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Merge pull request lightspeed-core#919 from tisnik/updated-openapi-spec
Updated OpenAPI specification
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docs/openapi.json

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"get_metrics",
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"get_config",
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"info",
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"model_override"
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"model_override",
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"rlsapi_v1_infer"
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],
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"title": "Action",
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"description": "Available actions in the system.\n\nNote: this is not a real model, just an enumeration of all action names."
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],
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"title": "Name space",
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"description": "Database namespace",
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"default": "lightspeed-stack"
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"default": "public"
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},
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"ssl_mode": {
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"type": "string",
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"application/json",
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"text/plain"
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]
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},
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"vector_store_ids": {
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"anyOf": [
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{
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"items": {
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"type": "string"
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},
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"type": "array"
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},
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{
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"type": "null"
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}
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],
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"title": "Vector Store Ids",
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"description": "Optional list of specific vector store IDs to query for RAG. If not provided, all available vector stores will be queried.",
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"examples": [
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"ocp_docs",
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"knowledge_base",
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"vector_db_1"
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]
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}
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},
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"additionalProperties": false,
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"query"
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],
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"title": "QueryRequest",
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"description": "Model representing a request for the LLM (Language Model).\n\nAttributes:\n query: The query string.\n conversation_id: The optional conversation ID (UUID).\n provider: The optional provider.\n model: The optional model.\n system_prompt: The optional system prompt.\n attachments: The optional attachments.\n no_tools: Whether to bypass all tools and MCP servers (default: False).\n generate_topic_summary: Whether to generate topic summary for new conversations.\n media_type: The optional media type for response format (application/json or text/plain).\n\nExample:\n ```python\n query_request = QueryRequest(query=\"Tell me about Kubernetes\")\n ```",
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"description": "Model representing a request for the LLM (Language Model).\n\nAttributes:\n query: The query string.\n conversation_id: The optional conversation ID (UUID).\n provider: The optional provider.\n model: The optional model.\n system_prompt: The optional system prompt.\n attachments: The optional attachments.\n no_tools: Whether to bypass all tools and MCP servers (default: False).\n generate_topic_summary: Whether to generate topic summary for new conversations.\n media_type: The optional media type for response format (application/json or text/plain).\n vector_store_ids: The optional list of specific vector store IDs to query for RAG.\n\nExample:\n ```python\n query_request = QueryRequest(query=\"Tell me about Kubernetes\")\n ```",
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"examples": [
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{
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"attachments": [
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"no_tools": false,
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"provider": "openai",
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"query": "write a deployment yaml for the mongodb image",
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"system_prompt": "You are a helpful assistant"
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"system_prompt": "You are a helpful assistant",
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"vector_store_ids": [
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"ocp_docs",
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"knowledge_base"
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]
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}
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]
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},

docs/openapi.md

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no_tools: Whether to bypass all tools and MCP servers (default: False).
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generate_topic_summary: Whether to generate topic summary for new conversations.
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media_type: The optional media type for response format (application/json or text/plain).
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vector_store_ids: The optional list of specific vector store IDs to query for RAG.
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Example:
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```python
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| no_tools | | Whether to bypass all tools and MCP servers |
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| generate_topic_summary | | Whether to generate topic summary for new conversations |
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| media_type | | Media type for the response format |
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| vector_store_ids | | Optional list of specific vector store IDs to query for RAG. If not provided, all available vector stores will be queried. |
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## QueryResponse

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