u/Affectionate_Ad_2324

Hey guys,

I'm trying to get a local AI agent to create and edit files on my Windows machine, but I’m stuck in a frustrating loop. Every time I ask the agent to do a file operation, it just prints the raw JSON tool call into the chat box or terminal instead of actually executing it.

My Specs:

• Windows
• 12 GB RAM
• Backend: Ollama (running locally)
• Model: qwen2.5-coder:7b

The Issue: If I tell the agent: "Create a text file named salut.txt containing 'hello'", nothing happens on my drive.

• In Open Interpreter, it just prints the PowerShell code inside a text block: {"name": "execute", "arguments": {...}} and stops dead.
• In AnythingLLM (Workspace Agent mode), it does the exact same thing. It spits out: { "name": "create-text-file", "arguments": { "filename": "salut.txt", ... } } right in the chat bubble.

The model clearly understands what I want and formats the JSON perfectly, but the host apps (AnythingLLM / Open Interpreter) won't intercept it to trigger the actual script.

Has anyone managed to get Qwen's tool-calling to actually work with Ollama on Windows? Do I need a specific system prompt or a workaround to force the apps to recognize the JSON output as an action?

Thanks!

Hey everyone,

I've been trying to set up Ollama with OpenClaw to build an autonomous agent, but I hit a massive roadblock with my hardware. On my current setup, it's just way too slow to be functional because I don't have enough RAM.

A friend of mine (Liam) and I have been grinding on this together, trying to figure out a workaround. I do have a desktop tower with 12 GB of RAM, but I really don't want to wipe or uninstall everything on it just to test this setup unless I absolutely have to.

Because of the hardware limitations, I started looking into cloud alternatives. I tried using Google AI Studio with an API key. I know they have a free tier with a specific token limit, but OpenClaw seems to burn through tokens way too fast for the free tier to be viable for long.

I also kept hearing the term "Inference" (or Inference APIs) thrown around as a solution, but to be honest, I'm not entirely sure how that works or if it fits my use case.

My ultimate goal: I want to build a remote AI agent that I can message or talk to from a distance, which can automatically sort, manage, and forward my emails.

Given my12 GB RAM desktop constraint and my goal, do you have any recommendations?
* Is there a way to make OpenClaw more efficient with Google AI Studio's free tier?
* Should I look into specific Inference APIs (like Groq, Together AI, etc.) that might have generous free tiers?
* Or is there a completely different lightweight stack you'd recommend for a remote email-sorting agent?

Thanks for the help!