Update app.py

app.py

@@ -20,22 +20,18 @@ import json
 import urllib.parse
 from config import MODELS
 
-# Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
 
-# Global event for cancellation
 cancel_event = threading.Event()
 
-# Constants - Handle empty token properly
 ACCESS_TOKEN = os.environ.get('HF_TOKEN', '')
 if ACCESS_TOKEN == '':
-    ACCESS_TOKEN = None  # Convert empty string to None for proper handling
+    ACCESS_TOKEN = None
 
 PIPELINES = {}
 SEARCH_TIMEOUT_DEFAULT = 5.0
 
-# Data classes for better structure
 @dataclass
 class SearchResult:
     title: str
@@ -64,8 +60,6 @@ class GenerationConfig:
         }
 
 class SearchEngine:
-    """Base class for search engines with common functionality"""
-    
     USER_AGENTS = [
         'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
         'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
@@ -85,11 +79,8 @@ class SearchEngine:
         }
 
 class GoogleSearch(SearchEngine):
-    """Google search implementation"""
-    
     @staticmethod
     def search(query: str, max_results: int = 6, max_chars: int = 50) -> List[SearchResult]:
-        """Perform Google search with multiple fallback strategies"""
         encoded_query = quote_plus(query)
         search_urls = [
             f"https://www.google.com/search?q={encoded_query}&safe=off&num={max_results}",
@@ -108,7 +99,6 @@ class GoogleSearch(SearchEngine):
                     
                     soup = BeautifulSoup(response.text, 'html.parser')
                     
-                    # Try multiple selectors
                     selectors = [
                         ('div', 'g'),
                         ('div', 'tF2Cxc'),
@@ -128,17 +118,14 @@ class GoogleSearch(SearchEngine):
                     results = []
                     for result in search_results[:max_results]:
                         try:
-                            # Extract title
                             title_elem = result.find('h3') or result.find('h2')
                             if not title_elem:
                                 continue
                             
-                            # Extract snippet
                             snippet_elem = result.find('div', class_='VwiC3b') or \
                                           result.find('div', class_='IsZvec') or \
                                           result.find('div', class_='lEBKkf')
                             
-                            # Extract link
                             link_elem = result.find('a')
                             if not link_elem:
                                 continue
@@ -171,8 +158,6 @@ class GoogleSearch(SearchEngine):
         return []
 
 class DuckDuckGoSearch(SearchEngine):
-    """DuckDuckGo search implementation"""
-    
     @staticmethod
     def search(query: str, max_results: int = 6, max_chars: int = 50) -> List[SearchResult]:
         try:
@@ -189,8 +174,6 @@ class DuckDuckGoSearch(SearchEngine):
             return []
 
 class BingSearch(SearchEngine):
-    """Bing search implementation"""
-    
     @staticmethod
     def search(query: str, max_results: int = 6, max_chars: int = 50) -> List[SearchResult]:
         try:
@@ -223,22 +206,12 @@ class BingSearch(SearchEngine):
             return []
 
 class SearchManager:
-    """Manages multiple search engines with fallback mechanism"""
-    
-    _engines = [
-        GoogleSearch,
-        DuckDuckGoSearch,
-        BingSearch
-    ]
+    _engines = [GoogleSearch, DuckDuckGoSearch, BingSearch]
     
     @classmethod
     def search(cls, query: str, max_results: int = 6, max_chars: int = 50, timeout: float = 5.0) -> List[SearchResult]:
-        """Search across all engines with timeout"""
-        results = []
-        
         for engine_cls in cls._engines:
             try:
-                # Use threading with timeout
                 result_container = []
                 search_thread = threading.Thread(
                     target=lambda: result_container.extend(engine_cls.search(query, max_results, max_chars))
@@ -255,24 +228,20 @@ class SearchManager:
                 logger.warning(f"Search engine {engine_cls.__name__} failed: {e}")
                 continue
         
-        return results
+        return []
 
 class ModelManager:
-    """Manages model loading and caching"""
-    
     _pipelines = {}
     _lock = threading.Lock()
     
     @classmethod
     def load_pipeline(cls, model_name: str) -> pipeline:
-        """Load and cache pipeline with fallback for dtype"""
         with cls._lock:
             if model_name in cls._pipelines:
                 return cls._pipelines[model_name]
             
             repo = MODELS[model_name]["repo_id"]
             
-            # Load tokenizer without token if not available
             try:
                 tokenizer = AutoTokenizer.from_pretrained(
                     repo, 
@@ -282,7 +251,6 @@ class ModelManager:
                 logger.warning(f"Failed to load tokenizer with token, trying without: {e}")
                 tokenizer = AutoTokenizer.from_pretrained(repo)
             
-            # Try different dtypes
             for dtype in (torch.bfloat16, torch.float16, torch.float32):
                 try:
                     pipe_kwargs = {
@@ -294,7 +262,6 @@ class ModelManager:
                         'device_map': "auto",
                         'use_cache': True,
                     }
-                    # Only add token if it exists
                     if ACCESS_TOKEN:
                         pipe_kwargs['token'] = ACCESS_TOKEN
                     
@@ -305,7 +272,6 @@ class ModelManager:
                     logger.warning(f"Failed to load with {dtype}: {e}")
                     continue
             
-            # Final fallback
             pipe_kwargs = {
                 'task': "text-generation",
                 'model': repo,
@@ -322,11 +288,8 @@ class ModelManager:
             return pipe
 
 class PromptBuilder:
-    """Builds prompts for different models"""
-    
     @staticmethod
     def format_conversation(history: List[Dict], system_prompt: str, tokenizer) -> str:
-        """Format conversation with proper chat template"""
         if hasattr(tokenizer, "chat_template") and tokenizer.chat_template:
             messages = [{"role": "system", "content": system_prompt.strip()}] + history
             return tokenizer.apply_chat_template(
@@ -336,462 +299,214 @@ class PromptBuilder:
                 enable_thinking=True
             )
         else:
-            # Fallback for base LMs
-            prompt = f"{ prompt = f"{system_prompt.stripsystem_prompt.strip()}\n"
-()}\n"
+            prompt = f"{system_prompt.strip()}\n"
             for msg in history:
-                role            for msg in history:
-                role = "User" = "User" if msg['role'] == 'user if msg['role'] == 'user' else "Assistant"
-                prompt += f"{role}: {msg['content' else "Assistant"
-                prompt += f"{role}: {msg['content'].strip()}\'].strip()}\n"
-            
-           n"
+                if msg['role'] == 'user':
+                    prompt += f"User: {msg['content'].strip()}\n"
+                elif msg['role'] == 'assistant':
+                    prompt += f"Assistant: {msg['content'].strip()}\n"
             
