reorganize

agent/agent.py → agent.py

@@ -132,8 +132,8 @@ def call_llm(messages: List[Dict[str, Any]], temperature: float = 0.7, model: st
 
 def generate_initial_vibe(state: AgentState) -> AgentState:
     """Node: Generate initial vibe description from uploaded images using VLM"""
-    from .prompts import VIBE_EXTRACTION
-    from .utils import parse_json_response, extract_vibe_components
+    from prompts import VIBE_EXTRACTION
+    from utils import parse_json_response, extract_vibe_components
 
     client = create_openai_client()
 
@@ -223,8 +223,8 @@ def generate_initial_vibe(state: AgentState) -> AgentState:
 
 def refine_vibe(state: AgentState) -> AgentState:
     """Node: Refine vibe based on user feedback - only refines feels_like portion"""
-    from .prompts import VIBE_REFINEMENT
-    from .utils import strip_thinking_tags
+    from prompts import VIBE_REFINEMENT
+    from utils import strip_thinking_tags
 
     print("[DEBUG AGENT] refine_vibe node started")
     
@@ -278,7 +278,7 @@ def refine_vibe(state: AgentState) -> AgentState:
 
 def check_vibe_satisfaction(state: AgentState) -> Literal["refine", "retrieve"]:
     """Conditional edge: Check if user is satisfied with vibe description"""
-    from .prompts import VIBE_SATISFACTION_CHECKER
+    from prompts import VIBE_SATISFACTION_CHECKER
 
     # Get the last user message
     user_messages = [m for m in state["messages"] if m.get("role") == "user"]
@@ -567,7 +567,7 @@ def fetch_book_metadata(state: AgentState) -> AgentState:
 
 def _generate_narrowing_question(state: AgentState, question_num: int) -> tuple:
     """Helper: Generate a narrowing question"""
-    from .prompts import NARROWING_QUESTION_GENERATOR
+    from prompts import NARROWING_QUESTION_GENERATOR
     
     books_summary_parts = []
     for i, b in enumerate(state["books_with_metadata"], 1):
@@ -669,7 +669,7 @@ def finalize_books(state: AgentState) -> AgentState:
     """Node: Use reasoning to select final 3 books based on vibe and preferences"""
     print(f"[DEBUG AGENT] finalize_books node started")
     print(f"[DEBUG AGENT] books_with_metadata count: {len(state.get('books_with_metadata', []))}")
-    from .prompts import get_book_finalizer_prompt
+    from prompts import get_book_finalizer_prompt
 
     # Build detailed book summary with full descriptions - no truncation
     books_summary_parts = []
@@ -693,7 +693,7 @@ def finalize_books(state: AgentState) -> AgentState:
 
     # Use reasoning model for book selection - this is a complex decision
     # Increase max_tokens since we're sending full book descriptions
-    selection_response, reasoning = call_llm(messages, temperature=0.3, model=REASONING_MODEL, include_reasoning=True, max_tokens=4000)
+    selection_response, reasoning = call_llm(messages, temperature=0.3, model=REASONING_MODEL, include_reasoning=True, max_tokens=5000)
     
     # Log reasoning even if empty
     state["reasoning"].append(f"🧠 REASONING (Book Selection):\n{reasoning or 'No reasoning provided'}")
@@ -755,7 +755,7 @@ def generate_soundtrack(state: AgentState) -> AgentState:
         print(f"[DEBUG AGENT] vibe_context built: {list(vibe_context.keys())}")
 
         # Use LLM to generate music prompt from vibe context
-        from .prompts import MUSIC_PROMPT_GENERATION
+        from prompts import MUSIC_PROMPT_GENERATION
         
         messages = [
             {"role": "system", "content": MUSIC_PROMPT_GENERATION},

agent/__init__.py

@@ -1 +0,0 @@
-"""Agent package for Vibe Reader"""

app.py

@@ -11,7 +11,7 @@ import logging
 warnings.filterwarnings("ignore", message=".*Invalid file descriptor.*")
 logging.getLogger("asyncio").setLevel(logging.CRITICAL)
 
-from agent.agent import run_agent
+from agent import run_agent
 
 
 
@@ -306,4 +306,4 @@ with gr.Blocks() as demo:
 
 if __name__ == "__main__":
     # Note: css_paths removed as custom.css location may vary
-    demo.queue().launch(theme=gr.themes.Monochrome(), share=True, ssr_mode=False)
+    demo.queue().launch(theme=gr.themes.Monochrome(), css_paths='assets/custom.css'), share=True, ssr_mode=False)