bunch more work to make adapters work

llama_toolchain/cli/api/api.py

@@ -9,6 +9,7 @@ import argparse
 from llama_toolchain.cli.subcommand import Subcommand
 
 from .build import ApiBuild
+from .configure import ApiConfigure
 
 
 class ApiParser(Subcommand):
@@ -24,3 +25,4 @@ class ApiParser(Subcommand):
 
         # Add sub-commands
         ApiBuild.create(subparsers)
+        ApiConfigure.create(subparsers)

llama_toolchain/cli/api/build.py

@@ -6,22 +6,92 @@
 
 import argparse
 import os
+import random
+import string
+import uuid
+from pydantic import BaseModel
+from datetime import datetime
+from enum import Enum
+from typing import Dict, List, Optional, Tuple
 
 import pkg_resources
 import yaml
 
-from llama_toolchain.cli.subcommand import Subcommand
-from llama_toolchain.common.config_dirs import DISTRIBS_BASE_DIR
-
 from termcolor import cprint
 
+from llama_toolchain.cli.subcommand import Subcommand
+from llama_toolchain.common.config_dirs import BUILDS_BASE_DIR
+from llama_toolchain.distribution.datatypes import *  # noqa: F403
+
+
+def random_string():
+    return "".join(random.choices(string.ascii_letters + string.digits, k=8))
+
+
+class BuildType(Enum):
+    container = "container"
+    conda_env = "conda_env"
+
+
+class Dependencies(BaseModel):
+    pip_packages: List[str]
+    docker_image: Optional[str] = None
+
+
+def get_dependencies(
+    provider: ProviderSpec, dependencies: Dict[str, ProviderSpec]
+) -> Dependencies:
+    def _deps(provider: ProviderSpec) -> Tuple[List[str], Optional[str]]:
+        if isinstance(provider, InlineProviderSpec):
+            return provider.pip_packages, provider.docker_image
+        else:
+            if provider.adapter:
+                return provider.adapter.pip_packages, None
+            return [], None
+
+    pip_packages, docker_image = _deps(provider)
+    for dep in dependencies.values():
+        dep_pip_packages, dep_docker_image = _deps(dep)
+        if docker_image and dep_docker_image:
+            raise ValueError(
+                "You can only have the root provider specify a docker image"
+            )
+
+        pip_packages.extend(dep_pip_packages)
+
+    return Dependencies(docker_image=docker_image, pip_packages=pip_packages)
+
+
+def parse_dependencies(
+    dependencies: str, parser: argparse.ArgumentParser
+) -> Dict[str, ProviderSpec]:
+    from llama_toolchain.distribution.distribution import api_providers
+
+    all_providers = api_providers()
+
+    deps = {}
+    for dep in dependencies.split(","):
+        dep = dep.strip()
+        if not dep:
+            continue
+        api_str, provider = dep.split("=")
+        api = Api(api_str)
+
+        provider = provider.strip()
+        if provider not in all_providers[api]:
+            parser.error(f"Provider `{provider}` is not available for API `{api}`")
+            return
+        deps[api] = all_providers[api][provider]
+
+    return deps
+
 
 class ApiBuild(Subcommand):
 
     def __init__(self, subparsers: argparse._SubParsersAction):
         super().__init__()
         self.parser = subparsers.add_parser(
-            "install",
+            "build",
             prog="llama api build",
             description="Build a Llama stack API provider container",
             formatter_class=argparse.RawTextHelpFormatter,
@@ -36,7 +106,7 @@ class ApiBuild(Subcommand):
         self.parser.add_argument(
             "api",
             choices=allowed_args,
-            help="Stack API (one of: {})".format(", ".join(allowed_args))
+            help="Stack API (one of: {})".format(", ".join(allowed_args)),
         )
 