-            if not prompt.strip if not prompt.strip().endswith("Assistant:"):
-               ().endswith("Assistant:"):
-                prompt += " prompt += "Assistant: "
-            returnAssistant: "
+            if not prompt.strip().endswith("Assistant:"):
+                prompt += "Assistant: "
             return prompt
     
     @staticmethod
-    def prompt
-    
-    @staticmethod
-    def build_search_context(search_results: List build_search_context(search_results: List[SearchResult], system_prompt: str[SearchResult], system_prompt: str, user_query: str) -> str, user_query: str) -> str:
-        """Build enriched prompt with search:
-        """Build enriched prompt with search context"""
+    def build_search_context(search_results: List[SearchResult], system_prompt: str, user_query: str) -> str:
         if not search_results:
- context"""
-        if not search_results:
-            return system_prompt.strip()
-        
             return system_prompt.strip()
         
-        formatted_results = "\n".join        formatted_results = "\n".join(f"[{i(f"[{i+1}] {r.format()}" for i, r+1}] {r.format()}" for i, r in enumerate(search_results in enumerate(search_results))
-        
-        return f"""{))
+        formatted_results = "\n".join(f"[{i+1}] {r.format()}" for i, r in enumerate(search_results))
         
         return f"""{system_prompt.strip()}
 
-#system_prompt.strip()}
-
-# SEARCH CONTEXT (TRUSTED SEARCH CONTEXT (TRUSTED SOURCES ONLY)
-Below are search SOURCES ONLY)
-Below are search results. Treat them as the ONLY source results. Treat them as the ONLY source of truth for answering.
-{formatted of truth for answering.
+# SEARCH CONTEXT (TRUSTED SOURCES ONLY)
+Below are search results. Treat them as the ONLY source of truth for answering.
 {formatted_results}
 
-RULES (VERY_results}
-
 RULES (VERY IMPORTANT):
-- Do NOT use outside IMPORTANT):
-- Do NOT use outside knowledge. Do NOT knowledge. Do NOT guess or fill missing information.
-- If the answer is guess or fill missing information.
-- If the answer is not clearly supported by not clearly supported by the search results, the search results, say: "Not say: "Not enough information in the provided sources."
-- Every factual statement must enough information in the provided sources."
-- Every factual statement must be directly supported by at least one citation be directly supported by at least one citation [citation:X].
-- Do NOT [citation:X].
-- Do NOT add explanations, examples, or background that add explanations, examples, or background that are not explicitly present in the sources.
- are not explicitly present in the sources.
-- Do NOT paraphrase beyond what is- Do NOT paraphrase beyond what is necessary for clarity.
-- If sources conflict necessary for clarity.
+- Do NOT use outside knowledge. Do NOT guess or fill missing information.
+- If the answer is not clearly supported by the search results, say: "Not enough information in the provided sources."
+- Every factual statement must be directly supported by at least one citation [citation:X].
+- Do NOT add explanations, examples, or background that are not explicitly present in the sources.
+- Do NOT paraphrase beyond what is necessary for clarity.
 - If sources conflict, mention the conflict and cite both.
-, mention the conflict and cite both.
-- If multiple sources are used, distribute- If multiple sources are used, distribute citations per sentence, not only at the citations per sentence, not only at the end.
-
-CITATION RULES end.
+- If multiple sources are used, distribute citations per sentence, not only at the end.
 
 CITATION RULES:
 - Use inline citations like this: [citation:1]
-- If multiple sources support:
-- Use inline citations like this: [citation:1]
 - If multiple sources support a sentence: [citation:1][citation:3]
- a sentence: [citation:1][citation:3]
 - Never place all citations only at the end.
 
 ANSWER POLICY:
 - Be concise and strictly grounded.
-- Never place all citations only at the end.
-
-ANSWER POLICY:
-- Be concise- No speculation, no assumptions, no "likely", no "probably".
-- and strictly grounded.
 - No speculation, no assumptions, no "likely", no "probably".
-- If the user requests a list, only include items explicitly If the user requests a list, only include items explicitly found in sources.
- found in sources.
-- If sources are insufficient, stop and ask for more data- If sources are insufficient, stop and ask for more data instead of guessing.
+- If the user requests a list, only include items explicitly found in sources.
+- If sources are insufficient, stop and ask for more data instead of guessing.
 
- instead of guessing.
-
-DATE CONTEXT:
 DATE CONTEXT:
-- Today is {- Today is {datetime.now().strftime('%Y-%mdatetime.now().strftime('%Y-%m-%d')} (use only-%d')} (use only for time reference, not for assumptions).
-
- for time reference, not for assumptions).
-
-USER QUESTION:
-{user_query}"""
+- Today is {datetime.now().strftime('%Y-%m-%d')} (use only for time reference, not for assumptions).
 
 USER QUESTION:
 {user_query}"""
 
 class StreamProcessor:
-    """Handlesclass StreamProcessor:
-    """Handles streaming token processing"""
-    
-    @staticmethod streaming token processing"""
-    
     @staticmethod
-    def process_stream(streamer
-    def process_stream(streamer: TextIteratorStreamer, history: TextIteratorStreamer, history: List[Dict]) -> Generator: List[Dict]) -> Generator[Tuple[List[Dict], str], None, None]:
-        """Process streaming tokens and handle thinking tags"""
-        thought[Tuple[List[Dict], str], None, None]:
-        """Process streaming_buf = ''
-        answer_buf = ''
-        in_ tokens and handle thinking tags"""
+    def process_stream(streamer: TextIteratorStreamer, history: List[Dict]) -> Generator[Tuple[List[Dict], str], None, None]:
         thought_buf = ''
         answer_buf = ''
-        inthought = False
-        assistant_message_started = False
-        
-        for chunk in streamer:
-_thought = False
+        in_thought = False
         assistant_message_started = False
         
