Add cache directory to Dockerfile and update embeddings model to use cache folder

.gitignore

@@ -182,3 +182,4 @@ app/models/chroma/data/chroma.sqlite3
 models/chroma/data/*.bin
 models/chroma/_data/chroma.sqlite3
 models/chroma/data/chroma.sqlite3
+cache

Dockerfile

@@ -7,6 +7,9 @@ COPY . .
 # Set the working directory to /app
 WORKDIR /app
 
+# Create a cache directory and set permissions
+RUN mkdir -p /app/cache && chmod -R 777 /app/cache
+
 # Install requirements.txt
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 

app/models/db/__init__.py

@@ -2,17 +2,13 @@
 import faiss
 from langchain_community.vectorstores import FAISS
 from langchain_community.docstore.in_memory import InMemoryDocstore
-# from langchain_chroma import Chroma
 from models.llm import EmbeddingsModel
 
 embeddings = EmbeddingsModel("all-MiniLM-L6-v2")
 
-index = faiss.IndexFlatL2(len(embeddings.embed_query("hello world")))
-print(index)
-
 vectorstore = FAISS(
     embedding_function=embeddings,
-    index=index,
+    index=faiss.IndexFlatL2(len(embeddings.embed_query("hello world"))),
     docstore=InMemoryDocstore(),
     index_to_docstore_id={}
 )

app/models/llm/__init__.py

@@ -115,7 +115,7 @@ class EmbeddingsModel(Embeddings):
         Args:
             model_name (str): The name of the model to be used for sentence transformation.
         """
-        self.model = SentenceTransformer(model_name)
+        self.model = SentenceTransformer(model_name, cache_folder="/app/cache")
 
     def embed_documents(self, documents: List[str]) -> List[List[float]]:
         """