Rename app_researcher.py to app.py

app.py

@@ -0,0 +1,4 @@
+import gradio as gr
+import os
+interview=gr.load("qualz/interview", src="spaces",hf_token=os.environ["hf_token"])
+interview.launch()

app_researcher.py

@@ -1,671 +0,0 @@
-import gradio as gr
-import openai
-from dotenv import find_dotenv
-import json
-import os
-from pathlib import Path
-from utils.app_common import * # common functions for both apps
-import hashlib
-from interviewer_utils.interviewer_persona import AI_PERSONALITIES
-from utils.database_helper import DatabaseIO
-import bcrypt
-import pymongo
-import pymongo.errors
-
-load_dotenv()
-
-USER_ID = os.environ["DEV_USER_ID"]
-TO_FILTER_STUDIES_BY_USERID = False
-project_dir = Path(os.environ['PROJECT_DIR'])
-assert project_dir.exists()
-
-with open(project_dir / 'study_prompts.json') as sp:
-    DEFINITION_OBJECTIVE_MAP = json.load(sp)
-
-# todo refactor: move this to study processor
-def_objective_keys = DEFINITION_OBJECTIVE_MAP.keys()  # iterate it in whatever order
-DEFINITION_OBJECTIVE_CHOICES_DICT = {k: DEFINITION_OBJECTIVE_MAP[k]['descriptive_name'] for k in def_objective_keys}
-DEFINITION_CHOICES_OBJECTIVE_DICT = {v: k for k, v in DEFINITION_OBJECTIVE_CHOICES_DICT.items()}
-
-FRAMEWORK_CHOICES = {
-    "Ethnographic": {
-        "Description": "An in-depth exploration of a particular cultural or social group. "
-                       "Best for: Studies where immersion in a community or culture is essential "
-                       "to understand its norms, rituals, and day-to-day practices. "
-                       "Useful when you want to capture the intricacies of daily life and societal roles."
-    },
-    "Narrative": {
-        "Description": "Focuses on collecting individual stories to shed light on personal"
-                       " experiences and the meanings people attach to them. "
-                       "Best for: Research aimed at understanding personal histories, "
-                       "changes over time, and the richness of individual life journeys."
-    },
-    "Grounded Theory": {
-        "Description": "A systematic approach aimed at generating new theories or concepts "
-                       "based on patterns found in qualitative data. "
-                       "Best for: Studies that start without a predetermined theory, "
-                       "allowing the data itself to drive the development of a new theory or framework."
-    },
-    "Case Study": {
-        "Description": "An in-depth examination of a specific instance, event,"
-                       " or case to gain a comprehensive understanding of its complexities."
-                       " Best for: Research that delves deep into a particular situation or problem, "
-                       "often to understand the 'why' and 'how' of an observed phenomenon."
-    },
-    "Phenomenological": {
-        "Description": "Seeks to understand the essence of a certain phenomenon by exploring "
-                       "individual lived experiences related to it. Best for: Studies focusing"
-                       " on deeply personal and subjective experiences, like the essence of grief "
-                       "or the experience of being a caregiver."
-    },
-    "Exploratory": {
-        "Description": "An approach used to dive into areas of study where little is known, "
-                       "aiming to discover fresh insights or formulate hypotheses for future research. "
-                       "Best for: Preliminary research phases where the aim is to identify patterns, "
-                       "ideas, or hypotheses rather than confirm preset notions."
