feat(tools): add TavilyAI search tool for enhanced LLM search results (#3774)

* add tavily new icon

* feat(tools): add TavilyAI search tool for enhanced LLM search results

* [autofix.ci] apply automated fixes

* add tavily icon

* [autofix.ci] apply automated fixes

---------

Co-authored-by: cristhianzl <cristhian.lousa@gmail.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

src/backend/base/langflow/components/tools/TavilyAISearch.py

@@ -0,0 +1,157 @@
+import httpx
+from langchain.tools import StructuredTool
+from pydantic import BaseModel, Field
+
+from langflow.base.langchain_utilities.model import LCToolComponent
+from langflow.field_typing import Tool
+from langflow.inputs import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput
+from langflow.schema import Data
+
+
+class TavilySearchToolComponent(LCToolComponent):
+    display_name = "Tavily AI Search"
+    description = """**Tavily AI** is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. It can be used independently or as an agent tool.
+
+Note: Check 'Advanced' for all options.
+"""
+    icon = "TavilyIcon"
+    name = "TavilyAISearch"
+    documentation = "https://docs.tavily.com/"
+
+    inputs = [
+        SecretStrInput(
+            name="api_key",
+            display_name="Tavily API Key",
+            required=True,
+            info="Your Tavily API Key.",
+        ),
+        MessageTextInput(
+            name="query",
+            display_name="Search Query",
+            info="The search query you want to execute with Tavily.",
+        ),
+        DropdownInput(
+            name="search_depth",
+            display_name="Search Depth",
+            info="The depth of the search.",
+            options=["basic", "advanced"],
+            value="advanced",
+            advanced=True,
+        ),
+        DropdownInput(
+            name="topic",
+            display_name="Search Topic",
+            info="The category of the search.",
+            options=["general", "news"],
+            value="general",
+            advanced=True,
+        ),
+        IntInput(
+            name="max_results",
+            display_name="Max Results",
+            info="The maximum number of search results to return.",
+            value=5,
+            advanced=True,
+        ),
+        BoolInput(
+            name="include_images",
+            display_name="Include Images",
+            info="Include a list of query-related images in the response.",
+            value=True,
+            advanced=True,
+        ),
+        BoolInput(
+            name="include_answer",
+            display_name="Include Answer",
+            info="Include a short answer to original query.",
+            value=True,
+            advanced=True,
+        ),
+    ]
+
+    class TavilySearchSchema(BaseModel):
+        query: str = Field(..., description="The search query you want to execute with Tavily.")
+        search_depth: str = Field("basic", description="The depth of the search.")
+        topic: str = Field("general", description="The category of the search.")
+        max_results: int = Field(5, description="The maximum number of search results to return.")
+        include_images: bool = Field(False, description="Include a list of query-related images in the response.")
+        include_answer: bool = Field(False, description="Include a short answer to original query.")
+
+    def run_model(self) -> list[Data]:
+        return self._tavily_search(
+            self.query,
+            self.search_depth,
+            self.topic,
+            self.max_results,
+            self.include_images,
+            self.include_answer,
+        )
+
+    def build_tool(self) -> Tool:
+        return StructuredTool.from_function(
+            name="tavily_search",
+            description="Perform a web search using the Tavily API.",
+            func=self._tavily_search,
+            args_schema=self.TavilySearchSchema,
+        )
+
+    def _tavily_search(
+        self,
+        query: str,
+        search_depth: str = "basic",
+        topic: str = "general",
+        max_results: int = 5,
+        include_images: bool = False,
+        include_answer: bool = False,
+    ) -> list[Data]:
+        try:
+            url = "https://api.tavily.com/search"
+            headers = {
+                "content-type": "application/json",
+                "accept": "application/json",
+            }
+            payload = {
+                "api_key": self.api_key,
+                "query": query,
+                "search_depth": search_depth,
+                "topic": topic,
+                "max_results": max_results,
+                "include_images": include_images,
+                "include_answer": include_answer,
+            }
+
+            with httpx.Client() as client:
+                response = client.post(url, json=payload, headers=headers)
+
+            response.raise_for_status()
+            search_results = response.json()
+
+            data_results = [
+                Data(
+                    data={
+                        "title": result.get("title"),
+                        "url": result.get("url"),
+                        "content": result.get("content"),
+                        "score": result.get("score"),
+                    }
+                )
+                for result in search_results.get("results", [])
+            ]
+
+            if include_answer and search_results.get("answer"):
+                data_results.insert(0, Data(data={"answer": search_results["answer"]}))
+
+            if include_images and search_results.get("images"):
+                data_results.append(Data(data={"images": search_results["images"]}))
+
+            self.status = data_results
+            return data_results
+
+        except httpx.HTTPStatusError as e:
+            error_message = f"HTTP error: {e.response.status_code} - {e.response.text}"
+            self.status = error_message
+            return [Data(data={"error": error_message})]
+        except Exception as e:
+            error_message = f"Unexpected error: {str(e)}"
+            self.status = error_message
+            return [Data(data={"error": error_message})]

