black

app.py

@@ -9,15 +9,19 @@ from src.core import (
 MAX_ROWS = 10
 
 import pandas as pd
+
+
 def generate_step_markdown(step_number: int, subtitle: str, description: str = None):
     return gr.Markdown(f"# Step {step_number}\n\n ### {subtitle}\n{description}")
 
-example_df = pd.read_csv('./src/data/synthetic/legal_entries_a.csv')
+
+example_df = pd.read_csv("./src/data/synthetic/legal_entries_a.csv")
+
+
 def load_example_template(template_df, example_df):
     return template_df.update(example_df)
 
 
-
 # TODO: use tempfile
 def export_csv(df, filename):
     df.to_csv(filename, index=False)
@@ -31,7 +35,6 @@ def export_text(content, filename):
     return gr.File.update(value=filename, visible=True)
 
 
-
 with gr.Blocks() as demo:
     gr.Markdown(
         "# LLM Data Mapper\n\nThis tool will help you map a source CSV to a template CSV, and then generate python code to transform the source CSV into the template CSV. You can edit all of the values, re-run the processes, and download files along the way."
@@ -58,7 +61,11 @@ with gr.Blocks() as demo:
             upload_template_btn.upload(
                 fn=process_csv_text, inputs=upload_template_btn, outputs=template_df
             )
-            load_template_btn.click(lambda _: pd.read_csv('./src/data/actual/template.csv'), upload_template_btn, template_df)
+            load_template_btn.click(
+                lambda _: pd.read_csv("./src/data/actual/template.csv"),
+                upload_template_btn,
+                template_df,
+            )
         with gr.Column():
             upload_source_button = gr.UploadButton(
                 label="Upload Source File",
@@ -74,7 +81,11 @@ with gr.Blocks() as demo:
             upload_source_button.upload(
                 fn=process_csv_text, inputs=upload_source_button, outputs=source_df
             )
-            load_source_button.click(lambda _: pd.read_csv('./src/data/actual/table_A.csv'), upload_source_button, source_df)
+            load_source_button.click(
+                lambda _: pd.read_csv("./src/data/actual/table_A.csv"),
+                upload_source_button,
+                source_df,
+            )
 
     # STEP 2
     generate_step_markdown(

src/core.py

@@ -14,9 +14,10 @@ from src.prompt import (
     SPEC_WRITER_PROMPT_STR,
     ENGINEER_PROMPT_STR,
 )
+
 load_dotenv()
 
-if os.environ.get('DEBUG') == 'true':
+if os.environ.get("DEBUG") == "true":
     os.environ["LANGCHAIN_WANDB_TRACING"] = "true"
     os.environ["WANDB_PROJECT"] = "llm-data-mapper"