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https://github.com/mudler/LocalAI.git
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c88074a19e
This PR adds support to support the 'reasoning' API field of the OpenAI spec. LocalAI now will extract automatically thinking tags in both SSE and non-SSE mode. The changes are adapted as well to the Chat UI now that will use the reasoning field to extract the thinking process and display it in the chat. This fixes https://github.com/mudler/LocalAI/issues/7944 Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
89 lines
2.7 KiB
Go
89 lines
2.7 KiB
Go
package schema
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import (
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"encoding/json"
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"github.com/mudler/xlog"
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"github.com/mudler/LocalAI/pkg/grpc/proto"
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)
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type Message struct {
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// The message role
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Role string `json:"role,omitempty" yaml:"role"`
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// The message name (used for tools calls)
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Name string `json:"name,omitempty" yaml:"name"`
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// The message content
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Content interface{} `json:"content" yaml:"content"`
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StringContent string `json:"string_content,omitempty" yaml:"string_content,omitempty"`
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StringImages []string `json:"string_images,omitempty" yaml:"string_images,omitempty"`
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StringVideos []string `json:"string_videos,omitempty" yaml:"string_videos,omitempty"`
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StringAudios []string `json:"string_audios,omitempty" yaml:"string_audios,omitempty"`
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// A result of a function call
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FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
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ToolCalls []ToolCall `json:"tool_calls,omitempty" yaml:"tool_call,omitempty"`
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// Reasoning content extracted from <thinking>...</thinking> tags
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Reasoning *string `json:"reasoning,omitempty" yaml:"reasoning,omitempty"`
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}
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type ToolCall struct {
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Index int `json:"index"`
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ID string `json:"id"`
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Type string `json:"type"`
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FunctionCall FunctionCall `json:"function"`
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}
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type FunctionCall struct {
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Name string `json:"name,omitempty"`
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Arguments string `json:"arguments"`
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}
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type Messages []Message
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// MessagesToProto converts schema.Message slice to proto.Message slice
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// It handles content conversion, tool_calls serialization, and optional fields
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func (messages Messages) ToProto() []*proto.Message {
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protoMessages := make([]*proto.Message, len(messages))
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for i, message := range messages {
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protoMessages[i] = &proto.Message{
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Role: message.Role,
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Name: message.Name, // needed by function calls
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}
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switch ct := message.Content.(type) {
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case string:
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protoMessages[i].Content = ct
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case []interface{}:
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// If using the tokenizer template, in case of multimodal we want to keep the multimodal content as and return only strings here
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data, _ := json.Marshal(ct)
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resultData := []struct {
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Text string `json:"text"`
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}{}
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json.Unmarshal(data, &resultData)
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for _, r := range resultData {
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protoMessages[i].Content += r.Text
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}
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}
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// Serialize tool_calls to JSON string if present
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if len(message.ToolCalls) > 0 {
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toolCallsJSON, err := json.Marshal(message.ToolCalls)
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if err != nil {
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xlog.Warn("failed to marshal tool_calls to JSON", "error", err)
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} else {
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protoMessages[i].ToolCalls = string(toolCallsJSON)
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}
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}
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// Note: tool_call_id is not in schema.Message yet
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// Reasoning field is now available in schema.Message but not yet in proto.Message
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}
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return protoMessages
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}
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