[Feature] Add metrics around human vs Fin AI usage

### Is there an existing feature request for this?

- [x] I have searched the existing issues

### Describe the Feature

The current model filters to only give stats on human interactions when fivetran is also collecting bot interactions, as more companies leverage fin ai to auto-resolve issues before escalating to a human, it would be useful to measure those interactions as well

### How would you implement this feature?

making the following updates:
models/intermediate/int_intercom__conversation_part_aggregates.sql
Add differentiation for FinAI involvement in ticket handling, allowing for more granular analytics
by adding counts for total, admin parts, and bot parts
adding additional breakdowns of all the other aggregate metrics to have for both admin (human) and bot (ai)
ie first_bot_response in addition to first_admin_response

models/intermediate/int_intercom__conversation_string_aggregates.sql
add an aggregation for all types (lead, admin, bot) that touched a given conversation

models/intermediate/int_intercom__conversation_part_events.sql
add a cte for bot events following the logic from admin_events, except changing the filter to author_type='bot'

models/intercom__conversation_enhanced.sql
add in ai_resolution_stage from the conversation_history table to allow for better tracking of that
models/intercom__conversation_metrics.sql
similar to the above, but also add in the admin metadata so you can drill down by support rep vs ai

### Describe alternatives you've considered

disabling these models from package and running an overwritten version, but then I am at risk of missing schema changes as fivetran updates the connector

### Are you interested in contributing this feature?

- [x] Yes.
- [ ] Yes, but I will need assistance.
- [ ] No.

### Anything else?

_No response_