Update templates/data_file.py

templates/data_file.py

@@ -1,136 +1,136 @@
-import gradio as gr
-from functions import example_question_generator, chatbot_func
-from data_sources import process_data_upload
-from utils import message_dict
-import ast
-
-def run_example(input):
-    return input
-
-def example_display(input):
-    if input == None:
-        display = True
-    else:
-        display = False
-    return [gr.update(visible=display),gr.update(visible=display),gr.update(visible=display),gr.update(visible=display)]
-
-with gr.Blocks() as demo:
-    description = gr.HTML("""
-                        <!-- Header -->
-                        <div class="max-w-4xl mx-auto mb-12 text-center">
-                            <div class="bg-blue-50 border border-blue-200 rounded-lg max-w-2xl mx-auto">
-                                <h2 class="font-semibold text-blue-800 ">
-                                    <i class="fas fa-info-circle mr-2"></i>Supported Files
-                                </h2>
-                                <div class="flex flex-wrap justify-center gap-3 pb-4 text-blue-700">
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-csv mr-1"></i>CSV
-                                        <span class="tooltip-text">Comma-separated values</span>
-                                    </span>
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-alt mr-1"></i>TSV
-                                        <span class="tooltip-text">Tab-separated values</span>
-                                    </span>
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-alt mr-1"></i>TXT
-                                        <span class="tooltip-text">Text files</span>
-                                    </span>
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-excel mr-1"></i>XLS/XLSX
-                                        <span class="tooltip-text">Excel spreadsheets</span>
-                                    </span>
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-code mr-1"></i>XML
-                                        <span class="tooltip-text">XML documents</span>
-                                    </span>
-                                    <span class="tooltip">
-                                        <i class="fas fa-file-code mr-1"></i>JSON
-                                        <span class="tooltip-text">JSON data files</span>
-                                    </span>
-                                </div>
-                            </div>
-                        </div>
-                          """, elem_classes="description_component")
-    example_file_1 = gr.File(visible=False, value="samples/bank_marketing_campaign.csv")
-    example_file_2 = gr.File(visible=False, value="samples/online_retail_data.csv")
-    example_file_3 = gr.File(visible=False, value="samples/tb_illness_data.csv")
-    with gr.Row():
-        example_btn_1 = gr.Button(value="Try Me: bank_marketing_campaign.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
-        example_btn_2 = gr.Button(value="Try Me: online_retail_data.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
-        example_btn_3 = gr.Button(value="Try Me: tb_illness_data.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
-
-    file_output = gr.File(label="Data File (CSV, TSV, TXT, XLS, XLSX, XML, JSON)", show_label=True, elem_classes="file_marker drop-zone border-2 border-dashed border-gray-300 rounded-lg hover:border-primary cursor-pointer bg-gray-50 hover:bg-blue-50 transition-colors duration-300", file_types=['.csv','.xlsx','.txt','.json','.ndjson','.xml','.xls','.tsv'])
-    example_btn_1.click(fn=run_example, inputs=example_file_1, outputs=file_output)
-    example_btn_2.click(fn=run_example, inputs=example_file_2, outputs=file_output)
-    example_btn_3.click(fn=run_example, inputs=example_file_3, outputs=file_output)
-    file_output.change(fn=example_display, inputs=file_output, outputs=[example_btn_1, example_btn_2, example_btn_3, description])
-
-    @gr.render(inputs=file_output)
-    def data_options(filename, request: gr.Request):
-        print(filename)
-        if request.session_hash not in message_dict:
-            message_dict[request.session_hash] = {}
-        message_dict[request.session_hash]['file_upload'] = None
-        if filename:
-            process_message = process_upload(filename, request.session_hash)
-            gr.HTML(value=process_message[1], padding=False)
-            if process_message[0] == "success":
-                if "bank_marketing_campaign" in filename:
-                    example_questions = [
-                                            ["Describe the dataset"],
-                                            ["What levels of education have the highest and lowest average balance?"],
-                                            ["What job is most and least common for a yes response from the individuals, not counting 'unknown'?"],
-                                            ["Can you generate a bar chart of education vs. average balance?"],
-                                            ["Can you generate a table of levels of education versus average balance, percent married, percent with a loan, and percent in default?"],
-                                            ["Can we predict the relationship between the number of contacts performed before this campaign and the average balance?"],
-                                            ["Can you plot the number of contacts performed before this campaign versus the duration and use balance as the size in a bubble chart?"]
