Upload functions

app/draw_diagram.py

@@ -0,0 +1,556 @@
+import streamlit as st
+import pandas as pd
+import numpy as np
+from streamlit_echarts import st_echarts
+# from streamlit_echarts import JsCode
+from streamlit_javascript import st_javascript
+# from PIL import Image 
+
+links_dic = {
+    "Meta-Llama-3-8B-Instruct": 'https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct', 
+    "Meta-Llama-3-70B-Instruct": 'https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct',
+    "Meta-Llama-3-8B": "https://huggingface.co/meta-llama/Meta-Llama-3-8B"
+}
+
+
+# huggingface_image = Image.open('style/huggingface.jpg')
+
+def nav_to(url):
+    # print(url)
+    js = f'window.open("{url}", "_blank").then(r => window.parent.location.href);'
+    st_javascript(js)
+
+    # nav_script = """
+    #     <meta http-equiv="refresh" content="0; url='%s'">
+    # """ % (url)
+    # st.write(nav_script, unsafe_allow_html=True)
+
+def highlight_table_line(model_name):
+
+    st.write(model_name)
+
+
+def draw_cross_lingual(category_one, category_two, sort, sorted):
+
+    folder = "./results/cross_lingual/"
+    subtitle = ''
+    data_path = f'{folder}/{category_one}/{category_two}.csv'
+    chart_data = pd.read_csv(data_path).dropna(axis='columns').round(2)
+
+    if sorted == 'Ascending':
+        ascend = True 
+    else:
+        ascend = False
+    
+    chart_data = chart_data.sort_values(by=[sort], ascending=ascend)
+
+    min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1) 
+    max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1) 
+
+    if category_two in ['cross_mmlu', 'cross_logiqa']:  
+        # print(category_two)
+        
+        if category_two == 'cross_mmlu':
+            subtitle = 'Cross-MMLU'
+        
+        elif category_two == 'cross_logiqa':
+            subtitle = 'Cross-LogiQA'
+        
+        options = {
+            "title": {"text": f"{subtitle}"},
+            "tooltip": {
+                "trigger": "axis",
+                "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+                "triggerOn": 'mousemove',
+            },
+            "legend": {"data": ['Overall Accuracy','Cross-Lingual Consistency', 'AC3',
+                                'English', 'Chinese', 'Spanish', 'Vietnamese', 'Indonesian', 'Malay', 'Filipino']},
+            "toolbox": {"feature": {"saveAsImage": {}}},
+            "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+            "xAxis": [
+                {
+                    "type": "category",
+                    "boundaryGap": False,
+                    "triggerEvent": True,
+                    "data": chart_data['Model'].tolist(),
+                }
+            ],
+            "yAxis": [{"type": "value", 
+                    "min": min_value,
+                    "max": max_value, 
+                    # "splitNumber": 10
+                    }],
+            "series": [
+                {
+                    "name": "Overall Accuracy",
+                    "type": "line",
+                    "data": chart_data['Accuracy'].tolist(),
+                },
+                {
+                    "name": "Cross-Lingual Consistency",
+                    "type": "line",
+                    "data": chart_data["Cross-Lingual Consistency"].tolist(),
+                },
+                {
+                    "name": "AC3",
+                    "type": "line",
+                    "data": chart_data["AC3"].tolist(),
+                },
+                {
+                    "name": "English",
+                    "type": "line",
+                    "data": chart_data["English"].tolist(),
+                },
+                {
+                    "name": "Chinese",
+                    "type": "line",
+                    "data": chart_data["Chinese"].tolist(),
+                },
+                {
+                    "name": "Spanish",
+                    "type": "line",
+                    "data": chart_data["Spanish"].tolist(),
+                },
+                {
+                    "name": "Vietnamese",
+                    "type": "line",
+                    "data": chart_data["Vietnamese"].tolist(),
+                },
+                {
+                    "name": "Indonesian",
+                    "type": "line",
+                    "data": chart_data["Indonesian"].tolist(),
+                },
+                {
+                    "name": "Malay",
+                    "type": "line",
+                    "data": chart_data["Malay"].tolist(),
+                },
+                {
+                    "name": "Filipino",
+                    "type": "line",
+                    "data": chart_data["Filipino"].tolist(),
+                },
+            ],
+        }
+        
+        events = {
+            "click": "function(params) { return params.value }",
