import streamlit as st
from PIL import Image

#from .streamapp import trace_df
st.sidebar.image(Image.open("./test-logo.png"), use_column_width=True)

print("trace_df  ", st.session_state['trace_df'])

trace_df = st.session_state['trace_df']
print(list(trace_df))

trace_df = trace_df.loc[:,['name', 'span_kind', 'start_time', 'end_time', 'attributes.__computed__.latency_ms', 'status_code', 'status_message',  'attributes.llm.invocation_parameters', 'attributes.llm.prompts', 'attributes.input.value',  'attributes.output.value',  'attributes.llm.prompt_template.template', 'attributes.llm.prompt_template.variables', 'attributes.llm.prompt_template.version', 'attributes.retrieval.documents']]
trace_df = trace_df.sort_values(by='start_time', ascending = False)

blankIndex=[''] * len(trace_df)
trace_df.index=blankIndex

st.dataframe(trace_df)

# if px.active_session():  
#     df0 = px.active_session().get_spans_dataframe()
#     if not df0.empty:
#         df= df0.fillna('')
#         st.dataframe(df)


#'name', 'span_kind', 'start_time', 'end_time', 'status_code', 'status_message',  'attributes.llm.invocation_parameters', 'attributes.llm.prompts', 'attributes.input.value',  'attributes.output.value', 'attributes.__computed__.latency_ms', 'attributes.llm.prompt_template.template', 'attributes.llm.prompt_template.variables', 'attributes.llm.prompt_template.version', 'attributes.retrieval.documents'