diff --git a/server/memory_manager.py b/server/memory_manager.py index e3f7315..d1cff47 100644 --- a/server/memory_manager.py +++ b/server/memory_manager.py @@ -19,7 +19,6 @@ from .config import settings from .logger import logger # This block is for static analysis only (for Pylance). -# It is not executed at runtime, so it won't cause an ImportError. if TYPE_CHECKING: from chonkie import SemanticChunker from chonkie.embeddings import SentenceTransformerEmbeddings @@ -70,7 +69,11 @@ class MemoryManager: raise ImportError("Chonkie is configured but not installed correctly. Please run 'uv pip install \"chonkie[st]\"'.") logger.info("Initializing Chonkie with SemanticChunker...") - embedding_handler = SentenceTransformerEmbeddings(model_name=settings.memory.embedding_model, device="cpu") + # FIXED: Changed keyword from 'model_name' to 'model' + embedding_handler = SentenceTransformerEmbeddings( + model=settings.memory.embedding_model, + device="cpu" + ) self.chunker = SemanticChunker(embedding_model=embedding_handler) self.embedder = embedding_handler logger.info("Using 'chonkie' for text chunking.") @@ -107,9 +110,8 @@ class MemoryManager: if not text or not text.strip(): return try: if settings.memory.chunker == "chonkie" and self.chunker: - # The runtime code knows what self.chunker(text) returns chonkie_chunks = self.chunker(text) - chunks = [c.text for c in chonkie_chunks if c.text.strip()] # type: ignore (This might break, we're see) + chunks = [c.text for c in chonkie_chunks if c.text.strip()] # type: ignore (This *might* break things) else: chunks = self._simple_chunker(text) diff --git a/settings.yml b/settings.yml index e4052a4..65dbcf4 100644 --- a/settings.yml +++ b/settings.yml @@ -20,7 +20,7 @@ llm: # The model identifier for the chosen backend. # Example for OpenRouter: "google/gemma-2-9b-it" # Example for LM Studio: "gemma-2-9b-it-gguf" (or whatever you have loaded) - story_model: "google/gemma-3n-e4b" + story_model: "gemma-3-12b-it-GGUF" # The format for sending player actions to the AI. # "json": (Recommended) More reliable and less ambiguous for modern models. @@ -62,7 +62,7 @@ audio: memory: # The chunking strategy to use for breaking down text for the RAG system. # Options: "simple" (original method), "chonkie" (advanced library). - chunker: "simple" + chunker: "chonkie" # The SentenceTransformer model used to create embeddings for the AI's embedding_model: "google/embeddinggemma-300m" diff --git a/web/favicon.ico b/web/favicon.ico new file mode 100644 index 0000000..ed4702d Binary files /dev/null and b/web/favicon.ico differ