migrate router for memory wip

llama_stack/distribution/routers/__init__.py

@@ -0,0 +1,5 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.

llama_stack/distribution/routers/memory/__init__.py

@@ -0,0 +1,17 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, List, Tuple
+
+from llama_stack.distribution.datatypes import Api
+
+
+async def get_router_impl(inner_impls: List[Tuple[str, Any]], deps: List[Api]):
+    from .memory import MemoryRouterImpl
+
+    impl = MemoryRouterImpl(inner_impls, deps)
+    await impl.initialize()
+    return impl

llama_stack/distribution/routers/memory/memory.py

@@ -0,0 +1,91 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, Dict, List, Tuple
+
+from llama_stack.distribution.datatypes import Api
+from llama_stack.apis.memory import *  # noqa: F403
+
+
+class MemoryRouterImpl(Memory):
+    """Routes to an provider based on the memory bank type"""
+
+    def __init__(
+        self,
+        inner_impls: List[Tuple[str, Any]],
+        deps: List[Api],
+    ) -> None:
+        self.deps = deps
+
+        bank_types = [v.value for v in MemoryBankType]
+
+        self.providers = {}
+        for routing_key, provider_impl in inner_impls:
+            if routing_key not in bank_types:
+                raise ValueError(
+                    f"Unknown routing key `{routing_key}` for memory bank type"
+                )
+            self.providers[routing_key] = provider_impl
+
+        self.bank_id_to_type = {}
+
+    async def initialize(self) -> None:
+        pass
+
+    async def shutdown(self) -> None:
+        for p in self.providers.values():
+            await p.shutdown()
+
+    def get_provider(self, bank_type):
+        if bank_type not in self.providers:
+            raise ValueError(f"Memory bank type {bank_type} not supported")
+
+        return self.providers[bank_type]
+
+    async def create_memory_bank(
+        self,
+        name: str,
+        config: MemoryBankConfig,
+        url: Optional[URL] = None,
+    ) -> MemoryBank:
+        provider = self.get_provider(config.type)
+        bank = await provider.create_memory_bank(name, config, url)
+        self.bank_id_to_type[bank.bank_id] = config.type
+        return bank
+
+    async def get_memory_bank(self, bank_id: str) -> Optional[MemoryBank]:
+        bank_type = self.bank_id_to_type.get(bank_id)
+        if not bank_type:
+            raise ValueError(f"Could not find bank type for {bank_id}")
+
+        provider = self.get_provider(bank_type)
+        return await provider.get_memory_bank(bank_id)
+
+    async def insert_documents(
+        self,
+        bank_id: str,
+        documents: List[MemoryBankDocument],
+        ttl_seconds: Optional[int] = None,
+    ) -> None:
+        bank_type = self.bank_id_to_type.get(bank_id)
+        if not bank_type:
+            raise ValueError(f"Could not find bank type for {bank_id}")
+
+        provider = self.get_provider(bank_type)
+        return await provider.insert_documents(bank_id, documents, ttl_seconds)
+
+    async def query_documents(
+        self,
+        bank_id: str,
+        query: InterleavedTextMedia,
+        params: Optional[Dict[str, Any]] = None,
+    ) -> QueryDocumentsResponse:
+        bank_type = self.bank_id_to_type.get(bank_id)
+        if not bank_type:
+            raise ValueError(f"Could not find bank type for {bank_id}")
+
+        provider = self.get_provider(bank_type)
+        return await provider.query_documents(bank_id, query, params)

llama_stack/distribution/server/server.py

@@ -280,7 +280,56 @@ async def resolve_impls_with_routing(
     stack_run_config: StackRunConfig,
 ) -> Dict[Api, Any]:
 
-    raise NotImplementedError("This is not implemented yet")
+    all_providers = api_providers()
+    specs = {}
+
+    for api_str in stack_run_config.apis_to_serve:
+        api = Api(api_str)
+        providers = all_providers[api]
+
+        # check for regular providers without routing
+        if api_str in stack_run_config.provider_map:
+            provider_map_entry = stack_run_config.provider_map[api_str]
+            if provider_map_entry.provider_id not in providers:
+                raise ValueError(
+                    f"Unknown provider `{provider_id}` is not available for API `{api}`"
+                )
+            specs[api] = providers[provider_map_entry.provider_id]
+
+        # check for routing table, we need to pass routing table to the router implementation
+        if api_str in stack_run_config.provider_routing_table:
+            router_entry = stack_run_config.provider_routing_table[api_str]
+            inner_specs = []
+            for rt_entry in router_entry:
+                if rt_entry.provider_id not in providers:
+                    raise ValueError(
+                        f"Unknown provider `{rt_entry.provider_id}` is not available for API `{api}`"
+                    )
+                inner_specs.append(providers[rt_entry.provider_id])
+
+            specs[api] = RouterProviderSpec(
+                api=api,
+                module=f"llama_stack.distribution.routers.{api.value.lower()}",
+                api_dependencies=[],
+                inner_specs=inner_specs,
+            )
+
+    sorted_specs = topological_sort(specs.values())
+
+    impls = {}
+    for spec in sorted_specs:
+        api = spec.api
+        deps = {api: impls[api] for api in spec.api_dependencies}
+        if api.value in stack_run_config.provider_map:
+            provider_config = stack_run_config.provider_map[api.value]
+        elif api.value in stack_run_config.provider_routing_table:
+            provider_config = stack_run_config.provider_routing_table[api.value]
+        else:
+            raise ValueError(f"Cannot find provider_config for Api {api.value}")
+        impl = await instantiate_provider(spec, deps, provider_config)
+        impls[api] = impl
+
+    return impls, specs
 