-                                        ]
-                elif "online_retail_data" in filename:
-                    example_questions = [
-                                            ["Describe the dataset"],
-                                            ["What month had the highest revenue?"],
-                                            ["Is revenue higher in the morning or afternoon?"],
-                                            ["Can you generate a line graph of revenue per month?"],
-                                            ["Can you generate a table of revenue per month?"],
-                                            ["Can we predict how time of day affects transaction value in this data set?"],
-                                            ["Can you plot revenue per month with size being the number of units sold that month in a bubble chart?"]
-                                        ]
-                else:
-                    try:
-                        generated_examples = ast.literal_eval(example_question_generator(request.session_hash, 'file_upload', '', process_message[1], ''))
-                        example_questions = [
-                                                ["Describe the dataset"]
-                                            ]
-                        for example in generated_examples:
-                            example_questions.append([example])
-                    except Exception as e:
-                        print("DATA FILE QUESTION GENERATION ERROR")
-                        print(e)
-                        example_questions = [
-                                            ["Describe the dataset"],
-                                            ["List the columns in the dataset"],
-                                            ["What could this data be used for?"],
-                                        ]
-                session_hash = gr.Textbox(visible=False, value=request.session_hash)
-                data_source = gr.Textbox(visible=False, value='file_upload')
-                schema = gr.Textbox(visible=False, value='')
-                titles = gr.Textbox(value=process_message[1], interactive=False, visible=False)
-                bot = gr.Chatbot(type='messages', label="CSV Chat Window", render_markdown=True, sanitize_html=False, show_label=True, render=False, visible=True, elem_classes="chatbot")
-                chat = gr.ChatInterface(
-                                    fn=chatbot_func,
-                                    type='messages',
-                                    chatbot=bot,
-                                    title="Chat with your data file",
-                                    concurrency_limit=None,
-                                    examples=example_questions,
-                                    additional_inputs=[session_hash, data_source, titles, schema]
-                                    )
-                
-    def process_upload(upload_value, session_hash):
-        if upload_value:
-            process_message = process_data_upload(upload_value, session_hash)
-        return process_message
-                    
-
-if __name__ == "__main__":
+import gradio as gr
+from functions import example_question_generator, chatbot_func
+from data_sources import process_data_upload
+from utils import message_dict
+import ast
+
+def run_example(input):
+    return input
+
+def example_display(input):
+    if input == None:
+        display = True
+    else:
+        display = False
+    return [gr.update(visible=display),gr.update(visible=display),gr.update(visible=display),gr.update(visible=display)]
+
+with gr.Blocks() as demo:
+    description = gr.HTML("""
+                        <!-- Header -->
+                        <div class="max-w-4xl mx-auto mb-12 text-center">
+                            <div class="bg-blue-50 border border-blue-200 rounded-lg max-w-2xl mx-auto">
+                                <h2 class="font-semibold text-blue-800 ">
+                                    <i class="fas fa-info-circle mr-2"></i>Supported Files
+                                </h2>
+                                <div class="flex flex-wrap justify-center gap-3 pb-4 text-blue-700">
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-csv mr-1"></i>CSV
+                                        <span class="tooltip-text">Comma-separated values</span>
+                                    </span>
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-alt mr-1"></i>TSV
+                                        <span class="tooltip-text">Tab-separated values</span>
+                                    </span>
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-alt mr-1"></i>TXT
+                                        <span class="tooltip-text">Text files</span>
+                                    </span>
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-excel mr-1"></i>XLS/XLSX
+                                        <span class="tooltip-text">Excel spreadsheets</span>
+                                    </span>
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-code mr-1"></i>XML
+                                        <span class="tooltip-text">XML documents</span>
+                                    </span>
+                                    <span class="tooltip">
+                                        <i class="fas fa-file-code mr-1"></i>JSON
+                                        <span class="tooltip-text">JSON data files</span>
+                                    </span>
+                                </div>
+                            </div>
+                        </div>
+                          """, elem_classes="description_component")
+    example_file_1 = gr.File(visible=False, value="samples/bank_marketing_campaign.csv")
+    example_file_2 = gr.File(visible=False, value="samples/online_retail_data.csv")
+    example_file_3 = gr.File(visible=False, value="samples/tb_illness_data.csv")
+    with gr.Row():