         for chunk in streamer:
             if cancel_event.is_set():
-                if assistant_message_start            if cancel_event.is_set():
-                if assistant_message_started and history and history[-1]['role'] == 'ed and history and history[-1]['role'] == 'assistant':
-                   assistant':
-                    history[-1]['content'] += " [Generation Cancel history[-1]['content'] += " [Generation Canceled]"
-                yield history, "Generation canceled by usered]"
+                if assistant_message_started and history and history[-1]['role'] == 'assistant':
+                    history[-1]['content'] += " [Generation Canceled]"
                 yield history, "Generation canceled by user."
-               ."
                 break
             
             text = chunk
             
-            # Handle thinking tags
-            break
-            
-            text = chunk
-            
-            # Handle thinking tags
-            if not in_ if not in_thought and '<think>' in text:
-thought and '<think>' in text:
-                in_thought                in_thought = True
-                history.append({'role': 'assistant = True
-                history.append({'role': 'assistant', 'content':', 'content': '', 'metadata': {'title': '💭 Thought'}})
-                assistant_message_started = '', 'metadata': {'title': '💭 Thought'}})
+            if not in_thought and '<think>' in text:
+                in_thought = True
+                history.append({'role': 'assistant', 'content': '', 'metadata': {'title': '💭 Thought'}})
                 assistant_message_started = True
                 after = text.split('<think>', 1)[1]
                 thought_buf += after
                 
-                if '</think>' in thought_buf:
-                    before, after2 = thought_buf.split('</think>', 1 True
-                after = text.split('<think>', 1)[1]
-                thought_buf += after
-                
                 if '</think>' in thought_buf:
                     before, after2 = thought_buf.split('</think>', 1)
                     history[-1]['content'] = before.strip()
-                    in)
-                    history[-1]['content'] = before.strip()
                     in_thought = False
-                    answer_buf =_thought = False
                     answer_buf = after2
-                    history.append({'role after2
-                    history.append({'role': 'assistant', 'content':': 'assistant', 'content': answer_buf})
-                answer_buf})
+                    history.append({'role': 'assistant', 'content': answer_buf})
                 else:
-                    history[-1]['content'] = thought else:
                     history[-1]['content'] = thought_buf
                 yield history, ""
-_buf
-                yield history, ""
                 continue
             
-            if in_thought                continue
-            
             if in_thought:
                 thought_buf += text
-                if '</think>' in thought:
-                thought_buf += text
-                if '</think>' in thought_b_buf:
-                    beforeuf:
-                    before, after, after2 = thought_buf.split2 = thought_buf.split('</think>('</think>', 1)
-                    history[-1', 1)
+                if '</think>' in thought_buf:
+                    before, after2 = thought_buf.split('</think>', 1)
                     history[-1]['content'] = before.strip()
-                   ]['content'] = before.strip()
                     in_thought = False
-                    answer in_thought = False
                     answer_buf = after2
-                    history_buf = after2
-                    history.append({'role': 'assistant',.append({'role': 'assistant', 'content': answer_buf})
+                    history.append({'role': 'assistant', 'content': answer_buf})
                 else:
- 'content': answer_buf})
-                                   history else:
                     history[-1]['content'] = thought_buf
-                yield[-1]['content'] = thought_buf
                 yield history, ""
-                history, ""
                 continue
             
-            # continue
-            
-            # Stream answer
- Stream answer
-            if not assistant            if not assistant_message_started:
-_message_started:
-                history.append({'role': 'assistant', 'content                history.append({'role': 'assistant', 'content': ''})
-               ': ''})
-                assistant_message_started assistant_message_started = True
-            
- = True
+            if not assistant_message_started:
+                history.append({'role': 'assistant', 'content': ''})
+                assistant_message_started = True
             
             answer_buf += text
             history[-1]['content'] = answer_buf.strip()
-                       answer_buf += text
-            history[-1]['content'] yield history, ""
-
-# Main chat = answer_buf.strip()
             yield history, ""
 
-# Main chat function
-def chat_response(
-    user function
 def chat_response(
     user_msg: str,
-    chat_history:_msg: str,
     chat_history: List[Dict],
-    system_prompt List[Dict],
     system_prompt: str,
-    enable_search: bool: str,
     enable_search: bool,
     max_results: int,
-   ,
-    max_results: int,
     max_chars: int,
-    model max_chars: int,
     model_name: str,
-    max_tokens_name: str,
     max_tokens: int,
     temperature: float,
     top_k: int,
-    top: int,
-    temperature: float,
-    top_k: int,
     top_p: float,
     repeat_penalty: float,
-_p: float,
-    repeat_penalty: float,
     search_timeout: float
-) -> Generator[Tuple    search_timeout: float
 ) -> Generator[Tuple[List[Dict], str], None, None]:
-    """[List[Dict], str], None, None]:
-    """Generate streaming chat responses with search integration"""
-    
-    cancel_eventGenerate streaming chat responses with search integration"""
-    
     cancel_event.clear()
     history = list(chat_history or [])
     history.append({'role': 'user', 'content': user_msg})
     
-    # Perform search.clear()
-    history = list(chat_history or [])
-    history.append({'role': 'user', 'content': user_msg})
-    
-    # Perform search if enabled
-    if enabled
     search_results: List[SearchResult] = []
-    search_debug = " search_results: List[SearchResult] = []
     search_debug = "Web search disabled."
     
-    if enableWeb search disabled."
-    
     if enable_search:
-        search_debug = "_search:
-        search_debug = "🔍 Searching across multiple engines🔍 Searching across multiple engines..."
-        try:
-            search_results = SearchManager..."
+        search_debug = "🔍 Searching across multiple engines..."
         try:
             search_results = SearchManager.search(
                 user_msg, 
-               .search(
-                user_msg, 
                 int(max_results), 
-                int(max int(max_results), 
                 int(max_chars), 
                 float(search_timeout)
             )
             
