Update app.py

app.py

@@ -23,19 +23,19 @@ llama = LanguageModel("meta-llama/Meta-Llama-3.1-8B", token=access_token)
 #placeholder for reset
 prompts_with_probs = pd.DataFrame(
 {
-    "prompt": ['waiting for data'],
+    "prompt": [''],
     "layer": [0],
-    "results": ['hi'],
+    "results": [''],
     "probs": [0],
-    "expected": ['hi'],
+    "expected": [''],
 })
 prompts_with_ranks = pd.DataFrame(
 {
-    "prompt": ['waiting for data'],
+    "prompt": [''],
     "layer": [0],
-    "results": ['hi'],
+    "results": [''],
     "ranks": [0],
-    "expected": ['hi'],
+    "expected": [''],
 })
 
 def run_lens(model,PROMPT):
@@ -94,15 +94,6 @@ def process_file(prompts_data,file_path):
 
     return prompts
 
-
-
-#problem with using gr.LinePlot instead of a plt.figure is that text labels cannot be added for each individual point
-# def plot_prob(prompts_with_probs):
-#     return gr.LinePlot(prompts_with_probs, x="layer", y="probs",color="prompt", title="Probability of Expected Token",label="results",show_label=True,key="results")
-import matplotlib.pyplot as plt
-import pandas as pd
-import io
-from PIL import Image
 def plot_prob(prompts_with_probs):
     plt.figure(figsize=(10, 6))
     
@@ -134,13 +125,6 @@ def plot_prob(prompts_with_probs):
     img = Image.open(buf)
     plt.close()  # Close the figure to free memory
     return img
-# Example usage
-# prompts_with_probs should be a DataFrame with 'prompt', 'layer', and 'probs' columns
-
-import matplotlib.pyplot as plt
-import pandas as pd
-import io
-from PIL import Image
 
 def plot_rank(prompts_with_ranks):
     plt.figure(figsize=(10, 6))
@@ -174,11 +158,6 @@ def plot_rank(prompts_with_ranks):
     plt.close()  # Close the figure to free memory
     return img
 
-import matplotlib.pyplot as plt
-import pandas as pd
-import io
-from PIL import Image
-
 def plot_prob_mean(prompts_with_probs):
     # Calculate mean probabilities and variance
     summary_stats = prompts_with_probs.groupby("prompt")["probs"].agg(
@@ -213,9 +192,6 @@ def plot_prob_mean(prompts_with_probs):
     plt.close()  # Close the figure to free memory
     return img
 
-# Example usage
-# prompts_with_probs should be a DataFrame with 'prompt' and 'probs' columns
-
 def plot_rank_mean(prompts_with_ranks):
     # Calculate mean ranks and variance
     summary_stats = prompts_with_ranks.groupby("prompt")["ranks"].agg(