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FEATURE: optionally support OpenAI responses API (#1423)
OpenAI ship a new API for completions called "Responses API" Certain models (o3-pro) require this API. Additionally certain features are only made available to the new API. This allow enabling it per LLM. see: https://platform.openai.com/docs/api-reference/responses
This commit is contained in:
Sam
GitHub
parent
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commit
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@ -52,6 +52,7 @@ class LlmModel < ActiveRecord::Base
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disable_temperature: :checkbox,
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disable_top_p: :checkbox,
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disable_streaming: :checkbox,
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enable_responses_api: :checkbox,
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reasoning_effort: {
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type: :enum,
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values: %w[default low medium high],
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@ -579,6 +579,7 @@ en:
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reasoning_tokens: "Number of tokens used for reasoning"
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disable_temperature: "Disable temperature (some thinking models don't support temperature)"
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disable_top_p: "Disable top P (some thinking models don't support top P)"
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enable_responses_api: "Enable responses API (required on certain OpenAI models)"
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related_topics:
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title: "Related topics"
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@ -20,12 +20,19 @@ module DiscourseAi
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def embed_user_ids?
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return @embed_user_ids if defined?(@embed_user_ids)
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@embed_user_ids =
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@embed_user_ids = true if responses_api?
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@embed_user_ids ||=
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prompt.messages.any? do |m|
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m[:id] && m[:type] == :user && !m[:id].to_s.match?(VALID_ID_REGEX)
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end
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end
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def responses_api?
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return @responses_api if defined?(@responses_api)
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@responses_api = llm_model.lookup_custom_param("enable_responses_api")
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end
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def max_prompt_tokens
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# provide a buffer of 120 tokens - our function counting is not
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# 100% accurate and getting numbers to align exactly is very hard
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@ -51,7 +58,11 @@ module DiscourseAi
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if disable_native_tools?
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super
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else
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@tools_dialect ||= DiscourseAi::Completions::Dialects::OpenAiTools.new(prompt.tools)
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@tools_dialect ||=
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DiscourseAi::Completions::Dialects::OpenAiTools.new(
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prompt.tools,
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responses_api: responses_api?,
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)
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end
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end
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@ -120,7 +131,7 @@ module DiscourseAi
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to_encoded_content_array(
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content: content_array.flatten,
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image_encoder: ->(details) { image_node(details) },
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text_encoder: ->(text) { { type: "text", text: text } },
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text_encoder: ->(text) { text_node(text) },
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allow_vision: vision_support?,
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)
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@ -136,13 +147,21 @@ module DiscourseAi
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end
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end
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def text_node(text)
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if responses_api?
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{ type: "input_text", text: text }
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else
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{ type: "text", text: text }
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end
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end
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def image_node(details)
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{
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type: "image_url",
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image_url: {
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url: "data:#{details[:mime_type]};base64,#{details[:base64]}",
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},
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}
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encoded_image = "data:#{details[:mime_type]};base64,#{details[:base64]}"
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if responses_api?
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{ type: "input_image", image_url: encoded_image }
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else
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{ type: "image_url", image_url: { url: encoded_image } }
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end
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end
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def per_message_overhead
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@ -4,20 +4,32 @@ module DiscourseAi
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module Completions
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module Dialects
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class OpenAiTools
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def initialize(tools)
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def initialize(tools, responses_api: false)
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@responses_api = responses_api
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@raw_tools = tools
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end
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def translated_tools
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raw_tools.map do |tool|
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{
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type: "function",
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function: {
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if @responses_api
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raw_tools.map do |tool|
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{
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type: "function",
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name: tool.name,
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description: tool.description,
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parameters: tool.parameters_json_schema,
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},
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}
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}
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end
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else
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raw_tools.map do |tool|
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{
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type: "function",
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function: {
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name: tool.name,
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description: tool.description,
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parameters: tool.parameters_json_schema,
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},
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}
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end
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end
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end
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@ -30,20 +42,37 @@ module DiscourseAi
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call_details[:arguments] = call_details[:arguments].to_json
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call_details[:name] = raw_message[:name]
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{
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role: "assistant",
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content: nil,
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tool_calls: [{ type: "function", function: call_details, id: raw_message[:id] }],
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}
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if @responses_api
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{
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type: "function_call",
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call_id: raw_message[:id],
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name: call_details[:name],
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arguments: call_details[:arguments],
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}
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else
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{
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role: "assistant",
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content: nil,
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tool_calls: [{ type: "function", function: call_details, id: raw_message[:id] }],
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}
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end
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end
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def from_raw_tool(raw_message)
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{
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role: "tool",
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tool_call_id: raw_message[:id],
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content: raw_message[:content],
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name: raw_message[:name],
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}
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if @responses_api
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{
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type: "function_call_output",
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call_id: raw_message[:id],
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output: raw_message[:content],
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}
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else
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{
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role: "tool",
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tool_call_id: raw_message[:id],
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content: raw_message[:content],
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name: raw_message[:name],
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}
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end
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end
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private
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@ -89,6 +89,7 @@ module DiscourseAi
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# We'll fallback to guess this using the tokenizer.
