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Study Assistant
Privacy-first app to chat with your local documents.
Study Assistant is a local-first, privacy-focused RAG desktop application. It lets you index your local PDF, Word, and text files and chat with them using local LLMs via Ollama. It features a multi-provider fallback chain (Ollama → Gemini → Groq) to ensure reliable queries without requiring cloud connectivity for baseline tasks.
Hi everyone, I’m the developer behind Study Assistant.
I built this because I needed a way to query my collection of study documents without relying on cloud-based search or proprietary interfaces. It’s a local-first RAG desktop application designed for privacy and speed.
Key Technical Highlights:
• Local-First Architecture: Runs fully offline via Ollama.
• Fallback Chain: Implements a multi-provider strategy (Ollama → Gemini → Groq → OpenRouter) to ensure query success even if local compute capacity is hit.
• Smart Indexing: Uses file-hash validation to cache embeddings, preventing redundant processing of your document library.
I’m specifically looking for technical feedback on the retrieval accuracy and the UX of the multi-provider fallback logic. The code is entirely open-source and available for audit.
Looking forward to your technical critiques and suggestions for improving retrieval latency.
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About Study Assistant on Product Hunt
“Privacy-first app to chat with your local documents.”
Study Assistant was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #102 on the daily leaderboard. Study Assistant is a local-first, privacy-focused RAG desktop application. It lets you index your local PDF, Word, and text files and chat with them using local LLMs via Ollama. It features a multi-provider fallback chain (Ollama → Gemini → Groq) to ensure reliable queries without requiring cloud connectivity for baseline tasks.
Study Assistant was featured in Open Source (68.6k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 143k products, making this a competitive space to launch in.
Who hunted Study Assistant ?
Study Assistant was hunted by Abrar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Study Assistant stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Abrar