Update app.py

app.py

@@ -0,0 +1,133 @@
+import pandas as pd
+import pdfplumber
+import docx
+import openai
+import seaborn as sns
+import matplotlib.pyplot as plt
+import gradio as gr
+
+openai.api_key = 'sk-proj-PMkGJxtGRdaihzh15yJYT3BlbkFJ0bEWbrsZjjwV5d3XYSFc'
+def load_file(file):
+    file_type = file.name.split('.')[-1]
+    if file_type == 'csv':
+        return pd.read_csv(file.name)
+    elif file_type in ['xls', 'xlsx']:
+        return pd.read_excel(file.name)
+    elif file_type == 'pdf':
+        return load_pdf(file)
+    elif file_type in ['doc', 'docx']:
+        return load_doc(file)
+    else:
+        raise ValueError("Unsupported file type")
+
+def load_pdf(file):
+    with pdfplumber.open(file.name) as pdf:
+        pages = [page.extract_text() for page in pdf.pages]
+    text = "\n".join(pages)
+    return pd.DataFrame({"text": [text]})
+
+def load_doc(file):
+    doc = docx.Document(file.name)
+    text = "\n".join([para.text for para in doc.paragraphs])
+    return pd.DataFrame({"text": [text]})
+    def generate_query(prompt):
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=prompt,
+        max_tokens=150
+    )
+    return response.choices[0].text.strip()
+
+def handle_query(query, df):
+    if "number of columns" in query.lower():
+        return f"The number of columns is {df.shape[1]}"
+    elif "number of rows" in query.lower():
+        return f"The number of rows is {df.shape[0]}"
+    else:
+        try:
+            # Try executing the query as a pandas query
+            result_df = df.query(query)
+            return result_df.to_html()
+        except Exception as e:
+            return str(e)
+
+def draw_chart(query, df):
+    try:
+        result_df = df.query(query)
+        sns.scatterplot(data=result_df, x=result_df.columns[0], y=result_df.columns[1])
+        plt.title("Generated Chart")
+        plt.xlabel(result_df.columns[0])
+        plt.ylabel(result_df.columns[1])
+        plt.savefig('/content/chart.png')
+        plt.close()
+        return '/content/chart.png'
+    except Exception as e:
+        return str(e)
+
+        def generate_query(prompt):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+    return response['choices'][0]['message']['content'].strip()
+
+def handle_query(query, df):
+    if "number of columns" in query.lower():
+        return f"The number of columns is {df.shape[1]}"
+    elif "number of rows" in query.lower():
+        return f"The number of rows is {df.shape[0]}"
+    else:
+        try:
+            result_df = df.query(query)
+            return result_df.to_html()
+        except Exception as e:
+            return str(e)
+
+def draw_chart(query, df):
+    try:
+        result_df = df.query(query)
+        sns.scatterplot(data=result_df, x=result_df.columns[0], y=result_df.columns[1])
+        plt.title("Generated Chart")
+        plt.xlabel(result_df.columns[0])
+        plt.ylabel(result_df.columns[1])
+        plt.savefig('/content/chart.png')
+        plt.close()
+        return '/content/chart.png'
+    except Exception as e:
+        return str(e)
+
+        def chatbot(file, input_text):
+    try:
+        # Load the file into a DataFrame
+        df = load_file(file)
+        
+        # Generate a query from the input text
+        query = generate_query(input_text)
+        
+        # Handle the query and generate a response
+        response = handle_query(query, df)
+        
+        # If the query is suitable for generating a chart, do so
+        if "chart" in query.lower() or "graph" in query.lower():
+            chart_path = draw_chart(query, df)
+            return chart_path, response
+        
+        # Return the query response
+        return None, response
+    except Exception as e:
+        return None, str(e)
+
+        # Create a Gradio interface
+iface = gr.Interface(
+    fn=chatbot,
+    inputs=[gr.File(type="filepath", label="Upload File"), gr.Textbox(lines=2, placeholder="Enter your query here...")],
+    outputs=["image", "html"],
+    title="Data Analyst Chatbot",
+    description="Upload a file and enter a query to get responses based on the data."
+)
+
+# Launch the interface
+iface.launch()