-           _chars), 
-                float(search_timeout)
-            )
-            
-            if search if search_results:
-                search_results:
-                search_debug = f"✅ Search completed - Found {len_debug = f"✅ Search completed - Found {len(search_results)} results(search_results)} results\n\n" + "\n".join(
-                    f"-\n\n" + "\n".join(
-                    f"- {r.format(int(max_chars))}" for r {r.format(int(max_chars))}" for r in search_results
-                )
-            else:
-                search_debug = "❌ No search results found. Check internet connection or try again in search_results
+            if search_results:
+                search_debug = f"✅ Search completed - Found {len(search_results)} results\n\n" + "\n".join(
+                    f"- {r.format(int(max_chars))}" for r in search_results
                 )
             else:
                 search_debug = "❌ No search results found. Check internet connection or try again."
-        except Exception as e:
-            search_debug = f"❌ Search failed: {."
         except Exception as e:
             search_debug = f"❌ Search failed: {str(e)}"
-            logger.error(f"Search error:str(e)}"
             logger.error(f"Search error: {e}")
     
     try:
-        {e}")
-    
-    try:
-        # Build prompt
-        if enable_search and search_results:
- # Build prompt
         if enable_search and search_results:
             enriched_prompt = PromptBuilder.build_search_context(
                 search_results, 
-                           enriched_prompt = PromptBuilder.build_search_context(
-                search_results, 
-                system_prompt, system_prompt, 
-                user_msg
-            )
-        else:
-            enriched 
+                system_prompt, 
                 user_msg
             )
         else:
             enriched_prompt = system_prompt.strip()
         
-        # Load_prompt = system_prompt.strip()
-        
-        # Load model
-        pipe = ModelManager.load_pipeline(model_name model
         pipe = ModelManager.load_pipeline(model_name)
         
-        #)
-        
-        # Format prompt
         prompt = PromptBuilder.format_conversation(history, enriched_prompt, pipe.tokenizer)
-        Format prompt
-        prompt = PromptBuilder.format_conversation(history, enriched_prompt, pipe.tokenizer)
-        prompt_debug = f"\n\n--- Prompt Preview ---\n``` prompt_debug = f"\n\n--- Prompt Preview ---\n```\n{prompt[:500]}...\n```" if len(prompt) > 500 else f"\n\n--- Prompt Preview ---\n```\n{prompt}\n```"
-        
-        # Configure generation
-        config = GenerationConfig(
-            max_tokens\n{prompt[:500]}...\n```" if len(prompt) > 500 else f"\n\n--- Prompt Preview ---\n```\n{prompt}\n```"
+        prompt_debug = f"\n\n--- Prompt Preview ---\n```\n{prompt[:500]}...\n```" if len(prompt) > 500 else f"\n\n--- Prompt Preview ---\n```\n{prompt}\n```"
         
-        # Configure generation
         config = GenerationConfig(
             max_tokens=max_tokens,
             temperature=temperature,
             top_k=top_k,
             top_p=top_p,
-           =max_tokens,
-            temperature=temperature,
-            top_k=top_k,
-            top_p=top_p,
-            repetition_penalty= repetition_penalty=repeat_penalty
+            repetition_penalty=repeat_penalty
         )
         
-        # Setuprepeat_penalty
-        )
-        
-        # Setup streamer
-        streamer = TextIteratorStreamer(
- streamer
         streamer = TextIteratorStreamer(
-            pipe.tokenizer            pipe.tokenizer,
-            skip_prompt=True,
-            skip_special_t,
+            pipe.tokenizer,
             skip_prompt=True,
             skip_special_tokens=True
         )
         
-        # Start generation in background thread
-        genokens=True
-        )
-        
-        # Start generation in background thread
-        gen_kwargs =_kwargs = config.to_dict()
- config.to_dict()
-        gen_kwargs['streamer'] = streamer        gen_kwargs['streamer'] = streamer
-        gen_k
-        gen_kwargs['returnwargs['return_full_text'] = False
-        
-        gen_thread = threading.Thread_full_text'] = False
+        gen_kwargs = config.to_dict()
+        gen_kwargs['streamer'] = streamer
+        gen_kwargs['return_full_text'] = False
         
         gen_thread = threading.Thread(
-            target=(
             target=pipe,
-            argspipe,
             args=(prompt,),
-            kwargs=gen_kwargs=(prompt,),
             kwargs=gen_kwargs
         )
-       
-        )
         gen_thread.start()
- gen_thread.start()
         
-        # Yield        
-        # Yield initial state
-        yield history, search_debug initial state
         yield history, search_debug
         
-        # Process stream
-
-        
-        # Process stream
-        for history_update, debug_update in        for history_update, debug_update in StreamProcessor.process_stream(streamer, history):
-            yield history_update StreamProcessor.process_stream(streamer, history):
+        for history_update, debug_update in StreamProcessor.process_stream(streamer, history):
             yield history_update, debug_update
         
-        # Wait for, debug_update
-        
-        # Wait for completion
         gen_thread.join(timeout=5.0)
-        yield history completion
-        gen_thread.join(timeout=5.0)
-, search_debug + prompt_de        yield history, search_debug + prompt_debug
-        
-    exceptbug
+        yield history, search_debug + prompt_debug
         
     except GeneratorExit:
         logger.info("Generation cancelled by user")
- GeneratorExit:
-        logger.info("Generation cancelled by user")
         return
-           return
-    except Exception as e except Exception as e:
-        logger.error:
+    except Exception as e:
         logger.error(f"Generation error: {e}")
-        history.append({'role': 'ass(f"Generation error: {e}")
-        history.append({'role': 'assistant', 'content': f"Erroristant', 'content': f"Error: {str(e)}"})
-       : {str(e)}"})
+        history.append({'role': 'assistant', 'content': f"Error: {str(e)}"})
         yield history, search_debug
-    yield history, search_debug
     finally:
         gc.collect()
 
-# finally:
-        gc.collect()
-
-# Utility functions
-def get_model_size(model_name: str) -> Utility functions
 def get_model_size(model_name: str) -> float:
-    """Get model size in billions float:
-    """Get model size in billions of parameters"""
-    return MODELS.get(model_name of parameters"""
-    return MODELS.get(model_name, {}).get("params_b",, {}).get("params_b", 4.0)
-
-def get_d 4.0)
+    return MODELS.get(model_name, {}).get("params_b", 4.0)
 
 def get_duration_estimate(
     model_name: str,
@@ -799,35 +514,16 @@ def get_duration_estimate(
     max_tokens: int,
     search_timeout: float
 ) -> float:
-    """Calculate estimated GPU duration"""
-    model_size = get_modeluration_estimate(
-    model_name: str,
-    enable_search: bool,
-    max_tokens: int,
-    search_timeout: float
-) -> float:
-    """Calculate estimated GPU duration"""
     model_size = get_model_size(model_name)
     use_aot = model_size >= 2
     