-    }
-}
-
-
-def check_credentials(username, password):
-
-    try:
-        with DatabaseIO(collection_name=INTERVIEW_USERS_COLLECTION) as db_io:
-            user_collection = db_io.collection
-            user = user_collection.find_one({"username": username})
-            if user is not None:
-                if type(user) == list:
-                    user = user[0]
-                if user and bcrypt.checkpw(password.encode('utf-8'), user['password']):
-                    return True
-                else:
-                    return False
-    except pymongo.errors.ConnectionFailure as e:
-        print(f"Could not connect to MongoDB: {e}")
-        return False
-    except Exception as e:
-        print(f"Error occurred: {e}")
-        return False
-
-def create_link_for_real_interviews(study_id):
-    hash_code = hashlib.sha256(os.urandom(32)).hexdigest()[:32]
-    return f"https://qualz.net/studyId={study_id}&code={hash_code}"
-
-
-def delete_study(this_study_obj, this_study_repository):
-    this_study_repository.delete_study(study_id=this_study_obj._id)
-    this_study_obj.delete_study()
-
-
-def save_synthetic_panelists(this_study_obj,
-                             this_study_repository):
-    if not this_study_obj:
-        return "Please select a study"
-    return this_study_repository.update_study(study_id=this_study_obj._id, updated_data=this_study_obj.to_dict()),
-
-
-def update_study(this_study_obj,
-                 this_study_repository,
-                 this_study_descriptive_name,
-                 this_study_topic,
-                 this_study_objective,
-                 this_study_framework,
-                 this_study_research_questions,
-                 this_interview_questions):
-    if not len(this_study_descriptive_name) or not len(this_study_topic) or not len(this_study_objective) or not len(
-            this_study_framework) or not len(this_study_research_questions) or not len(
-        this_study_research_questions) or not len(this_interview_questions):
-        return "Study Creation failed, all fields above are mandatory"
-    updated_items = {
-        'study_descriptive_name': this_study_descriptive_name,
-        'study_topic': this_study_topic,
-        'study_objective': this_study_objective,
-        'study_framework': this_study_framework,
-        'research_questions': this_study_research_questions,
-        'interview_guidelines': this_interview_questions
-
-    }
-
-    return this_study_repository.update_study(study_id=this_study_obj._id, updated_data=updated_items)
-
-
-def show_interview_link_markdown(
-        this_study_obj,
-):
-    if hasattr(this_study_obj, "interview_url") and len(this_study_obj.interview_url) >= 5:
-        study_url = this_study_obj.interview_url
-    else:
-        study_url = create_link_for_real_interviews(str(this_study_obj._id))
-
-    study_markdown = f"""
-    
-    Please ask your participants to do the following:
-    
-    1.Go to  https://www.qualz.net
-    
-    2.Scroll down to Demos and Interview section
-    
-    3. Enter their email address in the 'username'
-    
-    4. Enter this code in the password section: {str(this_study_obj._id)}
-    
-    As people complete interviews, it will appear here."""
-    return study_markdown, ""
-
-
-def add_framework_details(dropdown_choice):
-    return FRAMEWORK_CHOICES.get(dropdown_choice)['Description']
-
-
-def guess_study_objective(study_access_obj,
-                          this_study_descriptive_name,
-                          this_topic,
-                          this_objective):
-    print(this_study_descriptive_name, this_topic, this_objective)
-
-    if not len(this_study_descriptive_name) or not len(this_topic) or not len(this_objective):
-        return study_access_obj, "", "To get suggestions on objective, please provide ALL of study name" \
-                                     "topic and jot down your initial thoughts for study objective",
-
-    else:
-        study_objective, study_reasoning = study_access_obj.chat_handler.guess_study_objective(
-            research_name=this_study_descriptive_name,
-            research_topic=this_topic,
-            study_objective_draft_or_instructions=this_objective)
-        # some magic buttons are available in the factory method as well as the study object
-        # if study object is the caller, update the in memory version of the study
-        # todo write this back to the study! by a direct access pattern
-        # if type(study_access_obj) == Study:
-        #     study_access_obj.study_objective = study_objective
-        return study_access_obj, study_objective, study_reasoning
-
-
-
-
-def start_synthetic_interviews(this_study_obj):
-    if not this_study_obj:
-        return this_study_obj, "Please select a study"
-    if not this_study_obj.synthetic_panel_pending_interviews or not len(this_study_obj.synthetic_panel_pending_interviews):
-        return this_study_obj, "Please create a panel before starting the interview process"
-
-    this_status_msg = f"Started conducting interviews with {len(this_study_obj.synthetic_panel_pending_interviews)} " \
-                      f"panelists. Please check back on this study after 15-20 minutes" \
-                      f"If registered for email updates, you will receive an email update when synthetic interviews" \
-                      f"are complete."
