🌿 Ecological impact
If you want to track the ecological impact of your LLM Usage, you can enable it in the Otoroshi LLM Extension (it should be enabled by default)
impacts {
enabled = true
enabled = ${?CLOUD_APIM_EXTENSIONS_LLM_EXTENSION_IMPACTS_ENABLED}
embed-description-in-json = true
embed-description-in-json = ${?CLOUD_APIM_EXTENSIONS_LLM_EXTENSION_IMPACTS_EMBED_DESCRIPTION_IN_JSON}
electricity-mix = "WOR"
electricity-mix = ${?CLOUD_APIM_EXTENSIONS_LLM_EXTENSION_IMPACTS_ELECTRICITY_MIX}
embed-impacts-in-responses = false
embed-impacts-in-responses = ${?CLOUD_APIM_EXTENSIONS_LLM_EXTENSION_IMPACTS_EMBED_IMPACTS_IN_RESPONSES}
}
Once it's enabled, audit events of kind LLMUsageAudit will have an impacts.
You can also embed the impacts value in your LLM responses using the impacts.embed-impacts-in-responses config.
Please remember that the impacts value is just an estimate of the real ecological impact of your LLM usage.
The ecological impact computation is based on project EcoLogits and only supports right now the following providers
- Mistral
- Gemini
- Anthropic
- OpenAI
- Cohere
- HuggingFace
but if you're okay with approximations, you can set some metadata on your providers to use supported providers / models
eco-impacts-electricity-mix-zone: the country where the model is hostedeco-impacts-provider: the provider used for eco impacts computationeco-impacts-model: the model used for eco impacts computation
Example of ecological impact embed in responses
NOTE: you can embed costs tracking informations by using embed_impacts=true query param
$ curl --request POST \
--url 'http://test.oto.tools:8080/v1/chat/completions?embed_impacts=true' \
--header 'content-type: application/json' \
--data '{
"messages": [
{
"role": "user",
"content": "tell me a joke"
}
]
}'
{
"id": "chatcmpl-POPo2920QC8UdFT6MEF8MnnMBOGXDNdg",
"object": "chat.completion",
"created": 1743161221,
"model": "gpt-4o-mini",
"system_fingerprint": "fp-8hSBjQkQnl3InFEJ88ckzfm3JUtNC2bH",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Why did the scarecrow win an award?\n\nBecause he was outstanding in his field!"
},
"logprobs": null,
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 11,
"completion_tokens": 18,
"total_tokens": 29,
"completion_tokens_details": {
"reasoning_tokens": 0
}
},
"impacts": {
"energy": {
"value": {
"min": 0.000045859386,
"max": 0.000140325354,
"avg": 0.00009309237000000001
},
"unit": "kWh"
},
"gwp": {
"value": {
"min": 0.00002877619380504681,
"max": 0.00008550637626962295,
"avg": 0.00005714128503733488
},
"unit": "kgCO2eq"
},
"adpe": {
"value": {
"min": 1.183887945516329e-10,
"max": 1.8973743554267144e-10,
"avg": 1.5406311504715217e-10
},
"unit": "kgSbeq"
},
"pe": {
"value": {
"min": 0.00047959646949585386,
"max": 0.001435187811341041,
"avg": 0.0009573921404184475
},
"unit": "MJ"
},
"usage": {
"energy": {
"value": {
"min": 0.000045859386,
"max": 0.000140325354,
"avg": 0.00009309237000000001
},
"unit": "kWh"
},
"gwp": {
"value": {
"min": 0.000027078958526507997,
"max": 0.00008285903437921199,
"avg": 0.000054968996452859996
},
"unit": "kgCO2eq"
},
"adpe": {
"value": {
"min": 3.3830835927287995e-12,
"max": 1.0351913624863199e-11,
"avg": 6.8674986087959995e-12
},
"unit": "kgSbeq"
},
"pe": {
"value": {
"min": 0.000458043547368,
"max": 0.001401569635752,
"avg": 0.00092980659156
},
"unit": "MJ"
}
},
"embodied": {
"gwp": {
"value": {
"min": 0.0000016972352785388126,
"max": 0.000002647341890410959,
"avg": 0.0000021722885844748857
},
"unit": "kgCO2eq"
},
"adpe": {
"value": {
"min": 1.150057109589041e-10,
"max": 1.7938552191780823e-10,
"avg": 1.4719561643835617e-10
},
"unit": "kgSbeq"
},
"pe": {
"value": {
"min": 0.00002155292212785388,
"max": 0.0000336181755890411,
"avg": 0.00002758554885844749
},
"unit": "MJ"
}
},
"warnings": null
}
}
Example of LLMUsageAudit event with ecological impact
{
"@id" : "1905575568334651655",
"@timestamp" : 1743159594030,
"@type" : "AuditEvent",
"@product" : "otoroshi",
"@serviceId" : "",
"@service" : "Otoroshi",
"@env" : "dev",
"audit" : "LLMUsageAudit",
"provider_kind" : "openai",
"provider" : "provider_10bbc76d-7cd8-4cb7-b760-61e749a1b691",
"duration" : 497,
"model" : "gpt-4o-mini",
"rate_limit" : {
"requests_limit" : 10000,
"requests_remaining" : 9998,
"tokens_limit" : 200000,
"tokens_remaining" : 199993
},
"usage" : {
"prompt_tokens" : 11,
"generation_tokens" : 18,
"reasoning_tokens" : 0
},
"error" : null,
"consumed_using" : "chat/completion/blocking",
"user" : null,
"apikey" : null,
"route" : {
"_loc" : {
"tenant" : "default",
"teams" : [ "default" ]
},
"id" : "route_e4a9d6cb3-d859-4203-a860-8d1dd6d09557",
"name" : "test",
"description" : "A new route",
"tags" : [ ],
"metadata" : {
"created_at" : "2025-03-28T10:10:19.448+01:00",
"updated_at" : "2025-03-28T10:48:48.218+01:00"
},
"enabled" : true,
"debug_flow" : false,
"export_reporting" : false,
"capture" : false,
"groups" : [ "default" ],
"bound_listeners" : [ ],
"frontend" : {
"domains" : [ "test.oto.tools" ],
"strip_path" : true,
"exact" : false,
"headers" : { },
"query" : { },
"methods" : [ ]
},
"backend" : {
"targets" : [ {
"id" : "target_1",
"hostname" : "request.otoroshi.io",
"port" : 443,
"tls" : true,
"weight" : 1,
"backup" : false,
"predicate" : {
"type" : "AlwaysMatch"
},
"protocol" : "HTTP/1.1",
"ip_address" : null,
"tls_config" : {
"certs" : [ ],
"trusted_certs" : [ ],
"enabled" : false,
"loose" : false,
"trust_all" : false
}
} ],
"root" : "/",
"rewrite" : false,
"load_balancing" : {
"type" : "RoundRobin"
},
"client" : {
"retries" : 1,
"max_errors" : 20,
"retry_initial_delay" : 50,
"backoff_factor" : 2,
"call_timeout" : 30000,
"call_and_stream_timeout" : 120000,
"connection_timeout" : 10000,
"idle_timeout" : 60000,
"global_timeout" : 30000,
"sample_interval" : 2000,
"proxy" : { },
"custom_timeouts" : [ ],
"cache_connection_settings" : {
"enabled" : false,
"queue_size" : 2048
}
},
"health_check" : {
"enabled" : false,
"url" : "",
"timeout" : 5000,
"healthyStatuses" : [ ],
"unhealthyStatuses" : [ ]
}
},
"backend_ref" : null,
"plugins" : [ {
"enabled" : true,
"debug" : false,
"plugin" : "cp:otoroshi.next.plugins.OverrideHost",
"include" : [ ],
"exclude" : [ ],
"config" : { },
"bound_listeners" : [ ],
"plugin_index" : {
"transform_request" : 0
}
}, {
"enabled" : true,
"debug" : false,
"plugin" : "cp:otoroshi_plugins.com.cloud.apim.otoroshi.extensions.aigateway.plugins.OpenAiCompatProxy",
"include" : [ ],
"exclude" : [ ],
"config" : {
"refs" : [ "provider_10bbc76d-7cd8-4cb7-b760-61e749a1b691" ]
},
"bound_listeners" : [ ],
"plugin_index" : { }
} ]
},
"input_prompt" : [ {
"role" : "user",
"content" : "tell me a joke"
} ],
"output" : {
"generations" : [ {
"message" : {
"role" : "assistant",
"content" : "Why did the scarecrow win an award?\n\nBecause he was outstanding in his field!"
}
} ],
"metadata" : {
"rate_limit" : {
"requests_limit" : 10000,
"requests_remaining" : 9998,
"tokens_limit" : 200000,
"tokens_remaining" : 199993
},
"usage" : {
"prompt_tokens" : 11,
"generation_tokens" : 18,
"reasoning_tokens" : 0
}
}
},
"provider_details" : {
"_loc" : {
"tenant" : "default",
"teams" : [ "default" ]
},
"id" : "provider_10bbc76d-7cd8-4cb7-b760-61e749a1b691",
"name" : "OpenAI",
"description" : "An OpenAI LLM api provider",
"metadata" : {
"created_at" : "2025-03-28T10:10:51.558+01:00"
},
"tags" : [ ],
"provider" : "openai",
"connection" : {
"base_url" : "https://api.openai.com/v1",
"token" : "xxx",
"timeout" : 30000
},
"options" : {
"model" : "gpt-4o-mini",
"frequency_penalty" : null,
"logit_bias" : null,
"logprobs" : null,
"top_logprobs" : null,
"max_tokens" : null,
"n" : 1,
"presence_penalty" : null,
"response_format" : null,
"seed" : null,
"stop" : null,
"stream" : false,
"temperature" : 1,
"top_p" : 1,
"tools" : null,
"tool_choice" : null,
"user" : null,
"wasm_tools" : [ ],
"mcp_connectors" : [ ],
"allow_config_override" : true
},
"provider_fallback" : null,
"context" : {
"default" : null,
"contexts" : [ ]
},
"models" : {
"include" : [ ],
"exclude" : [ ]
},
"guardrails" : [ ],
"guardrails_fail_on_deny" : false,
"cache" : {
"strategy" : "none",
"ttl" : 300000,
"score" : 0.8
}
},
"impacts" : {
"energy" : {
"value" : {
"min" : 0.000045859386,
"max" : 0.000140325354,
"avg" : 0.00009309237000000001
},
"unit" : "kWh",
"description" : "Energy: related to the final electricity consumption in kWh"
},
"gwp" : {
"value" : {
"min" : 0.00002877619380504681,
"max" : 0.00008550637626962295,
"avg" : 0.00005714128503733488
},
"unit" : "kgCO2eq",
"description" : "Global Warming Potential (GWP): related to climate change, commonly known as GHG emissions in kgCO2eq"
},
"adpe" : {
"value" : {
"min" : 1.183887945516329E-10,
"max" : 1.8973743554267144E-10,
"avg" : 1.5406311504715217E-10
},
"unit" : "kgSbeq",
"description" : "Abiotic Depletion Potential for Elements (ADPe): related to the depletion of minerals and metals in kgSbeq"
},
"pe" : {
"value" : {
"min" : 0.00047959646949585386,
"max" : 0.001435187811341041,
"avg" : 0.0009573921404184475
},
"unit" : "MJ",
"description" : "Primary Energy (PE): related to the energy consumed from primary sources like oil, gas or coal in MJ"
},
"usage" : {
"energy" : {
"value" : {
"min" : 0.000045859386,
"max" : 0.000140325354,
"avg" : 0.00009309237000000001
},
"unit" : "kWh",
"description" : "Energy: related to the final electricity consumption in kWh"
},
"gwp" : {
"value" : {
"min" : 0.000027078958526507997,
"max" : 0.00008285903437921199,
"avg" : 0.000054968996452859996
},
"unit" : "kgCO2eq",
"description" : "Global Warming Potential (GWP): related to climate change, commonly known as GHG emissions in kgCO2eq"
},
"adpe" : {
"value" : {
"min" : 3.3830835927287995E-12,
"max" : 1.0351913624863199E-11,
"avg" : 6.8674986087959995E-12
},
"unit" : "kgSbeq",
"description" : "Abiotic Depletion Potential for Elements (ADPe): related to the depletion of minerals and metals in kgSbeq"
},
"pe" : {
"value" : {
"min" : 0.000458043547368,
"max" : 0.001401569635752,
"avg" : 0.00092980659156
},
"unit" : "MJ",
"description" : "Primary Energy (PE): related to the energy consumed from primary sources like oil, gas or coal in MJ"
},
"description" : "related to the impacts of the energy consumption during model execution"
},
"embodied" : {
"gwp" : {
"value" : {
"min" : 0.0000016972352785388126,
"max" : 0.000002647341890410959,
"avg" : 0.0000021722885844748857
},
"unit" : "kgCO2eq",
"description" : "Global Warming Potential (GWP): related to climate change, commonly known as GHG emissions in kgCO2eq"
},
"adpe" : {
"value" : {
"min" : 1.150057109589041E-10,
"max" : 1.7938552191780823E-10,
"avg" : 1.4719561643835617E-10
},
"unit" : "kgSbeq",
"description" : "Abiotic Depletion Potential for Elements (ADPe): related to the depletion of minerals and metals in kgSbeq"
},
"pe" : {
"value" : {
"min" : 0.00002155292212785388,
"max" : 0.0000336181755890411,
"avg" : 0.00002758554885844749
},
"unit" : "MJ",
"description" : "Primary Energy (PE): related to the energy consumed from primary sources like oil, gas or coal in MJ"
},
"description" : "related to resource extraction, manufacturing and transportation of the hardware"
},
"warnings" : null
}
}
Dashboard example