-    base_duration = 20 if not use_aot else 40
-    token_duration = max_tokens * 0.005_size(model_name)
-    use_aot = model_size >= 2
-    
     base_duration = 20 if not use_aot else 40
     token_duration = max_tokens * 0.005
     search_duration = 10 if enable_search else 0
-    aot_compilation = 20
-    search_duration = 10 if enable_search else 0
     aot_compilation = 20 if use_aot else 0
     
     return base_duration + token_duration + search_duration + aot_compilation
 
-def update_duration_estimate(
-    if use_aot else 0
-    
-    return base_duration + token_duration + search_duration + aot_compilation
-
 def update_duration_estimate(
     model_name: str,
     enable_search: bool,
@@ -836,21 +532,6 @@ def update_duration_estimate(
     max_tokens: int,
     search_timeout: float
 ) -> str:
-    """Format duration estimate for display"""
-    try:
-        duration = get_duration_estimate(model_name, enable_search, max_tokens, search_timeout)
-        model_size = get_model_size(model_name)
-        
-        return f"""⏱️ **Estimated GPU Time: {duration:.1f} seconds**
-
- model_name: str,
-    enable_search: bool,
-    max_results: int,
-    max_chars: int,
-    max_tokens: int,
-    search_timeout: float
-) -> str:
-    """Format duration estimate for display"""
     try:
         duration = get_duration_estimate(model_name, enable_search, max_tokens, search_timeout)
         model_size = get_model_size(model_name)
@@ -858,142 +539,64 @@ def update_duration_estimate(
         return f"""⏱️ **Estimated GPU Time: {duration:.1f} seconds**
 
 📊 **Model Size:** {model_size:.1f}B parameters
-📊 **Model Size:** {model_size:.1f}B parameters
-🔍 **Web Search:** {'Enabled (Multi-Engine)' if enable_search else🔍 **Web Search:** {'Enabled (Multi-Engine)' if enable_search else 'Disabled'}"""
-    except Exception as 'Disabled'}"""
+🔍 **Web Search:** {'Enabled (Multi-Engine)' if enable_search else 'Disabled'}"""
     except Exception as e:
-        logger.error(f"Error e:
         logger.error(f"Error calculating estimate: {e}")
-        return calculating estimate: {e}")
-        return f"⚠️ Error calculating estimate: f"⚠️ Error calculating estimate: {e}"
-
-def update_default_p {e}"
+        return f"⚠️ Error calculating estimate: {e}"
 
-def update_default_prompt(enable_search: bool) ->rompt(enable_search: bool) -> str:
-    """Generate default system str:
-    """Generate default system prompt"""
+def update_default_prompt(enable_search: bool) -> str:
     return "You are a helpful assistant."
 
-# ------------------------------
-# Grad prompt"""
-    return "You are a helpful assistant."
-
-# ------------------------------
-io UI
-# ------------------------------
-with gr.Blocks(
-    title="# Gradio UI
-# ------------------------------
 with gr.Blocks(
     title="LLM Inference",
-    theme=gr.themes.SoftLLM Inference",
     theme=gr.themes.Soft(
         primary_hue="blue",
         secondary_hue="blue",
         neutral_hue="slate",
-       (
-        primary_hue="blue",
-        secondary_hue="blue",
-        neutral_hue="slate",
         radius_size="lg",
-        font=[gr.themes.GoogleFont("Syne"), "Arial", "s radius_size="lg",
         font=[gr.themes.GoogleFont("Syne"), "Arial", "sans-serif"]
     ),
     css="""
-        .durationans-serif"]
-    ),
-    css="""
-        .duration-estimate { background: linear-gradient(135deg, #-estimate { background: linear-gradient(667eea15 0%, #764ba215 135deg, #667eea15 0%, #764ba215 100%); border-left100%); border-left: 4px solid #667eea; padding: 12px; border-radius: 8px; margin: 16px 0; }
-        .chatbot: 4px solid #667eea; padding: 12px; border-radius: 8px; margin: 16px 0; }
- { border-radius: 12px; box-shadow: 0 4px        .chatbot { border-radius: 12px; box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1 6px -1px rgba(0, 0, 0,); }
+        .duration-estimate { background: linear-gradient(135deg, #667eea15 0%, #764ba215 100%); border-left: 4px solid #667eea; padding: 12px; border-radius: 8px; margin: 16px 0; }
+        .chatbot { border-radius: 12px; box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1); }
         button.primary { font-weight: 600; }
-        0.1); }
-        button.primary { font-weight: 600 .gradio-accordion { margin-bottom: 12px; }
-    """
-) as demo:
-    # Header
-    gr.Mark; }
         .gradio-accordion { margin-bottom: 12px; }
     """
 ) as demo:
-    # Header
     gr.Markdown("""
     # 🧠 LLM Inference with Multi-Engine Search
     """)
     
-   down("""
-    # 🧠 LLM Inference with Multi-Engine Search
-    """)
-    
     with gr.Row():
-        # Left Panel - Configuration
         with gr.Column(scale=3):
-            # Core with gr.Row():
-        # Left Panel - Configuration
-        with gr.Column(scale=3):
-            # Core Settings (Always Visible)
-            with gr.Group():
-                gr.Markdown(" Settings (Always Visible)
             with gr.Group():
                 gr.Markdown("### ⚙️ Core Settings")
-                model_dd = gr.Drop### ⚙️ Core Settings")
                 model_dd = gr.Dropdown(
                     label="🤖 Model",
                     choices=list(MODELS.keys()),
                     value="Qwen3-1.7B",
                     info="Select the language model to use"
                 )
-                search_chk = gr.Checkbox(
-                    label="🔍 Enabledown(
-                    label="🤖 Model",
-                    choices=list(MODELS.keys()),
-                    value="Qwen3-1.7B",
-                    info="Select the language model to use"
-                )
                 search_chk = gr.Checkbox(
                     label="🔍 Enable Web Search",
                     value=False,
-                    info="Search across Google Web Search",
-                    value=False,
                     info="Search across Google, DuckDuckGo, and Bing (no API required)"
                 )
-                sys_prompt = gr.Textbox(label="📝, DuckDuckGo, and Bing (no API required)"
-                )
                 sys_prompt = gr.Textbox(label="📝 System Prompt", lines=3, value=update_default_prompt(False), placeholder="Define the assistant's behavior and personality...")
             
