169b687ed0* Changed Youtube to YouTube * Updated AIML to AI/ML API * Updated AI/ML Model name * Changed Anthropic description * updated arXiv name * Set Astra Vectorize as legacy * Updated get env var * Updates firecrawl names * Updated Icon for Google Gen AI embeddings * Add Space on Home Assistant * Updated Hugging Face name * Updated Maritalk Name * Updated Not Diamond name * Updated ScrapeGraph names * Changed SearchApi Name * Changed TwelveLabs naming * Updated AstraDB naming * Updated VertexAI naming * Updated Wolfram * Updated Yahoo naming * Updated Yahoo Finance name * Updated Yahoo Finance * [autofix.ci] apply automated fixes * Update google serper bundle * updated ai ml icon name * Updated maritalk * Changed ai ml api name * removed openai from base url * Revert components-bundles changes * revert changes on components-vector-stores * Revert changes on deployment-hugging-face-spaces * Revert changes on integrations-nvidia-ingest * Revert changes on release-notes * Update changes on sequential agent * [autofix.ci] apply automated fixes * fixed filterSidebar test * updated filter edge test * updated shard 11 test with new sidebar names --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
from langchain_community.utilities.wolfram_alpha import WolframAlphaAPIWrapper
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from langflow.base.langchain_utilities.model import LCToolComponent
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from langflow.field_typing import Tool
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from langflow.inputs.inputs import MultilineInput, SecretStrInput
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from langflow.io import Output
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from langflow.schema.data import Data
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from langflow.schema.dataframe import DataFrame
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class WolframAlphaAPIComponent(LCToolComponent):
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display_name = "WolframAlpha API"
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description = """Enables queries to WolframAlpha for computational data, facts, and calculations across various \
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topics, delivering structured responses."""
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name = "WolframAlphaAPI"
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outputs = [
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Output(display_name="DataFrame", name="dataframe", method="fetch_content_dataframe"),
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]
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inputs = [
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MultilineInput(
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name="input_value", display_name="Input Query", info="Example query: 'What is the population of France?'"
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),
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SecretStrInput(name="app_id", display_name="App ID", required=True),
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]
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icon = "WolframAlphaAPI"
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def run_model(self) -> DataFrame:
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return self.fetch_content_dataframe()
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def build_tool(self) -> Tool:
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wrapper = self._build_wrapper()
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return Tool(name="wolfram_alpha_api", description="Answers mathematical questions.", func=wrapper.run)
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def _build_wrapper(self) -> WolframAlphaAPIWrapper:
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return WolframAlphaAPIWrapper(wolfram_alpha_appid=self.app_id)
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def fetch_content(self) -> list[Data]:
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wrapper = self._build_wrapper()
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result_str = wrapper.run(self.input_value)
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data = [Data(text=result_str)]
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self.status = data
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return data
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def fetch_content_dataframe(self) -> DataFrame:
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"""Convert the WolframAlpha results to a DataFrame.
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Returns:
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DataFrame: A DataFrame containing the query results.
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"""
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data = self.fetch_content()
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return DataFrame(data)
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