src/frontend/src/icons/Tavily/Tavily.jsx

@@ -0,0 +1,69 @@
+const Tavily = (props) => (
+  <svg
+    xmlns="http://www.w3.org/2000/svg"
+    width="1em"
+    height="1em"
+    viewBox="0 0 375 375"
+    {...props}
+  >
+    <defs>
+      <clipPath id="a">
+        <path d="M109.379 231.133h37.105v37.105H109.38Zm0 0" />
+      </clipPath>
+      <clipPath id="b">
+        <path d="M127.934 231.133c-10.246 0-18.555 8.304-18.555 18.554 0 10.247 8.308 18.551 18.555 18.551 10.246 0 18.55-8.304 18.55-18.55 0-10.25-8.304-18.555-18.55-18.555Zm0 0" />
+      </clipPath>
+    </defs>
+    <path
+      fill="none"
+      stroke="#f25022"
+      strokeLinecap="round"
+      strokeWidth={28.360419999999998}
+      d="M127.926 239.96V50.165"
+    />
+    <path
+      fill="none"
+      stroke="#f25022"
+      strokeLinecap="round"
+      strokeLinejoin="round"
+      strokeWidth={28.360419999999998}
+      d="m85.387 99.793 42.539-56.719 42.539 56.719"
+    />
+    <path
+      fill="none"
+      stroke="#ffb901"
+      strokeLinecap="round"
+      strokeWidth={28.360419999999998}
+      d="m141.012 254.168 172.476-.02"
+    />
+    <path
+      fill="none"
+      stroke="#ffb901"
+      strokeLinecap="round"
+      strokeLinejoin="round"
+      strokeWidth={28.360419999999998}
+      d="m263.855 211.613 56.723 42.535-56.715 42.547"
+    />
+    <path
+      fill="none"
+      stroke="#04a3ec"
+      strokeLinecap="round"
+      strokeWidth={23.20398}
+      d="m117.852 259.344-57.446 66.015"
+    />
+    <path
+      fill="none"
+      stroke="#04a3ec"
+      strokeLinecap="round"
+      strokeLinejoin="round"
+      strokeWidth={23.20398}
+      d="m113.32 317.574-56.718 12.16 4.207-57.859"
+    />
+    <g clipPath="url(#a)">
+      <g clipPath="url(#b)">
+        <path fill="#32b37f" d="M109.379 231.133h37.105v37.105H109.38Zm0 0" />
+      </g>
+    </g>
+  </svg>
+);
+export default Tavily;

src/frontend/src/icons/Tavily/index.tsx

@@ -0,0 +1,9 @@
+import React, { forwardRef } from "react";
+import Tavily from "./Tavily";
+
+export const TavilyIcon = forwardRef<
+  SVGSVGElement,
+  React.PropsWithChildren<{}>
+>((props, ref) => {
+  return <Tavily ref={ref} {...props} />;
+});

