Hi Everyone, I’m Anmol, a AI developer working with Triple Minds on some personal AI side projects and I’ve been researching deeply about the world of AI chatbots, and I keep coming back to one question that seems to fascinate a lot of developers: How hard is it to build a Candy AI clone from scratch? I’m not trying to copy Candy AI’s branding, but I’m extremely curious about how close an independent developer or small team can get to replicating the functionality of a true Candy AI clone. My Stack for Building a Candy AI Clone Here’s the rough tech stack I’m experimenting with for my Candy AI clone: LLMs: LLaMA-3, Mistral, Mixtral, Falcon Embeddings: bge-base-en-v1.5, text-embedding-3-small (for memory recall in the Candy AI clone) Vector DBs: Pinecone, ChromaDB Backend: FastAPI for serving the Candy AI clone’s inference calls Frontend: Next.js for building the chat UI for the Candy AI clone Voice (optional): ElevenLabs for giving the Candy AI clone a voice Images (optional): Stable Diffusion or SDXL for visuals tied into the Candy AI clone’s dialogue So my big question to the community is: ➡️ Has anyone here successfully built a Candy AI clone entirely with open-source models and custom data? What were the biggest wins or failures in your Candy AI clone journey? Did you fine-tune your models, or stick to prompt engineering for your Candy AI clone? How did you solve memory challenges in your Candy AI clone? Any lessons about integrating visuals or voice into a Candy AI clone without killing performance? I’d love to swap notes, see code samples, or just hear your high-level thoughts on whether a full Candy AI clone is achievable outside of big commercial labs. Thanks in advance for sharing any wisdom about building a Candy AI clone!