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All-in-one AI chat studio — 7 providers (Ollama, Claude, OpenAI, vLLM, Claude Code, Codex, Gemini CLI), RAG knowledge base, MCP tool integration, Mem0 shared memory, and 3-step pipeline. 100% local-capable. MIT licensed.

8 starsPython

I built a desktop app combining Claude, GPT, Gemini with local Ollama

by tsunamayo·Mar 1, 2026·1 point·1 comment
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AI Analysis

●●SolidSolve My ProblemSlick

Hybrid pipeline splits reasoning (cloud) and execution (local), but multi-model orchestration is becoming crowded.

Strengths
  • •3-phase decompose-execute-integrate pipeline uses cloud reasoning where it's strong (structure) and local inference for cost
  • •Dual interface (PyQt6 desktop + React web UI) means access from PC, phone, and LAN without extra deployment
  • •Built-in ChromaDB RAG and Discord webhooks show complete feature set, not just a proof-of-concept
Weaknesses
  • •Windows-only desktop app limits adoption; macOS and Linux users stuck with web UI
  • •Competes directly with LM Studio, Jan, and LocalAI—no clear differentiation beyond the 3-phase approach
Target Audience

Developers and AI practitioners who want hybrid cloud+local LLM workflows without high API costs

Similar To

LM Studio · Jan.ai · LocalAI

Post Description

I built a desktop app (PyQt6, Windows) that orchestrates multiple AI models in a 3-phase pipeline:

Phase 1 – A cloud LLM (Claude/GPT/Gemini) decomposes the prompt into structured sub-tasks Phase 2 – Local Ollama models process each sub-task (free, private, runs on your GPU) Phase 3 – The cloud LLM integrates the results into a coherent final answer

The motivation: cloud APIs are great at reasoning and structure but cost money. Local Ollama models are free but sometimes inconsistent. The pipeline lets you use each where it's strongest.

Also includes: - FastAPI + React web UI (accessible from LAN/mobile) - SQLite chat history - ChromaDB-based RAG - Discord webhook notifications

Stack: Python, PyQt6, FastAPI, React, Ollama, Anthropic/OpenAI/Google APIs. MIT license.

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