         self.parser.add_argument(
@@ -45,73 +115,104 @@ class ApiBuild(Subcommand):
             help="The provider to package into the container",
             required=True,
         )
-        self.parser.add_argument(
-            "--container-name",
-            type=str,
-            help="Name of the container (including tag if needed)",
-            required=True,
-        )
         self.parser.add_argument(
             "--dependencies",
             type=str,
             help="Comma separated list of (downstream_api=provider) dependencies needed for the API",
             required=False,
         )
+        self.parser.add_argument(
+            "--name",
+            type=str,
+            help="Name of the build target (image, conda env). Defaults to a random UUID",
+            required=False,
+        )
+        self.parser.add_argument(
+            "--type",
+            type=str,
+            default="container",
+            choices=[v.value for v in BuildType],
+        )
 
     def _run_api_build_command(self, args: argparse.Namespace) -> None:
         from llama_toolchain.common.exec import run_with_pty
-        from llama_toolchain.distribution.datatypes import DistributionConfig
-        from llama_toolchain.distribution.distribution import distribution_dependencies
-        from llama_toolchain.distribution.registry import resolve_distribution_spec
+        from llama_toolchain.distribution.distribution import api_providers
 
-        os.makedirs(DISTRIBS_BASE_DIR, exist_ok=True)
-        script = pkg_resources.resource_filename(
-            "llama_toolchain",
-            "distribution/build_api.sh",
-        )
+        os.makedirs(BUILDS_BASE_DIR, exist_ok=True)
+        all_providers = api_providers()
 
-        dist = resolve_distribution_spec(args.spec)
-        if dist is None:
-            self.parser.error(f"Could not find distribution {args.spec}")
+        api = Api(args.api)
+        assert api in all_providers
+
+        providers = all_providers[api]
+        if args.provider not in providers:
+            self.parser.error(
+                f"Provider `{args.provider}` is not available for API `{api}`"
+            )
             return
 
-        distrib_dir = DISTRIBS_BASE_DIR / args.name
-        os.makedirs(distrib_dir, exist_ok=True)
-
-        deps = distribution_dependencies(dist)
-        if not args.conda_env:
-            print(f"Using {args.name} as the Conda environment for this distribution")
-
-        conda_env = args.conda_env or args.name
-
-        config_file = distrib_dir / "config.yaml"
-        if config_file.exists():
-            c = DistributionConfig(**yaml.safe_load(config_file.read_text()))
-            if c.spec != dist.spec_id:
-                self.parser.error(
-                    f"already installed distribution with `spec={c.spec}` does not match provided spec `{args.spec}`"
-                )
-                return
-            if c.conda_env != conda_env:
-                self.parser.error(
-                    f"already installed distribution has `conda_env={c.conda_env}` different from provided conda env `{conda_env}`"
-                )
-                return
+        name = args.name or random_string()
+        if args.type == BuildType.container.value:
+            package_name = f"image-{args.provider}-{name}"
         else:
-            with open(config_file, "w") as f:
-                c = DistributionConfig(
-                    spec=dist.spec_id,
-                    name=args.name,
-                    conda_env=conda_env,
-                )
-                f.write(yaml.dump(c.dict(), sort_keys=False))
+            package_name = f"env-{args.provider}-{name}"
+        package_name = package_name.replace("::", "-")
 
-        return_code = run_with_pty([script, conda_env, args.name, " ".join(deps)])
+        build_dir = BUILDS_BASE_DIR / args.api
+        os.makedirs(build_dir, exist_ok=True)
 
