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Commit 42a29e48 by Calcium-Ion Committed by GitHub
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Merge pull request #1811 from somnifex/main 

refactor: 重构ollama渠道
parents 4bbd59c7 8c678965
Showing with 442 additions and 171 deletions
relay/channel/ollama/adaptor.go
......@@ -10,6 +10,7 @@ import (
relaycommon "one-api/relay/common"
relayconstant "one-api/relay/constant"
"one-api/types"
"strings"
"github.com/gin-gonic/gin"
)
......@@ -17,10 +18,7 @@ import (
type Adaptor struct {
}
func (a *Adaptor) ConvertGeminiRequest(*gin.Context, *relaycommon.RelayInfo, *dto.GeminiChatRequest) (any, error) {
//TODO implement me
return nil, errors.New("not implemented")
}
func (a *Adaptor) ConvertGeminiRequest(*gin.Context, *relaycommon.RelayInfo, *dto.GeminiChatRequest) (any, error) { return nil, errors.New("not implemented") }
func (a *Adaptor) ConvertClaudeRequest(c *gin.Context, info *relaycommon.RelayInfo, request *dto.ClaudeRequest) (any, error) {
openaiAdaptor := openai.Adaptor{}
......@@ -31,32 +29,21 @@ func (a *Adaptor) ConvertClaudeRequest(c *gin.Context, info *relaycommon.RelayIn
openaiRequest.(*dto.GeneralOpenAIRequest).StreamOptions = &dto.StreamOptions{
IncludeUsage: true,
}
return requestOpenAI2Ollama(c, openaiRequest.(*dto.GeneralOpenAIRequest))
// map to ollama chat request (Claude -> OpenAI -> Ollama chat)
return openAIChatToOllamaChat(c, openaiRequest.(*dto.GeneralOpenAIRequest))
}
func (a *Adaptor) ConvertAudioRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.AudioRequest) (io.Reader, error) {
//TODO implement me
return nil, errors.New("not implemented")
}
func (a *Adaptor) ConvertAudioRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.AudioRequest) (io.Reader, error) { return nil, errors.New("not implemented") }
func (a *Adaptor) ConvertImageRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.ImageRequest) (any, error) {
//TODO implement me
return nil, errors.New("not implemented")
}
func (a *Adaptor) ConvertImageRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.ImageRequest) (any, error) { return nil, errors.New("not implemented") }
func (a *Adaptor) Init(info *relaycommon.RelayInfo) {
}
func (a *Adaptor) GetRequestURL(info *relaycommon.RelayInfo) (string, error) {
if info.RelayFormat == types.RelayFormatClaude {
return info.ChannelBaseUrl + "/v1/chat/completions", nil
}
switch info.RelayMode {
case relayconstant.RelayModeEmbeddings:
return info.ChannelBaseUrl + "/api/embed", nil
default:
return relaycommon.GetFullRequestURL(info.ChannelBaseUrl, info.RequestURLPath, info.ChannelType), nil
}
if info.RelayMode == relayconstant.RelayModeEmbeddings { return info.ChannelBaseUrl + "/api/embed", nil }
if strings.Contains(info.RequestURLPath, "/v1/completions") || info.RelayMode == relayconstant.RelayModeCompletions { return info.ChannelBaseUrl + "/api/generate", nil }
return info.ChannelBaseUrl + "/api/chat", nil
}
func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Header, info *relaycommon.RelayInfo) error {
......@@ -66,10 +53,12 @@ func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Header, info *rel
}
func (a *Adaptor) ConvertOpenAIRequest(c *gin.Context, info *relaycommon.RelayInfo, request *dto.GeneralOpenAIRequest) (any, error) {
if request == nil {
return nil, errors.New("request is nil")
if request == nil { return nil, errors.New("request is nil") }
// decide generate or chat
if strings.Contains(info.RequestURLPath, "/v1/completions") || info.RelayMode == relayconstant.RelayModeCompletions {
return openAIToGenerate(c, request)
}
return requestOpenAI2Ollama(c, request)
return openAIChatToOllamaChat(c, request)
}
func (a *Adaptor) ConvertRerankRequest(c *gin.Context, relayMode int, request dto.RerankRequest) (any, error) {
