Update app.py

app.py

@@ -12,8 +12,8 @@ WHISPER_API_URL = "https://api-inference.huggingface.co/models/openai/whisper-la
 # Set up headers for the Whisper API request
 headers = {"Authorization": f"Bearer {api_key}"}
 
-# Load the DeepSeek model using Hugging Face's pipeline
-pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-R1-Distill-Qwen-7B")
+# Load the DeepSeek-R1-Distill-Qwen-1.5B model using Hugging Face's pipeline
+pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B")
 
 # Function to query the Hugging Face Whisper model for audio transcription
 def transcribe_audio(audio_file):
@@ -25,7 +25,7 @@ def transcribe_audio(audio_file):
     else:
         return f"Error: {response.status_code}, {response.text}"
 
-# Function to generate Mermaid.js code using the DeepSeek model (replaces Mistral API call)
+# Function to generate Mermaid.js code using the DeepSeek model (DeepSeek-R1-Distill-Qwen-1.5B)
 def generate_mermaid_code(prompt):
     # Instruction included in the prompt to guide DeepSeek to generate valid MermaidJS code
     deepseek_prompt = f"Generate a valid MermaidJS diagram code for the following: {prompt}"
@@ -39,11 +39,11 @@ def process_input(input_type, text_input, audio_input):
     if input_type == "Audio" and audio_input is not None:
         # Transcribe audio using the Whisper API
         transcription = transcribe_audio(audio_input)
-        # Generate Mermaid.js code from transcription using DeepSeek-R1
+        # Generate Mermaid.js code from transcription using DeepSeek-R1-Distill-Qwen-1.5B
         return generate_mermaid_code(transcription)
 
     elif input_type == "Text" and text_input:
-        # Generate Mermaid.js code directly from text input using DeepSeek-R1
+        # Generate Mermaid.js code directly from text input using DeepSeek-R1-Distill-Qwen-1.5B
         return generate_mermaid_code(text_input)
 
     elif input_type == "Text and Audio" and text_input and audio_input is not None:
@@ -51,7 +51,7 @@ def process_input(input_type, text_input, audio_input):
         transcription = transcribe_audio(audio_input)
         # Combine text input and transcription
         combined_input = f"{text_input} and {transcription}"
-        # Generate Mermaid.js code using DeepSeek-R1
+        # Generate Mermaid.js code using DeepSeek-R1-Distill-Qwen-1.5B
         return generate_mermaid_code(combined_input)
 
     else: