ollama

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package llm
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import (
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	_ "embed"
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	"fmt"
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	"time"
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	"github.com/jmorganca/ollama/api"
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)
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const jsonGrammar = `
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root   ::= object
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value  ::= object | array | string | number | ("true" | "false" | "null") ws
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object ::=
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  "{" ws (
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            string ":" ws value
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    ("," ws string ":" ws value)*
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  )? "}" ws
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array  ::=
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  "[" ws (
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            value
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    ("," ws value)*
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  )? "]" ws
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string ::=
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  "\"" (
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    [^"\\] |
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    "\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
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  )* "\"" ws
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number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
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# Optional space: by convention, applied in this grammar after literal chars when allowed
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ws ::= ([ \t\n] ws)?
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`
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type ImageData struct {
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	Data []byte `json:"data"`
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	ID   int    `json:"id"`
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}
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var payloadMissing = fmt.Errorf("expected dynamic library payloads not included in this build of ollama")
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type prediction struct {
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	Content string `json:"content"`
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	Model   string `json:"model"`
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	Prompt  string `json:"prompt"`
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	Stop    bool   `json:"stop"`
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	Timings struct {
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		PredictedN  int     `json:"predicted_n"`
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		PredictedMS float64 `json:"predicted_ms"`
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		PromptN     int     `json:"prompt_n"`
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		PromptMS    float64 `json:"prompt_ms"`
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	}
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}
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const maxRetries = 3
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type PredictOpts struct {
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	Prompt  string
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	Format  string
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	Images  []ImageData
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	Options api.Options
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}
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type PredictResult struct {
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	Content            string
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	Done               bool
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	PromptEvalCount    int
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	PromptEvalDuration time.Duration
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	EvalCount          int
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	EvalDuration       time.Duration
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}
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type TokenizeRequest struct {
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	Content string `json:"content"`
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}
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type TokenizeResponse struct {
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	Tokens []int `json:"tokens"`
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}
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type DetokenizeRequest struct {
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	Tokens []int `json:"tokens"`
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}
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type DetokenizeResponse struct {
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	Content string `json:"content"`
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}
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type EmbeddingRequest struct {
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	Content string `json:"content"`
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}
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type EmbeddingResponse struct {
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	Embedding []float64 `json:"embedding"`
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}
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