotoğrafı
Mercury.fi2 yıl önce

@LangChainAI @llama_index @PraisonAI @Docker @GroqInc @yousearchengine @mendableai @firecrawl_dev AI + Web3 = Innovation! 🚀🌐 @magnetaixyz @din_lol_ GODIN

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How to Fine Tune Llama 3 for Better Instruction Following? 🚀 Setup Environment 📊 Train Model 💾 Save Model Locally 🌐 Upload Model to Hugging Face 📈 Evaluate Performance 🛠 Using 🦥 Unsloth AI Subscribe: YT: Meta AI at Meta Daniel Han
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🔥 Introducing Praison AI Create & Publish Multiple AI Agents with Just 4 commands 📦 pip install praisonai 🔑 export OPENAI_API_KEY=xxxxxxxx 🚀 praisonai --init Create a Movie Script about Lion 🛠️ praisonai Deploy 🚢 praisonai --deploy Subscribe: YT: Also using ollama Groq Inc #crewai AutoGen João Moura
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INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with LlamaIndex 🦙 To connect your agents with more tools like Gmail, use
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INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with LlamaIndex 🦙 To connect your agents with more tools like Gmail, use

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INSANE: Grok 3 + Replit Agent is a Superpower!! Using the pair, I built an AI agent that reviews my Pull Requests Here's the flow: • Grok 3 generates PR-reviewing agent code using Composio + LlamaIndex • Replit Agent automatically crafts the front-end interface • Get a ready-to-run workflow where you paste the url to your PR, and the agent generates a code review instantly with suggestions. Built with Grok Replit ⠕ Agent Powered by LlamaIndex 🦙 Groq Inc repl link:
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INSANE: Grok 3 + Replit Agent is a Superpower!! Using the pair, I built an AI agent that reviews my Pull Requests Here's the flow: • Grok 3 generates PR-reviewing agent code using Composio + LlamaIndex • Replit Agent automatically crafts the front-end interface • Get a ready-to-run workflow where you paste the url to your PR, and the agent generates a code review instantly with suggestions. Built with Grok Replit ⠕ Agent Powered by LlamaIndex 🦙 Groq Inc repl link:

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Build a local LLM app with RAG to chat with Google Drive data using Mistral or Llama-3 running locally on your computer without wiring a single line of Python Code (100% free and without internet):
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Build a local LLM app with RAG to chat with Google Drive data using Mistral or Llama-3 running locally on your computer without wiring a single line of Python Code (100% free and without internet):

Shubham Saboo

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create-llama is now also the easiest way to get started with multi-agents using LlamaIndex 🦙 v0.2 adds multi-agents using LlamaIndex Workflows. Create a multi-agent chat UI like the one below in a single command line! 🖥️ $ npx create-llama 📄
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create-llama is now also the easiest way to get started with multi-agents using LlamaIndex 🦙 v0.2 adds multi-agents using LlamaIndex Workflows. Create a multi-agent chat UI like the one below in a single command line! 🖥️ $ npx create-llama 📄

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Transforming Invoice Data into JSON: Local LLM with LlamaIndex & Pydantic 🚀 Complete video: Code: I explain how to get structured JSON output with LlamaIndex and dynamic Pydantic class. This helps to implement the use case of data extraction from invoice documents. The solution runs on the local machine, thanks to Ollama. I'm using a MacBook Air M1 with 8GB RAM. LlamaIndex 🦙 Pydantic ollama #Python #LLM #RAG
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Transforming Invoice Data into JSON: Local LLM with LlamaIndex & Pydantic 🚀 Complete video: Code: I explain how to get structured JSON output with LlamaIndex and dynamic Pydantic class. This helps to implement the use case of data extraction from invoice documents. The solution runs on the local machine, thanks to Ollama. I'm using a MacBook Air M1 with 8GB RAM. LlamaIndex 🦙 Pydantic ollama #Python #LLM #RAG

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Introducing Repetitive AI Agents PraisonAI 🤖 Automates Thousand's of Tasks Instantly ⚡ Few Lines of Code 🔄 Handles Repetitive Tasks Automatically ⏱️ Sequential Task Execution 🔌 Integreate ollama Groq Inc Code below 👇 RT Please

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15,272 görüntüleme • 1 yıl önce

How to run LLMs locally in 1 minute [beginner-friendly] using ollama 🦙 and hugging face 🤗
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Let's create an AI tour planner agent using LlamaIndex 🦙 workflows 🔥 GitHub: Stacks used: - LlamaIndex workflow for orchestration - SerpAPI for finding flights, hotels etc. Full tutorial 👇
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Let's create an AI tour planner agent using LlamaIndex 🦙 workflows 🔥 GitHub: Stacks used: - LlamaIndex workflow for orchestration - SerpAPI for finding flights, hotels etc. Full tutorial 👇

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Llama 4 voice agent starter kit with Groq Inc and Pipecat AI ➡️ Groq STT (distil-whisper-large-v3) ➡️ Groq Llama 4 (llama-4-scout-17b-16e-instruct) ➡️ Groq TTS (playai-tts) ➡️ Function calling ➡️ Deploy to Pipecat Cloud for production ➡️ Optionally add a twilio phone number for telephone voice AI

kwindla

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Introducing LLaMA voice chat! 🦙 You can run this locally on an M1 Pro
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Introducing LLaMA voice chat! 🦙 You can run this locally on an M1 Pro

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Announcing Open Lovable 🔥 We've built an open-source AI web app builder that can transform any website URL into a working, editable clone, giving you a foundation to build on instantly. All powered by Groq Inc, E2B, and Firecrawl.

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I built an automated AI competitor analyis team with multi-agents. It has 3 AI agents working together as a team: 1. Data Extraction Agent using Firecrawl 2. Analyst Agent using OpenAI GPT-4o 3. Competitor Research Agent using Perplexity AI or Exa AI 100% Opensource code.

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Another example of the multiple TTS parallel pipelines pattern. Here's a voice AI agent that speaks both English and Arabic, using a specific model/voice for each language. These are PlayAI voices. The STT, TTS, and LLM inference is all running on Groq Inc. (The LLM is LLama 4 Maverick.)
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Another example of the multiple TTS parallel pipelines pattern. Here's a voice AI agent that speaks both English and Arabic, using a specific model/voice for each language. These are PlayAI voices. The STT, TTS, and LLM inference is all running on Groq Inc. (The LLM is LLama 4 Maverick.)

kwindla

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Just created Grok 3 AI Customer Support Agents 🔥 🤖 Grok 3 reads docs & builds the agent Elon Musk 🔍 DeepSearch for In-depth search ⚡ Flask web app + API setup 🚀 Browser-based deploy - Replit ⠕ Amjad Masad ✨ Zero manual coding needed PraisonAI Step-by-Step Tutorial: 👇
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Just created Grok 3 AI Customer Support Agents 🔥 🤖 Grok 3 reads docs & builds the agent Elon Musk 🔍 DeepSearch for In-depth search ⚡ Flask web app + API setup 🚀 Browser-based deploy - Replit ⠕ Amjad Masad ✨ Zero manual coding needed PraisonAI Step-by-Step Tutorial: 👇

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