Ireneusz Bachanowicz
2763b40b60
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- Simplified the FastAPI application structure and improved error handling with middleware. - Introduced a retry decorator for asynchronous functions to enhance reliability. - Modularized the LLM initialization and prompt loading into separate functions for better maintainability. - Updated Pydantic models for Jira webhook payload and analysis flags to ensure proper validation and structure. - Implemented a structured logging configuration for better traceability and debugging. - Added comprehensive unit tests for prompt loading, response validation, and webhook handling. - Established a CI/CD pipeline with GitHub Actions for automated testing and coverage reporting. - Enhanced the prompt template for LLM analysis to include specific instructions for handling escalations.
26 lines
1.0 KiB
Python
26 lines
1.0 KiB
Python
from typing import Optional, List, Union
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from pydantic import BaseModel, ConfigDict, field_validator, Field
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class JiraWebhookPayload(BaseModel):
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model_config = ConfigDict(alias_generator=lambda x: ''.join(word.capitalize() if i > 0 else word for i, word in enumerate(x.split('_'))), populate_by_name=True)
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issueKey: str
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summary: str
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description: Optional[str] = None
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comment: Optional[str] = None
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labels: Optional[Union[List[str], str]] = []
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@field_validator('labels', mode='before')
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@classmethod
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def convert_labels_to_list(cls, v):
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if isinstance(v, str):
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return [v]
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return v or []
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status: Optional[str] = None
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assignee: Optional[str] = None
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updated: Optional[str] = None
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class AnalysisFlags(BaseModel):
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hasMultipleEscalations: bool = Field(description="Is there evidence of multiple escalation attempts?")
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customerSentiment: Optional[str] = Field(description="Overall customer sentiment (e.g., 'neutral', 'frustrated', 'calm').") |