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mgbam commited on Jul 16

Commit

20ee71d

verified ·

1 Parent(s): b1d6425

Update api_clients.py

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Files changed (1) hide show

api_clients.py +14 -19

api_clients.py CHANGED Viewed

@@ -21,26 +21,15 @@ from web_extraction import extract_website_content, enhance_query_with_search
 # HF Inference Client
 HF_TOKEN = os.getenv('HF_TOKEN')
-GROQ_API_KEY = os.getenv('GROQ_API_KEY')
-FIREWORKS_API_KEY = os.getenv('FIREWORKS_API_KEY')
 def get_inference_client(model_id):
-    """Return an InferenceClient configured for Hugging Face, Groq, or Fireworks AI."""
-    if model_id == "moonshotai/Kimi-K2-Instruct":
-        return InferenceClient(
-            base_url="https://api.groq.com/openai/v1",
-            api_key=GROQ_API_KEY
-        )
-    elif model_id.startswith("fireworks/"):
-        return InferenceClient(
-            base_url="https://api.fireworks.ai/inference/v1",
-            api_key=FIREWORKS_API_KEY
-        )
-    else:
-        return InferenceClient(
-            model=model_id,
-            api_key=HF_TOKEN
-        )
 # Tavily Search Client
 TAVILY_API_KEY = os.getenv('TAVILY_API_KEY')
@@ -52,7 +41,7 @@ if TAVILY_API_KEY:
         print(f"Failed to initialize Tavily client: {e}")
         tavily_client = None
-async def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[List[Tuple[str, str]]], _current_model: Dict, enable_search: bool = False, language: str = "html"):
     if query is None:
         query = ''
     if _history is None:
@@ -65,6 +54,7 @@ async def generation_code(query: Optional[str], image: Optional[gr.Image], file:
         last_assistant_msg = _history[-1][1] if len(_history) > 0 else ""
         if '<!DOCTYPE html>' in last_assistant_msg or '<html' in last_assistant_msg:
             has_existing_html = True
     # Choose system prompt based on context
     if has_existing_html:
@@ -81,12 +71,14 @@ async def generation_code(query: Optional[str], image: Optional[gr.Image], file:
     # Extract file text and append to query if file is present
     file_text = ""
     if file:
         file_text = extract_text_from_file(file)
         if file_text:
             file_text = file_text[:5000]  # Limit to 5000 chars for prompt size
             query = f"{query}\n\n[Reference file content below]\n{file_text}"
     # Extract website content and append to query if website URL is present
     website_text = ""
     if website_url and website_url.strip():
@@ -105,6 +97,7 @@ Since I couldn't extract the website content, please provide additional details
 This will help me create a better design for you."""
             query = f"{query}\n\n[Error extracting website: {website_text}]{fallback_guidance}"
     # Enhance query with search if enabled
     enhanced_query = enhance_query_with_search(query, enable_search)
@@ -115,6 +108,7 @@ This will help me create a better design for you."""
         messages.append(create_multimodal_message(enhanced_query, image))
     else:
         messages.append({'role': 'user', 'content': enhanced_query})
     try:
         completion = client.chat.completions.create(
             model=_current_model["id"], # Corrected this line
@@ -122,6 +116,7 @@ This will help me create a better design for you."""
             stream=True,
             max_tokens=5000
         )
         content = ""
         for chunk in completion:
             if chunk.choices[0].delta.content:

 # HF Inference Client
 HF_TOKEN = os.getenv('HF_TOKEN')
 def get_inference_client(model_id):
+    """Return an InferenceClient with provider based on model_id."""
+    provider = "groq" if model_id == "moonshotai/Kimi-K2-Instruct" else "auto"
+    return InferenceClient(
+        provider=provider,
+        api_key=HF_TOKEN,
+        bill_to="huggingface"
+    )
 # Tavily Search Client
 TAVILY_API_KEY = os.getenv('TAVILY_API_KEY')
         print(f"Failed to initialize Tavily client: {e}")
         tavily_client = None
+async def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[List[Tuple[str, str]]], _current_model: Dict, enable_search: bool = False, language: str = "html", progress=gr.Progress(track_tqdm=True)):
     if query is None:
         query = ''
     if _history is None:
         last_assistant_msg = _history[-1][1] if len(_history) > 0 else ""
         if '<!DOCTYPE html>' in last_assistant_msg or '<html' in last_assistant_msg:
             has_existing_html = True
+    progress(0, desc="Initializing...")
     # Choose system prompt based on context
     if has_existing_html:
     # Extract file text and append to query if file is present
     file_text = ""
+    progress(0.1, desc="Processing file...")
     if file:
         file_text = extract_text_from_file(file)
         if file_text:
             file_text = file_text[:5000]  # Limit to 5000 chars for prompt size
             query = f"{query}\n\n[Reference file content below]\n{file_text}"
+    progress(0.2, desc="Extracting website content...")
     # Extract website content and append to query if website URL is present
     website_text = ""
     if website_url and website_url.strip():
 This will help me create a better design for you."""
             query = f"{query}\n\n[Error extracting website: {website_text}]{fallback_guidance}"
+    progress(0.4, desc="Performing web search...")
     # Enhance query with search if enabled
     enhanced_query = enhance_query_with_search(query, enable_search)
         messages.append(create_multimodal_message(enhanced_query, image))
     else:
         messages.append({'role': 'user', 'content': enhanced_query})
+    progress(0.5, desc="Generating code with AI model...")
     try:
         completion = client.chat.completions.create(
             model=_current_model["id"], # Corrected this line
             stream=True,
             max_tokens=5000
         )
+        progress(0.6, desc="Streaming response...")
         content = ""
         for chunk in completion:
             if chunk.choices[0].delta.content: