csv loader app commit

app.py

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+import gradio as gr
+import table_load as tl
+import comm
+
+
+css="""
+#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+"""
+
+title = """
+<div style="text-align: center;max-width: 700px;">
+    <h1>Analyze your CSV</h1>
+    <p style="text-align: center;">Please specify OpenAI Key before use</p>
+</div>
+"""
+
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(title)
+    with gr.Column():
+            openai_key = gr.Textbox(label="You OpenAI API key", type="password")
+            raw_table = gr.File(label="Load a table file (xls or csv)", file_types=['.csv, xlsx, xls'], type="file")
+            with gr.Row():
+                langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
+                load_table = gr.Button("Load table to langchain")
+
+    chatbot = gr.Chatbot([], elem_id="chatbot").style(height=350)
+    with gr.Column(scale=0.85):
+        question = gr.Textbox(show_label=False, placeholder="Type your question and hit Enter").style(container=False)
+    with gr.Column(scale=0.15, min_width=0):
+        clr_btn = gr.Button("Clear History")
+        
+        
+    load_table.click(tl.load_file, None, langchain_status, queue=False)    
+    load_table.click(tl.table_loader, inputs=[raw_table, openai_key], outputs=[langchain_status], queue=False)
+   
+    question.submit(comm.respond, [question, chatbot], [question, chatbot])
+    clr_btn.click(lambda: None, None, chatbot, queue=False)
+    
+demo.launch()

comm.py

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+def run(query):
+    from langchain.callbacks import get_openai_callback
+    
+    with get_openai_callback() as cb:
+        response = (agent.run(query))
+        costs = (f"Total Cost (USD): ${cb.total_cost}")
+        output = f'{response} \n {costs}'
+        return output
+    
+def respond(message, chat_history):
+    import time
+    
+    bot_message = run(message)
+    chat_history.append((message, bot_message))
+    time.sleep(0.5)
+    return "", chat_history

table_load.py

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+"""functions related to tables loading"""
+
+def load_file():
+    return "Loading..."
+
+def load_xlsx(name):
+    import pandas as pd
+    
+    xls_file = rf'{name}'
+    data = pd.read_excel(xls_file)  
+    return data
+
+def table_loader(table_file, open_ai_key):
+    import os
+    from langchain.llms import OpenAI
+    from langchain.agents import create_pandas_dataframe_agent    
+    from pandas import read_csv
+    
+    global agent
+    if open_ai_key is not None:
+        os.environ['OPENAI_API_KEY'] = open_ai_key
+    else:
+        return "Enter API"
+    
+    if table_file.name.endswith('.xlsx') or table_file.name.endswith('.xls'):
+        data = load_xlsx(table_file.name)
+        agent = create_pandas_dataframe_agent(OpenAI(temperature=0), data)
+        return "Ready!"
+    elif table_file.name.endswith('.csv'):
+        data = read_csv(table_file.name)
+        agent = create_pandas_dataframe_agent(OpenAI(temperature=0), data)
+        return "Ready!"
+    else:
+        return "Wrong file format! Upload excel file or csv!"
+