- Refinement of the chat client to have better visible clues for user vs chatbot messages
- Introduction of interview_phase and normal phase in TRAICIE_SELECTION_SPECIALIST to make interaction with bot more human. - More and random humanised messages to TRAICIE_SELECTION_SPECIALIST
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@@ -7,3 +7,7 @@ class RAGOutput(BaseModel):
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answer: str = Field(None, description="Answer to the questions asked, in Markdown format.")
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insufficient_info: bool = Field(None, description="An indication if there's insufficient information to answer")
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model_config = {
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"extra": "allow"
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}
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@@ -0,0 +1,12 @@
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class TraicieAdvancedRAGOutput(BaseModel):
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mode: str = Field(..., description="The mode of execution (RAG or CHECK).")
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answer: str = Field(None, description="Answer to the questions asked, when in RAG")
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insufficient_info: bool = Field(None, description="An indication if there's insufficient information to answer, when in RAG")
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affirmative_answer: bool = Field(None, description="An indication if the answer is affirmative (true) or negative (false), when in CHECK")
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@@ -0,0 +1,10 @@
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class TraicieAffirmativeAnswerOutput(BaseModel):
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affirmative: bool = Field(..., description="Is the provided answer affirmative (true) or negative (false).")
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@@ -0,0 +1,10 @@
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class TraicieInterviewModeOutput(BaseModel):
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mode: str = Field(..., description="Your answer: RAG or CHECK.")
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