+            # "dblclick": "function(params) { return params.value }"
+        }
+
+        value = st_echarts(options=options, events=events, height="500px")
+
+        
+        if value != None:
+            # print(value)
+            nav_to(links_dic[value])
+        
+        # if value != None:
+        #     highlight_table_line(value)
+
+
+    elif category_two == 'cross_xquad':
+        
+        subtitle = 'Cross-XQUAD'
+
+        options = {
+            "title": {"text": f"{subtitle}"},
+            "tooltip": {
+                "trigger": "axis",
+                "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+                "triggerOn": 'mousemove',
+            },
+            "legend": {"data": ['Overall Accuracy','Cross-Lingual Consistency', 'AC3',
+                                'English', 'Chinese', 'Spanish', 'Vietnamese', 'Indonesian', 'Malay', 'Filipino']},
+            "toolbox": {"feature": {"saveAsImage": {}}},
+            "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+            "xAxis": [
+                {
+                    "type": "category",
+                    "boundaryGap": False,
+                    "data": chart_data['Model'].tolist(),
+                }
+            ],
+            "yAxis": [{"type": "value",
+                    "min": min_value,
+                    "max": max_value, 
+                    # "splitNumber": 10
+                    }],
+            "series": [
+                {
+                    "name": "Overall Accuracy",
+                    "type": "line",
+                    "data": chart_data['Accuracy'].tolist(),
+                },
+                {
+                    "name": "Cross-Lingual Consistency",
+                    "type": "line",
+                    "data": chart_data["Cross-Lingual Consistency"].tolist(),
+                },
+                {
+                    "name": "AC3",
+                    "type": "line",
+                    "data": chart_data["AC3"].tolist(),
+                },
+                {
+                    "name": "English",
+                    "type": "line",
+                    "data": chart_data["English"].tolist(),
+                },
+                {
+                    "name": "Chinese",
+                    "type": "line",
+                    "data": chart_data["Chinese"].tolist(),
+                },
+                {
+                    "name": "Spanish",
+                    "type": "line",
+                    "data": chart_data["Spanish"].tolist(),
+                },
+                {
+                    "name": "Vietnamese",
+                    "type": "line",
+                    "data": chart_data["Vietnamese"].tolist(),
+                },
+            ],
+        }
+
+        events = {
+            "click": "function(params) { return params.value }"
+        }
+
+        value = st_echarts(options=options, events=events, height="500px")
+        
+        if value != None:
+            # print(value)
+            nav_to(links_dic[value])
+
+        # if value != None:
+        #     highlight_table_line(value)
+    
+    ### create table
+    st.divider()
+    # chart_data['Link'] = chart_data['Model'].map(links_dic)
+    st.dataframe(chart_data,
+                #  column_config = {
+                #      "Link": st.column_config.LinkColumn(
+                #          display_text= st.image(huggingface_image)
+                #      ),
+                #  }, 
+                    hide_index = True, 
+                    use_container_width=True)
+    
+    
+
+def draw_only_acc(folder_name, category_one, category_two, sorted):
+    # Cultural Reasonling / General Reasoning / Emotion / Fundamental NLP Tasks
+    
+    folder = f"./results/{folder_name}/"
+    category_two_dict = {}
+    
+    if folder_name == 'cultural_reasoning':
+        category_two_dict = {'SG EVAL': 'sg_eval', 
+                         'US EVAL': 'us_eval', 
+                         'CN EVAL': 'cn_eval', 
+                         'PH EVAL': 'ph_eval'}
+    elif folder_name == 'general_reasoning':
+        category_two_dict = {'MMLU': 'mmlu', 
+                         'C Eval': 'c_eval', 
+                         'CMMLU': 'cmmlu', 
+                         'ZBench': 'zbench', 
+                         'IndoMMLU': 'indommlu'}
+    
+    elif folder_name == 'emotion':
+        category_two_dict = {'Indonesian Emotion  Classification': 'ind_emotion', 
+                             'SST2': 'sst2'}
+    
+    elif folder_name == 'fundamental_nlp_tasks':
+        category_two_dict = {'OCNLI': 'ocnli', 
+                             'C3': 'c3', 
+                             'COLA': 'cola', 
+                             'QQP': 'qqp', 
+                             'MNLI': 'mnli', 
+                             'QNLI': 'qnli', 
+                             'WNLI': 'wnli', 
