feat(ai-statistics): add session ID tracking for multi-turn agent conversations (#3420)

This commit is contained in:
澄潭
2026-02-01 00:35:50 +08:00
committed by GitHub
parent 93075cbc03
commit 1b0ee6e837
5 changed files with 1105 additions and 38 deletions

View File

@@ -29,6 +29,7 @@ description: AI可观测配置参考
| `value_length_limit` | int | 非必填 | 4000 | 记录的单个value的长度限制 |
| `enable_path_suffixes` | []string | 非必填 | [] | 只对这些特定路径后缀的请求生效,可以配置为 "\*" 以匹配所有路径(通配符检查会优先进行以提高性能)。如果为空数组,则对所有路径生效 |
| `enable_content_types` | []string | 非必填 | [] | 只对这些内容类型的响应进行缓冲处理。如果为空数组,则对所有内容类型生效 |
| `session_id_header` | string | 非必填 | - | 指定读取 session ID 的 header 名称。如果不配置,将按以下优先级自动查找:`x-openclaw-session-key``x-clawdbot-session-key``x-moltbot-session-key``x-agent-session`。session ID 可用于追踪多轮 Agent 对话 |
Attribute 配置说明:
@@ -134,6 +135,14 @@ irate(route_upstream_model_consumer_metric_llm_duration_count[2m])
}
```
如果请求中携带了 session ID header日志中会自动添加 `session_id` 字段:
```json
{
"ai_log": "{\"session_id\":\"sess_abc123\",\"model\":\"qwen-turbo\",\"input_token\":\"10\",\"output_token\":\"69\",\"llm_first_token_duration\":\"309\",\"llm_service_duration\":\"1955\"}"
}
```
#### 链路追踪
配置为空时,不会在 span 中添加额外的 attribute
@@ -198,9 +207,11 @@ attributes:
### 记录问题与回答
#### 仅记录当前轮次的问题与回答
```yaml
attributes:
- key: question # 记录问题
- key: question # 记录当前轮次的问题(最后一条用户消息)
value_source: request_body
value: messages.@reverse.0.content
apply_to_log: true
@@ -215,6 +226,69 @@ attributes:
apply_to_log: true
```
#### 记录完整的多轮对话历史(推荐配置)
对于多轮 Agent 对话场景,使用内置属性可以大幅简化配置:
```yaml
session_id_header: "x-session-id" # 可选,指定 session ID header
attributes:
- key: messages # 完整对话历史
value_source: request_body
value: messages
apply_to_log: true
- key: question # 内置属性,自动提取最后一条用户消息
apply_to_log: true
- key: answer # 内置属性,自动提取回答
apply_to_log: true
- key: reasoning # 内置属性,自动提取思考过程
apply_to_log: true
- key: tool_calls # 内置属性,自动提取工具调用
apply_to_log: true
```
**内置属性说明:**
插件提供以下内置属性 key无需配置 `value_source``value` 字段即可自动提取:
| 内置 Key | 说明 | 默认 value_source |
|---------|------|-------------------|
| `question` | 自动提取最后一条用户消息 | `request_body` |
| `answer` | 自动提取回答内容(支持 OpenAI/Claude 协议) | `response_streaming_body` / `response_body` |
| `tool_calls` | 自动提取并拼接工具调用(流式场景自动按 index 拼接 arguments | `response_streaming_body` / `response_body` |
| `reasoning` | 自动提取思考过程reasoning_content如 DeepSeek-R1 | `response_streaming_body` / `response_body` |
> **注意**:如果配置了 `value_source` 和 `value`,将优先使用配置的值,以保持向后兼容。
日志输出示例:
```json
{
"ai_log": "{\"session_id\":\"sess_abc123\",\"messages\":[{\"role\":\"user\",\"content\":\"北京天气怎么样?\"}],\"question\":\"北京天气怎么样?\",\"reasoning\":\"用户想知道北京的天气,我需要调用天气查询工具。\",\"tool_calls\":[{\"index\":0,\"id\":\"call_abc123\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"location\\\":\\\"Beijing\\\"}\"}}],\"model\":\"deepseek-reasoner\"}"
}
```
**流式响应中的 tool_calls 处理:**
插件会自动按 `index` 字段识别每个独立的工具调用,拼接分片返回的 `arguments` 字符串,最终输出完整的工具调用列表。
## 调试
### 验证 ai_log 内容
在测试或调试过程中,可以通过开启 Higress 的 debug 日志来验证 ai_log 的内容:
```bash
# 日志格式示例
2026/01/31 23:29:30 proxy_debug_log: [ai-statistics] [nil] [test-request-id] [ai_log] attributes to be written: {"question":"What is 2+2?","answer":"4","reasoning":"...","tool_calls":[...],"session_id":"sess_123","model":"gpt-4","input_token":20,"output_token":10}
```
通过这个debug日志可以验证
- question/answer/reasoning 是否正确提取
- tool_calls 是否正确拼接特别是流式场景下的arguments
- session_id 是否正确识别
- 各个字段是否符合预期
## 进阶
配合阿里云 SLS 数据加工,可以将 ai 相关的字段进行提取加工,例如原始日志为:

View File

@@ -29,6 +29,7 @@ Users can also expand observable values through configuration:
| `value_length_limit` | int | optional | 4000 | length limit for each value |
| `enable_path_suffixes` | []string | optional | ["/v1/chat/completions","/v1/completions","/v1/embeddings","/v1/models","/generateContent","/streamGenerateContent"] | Only effective for requests with these specific path suffixes, can be configured as "\*" to match all paths |
| `enable_content_types` | []string | optional | ["text/event-stream","application/json"] | Only buffer response body for these content types |
| `session_id_header` | string | optional | - | Specify the header name to read session ID from. If not configured, it will automatically search in the following priority: `x-openclaw-session-key`, `x-clawdbot-session-key`, `x-moltbot-session-key`, `x-agent-session`. Session ID can be used to trace multi-turn Agent conversations |
Attribute Configuration instructions:
@@ -134,10 +135,35 @@ irate(route_upstream_model_consumer_metric_llm_duration_count[2m])
}
```
If the request contains a session ID header, the log will automatically include a `session_id` field:
```json
{
"ai_log": "{\"session_id\":\"sess_abc123\",\"model\":\"qwen-turbo\",\"input_token\":\"10\",\"output_token\":\"69\",\"llm_first_token_duration\":\"309\",\"llm_service_duration\":\"1955\"}"
}
```
#### Trace
When the configuration is empty, no additional attributes will be added to the span.
