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Does the 118K-Star AI Trading Agent Actually Work? I Installed and Tested TradingAgents v0.7.1 — Open-Source Agent, Tested #1

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Search description: I installed TradingAgents v0.7.1 — the 118K-star multi-agent trading framework — and tested it for real. Setup, keys, errors, honest verdict. Labels: Python, AI Agents, Open Source, Tutorials Versions used in this post — read this first: TradingAgents v0.7.1 (release tag, commit c4544913a14ed3df5f1ed7b9e8483270ce20682a — the exact code tested here) · Python 3.12.3 (the project requires Python 3.11 or later) · Repository figures — 118,913 stars, 22,731 forks, 884 watchers — read from the project's GitHub page on October 31, 2026 ; this repository gains hundreds of stars a day, so treat those numbers as a dated snapshot, not a permanent fact. Licence: Apache-2.0. A framing note before anything else. TradingAgents describes itself, in its own documentation, as a framework "designed for research purposes" that "is not intended as financial, investment, or trading advice." This post holds it to exactly that standard. This is an engineer...
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How Do I Deploy a FastAPI App to Azure App Service? Step by Step, From Zero

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Versions used in this post — read this first: Python 3.12.3 · Azure CLI 2.91.0 · fastapi 0.162.0 · uvicorn 0.54.0 · gunicorn 26.2.0 · uvicorn-worker 0.4.0 · App Service runtime PYTHON:3.12 . Everything runs from one file, main.py , printed in full below — the exact file in the companion repo. Recorded October 2026; the free-tier limits and prices below are Microsoft's published figures as of that date. The direct answer Deploy a FastAPI app to Azure App Service, step by step, on the free tier: put the app in a folder with requirements.txt at the root, create a resource group, a free (F1) App Service plan, and a Python 3.12 web app, set two app settings, deploy a zip of the code, and — the step most tutorials skip — set the startup command . On Python 3.13 and earlier, App Service auto-detects Django and Flask only; a FastAPI app with no startup command doesn't error, it silently serves a built-in default page. The startup command is one line, and this post explains every piec...
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I Built an AI Agent That Reads Release Notes So I Don't Have To

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Versions used in this post — read this first: Python 3.12.3 · requests 2.34.2 · google-genai 2.33.0 · Model: gemini-3.6-flash . Everything runs from one file, digest_agent.py , printed in full below — the exact file in the companion repo. The direct answer Build an AI agent in Python, step by step, that reads release notes for you. One small Python file is enough to stop reading changelogs by hand. Think of the agent as the smallest useful harness — three steps with a strict contract between them: fetch , summarize , write . It fetches the newest GitHub release of each project it tracks from the project's public releases feed, sends the release notes to Gemini with an instruction to return three summary bullets plus any breaking changes as JSON, and writes one Markdown file: digest.md , with the breaking changes collected at the top. Schedule it for 7:15 every morning and yesterday's releases are a one-page read with your coffee. No GitHub account, no token, no framework — the...
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