-            # Duration Estimate
             duration_display = gr.Markdown(
-                value=update_duration_estimate(" System Prompt", lines=3, value=update_default_prompt(False), placeholder="Define the assistant's behavior and personality...")
-            
-            # Duration Estimate
-            duration_display = gr.Markdown(
-                value=update_duration_estimate("Qwen3-Qwen3-1.7B", False, 4, 50, 1024, 5.0),
-                elem_classes="duration-estimate"
-            )
-1.7B", False, 4, 50, 1024, 5.0),
+                value=update_duration_estimate("Qwen3-1.7B", False, 4, 50, 1024, 5.0),
                 elem_classes="duration-estimate"
             )
             
-            # Advanced Settings (Collapsible)
-            with gr.Accordion("🎛️ Advanced Generation Parameters", open=False):
-                max_tok = gr.Slider(
-                    64, 16384, value            
-            # Advanced Settings (Collapsible)
             with gr.Accordion("🎛️ Advanced Generation Parameters", open=False):
                 max_tok = gr.Slider(
                     64, 16384, value=1024, step=32,
-                    label="Max=1024, step=32,
                     label="Max Tokens",
                     info="Maximum length of generated response"
                 )
                 temp = gr.Slider(
-                    0.1, 2.0, value=0. Tokens",
-                    info="Maximum length of generated response"
-                )
-                temp = gr.Slider(
-                    0.1, 2.0,7, step=0.1,
-                    label="Temperature",
-                    info="Higher = more creative, Lower value=0.7, step=0.1,
+                    0.1, 2.0, value=0.7, step=0.1,
                     label="Temperature",
                     info="Higher = more creative, Lower = more focused"
                 )
@@ -1004,73 +607,33 @@ with gr.Blocks(
                         info="Number of top tokens to consider"
                     )
                     p = gr.Slider(
- = more focused"
-                )
-                with gr.Row():
-                    k = gr.Slider(
-                        1, 100, value=40, step=1,
-                        label="Top-K",
-                        info="Number of top tokens to consider"
-                    )
-                    p = gr                        0.1, 1.0, value=0.9, step=0.05,
-                        label="Top-P",
-.Slider(
                         0.1, 1.0, value=0.9, step=0.05,
                         label="Top-P",
                         info="Nucleus sampling threshold"
                     )
-                rp = gr.Slider(
-                    1.0, 2.0, value=1.2, step=0.                        info="Nucleus sampling threshold"
-                    )
                 rp = gr.Slider(
                     1.0, 2.0, value=1.2, step=0.1,
                     label="Repetition Penalty",
                     info="Penalize repeated tokens"
                 )
             
-            # Web Search Settings (Collapsible)
-            with gr.Acc1,
-                    label="Repetition Penalty",
-                    info="Penalize repeated tokens"
-                )
-            
-            # Web Search Settings (Collapsible)
-            with gr.Accordion("ordion("🌐 Web Search Settings", open=False, visible=False) as search_settings:
-                mr = gr.Number(
-                    value=4, precision=0,
-                    label="Max🌐 Web Search Settings", open=False, visible=False) as search_settings:
+            with gr.Accordion("🌐 Web Search Settings", open=False, visible=False) as search_settings:
                 mr = gr.Number(
                     value=4, precision=0,
                     label="Max Results",
-                    info="Number of search results to Results",
                     info="Number of search results to retrieve"
                 )
                 mc = gr.Number(
                     value=50, precision=0,
                     label="Max Chars/Result",
-                    info="Character limit per search retrieve"
-                )
-                mc = gr.Number(
-                    value=50, precision=0,
-                    label="Max Chars/Result",
-                    info=" result"
-                )
-                st = grCharacter limit per search result"
+                    info="Character limit per search result"
                 )
                 st = gr.Slider(
-                    minimum=0.0, maximum=30.0, step=0.5, value=.Slider(
                     minimum=0.0, maximum=30.0, step=0.5, value=5.0,
                     label="Search Timeout (s)",
-                    info5.0,
-                    label="Search Timeout (s)",
                     info="Maximum time to wait for search results"
                 )
-                gr="Maximum time to wait for search results"
-                )
-                gr.Markdown("".Markdown("""
-                ⚠️ **Search Engines:**
-                - Google (primary)
-                - DuckD"
+                gr.Markdown("""
                 ⚠️ **Search Engines:**
                 - Google (primary)
                 - DuckDuckGo (fallback)
@@ -1079,303 +642,129 @@ with gr.Blocks(
                 SafeSearch is **OFF** for comprehensive results.
                 """)
             
-            # Actions
-            with gr.Row():
-                clr = gr.Button("uckGo (fallback)
-                - Bing (fallback)
-                
-                SafeSearch is **OFF** for comprehensive results.
-                """)
-            
-            # Actions
             with gr.Row():
-                clr =🗑️ Clear Chat", variant="secondary", scale=1 gr.Button("🗑️ Clear Chat", variant="secondary", scale=1)
+                clr = gr.Button("🗑️ Clear Chat", variant="secondary", scale=1)
         
-        # Right Panel - Chat)
-        
-        # Right Panel - Chat Interface
         with gr.Column(scale=7):
             chat = gr.Chatbot(
                 type="messages",
- Interface
-        with gr.Column(scale=7):
-            chat = gr.Chatbot(
-                type="messages                height=600,
-                label="💬 Conversation",
-                show_copy_button=True,
-                avatar_images=(
-                   ",
                 height=600,
                 label="💬 Conversation",
                 show_copy_button=True,
-                avatar "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3C_images=(
-                    "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3Crect width='40rect width='40' height='40' rx='20' fill='%' height='40' rx='20' fill='%23f093fb23f093fb'/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20''/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20' fill='white' font-family='Arial'%3E👤%3C/text%3E%3 fill='white' font-family='Arial'%3E👤%3C/text%3E%3C/svg%3E",
-                    "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3Crect width='40' height='40' rx='20' fill='%23667eea'/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20' fill='white'C/svg%3E",
-                    "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3Crect width='40' height='40' rx='20' fill='%23667eea'/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20' fill=' font-family='Arial'%3E🤖%3C/text%3E%3C/svg%3E"
-                ),
-                bubble_fullwhite' font-family='Arial'%3E🤖%3C/text%3E%3C/svg%3E"
+                avatar_images=(
+                    "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3Crect width='40' height='40' rx='20' fill='%23f093fb'/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20' fill='white' font-family='Arial'%3E👤%3C/text%3E%3C/svg%3E",
+                    "data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='40' height='40'%3E%3Crect width='40' height='40' rx='20' fill='%23667eea'/%3E%3Ctext x='20' y='28' text-anchor='middle' font-size='20' fill='white' font-family='Arial'%3E🤖%3C/text%3E%3C/svg%3E"
                 ),
                 bubble_full_width=False,
                 render_markdown=True,
-                sanit_width=False,
-                render_markdown=True,
                 sanitize_html=False
-ize_html=False
             )
             
