Update app.py

app.py

@@ -14,7 +14,7 @@ from datetime import datetime
 import sqlite3
 from datetime import datetime
 
-
+token=os.getenv('HF_TOKEN')
 # Initialize the database
 def init_db(file='logs.db'):
     conn = sqlite3.connect(file)
@@ -70,7 +70,51 @@ def check_ubuse(prompt,word_list=["little girl"]):
     return prompt
     
 def enhance_prompt(prompt, model="mistralai/Mistral-7B-Instruct-v0.1", style="photo-realistic"):
+
+    from gradio_client import Client
+
+    client = Client("K00B404/HugChatWrap")
+    result = client.predict(
+    		message=prompt,
+    		chat_history=[],
+    		system_message="""
+        You are a pragmatic coding assistant specializing in Python. Your task is to strictly respond with **Python code only**, ensuring all explanations and comments are embedded within the script using **multi-line comment blocks** (`### or #`).
     
+        **Response Requirements:**  
+        - **No external ### Explanation ### ** All descriptions, justifications, and context must be inside the script.  
+        - **Follow OOP principles** where applicable, improving maintainability and extensibility.  
+        - **Ensure compliance with PEP8 and autopep8 formatting.**  
+        - **Enhance and refactor the provided script**, making it a more efficient, readable, and reusable # IMPROVED PYTHON CODE #.  
+        - **At the end of every script, include a '### Future Features ###' comment block** outlining possible enhancements.  
+        
+        **Example Response Format:**  
+        ```python
+        # filename.py
+        # Module: Improved Script v1.0
+        # Description: [Brief explanation of script functionality]  
+        
+        # IMPROVED PYTHON CODE #
+                
+        ### Explanation ### 
+        #- inside comment block.
+        
+        ### Future Features ###
+        #- Suggested improvement 1
+        #- Suggested improvement 2
+        ```
+        
+        Now, improve and enhance the following script:""",
+    		max_tokens=2048,
+    		temperature=0.7,
+    		top_p=0.9,
+    		model_name= "mistralai/Mistral-Nemo-Instruct-2407",#"Qwen/Qwen2.5-Coder-3B-Instruct",
+    		api_name="/respond"
+    )
+    print(result)
+
+
+
+   ''' 
     client = Client("K00B404/Mistral-Nemo-custom")
     
     system_prompt=f"""
@@ -86,7 +130,7 @@ def enhance_prompt(prompt, model="mistralai/Mistral-7B-Instruct-v0.1", style="ph
     		max_tokens=256,
     		model_id=model,# "mistralai/Mistral-Nemo-Instruct-2407",
     		api_name="/predict"
-    )
+    )'''
     return result
     
     # The output value that appears in the "Response" Textbox component.
@@ -100,26 +144,6 @@ def enhance_prompt(prompt, model="mistralai/Mistral-7B-Instruct-v0.1", style="ph
     """
 
 
-def enhance_prompt_v2(prompt, model="mistralai/Mistral-Nemo-Instruct-2407", style="photo-realistic"):
-    
-    client = Client("K00B404/Mistral-Nemo-custom")
-    
-    system_prompt=f"""
-    You are a image generation prompt enhancer specialized in the {style} style. 
-    You must respond only with the enhanced version of the users input prompt
-    Remember, image generation models can be stimulated by refering to camera 'effect' in the prompt like :4k ,award winning, super details, 35mm lens, hd
-    """
-    user_message=f"###input image generation prompt### {prompt}"
-   
-    result = client.predict(
-    		system_prompt=system_prompt,
-    		user_message=user_message,
-    		max_tokens=256,
-    		model_id=model,
-    		api_name="/predict"
-    )
-    return result
-
     
 def mistral_nemo_call(prompt, API_TOKEN, model="mistralai/Mistral-Nemo-Instruct-2407", style="photo-realistic"):
     
@@ -172,7 +196,7 @@ def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Ka
 
     original_prompt = prompt
     if enhance_prompt_option:
-        prompt = mistral_nemo_call(prompt, style=enhance_prompt_style)
+        prompt = enhance_prompt(prompt, API_TOKEN=API_TOKEN, style=enhance_prompt_style)
         print(f'\033[1mGeneration {key} enhanced prompt:\033[0m {prompt}')
     if use_mistral_nemo:
         prompt = mistral_nemo_call(prompt, API_TOKEN=API_TOKEN, style=nemo_enhance_prompt_style)