Add LLM backend support and improve debugging observability

- Add LLM_BACKEND to environment configuration
- Implement detailed debug logging for LLM request/response cycles
- Add missing llama-index dependencies for embeddings and chroma
- Update prompt constraints to prevent lore redundancy
- Enable CUDA for transcription and set logging to DEBUG level
- Add entry point for running the orchestrator directly
- Cleanup unused comment in TUI context updates

src/llm/processor.py

@@ -45,6 +45,7 @@ class LLMProcessor:
             final_base_url = base_url or os.environ.get("OPENAI_BASE_URL")
             final_api_key = api_key or os.environ.get("OPENAI_API_KEY")
 
+        logger.info(f"Using LLM backend: {backend}")
         try:
             self.client = OpenAI(
                 api_key=final_api_key,
@@ -96,6 +97,14 @@ class LLMProcessor:
 
         messages.append({"role": "user", "content": user_prompt})
 
+        # Debugging: Dump inputs
+        logger.debug("--- LLM CALL START ---")
+        logger.debug(f"Model: {self.model}")
+        logger.debug(f"Messages: {messages}")
+        if response_format:
+            logger.debug(f"Response Format: {response_format}")
+        logger.debug("--- LLM CALL END ---")
+
         try:
             response = self.client.chat.completions.create(
                 model=self.model,
@@ -105,6 +114,11 @@ class LLMProcessor:
             )
             content = response.choices[0].message.content
 
+            # Debugging: Dump outputs
+            logger.debug("--- LLM RESPONSE START ---")
+            logger.debug(f"Content: {content}")
+            logger.debug("--- LLM RESPONSE END ---")
+
             return self._strip_markdown_code_blocks(content)
         except Exception as e:
             logger.error(f"LLM Error: {e}")