chore(package): migrate to src/ layout (#3920)

Migrates package structure to src/ layout following Python packaging
best practices.

All code moved from `llama_stack/` to `src/llama_stack/`. Public API
unchanged - imports remain `import llama_stack.*`.

Updated build configs, pre-commit hooks, scripts, and GitHub workflows
accordingly. All hooks pass, package builds cleanly.

**Developer note**: Reinstall after pulling: `pip install -e .`

src/llama_stack/providers/remote/tool_runtime/__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.

src/llama_stack/providers/remote/tool_runtime/bing_search/__init__.py

@@ -0,0 +1,21 @@
+# 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 .bing_search import BingSearchToolRuntimeImpl
+from .config import BingSearchToolConfig
+
+__all__ = ["BingSearchToolConfig", "BingSearchToolRuntimeImpl"]
+from pydantic import BaseModel
+
+
+class BingSearchToolProviderDataValidator(BaseModel):
+    bing_search_api_key: str
+
+
+async def get_adapter_impl(config: BingSearchToolConfig, _deps):
+    impl = BingSearchToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

src/llama_stack/providers/remote/tool_runtime/bing_search/bing_search.py

@@ -0,0 +1,112 @@
+# 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 json
+from typing import Any
+
+import httpx
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    ListToolDefsResponse,
+    ToolDef,
+    ToolGroup,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
+
+from .config import BingSearchToolConfig
+
+
+class BingSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+    def __init__(self, config: BingSearchToolConfig):
+        self.config = config
+        self.url = "https://api.bing.microsoft.com/v7.0/search"
+
+    async def initialize(self):
+        pass
+
+    async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+        pass
+
+    async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+        return
+
+    def _get_api_key(self) -> str:
+        if self.config.api_key:
+            return self.config.api_key
+
+        provider_data = self.get_request_provider_data()
+        if provider_data is None or not provider_data.bing_search_api_key:
+            raise ValueError(
+                'Pass Bing Search API Key in the header X-LlamaStack-Provider-Data as { "bing_search_api_key": <your api key>}'
+            )
+        return provider_data.bing_search_api_key
+
+    async def list_runtime_tools(
+        self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
+    ) -> ListToolDefsResponse:
+        return ListToolDefsResponse(
+            data=[
+                ToolDef(
+                    name="web_search",
+                    description="Search the web using Bing Search API",
+                    input_schema={
+                        "type": "object",
+                        "properties": {
+                            "query": {
+                                "type": "string",
+                                "description": "The query to search for",
+                            }
+                        },
+                        "required": ["query"],
+                    },
+                )
+            ]
+        )
+
+    async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
+        api_key = self._get_api_key()
+        headers = {
+            "Ocp-Apim-Subscription-Key": api_key,
+        }
+        params = {
+            "count": self.config.top_k,
+            "textDecorations": True,
+            "textFormat": "HTML",
+            "q": kwargs["query"],
+        }
+
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                url=self.url,
+                params=params,
+                headers=headers,
+            )
+            response.raise_for_status()
+
+        return ToolInvocationResult(content=json.dumps(self._clean_response(response.json())))
+
+    def _clean_response(self, search_response):
+        clean_response = []
+        query = search_response["queryContext"]["originalQuery"]
+        if "webPages" in search_response:
+            pages = search_response["webPages"]["value"]
+            for p in pages:
+                selected_keys = {"name", "url", "snippet"}
+                clean_response.append({k: v for k, v in p.items() if k in selected_keys})
+        if "news" in search_response:
+            clean_news = []
+            news = search_response["news"]["value"]
+            for n in news:
+                selected_keys = {"name", "url", "description"}
+                clean_news.append({k: v for k, v in n.items() if k in selected_keys})
+
+            clean_response.append(clean_news)
+
+        return {"query": query, "top_k": clean_response}

src/llama_stack/providers/remote/tool_runtime/bing_search/config.py

@@ -0,0 +1,22 @@
+# 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
+
+from pydantic import BaseModel
+
+
+class BingSearchToolConfig(BaseModel):
+    """Configuration for Bing Search Tool Runtime"""
+
+    api_key: str | None = None
+    top_k: int = 3
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
+        return {
+            "api_key": "${env.BING_API_KEY:}",
+        }

