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Adding RubyLLM Support #18
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -30,6 +30,17 @@ module SpanAttributes | |
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| # Deprecated | ||
| TRACELOOP_CORRELATION_ID = "traceloop.correlation.id" | ||
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| # Gen AI | ||
| GEN_AI_REQUEST_MODEL = "gen_ai.request.model" | ||
| GEN_AI_RESPONSE_MODEL = "gen_ai.response.model" | ||
| GEN_AI_USAGE_OUTPUT_TOKENS = "gen_ai.usage.output_tokens" | ||
| GEN_AI_USAGE_INPUT_TOKENS = "gen_ai.usage.input_tokens" | ||
| GEN_AI_COMPLETIONS = "gen_ai.completion" | ||
| GEN_AI_PROMPTS = "gen_ai.prompt" | ||
| GEN_AI_SYSTEM = "gen_ai.system" | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 🧩 Analysis chain🌐 Web query:
💡 Result:
What to use instead:
Sources: 🏁 Script executed: # Check the file context around lines 31-32 and 41-42
cat -n semantic_conventions_ai/lib/opentelemetry/semantic_conventions.rb | sed -n '25,50p'Repository: traceloop/openllmetry-ruby Length of output: 1250 Mark
🤖 Prompt for AI Agents |
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| GEN_AI_PROVIDER = "gen_ai.provider.name" | ||
| GEN_AI_CONVERSATION_ID = "gen_ai.conversation.id" | ||
| end | ||
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| module LLMRequestTypeValues | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -6,16 +6,21 @@ module Traceloop | |
| module SDK | ||
| class Traceloop | ||
| def initialize | ||
| api_key = ENV["TRACELOOP_API_KEY"] | ||
| raise "TRACELOOP_API_KEY environment variable is required" if api_key.nil? || api_key.empty? | ||
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| OpenTelemetry::SDK.configure do |c| | ||
| c.add_span_processor( | ||
| OpenTelemetry::SDK::Trace::Export::SimpleSpanProcessor.new( | ||
| OpenTelemetry::SDK::Trace::Export::BatchSpanProcessor.new( | ||
| OpenTelemetry::Exporter::OTLP::Exporter.new( | ||
| endpoint: "#{ENV.fetch("TRACELOOP_BASE_URL", "https://api.traceloop.com")}/v1/traces", | ||
| headers: { "Authorization" => "Bearer #{ENV.fetch("TRACELOOP_API_KEY")}" } | ||
| headers: { | ||
| "Authorization" => "#{ENV.fetch("TRACELOOP_AUTH_SCHEME", "Bearer")} #{ENV.fetch("TRACELOOP_API_KEY")}" | ||
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| } | ||
| ) | ||
| ) | ||
| ) | ||
| puts "Traceloop exporting traces to #{ENV.fetch("TRACELOOP_BASE", "https://api.traceloop.com")}" | ||
| puts "Traceloop exporting traces to #{ENV.fetch("TRACELOOP_BASE_URL", "https://api.traceloop.com")}" | ||
| end | ||
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| @tracer = OpenTelemetry.tracer_provider.tracer("Traceloop") | ||
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@@ -41,25 +46,30 @@ def log_messages(messages) | |
| def log_prompt(system_prompt="", user_prompt) | ||
| unless system_prompt.empty? | ||
| @span.add_attributes({ | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.0.role" => "system", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.0.content" => system_prompt, | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.1.role" => "user", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.1.content" => user_prompt | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.0.role" => "system", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.0.content" => system_prompt, | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.1.role" => "user", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.1.content" => user_prompt | ||
| }) | ||
| else | ||
| @span.add_attributes({ | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.0.role" => "user", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_PROMPTS}.0.content" => user_prompt | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.0.role" => "user", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROMPTS}.0.content" => user_prompt | ||
| }) | ||
| end | ||
| end | ||
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| def log_response(response) | ||
| if response.respond_to?(:body) | ||
| log_bedrock_response(response) | ||
| # Check for RubyLLM::Message objects | ||
| elsif response.is_a?(::RubyLLM::Message) | ||
| log_ruby_llm_message(response) | ||
| elsif response.is_a?(::RubyLLM::Tool::Halt) | ||
| log_ruby_llm_halt(response) | ||
| # This is Gemini specific, see - | ||
| # https://github.com/gbaptista/gemini-ai?tab=readme-ov-file#generate_content | ||
| elsif response.has_key?("candidates") | ||
| elsif response.respond_to?(:has_key?) && response.has_key?("candidates") | ||
| log_gemini_response(response) | ||
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| else | ||
| log_openai_response(response) | ||
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@@ -73,10 +83,29 @@ def log_gemini_response(response) | |