+                             'RTE': 'rte', 
+                             'MRPC': 'mrpc'}
+    
+    subtitle = category_two_dict[category_two]
+    data_path = f'{folder}/{category_one}/{subtitle}.csv'
+    chart_data = pd.read_csv(data_path).round(2)
+    
+    if sorted == 'Ascending':
+        ascend = True 
+    else:
+        ascend = False
+    
+    chart_data = chart_data.sort_values(by=['Accuracy'], ascending=ascend)
+    
+    min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1) 
+    max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1) 
+
+    options = {
+        "title": {"text": f"{category_two}"},
+        "tooltip": {
+            "trigger": "axis",
+            "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+            "triggerOn": 'mousemove',
+        },
+        "legend": {"data": ['Overall Accuracy']},
+        "toolbox": {"feature": {"saveAsImage": {}}},
+        "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+        "xAxis": [
+            {
+                "type": "category",
+                "boundaryGap": False,
+                "triggerEvent": True,
+                "data": chart_data['Model'].tolist(),
+            }
+        ],
+        "yAxis": [{"type": "value", 
+                    "min": min_value,
+                    "max": max_value, 
+                    # "splitNumber": 10
+                    }],
+        "series": [
+            {
+                "name": "Overall Accuracy",
+                "type": "line",
+                "data": chart_data['Accuracy'].tolist(),
+            },
+
+        ],
+    }
+    
+    events = {
+        "click": "function(params) { return params.value }"
+    }
+
+    value = st_echarts(options=options, events=events, height="500px")
+    
+    if value != None:
+        # print(value)
+        nav_to(links_dic[value])
+
+    # if value != None:
+    #     highlight_table_line(value)
+
+    ### create table
+    st.divider()
+    # chart_data['Link'] = chart_data['Model'].map(links_dic)
+    st.dataframe(chart_data,
+                #  column_config = {
+                #      "Link": st.column_config.LinkColumn(
+                #          display_text= st.image(huggingface_image)
+                #      ),
+                #  }, 
+                    hide_index = True, 
+                    use_container_width=True)
+
+def draw_flores_translation(category_one, category_two, sorted):
+    folder = "./results/flores_translation/"
+    category_two_dict = {'Indonesian to English': 'ind2eng', 
+                         'Vitenamese to English': 'vie2eng', 
+                         'Chinese to English': 'zho2eng', 
+                         'Nalay to English': 'zsm2eng'}
+    
+    subtitle = category_two_dict[category_two]
+    
+    data_path = f'{folder}/{category_one}/{subtitle}.csv'
+    chart_data = pd.read_csv(data_path).round(2)
+
+    if sorted == 'Ascending':
+        ascend = True 
+    else:
+        ascend = False
+    
+    chart_data = chart_data.sort_values(by=['BLEU'], ascending=ascend)
+
+    min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1) 
+    max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1) 
+    
+    options = {
+        "title": {"text": f"{category_two}"},
+        "tooltip": {
+            "trigger": "axis",
+            "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+            "triggerOn": 'mousemove',
+        },
+        "legend": {"data": ['BLEU']},
+        "toolbox": {"feature": {"saveAsImage": {}}},
+        "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+        "xAxis": [
+            {
+                "type": "category",
+                "boundaryGap": False,
+                "triggerEvent": True,
+                "data": chart_data['Model'].tolist(),
+            }
+        ],
+        "yAxis": [{"type": "value", 
+                    "min": min_value,
+                    "max": max_value, 
+                    # "splitNumber": 10
+                    }],
+        "series": [
+            {
+                "name": "BLEU",
+                "type": "line",
+                "data": chart_data['BLEU'].tolist(),
+            },
+
+        ],
+    }
+    
+    events = {
+        "click": "function(params) { return params.value }"
+    }
+
+    value = st_echarts(options=options, events=events, height="500px")
+    
+    if value != None:
+        # print(value)
+        nav_to(links_dic[value])
+
+
+    ### create table
+    st.divider()
+    # chart_data['Link'] = chart_data['Model'].map(links_dic)
+    st.dataframe(chart_data,
+                #  column_config = {
+                #      "Link": st.column_config.LinkColumn(
+                #          display_text= st.image(huggingface_image)
+                #      ),
+                #  }, 
+                    hide_index = True, 
+                    use_container_width=True)