-    return this_status_msg
-
-def guess_best_study_framework(
-        study_access_obj,
-        this_study_descriptive_name,
-        this_topic,
-        this_objective):
-    if not len(this_study_descriptive_name) or not len(this_topic) or not len(this_objective):
-        return study_access_obj, "", "To get suggestions on theoretical framework, please provide ALL of study " \
-                                     "name, " \
-                                     "topic and jot down your initial thoughts for study objective. " \
-                                     "The more details you have the better",
-
-    else:
-        study_framework_suggestion, framework_suggestion_reasoning = \
-            study_access_obj.chat_handler.guess_theoretical_framework(
-                research_name=this_study_descriptive_name,
-                research_topic=this_topic,
-                research_objective=this_objective)
-        # if type(study_access_obj) == Study:
-        #     study_access_obj.study_objective = study_framework_suggestion
-        return study_access_obj, study_framework_suggestion, framework_suggestion_reasoning
-
-
-def guess_interview_guidelines(
-        study_access_obj,
-        this_study_topic,
-        this_study_objective,
-        this_study_framework,
-        this_study_research_questions,
-        this_interview_guidelines_draft
-
-):
-    if not len(this_study_topic) or not len(this_study_objective) or not len(this_study_framework) or not len(
-            this_study_research_questions) or not len(this_interview_guidelines_draft):
-        return "", "To get suggestions on interview script, please provide ALL of study " \
-                   "please provide a few lines of initial draft or instructions AND ensure ALL of " \
-                   "the other fields above are written out well",
-    else:
-        this_interview_script, this_interview_script_details = \
-            study_access_obj.chat_handler.guess_interview_guidelines(
-                research_topic=this_study_topic,
-                research_objective=this_study_objective,
-                research_framework=this_study_framework,
-                research_questions=this_study_research_questions,
-                interview_guidelines_draft_or_instructions=this_interview_guidelines_draft
-            )
-        # if type(study_access_obj) == Study:
-        #     study_access_obj.study_objective = study_framework_suggestion
-        return this_interview_script, this_interview_script_details
-
-
-def get_generic_markdown(data, indent=0) -> str:
-    markdown_text = ""
-    if isinstance(data, list):
-        for item in data:
-            markdown_text += "  " * indent + "- " + get_generic_markdown(item, indent + 1) + "\n"
-    elif isinstance(data, dict):
-        for key, value in data.items():
-            markdown_text += "  " * indent + f"**{key}:** " + get_generic_markdown(value, indent + 1) + "\n"
-    else:
-        markdown_text += str(data)
-    return markdown_text
-
-
-def create_modify_synthetic_panel(study_access_obj, m_panel_creation_instructions, m_num_panelists):
-    if not study_access_obj:
-        return study_access_obj, "", "Please select a study"
-
-    m_synthetic_panelists, rationale, discussion = study_access_obj.chat_handler.create_synthetic_panel(
-        research_topic=study_access_obj.study_topic,
-        research_objective=study_access_obj.study_objective,
-        research_framework=study_access_obj.study_framework,
-        instructions=m_panel_creation_instructions,
-        num_panelists=int(m_num_panelists))
-    study_access_obj.synthetic_panel_pending_interviews = m_synthetic_panelists
-    markdown_string = get_generic_markdown([m_synthetic_panelists, rationale, discussion])
-    return study_access_obj, markdown_string, "Created new synthetic panel, you can save it for later or start interviews"
-
-
-def guess_some_research_questions(study_access_obj,
-                                  this_study_descriptive_name,
-                                  this_topic,
-                                  this_objective,
-                                  this_framework,
-                                  this_research_questions):
-    # if not study_access_obj:
-    #     return study_access_obj, "", "",
-    if not len(this_study_descriptive_name) or not len(this_topic) or not len(this_objective) or not len(
-            this_framework) or not len(this_research_questions):
-        return study_access_obj, "", "To get suggestions on research questions  ALL of study name, " \
