fall to back to read from chroma/pgvector when not in cache (#489)

# What does this PR do?

The chroma provider maintains a cache but does not sync up with chroma
on a cold start. this change adds a fallback to read from chroma on a
cache miss.


## Test Plan
```bash
#start stack
llama stack run /Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml
# Add documents
PYTHONPATH=. python -m examples.agents.rag_with_memory_bank localhost 5000

No available shields. Disable safety.
Using model: Llama3.1-8B-Instruct
Created session_id=b951b14f-a9d2-43a3-8b80-d80114d58322 for Agent(0687a251-6906-4081-8d4c-f52e19db9dd7)
memory_retrieval> Retrieved context from banks: ['test_bank'].
====
Here are the retrieved documents for relevant context:
=== START-RETRIEVED-CONTEXT ===
 id:num-1; content:_
the template from Llama2 to better support multiturn conversations. The same text
in the Lla...
>
inference> Based on the retrieved documentation, the top 5 topics that were explained are:
...............

# Kill stack
# Bootup stack
llama stack run /Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml
# Run a RAG app with just the agent flow. it discovers the previously added documents
No available shields. Disable safety.
Using model: Llama3.1-8B-Instruct
Created session_id=7a30c1a7-c87e-4787-936c-d0306589fe5d for Agent(b30420f3-c928-498a-887b-d084f0f3806c)
memory_retrieval> Retrieved context from banks: ['test_bank'].
====
Here are the retrieved documents for relevant context:
=== START-RETRIEVED-CONTEXT ===
 id:num-1; content:_
the template from Llama2 to better support multiturn conversations. The same text
in the Lla...
>
inference> Based on the provided documentation, the top 5 topics that were explained are:
.....
```

llama_stack/providers/remote/memory/chroma/chroma.py

@@ -147,9 +147,7 @@ class ChromaMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
         documents: List[MemoryBankDocument],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = self.cache.get(bank_id, None)
-        if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+        index = await self._get_and_cache_bank_index(bank_id)
 
         await index.insert_documents(documents)
 
@@ -159,8 +157,20 @@ class ChromaMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
         query: InterleavedTextMedia,
         params: Optional[Dict[str, Any]] = None,
     ) -> QueryDocumentsResponse:
-        index = self.cache.get(bank_id, None)
-        if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+        index = await self._get_and_cache_bank_index(bank_id)
 
         return await index.query_documents(query, params)
+
+    async def _get_and_cache_bank_index(self, bank_id: str) -> BankWithIndex:
+        if bank_id in self.cache:
+            return self.cache[bank_id]
+
+        bank = await self.memory_bank_store.get_memory_bank(bank_id)
+        if not bank:
+            raise ValueError(f"Bank {bank_id} not found in Llama Stack")
+        collection = await self.client.get_collection(bank_id)
+        if not collection:
+            raise ValueError(f"Bank {bank_id} not found in Chroma")
+        index = BankWithIndex(bank=bank, index=ChromaIndex(self.client, collection))
+        self.cache[bank_id] = index
+        return index

llama_stack/providers/remote/memory/pgvector/pgvector.py

@@ -201,10 +201,7 @@ class PGVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
         documents: List[MemoryBankDocument],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = self.cache.get(bank_id, None)
-        if not index:
-            raise ValueError(f"Bank {bank_id} not found")
-
+        index = await self._get_and_cache_bank_index(bank_id)
         await index.insert_documents(documents)
 
     async def query_documents(
@@ -213,8 +210,17 @@ class PGVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
         query: InterleavedTextMedia,
         params: Optional[Dict[str, Any]] = None,
     ) -> QueryDocumentsResponse:
-        index = self.cache.get(bank_id, None)
-        if not index:
-            raise ValueError(f"Bank {bank_id} not found")
-
+        index = await self._get_and_cache_bank_index(bank_id)
         return await index.query_documents(query, params)
+
+    async def _get_and_cache_bank_index(self, bank_id: str) -> BankWithIndex:
+        if bank_id in self.cache:
+            return self.cache[bank_id]
+
+        bank = await self.memory_bank_store.get_memory_bank(bank_id)
+        index = BankWithIndex(
+            bank=bank,
+            index=PGVectorIndex(bank, ALL_MINILM_L6_V2_DIMENSION, self.cursor),
+        )
+        self.cache[bank_id] = index
+        return index