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import streamlit as st
import pandas as pd
from apis import ask, run_sql
from utils import format_sql
def main():
st.title("💬 Wren AI Cloud API Demo - SQL Generation")
if "api_key" not in st.session_state or "project_id" not in st.session_state:
st.error("Please enter your API Key and Project ID in the sidebar of Home page to get started.")
return
if not st.session_state.api_key or not st.session_state.project_id:
st.error("Please enter your API Key and Project ID in the sidebar of Home page to get started.")
return
api_key = st.session_state.api_key
project_id = st.session_state.project_id
st.markdown('Using APIs: [Ask](https://wrenai.readme.io/reference/post_ask-1), [Run SQL](https://wrenai.readme.io/reference/cloud_post_run-sql)')
# Sidebar for API configuration
with st.sidebar:
st.header("🔧 Configuration")
language = st.text_input(
"Language",
"English",
help="Language of the response. Default is English."
)
sample_size = st.slider(
"Sample Size",
min_value=100,
max_value=10000,
value=1000,
step=100,
help="Number of data points to include in results"
)
# Initialize chat history
if "qa_messages" not in st.session_state:
st.session_state.qa_messages = []
if "qa_thread_id" not in st.session_state:
st.session_state.qa_thread_id = ""
# Display chat history
for message in st.session_state.qa_messages:
with st.chat_message(message["role"]):
if message["role"] == "user":
st.write(message["content"])
else:
st.write(message["content"])
if "sql" in message:
with st.expander("🔍 Generated SQL Query", expanded=False):
st.code(format_sql(message["sql"]), language="sql")
# Add button to run SQL
if st.button("🔄 Run SQL Query", key=f"run_sql_{message.get('message_id', 'unknown')}"):
with st.spinner("Executing SQL query..."):
sql_result, error = run_sql(api_key, project_id, message["sql"], st.session_state.qa_thread_id, sample_size)
if sql_result:
data = sql_result.get("records", [])
if data:
# Convert to DataFrame for better display
df = pd.DataFrame(data)
st.success("SQL query executed successfully!")
st.dataframe(df, use_container_width=True)
else:
st.info("Query executed but returned no data.")
else:
st.error(f"Error executing SQL: {error}")
if "sql_results" in message:
st.subheader("🔍 Query Results")
if message["sql_results"]:
st.dataframe(message["sql_results"], use_container_width=True)
else:
st.info("No results returned from the query.")
# Chat input
if prompt := st.chat_input("Ask a question about your data..."):
# Add user message to chat history
st.session_state.qa_messages.append({"role": "user", "content": prompt})
# Display user message
with st.chat_message("user"):
st.write(prompt)
# Generate response using ask API
with st.chat_message("assistant"):
with st.spinner("Generating answer..."):
ask_response, error = ask(api_key, project_id, prompt, st.session_state.qa_thread_id, sample_size=sample_size, language=language)
if ask_response:
answer = ask_response.get("summary", "")
sql_query = ask_response.get("sql", "")
st.session_state.qa_thread_id = ask_response.get("threadId", "")
if answer:
st.toast("Answer generated successfully!", icon="🎉")
# Create unique message ID
message_id = len(st.session_state.qa_messages)
# Store the response
assistant_message = {
"role": "assistant",
"content": answer,
"message_id": message_id
}
if sql_query:
assistant_message["sql"] = sql_query
st.session_state.qa_messages.append(assistant_message)
st.write(answer)
# Display SQL query if available
if sql_query:
with st.expander("🔍 Generated SQL Query", expanded=False):
st.code(format_sql(sql_query), language="sql")
# Add button to run SQL
if st.button("🔄 Run SQL Query", key=f"run_sql_{message_id}"):
with st.spinner("Executing SQL query..."):
sql_result, error = run_sql(api_key, project_id, sql_query, st.session_state.qa_thread_id, sample_size)
if sql_result:
data = sql_result.get("records", [])
if data:
# Convert to DataFrame for better display
df = pd.DataFrame(data)
st.success("SQL query executed successfully!")
st.dataframe(df, use_container_width=True)
else:
st.info("Query executed but returned no data.")
else:
st.error(f"Error executing SQL: {error}")
else:
st.toast("No answer was generated. Please try rephrasing your question.", icon="🤔")
assistant_message = {
"role": "assistant",
"content": "I couldn't generate an answer for your question. Please try rephrasing it or make sure it's related to your data."
}
st.session_state.qa_messages.append(assistant_message)
else:
st.toast(f"Error generating answer: {error}", icon="🤔")
assistant_message = {
"role": "assistant",
"content": "Sorry, I couldn't process your request. Please check your API credentials and try again."
}
st.session_state.qa_messages.append(assistant_message)
# Clear chat button
if st.sidebar.button("🧹 Clear Chat History"):
st.session_state.qa_messages = []
st.session_state.qa_thread_id = ""
st.rerun()
if __name__ == "__main__":
main() |