......@@ -80,10 +69,7 @@ func (a *Adaptor) ConvertEmbeddingRequest(c *gin.Context, info *relaycommon.Rela
return requestOpenAI2Embeddings(request), nil
}
func (a *Adaptor) ConvertOpenAIResponsesRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.OpenAIResponsesRequest) (any, error) {
// TODO implement me
return nil, errors.New("not implemented")
}
func (a *Adaptor) ConvertOpenAIResponsesRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.OpenAIResponsesRequest) (any, error) { return nil, errors.New("not implemented") }
func (a *Adaptor) DoRequest(c *gin.Context, info *relaycommon.RelayInfo, requestBody io.Reader) (any, error) {
return channel.DoApiRequest(a, c, info, requestBody)
......@@ -92,15 +78,13 @@ func (a *Adaptor) DoRequest(c *gin.Context, info *relaycommon.RelayInfo, request
func (a *Adaptor) DoResponse(c *gin.Context, resp *http.Response, info *relaycommon.RelayInfo) (usage any, err *types.NewAPIError) {
switch info.RelayMode {
case relayconstant.RelayModeEmbeddings:
usage, err = ollamaEmbeddingHandler(c, info, resp)
return ollamaEmbeddingHandler(c, info, resp)
default:
if info.IsStream {
usage, err = openai.OaiStreamHandler(c, info, resp)
} else {
usage, err = openai.OpenaiHandler(c, info, resp)
return ollamaStreamHandler(c, info, resp)
}
return ollamaChatHandler(c, info, resp)
}
return
}
func (a *Adaptor) GetModelList() []string {
......
relay/channel/ollama/dto.go
......@@ -2,48 +2,69 @@ package ollama
import (
"encoding/json"
"one-api/dto"
)
type OllamaRequest struct {
Model string `json:"model,omitempty"`
Messages []dto.Message `json:"messages,omitempty"`
Stream bool `json:"stream,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
Seed float64 `json:"seed,omitempty"`
Topp float64 `json:"top_p,omitempty"`
TopK int `json:"top_k,omitempty"`
Stop any `json:"stop,omitempty"`
MaxTokens uint `json:"max_tokens,omitempty"`
Tools []dto.ToolCallRequest `json:"tools,omitempty"`
ResponseFormat any `json:"response_format,omitempty"`
FrequencyPenalty float64 `json:"frequency_penalty,omitempty"`
PresencePenalty float64 `json:"presence_penalty,omitempty"`
Suffix any `json:"suffix,omitempty"`
StreamOptions *dto.StreamOptions `json:"stream_options,omitempty"`
Prompt any `json:"prompt,omitempty"`
Think json.RawMessage `json:"think,omitempty"`
}
type Options struct {
Seed int `json:"seed,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopK int `json:"top_k,omitempty"`
TopP float64 `json:"top_p,omitempty"`
FrequencyPenalty float64 `json:"frequency_penalty,omitempty"`
PresencePenalty float64 `json:"presence_penalty,omitempty"`
NumPredict int `json:"num_predict,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
type OllamaChatMessage struct {
Role string `json:"role"`
Content string `json:"content,omitempty"`
Images []string `json:"images,omitempty"`
ToolCalls []OllamaToolCall `json:"tool_calls,omitempty"`
ToolName string `json:"tool_name,omitempty"`
Thinking json.RawMessage `json:"thinking,omitempty"`
}
type OllamaToolFunction struct {
Name string `json:"name"`
Description string `json:"description,omitempty"`
Parameters interface{} `json:"parameters,omitempty"`
}
type OllamaTool struct {
Type string `json:"type"`
Function OllamaToolFunction `json:"function"`
}
type OllamaToolCall struct {
Function struct {
Name string `json:"name"`
Arguments interface{} `json:"arguments"`
} `json:"function"`
}
type OllamaChatRequest struct {
Model string `json:"model"`
Messages []OllamaChatMessage `json:"messages"`
Tools interface{} `json:"tools,omitempty"`
Format interface{} `json:"format,omitempty"`
Stream bool `json:"stream,omitempty"`
Options map[string]any `json:"options,omitempty"`
KeepAlive interface{} `json:"keep_alive,omitempty"`
