src.ai.learning package#

AI Learning Components.

class src.ai.learning.ContextualLearningSystem[source]#

Bases: object

Learns patterns specific to teams, technologies, and project types.

Provides intelligent adaptation based on context-specific learnings rather than generic patterns.

__init__()[source]#

Return type:: None

async learn_team_patterns(team_id, completed_projects)[source]#

Learn team-specific patterns from completed projects.

Parameters:

team_id (str)
completed_projects (List[Dict[str, Any]])

Return type:

TeamLearnings

Returns:

Team learnings with patterns and preferences

async learn_technology_patterns(tech_stack, project_outcomes)[source]#

Learn technology-specific patterns from project outcomes.

Parameters:

tech_stack (str)
project_outcomes (List[Dict[str, Any]])

Return type:

TechnologyLearnings

Returns:

Technology learnings with patterns and multipliers

async adapt_templates_intelligently(project_context)[source]#

Adapt templates based on learned patterns.

Parameters:: project_context (Dict[str, Any])
Return type:: Dict[str, AdaptedTemplate]
Returns:: Dictionary of adapted templates

async get_contextual_recommendations(project_context, current_state)[source]#

Get contextual recommendations based on learnings.

Parameters:

project_context (Dict[str, Any])
current_state (Dict[str, Any])

Return type:

Dict[str, Any]

Returns:

Context-specific recommendations

class src.ai.learning.TeamLearnings[source]#

Bases: object

Learnings specific to a team.

team_id: str#

velocity_patterns: Dict[str, float]#

skill_strengths: Dict[str, float]#

preferred_task_types: Dict[str, float]#

collaboration_patterns: Dict[str, Any]#

quality_metrics: Dict[str, float]#

last_updated: datetime#

__init__(team_id, velocity_patterns, skill_strengths, preferred_task_types, collaboration_patterns, quality_metrics, last_updated)#

Parameters:

team_id (str)
velocity_patterns (Dict[str, float])
skill_strengths (Dict[str, float])
preferred_task_types (Dict[str, float])
collaboration_patterns (Dict[str, Any])
quality_metrics (Dict[str, float])
last_updated (datetime)

Return type:

None

class src.ai.learning.TechnologyLearnings[source]#

Bases: object

Learnings specific to technology stacks.

tech_stack: str#

typical_patterns: Dict[str, Any]#

estimation_multipliers: Dict[str, float]#

common_dependencies: List[Tuple[str, str]]#

risk_factors: Dict[str, float]#

best_practices: List[str]#

last_updated: datetime#

__init__(tech_stack, typical_patterns, estimation_multipliers, common_dependencies, risk_factors, best_practices, last_updated)#

Parameters:

tech_stack (str)
typical_patterns (Dict[str, Any])
estimation_multipliers (Dict[str, float])
common_dependencies (List[Tuple[str, str]])
risk_factors (Dict[str, float])
best_practices (List[str])
last_updated (datetime)

Return type:

None

Submodules#

src.ai.learning.contextual_learner module