-                                     "topic, objectives, and theoretical framework" \
-                                     " and jot down your initial thoughts for research questions objective. " \
-                                     "The more details you have the better",
-
-    else:
-        research_questions, reasoning = study_access_obj.chat_handler.guess_research_questions(
-            research_name=this_study_descriptive_name,
-            research_topic=this_topic,
-            research_objective=this_objective,
-            research_framework=this_framework,
-            research_questions_draft=this_research_questions)
-        return study_access_obj, research_questions, reasoning
-
-
-def create_new_study_fn(
-        study_repository_obj,
-        this_study_descriptive_name,
-        this_topic,
-        this_objective,
-        this_framework,
-        this_research_questions
-):
-    if not len(this_study_descriptive_name) or not len(this_topic) or not len(this_objective) or not len(
-            this_framework) or not len(this_research_questions):
-        return "Study Creation failed, all fields above are mandatory", study_repository_obj
-    else:
-
-        study_id = study_repository_obj.create_study({"study_descriptive_name": this_study_descriptive_name,
-                                                      "study_topic": this_topic,
-                                                      "study_objective": this_objective,
-                                                      "study_framework": this_framework,
-                                                      "research_questions": this_research_questions,
-                                                      })
-        return f"New Study with id: {str(study_id)} created. You can now access it in existing studies tab on top", \
-            study_repository_obj
-
-
-def show_existing_study_fields(this_study_obj):
-    this_synthetic_panel_markdown = get_generic_markdown(
-        {'Panelists': this_study_obj.synthetic_panel_pending_interviews,
-         'Reason': "",
-         'Discussion': ""})
-
-    return this_study_obj, this_study_obj._id, this_study_obj.study_descriptive_name, this_study_obj.study_topic,\
-        this_study_obj.study_objective, \
-        this_study_obj.study_framework, this_study_obj.research_questions, this_study_obj.interview_guidelines, \
-        this_synthetic_panel_markdown, ""
-
-
-def get_dropdown_choices(dropdown_choices_study_repository_obj=None):
-    accessed_during_page_load = False
-    if not dropdown_choices_study_repository_obj:
-        accessed_during_page_load = True
-        dropdown_choices_study_repository_obj = StudyRepository()
-    # creating a new repository object as state might not be initialized
-    existing_studies = dropdown_choices_study_repository_obj.get_studies(user_id=USER_ID,
-                                                                         to_filter_by_user_id=TO_FILTER_STUDIES_BY_USERID)
-    _ids = [st['_id'] for st in existing_studies]
-    _descriptions = [st['study_descriptive_name'] for st in existing_studies]
-    this_choices = [f"{str(_id)}:{desc}" for _id, desc in zip(_ids, _descriptions)]
-
-    # workaround for first page load the repository object may not be initialized
-    if accessed_during_page_load:
-        return this_choices
-    else:
-        return gr.Dropdown.update(choices=this_choices)
-
-
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown(f"Welcome to QualZ. I am your friendly A.I. Assistant for research. "
-                f"Go through the various tabs to select a topic to start researching!")
-    view_study_repository = gr.State(value=StudyRepository())
-    # existing_studies_dropdown_choices = get_dropdown_choices()
-    view_active_study = gr.State(value=None)
-    with gr.Tab("+ New Study"):
-        with gr.Row():
-            with gr.Column():
-                new_study_descriptive_name = gr.Textbox(label="New Research Name",
-                                                        placeholder="Give your study a memorable name to refer it by")
-
-                new_study_topic = gr.Textbox(label="Study Topic",
-                                             placeholder="Give your study a topic")
-
-                new_study_objective_details = gr.Markdown("Jot down your thoughts and let Qualz suggestions")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        new_study_objective = gr.Textbox(label="Study objective",
-                                                         placeholder="Briefly describe the main aim of this study...")
