From 2d688d324265897d26d6dc4377ae2c1da8342f0f Mon Sep 17 00:00:00 2001
From: amesar <amesar>
Date: Tue, 17 Oct 2023 02:53:53 +0000
Subject: [PATCH] Issue #18: updates to notebook Batch_Score_Llama_2

---
 databricks/notebooks/llama2/Batch_Score_Llama_2.py | 10 +++++-----
 databricks/notebooks/llama2/Common.py              |  6 +++---
 databricks/notebooks/llama2/_README.py             |  3 +++
 3 files changed, 11 insertions(+), 8 deletions(-)

diff --git a/databricks/notebooks/llama2/Batch_Score_Llama_2.py b/databricks/notebooks/llama2/Batch_Score_Llama_2.py
index 32fe99f..21a3d67 100644
--- a/databricks/notebooks/llama2/Batch_Score_Llama_2.py
+++ b/databricks/notebooks/llama2/Batch_Score_Llama_2.py
@@ -40,8 +40,8 @@
 
 dbutils.widgets.text("1. Model", default_model_name)
 dbutils.widgets.text("2. Version", "1")
-dbutils.widgets.text("3. Input File or Table", "andre_m.default.llama2_in")
-dbutils.widgets.text("4. Output Table", "andre_m.default.llama2_out")
+dbutils.widgets.text("3. Input File or Table", "questions.csv")
+dbutils.widgets.text("4. Output Table", "")
 dbutils.widgets.dropdown("5. Write mode", "none", ["none", "append","overwrite"])
 
 model_name = dbutils.widgets.get("1. Model")
@@ -72,7 +72,7 @@
 
 # COMMAND ----------
 
-df_questions = mk_df_from_file_or_table(input_file_or_table)
+df_questions = load_data(input_file_or_table)
 display(df_questions)
 
 # COMMAND ----------
@@ -92,7 +92,7 @@
 
 # MAGIC %md ##### Load model as Spark UDF
 # MAGIC
-# MAGIC This takes a minute or so.
+# MAGIC This takes a minute or two.
 
 # COMMAND ----------
 
@@ -102,7 +102,7 @@
 
 # MAGIC %md ##### Call model with questions
 # MAGIC
-# MAGIC Takes about a minute per question.
+# MAGIC Takes about 30-60 seconds per question.
 
 # COMMAND ----------
 
diff --git a/databricks/notebooks/llama2/Common.py b/databricks/notebooks/llama2/Common.py
index cfffbaa..22a15de 100644
--- a/databricks/notebooks/llama2/Common.py
+++ b/databricks/notebooks/llama2/Common.py
@@ -23,7 +23,7 @@ def mk_absolute_path(path):
 
 from pyspark.sql.types import *
 
-def mk_df_from_csv_file(path):
+def load_from_path(path):
     print(f"Reading from file '{path}'")
     path = mk_absolute_path(path)
     print(f"Reading from file '{path}'")
@@ -35,10 +35,10 @@ def mk_df_from_csv_file(path):
 
 # COMMAND ----------
 
-def mk_df_from_file_or_table(name):
+def load_data(name):
     toks = name.split(".")
     if len(toks) == 3: # If unity catalog 3 component name
         print(f"Reading from table '{name}'")
         return spark.table(name)
     else: # otherwise assume its a CSV file
-        return mk_df_from_csv_file(name)
+        return load_from_path(name)
diff --git a/databricks/notebooks/llama2/_README.py b/databricks/notebooks/llama2/_README.py
index 540e712..5225cab 100644
--- a/databricks/notebooks/llama2/_README.py
+++ b/databricks/notebooks/llama2/_README.py
@@ -9,5 +9,8 @@
 # MAGIC * [Model_Serve_Llama_2]($Model_Serve_Llama_22) - Real-time scoring.
 # MAGIC * [Common]($Common)
 # MAGIC
+# MAGIC ##### Github
+# MAGIC * https://github.com/amesar/mlflow-examples/tree/master/databricks/notebooks/llama2
+# MAGIC
 # MAGIC
 # MAGIC Last updated: 2023-10-16