Handle parallel function calls for OpenAI LLMs #522
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| transport.input(), | ||
| context_aggregator.user(), | ||
| llm, | ||
| fl_out, | ||
| # fl_out, |
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should we just remove the frame loggers?
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Probably. I want to leave them in an example or two so people know they exist, though.
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I was thinking the same thing as @chadbailey59 . No reason not to leave them in a few examples as, um, examples.
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If we leave them we should uncomment them I think.
| # possible question for Aleix and Chad about what the right way | ||
| # to trigger speech is, now, with the new queues/async/sync refactors. | ||
| # await llm.push_frame(TextFrame("Let me check on that.")) | ||
| logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}") |
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The rule is... if a processor can push frames from a different task then it should be async. But function calls happen in the same task, no? If so, this should be OK.
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I just realized that, by default, all processors should be async and not the other way around. It makes more sense and it's safer this way. That was my initial idea but then changed my mine. But I think that was the right idea. I'll make the change in the morning and I believe that line should be safe.
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I will rebase and test again after this change.
…nly one function call at a time. Fixed this to handle multiple function calls.
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The hard work was done here by @jeevan057
#346 (review)
I rebased, fixed one small bug, and modified the code from the original PR to use the newer context aggregator frames approach. I've tested this heavily.
There's one question in the comments of the
14-function-calling.pyexample, but I don't think that should block a merge.