function_name = tool_call.function.name function_to_call = available_functions[function_name] function_args = json.loads(tool_call.function.arguments) function_response = function_to_call( location=function_args
because we are streaming in chunks I see the code that appends function names but this leads to the model failing to call functions where there are multiple function calls per completion pipecat.services.openai.OpenAIUnhandledFunctionException: The LLM tried to call a function named 'get_weather...
With OpenAI’s parallel function-calling feature, we can do some powerful stuff. We can use the below code to create JSON data which will be used further to call a local function. Then, It will call the local function and fetch details. After that, we take those details and hand them ...
examples, andLLMCompiler automatically computes an optimized orchestration for the function calls. LLMCompiler can be used with open-source models such as LLaMA, as well as OpenAI’s GPT models. Across a range of tasks that exhibit different patterns of parallel function calling, LLMCompiler ...
results. We observe consistent latency speedup of up to 3.7x, cost savings of up to 6.7x, and accuracy improvement of up to ~9% as compared to ReAct. Additionally, LLMCompiler achieves up to 1.35x latency gain over OpenAI's recent parallel function calling, while achieving similar accuracy....
Now when I try to run that script by calling it via a pushbutton, it suddenly uses 2 workers only. It doesn't change anything if I start the parallel pool manually before using the GUI or if i embed the code above inside the script or the GUI callback funct...
Performance of preprocessing and postprocessing libraries before calling the model prediction function Underlying ML framework backend performance Model-specific and hardware-specific optimizations In this section, we focus primarily on container latency and specifically on optimizi...
6.7x cost savings, and 9% accuracy improvement. In the Game of 24 benchmarks, LLMCompiler achieved a 2x speedup compared to Tree-of-Thoughts and outperformed OpenAI’s parallel function calling feature with up to 1.35x latency gain. The open...
vllm 当我设置tensor_parallel_size=2时，发生了一个时间错误,当tensor_parallel_size=2被使用时，输出...
vllm 当我设置tensor_parallel_size=2时，发生了一个时间错误,当tensor_parallel_size=2被使用时，输出...