## Debugging
### Verifying ai_log Content
During testing or debugging, you can enable Higress debug logging to verify the ai_log content:
```bash
# Log format example
2026/01/31 23:29:30 proxy_debug_log: [ai-statistics] [nil] [test-request-id] [ai_log] attributes to be written: {"question":"What is 2+2?","answer":"4","reasoning":"...","tool_calls":[...],"session_id":"sess_123","model":"gpt-4","input_token":20,"output_token":10}
```
This debug log allows you to verify:
- Whether question/answer/reasoning are correctly extracted
- Whether tool_calls are properly concatenated (especially arguments in streaming scenarios)
- Whether session_id is correctly identified
- Whether all fields match expectations
### Extract token usage information from non-openai protocols
When setting the protocol to original in ai-proxy, taking Alibaba Cloud Bailian as an example, you can make the following configuration to specify how to extract `model`, `input_token`, `output_token`
@@ -194,9 +220,11 @@ attributes:
### Record questions and answers
#### Record only current turn's question and answer
```yaml
attributes:
- key: question
- key: question # Record the current turn's question (last user message)
value_source: request_body
value: messages.@reverse.0.content
apply_to_log: true
@@ -211,6 +239,52 @@ attributes:
apply_to_log: true
```
#### Record complete multi-turn conversation history (Recommended)
For multi-turn Agent conversation scenarios, using built-in attributes greatly simplifies the configuration:
```yaml
session_id_header: "x-session-id" # Optional, specify session ID header
attributes:
- key: messages # Complete conversation history
value_source: request_body
value: messages
apply_to_log: true
- key: question # Built-in, auto-extracts last user message
apply_to_log: true
- key: answer # Built-in, auto-extracts answer
apply_to_log: true
- key: reasoning # Built-in, auto-extracts reasoning process
apply_to_log: true
- key: tool_calls # Built-in, auto-extracts tool calls
apply_to_log: true
```
**Built-in Attributes:**
The plugin provides the following built-in attribute keys that automatically extract values without configuring `value_source` and `value` fields:
| Built-in Key | Description | Default value_source |
|-------------|-------------|----------------------|
| `question` | Automatically extracts the last user message | `request_body` |
| `answer` | Automatically extracts answer content (supports OpenAI/Claude protocols) | `response_streaming_body` / `response_body` |
| `tool_calls` | Automatically extracts and assembles tool calls (streaming scenarios auto-concatenate arguments by index) | `response_streaming_body` / `response_body` |
| `reasoning` | Automatically extracts reasoning process (reasoning_content, e.g., DeepSeek-R1) | `response_streaming_body` / `response_body` |
> **Note**: If `value_source` and `value` are configured, the configured values take priority for backward compatibility.
Example log output:
```json
{
"ai_log": "{\"session_id\":\"sess_abc123\",\"messages\":[{\"role\":\"user\",\"content\":\"What's the weather in Beijing?\"}],\"question\":\"What's the weather in Beijing?\",\"reasoning\":\"The user wants to know the weather in Beijing, I need to call the weather query tool.\",\"tool_calls\":[{\"index\":0,\"id\":\"call_abc123\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"location\\\":\\\"Beijing\\\"}\"}}],\"model\":\"deepseek-reasoner\"}"
}
```
**Streaming tool_calls handling:**
The plugin automatically identifies each independent tool call by the `index` field, concatenates fragmented `arguments` strings, and outputs the complete tool call list.