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| @span.add_attributes({ | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.role" => "assistant", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.content" => response.dig("candidates", 0, "content", "parts", 0, "text") | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.content" => response.dig( | ||
| "candidates", 0, "content", "parts", 0, "text") | ||
| }) | ||
| end | ||
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| def log_ruby_llm_message(response) | ||
| @span.add_attributes({ | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_RESPONSE_MODEL => response.model_id, | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_USAGE_OUTPUT_TOKENS => response.output_tokens || 0, | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_USAGE_INPUT_TOKENS => response.input_tokens || 0, | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.role" => response.role.to_s, | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.content" => response.content | ||
| }) | ||
| end | ||
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Comment on lines
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🛡️ Proposed fix def log_ruby_llm_message(response)
`@span.add_attributes`({
- OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_RESPONSE_MODEL => response.model_id,
+ OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_RESPONSE_MODEL => response.model_id || `@model`,
OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_USAGE_OUTPUT_TOKENS => response.output_tokens || 0,
OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_USAGE_INPUT_TOKENS => response.input_tokens || 0,
"#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.role" => response.role.to_s,
- "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.content" => response.content
+ "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.content" => response.content.to_s
})
end🤖 Prompt for AI Agents |
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| def log_ruby_llm_halt(response) | ||
| @span.add_attributes({ | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_RESPONSE_MODEL => @model, | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.role" => "tool", | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_COMPLETIONS}.0.content" => response.content | ||
| }) | ||
| end | ||
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| def log_bedrock_response(response) | ||
| body = JSON.parse(response.body.read()) | ||
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@@ -109,25 +138,38 @@ def log_openai_response(response) | |
| }) | ||
| if response.has_key?("usage") | ||
| @span.add_attributes({ | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_TOTAL_TOKENS => response.dig("usage", "total_tokens"), | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_COMPLETION_TOKENS => response.dig("usage", "completion_tokens"), | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_PROMPT_TOKENS => response.dig("usage", "prompt_tokens"), | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_TOTAL_TOKENS => response.dig("usage", | ||
| "total_tokens"), | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_COMPLETION_TOKENS => response.dig( | ||
| "usage", "completion_tokens"), | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_USAGE_PROMPT_TOKENS => response.dig("usage", | ||
| "prompt_tokens"), | ||
| }) | ||
| end | ||
| if response.has_key?("choices") | ||
| @span.add_attributes({ | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.role" => response.dig("choices", 0, "message", "role"), | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.content" => response.dig("choices", 0, "message", "content") | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.role" => response.dig( | ||
| "choices", 0, "message", "role"), | ||
| "#{OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_COMPLETIONS}.0.content" => response.dig( | ||
| "choices", 0, "message", "content") | ||
| }) | ||
| end | ||
| end | ||
| end | ||
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| def llm_call(provider, model) | ||
| def llm_call(provider, model, conversation_id: nil) | ||
| @tracer.in_span("#{provider}.chat") do |span| | ||
| span.add_attributes({ | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::LLM_REQUEST_MODEL => model, | ||
| }) | ||
| attributes = { | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_REQUEST_MODEL => model, | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_SYSTEM => provider, | ||
| OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_PROVIDER => provider, | ||
| } | ||
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| if conversation_id | ||
| attributes[OpenTelemetry::SemanticConventionsAi::SpanAttributes::GEN_AI_CONVERSATION_ID] = conversation_id | ||
| end | ||
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| span.add_attributes(attributes) | ||
| yield Tracer.new(span, provider, model) | ||
| end | ||
| end | ||
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just replace the existing ones
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and remove references to llm semantics?