+    
+
+def draw_dialogue(category_one, category_two, sort, sorted):
+    folder = "./results/dialogue"
+    category_two_dict = {'DREAM': 'dream', 
+                         'SAMSum': 'samsum', 
+                         'DialogSum': 'dialogsum'}
+    
+    subtitle = category_two_dict[category_two]
+    
+    data_path = f'{folder}/{category_one}/{subtitle}.csv'
+    chart_data = pd.read_csv(data_path).round(2)
+
+    if sorted == 'Ascending':
+        ascend = True 
+    else:
+        ascend = False
+    
+    chart_data = chart_data.sort_values(by=[sort], ascending=ascend)
+
+    min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1) 
+    max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1) 
+    
+    options = {}
+    if category_two in ['SAMSum', 'DialogSum']:
+        options = {
+            "title": {"text": f"{category_two}"},
+            "tooltip": {
+                "trigger": "axis",
+                "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+                "triggerOn": 'mousemove',
+            },
+            "legend": {"data": list(chart_data.columns)},
+            "toolbox": {"feature": {"saveAsImage": {}}},
+            "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+            "xAxis": [
+                {
+                    "type": "category",
+                    "boundaryGap": False,
+                    "triggerEvent": True,
+                    "data": chart_data['Model'].tolist(),
+                }
+            ],
+            "yAxis": [{"type": "value", 
+                        "min": min_value,
+                        "max": max_value, 
+                        # "splitNumber": 10
+                        }],
+            "series": [
+                {
+                    "name": "Average",
+                    "type": "line",
+                    "data": chart_data['Average'].tolist(),
+                },
+                {
+                    "name": "ROUGE-1",
+                    "type": "line",
+                    "data": chart_data["ROUGE-1"].tolist(),
+                },
+                {
+                    "name": "ROUGE-2",
+                    "type": "line",
+                    "data": chart_data["ROUGE-2"].tolist(),
+                },
+                {
+                    "name": "ROUGE-L",
+                    "type": "line",
+                    "data": chart_data["ROUGE-L"].tolist(),
+                },
+
+            ],
+        }
+    
+    elif category_two == 'DREAM':
+        options = {
+            "title": {"text": f"{category_two}"},
+            "tooltip": {
+                "trigger": "axis",
+                "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
+                "triggerOn": 'mousemove',
+            },
+            "legend": {"data": list(chart_data.columns)},
+            "toolbox": {"feature": {"saveAsImage": {}}},
+            "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
+            "xAxis": [
+                {
+                    "type": "category",
+                    "boundaryGap": False,
+                    "triggerEvent": True,
+                    "data": chart_data['Model'].tolist(),
+                }
+            ],
+            "yAxis": [{"type": "value", 
+                        "min": min_value,
+                        "max": max_value, 
+                        # "splitNumber": 10
+                        }],
+            "series": [
+                {
+                    "name": "Accuracy",
+                    "type": "line",
+                    "data": chart_data['Accuracy'].tolist(),
+                },
+
+            ],
+        }
+
+    events = {
+        "click": "function(params) { return params.value }"
+    }
+
+    value = st_echarts(options=options, events=events, height="500px")
+    
+    if value != None:
+        # print(value)
+        nav_to(links_dic[value])
+
+
+    ### create table
+    st.divider()
+    # chart_data['Link'] = chart_data['Model'].map(links_dic)
+    st.dataframe(chart_data,
+                #  column_config = {
+                #      "Link": st.column_config.LinkColumn(
+                #          display_text= st.image(huggingface_image)
+                #      ),
+                #  }, 
+                    hide_index = True, 
+                    use_container_width=True)

app/pages.py

@@ -0,0 +1,191 @@
+import streamlit as st
+from draw_diagram import *
+
+def dashboard():
+    st.title("SeaEval")
+    
+    """
+    [gh]: https://github.com/SeaEval/SeaEval
+    [![GitHub Repo stars](https://img.shields.io/github/stars/SeaEval/SeaEval?style=social)][gh]
+    """
+
+    seaeval_url = "https://seaeval.github.io/"
+    st.markdown("[SeaEval](%s) is the new benchmark for multilingual foundation models consisting of 28 dataset." % seaeval_url)
+    st.markdown(".... haven't finished yet ...")