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payload[:stream_options] = { include_usage: true } if llm_model.provider == "open_ai"
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end
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if !xml_tools_enabled?
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if dialect.tools.present?
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payload[:tools] = dialect.tools
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@ -96,19 +97,39 @@ module DiscourseAi
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if dialect.tool_choice == :none
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payload[:tool_choice] = "none"
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else
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payload[:tool_choice] = {
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type: "function",
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function: {
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name: dialect.tool_choice,
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},
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}
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if responses_api?
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payload[:tool_choice] = { type: "function", name: dialect.tool_choice }
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else
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payload[:tool_choice] = {
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type: "function",
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function: {
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name: dialect.tool_choice,
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},
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}
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end
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end
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end
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end
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end
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convert_payload_to_responses_api!(payload) if responses_api?
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payload
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end
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def responses_api?
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return @responses_api if defined?(@responses_api)
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@responses_api = llm_model.lookup_custom_param("enable_responses_api")
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end
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def convert_payload_to_responses_api!(payload)
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payload[:input] = payload.delete(:messages)
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completion_tokens = payload.delete(:max_completion_tokens) || payload.delete(:max_tokens)
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payload[:max_output_tokens] = completion_tokens if completion_tokens
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# not supported in responses api
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payload.delete(:stream_options)
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end
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def prepare_request(payload)
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headers = { "Content-Type" => "application/json" }
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api_key = llm_model.api_key
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@ -159,7 +180,12 @@ module DiscourseAi
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private
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def processor
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@processor ||= OpenAiMessageProcessor.new(partial_tool_calls: partial_tool_calls)
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@processor ||=
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if responses_api?
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OpenAiResponsesMessageProcessor.new(partial_tool_calls: partial_tool_calls)
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else
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OpenAiMessageProcessor.new(partial_tool_calls: partial_tool_calls)
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end
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end
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end
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end
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160
lib/completions/open_ai_responses_message_processor.rb
Normal file
160
lib/completions/open_ai_responses_message_processor.rb
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@ -0,0 +1,160 @@
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# frozen_string_literal: true
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module DiscourseAi::Completions
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class OpenAiResponsesMessageProcessor
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attr_reader :prompt_tokens, :completion_tokens, :cached_tokens
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def initialize(partial_tool_calls: false)
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@tool = nil # currently streaming ToolCall
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@tool_arguments = +""
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@prompt_tokens = nil
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@completion_tokens = nil
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@cached_tokens = nil
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@partial_tool_calls = partial_tool_calls
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@streaming_parser = nil # JsonStreamingTracker, if used
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@has_new_data = false
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end
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# @param json [Hash] full JSON response from responses.create / retrieve
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# @return [Array<String,ToolCall>] pieces in the order they were produced
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def process_message(json)
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result = []
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(json[:output] || []).each do |item|
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type = item[:type]
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case type
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when "function_call"
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result << build_tool_call_from_item(item)
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when "message"
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text = extract_text(item)
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result << text if text
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end
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end
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update_usage(json)
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result
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end
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# @param json [Hash] a single streamed event, already parsed from ND-JSON
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# @return [String, ToolCall, nil] only when a complete chunk is ready
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def process_streamed_message(json)
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rval = nil
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event_type = json[:type] || json["type"]
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case event_type
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when "response.output_text.delta"
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delta = json[:delta] || json["delta"]
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rval = delta if !delta.empty?
