haive.agents.common.models.task_analysis.solvability
====================================================

.. py:module:: haive.agents.common.models.task_analysis.solvability

.. autoapi-nested-parse::

   Task solvability and readiness assessment.

   This module analyzes whether tasks are currently solvable, what barriers exist,
   and what would be required to make unsolvable tasks solvable.



Classes
-------

.. autoapisummary::

   haive.agents.common.models.task_analysis.solvability.SolvabilityAssessment
   haive.agents.common.models.task_analysis.solvability.SolvabilityBarrier


Module Contents
---------------

.. py:class:: SolvabilityAssessment(/, **data)

   Bases: :py:obj:`pydantic.BaseModel`


   Comprehensive assessment of task solvability and readiness.

   Analyzes whether a task can be solved with current capabilities,
   what barriers exist, and what would be required to overcome them.

   .. attribute:: solvability_status

      Current solvability classification

   .. attribute:: is_currently_solvable

      Whether task can be solved right now

   .. attribute:: confidence_level

      Confidence in the solvability assessment

   .. attribute:: primary_barriers

      Main obstacles preventing solution

   .. attribute:: secondary_barriers

      Additional challenges that may arise

   .. attribute:: enabling_factors

      Factors that make the task more solvable

   .. attribute:: breakthrough_requirements

      What breakthroughs would be needed

   .. attribute:: estimated_time_to_solvable

      Time until task becomes solvable

   .. attribute:: alternative_approaches

      Possible alternative solution paths

   .. rubric:: Example

   .. code-block:: python

       # Simple factual lookup - highly solvable
       assessment = SolvabilityAssessment(
       solvability_status=SolvabilityStatus.READY,
       is_currently_solvable=True,
       confidence_level=0.95,
       primary_barriers=[],
       enabling_factors=["web_search", "public_databases"],
       estimated_time_to_solvable=timedelta(0)
       )

       # Cancer cure - major breakthrough required
       assessment = SolvabilityAssessment(
       solvability_status=SolvabilityStatus.THEORETICAL,
       is_currently_solvable=False,
       confidence_level=0.7,
       primary_barriers=[
       SolvabilityBarrier.KNOWLEDGE_GAP,
       SolvabilityBarrier.TECHNOLOGY_LIMITATION,
       SolvabilityBarrier.RESOURCE_CONSTRAINT
       ],
       breakthrough_requirements=[
       "fundamental_understanding_of_cancer_biology",
       "advanced_genetic_engineering_tools",
       "personalized_medicine_capabilities"
       ],
       estimated_time_to_solvable=timedelta(days=7300)  # ~20 years
       )

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:method:: estimate_breakthrough_timeline()

      Estimate timeline for required breakthroughs.

      :returns: Dictionary with breakthrough timeline analysis



   .. py:method:: generate_solvability_report()

      Generate a comprehensive solvability report.

      :returns: Formatted report string



   .. py:method:: get_addressable_barriers()

      Get barriers that could potentially be addressed.

      :returns: List of barriers that might be overcome



   .. py:method:: get_immediate_actions()

      Get recommended immediate actions to improve solvability.

      :returns: List of actionable recommendations



   .. py:method:: get_solvability_score()

      Get solvability as a normalized score (0.0-1.0).

      :returns: Normalized solvability score



   .. py:method:: has_showstopper_barriers()

      Check if task has barriers that are absolute showstoppers.

      :returns: True if task has insurmountable barriers



   .. py:method:: validate_solvability_consistency()

      Validate that solvability assessment is internally consistent.

      :returns: Self if validation passes

      :raises ValueError: If assessment has inconsistencies



   .. py:attribute:: model_config

      Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].


.. py:class:: SolvabilityBarrier

   Bases: :py:obj:`str`, :py:obj:`enum.Enum`


   Types of barriers that prevent task solvability.

   .. attribute:: KNOWLEDGE_GAP

      Missing fundamental knowledge or understanding

   .. attribute:: TECHNOLOGY_LIMITATION

      Current technology is insufficient

   .. attribute:: RESOURCE_CONSTRAINT

      Insufficient computational, financial, or material resources

   .. attribute:: THEORETICAL_IMPOSSIBILITY

      Task violates known physical or logical laws

   .. attribute:: REGULATORY_BARRIER

      Legal, ethical, or regulatory constraints

   .. attribute:: COORDINATION_COMPLEXITY

      Too complex to coordinate effectively

   .. attribute:: TIME_CONSTRAINT

      Not enough time available given current methods

   .. attribute:: DATA_UNAVAILABILITY

      Required data doesn't exist or isn't accessible

   .. attribute:: EXPERT_UNAVAILABILITY

      Required human expertise not available

   .. attribute:: INFRASTRUCTURE_LIMITATION

      Missing necessary infrastructure or systems

   .. attribute:: ETHICAL_CONCERN

      Ethical issues prevent pursuit of solution

   .. attribute:: SAFETY_RISK

      Safety risks are too high to attempt

   Initialize self.  See help(type(self)) for accurate signature.