src/llama_stack/providers/remote/tool_runtime/brave_search/__init__.py

@@ -0,0 +1,20 @@
+# 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 pydantic import BaseModel
+
+from .brave_search import BraveSearchToolRuntimeImpl
+from .config import BraveSearchToolConfig
+
+
+class BraveSearchToolProviderDataValidator(BaseModel):
+    brave_search_api_key: str
+
+
+async def get_adapter_impl(config: BraveSearchToolConfig, _deps):
+    impl = BraveSearchToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

src/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py

@@ -0,0 +1,148 @@
+# 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
+
+import httpx
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    ListToolDefsResponse,
+    ToolDef,
+    ToolGroup,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.models.llama.datatypes import BuiltinTool
+from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
+
+from .config import BraveSearchToolConfig
+
+
+class BraveSearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+    def __init__(self, config: BraveSearchToolConfig):
+        self.config = config
+
+    async def initialize(self):
+        pass
+
+    async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+        pass
+
+    async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+        return
+
+    def _get_api_key(self) -> str:
+        if self.config.api_key:
+            return self.config.api_key
+
+        provider_data = self.get_request_provider_data()
+        if provider_data is None or not provider_data.brave_search_api_key:
+            raise ValueError(
+                'Pass Search provider\'s API Key in the header X-LlamaStack-Provider-Data as { "brave_search_api_key": <your api key>}'
+            )
+        return provider_data.brave_search_api_key
+
+    async def list_runtime_tools(
+        self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
+    ) -> ListToolDefsResponse:
+        return ListToolDefsResponse(
+            data=[
+                ToolDef(
+                    name="web_search",
+                    description="Search the web for information",
+                    input_schema={
+                        "type": "object",
+                        "properties": {
+                            "query": {
+                                "type": "string",
+                                "description": "The query to search for",
+                            }
+                        },
+                        "required": ["query"],
+                    },
+                    built_in_type=BuiltinTool.brave_search,
+                )
+            ]
+        )
+
+    async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
+        api_key = self._get_api_key()
+        url = "https://api.search.brave.com/res/v1/web/search"
+        headers = {
+            "X-Subscription-Token": api_key,
+            "Accept-Encoding": "gzip",
+            "Accept": "application/json",
+        }
+        payload = {"q": kwargs["query"]}
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                url=url,
+                params=payload,
+                headers=headers,
+            )
+            response.raise_for_status()
+        results = self._clean_brave_response(response.json())
+        content_items = "\n".join([str(result) for result in results])
+        return ToolInvocationResult(
+            content=content_items,
+        )
+
+    def _clean_brave_response(self, search_response):
+        clean_response = []
+        if "mixed" in search_response:
+            mixed_results = search_response["mixed"]
+            for m in mixed_results["main"][: self.config.max_results]:
+                r_type = m["type"]
+                results = search_response[r_type]["results"]
+                cleaned = self._clean_result_by_type(r_type, results, m.get("index"))
+                clean_response.append(cleaned)
+
+        return clean_response
+
+    def _clean_result_by_type(self, r_type, results, idx=None):
+        type_cleaners = {
+            "web": (
+                ["type", "title", "url", "description", "date", "extra_snippets"],
+                lambda x: x[idx],
+            ),
+            "faq": (["type", "question", "answer", "title", "url"], lambda x: x),
+            "infobox": (
+                ["type", "title", "url", "description", "long_desc"],
+                lambda x: x[idx],
+            ),
+            "videos": (["type", "url", "title", "description", "date"], lambda x: x),
+            "locations": (
+                [
+                    "type",
+                    "title",
+                    "url",
+                    "description",
+                    "coordinates",
+                    "postal_address",
+                    "contact",
+                    "rating",
+                    "distance",
+                    "zoom_level",
+                ],
+                lambda x: x,
+            ),
+            "news": (["type", "title", "url", "description"], lambda x: x),
+        }
+
+        if r_type not in type_cleaners:
+            return ""
+
+        selected_keys, result_selector = type_cleaners[r_type]
+        results = result_selector(results)
+
+        if isinstance(results, list):
+            cleaned = [{k: v for k, v in item.items() if k in selected_keys} for item in results]
+        else:
+            cleaned = {k: v for k, v in results.items() if k in selected_keys}
+
+        return str(cleaned)

