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