[ai-sdk] [docs] map out `ai` semantic conventions and how it maps to openinference

Vercel AI SDK Semantic Conventions to OpenInference Semantic Conventions

The following is a map from the current Vercel AI SDK semantic OpenTelemetry semantic conventions to the OpenInference semantic conventions Vercel AI SDK Semantic Conventions

OpenInference Semantic Conventions

Vercel captures some basic info for LLM, embedding, and tool calls Additionally, they capture more specific data depending on which AI SDK function (e.g., generateText) you are calling.

Vercel Attributes	OpenInference Attributes	Additional Info
-------
LLM Spans
`ai.model.id`	`llm.model_name`
`ai.model.provider`	N/A
`ai.request.headers.*`	N/A	Can use OTEL semconv (`http.request.header.\<key\>`)
`ai.settings.\<key\>`	`llm.invocation_parameters.\<key\>`
`ai.settings.maxRetries`	`llm.invocation_parameters`
`ai.telemetry.functionId`	`name`	This is not an LLM function this is the id of the function called in application code
`ai.telemetry.metadata.*`	`metadata`
`ai.usage.completionTokens`	`llm.token_count.completion`
`ai.usage.promptTokens`	`llm.token_count.prompt`
`resource.name`	`name`	this is set in the same way as `ai.telmetry.functionId` (see above)
`ai.prompt`	`input.value`	`input.mime_type=text/plain`
`ai.result.text`	`output.value`
`ai.result.toolCalls`	`llm.output_messages.message.tool_calls`	This is on result for vercel, we could do input, output, or top level tool calls
`ai.finishReason`	N/A
`ai.settings.maxToolRoundtrips`	`llm.invocation_parameters`	This could go in invocation parameters
`operation.name`	`name` / `openinference.span.kind`	this is a combination of the SDK function called (e.g., ai.generateText) and the functionId (see above) since this fvalue is formatted like ai.\<sdk-function-name>.\<function-id> we can use this to determine the span kind as well
`ai.prompt.format`	N/A	The format of the prompt. Not sure exactly what this means maybe how template variables are specified. This comes from `ai.generateText.doGenerate` TODO look into what this value could be.
`ai.prompt.messages`	`llm.input_messages`
`ai.schema`	N/A	This is captured on the generateObject function Description: Stringified JSON schema version of the schema that was passed into the `generateObject` function
`ai.schema.name`	N/A	(see above)
`ai.schema.description`	N/A	(see above)
`ai.result.object`	`output.value`	use with `output.mime_type=application/json`
`ai.settings.mode`	N/A	This is captured on the generateObject function Description: the object generation mode
-------
Embedding Spans
`ai.model.id`	`embedding.model_name`
`ai.model.provider`	N/A
`ai.request.headers.*`	N/A	Can use OTEL semconv (`http.request.header.\<key\>`)
`ai.settings.maxRetries`	N/A
`ai.telemetry.functionId`	`name`	This is not an LLM function this is the id of the function called in application code	`ai.telemetry.metadata.*`	`metadata`
`ai.usage.tokens`	N/A	For embeddings we don't currently track tokens but do capture the vector Vercel Explanation of this attribute: the number of tokens that were used
`resource.name`	`name`	this is set in the same way as `ai.telmetry.functionId` (see above)
`ai.value`	`embedding.text`
`ai.embedding`	`embedding.vector`
`ai.values`	`embedding.embeddings.{i}.embedding.text`
`ai.embeddings`	`embedding.embeddings.{i}.embedding.vector`
-------
Tool call spans
`ai.toolCall.name`	`tool.name`
`ai.toolCall.id`	N/A	OpenInference does not currently capture this
`ai.toolCall.args`	`tool.parameters`	Although named args from vercel their description is: the parameters of the tool call
`ai.toolCall.output`	`output.value`	output.mime_type="application/json" Only available from vercel if "tool call is successful and the result is serializable"

Standardized `gen_ai` Attributes

Vercel also specifies some "standardized gen_ai attributes". Presumably those are referring to these https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/, however the links in their docs (see link above) are broken and there is a slight mismatch in the conventions. That being said, below is the mapping of the gen_ai attributes as outlined currently in the Vercel documentation (which is not exhaustive when compared to the link above) to OpenInference semantic conventions.

gen_ai Attributes	OpenInference Attributes	Additional Info
`gen_ai.request.model`	`llm.model_name`
`gen_ai.response.finish_reasons`	N/A
`gen_ai.system`	N/A	Otherwise known as the provider (e.g., openai)
`gen_ai.usage.completion_tokens`	`llm.token_count.completion`	This does not match the conventions in the spec linked above, there this is called `gen_ai.usage.completion_tokens`
`gen_ai.usage.prompt_tokens`	`llm.token_count.prompt`	This does not match the conventions in the spec linked above, there this is called `gen_ai.usage.input_tokens`

Arize-ai / openinference