wehub-resource-sync
77 lines
2.4 KiB
Lua
77 lines
2.4 KiB
Lua
local typedefs = require("kong.db.schema.typedefs")
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local llm = require("kong.llm")
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return {
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name = "ai-request-transformer",
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fields = {
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{ protocols = typedefs.protocols_http },
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{ consumer = typedefs.no_consumer },
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{ config = {
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type = "record",
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fields = {
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{ prompt = {
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description = "Use this prompt to tune the LLM system/assistant message for the incoming "
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.. "proxy request (from the client), and what you are expecting in return.",
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type = "string",
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required = true,
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}},
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{ transformation_extract_pattern = {
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description = "Defines the regular expression that must match to indicate a successful AI transformation "
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.. "at the request phase. The first match will be set as the outgoing body. "
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.. "If the AI service's response doesn't match this pattern, it is marked as a failure.",
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type = "string",
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required = false,
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}},
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{ http_timeout = {
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description = "Timeout in milliseconds for the AI upstream service.",
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type = "integer",
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required = true,
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default = 60000,
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}},
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{ https_verify = {
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description = "Verify the TLS certificate of the AI upstream service.",
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type = "boolean",
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required = true,
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default = true,
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}},
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{
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max_request_body_size = {
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type = "integer",
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default = 8 * 1024,
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gt = 0,
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description = "max allowed body size allowed to be introspected",}
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},
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-- from forward-proxy
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{ http_proxy_host = typedefs.host },
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{ http_proxy_port = typedefs.port },
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{ https_proxy_host = typedefs.host },
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{ https_proxy_port = typedefs.port },
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{ llm = llm.config_schema },
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},
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}},
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},
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entity_checks = {
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{
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conditional = {
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if_field = "config.llm.route_type",
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if_match = {
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not_one_of = {
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"llm/v1/chat",
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}
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},
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then_field = "config.llm.route_type",
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then_match = { eq = "llm/v1/chat" },
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then_err = "'config.llm.route_type' must be 'llm/v1/chat' for AI transformer plugins",
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},
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},
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{ mutually_required = { "config.http_proxy_host", "config.http_proxy_port" } },
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{ mutually_required = { "config.https_proxy_host", "config.https_proxy_port" } },
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},
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}
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