Sagar Desai

> Hi, thanks for the recommendations. I have combined two cases to solve this problem after reading your instructions, you can just follow them here. > > If you encountered...

no straight forward answer, trial and error, can suggest few point to look to decide 1. check the splits post loading `vector_store.similarity_search_with_score()` make sure it makes sense to your question...

yes for model like gpt-4 system messages are respected. you will be able to achieve the task with curated system message. for gpt3.5, compared to 4 pays less attention to...

as you are using `memory` from conversion. it has not be reset, as you can see it is showing 2 past conversion records. Reset the karnel and try again.

yes faced same issue. `retriever = db.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .5})` this does not work. use this ``` search_result = vector_store.similarity_search_with_score(query, k=30) search_result ```

faced same issue work with `result = chain(query)` `result = chain.run(query) ` throws error

getting same errror for Gemma model ``` [TensorRT-LLM] TensorRT-LLM version: 0.11.0.dev2024052800 Traceback (most recent call last): File "/userhome/home/sagdesai/work/gemma-trt/TensorRT-LLM/examples/gemma/../run.py", line 602, in main(args) File "/userhome/home/sagdesai/work/gemma-trt/TensorRT-LLM/examples/gemma/../run.py", line 451, in main runner =...

1. cloned https://github.com/NVIDIA/TensorRT-LLM.git - following - `https://github.com/NVIDIA/TensorRT-LLM/tree/main/examples/gemma#run-inference-under-bfloat16-for-hf-checkpoint` 2. installed `requirement.txt` for `Gemma` 3. ``` python3 ./convert_checkpoint.py \ --ckpt-type hf \ --model-dir /sadata/models_hf/gemma-2b-it/ \ --dtype bfloat16 \ --world-size 1 \ --output-model-dir...

We alredy calculating tokens , we can get the pricing from the openai Then calculate cost. Make sure each time before going to query we check the cost condition Add...