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discourse-ai/spec/lib/completions/endpoints/open_ai_spec.rb

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# frozen_string_literal: true
require_relative "endpoint_compliance"
class OpenAiMock < EndpointMock
def response(content, tool_call: false)
message_content =
if tool_call
{ tool_calls: [content] }
else
{ content: content }
end
{
id: "chatcmpl-6sZfAb30Rnv9Q7ufzFwvQsMpjZh8S",
object: "chat.completion",
created: 1_678_464_820,
model: "gpt-3.5-turbo-0301",
usage: {
prompt_tokens: 337,
completion_tokens: 162,
total_tokens: 499,
},
choices: [
{ message: { role: "assistant" }.merge(message_content), finish_reason: "stop", index: 0 },
],
}
end
def stub_response(prompt, response_text, tool_call: false)
WebMock
.stub_request(:post, "https://api.openai.com/v1/chat/completions")
.with(body: request_body(prompt, tool_call: tool_call))
.to_return(status: 200, body: JSON.dump(response(response_text, tool_call: tool_call)))
end
def stream_line(delta, finish_reason: nil, tool_call: false)
message_content =
if tool_call
{ tool_calls: [delta] }
else
{ content: delta }
end
+"data: " << {
id: "chatcmpl-#{SecureRandom.hex}",
object: "chat.completion.chunk",
created: 1_681_283_881,
model: "gpt-3.5-turbo-0301",
choices: [{ delta: message_content }],
finish_reason: finish_reason,
index: 0,
}.to_json
end
def stub_raw(chunks)
WebMock.stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(
status: 200,
body: chunks,
)
end
def stub_streamed_response(prompt, deltas, tool_call: false)
chunks =
deltas.each_with_index.map do |_, index|
if index == (deltas.length - 1)
stream_line(deltas[index], finish_reason: "stop_sequence", tool_call: tool_call)
else
stream_line(deltas[index], tool_call: tool_call)
end
end
chunks = (chunks.join("\n\n") << "data: [DONE]").split("")
WebMock
.stub_request(:post, "https://api.openai.com/v1/chat/completions")
.with(body: request_body(prompt, stream: true, tool_call: tool_call))
.to_return(status: 200, body: chunks)
yield if block_given?
end
def tool_deltas
[
{ id: tool_id, function: {} },
{ id: tool_id, function: { name: "get_weather", arguments: "" } },
{ id: tool_id, function: { arguments: "" } },
{ id: tool_id, function: { arguments: "{" } },
{ id: tool_id, function: { arguments: " \"location\": \"Sydney\"" } },
{ id: tool_id, function: { arguments: " ,\"unit\": \"c\" }" } },
]
end
def tool_response
{
id: tool_id,
function: {
name: "get_weather",
arguments: { location: "Sydney", unit: "c" }.to_json,
},
}
end
def tool_id
"tool_0"
end
def tool_payload
{
type: "function",
function: {
name: "get_weather",
description: "Get the weather in a city",
parameters: {
type: "object",
properties: {
location: {
type: "string",
description: "the city name",
},
unit: {
type: "string",
description: "the unit of measurement celcius c or fahrenheit f",
enum: %w[c f],
},
},
required: %w[location unit],
},
},
}
end
def request_body(prompt, stream: false, tool_call: false)
model
.default_options
.merge(messages: prompt)
.tap do |b|
if stream
b[:stream] = true
b[:stream_options] = { include_usage: true }
end
b[:tools] = [tool_payload] if tool_call
end
.to_json
end
end
RSpec.describe DiscourseAi::Completions::Endpoints::OpenAi do
subject(:endpoint) do
described_class.new("gpt-3.5-turbo", DiscourseAi::Tokenizer::OpenAiTokenizer)
end
fab!(:user)
let(:echo_tool) do
{
name: "echo",
description: "echo something",
parameters: [{ name: "text", type: "string", description: "text to echo", required: true }],
}
end
let(:tools) { [echo_tool] }
let(:open_ai_mock) { OpenAiMock.new(endpoint) }
let(:compliance) do
EndpointsCompliance.new(self, endpoint, DiscourseAi::Completions::Dialects::ChatGpt, user)
end
let(:image100x100) { plugin_file_from_fixtures("100x100.jpg") }
let(:upload100x100) do
UploadCreator.new(image100x100, "image.jpg").create_for(Discourse.system_user.id)
end
describe "repeat calls" do
it "can properly reset context" do
llm = DiscourseAi::Completions::Llm.proxy("open_ai:gpt-4-turbo")
tools = [
{
name: "echo",
description: "echo something",
parameters: [