+        provider_deps = parse_dependencies(args.dependencies or "", self.parser)
+        dependencies = get_dependencies(providers[args.provider], provider_deps)
+
+        package_file = build_dir / f"{package_name}.yaml"
+
+        stub_config = {
+            api.value: {
+                "provider_id": args.provider,
+            },
+            **{k: {"provider_id": v} for k, v in provider_deps.items()},
+        }
+        with open(package_file, "w") as f:
+            c = PackageConfig(
+                built_at=datetime.now(),
+                package_name=package_name,
+                docker_image=(
+                    package_name if args.type == BuildType.container.value else None
+                ),
+                conda_env=(
+                    package_name if args.type == BuildType.conda_env.value else None
+                ),
+                providers=stub_config,
+            )
+            f.write(yaml.dump(c.dict(), sort_keys=False))
+
+        if args.type == BuildType.container.value:
+            script = pkg_resources.resource_filename(
+                "llama_toolchain", "distribution/build_container.sh"
+            )
+            args = [
+                script,
+                args.api,
+                package_name,
+                dependencies.docker_image or "python:3.10-slim",
+                " ".join(dependencies.pip_packages),
+            ]
+        else:
+            script = pkg_resources.resource_filename(
+                "llama_toolchain", "distribution/build_conda_env.sh"
+            )
+            args = [
+                script,
+                args.api,
+                package_name,
+                " ".join(dependencies.pip_packages),
+            ]
+
+        return_code = run_with_pty(args)
         assert return_code == 0, cprint(
-            f"Failed to install distribution {dist.spec_id}", color="red"
+            f"Failed to build target {package_name}", color="red"
         )
         cprint(
-            f"Distribution `{args.name}` (with spec {dist.spec_id}) has been installed successfully!",
+            f"Target `{target_name}` built with configuration at {str(package_file)}",
             color="green",
         )

llama_toolchain/cli/api/configure.py

@@ -0,0 +1,100 @@
+# 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.
+
+import argparse
+import json
+
+from pathlib import Path
+
+import yaml
+
+from llama_toolchain.cli.subcommand import Subcommand
+from llama_toolchain.common.config_dirs import BUILDS_BASE_DIR
+from llama_toolchain.distribution.datatypes import *  # noqa: F403
+from termcolor import cprint
+
+
+class ApiConfigure(Subcommand):
+    """Llama cli for configuring llama toolchain configs"""
+
+    def __init__(self, subparsers: argparse._SubParsersAction):
+        super().__init__()
+        self.parser = subparsers.add_parser(
+            "configure",
+            prog="llama api configure",
+            description="configure a llama stack API provider",
+            formatter_class=argparse.RawTextHelpFormatter,
+        )
+        self._add_arguments()
+        self.parser.set_defaults(func=self._run_api_configure_cmd)
+
+    def _add_arguments(self):
+        from llama_toolchain.distribution.distribution import stack_apis
+
+        allowed_args = [a.name for a in stack_apis()]
+        self.parser.add_argument(
+            "api",
+            choices=allowed_args,
+            help="Stack API (one of: {})".format(", ".join(allowed_args)),
+        )
+        self.parser.add_argument(
+            "--name",
+            type=str,
+            help="Name of the provider build to fully configure",
+            required=True,
+        )
+
+    def _run_api_configure_cmd(self, args: argparse.Namespace) -> None:
+        config_file = BUILDS_BASE_DIR / args.api / f"{args.name}.yaml"
+        if not config_file.exists():
+            self.parser.error(
+                f"Could not find {config_file}. Please run `llama api build` first"
+            )
+            return
+
+        configure_llama_provider(config_file)
+
+
+def configure_llama_provider(config_file: Path) -> None:
+    from llama_toolchain.common.prompt_for_config import prompt_for_config
+    from llama_toolchain.common.serialize import EnumEncoder
+    from llama_toolchain.distribution.distribution import api_providers
+    from llama_toolchain.distribution.dynamic import instantiate_class_type
+
+    with open(config_file, "r") as f:
+        config = PackageConfig(**yaml.safe_load(f))
+
+    all_providers = api_providers()
+
+    provider_configs = {}
+    for api, stub_config in config.providers.items():
+        providers = all_providers[Api(api)]
+        provider_id = stub_config["provider_id"]
+        if provider_id not in providers:
+            raise ValueError(
+                f"Unknown provider `{provider_id}` is not available for API `{api}`"
+            )
+
+        provider_spec = providers[provider_id]
+        cprint(f"Configuring API surface: {api}", "white", attrs=["bold"])
+        config_type = instantiate_class_type(provider_spec.config_class)
+        print(f"Config type: {config_type}")
+        provider_config = prompt_for_config(
+            config_type,
+        )
+        print("")
+
+        provider_configs[api.value] = {
+            "provider_id": provider_id,
+            **provider_config.dict(),
+        }
+
+    config.providers = provider_configs
+    with open(config_file, "w") as fp:
+        to_write = json.loads(json.dumps(config.dict(), cls=EnumEncoder))
+        fp.write(yaml.dump(to_write, sort_keys=False))
+
+    print(f"YAML configuration has been written to {config_path}")

