25213f2004
- eveai_chat becomes deprecated and should be replaced with SSE - Adaptation of STANDARD_RAG specialist - Base class definition allowing to realise specialists with crewai framework - Implementation of SPIN_SPECIALIST - Implementation of test app for testing specialists (test_specialist_client). Also serves as an example for future SSE-based client - Improvements to startup scripts to better handle and scale multiple connections - Small improvements to the interaction forms and views - Caching implementation improved and augmented with additional caches
25 lines
1.2 KiB
Python
25 lines
1.2 KiB
Python
from typing import List, Optional
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from pydantic import BaseModel, Field
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class SPINOutput(BaseModel):
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situation: Optional[str] = Field(None, description="Situation information")
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problem: Optional[str] = Field(None, description="Problem information")
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implication: Optional[str] = Field(None, description="Implication information")
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need: Optional[str] = Field(None, description="Need-payoff information")
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additional_info: Optional[str] = Field(None, description="Additional sales-related information.")
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questions: Optional[str] = Field(None, description="Additional questions to further clarify SPIN")
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potential_customer: Optional[bool] = Field(False, description="Indication if this could be a good customer")
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def __str__(self):
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"""Custom string output for usage in agents and tasks"""
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return (f"Situation: {self.situation or 'N/A'}\n"
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f"Problem: {self.problem or 'N/A'}\n"
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f"Implication: {self.implication or 'N/A'}\n"
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f"Need: {self.need or 'N/A'}\n"
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f"Additional Info: {self.additional_info or 'N/A'}\n"
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f"Questions: {self.questions or 'N/A'}\n"
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f"Potential Customer: {self.potential_customer or 'N/A'}\n")
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