src/llama_stack/providers/remote/tool_runtime/brave_search/config.py

@@ -0,0 +1,27 @@
+# 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
+
+from pydantic import BaseModel, Field
+
+
+class BraveSearchToolConfig(BaseModel):
+    api_key: str | None = Field(
+        default=None,
+        description="The Brave Search API Key",
+    )
+    max_results: int = Field(
+        default=3,
+        description="The maximum number of results to return",
+    )
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+        return {
+            "api_key": "${env.BRAVE_SEARCH_API_KEY:=}",
+            "max_results": 3,
+        }

src/llama_stack/providers/remote/tool_runtime/model_context_protocol/__init__.py

@@ -0,0 +1,15 @@
+# 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 .config import MCPProviderConfig
+
+
+async def get_adapter_impl(config: MCPProviderConfig, _deps):
+    from .model_context_protocol import ModelContextProtocolToolRuntimeImpl
+
+    impl = ModelContextProtocolToolRuntimeImpl(config, _deps)
+    await impl.initialize()
+    return impl

src/llama_stack/providers/remote/tool_runtime/model_context_protocol/config.py

@@ -0,0 +1,20 @@
+# 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
+
+from pydantic import BaseModel
+
+
+class MCPProviderDataValidator(BaseModel):
+    # mcp_endpoint => dict of headers to send
+    mcp_headers: dict[str, dict[str, str]] | None = None
+
+
+class MCPProviderConfig(BaseModel):
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
+        return {}

src/llama_stack/providers/remote/tool_runtime/model_context_protocol/model_context_protocol.py

@@ -0,0 +1,73 @@
+# 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
+from urllib.parse import urlparse
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.datatypes import Api
+from llama_stack.apis.tools import (
+    ListToolDefsResponse,
+    ToolGroup,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.log import get_logger
+from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
+from llama_stack.providers.utils.tools.mcp import invoke_mcp_tool, list_mcp_tools
+
+from .config import MCPProviderConfig
+
+logger = get_logger(__name__, category="tools")
+
+
+class ModelContextProtocolToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+    def __init__(self, config: MCPProviderConfig, _deps: dict[Api, Any]):
+        self.config = config
+
+    async def initialize(self):
+        pass
+
+    async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+        pass
+
+    async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+        return
+
+    async def list_runtime_tools(
+        self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
+    ) -> ListToolDefsResponse:
+        # this endpoint should be retrieved by getting the tool group right?
+        if mcp_endpoint is None:
+            raise ValueError("mcp_endpoint is required")
+        headers = await self.get_headers_from_request(mcp_endpoint.uri)
+        return await list_mcp_tools(mcp_endpoint.uri, headers)
+
+    async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
+        tool = await self.tool_store.get_tool(tool_name)
+        if tool.metadata is None or tool.metadata.get("endpoint") is None:
+            raise ValueError(f"Tool {tool_name} does not have metadata")
+        endpoint = tool.metadata.get("endpoint")
+        if urlparse(endpoint).scheme not in ("http", "https"):
+            raise ValueError(f"Endpoint {endpoint} is not a valid HTTP(S) URL")
+
+        headers = await self.get_headers_from_request(endpoint)
+        return await invoke_mcp_tool(endpoint, headers, tool_name, kwargs)
+
+    async def get_headers_from_request(self, mcp_endpoint_uri: str) -> dict[str, str]:
+        def canonicalize_uri(uri: str) -> str:
+            return f"{urlparse(uri).netloc or ''}/{urlparse(uri).path or ''}"
+
+        headers = {}
+
+        provider_data = self.get_request_provider_data()
+        if provider_data and provider_data.mcp_headers:
+            for uri, values in provider_data.mcp_headers.items():
+                if canonicalize_uri(uri) != canonicalize_uri(mcp_endpoint_uri):
+                    continue
+                headers.update(values)
+        return headers