### Path and Content Type Filtering Configuration Examples
#### Process Only Specific AI Paths

View File

@@ -0,0 +1,15 @@
--- a/main.go
+++ b/main.go
@@ -790,6 +790,14 @@
buffer = extractStreamingToolCalls(body, buffer)
ctx.SetContext(CtxStreamingToolCallsBuffer, buffer)
+ // Also set tool_calls to user attributes so they appear in ai_log
+ toolCalls := getToolCallsFromBuffer(buffer)
+ if len(toolCalls) > 0 {
+ ctx.SetUserAttribute(BuiltinToolCallsKey, toolCalls)
+ return toolCalls
+ }
}
} else if source == ResponseBody {
if value := gjson.GetBytes(body, ToolCallsPathNonStreaming).Value(); value != nil {

View File

@@ -48,6 +48,9 @@ const (
RequestPath = "request_path"
SkipProcessing = "skip_processing"
// Session ID related
SessionID = "session_id"
// AI API Paths
PathOpenAIChatCompletions = "/v1/chat/completions"
PathOpenAICompletions = "/v1/completions"
@@ -87,8 +90,10 @@ const (
RuleAppend = "append"
// Built-in attributes
BuiltinQuestionKey = "question"
BuiltinAnswerKey = "answer"
BuiltinQuestionKey = "question"
BuiltinAnswerKey = "answer"
BuiltinToolCallsKey = "tool_calls"
BuiltinReasoningKey = "reasoning"
// Built-in attribute paths
// Question paths (from request body)
@@ -102,8 +107,132 @@ const (
// Answer paths (from response streaming body)
AnswerPathOpenAIStreaming = "choices.0.delta.content"
AnswerPathClaudeStreaming = "delta.text"
// Tool calls paths
ToolCallsPathNonStreaming = "choices.0.message.tool_calls"
ToolCallsPathStreaming = "choices.0.delta.tool_calls"
// Reasoning paths
ReasoningPathNonStreaming = "choices.0.message.reasoning_content"
ReasoningPathStreaming = "choices.0.delta.reasoning_content"
// Context key for streaming tool calls buffer
CtxStreamingToolCallsBuffer = "streamingToolCallsBuffer"
)
// Default session ID headers in priority order
var defaultSessionHeaders = []string{
"x-openclaw-session-key",
"x-clawdbot-session-key",
"x-moltbot-session-key",
"x-agent-session",
}
// extractSessionId extracts session ID from request headers
// If customHeader is configured, it takes priority; otherwise falls back to default headers
func extractSessionId(customHeader string) string {
// If custom header is configured, try it first
if customHeader != "" {
if sessionId, _ := proxywasm.GetHttpRequestHeader(customHeader); sessionId != "" {
return sessionId
}
}
// Fall back to default session headers in priority order
for _, header := range defaultSessionHeaders {
if sessionId, _ := proxywasm.GetHttpRequestHeader(header); sessionId != "" {
return sessionId
}
}
return ""
}
// ToolCall represents a single tool call in the response
type ToolCall struct {
Index int `json:"index,omitempty"`
ID string `json:"id,omitempty"`
Type string `json:"type,omitempty"`
Function ToolCallFunction `json:"function,omitempty"`
}
// ToolCallFunction represents the function details in a tool call
type ToolCallFunction struct {
Name string `json:"name,omitempty"`
Arguments string `json:"arguments,omitempty"`
}
// StreamingToolCallsBuffer holds the state for assembling streaming tool calls
type StreamingToolCallsBuffer struct {
ToolCalls map[int]*ToolCall // keyed by index
}
// extractStreamingToolCalls extracts and assembles tool calls from streaming response chunks
func extractStreamingToolCalls(data []byte, buffer *StreamingToolCallsBuffer) *StreamingToolCallsBuffer {
if buffer == nil {
buffer = &StreamingToolCallsBuffer{
ToolCalls: make(map[int]*ToolCall),
}
}
chunks := bytes.Split(bytes.TrimSpace(wrapper.UnifySSEChunk(data)), []byte("\n\n"))
for _, chunk := range chunks {
toolCallsResult := gjson.GetBytes(chunk, ToolCallsPathStreaming)
if !toolCallsResult.Exists() || !toolCallsResult.IsArray() {
continue
}
for _, tcResult := range toolCallsResult.Array() {
index := int(tcResult.Get("index").Int())
// Get or create tool call entry
tc, exists := buffer.ToolCalls[index]
if !exists {
tc = &ToolCall{Index: index}
buffer.ToolCalls[index] = tc
}
// Update fields if present
if id := tcResult.Get("id").String(); id != "" {
tc.ID = id
}
if tcType := tcResult.Get("type").String(); tcType != "" {
tc.Type = tcType
}
if funcName := tcResult.Get("function.name").String(); funcName != "" {
tc.Function.Name = funcName
}
// Append arguments (they come in chunks)
if args := tcResult.Get("function.arguments").String(); args != "" {
tc.Function.Arguments += args
}
}
}
return buffer
}
// getToolCallsFromBuffer converts the buffer to a sorted slice of tool calls
func getToolCallsFromBuffer(buffer *StreamingToolCallsBuffer) []ToolCall {
if buffer == nil || len(buffer.ToolCalls) == 0 {
return nil
}
// Find max index to create properly sized slice
maxIndex := 0
for idx := range buffer.ToolCalls {
if idx > maxIndex {
maxIndex = idx
}
}
result := make([]ToolCall, 0, len(buffer.ToolCalls))
for i := 0; i <= maxIndex; i++ {
if tc, exists := buffer.ToolCalls[i]; exists {
result = append(result, *tc)
}
}
return result
}
// TracingSpan is the tracing span configuration.
type Attribute struct {
Key string `json:"key"`
@@ -132,6 +261,8 @@ type AIStatisticsConfig struct {
enablePathSuffixes []string
// Content types to enable response body buffering
enableContentTypes []string
// Session ID header name (if configured, takes priority over default headers)
sessionIdHeader string
}
func generateMetricName(route, cluster, model, consumer, metricName string) string {
@@ -272,6 +403,11 @@ func parseConfig(configJson gjson.Result, config *AIStatisticsConfig) error {
config.enableContentTypes = append(config.enableContentTypes, contentTypeStr)
}
// Parse session ID header configuration
if sessionIdHeader := configJson.Get("session_id_header"); sessionIdHeader.Exists() {
config.sessionIdHeader = sessionIdHeader.String()
}
return nil
}
@@ -307,6 +443,12 @@ func onHttpRequestHeaders(ctx wrapper.HttpContext, config AIStatisticsConfig) ty
ctx.SetRequestBodyBufferLimit(defaultMaxBodyBytes)
// Extract session ID from headers
sessionId := extractSessionId(config.sessionIdHeader)
if sessionId != "" {
ctx.SetUserAttribute(SessionID, sessionId)
}
// Set span attributes for ARMS.
setSpanAttribute(ArmsSpanKind, "LLM")
// Set user defined log & span attributes which type is fixed_value
@@ -361,6 +503,7 @@ func onHttpRequestBody(ctx wrapper.HttpContext, config AIStatisticsConfig, body
ctx.SetUserAttribute(ChatRound, userPromptCount)
// Write log
debugLogAiLog(ctx)
_ = ctx.WriteUserAttributeToLogWithKey(wrapper.AILogKey)
return types.ActionContinue
}
@@ -452,6 +595,7 @@ func onHttpStreamingBody(ctx wrapper.HttpContext, config AIStatisticsConfig, dat
}
// Write log
debugLogAiLog(ctx)
_ = ctx.WriteUserAttributeToLogWithKey(wrapper.AILogKey)
// Write metrics
@@ -497,6 +641,7 @@ func onHttpResponseBody(ctx wrapper.HttpContext, config AIStatisticsConfig, body
setAttributeBySource(ctx, config, ResponseBody, body)
// Write log
debugLogAiLog(ctx)
_ = ctx.WriteUserAttributeToLogWithKey(wrapper.AILogKey)
// Write metrics
@@ -511,8 +656,16 @@ func setAttributeBySource(ctx wrapper.HttpContext, config AIStatisticsConfig, so
for _, attribute := range config.attributes {
var key string
var value interface{}
if source == attribute.ValueSource {
key = attribute.Key
key = attribute.Key
// Check if this attribute should be processed for the current source
// For built-in attributes without value_source configured, use default source matching
if !shouldProcessBuiltinAttribute(key, attribute.ValueSource, source) {
continue
}
// If value is configured, try to extract using the configured path
if attribute.Value != "" {
switch source {
case FixedValue:
value = attribute.Value
@@ -528,52 +681,81 @@ func setAttributeBySource(ctx wrapper.HttpContext, config AIStatisticsConfig, so
value = gjson.GetBytes(body, attribute.Value).Value()
default:
}
}
// Handle built-in attributes with Claude/OpenAI protocol fallback logic
if (value == nil || value == "") && isBuiltinAttribute(key) {
value = getBuiltinAttributeFallback(ctx, config, key, source, body, attribute.Rule)
if value != nil && value != "" {
log.Debugf("[attribute] Used protocol fallback for %s: %+v", key, value)
}
// Handle built-in attributes: use fallback if value is empty or not configured
if (value == nil || value == "") && isBuiltinAttribute(key) {
value = getBuiltinAttributeFallback(ctx, config, key, source, body, attribute.Rule)
if value != nil && value != "" {
log.Debugf("[attribute] Used built-in extraction for %s: %+v", key, value)
}
}
if (value == nil || value == "") && attribute.DefaultValue != "" {
value = attribute.DefaultValue
}
if len(fmt.Sprint(value)) > config.valueLengthLimit {
value = fmt.Sprint(value)[:config.valueLengthLimit/2] + " [truncated] " + fmt.Sprint(value)[len(fmt.Sprint(value))-config.valueLengthLimit/2:]
}
log.Debugf("[attribute] source type: %s, key: %s, value: %+v", source, key, value)
if attribute.ApplyToLog {
if attribute.AsSeparateLogField {
marshalledJsonStr := wrapper.MarshalStr(fmt.Sprint(value))
if err := proxywasm.SetProperty([]string{key}, []byte(marshalledJsonStr)); err != nil {
log.Warnf("failed to set %s in filter state, raw is %s, err is %v", key, marshalledJsonStr, err)
}
} else {
ctx.SetUserAttribute(key, value)
if (value == nil || value == "") && attribute.DefaultValue != "" {
value = attribute.DefaultValue
}
if len(fmt.Sprint(value)) > config.valueLengthLimit {
value = fmt.Sprint(value)[:config.valueLengthLimit/2] + " [truncated] " + fmt.Sprint(value)[len(fmt.Sprint(value))-config.valueLengthLimit/2:]
}
log.Debugf("[attribute] source type: %s, key: %s, value: %+v", source, key, value)
if attribute.ApplyToLog {
if attribute.AsSeparateLogField {
marshalledJsonStr := wrapper.MarshalStr(fmt.Sprint(value))
if err := proxywasm.SetProperty([]string{key}, []byte(marshalledJsonStr)); err != nil {
log.Warnf("failed to set %s in filter state, raw is %s, err is %v", key, marshalledJsonStr, err)
}
} else {
ctx.SetUserAttribute(key, value)
}
// for metrics
if key == tokenusage.CtxKeyModel || key == tokenusage.CtxKeyInputToken || key == tokenusage.CtxKeyOutputToken || key == tokenusage.CtxKeyTotalToken {
ctx.SetContext(key, value)
}
if attribute.ApplyToSpan {
if attribute.TraceSpanKey != "" {
key = attribute.TraceSpanKey
}
setSpanAttribute(key, value)
}
// for metrics
if key == tokenusage.CtxKeyModel || key == tokenusage.CtxKeyInputToken || key == tokenusage.CtxKeyOutputToken || key == tokenusage.CtxKeyTotalToken {
ctx.SetContext(key, value)
}
if attribute.ApplyToSpan {
if attribute.TraceSpanKey != "" {
key = attribute.TraceSpanKey
}
setSpanAttribute(key, value)
}
}
}
// isBuiltinAttribute checks if the given key is a built-in attribute
func isBuiltinAttribute(key string) bool {
return key == BuiltinQuestionKey || key == BuiltinAnswerKey
return key == BuiltinQuestionKey || key == BuiltinAnswerKey || key == BuiltinToolCallsKey || key == BuiltinReasoningKey
}
// getBuiltinAttributeFallback provides protocol compatibility fallback for question/answer attributes
// getBuiltinAttributeDefaultSources returns the default value_source(s) for a built-in attribute
// Returns nil if the key is not a built-in attribute
func getBuiltinAttributeDefaultSources(key string) []string {
switch key {
case BuiltinQuestionKey:
return []string{RequestBody}
case BuiltinAnswerKey, BuiltinToolCallsKey, BuiltinReasoningKey:
return []string{ResponseStreamingBody, ResponseBody}
default:
return nil
}
}
// shouldProcessBuiltinAttribute checks if a built-in attribute should be processed for the given source
func shouldProcessBuiltinAttribute(key, configuredSource, currentSource string) bool {
// If value_source is configured, use exact match
if configuredSource != "" {
return configuredSource == currentSource
}
// If value_source is not configured and it's a built-in attribute, check default sources
defaultSources := getBuiltinAttributeDefaultSources(key)
for _, src := range defaultSources {
if src == currentSource {
return true
}
}
return false
}
// getBuiltinAttributeFallback provides protocol compatibility fallback for built-in attributes
func getBuiltinAttributeFallback(ctx wrapper.HttpContext, config AIStatisticsConfig, key, source string, body []byte, rule string) interface{} {
switch key {
case BuiltinQuestionKey:
@@ -603,6 +785,37 @@ func getBuiltinAttributeFallback(ctx wrapper.HttpContext, config AIStatisticsCon
return value
}
}
case BuiltinToolCallsKey:
if source == ResponseStreamingBody {
// Get or create buffer from context
var buffer *StreamingToolCallsBuffer
if existingBuffer, ok := ctx.GetContext(CtxStreamingToolCallsBuffer).(*StreamingToolCallsBuffer); ok {
buffer = existingBuffer
}
buffer = extractStreamingToolCalls(body, buffer)
ctx.SetContext(CtxStreamingToolCallsBuffer, buffer)
// Also set tool_calls to user attributes so they appear in ai_log
toolCalls := getToolCallsFromBuffer(buffer)
if len(toolCalls) > 0 {
ctx.SetUserAttribute(BuiltinToolCallsKey, toolCalls)
return toolCalls
}
} else if source == ResponseBody {
if value := gjson.GetBytes(body, ToolCallsPathNonStreaming).Value(); value != nil {
return value
}
}
case BuiltinReasoningKey:
if source == ResponseStreamingBody {
if value := extractStreamingBodyByJsonPath(body, ReasoningPathStreaming, RuleAppend); value != nil && value != "" {
return value
}
} else if source == ResponseBody {
if value := gjson.GetBytes(body, ReasoningPathNonStreaming).Value(); value != nil && value != "" {
return value
}
}
}
return nil
}
@@ -641,6 +854,61 @@ func extractStreamingBodyByJsonPath(data []byte, jsonPath string, rule string) i
return value
}
// debugLogAiLog logs the current user attributes that will be written to ai_log
func debugLogAiLog(ctx wrapper.HttpContext) {
// Get all user attributes as a map
userAttrs := make(map[string]interface{})
// Try to reconstruct from GetUserAttribute (note: this is best-effort)
// The actual attributes are stored internally, we log what we know
if question := ctx.GetUserAttribute("question"); question != nil {
userAttrs["question"] = question
}
if answer := ctx.GetUserAttribute("answer"); answer != nil {
userAttrs["answer"] = answer
}
if reasoning := ctx.GetUserAttribute("reasoning"); reasoning != nil {
userAttrs["reasoning"] = reasoning
}
if toolCalls := ctx.GetUserAttribute("tool_calls"); toolCalls != nil {
userAttrs["tool_calls"] = toolCalls
}
if messages := ctx.GetUserAttribute("messages"); messages != nil {
userAttrs["messages"] = messages
}
if sessionId := ctx.GetUserAttribute("session_id"); sessionId != nil {
userAttrs["session_id"] = sessionId
}
if model := ctx.GetUserAttribute("model"); model != nil {
userAttrs["model"] = model
}
if inputToken := ctx.GetUserAttribute("input_token"); inputToken != nil {
userAttrs["input_token"] = inputToken
}
if outputToken := ctx.GetUserAttribute("output_token"); outputToken != nil {
userAttrs["output_token"] = outputToken
}
if totalToken := ctx.GetUserAttribute("total_token"); totalToken != nil {
userAttrs["total_token"] = totalToken
}
if chatId := ctx.GetUserAttribute("chat_id"); chatId != nil {
userAttrs["chat_id"] = chatId
}
if responseType := ctx.GetUserAttribute("response_type"); responseType != nil {
userAttrs["response_type"] = responseType
}
if llmFirstTokenDuration := ctx.GetUserAttribute("llm_first_token_duration"); llmFirstTokenDuration != nil {
userAttrs["llm_first_token_duration"] = llmFirstTokenDuration
}
if llmServiceDuration := ctx.GetUserAttribute("llm_service_duration"); llmServiceDuration != nil {
userAttrs["llm_service_duration"] = llmServiceDuration
}
// Log the attributes as JSON
logJson, _ := json.Marshal(userAttrs)
log.Debugf("[ai_log] attributes to be written: %s", string(logJson))
}
// Set the tracing span with value.
func setSpanAttribute(key string, value interface{}) {
if value != "" {

View File

@@ -981,3 +981,639 @@ func TestCompleteFlow(t *testing.T) {
})
})
}
// ==================== Built-in Attributes Tests ====================
// 测试配置:历史兼容配置(显式配置 value_source 和 value
var legacyQuestionAnswerConfig = func() json.RawMessage {
data, _ := json.Marshal(map[string]interface{}{
"attributes": []map[string]interface{}{
{
"key": "question",
"value_source": "request_body",
"value": "messages.@reverse.0.content",
"apply_to_log": true,
},
{
"key": "answer",
"value_source": "response_streaming_body",
"value": "choices.0.delta.content",
"rule": "append",
"apply_to_log": true,
},
{
"key": "answer",
"value_source": "response_body",
"value": "choices.0.message.content",
"apply_to_log": true,
},
},
})
return data
}()
// 测试配置:内置属性简化配置(不配置 value_source 和 value
var builtinAttributesConfig = func() json.RawMessage {
data, _ := json.Marshal(map[string]interface{}{
"attributes": []map[string]interface{}{
{
"key": "question",
"apply_to_log": true,
},
{
"key": "answer",
"apply_to_log": true,
},
{
"key": "reasoning",
"apply_to_log": true,
},
{
"key": "tool_calls",
"apply_to_log": true,
},
},
})
return data
}()
// 测试配置session_id 配置
var sessionIdConfig = func() json.RawMessage {
data, _ := json.Marshal(map[string]interface{}{
"session_id_header": "x-custom-session",
"attributes": []map[string]interface{}{
{
"key": "question",
"apply_to_log": true,
},
{
"key": "answer",
"apply_to_log": true,
},
},
})
return data
}()
// TestLegacyConfigCompatibility 测试历史配置兼容性
func TestLegacyConfigCompatibility(t *testing.T) {
test.RunTest(t, func(t *testing.T) {
// 测试使用显式 value_source 和 value 配置的 question/answer
t.Run("legacy question answer config", func(t *testing.T) {
host, status := test.NewTestHost(legacyQuestionAnswerConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is 2+2?"}
]
}`)
action := host.CallOnHttpRequestBody(requestBody)
require.Equal(t, types.ActionContinue, action)
// 3. 处理响应头 (非流式)
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "application/json"},
})
// 4. 处理响应体
responseBody := []byte(`{
"choices": [{"message": {"role": "assistant", "content": "2+2 equals 4."}}],
"model": "gpt-4",
"usage": {"prompt_tokens": 20, "completion_tokens": 10, "total_tokens": 30}
}`)
action = host.CallOnHttpResponseBody(responseBody)
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
// 测试使用显式配置的流式响应
t.Run("legacy streaming answer config", func(t *testing.T) {
host, status := test.NewTestHost(legacyQuestionAnswerConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"stream": true,
"messages": [{"role": "user", "content": "Hello"}]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理流式响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "text/event-stream"},
})
// 4. 处理流式响应体
chunk1 := []byte(`data: {"choices":[{"delta":{"content":"Hello"}}]}`)
host.CallOnHttpStreamingResponseBody(chunk1, false)
chunk2 := []byte(`data: {"choices":[{"delta":{"content":" there!"}}]}`)
host.CallOnHttpStreamingResponseBody(chunk2, true)
host.CompleteHttp()
})
})
}
// TestBuiltinAttributesDefaultSource 测试内置属性的默认 value_source
func TestBuiltinAttributesDefaultSource(t *testing.T) {
test.RunTest(t, func(t *testing.T) {
// 测试不配置 value_source 的内置属性(非流式响应)
t.Run("builtin attributes non-streaming", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体 - question 应该自动从 request_body 提取
requestBody := []byte(`{
"model": "deepseek-reasoner",
"messages": [
{"role": "user", "content": "What is the capital of France?"}
]
}`)
action := host.CallOnHttpRequestBody(requestBody)
require.Equal(t, types.ActionContinue, action)
// 3. 处理响应头 (非流式)
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "application/json"},
})
// 4. 处理响应体 - answer, reasoning, tool_calls 应该自动从 response_body 提取
responseBody := []byte(`{
"choices": [{
"message": {
"role": "assistant",
"content": "The capital of France is Paris.",
"reasoning_content": "The user is asking about geography. France is a country in Europe, and its capital city is Paris."
}
}],
"model": "deepseek-reasoner",
"usage": {"prompt_tokens": 15, "completion_tokens": 25, "total_tokens": 40}
}`)
action = host.CallOnHttpResponseBody(responseBody)
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
// 测试不配置 value_source 的内置属性(流式响应)
t.Run("builtin attributes streaming", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "deepseek-reasoner",
"stream": true,
"messages": [{"role": "user", "content": "Tell me a joke"}]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理流式响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "text/event-stream"},
})
// 4. 处理流式响应体 - answer, reasoning 应该自动从 response_streaming_body 提取
chunk1 := []byte(`data: {"choices":[{"delta":{"reasoning_content":"Let me think of a good joke..."}}]}`)
host.CallOnHttpStreamingResponseBody(chunk1, false)
chunk2 := []byte(`data: {"choices":[{"delta":{"content":"Why did the chicken"}}]}`)
host.CallOnHttpStreamingResponseBody(chunk2, false)
chunk3 := []byte(`data: {"choices":[{"delta":{"content":" cross the road?"}}]}`)
host.CallOnHttpStreamingResponseBody(chunk3, true)
host.CompleteHttp()
})
})
}
// TestStreamingToolCalls 测试流式 tool_calls 解析
func TestStreamingToolCalls(t *testing.T) {
test.RunTest(t, func(t *testing.T) {
// 测试流式 tool_calls 拼接
t.Run("streaming tool calls assembly", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"stream": true,
"messages": [{"role": "user", "content": "What's the weather in Beijing?"}],
"tools": [{"type": "function", "function": {"name": "get_weather"}}]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理流式响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "text/event-stream"},
})
// 4. 处理流式响应体 - 模拟分片的 tool_calls
// 第一个 chunk: tool call 的 id 和 function name
chunk1 := []byte(`data: {"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"id":"call_abc123","type":"function","function":{"name":"get_weather","arguments":""}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk1, false)
// 第二个 chunk: arguments 的第一部分
chunk2 := []byte(`data: {"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"locat"}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk2, false)
// 第三个 chunk: arguments 的第二部分
chunk3 := []byte(`data: {"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ion\": \"Bei"}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk3, false)
// 第四个 chunk: arguments 的最后部分
chunk4 := []byte(`data: {"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"jing\"}"}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk4, false)
// 最后一个 chunk: 结束
chunk5 := []byte(`data: {"choices":[{"index":0,"delta":{},"finish_reason":"tool_calls"}]}`)
host.CallOnHttpStreamingResponseBody(chunk5, true)
host.CompleteHttp()
})
// 测试多个 tool_calls 的流式拼接
t.Run("multiple streaming tool calls", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"stream": true,
"messages": [{"role": "user", "content": "Compare weather in Beijing and Shanghai"}]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理流式响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "text/event-stream"},
})
// 4. 处理流式响应体 - 模拟多个 tool_calls
// 第一个 tool call
chunk1 := []byte(`data: {"choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_001","type":"function","function":{"name":"get_weather","arguments":""}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk1, false)
// 第二个 tool call
chunk2 := []byte(`data: {"choices":[{"delta":{"tool_calls":[{"index":1,"id":"call_002","type":"function","function":{"name":"get_weather","arguments":""}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk2, false)
// 第一个 tool call 的 arguments
chunk3 := []byte(`data: {"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"location\":\"Beijing\"}"}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk3, false)
// 第二个 tool call 的 arguments
chunk4 := []byte(`data: {"choices":[{"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\"location\":\"Shanghai\"}"}}]}}]}`)
host.CallOnHttpStreamingResponseBody(chunk4, false)
// 结束
chunk5 := []byte(`data: {"choices":[{"delta":{},"finish_reason":"tool_calls"}]}`)
host.CallOnHttpStreamingResponseBody(chunk5, true)
host.CompleteHttp()
})
// 测试非流式 tool_calls
t.Run("non-streaming tool calls", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"messages": [{"role": "user", "content": "What's the weather?"}]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "application/json"},
})
// 4. 处理响应体 - 非流式 tool_calls
responseBody := []byte(`{
"choices": [{
"message": {
"role": "assistant",
"content": null,
"tool_calls": [{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"Beijing\"}"
}
}]
},
"finish_reason": "tool_calls"
}],
"model": "gpt-4",
"usage": {"prompt_tokens": 20, "completion_tokens": 15, "total_tokens": 35}
}`)
action := host.CallOnHttpResponseBody(responseBody)
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
})
}
// TestSessionIdExtraction 测试 session_id 提取
func TestSessionIdExtraction(t *testing.T) {
test.RunTest(t, func(t *testing.T) {
// 测试自定义 session_id header
t.Run("custom session id header", func(t *testing.T) {
host, status := test.NewTestHost(sessionIdConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 处理请求头 - 带自定义 session header
action := host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
{"x-custom-session", "sess_custom_123"},
})
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
// 测试默认 session_id headers 优先级
t.Run("default session id headers priority", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 处理请求头 - 带多个默认 session headers应该使用优先级最高的
action := host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
{"x-agent-session", "sess_agent_456"},
{"x-clawdbot-session-key", "sess_clawdbot_789"},
{"x-openclaw-session-key", "sess_openclaw_123"}, // 最高优先级
})
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
// 测试 fallback 到次优先级 header
t.Run("session id fallback", func(t *testing.T) {
host, status := test.NewTestHost(builtinAttributesConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 处理请求头 - 只有低优先级的 session header
action := host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
{"x-agent-session", "sess_agent_only"},
})
require.Equal(t, types.ActionContinue, action)
host.CompleteHttp()
})
})
}
// TestExtractStreamingToolCalls 单独测试 extractStreamingToolCalls 函数
func TestExtractStreamingToolCalls(t *testing.T) {
t.Run("single tool call assembly", func(t *testing.T) {
// 模拟流式 chunks
chunks := [][]byte{
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_123","type":"function","function":{"name":"get_weather","arguments":""}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"loc"}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ation"}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\":\"Beijing\"}"}}]}}]}`),
}
var buffer *StreamingToolCallsBuffer
for _, chunk := range chunks {
buffer = extractStreamingToolCalls(chunk, buffer)
}
toolCalls := getToolCallsFromBuffer(buffer)
require.Len(t, toolCalls, 1)
require.Equal(t, "call_123", toolCalls[0].ID)
require.Equal(t, "function", toolCalls[0].Type)
require.Equal(t, "get_weather", toolCalls[0].Function.Name)
require.Equal(t, `{"location":"Beijing"}`, toolCalls[0].Function.Arguments)
})
t.Run("multiple tool calls assembly", func(t *testing.T) {
chunks := [][]byte{
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_001","type":"function","function":{"name":"get_weather","arguments":""}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":1,"id":"call_002","type":"function","function":{"name":"get_time","arguments":""}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"city\":\"Beijing\"}"}}]}}]}`),
[]byte(`{"choices":[{"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\"timezone\":\"UTC+8\"}"}}]}}]}`),
}
var buffer *StreamingToolCallsBuffer
for _, chunk := range chunks {
buffer = extractStreamingToolCalls(chunk, buffer)
}
toolCalls := getToolCallsFromBuffer(buffer)
require.Len(t, toolCalls, 2)
// 验证第一个 tool call
require.Equal(t, "call_001", toolCalls[0].ID)
require.Equal(t, "get_weather", toolCalls[0].Function.Name)
require.Equal(t, `{"city":"Beijing"}`, toolCalls[0].Function.Arguments)
// 验证第二个 tool call
require.Equal(t, "call_002", toolCalls[1].ID)
require.Equal(t, "get_time", toolCalls[1].Function.Name)
require.Equal(t, `{"timezone":"UTC+8"}`, toolCalls[1].Function.Arguments)
})
t.Run("empty chunks", func(t *testing.T) {
chunks := [][]byte{
[]byte(`{"choices":[{"delta":{}}]}`),
[]byte(`{"choices":[{"delta":{"content":"Hello"}}]}`),
}
var buffer *StreamingToolCallsBuffer
for _, chunk := range chunks {
buffer = extractStreamingToolCalls(chunk, buffer)
}
toolCalls := getToolCallsFromBuffer(buffer)
require.Len(t, toolCalls, 0)
})
}
// TestBuiltinAttributeHelpers 测试内置属性辅助函数
func TestBuiltinAttributeHelpers(t *testing.T) {
t.Run("isBuiltinAttribute", func(t *testing.T) {
require.True(t, isBuiltinAttribute("question"))
require.True(t, isBuiltinAttribute("answer"))
require.True(t, isBuiltinAttribute("tool_calls"))
require.True(t, isBuiltinAttribute("reasoning"))
require.False(t, isBuiltinAttribute("custom_key"))
require.False(t, isBuiltinAttribute("model"))
})
t.Run("getBuiltinAttributeDefaultSources", func(t *testing.T) {
// question 应该默认从 request_body 提取
questionSources := getBuiltinAttributeDefaultSources("question")
require.Equal(t, []string{RequestBody}, questionSources)
// answer 应该支持 streaming 和 non-streaming
answerSources := getBuiltinAttributeDefaultSources("answer")
require.Contains(t, answerSources, ResponseStreamingBody)
require.Contains(t, answerSources, ResponseBody)
// tool_calls 应该支持 streaming 和 non-streaming
toolCallsSources := getBuiltinAttributeDefaultSources("tool_calls")
require.Contains(t, toolCallsSources, ResponseStreamingBody)
require.Contains(t, toolCallsSources, ResponseBody)
// reasoning 应该支持 streaming 和 non-streaming
reasoningSources := getBuiltinAttributeDefaultSources("reasoning")
require.Contains(t, reasoningSources, ResponseStreamingBody)
require.Contains(t, reasoningSources, ResponseBody)
// 非内置属性应该返回 nil
customSources := getBuiltinAttributeDefaultSources("custom_key")
require.Nil(t, customSources)
})
t.Run("shouldProcessBuiltinAttribute", func(t *testing.T) {
// 配置了 value_source 时,应该精确匹配
require.True(t, shouldProcessBuiltinAttribute("question", RequestBody, RequestBody))
require.False(t, shouldProcessBuiltinAttribute("question", RequestBody, ResponseBody))
// 没有配置 value_source 时,内置属性应该使用默认 source
require.True(t, shouldProcessBuiltinAttribute("question", "", RequestBody))
require.False(t, shouldProcessBuiltinAttribute("question", "", ResponseBody))
require.True(t, shouldProcessBuiltinAttribute("answer", "", ResponseBody))
require.True(t, shouldProcessBuiltinAttribute("answer", "", ResponseStreamingBody))
require.False(t, shouldProcessBuiltinAttribute("answer", "", RequestBody))
// 非内置属性没有配置 value_source 时,不应该处理
require.False(t, shouldProcessBuiltinAttribute("custom_key", "", RequestBody))
require.False(t, shouldProcessBuiltinAttribute("custom_key", "", ResponseBody))
})
}
// TestSessionIdDebugOutput 演示session_id的debug日志输出
func TestSessionIdDebugOutput(t *testing.T) {
test.RunTest(t, func(t *testing.T) {
t.Run("session id with full flow", func(t *testing.T) {
host, status := test.NewTestHost(sessionIdConfig)
defer host.Reset()
require.Equal(t, types.OnPluginStartStatusOK, status)
// 1. 处理请求头 - 带 session_id
host.CallOnHttpRequestHeaders([][2]string{
{":authority", "example.com"},
{":path", "/v1/chat/completions"},
{":method", "POST"},
{"x-custom-session", "sess_abc123xyz"},
})
// 2. 处理请求体
requestBody := []byte(`{
"model": "gpt-4",
"messages": [
{"role": "user", "content": "What is 2+2?"}
]
}`)
host.CallOnHttpRequestBody(requestBody)
// 3. 处理响应头
host.CallOnHttpResponseHeaders([][2]string{
{":status", "200"},
{"content-type", "application/json"},
})
// 4. 处理响应体
responseBody := []byte(`{
"choices": [{"message": {"role": "assistant", "content": "2+2 equals 4."}}],
"model": "gpt-4",
"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
}`)
host.CallOnHttpResponseBody(responseBody)
host.CompleteHttp()
})
})
}