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platform-pipeline-provider

platform-pipeline-provider

Develop and debug LangBot platform adapters, HTTP Bot callbacks, message aggregation, pipeline stages, provider runners, model managers, local agent tools, and tool-loading workflows.

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Documentation de la Skill

GitHub

name: platform-pipeline-provider description: "Develop and debug LangBot platform adapters, HTTP Bot callbacks, message aggregation, pipeline stages, provider runners, model managers, local agent tools, and tool-loading workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Platform, Pipeline, and Provider

Use this sub-skill for message flow, IM platform adapters, HTTP Bot and WebSocket chat behavior, pipeline stages, providers/runners, model manager, local agent, and tool manager issues.

Read First

Common Workflows

Trace one message

  1. Platform adapter converts native event into shared message/event entities.
  2. RuntimeBot applies routing rules and pushes messages to aggregation.
  3. MessageAggregator collapses N-to-1 bursts by session.
  4. Controller schedules Query work subject to concurrency.
  5. RuntimePipeline executes configured stages.
  6. Chat stage invokes providers/tools/plugins and records session/history.
  7. Output stages send responses through the adapter.

Add or change an adapter

Keep vendor translation inside the adapter. Do not put LLM provider logic or pipeline business rules inside platform code. Add or update manifests, config schemas, icons/assets, i18n strings, docs, and focused adapter tests.

Debug provider/tool behavior

Start with fake provider/tool tests before using real API keys. If plugin, Box, native, or stdio MCP tools are involved, route deep runtime details to plugin-box-skills after confirming the provider/tool manager boundary.

Bundled Helper

Use scripts/http_bot_hmac_helper.py for self-contained HTTP Bot HMAC signing, verification, payload building, and optional signed POSTs. It adapts the public example client into a skill-owned helper and does not depend on the original checkout.

Focused Checks

python scripts/select_langbot_checks.py pipeline
uv run pytest tests/smoke/test_fake_message_flow.py -q --tb=short
uv run pytest tests/integration/pipeline/test_full_flow.py -q --tb=short
uv run pytest tests/unit_tests/platform/test_http_bot_tenancy.py -q --tb=short
uv run pytest tests/unit_tests/provider/test_tool_manager.py -q --tb=short
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