Think json.RawMessage `json:"think,omitempty"`
}
type OllamaGenerateRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt,omitempty"`
Suffix string `json:"suffix,omitempty"`
Images []string `json:"images,omitempty"`
Format interface{} `json:"format,omitempty"`
Stream bool `json:"stream,omitempty"`
Options map[string]any `json:"options,omitempty"`
KeepAlive interface{} `json:"keep_alive,omitempty"`
Think json.RawMessage `json:"think,omitempty"`
}
type OllamaEmbeddingRequest struct {
Model string `json:"model,omitempty"`
Input []string `json:"input"`
Options *Options `json:"options,omitempty"`
Model string `json:"model"`
Input interface{} `json:"input"`
Options map[string]any `json:"options,omitempty"`
Dimensions int `json:"dimensions,omitempty"`
}
type OllamaEmbeddingResponse struct {
Error string `json:"error,omitempty"`
Model string `json:"model"`
Embedding [][]float64 `json:"embeddings,omitempty"`
Error string `json:"error,omitempty"`
Model string `json:"model"`
Embeddings [][]float64 `json:"embeddings"`
PromptEvalCount int `json:"prompt_eval_count,omitempty"`
}
relay/channel/ollama/relay-ollama.go
package ollama
import (
"encoding/json"
"fmt"
"io"
"net/http"
......@@ -14,121 +15,176 @@ import (
"github.com/gin-gonic/gin"
)
func requestOpenAI2Ollama(c *gin.Context, request *dto.GeneralOpenAIRequest) (*OllamaRequest, error) {
messages := make([]dto.Message, 0, len(request.Messages))
for _, message := range request.Messages {
if !message.IsStringContent() {
mediaMessages := message.ParseContent()
for j, mediaMessage := range mediaMessages {
if mediaMessage.Type == dto.ContentTypeImageURL {
imageUrl := mediaMessage.GetImageMedia()
// check if not base64
if strings.HasPrefix(imageUrl.Url, "http") {
fileData, err := service.GetFileBase64FromUrl(c, imageUrl.Url, "formatting image for Ollama")
if err != nil {
return nil, err
func openAIChatToOllamaChat(c *gin.Context, r *dto.GeneralOpenAIRequest) (*OllamaChatRequest, error) {
chatReq := &OllamaChatRequest{
Model: r.Model,
Stream: r.Stream,
Options: map[string]any{},
Think: r.Think,
}
if r.ResponseFormat != nil {
if r.ResponseFormat.Type == "json" {
chatReq.Format = "json"
} else if r.ResponseFormat.Type == "json_schema" {
if len(r.ResponseFormat.JsonSchema) > 0 {
var schema any
_ = json.Unmarshal(r.ResponseFormat.JsonSchema, &schema)
chatReq.Format = schema
}
}
}
// options mapping
if r.Temperature != nil { chatReq.Options["temperature"] = r.Temperature }
if r.TopP != 0 { chatReq.Options["top_p"] = r.TopP }
if r.TopK != 0 { chatReq.Options["top_k"] = r.TopK }
if r.FrequencyPenalty != 0 { chatReq.Options["frequency_penalty"] = r.FrequencyPenalty }
if r.PresencePenalty != 0 { chatReq.Options["presence_penalty"] = r.PresencePenalty }
if r.Seed != 0 { chatReq.Options["seed"] = int(r.Seed) }
if mt := r.GetMaxTokens(); mt != 0 { chatReq.Options["num_predict"] = int(mt) }
if r.Stop != nil {
switch v := r.Stop.(type) {
case string:
chatReq.Options["stop"] = []string{v}
case []string:
chatReq.Options["stop"] = v
case []any:
arr := make([]string,0,len(v))
for _, i := range v { if s,ok:=i.(string); ok { arr = append(arr,s) } }
if len(arr)>0 { chatReq.Options["stop"] = arr }
}
}
if len(r.Tools) > 0 {
tools := make([]OllamaTool,0,len(r.Tools))
for _, t := range r.Tools {
tools = append(tools, OllamaTool{Type: "function", Function: OllamaToolFunction{Name: t.Function.Name, Description: t.Function.Description, Parameters: t.Function.Parameters}})
}
chatReq.Tools = tools
}
chatReq.Messages = make([]OllamaChatMessage,0,len(r.Messages))
for _, m := range r.Messages {
var textBuilder strings.Builder
var images []string
if m.IsStringContent() {
textBuilder.WriteString(m.StringContent())
} else {
parts := m.ParseContent()
for _, part := range parts {
if part.Type == dto.ContentTypeImageURL {
