Upload 2 files
Browse files- app.py +196 -0
- requirements.txt +6 -0
app.py
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import gradio as gr
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from database import Database
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from filesource import FileSource
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from agent import run_agent
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from services.utils import get_db_scheme_from_uri
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source = None
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def connect_to_file(file):
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"""
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This function is used to connect to a data source file like CSV or parquet
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Parameters:
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-----------
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file : File
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A file-like object (e.g., from a file upload or file picker) that contains structured data.
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Returns:
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--------
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tuple
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A tuple (schema, status) where:
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- schema (str): A string representation of the data schema if successful, or an empty string on failure.
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- status (str): A message indicating the success or failure of the connection.
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"""
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global source
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try:
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source = FileSource(file.name)
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status = source.connect()
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schema = source._pretify_schema()
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status = "Connection successful!"
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except Exception as e:
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schema = ""
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status = f"Error: {str(e)}"
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return schema, status
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def generate_and_run_sql(prompt):
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"""
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This function is used to give an answer to a user question related to a database or file source
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Parameters:
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-----------
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prompt : str
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A natural language instruction or question from the user (e.g., "Show me the top 10 customers by revenue").
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Returns:
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--------
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str
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The given response of the user question
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Notes:
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------
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- Requires a connected `source` (via `connect_to_file` or `connect_to_database`).
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- Uses a language agent to interpret the prompt and generate an appropriate SQL query or explanation.
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"""
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if source is None:
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return "Please connect to a database or add a file"
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answer = run_agent(source, prompt)
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out = ""
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for chunk in answer:
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out += chunk
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return out
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def connect_to_database(db_url):
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"""
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This function is used to connect to a database using the provided database URL and returns its schema.
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Parameters:
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-----------
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db_url : str
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A valid database connection string (e.g., "mysql://user:pass@host:port/dbname").
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Returns:
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--------
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tuple
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A tuple (schema, status) where:
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- schema (str): A string representation of the database schema if the connection is successful,
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or an empty string if it fails.
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- status (str): A message indicating the result of the connection attempt.
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Notes:
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------
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- The dialect is extracted from the URI to determine the database type (e.g., MySQL, PostgreSQL).
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"""
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global source
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try:
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dialect = get_db_scheme_from_uri(db_url)
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source = Database(db_url, dialect)
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status = source.connect()
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schema = source._pretify_schema()
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status = "Connection successful!"
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except Exception as e:
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schema = ""
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status = f"Error: {str(e)}"
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return schema, status
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# Function to add user message to chat history
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def user(user_message, chat_history):
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chat_history.append({"role": "user", "content": user_message})
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return "", chat_history
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# Function to generate a bot response
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def bot(chat_history):
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if source is None:
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chat_history.append({"role":"assistant","content":"please connect to a database before asking question"})
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yield chat_history
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else:
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answer = run_agent(source,chat_history[-1]['content'])
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chat_history.append({"role":"assistant","content":""})
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for chunk in answer:
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chat_history[-1]['content'] += chunk
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yield chat_history
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# Create the Gradio interface
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with gr.Blocks( theme=gr.themes.Default(), css="""
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.gr-button { margin: 5px; border-radius:16px; }
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.gr-textbox, .gr-text-area, .gr-dropdown, .gr-json { border-radius: 8px; }
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.gr-row { gap: 10px; }
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.gr-tab { border-radius: 8px; }
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.status-text { font-size: 0.9em; color: #555; }
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.gr-json { max-height: 300px; overflow-y: auto; } /* Added scrolling for JSON */
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""") as demo:
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gr.Markdown(
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f"""
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# 🤖 MCP DB Answer
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Your mcp server that allow you to talk to any database
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Powered by Ibis it support : PostgreSQL , SQLite , MySQL , MSSQL , ClickHouse , BigQuery and many other
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Also support .CSV and .parquet files
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""",
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elem_classes=["header"]
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)
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with gr.Column(scale=3):
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with gr.Tabs():
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with gr.TabItem("💬 Chat"):
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with gr.Group():
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main_chat_disp = gr.Chatbot(
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label=None, height=400,
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avatar_images=(None, "https://huggingface.co/spaces/Space-Share/bucket/resolve/main/images/pfp.webp"),
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show_copy_button=True, render_markdown=True, sanitize_html=True, type='messages'
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)
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with gr.Row(variant="compact"):
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user_msg_tb = gr.Textbox(
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show_label=False, placeholder="Talk with your data...",
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scale=7, lines=1, max_lines=3
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)
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send_btn = gr.Button("Send", variant="primary", scale=1, min_width=100)
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with gr.TabItem("Config"):
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with gr.Row():
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# Left column for database configuration.
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with gr.Column(scale=1):
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gr.Markdown("## Database Configuration")
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# Textbox for entering the database URL.
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db_url_tb = gr.Textbox(
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show_label=True, label="Database URL", placeholder="Enter the URL to connect to the database..."
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)
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# Button to connect to the database.
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connect_btn = gr.Button("Connect", variant="primary")
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gr.Markdown("## File Upload")
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file_uploader = gr.File(
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label="Upload File", file_types=[".csv", ".parquet", ".xls", ".xlsx"]
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)
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# Button to connect to the database.
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load_btn = gr.Button("Load", variant="primary")
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# Right column for displaying the database schema and status message.
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with gr.Column(scale=3):
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gr.Markdown("## Database Schema")
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# Textarea to display the database schema.
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schema_ta = gr.TextArea(
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show_label=False, placeholder="Database schema will be displayed here...",
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lines=20, max_lines=50, interactive=False
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)
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# Textbox to display the status message.
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status_tb = gr.Textbox(
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show_label=False, placeholder="Status message will be displayed here...",
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lines=1, max_lines=1, interactive=False, elem_classes=["status-text"]
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)
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connect_btn.click(fn=connect_to_database, inputs=db_url_tb, outputs=[schema_ta, status_tb])
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load_btn.click(fn=connect_to_file, inputs=file_uploader, outputs=[schema_ta, status_tb])
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send_btn.click(fn=user, inputs=[user_msg_tb, main_chat_disp], outputs=[user_msg_tb, main_chat_disp], queue=False).then(
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fn=bot, inputs=main_chat_disp, outputs=main_chat_disp
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)
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invisible_btn = gr.Button(visible=False)
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invisible_btn.click(fn=generate_and_run_sql, inputs=[user_msg_tb], outputs=None)
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if __name__ == "__main__":
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demo.launch(mcp_server=True)
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requirements.txt
ADDED
@@ -0,0 +1,6 @@
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gradio[mcp]>=5.33.0
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ibis-framework[duckdb,mssql,mysql,postgres,sqlite]>=10.5.0
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openai>=1.84.0
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pydantic>=2.11.5
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sqlglot>=26.24.0
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tabulate>=0.9.0
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