llama_toolchain/common/config_dirs.py

@@ -13,3 +13,5 @@ LLAMA_STACK_CONFIG_DIR = Path(os.path.expanduser("~/.llama/"))
 DISTRIBS_BASE_DIR = LLAMA_STACK_CONFIG_DIR / "distributions"
 
 DEFAULT_CHECKPOINT_DIR = LLAMA_STACK_CONFIG_DIR / "checkpoints"
+
+BUILDS_BASE_DIR = LLAMA_STACK_CONFIG_DIR / "builds"

llama_toolchain/common/prompt_for_config.py

@@ -71,6 +71,7 @@ def prompt_for_config(
     """
     config_data = {}
 
+    print(f"Configuring {config_type.__name__}:")
     for field_name, field in config_type.__fields__.items():
         field_type = field.annotation
 
@@ -85,6 +86,7 @@ def prompt_for_config(
                 if not isinstance(field.default, PydanticUndefinedType)
                 else None
             )
+        print(f"  {field_name}: {field_type} (default: {default_value})")
         is_required = field.is_required
 
         # Skip fields with Literal type

llama_toolchain/distribution/build_conda_env.sh

@@ -10,20 +10,29 @@ LLAMA_MODELS_DIR=${LLAMA_MODELS_DIR:-}
 LLAMA_TOOLCHAIN_DIR=${LLAMA_TOOLCHAIN_DIR:-}
 TEST_PYPI_VERSION=${TEST_PYPI_VERSION:-}
 
+echo "llama-toolchain-dir=$LLAMA_TOOLCHAIN_DIR"
 set -euo pipefail
 
+if [ "$#" -ne 3 ]; then
+  echo "Usage: $0 <api_or_stack> <environment_name> <pip_dependencies>" >&2
+  echo "Example: $0 [api|stack] conda-env 'numpy pandas scipy'" >&2
+  exit 1
+fi
+
+api_or_stack="$1"
+env_name="$2"
+pip_dependencies="$3"
+
 # Define color codes
 RED='\033[0;31m'
 GREEN='\033[0;32m'
 NC='\033[0m' # No Color
 
-error_handler() {
-  echo "Error occurred in script at line: ${1}" >&2
-  exit 1
-}
+# this is set if we actually create a new conda in which case we need to clean up
+ENVNAME=""
 
-# Set up the error trap
-trap 'error_handler ${LINENO}' ERR
+SCRIPT_DIR=$(dirname "$(readlink -f "$0")")
+source "$SCRIPT_DIR/common.sh"
 
 ensure_conda_env_python310() {
   local env_name="$1"
@@ -52,6 +61,9 @@ ensure_conda_env_python310() {
   else
     echo "Conda environment '${env_name}' does not exist. Creating with Python ${python_version}..."
     conda create -n "${env_name}" python="${python_version}" -y
+
+    ENVNAME="${env_name}"
+    setup_cleanup_handlers
   fi
 
   eval "$(conda shell.bash hook)"
@@ -94,19 +106,8 @@ ensure_conda_env_python310() {
   fi
 }
 
-if [ "$#" -ne 3 ]; then
-  echo "Usage: $0 <environment_name> <distribution_name> <pip_dependencies>" >&2
-  echo "Example: $0 my_env local-llama-8b 'numpy pandas scipy'" >&2
-  exit 1
-fi
-
-env_name="$1"
-distribution_name="$2"
-pip_dependencies="$3"
-
 ensure_conda_env_python310 "$env_name" "$pip_dependencies"
 
-echo -e "${GREEN}Successfully setup distribution environment. Configuring...${NC}"
+echo -e "${GREEN}Successfully setup conda environment. Configuring build...${NC}"
 
-which python3
-python3 -m llama_toolchain.cli.llama distribution configure --name "$distribution_name"
+$CONDA_PREFIX/bin/python3 -m llama_toolchain.cli.llama api configure "$api_or_stack" --name "$env_name"

llama_toolchain/distribution/common.sh

@@ -0,0 +1,40 @@
+# 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.
+
+cleanup() {
+  envname="$1"
+
+  set +x
+  echo "Cleaning up..."
+  conda deactivate
+  conda env remove --name $envname -y
+}
+
+handle_int() {
+  if [ -n $ENVNAME ]; then
+    cleanup $ENVNAME
+  fi
+  exit 1
+}
+
+handle_exit() {
+  if [ $? -ne 0 ]; then
+    echo -e "\033[1;31mABORTING.\033[0m"
+    if [ -n $ENVNAME ]; then
+      cleanup $ENVNAME
+    fi
+  fi
+}
+
+setup_cleanup_handlers() {
+  trap handle_int INT
+  trap handle_exit EXIT
+
+  __conda_setup="$('conda' 'shell.bash' 'hook' 2>/dev/null)"
+  eval "$__conda_setup"
+
+  conda deactivate
+}

llama_toolchain/distribution/datatypes.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+from datetime import datetime
 from enum import Enum
 from typing import Any, Dict, List, Optional
 
@@ -66,36 +67,45 @@ Fully-qualified name of the module to import. The module is expected to have:
 
 @json_schema_type
 class AdapterSpec(BaseModel):
+    adapter_id: str = Field(
+        ...,
+        description="Unique identifier for this adapter",
+    )
+    module: str = Field(
+        ...,
+        description="""
+Fully-qualified name of the module to import. The module is expected to have:
+
+ - `get_adapter_impl(config, deps)`: returns the adapter implementation
+""",
+    )
     pip_packages: List[str] = Field(
         default_factory=list,
         description="The pip dependencies needed for this implementation",
     )
-    config_class: str = Field(
-        ...,
+    config_class: Optional[str] = Field(
+        default=None,
         description="Fully-qualified classname of the config for this provider",
     )
 
 
 class RemoteProviderConfig(BaseModel):
-    base_url: str = Field(..., description="The base URL for the llama stack provider")
+    url: str = Field(..., description="The URL for the provider")
 
-    @validator("base_url")
+    @validator("url")
     @classmethod
-    def validate_base_url(cls, base_url: str) -> str:
-        if not base_url.startswith("http"):
-            raise ValueError(f"URL must start with http: {base_url}")
-        return base_url
+    def validate_url(cls, url: str) -> str:
+        if not url.startswith("http"):
+            raise ValueError(f"URL must start with http: {url}")
+        return url
+
+
+def remote_provider_id(adapter_id: str) -> str:
+    return f"remote::{adapter_id}"
 
 
 @json_schema_type
 class RemoteProviderSpec(ProviderSpec):
-    module: str = Field(
-        ...,
-        description="""
-Fully-qualified name of the module to import. The module is expected to have:
- - `get_client_impl(base_url)`: returns a client which can be used to call the remote implementation
-""",
-    )
     adapter: Optional[AdapterSpec] = Field(
         default=None,
         description="""
@@ -107,6 +117,32 @@ as being "Llama Stack compatible"
     config_class: str = "llama_toolchain.distribution.datatypes.RemoteProviderConfig"
 
 
+# need this wrapper since we don't have Pydantic v2 and that means we don't have
+# the @computed_field decorator
+def remote_provider_spec(
+    api: Api, adapter: Optional[AdapterSpec] = None
+) -> RemoteProviderSpec:
+    provider_id = (
+        remote_provider_id(adapter.adapter_id) if adapter is not None else "remote"
+    )
+    module = (
+        adapter.module if adapter is not None else f"llama_toolchain.{api.value}.client"
+    )
+    config_class = (
+        adapter.config_class
+        if adapter and adapter.config_class
+        else "llama_toolchain.distribution.datatypes.RemoteProviderConfig"
+    )
+
+    return RemoteProviderSpec(
+        api=api,
+        provider_id=provider_id,
+        pip_packages=adapter.pip_packages if adapter is not None else [],
+        module=module,
+        config_class=config_class,
+    )
+
+
 @json_schema_type
 class DistributionSpec(BaseModel):
     spec_id: str
@@ -119,13 +155,28 @@ class DistributionSpec(BaseModel):
 
 
 @json_schema_type
-class DistributionConfig(BaseModel):
-    """References to a installed / configured DistributionSpec"""
+class PackageConfig(BaseModel):
+    built_at: datetime
 
-    name: str
-    spec: str
-    conda_env: str
+    package_name: str = Field(
+        ...,
+        description="""
+Reference to the distribution this package refers to. For unregistered (adhoc) packages,
+this could be just a hash
+""",
+    )
+    docker_image: Optional[str] = Field(
+        default=None,
+        description="Reference to the docker image if this package refers to a container",
+    )
+    conda_env: Optional[str] = Field(
+        default=None,
+        description="Reference to the conda environment if this package refers to a conda environment",
+    )
     providers: Dict[str, Any] = Field(
         default_factory=dict,
-        description="Provider configurations for each of the APIs provided by this distribution",
+        description="""
+Provider configurations for each of the APIs provided by this package. This includes configurations for
+the dependencies of these providers as well.
+""",
     )

llama_toolchain/distribution/dynamic.py

@@ -30,7 +30,27 @@ def instantiate_provider(
     return asyncio.run(module.get_provider_impl(config, deps))
 
 
-def instantiate_client(provider_spec: RemoteProviderSpec, base_url: str):
+def instantiate_client(
+    provider_spec: RemoteProviderSpec, provider_config: Dict[str, Any]
+):
     module = importlib.import_module(provider_spec.module)
 
-    return asyncio.run(module.get_client_impl(base_url))
+    adapter = provider_spec.adapter
+    if adapter is not None:
+        if "adapter" not in provider_config:
+            raise ValueError(
+                f"Adapter is specified but not present in provider config: {provider_config}"
+            )
+            adapter_config = provider_config["adapter"]
+
+        config_type = instantiate_class_type(adapter.config_class)
+        if not issubclass(config_type, RemoteProviderConfig):
+            raise ValueError(
+                f"Config class {adapter.config_class} does not inherit from RemoteProviderConfig"
+            )
+
+        config = config_type(**adapter_config)
+    else:
+        config = RemoteProviderConfig(**provider_config)
+
+    return asyncio.run(module.get_adapter_impl(config))

llama_toolchain/distribution/registry.py

@@ -7,22 +7,10 @@
 from functools import lru_cache
 from typing import List, Optional
 
-from .datatypes import Api, DistributionSpec, RemoteProviderSpec
+from .datatypes import *  # noqa: F403
 from .distribution import api_providers
 
 
-def client_module(api: Api) -> str:
-    return f"llama_toolchain.{api.value}.client"
-
-
-def remote_spec(api: Api) -> RemoteProviderSpec:
-    return RemoteProviderSpec(
-        api=api,
-        provider_id=f"{api.value}-remote",
-        module=client_module(api),
-    )
-
-
 @lru_cache()
 def available_distribution_specs() -> List[DistributionSpec]:
     providers = api_providers()
@@ -40,13 +28,14 @@ def available_distribution_specs() -> List[DistributionSpec]:
         DistributionSpec(
             spec_id="remote",
             description="Point to remote services for all llama stack APIs",
-            provider_specs={x: remote_spec(x) for x in providers},
+            provider_specs={x: remote_provider_spec(x) for x in providers},
         ),
         DistributionSpec(
             spec_id="local-ollama",
             description="Like local, but use ollama for running LLM inference",
             provider_specs={
-                Api.inference: providers[Api.inference]["meta-ollama"],
+                # this is ODD; make this easier -- we just need a better function to retrieve registered providers
+                Api.inference: providers[Api.inference][remote_provider_id("ollama")],
                 Api.safety: providers[Api.safety]["meta-reference"],
                 Api.agentic_system: providers[Api.agentic_system]["meta-reference"],
                 Api.memory: providers[Api.memory]["meta-reference-faiss"],
@@ -57,9 +46,9 @@ def available_distribution_specs() -> List[DistributionSpec]:
             description="Test agentic with others as remote",
             provider_specs={
                 Api.agentic_system: providers[Api.agentic_system]["meta-reference"],
-                Api.inference: remote_spec(Api.inference),
-                Api.memory: remote_spec(Api.memory),
-                Api.safety: remote_spec(Api.safety),
+                Api.inference: remote_provider_spec(Api.inference),
+                Api.memory: remote_provider_spec(Api.memory),
+                Api.safety: remote_provider_spec(Api.safety),
             },
         ),
         DistributionSpec(

llama_toolchain/distribution/server.py

@@ -264,7 +264,8 @@ def resolve_impls(dist: DistributionSpec, config: Dict[str, Any]) -> Dict[Api, A
         provider_config = provider_configs[api.value]
         if isinstance(provider_spec, RemoteProviderSpec):
             impls[api] = instantiate_client(
-                provider_spec, provider_config["base_url"].rstrip("/")
+                provider_spec,
+                provider_config,
             )
         else:
             deps = {api: impls[api] for api in provider_spec.api_dependencies}

llama_toolchain/inference/adapters/__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_toolchain/inference/adapters/ollama/__init__.py

@@ -4,5 +4,4 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .config import OllamaImplConfig  # noqa
-from .ollama import get_provider_impl  # noqa
+from .ollama import get_adapter_impl  # noqa

llama_toolchain/inference/adapters/ollama/ollama.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import AsyncGenerator, Dict
+from typing import AsyncGenerator
 
 import httpx
 
@@ -14,7 +14,7 @@ from llama_models.llama3.api.tokenizer import Tokenizer
 from llama_models.sku_list import resolve_model
 from ollama import AsyncClient
 
-from llama_toolchain.distribution.datatypes import Api, ProviderSpec
+from llama_toolchain.distribution.datatypes import RemoteProviderConfig
 from llama_toolchain.inference.api import (
     ChatCompletionRequest,
     ChatCompletionResponse,
@@ -27,7 +27,6 @@ from llama_toolchain.inference.api import (
     ToolCallParseStatus,
 )
 from llama_toolchain.inference.prepare_messages import prepare_messages
-from .config import OllamaImplConfig
 
 # TODO: Eventually this will move to the llama cli model list command
 # mapping of Model SKUs to ollama models
@@ -37,26 +36,21 @@ OLLAMA_SUPPORTED_SKUS = {
 }
 
 
-async def get_provider_impl(
-    config: OllamaImplConfig, _deps: Dict[Api, ProviderSpec]
-) -> Inference:
-    assert isinstance(
-        config, OllamaImplConfig
-    ), f"Unexpected config type: {type(config)}"
-    impl = OllamaInference(config)
+async def get_adapter_impl(config: RemoteProviderConfig) -> Inference:
+    impl = OllamaInferenceAdapter(config.url)
     await impl.initialize()
     return impl
 
 
-class OllamaInference(Inference):
-    def __init__(self, config: OllamaImplConfig) -> None:
-        self.config = config
+class OllamaInferenceAdapter(Inference):
+    def __init__(self, url: str) -> None:
+        self.url = url
         tokenizer = Tokenizer.get_instance()
         self.formatter = ChatFormat(tokenizer)
 
     @property
     def client(self) -> AsyncClient:
-        return AsyncClient(host=self.config.url)
+        return AsyncClient(host=self.url)
 
     async def initialize(self) -> None:
         try:

llama_toolchain/inference/client.py

@@ -13,6 +13,8 @@ import httpx
 from pydantic import BaseModel
 from termcolor import cprint
 
+from llama_toolchain.distribution.datatypes import RemoteProviderConfig
+
 from .api import (
     ChatCompletionRequest,
     ChatCompletionResponse,
@@ -24,8 +26,8 @@ from .api import (
 from .event_logger import EventLogger
 
 
-async def get_client_impl(base_url: str):
-    return InferenceClient(base_url)
+async def get_adapter_impl(config: RemoteProviderConfig) -> Inference:
+    return InferenceClient(config.url)
 
 
 def encodable_dict(d: BaseModel):
@@ -34,7 +36,7 @@ def encodable_dict(d: BaseModel):
 
 class InferenceClient(Inference):
     def __init__(self, base_url: str):
-        print(f"Initializing client for {base_url}")
+        print(f"Inference passthrough to -> {base_url}")
         self.base_url = base_url
 
     async def initialize(self) -> None:

llama_toolchain/inference/ollama/config.py

@@ -1,16 +0,0 @@
-# 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 llama_models.schema_utils import json_schema_type
-from pydantic import BaseModel, Field
-
-
-@json_schema_type
-class OllamaImplConfig(BaseModel):
-    url: str = Field(
-        default="http://localhost:11434",
-        description="The URL for the ollama server",
-    )

llama_toolchain/inference/providers.py

@@ -6,7 +6,7 @@
 
 from typing import List
 
-from llama_toolchain.distribution.datatypes import Api, InlineProviderSpec, ProviderSpec
+from llama_toolchain.distribution.datatypes import *  # noqa: F403
 
 
 def available_inference_providers() -> List[ProviderSpec]:
@@ -27,13 +27,12 @@ def available_inference_providers() -> List[ProviderSpec]:
             module="llama_toolchain.inference.meta_reference",
             config_class="llama_toolchain.inference.meta_reference.MetaReferenceImplConfig",
         ),
-        InlineProviderSpec(
+        remote_provider_spec(
             api=Api.inference,
-            provider_id="meta-ollama",
-            pip_packages=[
-                "ollama",
-            ],
-            module="llama_toolchain.inference.ollama",
-            config_class="llama_toolchain.inference.ollama.OllamaImplConfig",
+            adapter=AdapterSpec(
+                adapter_id="ollama",
+                pip_packages=[],
+                module="llama_toolchain.inference.adapters.ollama",
+            ),
         ),
     ]

llama_toolchain/memory/client.py

@@ -6,24 +6,23 @@
 
 import asyncio
 
-# import json
 from typing import Dict, List, Optional
 
 import fire
 import httpx
 
-# from termcolor import cprint
+from llama_toolchain.distribution.datatypes import RemoteProviderConfig
 
 from .api import *  # noqa: F403
 
 
-async def get_client_impl(base_url: str):
-    return MemoryClient(base_url)
+async def get_adapter_impl(config: RemoteProviderConfig) -> Memory:
+    return MemoryClient(config.url)
 
 
 class MemoryClient(Memory):
     def __init__(self, base_url: str):
-        print(f"Initializing client for {base_url}")
+        print(f"Memory passthrough to -> {base_url}")
         self.base_url = base_url
 
     async def initialize(self) -> None:

llama_toolchain/safety/client.py

@@ -10,20 +10,17 @@ import fire
 import httpx
 
 from llama_models.llama3.api.datatypes import UserMessage
+
 from pydantic import BaseModel
 from termcolor import cprint
 
-from .api import (
-    BuiltinShield,
-    RunShieldRequest,
-    RunShieldResponse,
-    Safety,
-    ShieldDefinition,
-)
+from llama_toolchain.distribution.datatypes import RemoteProviderConfig
+
+from .api import *  # noqa: F403
 
 
-async def get_client_impl(base_url: str):
-    return SafetyClient(base_url)
+async def get_adapter_impl(config: RemoteProviderConfig) -> Safety:
+    return SafetyClient(config.url)
 
 
 def encodable_dict(d: BaseModel):
@@ -32,7 +29,7 @@ def encodable_dict(d: BaseModel):
 
 class SafetyClient(Safety):
     def __init__(self, base_url: str):
-        print(f"Initializing client for {base_url}")
+        print(f"Safety passthrough to -> {base_url}")
         self.base_url = base_url
 
     async def initialize(self) -> None: