Clelia Astra Bertelli's picture

Clelia Astra Bertelli

as-cle-bert

AI & ML interests

Biology + Artificial Intelligence = โค๏ธ | AI for sustainable development, sustainable development for AI | Researching on Machine Learning Enhancement | I love automation for everyday things | Blogger | Open Source

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posted an update about 5 hours ago
Llama-4 is out and I couldn't resist but to cook something with it... So I came up with ๐‹๐ฅ๐š๐ฆ๐š๐‘๐ž๐ฌ๐ž๐š๐ซ๐œ๐ก๐ž๐ซ (https://llamaresearcher.com), your deep-research AI companion!๐Ÿ”Ž The workflow behind ๐—Ÿ๐—น๐—ฎ๐—บ๐—ฎ๐—ฅ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต๐—ฒ๐—ฟ is simple: ๐Ÿ’ฌ You submit a query ๐Ÿ›ก๏ธ Your query is evaluated by Llama 3 guard model, which deems it safe or unsafe ๐Ÿง  If your query is safe, it is routed to the Researcher Agent โš™๏ธ The Researcher Agent expands the query into three sub-queries, with which to search the web ๐ŸŒ The web is searched for each of the sub-queries ๐Ÿ“Š The retrieved information is evaluated for relevancy against your original query โœ๏ธ The Researcher Agent produces an essay based on the information it gathered, paying attention to referencing its sources The agent itself is also built with easy-to-use and intuitive blocks: ๐Ÿฆ™ LlamaIndex provides the agentic architecture and the integrations with the language models โšกGroq makes Llama-4 available with its lightning-fast inference ๐Ÿ”Ž Linkup allows the agent to deep-search the web and provides sourced answers ๐Ÿ’ช FastAPI does the heavy loading with wrapping everything within an elegant API interface โฑ๏ธ Redis is used for API rate limiting ๐ŸŽจ Gradio creates a simple but powerful user interface Special mention also to Lovable, which helped me build the first draft of the landing page for LlamaResearcher!๐Ÿ’– If you're curious and you want to try LlamaResearcher, you can - completely for free and without subscription - for 30 days from now โžก๏ธ https://llamaresearcher.com And if you're like me, and you like getting your hands in code and build stuff on your own machine, I have good news: this is all open-source, fully reproducible locally and Docker-ready๐Ÿ‹ Just go to the GitHub repo: https://github.com/AstraBert/llama-4-researcher and don't forget to star it, if you find it useful!โญ As always, have fun and feel free to leave your feedbackโœจ
posted an update 4 days ago
I heard someone saying ๐˜ƒ๐—ผ๐—ถ๐—ฐ๐—ฒ assistants are the future, and someone else that ๐— ๐—–๐—ฃ will rule the AI world... So I decided to combine both!๐Ÿš€ Meet ๐“๐ฒ๐’๐•๐€ (๐—ง๐˜†pe๐—ฆcript ๐—ฉoice ๐—”ssistant, https://github.com/AstraBert/TySVA), your (speaking) AI companion for everyday TypeScript programming tasks!๐ŸŽ™๏ธ TySVA is a skilled TypeScript expert and, to provide accurate and up-to-date responses, she leverages the following workflow: ๐Ÿ—ฃ๏ธ If you talk to her, she converts the audio into a textual prompt, and use it a starting point to answer your questions (if you send a message, she'll use directly that๐Ÿ’ฌ) ๐Ÿง  She can solve your questions by (deep)searching the web and/or by retrieving relevant information from a vector database containing TypeScript documentation. If the answer is simple, she can also reply directly (no tools needed!) ๐Ÿ›œ To ease her life, TySVA has all the tools she needs available through Model Context Protocol (MCP) ๐Ÿ”Š Once she's done, she returns her answer to you, along with a voice summary of what she did and what solution she found But how does she do that? What are her components?๐Ÿคจ ๐Ÿ“– Qdrant + HuggingFace give her the documentation knowledge, providing the vector database and the embeddings ๐ŸŒ Linkup provides her with up-to-date, grounded answers, connecting her to the web ๐Ÿฆ™ LlamaIndex makes up her brain, with the whole agentic architecture ๐ŸŽค ElevenLabs gives her ears and mouth, transcribing and producing voice inputs and outoputs ๐Ÿ“œ Groq provides her with speech, being the LLM provider behind TySVA ๐ŸŽจ Gradio+FastAPI make up her face and fibers, providing a seamless backend-to-frontend integration If you're now curious of trying her, you can easily do that by spinning her up locally (and with Docker!๐Ÿ‹) from the GitHub repo โžก๏ธ https://github.com/AstraBert/TySVA And feel free to leave any feedback!โœจ
liked a dataset 9 days ago
lucadillenburg/startup-chatbot
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Visualize proteins on Hugging Face Spaces

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