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when "response.output_item.added"
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item = json[:item]
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if item && item[:type] == "function_call"
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handle_tool_stream(:start, item) { |finished| rval = finished }
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end
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when "response.function_call_arguments.delta"
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delta = json[:delta]
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handle_tool_stream(:progress, delta) { |finished| rval = finished } if delta
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when "response.output_item.done"
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item = json[:item]
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if item && item[:type] == "function_call"
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handle_tool_stream(:done, item) { |finished| rval = finished }
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end
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end
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update_usage(json)
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rval
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end
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# Called by JsonStreamingTracker when partial JSON arguments are parsed
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def notify_progress(key, value)
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if @tool
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@tool.partial = true
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@tool.parameters[key.to_sym] = value
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@has_new_data = true
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end
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end
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def current_tool_progress
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if @has_new_data
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@has_new_data = false
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@tool
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end
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end
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def finish
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rval = []
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if @tool
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process_arguments
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rval << @tool
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@tool = nil
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end
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rval
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end
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private
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def extract_text(message_item)
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(message_item[:content] || message_item["content"] || [])
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.filter { |c| (c[:type] || c["type"]) == "output_text" }
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.map { |c| c[:text] || c["text"] }
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.join
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end
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def build_tool_call_from_item(item)
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id = item[:call_id]
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name = item[:name]
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arguments = item[:arguments] || ""
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params = arguments.empty? ? {} : JSON.parse(arguments, symbolize_names: true)
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ToolCall.new(id: id, name: name, parameters: params)
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end
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def handle_tool_stream(event_type, json)
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if event_type == :start
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start_tool_stream(json)
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elsif event_type == :progress
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@streaming_parser << json if @streaming_parser
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yield current_tool_progress
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elsif event_type == :done
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@tool_arguments << json[:arguments].to_s
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process_arguments
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finished = @tool
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@tool = nil
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yield finished
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end
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end
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def start_tool_stream(data)
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# important note... streaming API has both id and call_id
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# both seem to work as identifiers, api examples seem to favor call_id
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# so I am using it here
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id = data[:call_id]
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name = data[:name]
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@tool_arguments = +""
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@tool = ToolCall.new(id: id, name: name)
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@streaming_parser = JsonStreamingTracker.new(self) if @partial_tool_calls
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end
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# Parse accumulated @tool_arguments once we have a complete JSON blob
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def process_arguments
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return if @tool_arguments.to_s.empty?
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parsed = JSON.parse(@tool_arguments, symbolize_names: true)
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@tool.parameters = parsed
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@tool.partial = false
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@tool_arguments = nil
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rescue JSON::ParserError
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# leave arguments empty; caller can decide how to handle
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end
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def update_usage(json)
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usage = json.dig(:response, :usage)
