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import requests |
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from requests.auth import HTTPBasicAuth |
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from langflow.base.models.openai_constants import OPENAI_MODEL_NAMES |
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from langflow.custom import Component |
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from langflow.inputs import DropdownInput, SecretStrInput, StrInput |
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from langflow.io import MessageTextInput, Output |
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from langflow.schema import Data |
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from langflow.schema.message import Message |
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class CombinatorialReasonerComponent(Component): |
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display_name = "Combinatorial Reasoner" |
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description = "Uses Combinatorial Optimization to construct an optimal prompt with embedded reasons. Sign up here:\nhttps://forms.gle/oWNv2NKjBNaqqvCx6" |
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icon = "Icosa" |
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name = "Combinatorial Reasoner" |
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inputs = [ |
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MessageTextInput(name="prompt", display_name="Prompt"), |
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SecretStrInput( |
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name="openai_api_key", |
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display_name="OpenAI API Key", |
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info="The OpenAI API Key to use for the OpenAI model.", |
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advanced=False, |
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value="OPENAI_API_KEY", |
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), |
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StrInput( |
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name="username", |
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display_name="Username", |
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info="Username to authenticate access to Icosa CR API", |
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advanced=False, |
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), |
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SecretStrInput( |
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name="password", |
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display_name="Password", |
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info="Password to authenticate access to Icosa CR API.", |
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advanced=False, |
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), |
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DropdownInput( |
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name="model_name", |
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display_name="Model Name", |
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advanced=False, |
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options=OPENAI_MODEL_NAMES, |
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value=OPENAI_MODEL_NAMES[0], |
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), |
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] |
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outputs = [ |
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Output( |
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display_name="Optimized Prompt", |
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name="optimized_prompt", |
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method="build_prompt", |
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), |
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Output(display_name="Selected Reasons", name="reasons", method="build_reasons"), |
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] |
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def build_prompt(self) -> Message: |
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params = { |
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"prompt": self.prompt, |
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"apiKey": self.openai_api_key, |
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"model": self.model_name, |
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} |
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creds = HTTPBasicAuth(self.username, password=self.password) |
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response = requests.post( |
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"https://cr-api.icosacomputing.com/cr/langflow", |
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json=params, |
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auth=creds, |
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timeout=100, |
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) |
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response.raise_for_status() |
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prompt = response.json()["prompt"] |
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self.reasons = response.json()["finalReasons"] |
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return prompt |
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def build_reasons(self) -> Data: |
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final_reasons = [reason[0] for reason in self.reasons] |
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return Data(value=final_reasons) |
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