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| from pydantic import BaseModel, Field | |
| class ChatInterviewBody(BaseModel): | |
| """ | |
| Schema for streaming mock interview chat interactions. | |
| Sent for each turn of user input in the AI interview simulator. | |
| """ | |
| topic: str = Field( | |
| ..., | |
| description="The technical or behavioral topic of the mock interview.", | |
| example="Machine Learning Operations (MLOps)" | |
| ) | |
| companyName: str = Field( | |
| ..., | |
| description="The target company name for the simulated interview.", | |
| example="Google" | |
| ) | |
| time_remain: int = Field( | |
| ..., | |
| description="The remaining time for the interview in seconds.", | |
| example=1800 | |
| ) | |
| user_input: str = Field( | |
| ..., | |
| description="The message or response sent by the user during the chat round.", | |
| example="I have experience deploying models using Docker, Kubernetes, and FastAPI." | |
| ) | |
| thread_id: str = Field( | |
| '1', | |
| description="Unique thread identifier to track the chat session state in LangGraph checkpointer.", | |
| example="session_uuid_99" | |
| ) | |
| class Config: | |
| json_schema_extra = { | |
| "example": { | |
| "topic": "Machine Learning", | |
| "companyName": "Google", | |
| "time_remain": 1800, | |
| "user_input": "I specialize in deep learning and NLP architectures.", | |
| "thread_id": "google-ml-12345" | |
| } | |
| } |