testing model initialization

app.py

@@ -81,72 +81,6 @@ USE_LOCAL_MODELS = os.getenv('USE_LOCAL_MODELS', 'false').lower() == 'true'
 if not HF_TOKEN:
         print("❌ HuggingFace token not found. Please check your .env file.") 
 
-try:
-    # Login to HuggingFace
-    login(HF_TOKEN, add_to_git_credential=False)
-
-    # Initialize NER model
-    print("Initialize NER")
-    ner_model = GLiNER.from_pretrained("knowledgator/modern-gliner-bi-large-v1.0")
-    print(f"Initialized NER")
-
-    
-    llm_engine = InferenceClientModel(
-            api_key=HF_TOKEN,
-            model_id="Qwen/Qwen3-Coder-480B-A35B-Instruct" ,
-            timeout=3000,
-            provider="fireworks-ai",
-            temperature=0.25
-        )
-    
-    
-    # Initialize agent
-    agent = CodeAgent(
-        model=llm_engine,
-        tools=[],
-        add_base_tools=False,
-        name="data_agent",
-        description="Runs data analysis for you.",
-        max_steps=1,
-    )
-
-    # Initialize agent
-    writer_agent = CodeAgent(
-        model=llm_engine,
-        tools=[],
-        add_base_tools=False,
-        name="writer_agent",
-        description="Write an engaging and creative LinkedIn post.",
-        max_steps=5,
-    )
-    
-    writer_engine = InferenceClientModel(
-            api_key=HF_TOKEN,
-            model_id="Qwen/Qwen3-Coder-480B-A35B-Instruct" ,
-            timeout=3000,
-            provider="fireworks-ai",
-            temperature=0.4
-        )
-    
-    
-    # Initialize agent
-    editor_agent = CodeAgent(
-        model=writer_engine,
-        tools=[],
-        add_base_tools=False,
-        name="editor_agent",
-        description="Edits LinkedIn post.",
-        max_steps=5,
-    )
-
-    # Add system prompt
-    #system_prompt = f"You are a strategic digital marketing manager focused on improving my social footprint. My interests are {interests}. You will receive a social media post. Please let me know which one I should react on."
-    #agent.prompt_templates["system_prompt"] += system_prompt
-    
-    print("… Models initialized successfully!") 
-    
-except Exception as e:
-    print( f"⌠Error initializing models: {str(e)}")
 
 def check_environment():
     """Check if required environment variables are set"""
@@ -335,7 +269,73 @@ def process_single_article(post, interests):
     """Process a single news article and generate LinkedIn post"""
     global agent, writer_agent, ner_model, editor_agent
     
-   
+    try:
+        # Login to HuggingFace
+        login(HF_TOKEN, add_to_git_credential=False)
+
+        # Initialize NER model
+        print("Initialize NER")
+        ner_model = GLiNER.from_pretrained("knowledgator/modern-gliner-bi-large-v1.0")
+        print(f"Initialized NER")
+
+        
+        llm_engine = InferenceClientModel(
+                api_key=HF_TOKEN,
+                model_id="Qwen/Qwen3-Coder-480B-A35B-Instruct" ,
+                timeout=3000,
+                provider="fireworks-ai",
+                temperature=0.25
+            )
+        
+        
+        # Initialize agent
+        agent = CodeAgent(
+            model=llm_engine,
+            tools=[],
+            add_base_tools=False,
+            name="data_agent",
+            description="Runs data analysis for you.",
+            max_steps=1,
+        )
+
+        # Initialize agent
+        writer_agent = CodeAgent(
+            model=llm_engine,
+            tools=[],
+            add_base_tools=False,
+            name="writer_agent",
+            description="Write an engaging and creative LinkedIn post.",
+            max_steps=5,
+        )
+        
+        writer_engine = InferenceClientModel(
+                api_key=HF_TOKEN,
+                model_id="Qwen/Qwen3-Coder-480B-A35B-Instruct" ,
+                timeout=3000,
+                provider="fireworks-ai",
+                temperature=0.4
+            )
+        
+        
+        # Initialize agent
+        editor_agent = CodeAgent(
+            model=writer_engine,
+            tools=[],
+            add_base_tools=False,
+            name="editor_agent",
+            description="Edits LinkedIn post.",
+            max_steps=5,
+        )
+
+        # Add system prompt
+        #system_prompt = f"You are a strategic digital marketing manager focused on improving my social footprint. My interests are {interests}. You will receive a social media post. Please let me know which one I should react on."
+        #agent.prompt_templates["system_prompt"] += system_prompt
+        
+        print("… Models initialized successfully!") 
+        
+    except Exception as e:
+        print( f"! Error initializing models: {str(e)}")
+
 
     if agent is None or ner_model is None or writer_agent is None or editor_agent is None:
         return {"error": f"Models agent {agent}, ner_model {type(ner_model)} write_agent {writer_agent}, editor_agent {editor_agent} not initialized. Please initialize models first."}