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1dde82eb58
This PR adds support for disabling further tool calls by setting tool_choice to :none across all supported LLM providers:
- OpenAI: Uses "none" tool_choice parameter
- Anthropic: Uses {type: "none"} and adds a prefill message to prevent confusion
- Gemini: Sets function_calling_config mode to "NONE"
- AWS Bedrock: Doesn't natively support tool disabling, so adds a prefill message
We previously used to disable tool calls by simply removing tool definitions, but this would cause errors with some providers. This implementation uses the supported method appropriate for each provider while providing a fallback for Bedrock.
Co-authored-by: Natalie Tay <natalie.tay@gmail.com>
* remove stray puts
* cleaner chain breaker for last tool call (works in thinking)
remove unused code
* improve test
---------
Co-authored-by: Natalie Tay <natalie.tay@gmail.com>
119 lines
3.6 KiB
Ruby
119 lines
3.6 KiB
Ruby
# frozen_string_literal: true
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class TestDialect < DiscourseAi::Completions::Dialects::Dialect
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attr_accessor :max_prompt_tokens
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def trim(messages)
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trim_messages(messages)
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end
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def system_msg(msg)
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msg
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end
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def user_msg(msg)
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msg
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end
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def model_msg(msg)
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msg
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end
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def tokenizer
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DiscourseAi::Tokenizer::OpenAiTokenizer
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end
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end
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RSpec.describe DiscourseAi::Completions::Dialects::Dialect do
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fab!(:llm_model)
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describe "#translate" do
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let(:five_token_msg) { "This represents five tokens." }
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let(:tools) do
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[
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{
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name: "echo",
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description: "echo a string",
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parameters: [
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{ name: "text", type: "string", description: "string to echo", required: true },
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],
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},
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]
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end
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it "injects done message when tool_choice is :none and last message follows tool pattern" do
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tool_call_prompt = { name: "echo", arguments: { text: "test message" } }
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prompt = DiscourseAi::Completions::Prompt.new("System instructions", tools: tools)
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prompt.push(type: :user, content: "echo test message")
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prompt.push(type: :tool_call, content: tool_call_prompt.to_json, id: "123", name: "echo")
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prompt.push(type: :tool, content: "test message".to_json, name: "echo", id: "123")
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prompt.tool_choice = :none
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dialect = TestDialect.new(prompt, llm_model)
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dialect.max_prompt_tokens = 100 # Set high enough to avoid trimming
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translated = dialect.translate
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expect(translated).to eq(
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[
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{ type: :system, content: "System instructions" },
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{ type: :user, content: "echo test message" },
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{
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type: :tool_call,
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content:
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"<function_calls>\n<invoke>\n<tool_name>echo</tool_name>\n<parameters>\n<text>test message</text>\n</parameters>\n</invoke>\n</function_calls>",
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id: "123",
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name: "echo",
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},
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{
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type: :tool,
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id: "123",
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name: "echo",
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content:
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"<function_results>\n<result>\n<tool_name>echo</tool_name>\n<json>\n\"test message\"\n</json>\n</result>\n</function_results>\n\n#{::DiscourseAi::Completions::Dialects::XmlTools::DONE_MESSAGE}",
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},
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],
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)
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end
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end
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describe "#trim_messages" do
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let(:five_token_msg) { "This represents five tokens." }
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it "should trim tool messages if tool_calls are trimmed" do
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prompt = DiscourseAi::Completions::Prompt.new(five_token_msg)
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prompt.push(type: :user, content: five_token_msg)
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prompt.push(type: :tool_call, content: five_token_msg, id: 1)
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prompt.push(type: :tool, content: five_token_msg, id: 1)
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prompt.push(type: :user, content: five_token_msg)
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dialect = TestDialect.new(prompt, llm_model)
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dialect.max_prompt_tokens = 15 # fits the user messages and the tool_call message
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trimmed = dialect.trim(prompt.messages)
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expect(trimmed).to eq(
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[{ type: :system, content: five_token_msg }, { type: :user, content: five_token_msg }],
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)
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end
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it "limits the system message to 60% of available tokens" do
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prompt = DiscourseAi::Completions::Prompt.new("I'm a system message consisting of 10 tokens")
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prompt.push(type: :user, content: five_token_msg)
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dialect = TestDialect.new(prompt, llm_model)
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dialect.max_prompt_tokens = 15
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trimmed = dialect.trim(prompt.messages)
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expect(trimmed).to eq(
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[
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{ type: :system, content: "I'm a system message consisting of 10" },
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{ type: :user, content: five_token_msg },
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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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