Stores GenAI case analysis in JSON format in the database while preserving format on the Slack side

[mvilanova]

This pull request introduces several changes to enhance the Case model and improve the handling of GenAI signal analysis messages in the Slack plugin. The most significant updates include adding a new JSONB column to the Case model, updating the Alembic migration script, and modifying the Slack plugin to handle JSON responses for GenAI analysis.

Enhancements to Case Model:

• Added a new genai_analysis column of type JSONB to the Case model, with default values and non-null constraints (src/dispatch/case/models.py).
• Updated the CaseRead schema to include the genai_analysis field (src/dispatch/case/models.py).

Alembic Migration:

• Added a new Alembic migration script to create the genai_analysis column in the case table (src/dispatch/database/revisions/tenant/versions/2024-10-08_b057c079c2d5.py).

Slack Plugin Enhancements:

• Introduced a utility function json_to_slack_format to convert JSON dictionaries to Slack markup format (src/dispatch/plugins/dispatch_slack/case/messages.py) [1] [2].
• Updated the create_genai_signal_analysis_message function to return a tuple containing the GenAI analysis message and Slack message blocks (src/dispatch/plugins/dispatch_slack/case/messages.py) [1] [2] [3] [4] [5].
• Modified the create_threaded method to store the GenAI analysis message in the genai_analysis field of the Case model (src/dispatch/plugins/dispatch_slack/plugin.py).

These changes collectively improve the data structure and processing of GenAI analysis within the case management and Slack communication workflows.

[kevgliss]

This looks good. I think the next step could be to generate embeddings for all closed cases and use that as future context.

https://www.timescale.com/blog/postgresql-as-a-vector-database-create-store-and-query-openai-embeddings-with-pgvector/