vouchervision/VoucherVision_Config_Builder.py

import os, yaml, platform, traceback
from vouchervision.LeafMachine2_Config_Builder import get_default_download_folder, write_config_file
from vouchervision.general_utils import validate_dir, print_main_fail
from vouchervision.vouchervision_main import voucher_vision
from general_utils import get_cfg_from_full_path

def build_VV_config():
    #############################################
    ############ Set common defaults ############
    #############################################
    # Changing the values below will set new 
    # default values each time you open the 
    # VoucherVision user interface
    #############################################
    #############################################
    #############################################

    dir_home = os.path.dirname(os.path.dirname(__file__))
    run_name = 'test'
    # dir_images_local = 'D:/Dropbox/LM2_Env/Image_Datasets/GBIF_BroadSample_3SppPerFamily1'
    dir_images_local = os.path.join(dir_home,'demo','demo_images')
    
    # The default output location is the computer's "Downloads" folder
    #    You can set dir_output directly by typing the folder path,
    # OR you can uncomment the line "dir_output = default_output_folder" 
    #    to have VoucherVision save to the Downloads folder by default
    default_output_folder = get_default_download_folder()
    dir_output = default_output_folder
    # dir_output = 'D:/D_Desktop/LM2'

    prefix_removal = '' #'MICH-V-'
    suffix_removal = ''
    catalog_numerical_only = False

    LLM_version_user = 'Azure GPT 4'
    prompt_version = 'Version 2' # from ["Version 1", "Version 1 No Domain Knowledge", "Version 2"]
    use_LeafMachine2_collage_images = False # Use LeafMachine2 collage images

    batch_size = 500

    path_domain_knowledge = os.path.join(dir_home,'domain_knowledge','SLTP_UM_AllAsiaMinimalInRegion.xlsx')
    embeddings_database_name = os.path.splitext(os.path.basename(path_domain_knowledge))[0]

    #############################################
    #############################################
    ########## DO NOT EDIT BELOW HERE ###########
    #############################################
    #############################################
    return assemble_config(dir_home, run_name, dir_images_local,dir_output,
                    prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                    path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                    prompt_version, use_domain_knowledge=False)

def assemble_config(dir_home, run_name, dir_images_local,dir_output,
                    prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                    path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                    prompt_version, use_domain_knowledge=False):
    

    # Initialize the base structure
    config_data = {
        'leafmachine': {}
    }

    # Modular sections to be added to 'leafmachine'
    do_section = {
        'check_for_illegal_filenames': False,
        'check_for_corrupt_images_make_vertical': True,
    }

    print_section = {
        'verbose': True,
        'optional_warnings': True
    }

    logging_section = {
        'log_level': None
    }


    project_section = {
        'dir_output': dir_output, 
        'run_name': run_name,
        'image_location': 'local',
        'batch_size': batch_size,
        'num_workers': 1,
        'dir_images_local': dir_images_local,
        'continue_run_from_partial_xlsx': '',
        'prefix_removal': prefix_removal,
        'suffix_removal': suffix_removal,
        'catalog_numerical_only': catalog_numerical_only,
        'use_domain_knowledge': use_domain_knowledge,
        'embeddings_database_name': embeddings_database_name,
        'build_new_embeddings_database': False,
        'path_to_domain_knowledge_xlsx': path_domain_knowledge,
        'prompt_version': prompt_version,
        'delete_all_temps': False,
        'delete_temps_keep_VVE': False,
    }

    modules_section = {
        'specimen_crop': True
    }

    LLM_version = LLM_version_user 
    use_RGB_label_images = use_LeafMachine2_collage_images # Use LeafMachine2 collage images
    
    cropped_components_section = {
        'do_save_cropped_annotations': True,
        'save_cropped_annotations': ['label','barcode'],
        'save_per_image': False,
        'save_per_annotation_class': True,
        'binarize_labels': False,
        'binarize_labels_skeletonize': False
    }

    data_section = {
        'save_json_rulers': False,
        'save_json_measurements': False,
        'save_individual_csv_files_rulers': False,
        'save_individual_csv_files_measurements': False,
        'save_individual_csv_files_landmarks': False,
        'save_individual_efd_files': False,
        'include_darwin_core_data_from_combined_file': False,
        'do_apply_conversion_factor': False
    }

    overlay_section = {
        'save_overlay_to_pdf': False,
        'save_overlay_to_jpgs': True,
        'overlay_dpi': 300, # Between 100 to 300
        'overlay_background_color': 'black', # Either 'white' or 'black'

        'show_archival_detections': True,
        'show_plant_detections': True,
        'show_segmentations': True,
        'show_landmarks': True,
        'ignore_archival_detections_classes': [],
        'ignore_plant_detections_classes': ['leaf_whole', 'specimen'], # Could also include 'leaf_partial' and others if needed
        'ignore_landmark_classes': [],

        'line_width_archival': 12, # Previous value given was 2
        'line_width_plant': 12, # Previous value given was 6
        'line_width_seg': 12, # 12 is specified as "thick"
        'line_width_efd': 12, # 3 is specified as "thick" but 12 is given here
        'alpha_transparency_archival': 0.3,
        'alpha_transparency_plant': 0,
        'alpha_transparency_seg_whole_leaf': 0.4,
        'alpha_transparency_seg_partial_leaf': 0.3
    }

    archival_component_detector_section = {
        'detector_type': 'Archival_Detector',
        'detector_version': 'PREP_final',
        'detector_iteration': 'PREP_final',
        'detector_weights': 'best.pt',
        'minimum_confidence_threshold': 0.5, # Default is 0.5
        'do_save_prediction_overlay_images': True,
        'ignore_objects_for_overlay': []
    }

    # Add the sections to the 'leafmachine' key
    config_data['leafmachine']['do'] = do_section
    config_data['leafmachine']['print'] = print_section
    config_data['leafmachine']['logging'] = logging_section
    config_data['leafmachine']['project'] = project_section
    config_data['leafmachine']['LLM_version'] = LLM_version
    config_data['leafmachine']['use_RGB_label_images'] = use_RGB_label_images
    config_data['leafmachine']['cropped_components'] = cropped_components_section
    config_data['leafmachine']['modules'] = modules_section
    config_data['leafmachine']['data'] = data_section
    config_data['leafmachine']['overlay'] = overlay_section
    config_data['leafmachine']['archival_component_detector'] = archival_component_detector_section

    return config_data, dir_home

def build_api_tests(api):
    dir_home = os.path.dirname(os.path.dirname(__file__))
    path_to_configs = os.path.join(dir_home,'demo','demo_configs')

    dir_home = os.path.dirname(os.path.dirname(__file__))
    dir_images_local = os.path.join(dir_home,'demo','demo_images')
    validate_dir(os.path.join(dir_home,'demo','demo_configs'))
    path_domain_knowledge = os.path.join(dir_home,'domain_knowledge','SLTP_UM_AllAsiaMinimalInRegion.xlsx')
    embeddings_database_name = os.path.splitext(os.path.basename(path_domain_knowledge))[0]
    prefix_removal = ''
    suffix_removal = ''
    catalog_numerical_only = False
    batch_size = 500


    # ### Option 1: "GPT 4" of ["GPT 4", "GPT 3.5", "Azure GPT 4", "Azure GPT 3.5", "PaLM 2"]
    # LLM_version_user = 'Azure GPT 4'
    
    # ### Option 2: False of [False, True]
    # use_LeafMachine2_collage_images = False
    
    # ### Option 3: False of [False, True]
    # use_domain_knowledge = True

    test_results = {}
    if api == 'openai':
        OPT1, OPT2, OPT3 = TestOptionsAPI_openai.get_options()
    elif api == 'palm':
        OPT1, OPT2, OPT3 = TestOptionsAPI_palm.get_options()
    elif api == 'azure_openai':
        OPT1, OPT2, OPT3 = TestOptionsAPI_azure_openai.get_options()
    else:
        raise

    ind = -1
    ind_opt1 = -1
    ind_opt2 = -1
    ind_opt3 = -1

    for opt1 in OPT1:
        ind_opt1+= 1
        for opt2 in OPT2:
            ind_opt2 += 1
            for opt3 in OPT3:
                ind += 1
                ind_opt3 += 1
                
