Hasti11 commited on
Commit
d788ce3
1 Parent(s): ff8d654

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -11
app.py CHANGED
@@ -8,6 +8,7 @@ from PIL import Image
8
  import moviepy.editor as mp
9
  from gtts import gTTS
10
  from groq import Groq
 
11
 
12
  client = Groq(
13
  api_key="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",
@@ -19,7 +20,7 @@ audio_pipeline = pipeline("audio-classification", model="audeering/wav2vec2-larg
19
  text_pipeline = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions", top_k=2)
20
 
21
  conversation_history = []
22
- max_history_length = 3
23
 
24
  def process_input(video_stream, conversation_history):
25
  if isinstance(video_stream, str):
@@ -75,7 +76,7 @@ def process_input(video_stream, conversation_history):
75
  audio_emotions = audio_pipeline(audio_data)
76
  if audio_emotions:
77
  audio_emotion = audio_emotions[0]['label']
78
- print("Audio emotion:", audio_emotion)
79
 
80
  # Recognize audio
81
  text_input = recognizer.recognize_google(audio)
@@ -119,12 +120,8 @@ def process_input(video_stream, conversation_history):
119
  print(f"Error processing text data: {e}")
120
 
121
 
122
-
123
-
124
-
125
-
126
  if conversation_history is not None:
127
- conversation_history = conversation_history[-max_history_length:] # Keep most recent entries
128
  conversation_history.append({
129
  "user_input": text_input,
130
  "image_features": image_features,
@@ -188,8 +185,10 @@ def display_history(conversation_history):
188
  if "user_input" in turn:
189
  history_str += f"User: {turn['user_input']}\n"
190
  if "ai_response" in turn:
 
 
191
  history_str += f"Therapist: {turn['ai_response']}\n\n"
192
- return history_str # Truncate long histories for model input
193
 
194
 
195
  # Create the Gradio interface
@@ -211,9 +210,6 @@ gr.Interface .gradio-description {
211
  font-size: 16px;
212
  margin-top: 10px;
213
  }
214
-
215
-
216
-
217
  """
218
 
219
  description = """
 
8
  import moviepy.editor as mp
9
  from gtts import gTTS
10
  from groq import Groq
11
+ import re
12
 
13
  client = Groq(
14
  api_key="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",
 
20
  text_pipeline = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions", top_k=2)
21
 
22
  conversation_history = []
23
+ # max_history_length = 3
24
 
25
  def process_input(video_stream, conversation_history):
26
  if isinstance(video_stream, str):
 
76
  audio_emotions = audio_pipeline(audio_data)
77
  if audio_emotions:
78
  audio_emotion = audio_emotions[0]['label']
79
+ print("Audio emotion:", audio_emotion)a
80
 
81
  # Recognize audio
82
  text_input = recognizer.recognize_google(audio)
 
120
  print(f"Error processing text data: {e}")
121
 
122
 
 
 
 
 
123
  if conversation_history is not None:
124
+ # conversation_history = conversation_history[-max_history_length:] # Keep most recent entries
125
  conversation_history.append({
126
  "user_input": text_input,
127
  "image_features": image_features,
 
185
  if "user_input" in turn:
186
  history_str += f"User: {turn['user_input']}\n"
187
  if "ai_response" in turn:
188
+ ai_response = turn['ai_response']
189
+ ai_response = re.sub(r'\*\*', '', ai_response)
190
  history_str += f"Therapist: {turn['ai_response']}\n\n"
191
+ return history_str
192
 
193
 
194
  # Create the Gradio interface
 
210
  font-size: 16px;
211
  margin-top: 10px;
212
  }
 
 
 
213
  """
214
 
215
  description = """