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utils.py

@@ -64,13 +64,12 @@ def save_key(api_key):
 def query_pinecone(
     query, top_k, model, index, year, quarter, ticker, participant_type, threshold=0.25
 ):
-    # generate embeddings for the query
-    xq = model.encode([query]).tolist()
-
     if participant_type == "Company Speaker":
-        participant = "Speaker"
+        participant = "Answer"
     else:
-        participant = participant_type
+        participant = "Question"
+    # generate embeddings for the query
+    xq = model.encode([query]).tolist()
 
     if year == "All":
         if quarter == "All":
@@ -126,7 +125,6 @@ def query_pinecone(
             },
             include_metadata=True,
         )
-
     # filter the context passages based on the score threshold
     filtered_matches = []
     for match in xc["matches"]:
@@ -167,7 +165,7 @@ def text_lookup(data, sentence_ids):
 
 def generate_prompt(query_text, context_list):
     context = " ".join(context_list)
-    prompt = f"""Answer the question as accurately as possible using the provided context. Try to include as many key details as possible.
+    prompt = f"""Answer the question in 5 detailed points as accurately as possible using the provided context. Try to include as many key details as possible.
 Context: {context}
 Question: {query_text}
 Answer:"""
@@ -204,17 +202,26 @@ def gpt_model(prompt):
 
 
 def retrieve_transcript(data, year, quarter, ticker):
-    row = (
-        data.loc[
-            (data.Year == int(year))
-            & (data.Quarter == quarter)
-            & (data.Ticker == ticker),
-            ["File_Name"],
-        ]
-        .drop_duplicates()
-        .iloc[0, 0]
-    )
-    print(row)
+    if year == "All" or quarter == "All":
+        row = (
+            data.loc[
+                (data.Ticker == ticker),
+                ["File_Name"],
+            ]
+            .drop_duplicates()
+            .iloc[0, 0]
+        )
+    else:
+        row = (
+            data.loc[
+                (data.Year == int(year))
+                & (data.Quarter == quarter)
+                & (data.Ticker == ticker),
+                ["File_Name"],
+            ]
+            .drop_duplicates()
+            .iloc[0, 0]
+        )
     # convert row to a string and join values with "-"
     # row_str = "-".join(row.astype(str)) + ".txt"
     open_file = open(