Add embeddings cache (#318)

Initial design and refactor here. 
- Includes some clean up for the internals of the OG `SemanticCache`.
- Refactors the core of the cache classes to use `BaseCache` for both
`EmbeddingsCache` and `SemanticCache`.
- Updates documentation, working tests, and user guides.

NOTE: Will hold off on integrating with our vectorizers for a separate
PR. This one is already long.

Author: tylerhutcherson

README.md

@@ -238,7 +238,7 @@ We're excited to announce the support for **RedisVL Extensions**. These modules
 Increase application throughput and reduce the cost of using LLM models in production by leveraging previously generated knowledge with the [`SemanticCache`](https://docs.redisvl.com/en/stable/api/cache.html#semanticcache).
 
 ```python
-from redisvl.extensions.llmcache import SemanticCache
+from redisvl.extensions.cache.llm import SemanticCache
 
 # init cache with TTL and semantic distance threshold
 llmcache = SemanticCache(

docs/api/cache.rst

@@ -7,9 +7,26 @@ SemanticCache
 
 .. _semantic_cache_api:
 
-.. currentmodule:: redisvl.extensions.llmcache
+.. currentmodule:: redisvl.extensions.cache.llm
 
 .. autoclass:: SemanticCache
    :show-inheritance:
    :members:
    :inherited-members:
+
+
+****************
+Embeddings Cache
+****************
+
+EmbeddingsCache
+===============
+
+.. _embeddings_cache_api:
+
+.. currentmodule:: redisvl.extensions.cache.embeddings
+
+.. autoclass:: EmbeddingsCache
+   :show-inheritance:
+   :members:
+   :inherited-members:

docs/user_guide/03_llmcache.ipynb

@@ -88,7 +88,7 @@
     }
    ],
    "source": [
-    "from redisvl.extensions.llmcache import SemanticCache\n",
+    "from redisvl.extensions.cache.llm import SemanticCache\n",
     "\n",
     "llmcache = SemanticCache(\n",
     "    name=\"llmcache\",                     # underlying search index name\n",

docs/user_guide/04_vectorizers.ipynb

@@ -609,7 +609,7 @@
          "metadata": {},
          "outputs": [],
          "source": [
-            "from redisvl.extensions.llmcache import SemanticCache\n",
+            "from redisvl.extensions.cache.llm import SemanticCache\n",
             "\n",
             "cache = SemanticCache(name=\"custom_cache\", vectorizer=custom_vectorizer)\n",
             "\n",

docs/user_guide/09_threshold_optimization.ipynb

@@ -24,7 +24,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from redisvl.extensions.llmcache import SemanticCache\n",
+    "from redisvl.extensions.cache.llm import SemanticCache\n",
     "\n",
     "sem_cache = SemanticCache(\n",
     "    name=\"sem_cache\",                    # underlying search index name\n",