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return if !usage
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cached_tokens = usage.dig(:input_tokens_details, :cached_tokens).to_i
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@prompt_tokens ||= usage[:input_tokens] - cached_tokens
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@completion_tokens ||= usage[:output_tokens]
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@cached_tokens ||= cached_tokens
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end
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end
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end
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240
spec/lib/completions/endpoints/open_ai_responses_api_spec.rb
Normal file
240
spec/lib/completions/endpoints/open_ai_responses_api_spec.rb
Normal file
@ -0,0 +1,240 @@
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# frozen_string_literal: true
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RSpec.describe DiscourseAi::Completions::Endpoints::OpenAi do
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subject(:endpoint) { described_class.new(model) }
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fab!(:model) do
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Fabricate(
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:llm_model,
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provider: "open_ai",
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url: "https://api.openai.com/v1/responses",
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provider_params: {
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enable_responses_api: true,
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},
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)
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end
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let(:prompt_with_tools) do
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prompt = DiscourseAi::Completions::Prompt.new("echo: Hello")
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prompt.tools = [
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DiscourseAi::Completions::ToolDefinition.new(
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name: "echo",
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description: "Used for testing of llms, will echo the param given to it",
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parameters: [
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DiscourseAi::Completions::ToolDefinition::ParameterDefinition.from_hash(
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{ name: "string", description: "string to echo", type: :string, required: true },
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),
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],
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),
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]
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prompt
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end
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it "can perform simple streaming completion" do
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response_payload = <<~TEXT
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event: response.created
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data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_6848d84bee44819d98e5f4f5103562090333bc932679b022","object":"response","created_at":1749604427,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
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event: response.in_progress
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data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_6848d84bee44819d98e5f4f5103562090333bc932679b022","object":"response","created_at":1749604427,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
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event: response.output_item.added
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data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","type":"message","status":"in_progress","content":[],"role":"assistant"}}
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event: response.content_part.added
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data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":""}}
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event: response.output_text.delta
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data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"delta":"Hello"}
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event: response.output_text.delta
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data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"delta":" "}
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event: response.output_text.delta
|
||||
data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"delta":"World"}
|
||||
|
||||
event: response.output_text.done
|
||||
data: {"type":"response.output_text.done","sequence_number":5,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"text":"Hello World"}
|
||||
|
||||
event: response.content_part.done
|
||||
data: {"type":"response.content_part.done","sequence_number":6,"item_id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":"Hello World"}}
|
||||
|
||||
event: response.output_item.done
|
||||
data: {"type":"response.output_item.done","sequence_number":7,"output_index":0,"item":{"id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"Hello World"}],"role":"assistant"}}
|
||||
|
||||
event: response.completed
|
||||
data: {"type":"response.completed","sequence_number":8,"response":{"id":"resp_6848d84bee44819d98e5f4f5103562090333bc932679b022","object":"response","created_at":1749604427,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[{"id":"msg_6848d84c3bc8819dace0eadec6e205090333bc932679b022","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"Hello"}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":35,"input_tokens_details":{"cached_tokens":5},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":37},"user":null,"metadata":{}}}
|
||||
TEXT
|
||||
|
||||
partials = []
|
||||
|
||||
stub_request(:post, "https://api.openai.com/v1/responses").to_return(
|
||||
status: 200,
|
||||
body: response_payload,
|
||||
)
|
||||
|
||||
model
|
||||
.to_llm
|
||||
.generate("Say: Hello World", user: Discourse.system_user) { |partial| partials << partial }
|
||||
|
||||
expect(partials).to eq(["Hello", " ", "World"])
|
||||
|
||||
log = AiApiAuditLog.last
|
||||
|
||||
# note: our report counts cache and request tokens separately see: DiscourseAi::Completions::Report
|
||||
expect(log).to be_present
|
||||
expect(log.request_tokens).to eq(30)
|
||||
expect(log.response_tokens).to eq(9)
|
||||
expect(log.cached_tokens).to eq(5)
|
||||
end
|
||||
|
||||
it "can properly stream tool calls" do
|
||||
response_payload = <<~TEXT
|
||||
event: response.created
|
||||