src/llama_stack/providers/remote/tool_runtime/tavily_search/__init__.py

@@ -0,0 +1,20 @@
+# 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 pydantic import BaseModel
+
+from .config import TavilySearchToolConfig
+from .tavily_search import TavilySearchToolRuntimeImpl
+
+
+class TavilySearchToolProviderDataValidator(BaseModel):
+    tavily_search_api_key: str
+
+
+async def get_adapter_impl(config: TavilySearchToolConfig, _deps):
+    impl = TavilySearchToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

src/llama_stack/providers/remote/tool_runtime/tavily_search/config.py

@@ -0,0 +1,27 @@
+# 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
+
+from pydantic import BaseModel, Field
+
+
+class TavilySearchToolConfig(BaseModel):
+    api_key: str | None = Field(
+        default=None,
+        description="The Tavily Search API Key",
+    )
+    max_results: int = Field(
+        default=3,
+        description="The maximum number of results to return",
+    )
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+        return {
+            "api_key": "${env.TAVILY_SEARCH_API_KEY:=}",
+            "max_results": 3,
+        }

src/llama_stack/providers/remote/tool_runtime/tavily_search/tavily_search.py

@@ -0,0 +1,84 @@
+# 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 json
+from typing import Any
+
+import httpx
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    ListToolDefsResponse,
+    ToolDef,
+    ToolGroup,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
+
+from .config import TavilySearchToolConfig
+
+
+class TavilySearchToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+    def __init__(self, config: TavilySearchToolConfig):
+        self.config = config
+
+    async def initialize(self):
+        pass
+
+    async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+        pass
+
+    async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+        return
+
+    def _get_api_key(self) -> str:
+        if self.config.api_key:
+            return self.config.api_key
+
+        provider_data = self.get_request_provider_data()
+        if provider_data is None or not provider_data.tavily_search_api_key:
+            raise ValueError(
+                'Pass Search provider\'s API Key in the header X-LlamaStack-Provider-Data as { "tavily_search_api_key": <your api key>}'
+            )
+        return provider_data.tavily_search_api_key
+
+    async def list_runtime_tools(
+        self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
+    ) -> ListToolDefsResponse:
+        return ListToolDefsResponse(
+            data=[
+                ToolDef(
+                    name="web_search",
+                    description="Search the web for information",
+                    input_schema={
+                        "type": "object",
+                        "properties": {
+                            "query": {
+                                "type": "string",
+                                "description": "The query to search for",
+                            }
+                        },
+                        "required": ["query"],
+                    },
+                )
+            ]
+        )
+
+    async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
+        api_key = self._get_api_key()
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                "https://api.tavily.com/search",
+                json={"api_key": api_key, "query": kwargs["query"]},
+            )
+            response.raise_for_status()
+
+        return ToolInvocationResult(content=json.dumps(self._clean_tavily_response(response.json())))
+
+    def _clean_tavily_response(self, search_response, top_k=3):
+        return {"query": search_response["query"], "top_k": search_response["results"]}

src/llama_stack/providers/remote/tool_runtime/wolfram_alpha/__init__.py

@@ -0,0 +1,22 @@
+# 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 pydantic import BaseModel
+
+from .config import WolframAlphaToolConfig
+from .wolfram_alpha import WolframAlphaToolRuntimeImpl
+
+__all__ = ["WolframAlphaToolConfig", "WolframAlphaToolRuntimeImpl"]
+
+
+class WolframAlphaToolProviderDataValidator(BaseModel):
+    wolfram_alpha_api_key: str
+
+
+async def get_adapter_impl(config: WolframAlphaToolConfig, _deps):
+    impl = WolframAlphaToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

src/llama_stack/providers/remote/tool_runtime/wolfram_alpha/config.py

@@ -0,0 +1,21 @@
+# 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
+
+from pydantic import BaseModel
+
+
+class WolframAlphaToolConfig(BaseModel):
+    """Configuration for WolframAlpha Tool Runtime"""
+
+    api_key: str | None = None
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:
+        return {
+            "api_key": "${env.WOLFRAM_ALPHA_API_KEY:=}",
+        }