-            # Input Area
-            with            )
-            
-            # Input Area
             with gr.Row():
-                txt gr.Row():
                 txt = gr.Textbox(
-                    placeholder="💭 Type your = gr.Textbox(
-                    placeholder="💭 Type your message here... ( message here... (Press Enter to sendPress Enter to send)",
-                    scale)",
+                    placeholder="💭 Type your message here... (Press Enter to send)",
                     scale=9,
                     container=False,
-                   =9,
-                    container=False,
                     show_label=False,
-                    lines=1 show_label=False,
                     lines=1,
                     max_lines=5
-               ,
-                    max_lines=5
                 )
-                with gr.Column(scale= )
                 with gr.Column(scale=1, min_width=120):
-                   1, min_width=120):
-                    submit_btn = gr.Button("📤 Send", variant="primary", size submit_btn = gr.Button("📤 Send", variant="primary", size="lg")
-                    cancel_btn = gr.Button("⏹️ Stop", variant="stop", visible=False="lg")
+                    submit_btn = gr.Button("📤 Send", variant="primary", size="lg")
                     cancel_btn = gr.Button("⏹️ Stop", variant="stop", visible=False, size="lg")
             
-            #, size="lg")
-            
-            # Example Prompts
-            gr.Examples(
-                examples=[
-                    ["Explain Example Prompts
             gr.Examples(
                 examples=[
                     ["Explain quantum computing in simple terms"],
-                    ["Write a Python function to quantum computing in simple terms"],
                     ["Write a Python function to calculate fibonacci numbers"],
-                    ["What are the calculate fibonacci numbers"],
-                    ["What are the latest developments in AI? (Enable latest developments in AI? (Enable web search)"],
+                    ["What are the latest developments in AI? (Enable web search)"],
                     ["Tell me a creative story about a time traveler"],
- web search)"],
-                    ["Tell me a creative story about a time traveler"],
-                    ["Help me debug this code: def add(a,b): return a+b+1"]
                     ["Help me debug this code: def add(a,b): return a+b+1"]
                 ],
-                inputs                ],
                 inputs=txt,
                 label="💡 Example Prompts"
-=txt,
-                label="💡 Example Prompts"
             )
             
-            # Debug/Status Info (Collapsible)
-            with gr.Accordion("🔍 Debug Info", open=False):
-                dbg = gr.Markdown()
-    
-    # Footer
-    gr.Markdown("""
-    ---
-    💡 **Tips            )
-            
-            # Debug/Status Info (Collapsible)
             with gr.Accordion("🔍 Debug Info", open=False):
                 dbg = gr.Markdown()
     
-    # Footer
     gr.Markdown("""
     ---
     💡 **Tips:** 
     - Use **Advanced Parameters** to fine-tune creativity and response length
-    - Enable **Web Search:** 
-    - Use **Advanced Parameters** to fine-tune creativity and response length
-    - Enable **Web Search** for real-time information (uses** for real-time information (uses multiple search engines)
-    - SafeSearch is **OFF** multiple search engines)
+    - Enable **Web Search** for real-time information (uses multiple search engines)
     - SafeSearch is **OFF** for comprehensive results
-    - Try different ** for comprehensive results
-    - Try different **models** for various tasks (reasonmodels** for various tasks (reasoning, coding, general chat)
-   ing, coding, general chat)
-    - Click the **Copy** button on - Click the **Copy** button on responses to save them to your clipboard
- responses to save them to your clipboard
+    - Try different **models** for various tasks (reasoning, coding, general chat)
+    - Click the **Copy** button on responses to save them to your clipboard
     """, elem_classes="footer")
 
-    # --- Event Listeners ---
+    chat_inputs = [txt, chat, sys_prompt, search_chk, mr, mc, model_dd, max_tok, temp, k, p, rp, st]
+    ui_components = [chat, dbg, txt, submit_btn, cancel_btn]
 
-       """, elem_classes="footer")
-
-    # --- Event Listeners ---
-
-    # Group # Group all inputs for cleaner event handling
-    chat_inputs = [txt, chat, sys_p all inputs for cleaner event handling
-    chat_inputs = [txt, chat, sys_prompt, search_chk,rompt, search_chk, mr, mc, model_dd, max mr, mc, model_dd, max_tok, temp, k, p_tok, temp, k, p, rp, st]
-    #, rp, st]
-    # Group all UI components that can Group all UI components that can be updated.
-    ui_components = be updated.
-    ui_components = [chat, dbg, txt, submit [chat, dbg, txt, submit_btn, cancel_btn, cancel_btn]
-
-    def submit_and_manage_ui(user_btn]
-
-    def submit_and_manage_ui(user_msg, chat_history_msg, chat_history, *args):
-, *args):
-        """
-        Orche        """
-        Orchestrator function that manages UI state andstrator function that manages UI state and calls the backend chat function.
-        """
- calls the backend chat function.
-        """
+    def submit_and_manage_ui(user_msg, chat_history, *args):
         if not user_msg.strip():
-                   if not user_msg.strip():
             yield {}
             return
 
-        # yield {}
-            return
-
-        # Update UI to "generating" state
-        yield {
-            txt: gr.update(value="", interactive Update UI to "generating" state
         yield {
-            txt: gr.update(value="",=False),
-            submit_btn: gr.update(inter interactive=False),
+            txt: gr.update(value="", interactive=False),
             submit_btn: gr.update(interactive=False),
-            cancel_active=False),
             cancel_btn: gr.update(visible=True),
         }
 
-btn: gr.update(visible=True),
-        }
-
-        cancelled = False        cancelled = False
+        cancelled = False
         try:
-            backend_args = [user_msg,
-        try:
-            backend_args = [user_msg, chat_history] + chat_history] + list(args)
-            for response_chunk in chat_response(*backend_args):
-                yield {
-                    chat list(args)
+            backend_args = [user_msg, chat_history] + list(args)
             for response_chunk in chat_response(*backend_args):
                 yield {
                     chat: response_chunk[0],
-                    dbg: response: response_chunk[0],
                     dbg: response_chunk[1],
                 }
         except GeneratorExit:
-_chunk[1],
-                }
-        except GeneratorExit:
             cancelled = True
-            print("Generation cancelled by user            cancelled = True
             print("Generation cancelled by user.")
             raise
         except Exception as e:
-            print.")
-            raise
-        except Exception as e:
-            print(f"An error occurred during generation: {e(f"An error occurred during generation: {e}")
-            error_history = (}")
+            print(f"An error occurred during generation: {e}")
             error_history = (chat_history or []) + [
-               chat_history or []) + [
                 {'role': 'user', 'content': user_msg},
-                {'role': 'assistant', 'content': f {'role': 'user', 'content': user_msg},
                 {'role': 'assistant', 'content': f"**An error occurred:** {str(e)}"}
             ]
-            yield {"**An error occurred:** {str(e)}"}
-            ]
             yield {chat: error_history}
         finally:
-chat: error_history}
-        finally:
             if not cancelled:
-                print("            if not cancelled:
                 print("Resetting UI state.")
                 yield {
-Resetting UI state.")
-                yield {
-                    txt: gr.update(inter                    txt: gr.update(interactive=True),
-                    submit_btn: gractive=True),
+                    txt: gr.update(interactive=True),
                     submit_btn: gr.update(interactive=True),
-.update(interactive=True),
-                    cancel_btn: gr.update(visible=False                    cancel_btn: gr.update(visible=False),
-                }
-
-    def set_c),
+                    cancel_btn: gr.update(visible=False),
                 }
 
     def set_cancel_flag():
-        """Called by the cancel button, sets the global eventancel_flag():
-        """Called by the cancel button, sets the global event."""
-        cancel_event.set()
-        print("Cancellation signal."""
         cancel_event.set()
         print("Cancellation signal sent.")
     
-    def reset_ui_after_cancel sent.")
-    
     def reset_ui_after_cancel():
-        """Reset UI components after cancellation."""
         cancel_event.clear()
         print("UI reset after cancellation.")
         return {
             txt: gr.update(interactive=True),
-           ():
-        """Reset UI components after cancellation."""
-        cancel_event.clear()
-        print("UI reset after cancellation.")
-        return {
-            txt: gr.update(interactive=True),
-            submit_btn: submit_btn: gr.update(interactive=True),
-            cancel_btn: gr.update(visible gr.update(interactive=True),
+            submit_btn: gr.update(interactive=True),
             cancel_btn: gr.update(visible=False),
         }
 
-    # Event for=False),
-        }
-
-    # Event for submitting text via Enter key or Submit submitting text via Enter key or Submit button
-    submit_event = txt button
     submit_event = txt.submit(
-        fn=submit_and.submit(
-        fn=submit_and_manage_ui_manage_ui,
-        inputs=chat_inputs,
-        outputs=ui,
+        fn=submit_and_manage_ui,
         inputs=chat_inputs,
         outputs=ui_components,
     )
-    submit_btn.click(
-        fn=submit_and_components,
-    )
     submit_btn.click(
         fn=submit_and_manage_ui,
-        inputs_manage_ui,
-        inputs==chat_inputs,
-        outputs=ui_components,
-    )
-
-    # Eventchat_inputs,
+        inputs=chat_inputs,
         outputs=ui_components,
     )
 
-    # Event for the "Cancel" button.
-    for the "Cancel" button.
-    cancel_btn.click cancel_btn.click(
-        fn=set_cancel_flag,
-        cancels=[submit_event]
-    ).then(
-        fn=reset_ui_after_cancel,
-        outputs=ui_components
-    )
-
-    # Listeners for updating the duration estimate
-    duration_inputs = [model_dd, search_chk, mr, mc, max_tok, st]
-    for(
+    cancel_btn.click(
         fn=set_cancel_flag,
         cancels=[submit_event]
     ).then(
@@ -1383,38 +772,19 @@ Resetting UI state.")
         outputs=ui_components
     )
 
-    # Listeners for updating the duration estimate
     duration_inputs = [model_dd, search_chk, mr, mc, max_tok, st]
     for component in duration_inputs:
-        component.change(fn=update_duration_ component in duration_inputs:
-        component.change(fn=update_duration_estimate, inputs=duration_inputs, outputs=duration_destimate, inputs=duration_inputs, outputs=duration_display)
-
-    #isplay)
+        component.change(fn=update_duration_estimate, inputs=duration_inputs, outputs=duration_display)
 
-    # Toggle web search Toggle web search settings visibility
     def toggle_search_settings(enabled):
-        settings visibility
-    def toggle_search_settings(enabled):
-        return gr.update( return gr.update(visible=enabled)
-    
-    search_chvisible=enabled)
+        return gr.update(visible=enabled)
     
     search_chk.change(
-        fn=lambda enabled:k.change(
-        fn=lambda enabled: (update_default_prompt(enabled), gr.update(visible (update_default_prompt(enabled), gr.update(visible=enabled)),
-       =enabled)),
-        inputs=search inputs=search_chk,
-        outputs_chk,
+        fn=lambda enabled: (update_default_prompt(enabled), gr.update(visible=enabled)),
+        inputs=search_chk,
         outputs=[sys_prompt, search_settings]
     )
-=[sys_prompt, search_settings]
-    )
-    
-    # Clear    
-    # Clear chat action
- chat action
-    clr.click(f    clr.click(fn=lambda: ([], "", ""n=lambda: ([], "", ""), outputs=[chat, txt, db), outputs=[chat, txt, dbg])
     
-    demo.launchg])
+    clr.click(fn=lambda: ([], "", ""), outputs=[chat, txt, dbg])
     
     demo.launch(share=True)