-                    with gr.Column(scale=1):
-                        new_study_objective_magic = gr.Button(value="💫")
-
-                new_framework_details = gr.Markdown(
-                    value="These are broad categories and can serve as a starting point. "
-                          "Depending on the specific nature and goals of your research, "
-                          "you might choose to narrow down or further specify these choices.")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        new_study_framework = gr.Dropdown(choices=[
-                            "Ethnographic", "Narrative", "Grounded Theory", "Case Study", "Phenomenological",
-                            "Exploratory"
-                        ], label="Choose a theoretical framework")
-                    with gr.Column(scale=1):
-                        new_framework_selection_magic = gr.Button(value="💫")
-
-                new_research_question_details = gr.Markdown(
-                    value="Jot down your thoughts and click to see suggestions",
-                    label="About Study Framework Choice")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        new_study_research_questions = gr.TextArea(
-                            value="What are some research questions you have ? It is best to start with "
-                                  "a few and expand on it later as new information becomes available",
-                            label="Research Questions"
-                        )
-                    with gr.Column(scale=1):
-                        new_research_questions_magic = gr.Button(value="💫")
-
-                create_new_study = gr.Button(value="Create New Study", variant="primary")
-                new_status_update = gr.Textbox(label="Status")
-                new_study_framework.select(add_framework_details,
-                                           inputs=[new_study_framework],
-                                           outputs=[new_framework_details])
-
-                new_study_objective_magic.click(guess_study_objective,
-                                                inputs=[
-                                                    view_study_repository,
-                                                    new_study_descriptive_name,
-                                                    new_study_topic,
-                                                    new_study_objective],
-                                                outputs=[view_study_repository,
-                                                         new_study_objective,
-                                                         new_study_objective_details])
-
-                new_framework_selection_magic.click(guess_best_study_framework,
-                                                    inputs=[view_study_repository,
-                                                            new_study_descriptive_name, new_study_topic,
-                                                            new_study_objective],
-                                                    outputs=[view_study_repository,
-                                                             new_study_framework, new_framework_details])
-
-                new_research_questions_magic.click(guess_some_research_questions,
-                                                   inputs=[view_study_repository,
-                                                           new_study_descriptive_name, new_study_topic,
-                                                           new_study_objective, new_study_framework,
-                                                           new_study_research_questions],
-                                                   outputs=[view_study_repository,
-                                                            new_study_research_questions, new_research_question_details]
-                                                   )
-                create_new_study.click(create_new_study_fn,
-                                       inputs=[view_study_repository,
-                                               new_study_descriptive_name, new_study_topic,
-                                               new_study_objective, new_study_framework,
-                                               new_study_research_questions
-                                               ],
-                                       outputs=[
-                                           new_status_update, view_study_repository
-                                       ])
-    with gr.Tab(" Existing Study"):
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    with gr.Column(scale=5):
-                        gr.Markdown("Choose existing study")
-                    with gr.Column(scale=2):
-                        refresh_studies = gr.Button("Refresh")
-                study_choice_dropdown = gr.Dropdown(
-                    choices=get_dropdown_choices(None),
-                    label="Choose a study", interactive=True)
-
-        with gr.Tab("+ Add Details"):
-            existing_study_id = gr.Textbox(label="Study ID")
-            existing_study_descriptive_name = gr.Textbox(label="Descriptive Name", interactive=True)
-            existing_study_topic = gr.Textbox(label="Study Topic", interactive=True)
-
-            with gr.Accordion('Modify Existing Details:', open=False):
-                existing_study_objective_details = gr.Markdown("Jot down your thoughts and let Qualz give suggestions")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        existing_study_objective = gr.Textbox(label="Study objective",
-                                                              placeholder="Briefly describe the main aim of this study...")