src/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py

@@ -0,0 +1,140 @@
+# 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 json
+from typing import Any
+
+import httpx
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    ListToolDefsResponse,
+    ToolDef,
+    ToolGroup,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.core.request_headers import NeedsRequestProviderData
+from llama_stack.providers.datatypes import ToolGroupsProtocolPrivate
+
+from .config import WolframAlphaToolConfig
+
+
+class WolframAlphaToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, NeedsRequestProviderData):
+    def __init__(self, config: WolframAlphaToolConfig):
+        self.config = config
+        self.url = "https://api.wolframalpha.com/v2/query"
+
+    async def initialize(self):
+        pass
+
+    async def register_toolgroup(self, toolgroup: ToolGroup) -> None:
+        pass
+
+    async def unregister_toolgroup(self, toolgroup_id: str) -> None:
+        return
+
+    def _get_api_key(self) -> str:
+        if self.config.api_key:
+            return self.config.api_key
+
+        provider_data = self.get_request_provider_data()
+        if provider_data is None or not provider_data.wolfram_alpha_api_key:
+            raise ValueError(
+                'Pass WolframAlpha API Key in the header X-LlamaStack-Provider-Data as { "wolfram_alpha_api_key": <your api key>}'
+            )
+        return provider_data.wolfram_alpha_api_key
+
+    async def list_runtime_tools(
+        self, tool_group_id: str | None = None, mcp_endpoint: URL | None = None
+    ) -> ListToolDefsResponse:
+        return ListToolDefsResponse(
+            data=[
+                ToolDef(
+                    name="wolfram_alpha",
+                    description="Query WolframAlpha for computational knowledge",
+                    input_schema={
+                        "type": "object",
+                        "properties": {
+                            "query": {
+                                "type": "string",
+                                "description": "The query to compute",
+                            }
+                        },
+                        "required": ["query"],
+                    },
+                )
+            ]
+        )
+
+    async def invoke_tool(self, tool_name: str, kwargs: dict[str, Any]) -> ToolInvocationResult:
+        api_key = self._get_api_key()
+        params = {
+            "input": kwargs["query"],
+            "appid": api_key,
+            "format": "plaintext",
+            "output": "json",
+        }
+        async with httpx.AsyncClient() as client:
+            response = await client.get(params=params, url=self.url)
+            response.raise_for_status()
+        return ToolInvocationResult(content=json.dumps(self._clean_wolfram_alpha_response(response.json())))
+
+    def _clean_wolfram_alpha_response(self, wa_response):
+        remove = {
+            "queryresult": [
+                "datatypes",
+                "error",
+                "timedout",
+                "timedoutpods",
+                "numpods",
+                "timing",
+                "parsetiming",
+                "parsetimedout",
+                "recalculate",
+                "id",
+                "host",
+                "server",
+                "related",
+                "version",
+                {
+                    "pods": [
+                        "scanner",
+                        "id",
+                        "error",
+                        "expressiontypes",
+                        "states",
+                        "infos",
+                        "position",
+                        "numsubpods",
+                    ]
+                },
+                "assumptions",
+            ],
+        }
+        for main_key in remove:
+            for key_to_remove in remove[main_key]:
+                try:
+                    if key_to_remove == "assumptions":
+                        if "assumptions" in wa_response[main_key]:
+                            del wa_response[main_key][key_to_remove]
+                    if isinstance(key_to_remove, dict):
+                        for sub_key in key_to_remove:
+                            if sub_key == "pods":
+                                for i in range(len(wa_response[main_key][sub_key])):
+                                    if wa_response[main_key][sub_key][i]["title"] == "Result":
+                                        del wa_response[main_key][sub_key][i + 1 :]
+                                        break
+                            sub_items = wa_response[main_key][sub_key]
+                            for i in range(len(sub_items)):
+                                for sub_key_to_remove in key_to_remove[sub_key]:
+                                    if sub_key_to_remove in sub_items[i]:
+                                        del sub_items[i][sub_key_to_remove]
+                    elif key_to_remove in wa_response[main_key]:
+                        del wa_response[main_key][key_to_remove]
+                except KeyError:
+                    pass
+        return wa_response