mirror of
https://github.com/mudler/LocalAI.git
synced 2024-12-19 12:47:54 +00:00
323 lines
9.9 KiB
Go
323 lines
9.9 KiB
Go
package openai
|
|
|
|
import (
|
|
"bufio"
|
|
"bytes"
|
|
"encoding/json"
|
|
"fmt"
|
|
"strings"
|
|
|
|
"github.com/go-skynet/LocalAI/api/backend"
|
|
config "github.com/go-skynet/LocalAI/api/config"
|
|
"github.com/go-skynet/LocalAI/api/options"
|
|
"github.com/go-skynet/LocalAI/pkg/grammar"
|
|
model "github.com/go-skynet/LocalAI/pkg/model"
|
|
"github.com/gofiber/fiber/v2"
|
|
"github.com/rs/zerolog/log"
|
|
"github.com/valyala/fasthttp"
|
|
)
|
|
|
|
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
|
emptyMessage := ""
|
|
|
|
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
|
|
initialMessage := OpenAIResponse{
|
|
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
|
Choices: []Choice{{Delta: &Message{Role: "assistant", Content: &emptyMessage}}},
|
|
Object: "chat.completion.chunk",
|
|
}
|
|
responses <- initialMessage
|
|
|
|
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
|
|
resp := OpenAIResponse{
|
|
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
|
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
|
|
Object: "chat.completion.chunk",
|
|
}
|
|
|
|
responses <- resp
|
|
return true
|
|
})
|
|
close(responses)
|
|
}
|
|
return func(c *fiber.Ctx) error {
|
|
processFunctions := false
|
|
funcs := grammar.Functions{}
|
|
model, input, err := readInput(c, o.Loader, true)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
|
|
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
|
if err != nil {
|
|
return fmt.Errorf("failed reading parameters from request:%w", err)
|
|
}
|
|
log.Debug().Msgf("Configuration read: %+v", config)
|
|
|
|
// Allow the user to set custom actions via config file
|
|
// to be "embedded" in each model
|
|
noActionName := "answer"
|
|
noActionDescription := "use this action to answer without performing any action"
|
|
|
|
if config.FunctionsConfig.NoActionFunctionName != "" {
|
|
noActionName = config.FunctionsConfig.NoActionFunctionName
|
|
}
|
|
if config.FunctionsConfig.NoActionDescriptionName != "" {
|
|
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
|
|
}
|
|
|
|
// process functions if we have any defined or if we have a function call string
|
|
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
|
|
log.Debug().Msgf("Response needs to process functions")
|
|
|
|
processFunctions = true
|
|
|
|
noActionGrammar := grammar.Function{
|
|
Name: noActionName,
|
|
Description: noActionDescription,
|
|
Parameters: map[string]interface{}{
|
|
"properties": map[string]interface{}{
|
|
"message": map[string]interface{}{
|
|
"type": "string",
|
|
"description": "The message to reply the user with",
|
|
}},
|
|
},
|
|
}
|
|
|
|
// Append the no action function
|
|
funcs = append(funcs, input.Functions...)
|
|
if !config.FunctionsConfig.DisableNoAction {
|
|
funcs = append(funcs, noActionGrammar)
|
|
}
|
|
|
|
// Force picking one of the functions by the request
|
|
if config.FunctionToCall() != "" {
|
|
funcs = funcs.Select(config.FunctionToCall())
|
|
}
|
|
|
|
// Update input grammar
|
|
jsStruct := funcs.ToJSONStructure()
|
|
config.Grammar = jsStruct.Grammar("")
|
|
} else if input.JSONFunctionGrammarObject != nil {
|
|
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
|
|
}
|
|
|
|
// functions are not supported in stream mode (yet?)
|
|
toStream := input.Stream && !processFunctions
|
|
|
|
log.Debug().Msgf("Parameters: %+v", config)
|
|
|
|
var predInput string
|
|
|
|
mess := []string{}
|
|
for _, i := range input.Messages {
|
|
var content string
|
|
role := i.Role
|
|
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
|
|
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
|
|
if i.FunctionCall != nil && i.Role == "assistant" {
|
|
roleFn := "assistant_function_call"
|
|
r := config.Roles[roleFn]
|
|
if r != "" {
|
|
role = roleFn
|
|
}
|
|
}
|
|
r := config.Roles[role]
|
|
contentExists := i.Content != nil && *i.Content != ""
|
|
if r != "" {
|
|
if contentExists {
|
|
content = fmt.Sprint(r, " ", *i.Content)
|
|
}
|
|
if i.FunctionCall != nil {
|
|
j, err := json.Marshal(i.FunctionCall)
|
|
if err == nil {
|
|
if contentExists {
|
|
content += "\n" + fmt.Sprint(r, " ", string(j))
|
|
} else {
|
|
content = fmt.Sprint(r, " ", string(j))
|
|
}
|
|
}
|
|
}
|
|
} else {
|
|
if contentExists {
|
|
content = fmt.Sprint(*i.Content)
|
|
}
|
|
if i.FunctionCall != nil {
|
|
j, err := json.Marshal(i.FunctionCall)
|
|
if err == nil {
|
|
if contentExists {
|
|
content += "\n" + string(j)
|
|
} else {
|
|
content = string(j)
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
mess = append(mess, content)
|
|
}
|
|
|
|
predInput = strings.Join(mess, "\n")
|
|
log.Debug().Msgf("Prompt (before templating): %s", predInput)
|
|
|
|
if toStream {
|
|
log.Debug().Msgf("Stream request received")
|
|
c.Context().SetContentType("text/event-stream")
|
|
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
|
// c.Set("Content-Type", "text/event-stream")
|
|
c.Set("Cache-Control", "no-cache")
|
|
c.Set("Connection", "keep-alive")
|
|
c.Set("Transfer-Encoding", "chunked")
|
|
}
|
|
|
|
templateFile := config.Model
|
|
|
|
if config.TemplateConfig.Chat != "" && !processFunctions {
|
|
templateFile = config.TemplateConfig.Chat
|
|
}
|
|
|
|
if config.TemplateConfig.Functions != "" && processFunctions {
|
|
templateFile = config.TemplateConfig.Functions
|
|
}
|
|
|
|
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
|
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
|
|
Input string
|
|
Functions []grammar.Function
|
|
}{
|
|
Input: predInput,
|
|
Functions: funcs,
|
|
})
|
|
if err == nil {
|
|
predInput = templatedInput
|
|
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
|
} else {
|
|
log.Debug().Msgf("Template failed loading: %s", err.Error())
|
|
}
|
|
|
|
log.Debug().Msgf("Prompt (after templating): %s", predInput)
|
|
if processFunctions {
|
|
log.Debug().Msgf("Grammar: %+v", config.Grammar)
|
|
}
|
|
|
|
if toStream {
|
|
responses := make(chan OpenAIResponse)
|
|
|
|
go process(predInput, input, config, o.Loader, responses)
|
|
|
|
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
|
|
|
for ev := range responses {
|
|
var buf bytes.Buffer
|
|
enc := json.NewEncoder(&buf)
|
|
enc.Encode(ev)
|
|
|
|
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
|
fmt.Fprintf(w, "data: %v\n", buf.String())
|
|
w.Flush()
|
|
}
|
|
|
|
resp := &OpenAIResponse{
|
|
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
|
Choices: []Choice{
|
|
{
|
|
FinishReason: "stop",
|
|
Index: 0,
|
|
Delta: &Message{Content: &emptyMessage},
|
|
}},
|
|
Object: "chat.completion.chunk",
|
|
}
|
|
respData, _ := json.Marshal(resp)
|
|
|
|
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
|
w.WriteString("data: [DONE]\n\n")
|
|
w.Flush()
|
|
}))
|
|
return nil
|
|
}
|
|
|
|
result, err := ComputeChoices(predInput, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
|
|
if processFunctions {
|
|
// As we have to change the result before processing, we can't stream the answer (yet?)
|
|
ss := map[string]interface{}{}
|
|
json.Unmarshal([]byte(s), &ss)
|
|
log.Debug().Msgf("Function return: %s %+v", s, ss)
|
|
|
|
// The grammar defines the function name as "function", while OpenAI returns "name"
|
|
func_name := ss["function"]
|
|
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
|
|
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
|
|
d, _ := json.Marshal(args)
|
|
|
|
ss["arguments"] = string(d)
|
|
ss["name"] = func_name
|
|
|
|
// if do nothing, reply with a message
|
|
if func_name == noActionName {
|
|
log.Debug().Msgf("nothing to do, computing a reply")
|
|
|
|
// If there is a message that the LLM already sends as part of the JSON reply, use it
|
|
arguments := map[string]interface{}{}
|
|
json.Unmarshal([]byte(d), &arguments)
|
|
m, exists := arguments["message"]
|
|
if exists {
|
|
switch message := m.(type) {
|
|
case string:
|
|
if message != "" {
|
|
log.Debug().Msgf("Reply received from LLM: %s", message)
|
|
message = backend.Finetune(*config, predInput, message)
|
|
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
|
|
|
|
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
|
|
return
|
|
}
|
|
}
|
|
}
|
|
|
|
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
|
|
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
|
|
// Note: This costs (in term of CPU) another computation
|
|
config.Grammar = ""
|
|
predFunc, err := backend.ModelInference(predInput, o.Loader, *config, o, nil)
|
|
if err != nil {
|
|
log.Error().Msgf("inference error: %s", err.Error())
|
|
return
|
|
}
|
|
|
|
prediction, err := predFunc()
|
|
if err != nil {
|
|
log.Error().Msgf("inference error: %s", err.Error())
|
|
return
|
|
}
|
|
|
|
prediction = backend.Finetune(*config, predInput, prediction)
|
|
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
|
|
} else {
|
|
// otherwise reply with the function call
|
|
*c = append(*c, Choice{
|
|
FinishReason: "function_call",
|
|
Message: &Message{Role: "assistant", FunctionCall: ss},
|
|
})
|
|
}
|
|
|
|
return
|
|
}
|
|
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &s}})
|
|
}, nil)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
resp := &OpenAIResponse{
|
|
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
|
Choices: result,
|
|
Object: "chat.completion",
|
|
}
|
|
respData, _ := json.Marshal(resp)
|
|
log.Debug().Msgf("Response: %s", respData)
|
|
|
|
// Return the prediction in the response body
|
|
return c.JSON(resp)
|
|
}
|
|
}
|