Create app.py

app.py

@@ -0,0 +1,51 @@
+import gradio as gr
+import pandas as pd
+from io import StringIO
+from pandasai import PandasAI
+from pandasai.llm.huggingface import HuggingFaceLLM
+
+# Initialize an open-source LLM.
+# Here we use "google/flan-t5-small", a small free model from Hugging Face.
+llm = HuggingFaceLLM(model_name="google/flan-t5-small")
+pandas_ai = PandasAI(llm)
+
+def process_file_and_query(file_obj, question):
+    """
+    This function reads the uploaded CSV file, converts it into a DataFrame,
+    and then uses PandasAI to answer the user's question about the data.
+    """
+    if file_obj is None:
+        return "Please upload a CSV file."
+    
+    try:
+        # Read the file content. file_obj.read() returns bytes, so decode to string.
+        file_contents = file_obj.read().decode("utf-8")
+        # Use StringIO to convert the string data into a stream for pandas
+        df = pd.read_csv(StringIO(file_contents))
+    except Exception as e:
+        return f"Error reading CSV file: {e}"
+    
+    try:
+        # Use PandasAI to answer the question using the DataFrame.
+        answer = pandas_ai.run(df, prompt=question)
+        return answer
+    except Exception as e:
+        return f"Error processing the query: {e}"
+
+# Create a Gradio interface.
+iface = gr.Interface(
+    fn=process_file_and_query,
+    inputs=[
+        gr.File(label="Upload CSV file"),
+        gr.Textbox(label="Ask a question about your data", placeholder="E.g., What is the average of column X?")
+    ],
+    outputs="text",
+    title="Chat with Your CSV",
+    description=(
+        "Upload your CSV file and ask questions about the data. "
+        "This app uses an open-source LLM (google/flan-t5-small) via PandasAI to answer your questions interactively."
+    )
+)
+
+if __name__ == "__main__":
+    iface.launch()