                LLM_version_user = opt1
                use_LeafMachine2_collage_images = opt2
                prompt_version = opt3

                filename = f"{ind}__OPT1-{ind_opt1}__OPT2-{ind_opt2}__OPT3-{ind_opt3}.yaml"
                run_name = f"{ind}__OPT1-{ind_opt1}__OPT2-{ind_opt2}__OPT3-{ind_opt3}"

                dir_output = os.path.join(dir_home,'demo','demo_output','run_name')
                validate_dir(dir_output)
                
                config_data, dir_home = assemble_config(dir_home, run_name, dir_images_local,dir_output,
                    prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                    path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                    prompt_version)
                
                write_config_file(config_data, os.path.join(dir_home,'demo','demo_configs'),filename=filename)

                test_results[run_name] = False
            ind_opt3 = -1
        ind_opt2 = -1
    ind_opt1 = -1
        
    return dir_home, path_to_configs, test_results

def build_demo_tests(llm_version):
    dir_home = os.path.dirname(os.path.dirname(__file__))
    path_to_configs = os.path.join(dir_home,'demo','demo_configs')

    dir_home = os.path.dirname(os.path.dirname(__file__))
    dir_images_local = os.path.join(dir_home,'demo','demo_images')
    validate_dir(os.path.join(dir_home,'demo','demo_configs'))
    path_domain_knowledge = os.path.join(dir_home,'domain_knowledge','SLTP_UM_AllAsiaMinimalInRegion.xlsx')
    embeddings_database_name = os.path.splitext(os.path.basename(path_domain_knowledge))[0]
    prefix_removal = ''
    suffix_removal = ''
    catalog_numerical_only = False
    batch_size = 500


    # ### Option 1: "GPT 4" of ["GPT 4", "GPT 3.5", "Azure GPT 4", "Azure GPT 3.5", "PaLM 2"]
    # LLM_version_user = 'Azure GPT 4'
    
    # ### Option 2: False of [False, True]
    # use_LeafMachine2_collage_images = False
    
    # ### Option 3: False of [False, True]
    # use_domain_knowledge = True

    test_results = {}
    if llm_version == 'gpt':
        OPT1, OPT2, OPT3 = TestOptionsGPT.get_options()
    elif llm_version == 'palm':
        OPT1, OPT2, OPT3 = TestOptionsPalm.get_options()
    else:
        raise

    ind = -1
    ind_opt1 = -1
    ind_opt2 = -1
    ind_opt3 = -1

    for opt1 in OPT1:
        ind_opt1+= 1
        for opt2 in OPT2:
            ind_opt2 += 1
            for opt3 in OPT3:
                ind += 1
                ind_opt3 += 1
                
                LLM_version_user = opt1
                use_LeafMachine2_collage_images = opt2
                prompt_version = opt3

                filename = f"{ind}__OPT1-{ind_opt1}__OPT2-{ind_opt2}__OPT3-{ind_opt3}.yaml"
                run_name = f"{ind}__OPT1-{ind_opt1}__OPT2-{ind_opt2}__OPT3-{ind_opt3}"

                dir_output = os.path.join(dir_home,'demo','demo_output','run_name')
                validate_dir(dir_output)
                

                if llm_version == 'gpt':
                    if prompt_version in ['Version 1']:
                        config_data, dir_home = assemble_config(dir_home, run_name, dir_images_local,dir_output,
                            prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                            path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                            prompt_version, use_domain_knowledge=True)
                    else:
                        config_data, dir_home = assemble_config(dir_home, run_name, dir_images_local,dir_output,
                            prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                            path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                            prompt_version)
                elif llm_version == 'palm':
                    if prompt_version in ['Version 1 PaLM 2']:
                        config_data, dir_home = assemble_config(dir_home, run_name, dir_images_local,dir_output,
                            prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                            path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                            prompt_version, use_domain_knowledge=True)
                    else:
                        config_data, dir_home = assemble_config(dir_home, run_name, dir_images_local,dir_output,
                            prefix_removal,suffix_removal,catalog_numerical_only,LLM_version_user,batch_size,
                            path_domain_knowledge,embeddings_database_name,use_LeafMachine2_collage_images,
                            prompt_version)
                