{ name: "text", type: "string", description: "text to echo", required: true },
],
},
]
prompt =
DiscourseAi::Completions::Prompt.new(
"You are a bot",
messages: [type: :user, id: "user1", content: "echo hello"],
tools: tools,
)
response = {
id: "chatcmpl-9JxkAzzaeO4DSV3omWvok9TKhCjBH",
object: "chat.completion",
created: 1_714_544_914,
model: "gpt-4-turbo-2024-04-09",
choices: [
{
index: 0,
message: {
role: "assistant",
content: nil,
tool_calls: [
{
id: "call_I8LKnoijVuhKOM85nnEQgWwd",
type: "function",
function: {
name: "echo",
arguments: "{\"text\":\"hello\"}",
},
},
],
},
logprobs: nil,
finish_reason: "tool_calls",
},
],
usage: {
prompt_tokens: 55,
completion_tokens: 13,
total_tokens: 68,
},
system_fingerprint: "fp_ea6eb70039",
}.to_json
stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(body: response)
result = llm.generate(prompt, user: user)
expected = (<<~TXT).strip
<function_calls>
<invoke>
<tool_name>echo</tool_name>
<parameters>
<text>hello</text>
</parameters>
<tool_id>call_I8LKnoijVuhKOM85nnEQgWwd</tool_id>
</invoke>
</function_calls>
TXT
expect(result.strip).to eq(expected)
stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(
body: { choices: [message: { content: "OK" }] }.to_json,
)
result = llm.generate(prompt, user: user)
expect(result).to eq("OK")
end
end
describe "image support" do
it "can handle images" do
llm = DiscourseAi::Completions::Llm.proxy("open_ai:gpt-4-turbo")
prompt =
DiscourseAi::Completions::Prompt.new(
"You are image bot",
messages: [type: :user, id: "user1", content: "hello", upload_ids: [upload100x100.id]],
)
encoded = prompt.encoded_uploads(prompt.messages.last)
parsed_body = nil
stub_request(:post, "https://api.openai.com/v1/chat/completions").with(
body:
proc do |req_body|
parsed_body = JSON.parse(req_body, symbolize_names: true)
true
end,
).to_return(status: 200, body: { choices: [message: { content: "nice pic" }] }.to_json)
completion = llm.generate(prompt, user: user)
expect(completion).to eq("nice pic")
expected_body = {
model: "gpt-4-turbo",
messages: [
{ role: "system", content: "You are image bot" },
{
role: "user",
content: [
{
type: "image_url",
image_url: {
url: "data:#{encoded[0][:mime_type]};base64,#{encoded[0][:base64]}",
},
},
{ type: "text", text: "hello" },
],
name: "user1",
},
],
}
expect(parsed_body).to eq(expected_body)
end
end
describe "#perform_completion!" do
context "when using regular mode" do
context "with simple prompts" do
it "completes a trivial prompt and logs the response" do
compliance.regular_mode_simple_prompt(open_ai_mock)
end
end
context "with tools" do
it "returns a function invocation" do
compliance.regular_mode_tools(open_ai_mock)
end
end
end
describe "when using streaming mode" do
context "with simple prompts" do
it "completes a trivial prompt and logs the response" do
compliance.streaming_mode_simple_prompt(open_ai_mock)
end
it "will automatically recover from a bad payload" do
called = false
# this should not happen, but lets ensure nothing bad happens
# the row with test1 is invalid json
raw_data = <<~TEXT.strip
d|a|t|a|:| |{|"choices":[{"delta":{"content":"test,"}}]}
data: {"choices":[{"delta":{"content":"test|1| |,"}}]
data: {"choices":[{"delta":|{"content":"test2 ,"}}]}
data: {"choices":[{"delta":{"content":"test3,"}}]|}
data: {"choices":[{|"|d|elta":{"content":"test4"}}]|}
data: [D|ONE]
TEXT
chunks = raw_data.split("|")
open_ai_mock.with_chunk_array_support do
open_ai_mock.stub_raw(chunks)
partials = []
endpoint.perform_completion!(compliance.dialect, user) { |partial| partials << partial }
called = true
expect(partials.join).to eq("test,test2 ,test3,test4")
end
expect(called).to be(true)
end
end
context "with tools" do
it "returns a function invocation" do
compliance.streaming_mode_tools(open_ai_mock)
end
it "properly handles multiple tool calls" do
raw_data = <<~TEXT.strip
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"role":"assistant","content":null},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"id":"call_3Gyr3HylFJwfrtKrL6NaIit1","type":"function","function":{"name":"search","arguments":""}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\\"se"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"arch_"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"query\\""}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":": \\"D"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"iscou"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"rse AI"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":" bot"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\\"}"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"id":"call_H7YkbgYurHpyJqzwUN4bghwN","type":"function","function":{"name":"search","arguments":""}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\\"qu"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"ery\\":"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":" \\"Disc"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"ours"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"e AI "}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"bot\\"}"}}]},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"tool_calls"}]}
data: [DONE]
TEXT
open_ai_mock.stub_raw(raw_data)
content = +""
dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
endpoint.perform_completion!(dialect, user) { |partial| content << partial }
expected = <<~TEXT
<function_calls>
<invoke>
<tool_name>search</tool_name>
<parameters>
<search_query>Discourse AI bot</search_query>
</parameters>
<tool_id>call_3Gyr3HylFJwfrtKrL6NaIit1</tool_id>
</invoke>
<invoke>
<tool_name>search</tool_name>
<parameters>
<query>Discourse AI bot</query>
</parameters>
<tool_id>call_H7YkbgYurHpyJqzwUN4bghwN</tool_id>
</invoke>
</function_calls>
TEXT
expect(content).to eq(expected)
end
it "uses proper token accounting" do
response = <<~TEXT.strip
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}],"usage":null}|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}],"usage":null}|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null}|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[],"usage":{"prompt_tokens":20,"completion_tokens":9,"total_tokens":29}}|
data: [DONE]
TEXT
chunks = response.split("|")
open_ai_mock.with_chunk_array_support do
open_ai_mock.stub_raw(chunks)
partials = []
dialect = compliance.dialect(prompt: compliance.generic_prompt)
endpoint.perform_completion!(dialect, user) { |partial| partials << partial }
expect(partials).to eq(["Hello"])
log = AiApiAuditLog.order("id desc").first
expect(log.request_tokens).to eq(20)
expect(log.response_tokens).to eq(9)
end
end
it "properly handles spaces in tools payload" do
raw_data = <<~TEXT.strip
data: {"choices":[{"index":0,"delta":{"role":"assistant","content":null,"tool_calls":[{"index":0,"id":"func_id","type":"function","function":{"name":"go|ogle","arg|uments":""}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "{\\""}}]}}]}
data: {"ch|oices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "query"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "\\":\\""}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "Ad"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "a|b"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "as"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": |"| "}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "9"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "."}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"argume|nts": "1"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "\\"}"}}]}}]}
data: {"choices": [{"index": 0, "delta": {"tool_calls": []}}]}
data: [D|ONE]
TEXT
chunks = raw_data.split("|")
open_ai_mock.with_chunk_array_support do
open_ai_mock.stub_raw(chunks)
partials = []
dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
endpoint.perform_completion!(dialect, user) { |partial| partials << partial }
expect(partials.length).to eq(1)
function_call = (<<~TXT).strip
<function_calls>
<invoke>
<tool_name>google</tool_name>
<parameters>
<query>Adabas 9.1</query>
</parameters>
<tool_id>func_id</tool_id>
</invoke>
</function_calls>
TXT
expect(partials[0].strip).to eq(function_call)
end
end
end
end
end
end
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