aiben / src /evaluate_params.py
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input_args_list = [
"model_state",
"my_db_state",
"selection_docs_state",
"requests_state",
"roles_state",
]
no_default_param_names = [
"instruction",
"iinput",
"context",
"instruction_nochat",
"iinput_nochat",
"h2ogpt_key",
"model_lock",
]
gen_hyper0 = [
"num_beams",
"max_new_tokens",
"min_new_tokens",
"early_stopping",
"max_time",
"repetition_penalty",
"num_return_sequences",
"do_sample",
"seed",
]
gen_hyper = ["temperature", "top_p", "top_k", "penalty_alpha"] + gen_hyper0
reader_names = [
"image_audio_loaders",
"pdf_loaders",
"url_loaders",
"jq_schema",
"extract_frames",
"llava_prompt",
]
eval_func_param_names = (
["instruction", "iinput", "context", "stream_output", "enable_caching", "prompt_type", "prompt_dict", "chat_template"]
+ 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",
"document_source_substrings",
"document_source_substrings_op",
"document_content_substrings",
"document_content_substrings_op",
"pre_prompt_query",
"prompt_query",
"pre_prompt_summary",
"prompt_summary",
"hyde_llm_prompt",
"all_docs_start_prompt",
"all_docs_finish_prompt",
"user_prompt_for_fake_system_prompt",
"json_object_prompt",
"json_object_prompt_simpler",
"json_code_prompt",
"json_code_prompt_if_no_schema",
"json_schema_instruction",
"json_preserve_system_prompt",
"json_object_post_prompt_reminder",
"json_code_post_prompt_reminder",
"json_code2_post_prompt_reminder",
"system_prompt",
]
+ reader_names
+ [
"visible_models",
"visible_image_models",
"image_size",
"image_quality",
"image_guidance_scale",
"image_num_inference_steps",
"h2ogpt_key",
"add_search_to_context",
"chat_conversation",
"text_context_list",
"docs_ordering_type",
"min_max_new_tokens",
"max_input_tokens",
"max_total_input_tokens",
"docs_token_handling",
"docs_joiner",
"hyde_level",
"hyde_template",
"hyde_show_only_final",
"doc_json_mode",
"metadata_in_context",
"chatbot_role",
"speaker",
"tts_language",
"tts_speed",
"image_file",
"image_control",
"images_num_max",
"image_resolution",
"image_format",
"rotate_align_resize_image",
"video_frame_period",
"image_batch_image_prompt",
"image_batch_final_prompt",
"image_batch_stream",
"visible_vision_models",
"video_file",
"response_format",
"guided_json",
"guided_regex",
"guided_choice",
"guided_grammar",
"guided_whitespace_pattern",
"model_lock",
"client_metadata",
]
)
# 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", "sources"]
# 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", "chat_template"]
in_model_state_and_evaluate = ['prompt_type', 'prompt_dict', 'chat_template',
'visible_models', 'h2ogpt_key', 'images_num_max',
'image_resolution',
'image_format', 'video_frame_period', 'visible_vision_models']
image_quality_choices = ['standard', 'hd', 'quick', 'manual']
image_size_default = "1024x1024"