                
                write_config_file(config_data, os.path.join(dir_home,'demo','demo_configs'),filename=filename)

                test_results[run_name] = False
            ind_opt3 = -1
        ind_opt2 = -1
    ind_opt1 = -1
        
    return dir_home, path_to_configs, test_results

class TestOptionsGPT:
    OPT1 = ["GPT 4", "GPT 3.5", "Azure GPT 4", "Azure GPT 3.5"]
    OPT2 = [False, True]
    OPT3 = ["Version 1", "Version 1 No Domain Knowledge", "Version 2"]

    @classmethod
    def get_options(cls):
        return cls.OPT1, cls.OPT2, cls.OPT3
    @classmethod
    def get_length(cls):
        return 24
    
class TestOptionsPalm:
    OPT1 = ["PaLM 2"]
    OPT2 = [False, True]
    OPT3 = ["Version 1 PaLM 2", "Version 1 PaLM 2 No Domain Knowledge", "Version 2 PaLM 2"]

    @classmethod
    def get_options(cls):
        return cls.OPT1, cls.OPT2, cls.OPT3
    @classmethod
    def get_length(cls):
        return 6
    
class TestOptionsAPI_openai:
    OPT1 = ["GPT 3.5"]
    OPT2 = [False]
    OPT3 = ["Version 2"]

    @classmethod
    def get_options(cls):
        return cls.OPT1, cls.OPT2, cls.OPT3
    @classmethod
    def get_length(cls):
        return 24
    
class TestOptionsAPI_azure_openai:
    OPT1 = ["Azure GPT 3.5"]
    OPT2 = [False]
    OPT3 = ["Version 2"]

    @classmethod
    def get_options(cls):
        return cls.OPT1, cls.OPT2, cls.OPT3
    @classmethod
    def get_length(cls):
        return 24
    
class TestOptionsAPI_palm:
    OPT1 = ["PaLM 2"]
    OPT2 = [False]
    OPT3 = ["Version 2 PaLM 2"]

    @classmethod
    def get_options(cls):
        return cls.OPT1, cls.OPT2, cls.OPT3
    @classmethod
    def get_length(cls):
        return 6
    
def run_demo_tests_GPT(progress_report):
    dir_home, path_to_configs, test_results = build_demo_tests('gpt')
    progress_report.set_n_overall(len(test_results.items()))

    JSON_results = {}

    for ind, (cfg, result) in enumerate(test_results.items()):
        OPT1, OPT2, OPT3 = TestOptionsGPT.get_options()
        
        test_ind, ind_opt1, ind_opt2, ind_opt3 = cfg.split('__')
        opt1_readable = OPT1[int(ind_opt1.split('-')[1])]

        if opt1_readable in ["Azure GPT 4", "Azure GPT 3.5"]:
            api_version = 'gpt-azure'
        elif opt1_readable in ["GPT 4", "GPT 3.5"]:
            api_version = 'gpt'
        else:
            raise

        opt2_readable = "Use LeafMachine2 for Collage Images" if OPT2[int(ind_opt2.split('-')[1])] else "Don't use LeafMachine2 for Collage Images"
        opt3_readable = f"Prompt {OPT3[int(ind_opt3.split('-')[1])]}"
        # Construct the human-readable test name
        human_readable_name = f"{opt1_readable}, {opt2_readable}, {opt3_readable}"
        get_n_overall = progress_report.get_n_overall()
        progress_report.update_overall(f"Test {int(test_ind)+1} of {get_n_overall} --- Validating {human_readable_name}")
        print_main_fail(f"Starting validation test: {human_readable_name}")
        cfg_file_path = os.path.join(path_to_configs,'.'.join([cfg,'yaml']))
        