src/frontend/src/icons/Tavily/tavily.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="500" zoomAndPan="magnify" viewBox="0 0 375 374.999991" height="500" preserveAspectRatio="xMidYMid meet" version="1.0"><defs><clipPath id="d0348dc115"><path d="M 109.378906 231.132812 L 146.484375 231.132812 L 146.484375 268.238281 L 109.378906 268.238281 Z M 109.378906 231.132812 " clip-rule="nonzero"/></clipPath><clipPath id="a28b194a7a"><path d="M 127.933594 231.132812 C 117.6875 231.132812 109.378906 239.4375 109.378906 249.6875 C 109.378906 259.933594 117.6875 268.238281 127.933594 268.238281 C 138.179688 268.238281 146.484375 259.933594 146.484375 249.6875 C 146.484375 239.4375 138.179688 231.132812 127.933594 231.132812 Z M 127.933594 231.132812 " clip-rule="nonzero"/></clipPath></defs><path stroke-linecap="round" transform="matrix(0, -2.578223, 2.578223, 0, 113.745458, 254.140061)" fill="none" stroke-linejoin="miter" d="M 5.499573 5.500038 L 79.114962 5.500038 " stroke="#f25022" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(0, -2.578223, 2.578223, 0, 113.745458, 254.140061)" fill="none" stroke-linejoin="round" d="M 59.865692 -10.999336 L 81.864858 5.500038 L 59.865692 21.999412 " stroke="#f25022" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(2.578223, -0.000251357, 0.000251357, 2.578223, 126.828174, 239.987372)" fill="none" stroke-linejoin="miter" d="M 5.500751 5.50068 L 72.398214 5.499627 " stroke="#ffb901" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(2.578223, -0.000251357, 0.000251357, 2.578223, 126.828174, 239.987372)" fill="none" stroke-linejoin="round" d="M 53.149037 -11.000109 L 75.148109 5.499895 L 53.14885 22.000154 " stroke="#ffb901" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(-1.692446, 1.944957, -1.944957, -1.692446, 134.219043, 258.208373)" fill="none" stroke-linejoin="miter" d="M 4.499518 4.49999 L 38.441562 4.500107 " stroke="#04a3ec" stroke-width="9" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(-1.692446, 1.944957, -1.944957, -1.692446, 134.219043, 258.208373)" fill="none" stroke-linejoin="round" d="M 22.691248 -9.000192 L 40.69038 4.49943 L 22.68978 17.999994 " stroke="#04a3ec" stroke-width="9" stroke-opacity="1" stroke-miterlimit="4"/><g clip-path="url(#d0348dc115)"><g clip-path="url(#a28b194a7a)"><path fill="#32b37f" d="M 109.378906 231.132812 L 146.484375 231.132812 L 146.484375 268.238281 L 109.378906 268.238281 Z M 109.378906 231.132812 " fill-opacity="1" fill-rule="nonzero"/></g></g></svg>

src/frontend/src/utils/styleUtils.ts

@@ -1,6 +1,7 @@
 import { AIMLIcon } from "@/icons/AIML";
 import { DuckDuckGoIcon } from "@/icons/DuckDuckGo";
 import Perplexity from "@/icons/Perplexity/Perplexity";
+import { TavilyIcon } from "@/icons/Tavily";
 import { UnstructuredIcon } from "@/icons/Unstructured";
 import { AthenaIcon } from "@/icons/athena/index";
 import { freezeAllIcon } from "@/icons/freezeAll";
@@ -636,6 +637,7 @@ export const nodeIconsLucide: iconsType = {
   OptionIcon: OptionIcon,
   Option: OptionIcon,
   Perplexity,
+  TavilyIcon,
   DuckDuckGo: DuckDuckGoIcon,
   OpenSearch,
 };