Steve Dudenhoeffer
693ac4e6a7
Introduce multiple agents, tools, and utilities for processing, extracting, and answering user-provided questions using LLMs and external data. Key features include knowledge processing, question splitting, search term generation, and contextual knowledge handling.
67 lines
1.6 KiB
Go
67 lines
1.6 KiB
Go
package agents
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import (
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"context"
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"fmt"
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"strings"
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gollm "gitea.stevedudenhoeffer.com/steve/go-llm"
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)
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type QuestionSplitter struct {
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Model gollm.ChatCompletion
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ContextualInfo []string
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}
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func (q QuestionSplitter) SplitQuestion(ctx context.Context, question string) ([]string, error) {
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var res []string
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req := gollm.Request{
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Toolbox: gollm.NewToolBox(
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gollm.NewFunction(
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"questions",
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"split the provided question by the user into sub-questions",
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func(ctx *gollm.Context, args struct {
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Questions []string `description:"The questions to evaluate"`
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}) (string, error) {
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res = args.Questions
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return "", nil
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}),
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),
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Messages: []gollm.Message{
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{
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Role: gollm.RoleSystem,
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Text: `The user is going to ask you a question, if the question would be better answered split into multiple questions, please do so.
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Respond using the "questions" function.
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If the question is fine as is, respond with the original question passed to the "questions" function.`,
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},
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},
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}
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if len(q.ContextualInfo) > 0 {
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req.Messages = append(req.Messages, gollm.Message{
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Role: gollm.RoleSystem,
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Text: "Some contextual information you should be aware of: " + strings.Join(q.ContextualInfo, "\n"),
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})
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}
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req.Messages = append(req.Messages, gollm.Message{
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Role: gollm.RoleUser,
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Text: question,
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})
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resp, err := q.Model.ChatComplete(ctx, req)
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if err != nil {
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return nil, err
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}
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if len(resp.Choices) == 0 {
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return nil, fmt.Errorf("no choices found")
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}
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choice := resp.Choices[0]
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_, _ = req.Toolbox.ExecuteCallbacks(gollm.NewContext(ctx, req, &choice, nil), choice.Calls, nil, nil)
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return res, nil
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}
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