Update app.py

app.py

@@ -1,37 +1,32 @@
 import gradio as gr
 import requests
 import os
-from huggingface_hub import InferenceClient
 
 # Set up the Hugging Face API key (ensure you've set this as an environment variable)
 api_key = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
 # API URLs
 WHISPER_API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
+DEEPSEEK_API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/DeepSeek-R1"
 
-# Set up inference client for DeepSeek-R1
-client = InferenceClient(
-    provider="together",
-    api_key=api_key
-)
+headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
 
 def transcribe_audio(audio_file):
     with open(audio_file, "rb") as f:
         data = f.read()
-    response = requests.post(WHISPER_API_URL, headers={"Authorization": f"Bearer {api_key}"}, data=data)
+    response = requests.post(WHISPER_API_URL, headers=headers, data=data)
     if response.status_code == 200:
         return response.json().get("text", "Transcription not available.")
     else:
         return f"Error: {response.status_code}, {response.text}"
 
 def generate_mermaid_code(prompt):
-    messages = [{"role": "user", "content": f"Generate a valid MermaidJS diagram code for the following: {prompt}"}]
-    completion = client.chat.completions.create(
-        model="deepseek-ai/DeepSeek-R1",
-        messages=messages,
-        max_tokens=500
-    )
-    return completion.choices[0].message['content'].strip()
+    payload = {"inputs": prompt, "parameters": {"max_tokens": 500}}
+    response = requests.post(DEEPSEEK_API_URL, headers=headers, json=payload)
+    if response.status_code == 200:
+        return response.json()["generated_text"].strip()
+    else:
+        return f"Error: {response.status_code}, {response.text}"
 
 def process_input(input_type, text_input, audio_input):
     if input_type == "Audio" and audio_input is not None: