tbphp
91df89efed
* fix(execution): 保留跨协议工具调用约束 * fix(cpa): 修正工具白名单兼容边界 * fix(bifrost): 拒绝丢失压缩上下文 * fix(execution): 保持计数请求工具约束 * fix(bifrost): 恢复兼容渠道的工具降级转发
198 lines
9.3 KiB
Go
198 lines
9.3 KiB
Go
package bifrost
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import (
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"net/http/httptest"
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"strings"
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"sync/atomic"
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"testing"
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"github.com/tidwall/gjson"
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"gpt-load/internal/channel"
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"gpt-load/internal/execution"
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"gpt-load/internal/protocol"
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)
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func TestCompatibleBestEffortToolConversion(t *testing.T) {
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t.Parallel()
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for _, test := range []struct {
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name string
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client protocol.Protocol
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body string
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wantTools int64
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}{
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{"Codex mixed tools", protocol.OpenAIResponses, `{"model":"client-model","input":"hello","store":false,"tool_choice":"auto","tools":[{"type":"function","name":"lookup","parameters":{"type":"object"}},{"type":"namespace","name":"helpers","tools":[{"type":"function","name":"search","parameters":{"type":"object"}}]},{"type":"web_search"},{"type":"custom","name":"apply_patch","format":{"type":"text"}}]}`, 1},
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{"Responses selected search", protocol.OpenAIResponses, `{"model":"client-model","input":"hello","store":false,"tools":[{"type":"web_search"}],"tool_choice":{"type":"function","name":"web_search"}}`, 0},
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{"Claude selected search", protocol.Anthropic, `{"model":"client-model","max_tokens":64,"messages":[{"role":"user","content":"hello"}],"tools":[{"type":"web_search_20250305","name":"web_search"}],"tool_choice":{"type":"tool","name":"web_search"}}`, 0},
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} {
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for _, stream := range []bool{false, true} {
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t.Run(fmt.Sprintf("%s/stream=%t", test.name, stream), func(t *testing.T) {
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var calls atomic.Int64
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server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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calls.Add(1)
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body, err := io.ReadAll(r.Body)
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if err != nil {
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t.Error(err)
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return
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}
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if r.URL.Path != "/chat/completions" || gjson.GetBytes(body, "tools.#").Int() != test.wantTools {
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t.Errorf("unexpected SDK fallback wire: path=%s body=%s", r.URL.Path, body)
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}
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if test.wantTools == 1 {
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if gjson.GetBytes(body, "tools.0.function.name").String() != "lookup" || gjson.GetBytes(body, "tool_choice").String() != "auto" {
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t.Errorf("function or mode lost: %s", body)
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}
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} else if gjson.GetBytes(body, "tool_choice").Exists() {
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t.Errorf("SDK should omit unsupported choice: %s", body)
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}
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if stream {
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w.Header().Set("Content-Type", "text/event-stream")
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_, _ = io.WriteString(w, openAIChatFinalStream)
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} else {
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w.Header().Set("Content-Type", "application/json")
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_, _ = io.WriteString(w, openAIChatFinalResponse)
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}
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}))
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defer server.Close()
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runtime := newRuntimeForTest(t, testRuntimeOptions{allowPrivateNetwork: true})
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runtime.baseURLs[channel.OpenAICompatible] = server.URL
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op, path := execution.OperationResponsesCreate, "/v1/responses"
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if test.client == protocol.Anthropic {
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op, path = execution.OperationChatCompletion, "/v1/messages"
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}
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spec := convertedSpec(channel.OpenAICompatible, test.client, op, path, []byte(test.body))
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var failure *execution.ErrorEvidence
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if stream {
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failure = runtime.ExecuteStream(t.Context(), spec, func(execution.StreamEvent) error { return nil }).Error
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} else {
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failure = runtime.Execute(t.Context(), spec).Error
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}
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if failure != nil || calls.Load() != 1 {
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t.Fatalf("best effort request blocked: calls=%d error=%+v", calls.Load(), failure)
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}
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})
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}
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}
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}
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func TestOpenAICompatibleAllowedToolsTwoTurnFunctionFlow(t *testing.T) {
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t.Parallel()
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for _, stream := range []bool{false, true} {
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t.Run(fmt.Sprintf("stream=%t", stream), func(t *testing.T) {
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var calls atomic.Int64
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server := httptest.NewServer(http.HandlerFunc(func(writer http.ResponseWriter, request *http.Request) {
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call := calls.Add(1)
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body, _ := io.ReadAll(request.Body)
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if request.URL.Path != "/tenant/v1/chat/completions" ||
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gjson.GetBytes(body, "tools.#").Int() != 1 ||
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gjson.GetBytes(body, "tools.0.function.name").String() != "lookup" ||
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gjson.GetBytes(body, "tool_choice").String() != "required" ||
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gjson.GetBytes(body, "parallel_tool_calls").Bool() {
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t.Errorf("converted request lost tool constraints: %s", body)
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}
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if call == 2 {
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assertChatFunctionHistory(t, body)
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}
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if stream {
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writer.Header().Set("Content-Type", "text/event-stream")
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if call == 1 {
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_, _ = io.WriteString(writer, openAIChatToolStream)
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} else {
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_, _ = io.WriteString(writer, openAIChatFinalStream)
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}
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return
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}
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writer.Header().Set("Content-Type", "application/json")
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if call == 1 {
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_, _ = io.WriteString(writer, openAIChatToolResponse)
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} else {
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_, _ = io.WriteString(writer, openAIChatFinalResponse)
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}
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}))
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defer server.Close()
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runtime := newProtocolTestRuntime(t, testRuntimeOptions{allowPrivateNetwork: true})
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target, _ := json.Marshal(map[string]string{"base_url": server.URL + "/tenant/v1"})
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first := executeConvertedToolTurn(t, runtime, target, stream,
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`[{"role":"user","content":"start"}]`)
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if !strings.Contains(first, "call_1") || !strings.Contains(first, "lookup") || !strings.Contains(first, `\"query\"`) {
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t.Fatalf("tool call was not returned as Responses output: %s", first)
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}
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second := executeConvertedToolTurn(t, runtime, target, stream,
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`[{"role":"user","content":"start"},{"type":"function_call","id":"fc_1","call_id":"call_1","name":"lookup","arguments":"{\"query\":\"x\"}"},{"type":"function_call_output","call_id":"call_1","output":""},{"role":"user","content":"continue"}]`)
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if !strings.Contains(second, "done") {
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t.Fatalf("final response was not returned: %s", second)
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}
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if calls.Load() != 2 {
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t.Fatalf("upstream calls = %d, want 2", calls.Load())
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}
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})
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}
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}
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func executeConvertedToolTurn(
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t *testing.T,
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runtime *testRuntime,
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target json.RawMessage,
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stream bool,
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input string,
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) string {
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t.Helper()
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spec := openAIResponsesSpec(execution.OperationResponsesCreate, http.MethodPost, "/v1/responses")
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spec.ChannelID = string(channel.OpenAICompatible)
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spec.TargetConfig = target
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spec.ClientModel = "client-model"
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spec.UpstreamModel = "upstream-model"
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spec.Body = []byte(fmt.Sprintf(`{"model":"client-model","stream":%t,"input":%s,"store":false,"parallel_tool_calls":false,"tools":%s,"tool_choice":{"type":"allowed_tools","mode":"required","tools":[{"type":"function","name":"lookup"}]}}`, stream, input, convertedAllowedTools))
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spec = freezeTestAttempt(spec)
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if !stream {
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result := runtime.Execute(context.Background(), spec)
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if err := result.Validate(); err != nil || result.Error != nil {
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t.Fatalf("execute converted tool turn: result=%+v err=%v body=%s", result, err, result.Body)
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}
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return string(result.Body)
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}
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var data bytes.Buffer
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result := runtime.ExecuteStream(context.Background(), spec, func(event execution.StreamEvent) error {
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if event.Kind == execution.StreamEventData {
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data.Write(event.Data)
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}
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return nil
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})
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if err := result.Validate(); err != nil || result.Error != nil {
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t.Fatalf("stream converted tool turn: result=%+v err=%v data=%s", result, err, data.String())
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}
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return data.String()
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}
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func assertChatFunctionHistory(t *testing.T, body []byte) {
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t.Helper()
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assistant := gjson.GetBytes(body, `messages.#(role=="assistant")`)
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tool := gjson.GetBytes(body, `messages.#(role=="tool")`)
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if assistant.Get("tool_calls.0.id").String() != "call_1" ||
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assistant.Get("tool_calls.0.function.name").String() != "lookup" ||
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assistant.Get("tool_calls.0.function.arguments").String() != `{"query":"x"}` ||
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tool.Get("tool_call_id").String() != "call_1" || tool.Get("content").String() != "" {
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t.Errorf("function call history was not preserved: %s", body)
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}
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}
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const openAIChatToolResponse = `{"id":"chat_tool_1","object":"chat.completion","created":1,"model":"served","choices":[{"index":0,"message":{"role":"assistant","content":null,"tool_calls":[{"id":"call_1","type":"function","function":{"name":"lookup","arguments":"{\"query\":\"x\"}"}}]},"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":5,"completion_tokens":2,"total_tokens":7}}`
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const openAIChatFinalResponse = `{"id":"chat_final_1","object":"chat.completion","created":2,"model":"served","choices":[{"index":0,"message":{"role":"assistant","content":"done"},"finish_reason":"stop"}],"usage":{"prompt_tokens":8,"completion_tokens":1,"total_tokens":9}}`
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const openAIChatToolStream = "data: {\"id\":\"chat_tool_1\",\"object\":\"chat.completion.chunk\",\"created\":1,\"model\":\"served\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"id\":\"call_1\",\"type\":\"function\",\"function\":{\"name\":\"lookup\",\"arguments\":\"{\\\"query\\\":\\\"x\\\"}\"}}]},\"finish_reason\":null}]}\n\n" +
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"data: {\"id\":\"chat_tool_1\",\"object\":\"chat.completion.chunk\",\"created\":1,\"model\":\"served\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"tool_calls\"}],\"usage\":{\"prompt_tokens\":5,\"completion_tokens\":2,\"total_tokens\":7}}\n\n" +
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"data: [DONE]\n\n"
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const openAIChatFinalStream = "data: {\"id\":\"chat_final_1\",\"object\":\"chat.completion.chunk\",\"created\":2,\"model\":\"served\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"done\"},\"finish_reason\":null}]}\n\n" +
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"data: {\"id\":\"chat_final_1\",\"object\":\"chat.completion.chunk\",\"created\":2,\"model\":\"served\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":8,\"completion_tokens\":1,\"total_tokens\":9}}\n\n" +
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"data: [DONE]\n\n"
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