img := part.GetImageMedia()
if img != nil && img.Url != "" {
var base64Data string
if strings.HasPrefix(img.Url, "http") {
fileData, err := service.GetFileBase64FromUrl(c, img.Url, "fetch image for ollama chat")
if err != nil { return nil, err }
base64Data = fileData.Base64Data
} else if strings.HasPrefix(img.Url, "data:") {
if idx := strings.Index(img.Url, ","); idx != -1 && idx+1 < len(img.Url) { base64Data = img.Url[idx+1:] }
} else {
base64Data = img.Url
}
imageUrl.Url = fmt.Sprintf("data:%s;base64,%s", fileData.MimeType, fileData.Base64Data)
if base64Data != "" { images = append(images, base64Data) }
}
mediaMessage.ImageUrl = imageUrl
mediaMessages[j] = mediaMessage
} else if part.Type == dto.ContentTypeText {
textBuilder.WriteString(part.Text)
}
}
}
cm := OllamaChatMessage{Role: m.Role, Content: textBuilder.String()}
if len(images)>0 { cm.Images = images }
if m.Role == "tool" && m.Name != nil { cm.ToolName = *m.Name }
if m.ToolCalls != nil && len(m.ToolCalls) > 0 {
parsed := m.ParseToolCalls()
if len(parsed) > 0 {
calls := make([]OllamaToolCall,0,len(parsed))
for _, tc := range parsed {
var args interface{}
if tc.Function.Arguments != "" { _ = json.Unmarshal([]byte(tc.Function.Arguments), &args) }
if args==nil { args = map[string]any{} }
oc := OllamaToolCall{}
oc.Function.Name = tc.Function.Name
oc.Function.Arguments = args
calls = append(calls, oc)
}
cm.ToolCalls = calls
}
message.SetMediaContent(mediaMessages)
}
messages = append(messages, dto.Message{
Role: message.Role,
Content: message.Content,
ToolCalls: message.ToolCalls,
ToolCallId: message.ToolCallId,
})
chatReq.Messages = append(chatReq.Messages, cm)
}
str, ok := request.Stop.(string)
var Stop []string
if ok {
Stop = []string{str}
} else {
Stop, _ = request.Stop.([]string)
return chatReq, nil
}
// openAIToGenerate converts OpenAI completions request to Ollama generate
func openAIToGenerate(c *gin.Context, r *dto.GeneralOpenAIRequest) (*OllamaGenerateRequest, error) {
gen := &OllamaGenerateRequest{
Model: r.Model,
Stream: r.Stream,
Options: map[string]any{},
Think: r.Think,
}
// Prompt may be in r.Prompt (string or []any)
if r.Prompt != nil {
switch v := r.Prompt.(type) {
case string:
gen.Prompt = v
case []any:
var sb strings.Builder
for _, it := range v { if s,ok:=it.(string); ok { sb.WriteString(s) } }
gen.Prompt = sb.String()
default:
gen.Prompt = fmt.Sprintf("%v", r.Prompt)
}
}
ollamaRequest := &OllamaRequest{
Model: request.Model,
Messages: messages,
Stream: request.Stream,
Temperature: request.Temperature,
Seed: request.Seed,
Topp: request.TopP,
TopK: request.TopK,
Stop: Stop,
Tools: request.Tools,
MaxTokens: request.GetMaxTokens(),
ResponseFormat: request.ResponseFormat,
FrequencyPenalty: request.FrequencyPenalty,
PresencePenalty: request.PresencePenalty,
Prompt: request.Prompt,
StreamOptions: request.StreamOptions,
Suffix: request.Suffix,
if r.Suffix != nil { if s,ok:=r.Suffix.(string); ok { gen.Suffix = s } }
if r.ResponseFormat != nil {
if r.ResponseFormat.Type == "json" { gen.Format = "json" } else if r.ResponseFormat.Type == "json_schema" { var schema any; _ = json.Unmarshal(r.ResponseFormat.JsonSchema,&schema); gen.Format=schema }
}
ollamaRequest.Think = request.Think
return ollamaRequest, nil
if r.Temperature != nil { gen.Options["temperature"] = r.Temperature }
if r.TopP != 0 { gen.Options["top_p"] = r.TopP }
if r.TopK != 0 { gen.Options["top_k"] = r.TopK }
if r.FrequencyPenalty != 0 { gen.Options["frequency_penalty"] = r.FrequencyPenalty }
if r.PresencePenalty != 0 { gen.Options["presence_penalty"] = r.PresencePenalty }
if r.Seed != 0 { gen.Options["seed"] = int(r.Seed) }
if mt := r.GetMaxTokens(); mt != 0 { gen.Options["num_predict"] = int(mt) }
if r.Stop != nil {
switch v := r.Stop.(type) {