        if check_API_key(dir_home, api_version) and check_API_key(dir_home, 'google-vision-ocr'):
            try:
                last_JSON_response, total_cost = voucher_vision(cfg_file_path, dir_home, cfg_test=None, progress_report=progress_report, test_ind=int(test_ind))
                test_results[cfg] = True
                JSON_results[ind] = last_JSON_response
            except Exception as e:
                JSON_results[ind] = None
                test_results[cfg] = False
                print(f"An exception occurred: {e}")
                traceback.print_exc()  # This will print the full traceback
        else:
            fail_response = ''
            if not check_API_key(dir_home, 'google-vision-ocr'):
                fail_response += "No API key found for Google Vision OCR"
            if not check_API_key(dir_home, api_version):
                fail_response += f"  +  No API key found for {api_version}"
            test_results[cfg] = False
            JSON_results[ind] = fail_response
            print(f"No API key found for {fail_response}")
            
    return test_results, JSON_results

def run_demo_tests_Palm(progress_report):
    api_version = 'palm'

    dir_home, path_to_configs, test_results = build_demo_tests('palm')
    progress_report.set_n_overall(len(test_results.items()))

    JSON_results = {}

    for ind, (cfg, result) in enumerate(test_results.items()):
        OPT1, OPT2, OPT3 = TestOptionsPalm.get_options()
        test_ind, ind_opt1, ind_opt2, ind_opt3 = cfg.split('__')
        opt1_readable = OPT1[int(ind_opt1.split('-')[1])]
        opt2_readable = "Use LeafMachine2 for Collage Images" if OPT2[int(ind_opt2.split('-')[1])] else "Don't use LeafMachine2 for Collage Images"
        opt3_readable = f"Prompt {OPT3[int(ind_opt3.split('-')[1])]}"
        # opt3_readable = "Use Domain Knowledge" if OPT3[int(ind_opt3.split('-')[1])] else "Don't use Domain Knowledge"
        # Construct the human-readable test name
        human_readable_name = f"{opt1_readable}, {opt2_readable}, {opt3_readable}"
        get_n_overall = progress_report.get_n_overall()
        progress_report.update_overall(f"Test {int(test_ind)+1} of {get_n_overall} --- Validating {human_readable_name}")
        print_main_fail(f"Starting validation test: {human_readable_name}")
        cfg_file_path = os.path.join(path_to_configs,'.'.join([cfg,'yaml']))
        
        if check_API_key(dir_home, api_version) and check_API_key(dir_home, 'google-vision-ocr') :
            try:
                last_JSON_response, total_cost = voucher_vision(cfg_file_path, dir_home, cfg_test=None, progress_report=progress_report, test_ind=int(test_ind))
                test_results[cfg] = True
                JSON_results[ind] = last_JSON_response
            except Exception as e:
                test_results[cfg] = False
                JSON_results[ind] = None
                print(f"An exception occurred: {e}")
                traceback.print_exc()  # This will print the full traceback
        else:
            fail_response = ''
            if not check_API_key(dir_home, 'google-vision-ocr'):
                fail_response += "No API key found for Google Vision OCR"
            if not check_API_key(dir_home, api_version):
                fail_response += f"  +  No API key found for {api_version}"
            test_results[cfg] = False
            JSON_results[ind] = fail_response
            print(f"No API key found for {fail_response}")

    return test_results, JSON_results

def run_api_tests(api):
    try:
        dir_home, path_to_configs, test_results = build_api_tests(api)

