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earnings-calls-qa

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awinml commited on Jun 12, 2023

Commit

15c7806

•

1 Parent(s): aeaab1d

Upload 17 files

Files changed (5) hide show

app.py CHANGED Viewed

@@ -74,7 +74,7 @@ with st.sidebar:
         )
     )
-    use_bm25 = st.checkbox("Use 2-Stage Retrieval (BM25)")
     num_candidates = int(
         st.number_input(
             "Number of Candidates to Generate:",
@@ -252,7 +252,7 @@ with tab2:
         for ticker, quarter, year in ticker_year_quarter_tuples_list:
             file_text = retrieve_transcript(data, year, quarter, ticker)
             with st.expander(f"See Transcript - {quarter} {year}"):
-                st.subheader("Earnings Call Transcript - {quarter} {year}:")
                 stx.scrollableTextbox(
                     file_text,
                     height=700,
@@ -262,5 +262,5 @@ with tab2:
     else:
         st.write(
-            "No specific document chosen. Please mention Ticker and Duration in Question."
         )

         )
     )
+    use_bm25 = st.checkbox("Use 2-Stage Retrieval (BM25)", value=True)
     num_candidates = int(
         st.number_input(
             "Number of Candidates to Generate:",
         for ticker, quarter, year in ticker_year_quarter_tuples_list:
             file_text = retrieve_transcript(data, year, quarter, ticker)
             with st.expander(f"See Transcript - {quarter} {year}"):
+                st.subheader(f"Earnings Call Transcript - {quarter} {year}:")
                 stx.scrollableTextbox(
                     file_text,
                     height=700,
     else:
         st.write(
+            "No specific document chosen. Please mention Ticker and Duration in the Question."
         )

utils/__pycache__/prompts.cpython-38.pyc CHANGED Viewed

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utils/__pycache__/retriever.cpython-38.pyc CHANGED Viewed

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utils/__pycache__/vector_index.cpython-38.pyc CHANGED Viewed

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utils/models.py CHANGED Viewed

@@ -105,7 +105,6 @@ def get_vicuna_text_gen_model():
     return client
-@st.cache_resource
 def get_bm25_model(data):
     corpus = data.Text.tolist()
     corpus_clean = [preprocess_text(x) for x in corpus]

     return client
 def get_bm25_model(data):
     corpus = data.Text.tolist()
     corpus_clean = [preprocess_text(x) for x in corpus]