case string: gen.Options["stop"] = []string{v}
case []string: gen.Options["stop"] = v
case []any: arr:=make([]string,0,len(v)); for _,i:= range v { if s,ok:=i.(string); ok { arr=append(arr,s) } }; if len(arr)>0 { gen.Options["stop"]=arr }
}
}
return gen, nil
}
func requestOpenAI2Embeddings(request dto.EmbeddingRequest) *OllamaEmbeddingRequest {
return &OllamaEmbeddingRequest{
Model: request.Model,
Input: request.ParseInput(),
Options: &Options{
Seed: int(request.Seed),
Temperature: request.Temperature,
TopP: request.TopP,
FrequencyPenalty: request.FrequencyPenalty,
PresencePenalty: request.PresencePenalty,
},
}
func requestOpenAI2Embeddings(r dto.EmbeddingRequest) *OllamaEmbeddingRequest {
opts := map[string]any{}
if r.Temperature != nil { opts["temperature"] = r.Temperature }
if r.TopP != 0 { opts["top_p"] = r.TopP }
if r.FrequencyPenalty != 0 { opts["frequency_penalty"] = r.FrequencyPenalty }
if r.PresencePenalty != 0 { opts["presence_penalty"] = r.PresencePenalty }
if r.Seed != 0 { opts["seed"] = int(r.Seed) }
if r.Dimensions != 0 { opts["dimensions"] = r.Dimensions }
input := r.ParseInput()
if len(input)==1 { return &OllamaEmbeddingRequest{Model:r.Model, Input: input[0], Options: opts, Dimensions:r.Dimensions} }
return &OllamaEmbeddingRequest{Model:r.Model, Input: input, Options: opts, Dimensions:r.Dimensions}
}
func ollamaEmbeddingHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
var ollamaEmbeddingResponse OllamaEmbeddingResponse
responseBody, err := io.ReadAll(resp.Body)
if err != nil {
return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
var oResp OllamaEmbeddingResponse
body, err := io.ReadAll(resp.Body)
if err != nil { return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError) }
service.CloseResponseBodyGracefully(resp)
err = common.Unmarshal(responseBody, &ollamaEmbeddingResponse)
if err != nil {
return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
if ollamaEmbeddingResponse.Error != "" {
return nil, types.NewOpenAIError(fmt.Errorf("ollama error: %s", ollamaEmbeddingResponse.Error), types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
flattenedEmbeddings := flattenEmbeddings(ollamaEmbeddingResponse.Embedding)
data := make([]dto.OpenAIEmbeddingResponseItem, 0, 1)
data = append(data, dto.OpenAIEmbeddingResponseItem{
Embedding: flattenedEmbeddings,
Object: "embedding",
})
usage := &dto.Usage{
TotalTokens: info.PromptTokens,
CompletionTokens: 0,
PromptTokens: info.PromptTokens,
}
embeddingResponse := &dto.OpenAIEmbeddingResponse{
Object: "list",
Data: data,
Model: info.UpstreamModelName,
Usage: *usage,
}
doResponseBody, err := common.Marshal(embeddingResponse)
if err != nil {
return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
service.IOCopyBytesGracefully(c, resp, doResponseBody)
if err = common.Unmarshal(body, &oResp); err != nil { return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError) }
if oResp.Error != "" { return nil, types.NewOpenAIError(fmt.Errorf("ollama error: %s", oResp.Error), types.ErrorCodeBadResponseBody, http.StatusInternalServerError) }
data := make([]dto.OpenAIEmbeddingResponseItem,0,len(oResp.Embeddings))
for i, emb := range oResp.Embeddings { data = append(data, dto.OpenAIEmbeddingResponseItem{Index:i,Object:"embedding",Embedding:emb}) }
usage := &dto.Usage{PromptTokens: oResp.PromptEvalCount, CompletionTokens:0, TotalTokens: oResp.PromptEvalCount}
embResp := &dto.OpenAIEmbeddingResponse{Object:"list", Data:data, Model: info.UpstreamModelName, Usage:*usage}
out, _ := common.Marshal(embResp)
service.IOCopyBytesGracefully(c, resp, out)
return usage, nil
}
func flattenEmbeddings(embeddings [][]float64) []float64 {
flattened := []float64{}
for _, row := range embeddings {
flattened = append(flattened, row...)