data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_684910c81eec81a3a9222aa336d9fcf202d35c1819a50f63","object":"response","created_at":1749618888,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":{"type":"function","name":"echo"},"tools":[{"type":"function","description":"Used for testing of llms, will echo the param given to it","name":"echo","parameters":{"type":"object","properties":{"string":{"type":"string","description":"string to echo"}},"required":["string"]},"strict":true}],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
|
||||
|
||||
event: response.in_progress
|
||||
data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_684910c81eec81a3a9222aa336d9fcf202d35c1819a50f63","object":"response","created_at":1749618888,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":{"type":"function","name":"echo"},"tools":[{"type":"function","description":"Used for testing of llms, will echo the param given to it","name":"echo","parameters":{"type":"object","properties":{"string":{"type":"string","description":"string to echo"}},"required":["string"]},"strict":true}],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
|
||||
|
||||
event: response.output_item.added
|
||||
data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","type":"function_call","status":"in_progress","arguments":"","call_id":"call_TQyfNmFnKblzXl5rlcGeIsg5","name":"echo"}}
|
||||
|
||||
event: response.function_call_arguments.delta
|
||||
data: {"type":"response.function_call_arguments.delta","sequence_number":3,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"delta":"{\\""}
|
||||
|
||||
event: response.function_call_arguments.delta
|
||||
data: {"type":"response.function_call_arguments.delta","sequence_number":4,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"delta":"string"}
|
||||
|
||||
event: response.function_call_arguments.delta
|
||||
data: {"type":"response.function_call_arguments.delta","sequence_number":5,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"delta":"\\":\\""}
|
||||
|
||||
event: response.function_call_arguments.delta
|
||||
data: {"type":"response.function_call_arguments.delta","sequence_number":6,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"delta":"hello"}
|
||||
|
||||
event: response.function_call_arguments.delta
|
||||
data: {"type":"response.function_call_arguments.delta","sequence_number":7,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"delta":"\\"}"}
|
||||
|
||||
event: response.function_call_arguments.done
|
||||
data: {"type":"response.function_call_arguments.done","sequence_number":8,"item_id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","output_index":0,"arguments":"{\\"string\\":\\"hello\\"}"}
|
||||
|
||||
event: response.output_item.done
|
||||
data: {"type":"response.output_item.done","sequence_number":9,"output_index":0,"item":{"id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","type":"function_call","status":"completed","arguments":"{\\"string\\":\\"hello\\"}","call_id":"call_TQyfNmFnKblzXl5rlcGeIsg5","name":"echo"}}
|
||||
|
||||
event: response.completed
|
||||
data: {"type":"response.completed","sequence_number":10,"response":{"id":"resp_684910c81eec81a3a9222aa336d9fcf202d35c1819a50f63","object":"response","created_at":1749618888,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4.1-nano-2025-04-14","output":[{"id":"fc_684910c8b68881a3b43610e1d57ef00702d35c1819a50f63","type":"function_call","status":"completed","arguments":"{\\"string\\":\\"hello\\"}","call_id":"call_TQyfNmFnKblzXl5rlcGeIsg5","name":"echo"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":{"type":"function","name":"echo"},"tools":[{"type":"function","description":"Used for testing of llms, will echo the param given to it","name":"echo","parameters":{"type":"object","properties":{"string":{"type":"string","description":"string to echo"}},"required":["string"]},"strict":true}],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":71,"input_tokens_details":{"cached_tokens":0},"output_tokens":6,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":77},"user":null,"metadata":{}}}
|
||||
|
||||
TEXT
|
||||
|
||||
partials = []
|
||||
|
||||
stub_request(:post, "https://api.openai.com/v1/responses").to_return(
|
||||
status: 200,
|
||||
body: response_payload,
|
||||
)
|
||||
|
||||
model
|
||||
.to_llm
|
||||
.generate(
|
||||
prompt_with_tools,
|
||||
user: Discourse.system_user,
|
||||
partial_tool_calls: true,
|
||||
) { |partial| partials << partial.dup }
|
||||
|
||||
# the partial tools are deduped
|
||||
expect(partials.length).to eq(1)
|
||||
|
||||
expect(partials.first).to be_a(DiscourseAi::Completions::ToolCall)
|
||||
expect(partials.first.name).to eq("echo")
|
||||
expect(partials.first.parameters).to eq({ string: "hello" })
|
||||
expect(partials.first.id).to eq("call_TQyfNmFnKblzXl5rlcGeIsg5")
|
||||
end
|
||||
|
||||
it "can handle non streaming tool calls" do
|
||||
response_object = {
|
||||
id: "resp_68491ed72974819f94652a73fb58109c08901d75ebf6c66e",
|
||||
object: "response",
|
||||
created_at: 1_749_622_487,
|
||||
status: "completed",
|
||||
background: false,
|
||||
error: nil,
|
||||
incomplete_details: nil,
|
||||
instructions: nil,
|
||||
max_output_tokens: nil,
|
||||
model: "gpt-4.1-nano-2025-04-14",
|
||||
output: [
|
||||
{
|
||||
id: "fc_68491ed75e0c819f87462ff642c58d2e08901d75ebf6c66e",
|
||||
type: "function_call",
|
||||
status: "completed",
|
||||
arguments: "{\"string\":\"sam\"}",
|
||||
call_id: "call_UdxBpinIVc5nRZ0VnWJIgneA",
|
||||
name: "echo",
|
||||
},
|
||||
],
|
||||
parallel_tool_calls: true,
|
||||
previous_response_id: nil,
|
||||
reasoning: {
|
||||
effort: nil,
|
||||
summary: nil,
|
||||
},
|
||||
service_tier: "default",
|
||||
store: true,
|
||||
temperature: 1.0,
|
||||
text: {
|
||||
format: {
|
||||
type: "text",
|
||||
},
|
||||
},
|
||||
tool_choice: {
|
||||
type: "function",
|
||||
name: "echo",
|
||||
},
|
||||
tools: [
|
||||
{
|
||||
type: "function",
|
||||
description: "Used for testing of llms, will echo the param given to it",
|
||||
name: "echo",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: {
|
||||
string: {
|
||||
type: "string",
|
||||
description: "string to echo",
|
||||
},
|
||||
},
|
||||
required: ["string"],
|
||||
},
|
||||
strict: true,
|
||||
},
|
||||
],
|
||||
top_p: 1.0,
|
||||
truncation: "disabled",
|
||||
usage: {
|
||||
input_tokens: 73,
|
||||
input_tokens_details: {
|
||||
cached_tokens: 0,
|
||||
},
|
||||
output_tokens: 6,
|
||||
output_tokens_details: {
|
||||
reasoning_tokens: 0,
|
||||
},
|
||||
total_tokens: 79,
|
||||
},
|
||||
user: nil,
|
||||
metadata: {
|
||||
},
|
||||
}
|
||||
|
||||
stub_request(:post, "https://api.openai.com/v1/responses").to_return(
|
||||
status: 200,
|
||||
body: response_object.to_json,
|
||||
)
|
||||
|
||||
result = model.to_llm.generate(prompt_with_tools, user: Discourse.system_user)
|
||||
|
||||
expect(result).to be_a(DiscourseAi::Completions::ToolCall)
|
||||
expect(result.name).to eq("echo")
|
||||
expect(result.parameters).to eq({ string: "sam" })
|
||||
expect(result.id).to eq("call_UdxBpinIVc5nRZ0VnWJIgneA")
|
||||
end
|
||||
end
|
||||
Loading…
x
Reference in New Issue
Block a user