-                    with gr.Column(scale=1):
-                        existing_study_objective_magic = gr.Button(value="💫")
-
-                existing_framework_details = gr.Markdown(
-                    value="These are broad categories and can serve as a starting point. "
-                          "Depending on the specific nature and goals of your research, "
-                          "you might choose to narrow down or further specify these choices.")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        existing_study_framework = gr.Dropdown(choices=[
-                            "Ethnographic", "Narrative", "Grounded Theory", "Case Study", "Phenomenological",
-                            "Exploratory"
-                        ], label="Choose a theoretical framework")
-                    with gr.Column(scale=1):
-                        existing_framework_selection_magic = gr.Button(value="💫")
-
-                existing_research_question_details = gr.Markdown(
-                    value="Jot down your thoughts and click to see suggestions",
-                    label="About Study Framework Choice")
-                with gr.Row():
-                    with gr.Column(scale=25):
-                        existing_study_research_questions = gr.TextArea(
-                            value="What are some research questions you have ? It is best to start with "
-                                  "a few and expand on it later as new information becomes available",
-                            label="Research Questions"
-                        )
-                    with gr.Column(scale=1):
-                        existing_research_questions_magic = gr.Button(value="💫")
-
-            interview_script_details = gr.Markdown(
-                value="Create a numbered outline of questions to ask, or give instructions about this and "
-                      "click the magic button to create guideline questions according to all study details",
-                label=" Interview Guidelines")
-            with gr.Row():
-                with gr.Column(scale=25):
-                    interview_script_guideline = gr.TextArea(
-                        value="Start with some questions you would like to ask, or enter instructions"
-                              "for creating the guiding questions. ",
-                        label="Interview Guideline"
-                    )
-                with gr.Column(scale=1):
-                    interview_script_guideline_magic = gr.Button(value="💫")
-            existing_update_study_btn = gr.Button(value="Update study Details", variant="primary")
-            existing_delete_study_btn = gr.Button(value="Delete Study", variant="secondary")
-        with gr.Tab("Interviews"):
-            with gr.Tab("Human Interviews"):
-                ai_personality = gr.Dropdown(value="Rachel", choices=list(AI_PERSONALITIES.keys()),
-                                             label="Select AI Personality to conduct interviews. "
-                                                   "Selection will determine voice that you can preview below",
-                                             interactive=True)
-                interview_duration = gr.Slider(minimum=10, maximum=120, value=30, step=10,
-                                               label="Intended duration of interview ")
-
-                existing_interview_link_markdown = gr.Markdown(f"""
-                Your Study link will appear here after an interview script is created! 
-                """)
-            with gr.Tab("Synthetic Interviews"):
-                with gr.Row():
-                    with gr.Column():
-                        number_of_synth_panelists = gr.Number(label="Number of Panelists", value=5)
-                        panel_creation_instructions = gr.Text(label="Panel Creation Instructions",
-                                                              placeholder=
-                                                              "Enter helpful instructions for panel creation")
-                        create_synthetic_interviewers_button = gr.Button(value="Create/Update a panel",
-                                                                         variant="primary")
-                        cost_estimate = gr.Label("Cost Estimate: $5")
-
-                    with gr.Column():
-                        # todo refactor name
-                        synthetic_panelists_markdown = gr.Markdown("Suggested panelists will appear here")
-
-                        # synthetic_panelist_1 = gr.TextArea("ID: 123123; Name: Francis Age: 55, Gender: Male,"
-                        #                                "Sector: Large Enterprise, "
-                        #                                "Bio: Francis is a market director drawn to this field out of a "
-                        #                                "fascination with consumer behavior and a desire to influence"
-                        #
-                        #                               "business strategy", interactive=False, label="1", lines=3)
-                        # synthetic_panelists_desc_text_areas = []
-                        # for i in range(15):
-                        #     a = gr.TextArea("ID: 123123; Name: Francis Age: 55, Gender: Male,"
-                        #                     "Sector: Large Enterprise, "
-                        #                     "Bio: Francis is a market director drawn to this field out of a "
-                        #                     "fascination with consumer behavior and a desire to influence"
-                        #                     "business strategy", interactive=False, label=str(i), lines=3)
-                        #     synthetic_panelists_desc_text_areas.append(a)
-                        # synthetic_panelists_desc_text_areas.append(view_active_study)
-
-                with gr.Row():
-                    save_panelists_to_db_button = gr.Button(value="Save current panelists",
-                                                            variant="secondary")
-                    start_synthetic_interviews_button = gr.Button(value="Start Synthetic Interviews (Auto saves)",
-                                                                  variant="primary")
-
-                # with gr.Row():