}
return flattened
}
relay/channel/ollama/stream.go 0 → 100644
package ollama
import (
"bufio"
"encoding/json"
"fmt"
"io"
"net/http"
"one-api/common"
"one-api/dto"
"one-api/logger"
relaycommon "one-api/relay/common"
"one-api/relay/helper"
"one-api/service"
"one-api/types"
"strings"
"time"
"github.com/gin-gonic/gin"
)
type ollamaChatStreamChunk struct {
Model string `json:"model"`
CreatedAt string `json:"created_at"`
// chat
Message *struct {
Role string `json:"role"`
Content string `json:"content"`
Thinking json.RawMessage `json:"thinking"`
ToolCalls []struct {
Function struct {
Name string `json:"name"`
Arguments interface{} `json:"arguments"`
} `json:"function"`
} `json:"tool_calls"`
} `json:"message"`
// generate
Response string `json:"response"`
Done bool `json:"done"`
DoneReason string `json:"done_reason"`
TotalDuration int64 `json:"total_duration"`
LoadDuration int64 `json:"load_duration"`
PromptEvalCount int `json:"prompt_eval_count"`
EvalCount int `json:"eval_count"`
PromptEvalDuration int64 `json:"prompt_eval_duration"`
EvalDuration int64 `json:"eval_duration"`
}
func toUnix(ts string) int64 {
if ts == "" { return time.Now().Unix() }
// try time.RFC3339 or with nanoseconds
t, err := time.Parse(time.RFC3339Nano, ts)
if err != nil { t2, err2 := time.Parse(time.RFC3339, ts); if err2==nil { return t2.Unix() }; return time.Now().Unix() }
return t.Unix()
}
func ollamaStreamHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
if resp == nil || resp.Body == nil { return nil, types.NewOpenAIError(fmt.Errorf("empty response"), types.ErrorCodeBadResponse, http.StatusBadRequest) }
defer service.CloseResponseBodyGracefully(resp)
helper.SetEventStreamHeaders(c)
scanner := bufio.NewScanner(resp.Body)
usage := &dto.Usage{}
var model = info.UpstreamModelName
var responseId = common.GetUUID()
var created = time.Now().Unix()
var toolCallIndex int
start := helper.GenerateStartEmptyResponse(responseId, created, model, nil)
if data, err := common.Marshal(start); err == nil { _ = helper.StringData(c, string(data)) }
for scanner.Scan() {
line := scanner.Text()
line = strings.TrimSpace(line)
if line == "" { continue }
var chunk ollamaChatStreamChunk
if err := json.Unmarshal([]byte(line), &chunk); err != nil {
logger.LogError(c, "ollama stream json decode error: "+err.Error()+" line="+line)
return usage, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
}
if chunk.Model != "" { model = chunk.Model }
created = toUnix(chunk.CreatedAt)
if !chunk.Done {
// delta content
var content string
if chunk.Message != nil { content = chunk.Message.Content } else { content = chunk.Response }
delta := dto.ChatCompletionsStreamResponse{
Id: responseId,
Object: "chat.completion.chunk",
Created: created,
Model: model,
Choices: []dto.ChatCompletionsStreamResponseChoice{ {
Index: 0,
Delta: dto.ChatCompletionsStreamResponseChoiceDelta{ Role: "assistant" },
} },
}
if content != "" { delta.Choices[0].Delta.SetContentString(content) }
if chunk.Message != nil && len(chunk.Message.Thinking) > 0 {
raw := strings.TrimSpace(string(chunk.Message.Thinking))
if raw != "" && raw != "null" { delta.Choices[0].Delta.SetReasoningContent(raw) }
}
// tool calls
if chunk.Message != nil && len(chunk.Message.ToolCalls) > 0 {
delta.Choices[0].Delta.ToolCalls = make([]dto.ToolCallResponse,0,len(chunk.Message.ToolCalls))
for _, tc := range chunk.Message.ToolCalls {
// arguments -> string
argBytes, _ := json.Marshal(tc.Function.Arguments)
toolId := fmt.Sprintf("call_%d", toolCallIndex)
tr := dto.ToolCallResponse{ID:toolId, Type:"function", Function: dto.FunctionResponse{Name: tc.Function.Name, Arguments: string(argBytes)}}
tr.SetIndex(toolCallIndex)
toolCallIndex++
delta.Choices[0].Delta.ToolCalls = append(delta.Choices[0].Delta.ToolCalls, tr)
