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Ashpreet Bedi

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Agents with gpt-4o from scratch 🔥 in 11 minutes we'll build: 🌎 Web Search Agent (2:40) 📈 Finance Agent (3:30) 🫡 Hackernews Agent (5:50) 📊 Data Analysis Agent (8:10) 🗒️ Research Agent (9:35) code:

Agents with gpt-4o from scratch 🔥 in 11 minutes we'll build: 🌎 Web Search Agent (2:40) 📈 Finance Agent (3:30) 🫡 Hackernews Agent (5:50) 📊 Data Analysis Agent (8:10) 🗒️ Research Agent (9:35) code:

697,323 просмотров • 2 лет назад

Phidata is now Agno. Announcing our new brand identity and the fastest way to build multi-modal Agents.

202,494 просмотров • 1 год назад

Building the LLM OS by Andrej Karpathy with gpt-4o The speed + quality is 🔥🤯 code:

Building the LLM OS by Andrej Karpathy with gpt-4o The speed + quality is 🔥🤯 code:

251,567 просмотров • 2 лет назад

This was a great read. So I started building an open-source data agent with 6 layers of context: 1. Table usage 2. Human annotations 3. Query patterns 4. Institutional knowledge 5. Memory 6. Runtime context Early version if you want to follow along:

This was a great read. So I started building an open-source data agent with 6 layers of context: 1. Table usage 2. Human annotations 3. Query patterns 4. Institutional knowledge 5. Memory 6. Runtime context Early version if you want to follow along:

51,251 просмотров • 5 месяцев назад

Generate dashboards on-demand using agents Agents can now generate beautiful, just-in-time dashboards. Dynamic software is the future

Generate dashboards on-demand using agents Agents can now generate beautiful, just-in-time dashboards. Dynamic software is the future

28,308 просмотров • 2 месяцев назад

Lets build `Auto-RAG` where we let the LLM pull the data it needs from different sources. 🔎 The user asks a question. 🤔 LLM decides whether to search its knowledge, memory, internet or make an API call. ✍️ LLM answers with the context. Code:

Lets build `Auto-RAG` where we let the LLM pull the data it needs from different sources. 🔎 The user asks a question. 🤔 LLM decides whether to search its knowledge, memory, internet or make an API call. ✍️ LLM answers with the context. Code:

174,580 просмотров • 2 лет назад

🌶️ Hot take: The only way Autonomous Multi-Agent Systems work is by adding Reasoning & Agentic Context. I've tried it all, and here are my learnings👇

🌶️ Hot take: The only way Autonomous Multi-Agent Systems work is by adding Reasoning & Agentic Context. I've tried it all, and here are my learnings👇

91,445 просмотров • 1 год назад

🚀 Say hello to the new & improved phidata 🚀 Build, ship, and monitor Agents with blazing-fast memory, knowledge, tools & reasoning 🔥 ⚡️ 70% faster memory & knowledge 🛠 100+ tools 🧠 Reasoning Agents 🤝 Multi-agent collaboration 📊 Built-in monitoring and Agent UI

🚀 Say hello to the new & improved phidata 🚀 Build, ship, and monitor Agents with blazing-fast memory, knowledge, tools & reasoning 🔥 ⚡️ 70% faster memory & knowledge 🛠 100+ tools 🧠 Reasoning Agents 🤝 Multi-agent collaboration 📊 Built-in monitoring and Agent UI

114,568 просмотров • 1 год назад

Prompt In → Video Out Introducing Vibe-Video: a multi-agent team that turns curiosity into motion-graphics videos. Built with HeyGen Hyperframes and Opus 4.7 Researches topics via Parallel Web Systems, explains GitHub repos, renders the result. Free and open-source ↓

Prompt In → Video Out Introducing Vibe-Video: a multi-agent team that turns curiosity into motion-graphics videos. Built with HeyGen Hyperframes and Opus 4.7 Researches topics via Parallel Web Systems, explains GitHub repos, renders the result. Free and open-source ↓

24,696 просмотров • 3 месяцев назад

🚀 Introducing the first-ever Agent UI 🚀 This is hands-down my favorite product! Chat with local Agents tailored to my needs. Local memory, storage, knowledge and tools 🔥 ⚡️ Your data, your control 🧠 Compatible with any LLM 🤝 Run multiple agents or a team of agents

🚀 Introducing the first-ever Agent UI 🚀 This is hands-down my favorite product! Chat with local Agents tailored to my needs. Local memory, storage, knowledge and tools 🔥 ⚡️ Your data, your control 🧠 Compatible with any LLM 🤝 Run multiple agents or a team of agents

69,015 просмотров • 1 год назад

Build Multi Agent Systems with Reasoning and Context Thanks to sonnet-4, we have level 4 autonomous multi-agent systems working. Learn how to add: -> Reasoning Tools (think -> analyze) -> Shared Agentic Context -> Agentic Memory Code below 👇

Build Multi Agent Systems with Reasoning and Context Thanks to sonnet-4, we have level 4 autonomous multi-agent systems working. Learn how to add: -> Reasoning Tools (think -> analyze) -> Shared Agentic Context -> Agentic Memory Code below 👇

38,576 просмотров • 1 год назад

Super impressed with the new Ollama updates! Adjusting my rating from 30-40% to a solid 80-90% -- thats how good it is now for building Agents 🙌 Exceptional work by the ollama team, not sure how they got this perf from 8b models 🔥

Super impressed with the new Ollama updates! Adjusting my rating from 30-40% to a solid 80-90% -- thats how good it is now for building Agents 🙌 Exceptional work by the ollama team, not sure how they got this perf from 8b models 🔥

39,270 просмотров • 1 год назад

Introducing `Personalized Agentic RAG` - where the LLM remembers key details about the user and automatically chooses the tool for RAG. We'll build: 👏 ChatGPT like memory ⚙️ Function calling 🧙 Multi-Agent orchestration code:

Introducing `Personalized Agentic RAG` - where the LLM remembers key details about the user and automatically chooses the tool for RAG. We'll build: 👏 ChatGPT like memory ⚙️ Function calling 🧙 Multi-Agent orchestration code:

45,035 просмотров • 2 лет назад

While others fight, we ship 🚀 Agno’s ReasoningTools are now live on the Playground — giving non-reasoning models the ability to "think", "analyze", and outperform Reasoning Models on Agentic workloads. If you haven't tried `ReasoningTools` yet - you definitely should 👇

While others fight, we ship 🚀 Agno’s ReasoningTools are now live on the Playground — giving non-reasoning models the ability to "think", "analyze", and outperform Reasoning Models on Agentic workloads. If you haven't tried `ReasoningTools` yet - you definitely should 👇

27,864 просмотров • 1 год назад

Today we’re launching monitoring and observability support for Agno via OpenInference (compatible with OpenTelemetry). You can now use your favorite tracing and eval tools like arize phoenix, langsmith, langfuse, langtrace and weave directly with Agno Here are some examples with code 👇

Today we’re launching monitoring and observability support for Agno via OpenInference (compatible with OpenTelemetry). You can now use your favorite tracing and eval tools like arize phoenix, langsmith, langfuse, langtrace and weave directly with Agno Here are some examples with code 👇

13,804 просмотров • 1 год назад

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