h2ogpt-chatbot / src /evaluate_params.py
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input_args_list = ['model_state', 'my_db_state', 'selection_docs_state', 'requests_state']
no_default_param_names = [
'instruction',
'iinput',
'context',
'instruction_nochat',
'iinput_nochat',
]
gen_hyper0 = ['num_beams',
'max_new_tokens',
'min_new_tokens',
'early_stopping',
'max_time',
'repetition_penalty',
'num_return_sequences',
'do_sample',
]
gen_hyper = ['temperature',
'top_p',
'top_k'] + gen_hyper0
reader_names = ['image_loaders', 'pdf_loaders', 'url_loaders', 'jq_schema']
eval_func_param_names = ['instruction',
'iinput',
'context',
'stream_output',
'prompt_type',
'prompt_dict'] + \
gen_hyper + \
['chat',
'instruction_nochat',
'iinput_nochat',
'langchain_mode',
'add_chat_history_to_context',
'langchain_action',
'langchain_agents',
'top_k_docs',
'chunk',
'chunk_size',
'document_subset',
'document_choice',
'pre_prompt_query',
'prompt_query',
'pre_prompt_summary',
'prompt_summary',
'system_prompt',
] + \
reader_names + \
['visible_models',
'h2ogpt_key',
'add_search_to_context',
'chat_conversation',
'text_context_list',
'docs_ordering_type',
'min_max_new_tokens',
]
# form evaluate defaults for submit_nochat_api
eval_func_param_names_defaults = eval_func_param_names.copy()
for k in no_default_param_names:
if k in eval_func_param_names_defaults:
eval_func_param_names_defaults.remove(k)
eval_extra_columns = ['prompt', 'response', 'score']
# override default_kwargs if user_kwargs None for args evaluate() uses that are not just in model_state
# ensure prompt_type consistent with prep_bot(), so nochat API works same way
# see how default_kwargs is set in gradio_runner.py
key_overrides = ['prompt_type', 'prompt_dict']