}
}
if data, err := common.Marshal(delta); err == nil { _ = helper.StringData(c, string(data)) }
continue
}
// done frame
// finalize once and break loop
usage.PromptTokens = chunk.PromptEvalCount
usage.CompletionTokens = chunk.EvalCount
usage.TotalTokens = usage.PromptTokens + usage.CompletionTokens
finishReason := chunk.DoneReason
if finishReason == "" { finishReason = "stop" }
// emit stop delta
if stop := helper.GenerateStopResponse(responseId, created, model, finishReason); stop != nil {
if data, err := common.Marshal(stop); err == nil { _ = helper.StringData(c, string(data)) }
}
// emit usage frame
if final := helper.GenerateFinalUsageResponse(responseId, created, model, *usage); final != nil {
if data, err := common.Marshal(final); err == nil { _ = helper.StringData(c, string(data)) }
}
// send [DONE]
helper.Done(c)
break
}
if err := scanner.Err(); err != nil && err != io.EOF { logger.LogError(c, "ollama stream scan error: "+err.Error()) }
return usage, nil
}
// non-stream handler for chat/generate
func ollamaChatHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *http.Response) (*dto.Usage, *types.NewAPIError) {
body, err := io.ReadAll(resp.Body)
if err != nil { return nil, types.NewOpenAIError(err, types.ErrorCodeReadResponseBodyFailed, http.StatusInternalServerError) }
service.CloseResponseBodyGracefully(resp)
raw := string(body)
if common.DebugEnabled { println("ollama non-stream raw resp:", raw) }
lines := strings.Split(raw, "\n")
var (
aggContent strings.Builder
reasoningBuilder strings.Builder
lastChunk ollamaChatStreamChunk
parsedAny bool
)
for _, ln := range lines {
ln = strings.TrimSpace(ln)
if ln == "" { continue }
var ck ollamaChatStreamChunk
if err := json.Unmarshal([]byte(ln), &ck); err != nil {
if len(lines) == 1 { return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError) }
continue
}
parsedAny = true
lastChunk = ck
if ck.Message != nil && len(ck.Message.Thinking) > 0 {
raw := strings.TrimSpace(string(ck.Message.Thinking))
if raw != "" && raw != "null" { reasoningBuilder.WriteString(raw) }
}
if ck.Message != nil && ck.Message.Content != "" { aggContent.WriteString(ck.Message.Content) } else if ck.Response != "" { aggContent.WriteString(ck.Response) }
}
if !parsedAny {
var single ollamaChatStreamChunk
if err := json.Unmarshal(body, &single); err != nil { return nil, types.NewOpenAIError(err, types.ErrorCodeBadResponseBody, http.StatusInternalServerError) }
lastChunk = single
if single.Message != nil {
if len(single.Message.Thinking) > 0 { raw := strings.TrimSpace(string(single.Message.Thinking)); if raw != "" && raw != "null" { reasoningBuilder.WriteString(raw) } }
aggContent.WriteString(single.Message.Content)
} else { aggContent.WriteString(single.Response) }
}
model := lastChunk.Model
if model == "" { model = info.UpstreamModelName }
created := toUnix(lastChunk.CreatedAt)
usage := &dto.Usage{PromptTokens: lastChunk.PromptEvalCount, CompletionTokens: lastChunk.EvalCount, TotalTokens: lastChunk.PromptEvalCount + lastChunk.EvalCount}
content := aggContent.String()
finishReason := lastChunk.DoneReason
if finishReason == "" { finishReason = "stop" }
msg := dto.Message{Role: "assistant", Content: contentPtr(content)}
if rc := reasoningBuilder.String(); rc != "" { msg.ReasoningContent = rc }
full := dto.OpenAITextResponse{
Id: common.GetUUID(),
Model: model,
Object: "chat.completion",
Created: created,
Choices: []dto.OpenAITextResponseChoice{ {
Index: 0,
Message: msg,
FinishReason: finishReason,
} },
Usage: *usage,
}
out, _ := common.Marshal(full)
service.IOCopyBytesGracefully(c, resp, out)
return usage, nil
}
func contentPtr(s string) *string { if s=="" { return nil }; return &s }
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