add wolfram alpha, bing search

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):
+    api_key: str
+
+
+async def get_adapter_impl(config: BingSearchToolConfig, _deps):
+    impl = BingSearchToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

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

@@ -0,0 +1,116 @@
+# 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, Dict, List, Optional
+
+import requests
+from llama_models.llama3.api.datatypes import BuiltinTool
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    Tool,
+    ToolDef,
+    ToolInvocationResult,
+    ToolParameter,
+    ToolRuntime,
+)
+from llama_stack.distribution.request_headers import NeedsRequestProviderData
+from llama_stack.providers.datatypes import ToolsProtocolPrivate
+
+from .config import BingSearchToolConfig
+
+
+class BingSearchToolRuntimeImpl(
+    ToolsProtocolPrivate, 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_tool(self, tool: Tool):
+        pass
+
+    async def unregister_tool(self, tool_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.api_key:
+            raise ValueError(
+                'Pass Bing Search API Key in the header X-LlamaStack-ProviderData as { "api_key": <your api key>}'
+            )
+        return provider_data.api_key
+
+    async def list_tools(
+        self, tool_group_id: Optional[str] = None, mcp_endpoint: Optional[URL] = None
+    ) -> List[ToolDef]:
+        return [
+            ToolDef(
+                name="web_search",
+                description="Search the web using Bing Search API",
+                parameters=[
+                    ToolParameter(
+                        name="query",
+                        description="The query to search for",
+                        parameter_type="string",
+                    )
+                ],
+                built_in_type=BuiltinTool.brave_search,
+            )
+        ]
+
+    async def invoke_tool(
+        self, tool_name: str, args: 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": args["query"],
+        }
+
+        response = requests.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}

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

@@ -0,0 +1,16 @@
+# 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 Optional
+
+from pydantic import BaseModel
+
+
+class BingSearchToolConfig(BaseModel):
+    """Configuration for Bing Search Tool Runtime"""
+
+    api_key: Optional[str] = None
+    top_k: int = 3

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

@@ -7,6 +7,7 @@
 from typing import Any, Dict, List, Optional
 
 import requests
+from llama_models.llama3.api.datatypes import BuiltinTool
 
 from llama_stack.apis.common.content_types import URL
 from llama_stack.apis.tools import (
@@ -62,6 +63,7 @@ class BraveSearchToolRuntimeImpl(
                         parameter_type="string",
                     )
                 ],
+                built_in_type=BuiltinTool.brave_search,
             )
         ]
 

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

@@ -8,6 +8,7 @@ import json
 from typing import Any, Dict, List, Optional
 
 import requests
+from llama_models.llama3.api.datatypes import BuiltinTool
 
 from llama_stack.apis.common.content_types import URL
 from llama_stack.apis.tools import (
@@ -63,6 +64,7 @@ class TavilySearchToolRuntimeImpl(
                         parameter_type="string",
                     )
                 ],
+                built_in_type=BuiltinTool.brave_search,
             )
         ]
 

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):
+    api_key: str
+
+
+async def get_adapter_impl(config: WolframAlphaToolConfig, _deps):
+    impl = WolframAlphaToolRuntimeImpl(config)
+    await impl.initialize()
+    return impl

llama_stack/providers/remote/tool_runtime/wolfram_alpha/config.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 typing import Optional
+
+from pydantic import BaseModel
+
+
+class WolframAlphaToolConfig(BaseModel):
+    """Configuration for WolframAlpha Tool Runtime"""
+
+    api_key: Optional[str] = None

llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.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.
+
+import json
+from typing import Any, Dict, List, Optional
+
+import requests
+from llama_models.llama3.api.datatypes import BuiltinTool
+
+from llama_stack.apis.common.content_types import URL
+from llama_stack.apis.tools import (
+    Tool,
+    ToolDef,
+    ToolInvocationResult,
+    ToolParameter,
+    ToolRuntime,
+)
+from llama_stack.distribution.request_headers import NeedsRequestProviderData
+from llama_stack.providers.datatypes import ToolsProtocolPrivate
+
+from .config import WolframAlphaToolConfig
+
+
+class WolframAlphaToolRuntimeImpl(
+    ToolsProtocolPrivate, 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_tool(self, tool: Tool):
+        pass
+
+    async def unregister_tool(self, tool_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.api_key:
+            raise ValueError(
+                'Pass WolframAlpha API Key in the header X-LlamaStack-ProviderData as { "api_key": <your api key>}'
+            )
+        return provider_data.api_key
+
+    async def list_tools(
+        self, tool_group_id: Optional[str] = None, mcp_endpoint: Optional[URL] = None
+    ) -> List[ToolDef]:
+        return [
+            ToolDef(
+                name="wolfram_alpha",
+                description="Query WolframAlpha for computational knowledge",
+                parameters=[
+                    ToolParameter(
+                        name="query",
+                        description="The query to compute",
+                        parameter_type="string",
+                    )
+                ],
+                built_in_type=BuiltinTool.wolfram_alpha,
+            )
+        ]
+
+    async def invoke_tool(
+        self, tool_name: str, args: Dict[str, Any]
+    ) -> ToolInvocationResult:
+        api_key = self._get_api_key()
+        params = {
+            "input": args["query"],
+            "appid": api_key,
+            "format": "plaintext",
+            "output": "json",
+        }
+        response = requests.get(
+            self.url,
+            params=params,
+        )
+
+        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