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fix: refactor DuckDuckGo search component to use new Component base c…
…lass (nightly fix) (#6064) Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
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src/backend/base/langflow/components/tools/duck_duck_go_search_run.py
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Original file line number | Diff line number | Diff line change |
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@@ -1,75 +1,91 @@ | ||
from typing import Any | ||
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from langchain.tools import StructuredTool | ||
from langchain_community.tools import DuckDuckGoSearchRun | ||
from langchain_core.tools import ToolException | ||
from pydantic import BaseModel, Field | ||
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from langflow.base.langchain_utilities.model import LCToolComponent | ||
from langflow.field_typing import Tool | ||
from langflow.custom import Component | ||
from langflow.inputs import IntInput, MessageTextInput | ||
from langflow.io import Output | ||
from langflow.schema import Data | ||
from langflow.schema.message import Message | ||
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class DuckDuckGoSearchComponent(Component): | ||
"""Component for performing web searches using DuckDuckGo.""" | ||
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display_name = "DuckDuckGo Search" | ||
description = "Search the web using DuckDuckGo with customizable result limits" | ||
documentation = "https://python.langchain.com/docs/integrations/tools/ddg" | ||
icon = "DuckDuckGo" | ||
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class DuckDuckGoSearchComponent(LCToolComponent): | ||
display_name: str = "DuckDuckGo Search" | ||
description: str = "Perform web searches using the DuckDuckGo search engine with result limiting" | ||
name = "DuckDuckGoSearch" | ||
documentation: str = "https://python.langchain.com/docs/integrations/tools/ddg" | ||
icon: str = "DuckDuckGo" | ||
inputs = [ | ||
MessageTextInput( | ||
name="input_value", | ||
display_name="Search Query", | ||
required=True, | ||
info="The search query to execute with DuckDuckGo", | ||
tool_mode=True, | ||
), | ||
IntInput( | ||
name="max_results", | ||
display_name="Max Results", | ||
value=5, | ||
required=False, | ||
advanced=True, | ||
info="Maximum number of search results to return", | ||
), | ||
IntInput( | ||
name="max_snippet_length", | ||
display_name="Max Snippet Length", | ||
value=100, | ||
required=False, | ||
advanced=True, | ||
info="Maximum length of each result snippet", | ||
), | ||
IntInput(name="max_results", display_name="Max Results", value=5, advanced=True), | ||
IntInput(name="max_snippet_length", display_name="Max Snippet Length", value=100, advanced=True), | ||
] | ||
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class DuckDuckGoSearchSchema(BaseModel): | ||
query: str = Field(..., description="The search query") | ||
max_results: int = Field(5, description="Maximum number of results to return") | ||
max_snippet_length: int = Field(100, description="Maximum length of each result snippet") | ||
outputs = [ | ||
Output(display_name="Data", name="data", method="fetch_content"), | ||
Output(display_name="Text", name="text", method="fetch_content_text"), | ||
] | ||
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def _build_wrapper(self): | ||
def _build_wrapper(self) -> DuckDuckGoSearchRun: | ||
"""Build the DuckDuckGo search wrapper.""" | ||
return DuckDuckGoSearchRun() | ||
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def build_tool(self) -> Tool: | ||
wrapper = self._build_wrapper() | ||
def run_model(self) -> list[Data]: | ||
return self.fetch_content() | ||
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def search_func(query: str, max_results: int = 5, max_snippet_length: int = 100) -> list[dict[str, Any]]: | ||
try: | ||
full_results = wrapper.run(f"{query} (site:*)") | ||
result_list = full_results.split("\n")[:max_results] | ||
limited_results = [] | ||
for result in result_list: | ||
limited_result = { | ||
"snippet": result[:max_snippet_length], | ||
} | ||
limited_results.append(limited_result) | ||
except Exception as e: | ||
msg = f"Error in DuckDuckGo Search: {e!s}" | ||
raise ToolException(msg) from e | ||
return limited_results | ||
def fetch_content(self) -> list[Data]: | ||
"""Execute the search and return results as Data objects.""" | ||
try: | ||
wrapper = self._build_wrapper() | ||
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tool = StructuredTool.from_function( | ||
name="duckduckgo_search", | ||
description="Search for recent results using DuckDuckGo with result limiting", | ||
func=search_func, | ||
args_schema=self.DuckDuckGoSearchSchema, | ||
) | ||
self.status = "DuckDuckGo Search Tool created" | ||
return tool | ||
full_results = wrapper.run(f"{self.input_value} (site:*)") | ||
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def run_model(self) -> list[Data]: | ||
tool = self.build_tool() | ||
results = tool.run( | ||
{ | ||
"query": self.input_value, | ||
"max_results": self.max_results, | ||
"max_snippet_length": self.max_snippet_length, | ||
} | ||
) | ||
data_list = [Data(data=result, text=result.get("snippet", "")) for result in results] | ||
self.status = data_list # type: ignore[assignment] | ||
return data_list | ||
result_list = full_results.split("\n")[: self.max_results] | ||
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data_results = [] | ||
for result in result_list: | ||
if result.strip(): | ||
snippet = result[: self.max_snippet_length] | ||
data_results.append( | ||
Data( | ||
text=snippet, | ||
data={ | ||
"content": result, | ||
"snippet": snippet, | ||
}, | ||
) | ||
) | ||
except (ValueError, AttributeError) as e: | ||
error_data = [Data(text=str(e), data={"error": str(e)})] | ||
self.status = error_data | ||
return error_data | ||
else: | ||
self.status = data_results | ||
return data_results | ||
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def fetch_content_text(self) -> Message: | ||
"""Return search results as a single text message.""" | ||
data = self.fetch_content() | ||
result_string = "\n".join(item.text for item in data) | ||
self.status = result_string | ||
return Message(text=result_string) |