+        example_btn_1 = gr.Button(value="Try Me: bank_marketing_campaign.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
+        example_btn_2 = gr.Button(value="Try Me: online_retail_data.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
+        example_btn_3 = gr.Button(value="Try Me: tb_illness_data.csv", elem_classes="sample-btn bg-gradient-to-r from-purple-500 to-indigo-600 text-white p-6 rounded-lg text-left hover:shadow-lg", size="md", variant="primary")
+
+    file_output = gr.File(label="Data File (CSV, TSV, TXT, XLS, XLSX, XML, JSON)", show_label=True, elem_classes="file_marker drop-zone border-2 border-dashed border-gray-300 rounded-lg hover:border-primary cursor-pointer bg-gray-50 hover:bg-blue-50 transition-colors duration-300", file_types=['.csv','.xlsx','.txt','.json','.ndjson','.xml','.xls','.tsv'])
+    example_btn_1.click(fn=run_example, inputs=example_file_1, outputs=file_output)
+    example_btn_2.click(fn=run_example, inputs=example_file_2, outputs=file_output)
+    example_btn_3.click(fn=run_example, inputs=example_file_3, outputs=file_output)
+    file_output.change(fn=example_display, inputs=file_output, outputs=[example_btn_1, example_btn_2, example_btn_3, description])
+
+    @gr.render(inputs=file_output)
+    def data_options(filename, request: gr.Request):
+        print(filename)
+        if request.session_hash not in message_dict:
+            message_dict[request.session_hash] = {}
+        message_dict[request.session_hash]['file_upload'] = None
+        if filename:
+            process_message = process_upload(filename, request.session_hash)
+            gr.HTML(value=process_message[1], padding=False)
+            if process_message[0] == "success":
+                if "bank_marketing_campaign" in filename:
+                    example_questions = [
+                                            ["Describe the dataset"],
+                                            ["What levels of education have the highest and lowest average balance?"],
+                                            ["What job is most and least common for a yes response from the individuals, not counting 'unknown'?"],
+                                            ["Can you generate a bar chart of education vs. average balance?"],
+                                            ["Can you generate a table of levels of education versus average balance, percent married, percent with a loan, and percent in default?"],
+                                            ["Can we predict the relationship between the number of contacts performed before this campaign and the average balance?"],
+                                            ["Can you plot the number of contacts performed before this campaign versus the duration and use balance as the size in a bubble chart?"]
+                                        ]
+                elif "online_retail_data" in filename:
+                    example_questions = [
+                                            ["Describe the dataset"],
+                                            ["What month had the highest revenue?"],
+                                            ["Is revenue higher in the morning or afternoon?"],
+                                            ["Can you generate a line graph of revenue per month?"],
+                                            ["Can you generate a table of revenue per month?"],
+                                            ["Can we predict how time of day affects transaction value in this data set?"],
+                                            ["Can you plot revenue per month with size being the number of units sold that month in a bubble chart?"]
+                                        ]
+                else:
+                    try:
+                        generated_examples = ast.literal_eval(example_question_generator(request.session_hash, 'file_upload', '', process_message[1], ''))
+                        example_questions = [
+                                                ["Describe the dataset"]
+                                            ]
+                        for example in generated_examples:
+                            example_questions.append([example])
+                    except Exception as e:
+                        print("DATA FILE QUESTION GENERATION ERROR")
+                        print(e)
+                        example_questions = [
+                                            ["Describe the dataset"],
+                                            ["List the columns in the dataset"],
+                                            ["What could this data be used for?"],
+                                        ]
+                session_hash = gr.Textbox(visible=False, value=request.session_hash)
+                data_source = gr.Textbox(visible=False, value='file_upload')
+                schema = gr.Textbox(visible=False, value='')
+                titles = gr.Textbox(value=process_message[2], interactive=False, visible=False)
+                bot = gr.Chatbot(type='messages', label="CSV Chat Window", render_markdown=True, sanitize_html=False, show_label=True, render=False, visible=True, elem_classes="chatbot")
+                chat = gr.ChatInterface(
+                                    fn=chatbot_func,
+                                    type='messages',
+                                    chatbot=bot,
+                                    title="Chat with your data file",
+                                    concurrency_limit=None,
+                                    examples=example_questions,
+                                    additional_inputs=[session_hash, data_source, titles, schema]
+                                    )
+                
+    def process_upload(upload_value, session_hash):
+        if upload_value:
+            process_message = process_data_upload(upload_value, session_hash)
+        return process_message
+                    
+
+if __name__ == "__main__":
     demo.launch()