+
+def cross_lingual_consistency():
+    st.title("Cross-Lingual Consistency")
+    
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['Cross-MMLU', 'Cross-XQUAD', 'Cross-LogiQA']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+    category_two_dict = {'Cross-MMLU': 'cross_mmlu', 
+                         'Cross-XQUAD': 'cross_xquad', 
+                         'Cross-LogiQA': 'cross_logiqa'}
+
+    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with middle:
+        sort = st.selectbox('Sort', ['Accuracy','Cross-Lingual Consistency', 'AC3',
+                                     'English', 'Chinese', 'Spanish', 'Vietnamese'])
+    with right:
+        sorted = st.selectbox('by', ['Ascending', 'Descending'])
+
+    if category_one or category_two or sort or sorted:
+        category_one = category_one_dict[category_one]
+        category_two = category_two_dict[category_two]
+        
+        draw_cross_lingual(category_one, category_two, sort, sorted)
+    else:
+        draw_cross_lingual('zero_shot', 'cross_mmlu', 'Accuracy', 'Descending')
+
+def cultural_reasoning():
+    st.title("Cultural Reasoning")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['SG EVAL', 'CN EVAL', 'PH EVAL', 'US EVAL']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+
+    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with right:
+        sorted = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sorted:
+        category_one = category_one_dict[category_one]
+        draw_only_acc('cultural_reasoning', category_one, category_two, sorted)
+    else:
+        draw_only_acc('cultural_reasoning', 'zero_shot', 'sg_eval', 'Descending')
+
+
+def general_reasoning():
+    st.title("General Reasoning")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['MMLU', 'C Eval', 'CMMLU', 'ZBench', 'IndoMMLU']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+
+    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with right:
+        sorted = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sorted:
+        category_one = category_one_dict[category_one]
+        draw_only_acc('general_reasoning', category_one, category_two, sorted)
+    else:
+        draw_only_acc('general_reasoning', 'zero_shot', 'MMLU Full', 'Descending')
+
+def flores():
+    st.title("FLORES-Translation")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['Indonesian to English', 'Vitenamese to English', 'Chinese to English', 'Nalay to English']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+    
+
+    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with right:
+        sorted = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sorted:
+        category_one = category_one_dict[category_one]
+        draw_flores_translation(category_one, category_two, sorted)
+    else:
+        draw_flores_translation('zero_shot', 'Indonesian to English', 'Descending')
+
+def emotion():
+    st.title("Emotion")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['Indonesian Emotion  Classification', 'SST2']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+
+    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with right:
+        sorted = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sorted:
+        category_one = category_one_dict[category_one]
+        draw_only_acc('emotion', category_one, category_two, sorted)
+    else:
+        draw_only_acc('emotion', 'zero_shot', 'Indonesian Emotion  Classification', 'Descending')
+
+def dialogue():
+    st.title("Dialogue")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['DREAM', 'SAMSum', 'DialogSum']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+
+    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with middle:
+        if category_two == 'DREAM':
+            sort = st.selectbox('Sort', ['Accuracy'])
+        else:
+            sort = st.selectbox('Sort', ['Average', 'ROUGE-1', 'ROUGE-2', 'ROUGE-L'])
+    
+    with right:
+        sorted = st.selectbox('by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sort or sorted:
+        category_one = category_one_dict[category_one]
+        draw_dialogue(category_one, category_two, sort, sorted)
+    else:
+        draw_dialogue('zero_shot', 'DREAM', sort[0],'Descending')
+
+def fundamental_nlp_tasks():
+    st.title("Fundamental NLP Tasks")
+
+    filters_levelone = ['Zero Shot', 'Few Shot']
+    filters_leveltwo = ['OCNLI', 'C3', 'COLA', 'QQP', 'MNLI', 'QNLI', 'WNLI', 'RTE', 'MRPC']
+    
+    category_one_dict = {'Zero Shot': 'zero_shot', 
+                         'Few Shot': 'few_shot'}
+
+    left, center, _, right = st.columns([0.2, 0.2, 0.4, 0.2])
+    with left:
+        category_one = st.selectbox('Select Zero / Few shot', filters_levelone)
+    with center:
+        category_two = st.selectbox('Select the sub-category', filters_leveltwo)
+    with right:
+        sorted = st.selectbox('sorted by', ['Ascending', 'Descending'])
+    
+    if category_one or category_two or sorted:
+        category_one = category_one_dict[category_one]
+        draw_only_acc('fundamental_nlp_tasks', category_one, category_two, sorted)
+    else:
+        draw_only_acc('fundamental_nlp_tasks', 'zero_shot', 'OCNLI', 'Descending')