-                #     synthetic_interview_status = gr.Textbox(label="Status")
-
-        with gr.Tab("2. Interview Analysis"):
-            pass
-        with gr.Tab("3. Interpretation"):
-            pass
-        with gr.Row():
-            existing_status_update = gr.Textbox(label="Status")
-
-    start_synthetic_interviews_button.click(start_synthetic_interviews,
-                                            inputs=[view_active_study],
-                                            outputs=[view_active_study, existing_status_update])
-    save_panelists_to_db_button.click(save_synthetic_panelists,
-                                      inputs=[view_active_study, view_study_repository],
-                                      outputs=[existing_status_update])
-    study_choice_dropdown.select(set_active_study,
-                                 inputs=[view_study_repository,
-                                         study_choice_dropdown],
-                                 outputs=[view_active_study, existing_status_update], queue=False).then(
-        show_existing_study_fields,
-        inputs=[view_active_study],
-        outputs=[view_active_study,
-                 existing_study_id,
-                 existing_study_descriptive_name,
-                 existing_study_topic,
-                 existing_study_objective,
-                 existing_study_framework,
-                 existing_study_research_questions,
-                 interview_script_guideline,
-                 synthetic_panelists_markdown,
-                 existing_status_update
-                 ]
-    ).then(
-        show_interview_link_markdown,
-        inputs=[view_active_study],
-        outputs=[existing_interview_link_markdown, existing_status_update]
-    )
-    refresh_studies.click(get_dropdown_choices, inputs=[view_study_repository], outputs=[study_choice_dropdown])
-    existing_study_objective_magic.click(guess_study_objective,
-                                         inputs=[
-                                             view_active_study,
-                                             existing_study_descriptive_name,
-                                             existing_study_topic,
-                                             existing_study_objective],
-                                         outputs=[view_active_study,
-                                                  existing_study_objective,
-                                                  existing_study_objective_details])
-
-    existing_framework_selection_magic.click(guess_best_study_framework,
-                                             inputs=[view_active_study,
-                                                     existing_study_descriptive_name, existing_study_topic,
-                                                     existing_study_objective],
-                                             outputs=[view_active_study,
-                                                      existing_study_framework, existing_framework_details])
-
-    existing_research_questions_magic.click(guess_some_research_questions,
-                                            inputs=[view_active_study,
-                                                    existing_study_descriptive_name, existing_study_topic,
-                                                    existing_study_objective, existing_study_framework,
-                                                    existing_study_research_questions],
-                                            outputs=[view_active_study,
-                                                     existing_study_research_questions,
-                                                     existing_research_question_details]
-                                            )
-    create_synthetic_interviewers_button.click(create_modify_synthetic_panel,
-                                               inputs=[
-                                                   view_active_study,
-                                                   panel_creation_instructions,
-                                                   number_of_synth_panelists,
-                                               ],
-                                               outputs=[
-                                                   view_active_study,
-                                                   synthetic_panelists_markdown,
-                                                   existing_status_update
-                                               ])
-    interview_script_guideline_magic.click(
-        guess_interview_guidelines,
-        inputs=[
-            view_active_study,
-            existing_study_topic,
-            existing_study_objective,
-            existing_study_framework,
-            existing_study_research_questions,
-            interview_script_guideline
-        ],
-        outputs=[
-            interview_script_guideline,
-            interview_script_details
-        ]
-    )
-    existing_update_study_btn.click(update_study,
-                                    inputs=[view_active_study,
-                                            view_study_repository,
-                                            existing_study_descriptive_name, existing_study_topic,
-                                            existing_study_objective, existing_study_framework,
-                                            existing_study_research_questions,
-                                            interview_script_guideline
-                                            ],
-                                    outputs=[
-                                        existing_status_update
-                                    ])
-    existing_delete_study_btn.click(delete_study,
-                                    inputs=[view_active_study,
-                                            view_study_repository
-                                            ],
-                                    outputs=[
-                                        existing_status_update
-                                    ])
-if __name__ == "__main__":
-    _ = load_dotenv(find_dotenv())
-    openai.api_key = os.getenv('OPENAI_API_KEY')
-    demo.queue(concurrency_count=10).launch(server_port=7860, share=True, auth=check_credentials)