From 94aba6ea1a69e47dabf71303ccccc8aa2437de07 Mon Sep 17 00:00:00 2001
From: y9938 <nbla6302@gmail.com>
Date: Tue, 30 Dec 2025 07:02:52 +0300
Subject: [PATCH] fix: colors

---
 .env.example |  1 +
 main.py      | 17 +++++++++--------
 2 files changed, 10 insertions(+), 8 deletions(-)

diff --git a/.env.example b/.env.example
index 1159ced..03ebeda 100644
--- a/.env.example
+++ b/.env.example
@@ -3,6 +3,7 @@ EMBEDDING_MODEL=mxbai-embed-large:latest
 LLM_MODEL=qwen2.5:7b-instruct-q8_0
 OLLAMA_BASE_URL=http://localhost:11434
 
+ANSWER_COLOR=purple
 SYSTEM_PROMPT="You are a precise technical assistant. Cite sources using [filename]. Be concise."
 
 USER_PROMPT_TEMPLATE="Previous Conversation:
diff --git a/main.py b/main.py
index cb67230..7d38456 100644
--- a/main.py
+++ b/main.py
@@ -36,6 +36,7 @@ load_dotenv()
 style = Style.from_dict({"prompt": "bold #6a0dad"})
 
 OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")
+ANSWER_COLOR = os.getenv("ANSWER_COLOR", "blue")
 
 SYSTEM_PROMPT_SEARCH = os.getenv("SYSTEM_PROMPT", "You are a precise technical assistant. Cite sources using [filename]. Be concise.")
 SYSTEM_PROMPT_ANALYSIS = (
@@ -49,7 +50,7 @@ SYSTEM_PROMPT_ANALYSIS = (
 USER_PROMPT_TEMPLATE = os.getenv("USER_PROMPT_TEMPLATE", 
     "Previous Conversation:\n{history}\n\nContext from Docs:\n{context}\n\nCurrent Question: {question}")
 
-MD_DIRECTORY = os.getenv("MD_FOLDER", "./my_docs")
+MD_DIRECTORY = os.getenv("MD_FOLDER", "./notes")
 EMBEDDING_MODEL = os.getenv("EMBEDDING_MODEL", "nomic-embed-text")
 LLM_MODEL = os.getenv("LLM_MODEL", "llama3")
 
@@ -91,7 +92,7 @@ def classify_intent(query: str) -> str:
         r"what have i learned", r"summary of (my )?notes", 
         r"my progress", r"learning path", r"knowledge gap",
         r"оцени (мой )?прогресс", r"что я выучил", r"итоги", r"анализ знаний",
-        r"сегодня урок", r"что я изучил"
+        r"сегодня(?:\s+\w+)*\s*урок", r"что я изучил"
     ]
     
     query_lower = query.lower()
@@ -286,7 +287,7 @@ async def main():
     processor = ChunkProcessor(vectorstore)
     cache = load_hash_cache()
 
-    console.print("Checking documents...", style="yellow")
+    # Checking documents
     files = [
         os.path.join(root, file)
         for root, _, files in os.walk(MD_DIRECTORY)
@@ -306,17 +307,17 @@ async def main():
     observer = start_watcher(processor, cache)
     memory = ConversationMemory()
 
-    console.print("💬 Ready! Type 'exit' to quit.", style="bold green")
-
     try:
         while True:
             query = await session.prompt_async("> ", style=style)
             query = query.strip()
             if query.lower() in {"exit", "quit", "q"}:
-                console.print("Goodbye!", style="yellow")
+                console.print("\nGoodbye!", style="yellow")
                 break
             if not query: continue
 
+            console.print()
+
             mode = classify_intent(query)
             history_str = memory.get_history()
 
@@ -366,7 +367,7 @@ async def main():
                 "question": query,
                 "history": history_str
             }):
-                print(chunk, end="")
+                console.print(chunk, end="", style=ANSWER_COLOR)
                 response += chunk
             console.print("\n")
 
@@ -385,5 +386,5 @@ if __name__ == "__main__":
         loop = asyncio.get_event_loop()
         loop.run_until_complete(main())
     except KeyboardInterrupt:
-        console.print("Goodbye!", style="yellow")
+        console.print("\nGoodbye!", style="yellow")
         sys.exit(0)