feat(pipeline): add DBGPT integration pipeline

[hjwei0305]

Summary

This PR introduces a new DBGPT integration pipeline for OpenWebUI.

The pipeline enables OpenWebUI to use a self-hosted DBGPT service as an external
AI backend, with a focus on enterprise stability, text-to-SQL workflows,
and robust error handling.

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Key Features

• DBGPT integration

  • Supports DBGPT /api/v1/chat/completions endpoint
  • Designed for self-hosted / private deployments

• Blocking-only execution model

  • Although DBGPT may stream internally, this pipeline always returns a finalized response
  • Prevents partial responses and shields frontend from backend exceptions
  • Proven to be more stable for demos and production environments

• Output normalization

  • Cleans mixed DBGPT responses (text, <think>, internal JSON, <chart-view />)
  • Preserves chart-view output while ensuring clean natural-language responses

• Exception shielding

  • Prevents backend parsing / SQL-generation errors from propagating to the OpenWebUI frontend
  • Ensures user-facing responses remain consistent even on backend failures

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Why Blocking Instead of Streaming?

In real-world enterprise scenarios (especially text-to-SQL and BI use cases),
streaming responses can expose intermediate or malformed outputs that break
frontend rendering or user experience.

This pipeline intentionally adopts a blocking execution model to:

• Improve reliability
• Simplify frontend handling
• Provide consistent, production-safe responses

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Scope & Compatibility

• Fully self-contained integration under pipelines/integrations/
• Does not modify any existing pipelines or core logic
• Follows existing pipeline structure (e.g. dify_pipeline.py)
• Optional inlet / outlet hooks preserved for extensibility

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Notes

This pipeline is intended as an integration example rather than a provider
replacement. Configuration values (API URL, app code, model name) can be adjusted
by users according to their DBGPT deployment.

Feedback and suggestions are very welcome!