HF app

.gitignore

@@ -3,4 +3,5 @@ __pycache__
 *.png
 *.csv
 *.jpeg
-*.jpg
+*.jpg
+user_data*

README.md

@@ -0,0 +1,10 @@
+---
+title: Maker Faire Bot
+emoji: 👀
+colorFrom: pink
+colorTo: blue
+sdk: gradio
+sdk_version: 4.20.1
+app_file: app.py
+pinned: false
+---

app.py

@@ -4,19 +4,12 @@ import os
 import gradio as gr
 from dotenv import load_dotenv
 
-from utils import add_result
-
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.DEBUG)
 
 load_dotenv()
 
 
-def submit_result(user_answer):
-    add_result({"user_answer": user_answer})
-    return
-
-
 def get_user_prompt():
     return {
         "images": [
@@ -25,9 +18,9 @@ def get_user_prompt():
             "images/1.jpeg",
         ],
         "labels": [
-            "A pencil",
+            "A roll of string",
             "A camera",
-            "A sheet of paper",
+            "A loudspeaker",
         ],
     }
 
@@ -76,24 +69,42 @@ with gr.Blocks(theme=theme) as demo:
 
     user_answer_object = gr.Textbox(
         autofocus=True,
-        placeholder="(example): An electronic guitar",
+        placeholder="(example): An digital electronic guitar",
         label="What would you build?",
     )
     user_answer_explanation = gr.TextArea(
         autofocus=True,
         label="How would you build it?",
-        placeholder="""I'd use the camera to detect when the user touches the strings and make a sound using the loudspeakers when that happens.""",
+        # The example uses a roll of string, a camera, and a loudspeaker to build an electronic guitar.
+        placeholder="""To build an electronic guitar, I would:
+1. Use the roll of string to create the strings of the guitar.
+2. Use the camera to capture a live video of the hand movements. That way, I can use an AI model to predict the chords.
+3. Using a computer vision model, identify where the fingers are placed on the strings.
+4. Calculate the sounds that the loudspeaker should produce based on the finger placements.
+5. Play the sound through the loudspeaker.
+""",
     )
 
-    csv_writer.setup(components=[user_prompt, user_answer_object, user_answer_explanation], flagging_dir="flagged_data_csv")
-    hf_writer.setup(components=[user_prompt, user_answer_object, user_answer_explanation], flagging_dir="flagged_data_hf")
+    csv_writer.setup(
+        components=[user_prompt, user_answer_object, user_answer_explanation],
+        flagging_dir="user_data_csv",
+    )
+    hf_writer.setup(
+        components=[user_prompt, user_answer_object, user_answer_explanation],
+        flagging_dir="user_data_hf",
+    )
 
     submit_btn = gr.Button("Submit", variant="primary")
+
     def log_results(prompt, object, explanation):
         csv_writer.flag([prompt, object, explanation])
         hf_writer.flag([prompt, object, explanation])
 
-    submit_btn.click(log_results, inputs=[user_prompt, user_answer_object, user_answer_explanation], preprocess=False)
+    submit_btn.click(
+        log_results,
+        inputs=[user_prompt, user_answer_object, user_answer_explanation],
+        preprocess=False,
+    )
 
     gr.Markdown(
         """