clean up
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@ -226,10 +226,7 @@ type EmbeddingRequest struct {
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Model string `json:"model"`
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// Prompt is the textual prompt to embed.
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Prompt string `json:"prompt,omitempty"`
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// PromptBatch is a list of prompts to embed.
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PromptBatch []string `json:"prompt_batch,omitempty"`
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Prompt string `json:"prompt"`
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// KeepAlive controls how long the model will stay loaded in memory following
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// this request.
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@ -246,8 +243,7 @@ type EmbedResponse struct {
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// EmbeddingResponse is the response from [Client.Embeddings].
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type EmbeddingResponse struct {
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Embedding []float64 `json:"embedding,omitempty"`
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EmbeddingBatch [][]float64 `json:"embedding_batch,omitempty"`
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Embedding []float64 `json:"embedding"`
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}
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// CreateRequest is the request passed to [Client.Create].
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8
llm/ext_server/server.cpp
vendored
8
llm/ext_server/server.cpp
vendored
@ -3156,14 +3156,14 @@ int main(int argc, char **argv) {
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{
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res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
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const json body = json::parse(req.body);
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json input;
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json prompt;
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if (body.count("content") != 0)
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{
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input = body["content"];
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prompt = body["content"];
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}
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else
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{
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input = "";
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prompt = "";
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}
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// create and queue the task
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@ -3171,7 +3171,7 @@ int main(int argc, char **argv) {
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{
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const int id_task = llama.queue_tasks.get_new_id();
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llama.queue_results.add_waiting_task_id(id_task);
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llama.request_completion(id_task, {{"prompt", input}}, true, -1);
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llama.request_completion(id_task, {{"prompt", prompt}}, true, -1);
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// get the result
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task_result result = llama.queue_results.recv(id_task);
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@ -473,6 +473,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
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c.JSON(http.StatusOK, api.EmbeddingResponse{Embedding: []float64{}})
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return
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}
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embedding, err := runner.llama.Embedding(c.Request.Context(), req.Prompt)
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if err != nil {
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slog.Info(fmt.Sprintf("embedding generation failed: %v", err))
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