Hey folks, I was just setting up a new BabyAGI instance for a side project and went to check the latest API pricing. I could have sworn the per-task cost was lower a couple months ago when I last integrated it.
Pulled up my old notes and compared. Yep, there's definitely been an increase on their hosted platform tier. For the volume I'm running (around 5k-10k tasks/month), my projected monthly cost is nearly double what I had modeled initially. 😬
Has anyone else run into this recently? I'm a big believer in testing things thoroughly before committing, so I want to make sure this isn't just a temporary surge or a misunderstanding on my part. If this is the new normal, I might need to revisit my architecture—maybe look at more aggressive caching or even a self-hosted option, though that brings its own operational overhead.
For reference, here's the quick comparison I scribbled down from my notes:
```python
# Old model (approx 2 months ago)
# cost_per_1k_tasks = 0.85
# Current pricing page shows
# cost_per_1k_tasks = 1.40
```
That's a pretty significant jump for those of us building on a budget. Curious if others have seen this and what your strategies are. Are you absorbing the cost, optimizing usage, or exploring alternatives?
~d
Yikes, that's a big jump. I haven't used BabyAGI specifically but I've seen this pattern with other managed services lately.
It's making me rethink using any hosted API as a core component without a clear cost history. Did you check if they announced a pricing tier change or if it's just the base rate that went up? Sometimes they bury the news in a blog post.
Your idea about caching is good. I'm wondering if you could batch tasks somehow to cut down on calls.
Still learning
Exactly. This isn't isolated. I've watched API costs for several serverless platforms inch up over the last year. For instance, some AWS Step Functions state transitions got more expensive, and they barely mentioned it in the fine print.
Batching tasks can cut costs, but it's not always straightforward. If BabyAGI's tasks are stateful or require immediate processing, batching might introduce latency. You'd need to balance cost savings against user experience.
Always assume hosted services will get pricier. That's why I push for cost alerts and regular architecture reviews. Did you set up billing alarms when you started?
cost optimization, not cost cutting
Yeah, that's a noticeable increase for sure. I just checked my dashboard from a small prototype last month, and my per-task cost aligns with your new number. It's definitely not a temporary surge.
For a side project at 5k-10k tasks, that operational cost adds up fast. Have you looked into the new lower-tier pricing from other orchestration services, like CrewAI's hosted offering? It might be a good time for a quick comparative test before re-architecting everything.
What's the nature of your tasks? If they're not all time-sensitive, you could experiment with queueing them and processing in scheduled bursts to stay under a lower usage tier.
Yeah, that pattern with managed services is a real concern. I've noticed sometimes the official announcements about rate changes aren't easy to find, tucked away in a quarterly update email or a change log that doesn't get much visibility. It's a good habit to check their docs' "pricing history" section if they have one.
On batching, it can definitely reduce calls, but it's worth checking if the API call pricing is based on tasks within a call or if it's strictly per-call. Some services charge per "unit of work" regardless of batching, so the savings might be less than expected.
Keep it civil, keep it real.