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Use a FakeLLM to be able to test certain features without an API KEY #20
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- add `model_type` argument which can be `gpt`, `hugging-face` or `fake` - note: currently `hugging-face` model cannot be use due to [issue](langchain-ai/langchain#18639) - note: `FakeLLM` is not supported on Windows yet - replace client test with `TestFakeLLM` which should work in the pipeline without needing any API KEY or TOKEN, however won't work on Windows - add `clean-env.bat` script to re-install direct dependencies and remove non-used ones
- add `model_type` argument which can be `gpt`, `hugging-face` or `fake` - note: currently `hugging-face` model cannot be use due to [issue](langchain-ai/langchain#18639) - note: `FakeLLM` is not supported on Windows yet - replace client test with `TestFakeLLM` which should work in the pipeline without needing any API KEY or TOKEN, however won't work on Windows - add `clean-env.bat` script to re-install direct dependencies and remove non-used ones
Currently |
- remove `FakeLLM` implementation because `langchain-contrib` doesn't support latest version of `langchain` - remove `langchain-contrib` dependency - update `langchain` to latest version: `0.1.11` #23 - remove `TestFakeLLM` unit test - restore `TestLLMClient` unit test - add versions to `direct-requirements.txt`
- remove `FakeLLM` implementation because `langchain-contrib` doesn't support latest version of `langchain` - remove `langchain-contrib` dependency - update `langchain` to latest version: `0.1.11` #23 - remove `TestFakeLLM` unit test - restore `TestLLMClient` unit test - add versions to `direct-requirements.txt`
I decided to remove |
- use `FakeListChatModel` to instantiate fake models for testing - remove `gpt` model unit test - add `fake` model unit test - note: with this, we won't incur in costs when running unit tests
- use `FakeListChatModel` to instantiate fake models for testing - remove `gpt` model unit test - add `fake` model unit test - note: with this, we won't incur in costs when running unit tests
We will use |
- use `ChatHuggingFace` to instantiate a `Hugging Face` models - use `HuggingFaceEndpoint` to connect to the `Hugging Face` model - add `hugging-face` to `LLMClient` - add `TestHuggingFaceLLMClient` unit test #20 - update `langchain` to `0.1.12` version #23 - install `transformers` dependency - install `Jinja2` dependency
- use `ChatHuggingFace` to instantiate a `Hugging Face` models - use `HuggingFaceEndpoint` to connect to the `Hugging Face` model - add `hugging-face` to `LLMClient` - add `TestHuggingFaceLLMClient` unit test #20 - update `langchain` to `0.1.12` version #23 - install `transformers` dependency - install `Jinja2` dependency
- use `ChatHuggingFace` to instantiate a `Hugging Face` models - use `HuggingFaceEndpoint` to connect to the `Hugging Face` model - add `hugging-face` to `LLMClient` - add `TestHuggingFaceLLMClient` unit test #20 - update `langchain` to `0.1.12` version #23 - install `transformers` dependency - install `Jinja2` dependency - add `HUGGINGFACEHUB_API_TOKEN` to `pipeline.yml`
- use `ChatHuggingFace` to instantiate a `Hugging Face` models - use `HuggingFaceEndpoint` to connect to the `Hugging Face` model - add `hugging-face` to `LLMClient` - add `TestHuggingFaceLLMClient` unit test #20 - update `langchain` to `0.1.12` version #23 - install `transformers` dependency - install `Jinja2` dependency - add `HUGGINGFACEHUB_API_TOKEN` to `pipeline.yml`
- use `ChatHuggingFace` to instantiate a `Hugging Face` models - use `HuggingFaceEndpoint` to connect to the `Hugging Face` model - add `hugging-face` to `LLMClient` - add `TestHuggingFaceLLMClient` unit test #20 - update `langchain` to `0.1.12` version #23 - install `transformers` dependency - install `Jinja2` dependency - add `HUGGINGFACEHUB_API_TOKEN` to `pipeline.yml`
Issue seemed to have been solved in |
There should be a way for contributors to test most of the features without using the actual OpenAI model. This would allow them implementing features and making contributions without being charged.
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