 
 async def resolve_impls(
@@ -345,6 +394,7 @@ def main(yaml_config: str, port: int = 5000, disable_ipv6: bool = False):
     if config.provider_routing_table is not None:
         impls, specs = asyncio.run(resolve_impls_with_routing(config))
     else:
+        # keeping this for backwards compatibility,could
         impls, specs = asyncio.run(resolve_impls(config.provider_map))
 
     if Api.telemetry in impls:

llama_stack/distribution/utils/dynamic.py

@@ -33,6 +33,7 @@ async def instantiate_provider(
 
         assert isinstance(provider_config, GenericProviderConfig)
         config_type = instantiate_class_type(provider_spec.config_class)
+        print("!!!", provider_config)
         config = config_type(**provider_config.config)
         args = [config, deps]
     elif isinstance(provider_spec, RouterProviderSpec):

llama_stack/examples/router-table-run.yaml

@@ -3,26 +3,27 @@ image_name: local
 docker_image: null
 conda_env: local
 apis_to_serve:
-- inference
+# - inference
 - memory
+- telemetry
 provider_map:
-  # use builtin-router as dummy field
-  memory: builtin-router
-  inference: builtin-router
+  telemetry:
+    provider_id: meta-reference
+    config: {}
 provider_routing_table:
-  inference:
-    - routing_key: Meta-Llama3.1-8B-Instruct
-      provider_id: meta-reference
-      config:
-        model: Meta-Llama3.1-8B-Instruct
-        quantization: null
-        torch_seed: null
-        max_seq_len: 4096
-        max_batch_size: 1
-    - routing_key: Meta-Llama3.1-8B
-      provider_id: remote::ollama
-      config:
-        url: http:ollama-url-1.com
+  # inference:
+  #   - routing_key: Meta-Llama3.1-8B-Instruct
+  #     provider_id: meta-reference
+  #     config:
+  #       model: Meta-Llama3.1-8B-Instruct
+  #       quantization: null
+  #       torch_seed: null
+  #       max_seq_len: 4096
+  #       max_batch_size: 1
+  #   - routing_key: Meta-Llama3.1-8B
+  #     provider_id: remote::ollama
+  #     config:
+  #       url: http:ollama-url-1.com
   memory:
     - routing_key: keyvalue
       provider_id: remote::pgvector
@@ -31,6 +32,7 @@ provider_routing_table:
         port: 5432
         db: vectordb
         user: vectoruser
+        password: xxxx
     - routing_key: vector
       provider_id: meta-reference
       config: {}

llama_stack/providers/adapters/memory/pgvector/pgvector.py

@@ -128,35 +128,36 @@ class PGVectorMemoryAdapter(Memory):
         self.cache = {}
 
     async def initialize(self) -> None:
-        try:
-            self.conn = psycopg2.connect(
-                host=self.config.host,
-                port=self.config.port,
-                database=self.config.db,
-                user=self.config.user,
-                password=self.config.password,
-            )
-            self.cursor = self.conn.cursor()
+        print("Init PGVector!")
+        # try:
+        #     self.conn = psycopg2.connect(
+        #         host=self.config.host,
+        #         port=self.config.port,
+        #         database=self.config.db,
+        #         user=self.config.user,
+        #         password=self.config.password,
+        #     )
+        #     self.cursor = self.conn.cursor()
 
-            version = check_extension_version(self.cursor)
-            if version:
-                print(f"Vector extension version: {version}")
-            else:
-                raise RuntimeError("Vector extension is not installed.")
+        #     version = check_extension_version(self.cursor)
+        #     if version:
+        #         print(f"Vector extension version: {version}")
+        #     else:
+        #         raise RuntimeError("Vector extension is not installed.")
 
-            self.cursor.execute(
-                """
-                CREATE TABLE IF NOT EXISTS metadata_store (
-                    key TEXT PRIMARY KEY,
-                    data JSONB
-                )
-            """
-            )
-        except Exception as e:
-            import traceback
+        #     self.cursor.execute(
+        #         """
+        #         CREATE TABLE IF NOT EXISTS metadata_store (
+        #             key TEXT PRIMARY KEY,
+        #             data JSONB
+        #         )
+        #     """
+        #     )
+        # except Exception as e:
+        #     import traceback
 
-            traceback.print_exc()
-            raise RuntimeError("Could not connect to PGVector database server") from e
+        #     traceback.print_exc()
+        #     raise RuntimeError("Could not connect to PGVector database server") from e
 
     async def shutdown(self) -> None:
         pass

llama_stack/providers/impls/meta_reference/memory/faiss.py

@@ -68,7 +68,8 @@ class FaissMemoryImpl(Memory):
         self.config = config
         self.cache = {}
 
-    async def initialize(self) -> None: ...
+    async def initialize(self) -> None:
+        print("INIT meta-reference")
 
     async def shutdown(self) -> None: ...