        JSON_results = {}

        for ind, (cfg, result) in enumerate(test_results.items()):
            if api == 'openai':
                OPT1, OPT2, OPT3 = TestOptionsAPI_openai.get_options()
            elif 'azure_openai':
                OPT1, OPT2, OPT3 = TestOptionsAPI_azure_openai.get_options()
            elif 'palm':
                OPT1, OPT2, OPT3 = TestOptionsAPI_palm.get_options()
            test_ind, ind_opt1, ind_opt2, ind_opt3 = cfg.split('__')
            opt1_readable = OPT1[int(ind_opt1.split('-')[1])]
            opt2_readable = "Use LeafMachine2 for Collage Images" if OPT2[int(ind_opt2.split('-')[1])] else "Don't use LeafMachine2 for Collage Images"
            opt3_readable = f"Prompt {OPT3[int(ind_opt3.split('-')[1])]}"
            # opt3_readable = "Use Domain Knowledge" if OPT3[int(ind_opt3.split('-')[1])] else "Don't use Domain Knowledge"
            # Construct the human-readable test name
            human_readable_name = f"{opt1_readable}, {opt2_readable}, {opt3_readable}"
            print_main_fail(f"Starting validation test: {human_readable_name}")
            cfg_file_path = os.path.join(path_to_configs,'.'.join([cfg,'yaml']))
            
            if check_API_key(dir_home, api) and check_API_key(dir_home, 'google-vision-ocr') :
                try:
                    last_JSON_response, total_cost = voucher_vision(cfg_file_path, dir_home, None, cfg_test=None, progress_report=None, test_ind=int(test_ind))
                    test_results[cfg] = True
                    JSON_results[ind] = last_JSON_response
                    return True

                except Exception as e:
                    print(e)
                    return False
            else:
                return False
    except Exception as e:
        print(e)
        return False

# def has_API_key(val):
#         if val != '':
#             return True
#         else:
#             return False
def has_API_key(key_name):
    # Check if the environment variable by key_name is not None
    return os.getenv(key_name) is not None

        
# def check_if_usable():
#     dir_home = os.path.dirname(os.path.dirname(__file__))
#     path_cfg_private = os.path.join(dir_home, 'PRIVATE_DATA.yaml')
#     cfg_private = get_cfg_from_full_path(path_cfg_private)

#     has_key_openai = has_API_key(cfg_private['openai']['OPENAI_API_KEY'])

#     has_key_azure_openai = has_API_key(cfg_private['openai_azure']['api_version']) 

#     has_key_palm2 = has_API_key(cfg_private['google_palm']['google_palm_api'])
    
#     has_key_google_OCR = has_API_key(cfg_private['google_cloud']['path_json_file'])

#     if has_key_google_OCR and (has_key_azure_openai or has_key_openai or has_key_palm2):
#         return True
#     else:
#         return False
def check_if_usable():
    has_key_openai = os.getenv('OPENAI_API_KEY') is not None
    has_key_palm2 = os.getenv('PALM') is not None
    has_key_google_OCR = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') is not None

    return has_key_google_OCR and (has_key_openai or has_key_palm2)

# def check_API_key(dir_home, api_version):
#     dir_home = os.path.dirname(os.path.dirname(__file__))
#     path_cfg_private = os.path.join(dir_home, 'PRIVATE_DATA.yaml')
#     cfg_private = get_cfg_from_full_path(path_cfg_private)

#     has_key_openai = has_API_key(cfg_private['openai']['OPENAI_API_KEY'])

#     has_key_azure_openai = has_API_key(cfg_private['openai_azure']['api_version']) 

#     has_key_palm2 = has_API_key(cfg_private['google_palm']['google_palm_api'])

#     has_key_google_OCR = has_API_key(cfg_private['google_cloud']['path_json_file'])

#     if api_version == 'palm' and has_key_palm2:
#         return True
#     elif api_version in ['gpt','openai'] and has_key_openai:
#         return True
#     elif api_version in ['gpt-azure', 'azure_openai'] and has_key_azure_openai:
#         return True
#     elif api_version == 'google-vision-ocr' and has_key_google_OCR:
#         return True
#     else:
#         return False
def check_API_key(api_version):
    # The API keys are assumed to be set in the environment variables
    has_key_openai = os.getenv('OPENAI_API_KEY') is not None
    has_key_palm2 = os.getenv('PALM') is not None
    has_key_google_OCR = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') is not None

    # Depending on the api_version, check if the corresponding key is present
    if api_version == 'palm' and has_key_palm2:
        return True
    elif api_version in ['gpt', 'openai'] and has_key_openai:
        return True
    elif api_version == 'google-vision-ocr' and has_key_google_OCR:
        return True
    else:
        return False