Phidata: Easily Build Autonomous AI Agents with GPT-4o!

In today's video, I will be showcasing Phidata - a toolkit for building AI Assistants using function calling.

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Phidata is a cutting-edge framework designed for creating autonomous AI assistants (aka Agents) that have long-term memory, contextual knowledge, and the ability to perform actions using function calling. This enables more dynamic and context-aware interactions, paving the way for advanced AI applications.

**Why Phidata?**
LLMs often face challenges due to limited context and inability to take actions. Phidata addresses these issues by incorporating:
- **Memory:** Stores chat history in a database, allowing long-term conversations.
- **Knowledge:** Uses a vector database to provide LLMs with business context.
- **Tools:** Enables LLMs to execute actions like pulling data from APIs, sending emails, or querying databases.

**How It Works**
1. **Create an Assistant:** Begin by defining your autonomous assistant.
2. **Add Tools, Knowledge, and Storage:** Integrate functions, vector databases, and storage to enhance capabilities.
3. **Serve Your AI Application:** Utilize platforms like Streamlit, FastAPI, or Django to deploy your AI assistant.

**Key Highlights**
- Build AI assistants that remember past interactions.
- Equip your AI with relevant business context.
- Empower your AI to perform real-world actions seamlessly.

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**Additional Tags and Keywords:**
AI, Autonomous Assistants, Phidata, Long-term Memory, Contextual Knowledge, AI Tools, Machine Learning, Vector Database, Function Calling, Streamlit, FastAPI, Django, AI Development, Advanced AI Applications

**Hashtags:**
#ai #Phidata #AutonomousAssistants #machinelearning #aidevelopment #TechInnovation

[intheworldofai]

💗 Thank you so much for watching guys! I would highly appreciate it if you subscribe (turn on notifcation bell), like, and comment what else you want to see!

[phidata]

Big thank-you for highlighting Phidata! We’re grateful for your support and love your content!

[sumlikeno]

The video description is amazing. Adding examples of use-cases helps .

[lifeofcode]

Ive built something similar to crew ai called node-agency. So far ive matched a lot of the functionality.

[copycat]

I’m a week into learning how to code, I’m having trouble finalizing the agent back testing and the environment is past my grasp still

[bambanx]

Its possible run multi agents on flowise or langflow or other visual tool? Thanks you so much

[johnharris_ai]

That's impressive! Btw, what IDE are you using in this video?

[nikitakuznetsov]

Can someone share any public repo of complex RAG with several tools calling and explaining how to make a llm decide which tool to call?

It can be langchain or phi usage, doesn't matter.

Cause even in this demo i cant realize if we provide tools with several functions, how llm decides next steps

Thx in advance