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add tool for bing search
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parent
741310f78e
commit
640c5f8ab9
5 changed files with 79 additions and 10 deletions
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@ -16,6 +16,7 @@ from pydantic import BaseModel
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from termcolor import cprint
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
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from llama_toolchain.core.datatypes import RemoteProviderConfig
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from .api import * # noqa: F403
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@ -134,8 +135,21 @@ async def run_main(host: str, port: int):
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api = AgenticSystemClient(f"http://{host}:{port}")
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tool_definitions = [
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BraveSearchToolDefinition(),
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WolframAlphaToolDefinition(),
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BraveSearchToolDefinition(
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remote_execution=RestAPIExecutionConfig(
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url=URL(uri="https://api.bing.microsoft.com/v7.0/search"),
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method=RestAPIMethod.GET,
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headers={
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"Ocp-Apim-Subscription-Key": "2259b3f9e0cb4fc9b968bb3b02ab13e7"
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},
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params={
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"count": 3,
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"textDecorations": True,
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"textFormat": "HTML",
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},
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)
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),
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# WolframAlphaToolDefinition(),
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CodeInterpreterToolDefinition(),
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]
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tool_definitions += [
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@ -18,6 +18,7 @@ from llama_toolchain.tools.builtin import (
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BraveSearchTool,
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CodeInterpreterTool,
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PhotogenTool,
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RemoteSearchTool,
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WolframAlphaTool,
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)
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from llama_toolchain.tools.safety import with_safety
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@ -63,10 +64,13 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
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raise ValueError("Wolfram API key not defined in config")
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tool = WolframAlphaTool(key)
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elif isinstance(tool_defn, BraveSearchToolDefinition):
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key = self.config.brave_search_api_key
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if not key:
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raise ValueError("Brave API key not defined in config")
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tool = BraveSearchTool(key)
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if tool_defn.remote_execution is not None:
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tool = RemoteSearchTool(tool_defn.remote_execution)
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else:
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key = self.config.brave_search_api_key
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if not key:
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raise ValueError("Brave API key not defined in config")
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tool = BraveSearchTool(key)
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elif isinstance(tool_defn, CodeInterpreterToolDefinition):
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tool = CodeInterpreterTool()
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elif isinstance(tool_defn, PhotogenToolDefinition):
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@ -5,7 +5,7 @@
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# the root directory of this source tree.
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from enum import Enum
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from typing import Dict, Optional
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from typing import Any, Dict, Optional
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from llama_models.llama3.api.datatypes import URL
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@ -26,6 +26,6 @@ class RestAPIMethod(Enum):
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class RestAPIExecutionConfig(BaseModel):
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url: URL
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method: RestAPIMethod
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params: Optional[Dict[str, str]] = None
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headers: Optional[Dict[str, str]] = None
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body: Optional[Dict[str, str]] = None
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params: Optional[Dict[str, Any]] = None
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headers: Optional[Dict[str, Any]] = None
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body: Optional[Dict[str, Any]] = None
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@ -86,6 +86,14 @@ class InferenceClient(Inference):
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async def run_main(host: str, port: int, stream: bool):
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client = InferenceClient(f"http://{host}:{port}")
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# from llama_toolchain.inference.meta_reference import get_provider_impl
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# from .meta_reference.config import MetaReferenceImplConfig
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# config = MetaReferenceImplConfig(
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# model="Meta-Llama3.1-8B-Instruct",
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# max_seq_len=4096,
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# )
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# client = await get_provider_impl(config, {})
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message = UserMessage(content="hello world, troll me in two-paragraphs about 42")
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cprint(f"User>{message.content}", "green")
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@ -14,6 +14,8 @@ from typing import List, Optional
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import requests
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from termcolor import cprint
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from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
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from .ipython_tool.code_execution import (
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CodeExecutionContext,
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CodeExecutionRequest,
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@ -83,6 +85,47 @@ class PhotogenTool(SingleMessageBuiltinTool):
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raise NotImplementedError()
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class RemoteSearchTool(SingleMessageBuiltinTool):
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def __init__(self, config: RestAPIExecutionConfig) -> None:
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self.config = config
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def get_name(self) -> str:
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return BuiltinTool.brave_search.value
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async def run_impl(self, query: str) -> str:
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params = self.config.params.copy()
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params["q"] = query
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response = requests.get(
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url=self.config.url,
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params=params,
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headers=self.config.headers,
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)
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response.raise_for_status()
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clean = self._clean_response(response.json())
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return json.dumps(clean)
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def _clean_response(self, search_response):
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clean_response = []
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query = search_response["queryContext"]["originalQuery"]
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if "webPages" in search_response:
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pages = search_response["webPages"]["value"]
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for p in pages:
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selected_keys = {"name", "url", "snippet"}
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clean_response.append(
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{k: v for k, v in p.items() if k in selected_keys}
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)
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if "news" in search_response:
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clean_news = []
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news = search_response["news"]["value"]
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for n in news:
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selected_keys = {"name", "url", "description"}
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clean_news.append({k: v for k, v in n.items() if k in selected_keys})
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clean_response.append(clean_news)
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return {"query": query, "top_k": clean_response}
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class BraveSearchTool(SingleMessageBuiltinTool):
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def __init__(self, api_key: str) -> None:
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self.api_key = api_key
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