128 lines
2.9 KiB
Go
128 lines
2.9 KiB
Go
/*
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Copyright 2024 The Dapr Authors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package ollama
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import (
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"context"
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"reflect"
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"github.com/dapr/components-contrib/conversation"
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"github.com/dapr/components-contrib/metadata"
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"github.com/dapr/kit/logger"
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kmeta "github.com/dapr/kit/metadata"
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"github.com/tmc/langchaingo/llms"
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"github.com/tmc/langchaingo/llms/ollama"
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)
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type Ollama struct {
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llm llms.Model
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logger logger.Logger
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}
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func NewOllama(logger logger.Logger) conversation.Conversation {
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o := &Ollama{
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logger: logger,
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}
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return o
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}
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const defaultModel = "llama3.2:latest"
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func (o *Ollama) Init(ctx context.Context, meta conversation.Metadata) error {
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md := conversation.LangchainMetadata{}
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err := kmeta.DecodeMetadata(meta.Properties, &md)
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if err != nil {
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return err
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}
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model := defaultModel
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if md.Model != "" {
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model = md.Model
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}
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llm, err := ollama.New(
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ollama.WithModel(model),
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)
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if err != nil {
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return err
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}
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o.llm = llm
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if md.CacheTTL != "" {
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cachedModel, cacheErr := conversation.CacheModel(ctx, md.CacheTTL, o.llm)
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if cacheErr != nil {
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return cacheErr
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}
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o.llm = cachedModel
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}
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return nil
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}
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func (o *Ollama) GetComponentMetadata() (metadataInfo metadata.MetadataMap) {
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metadataStruct := conversation.LangchainMetadata{}
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metadata.GetMetadataInfoFromStructType(reflect.TypeOf(metadataStruct), &metadataInfo, metadata.ConversationType)
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return
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}
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func (o *Ollama) Converse(ctx context.Context, r *conversation.ConversationRequest) (res *conversation.ConversationResponse, err error) {
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messages := make([]llms.MessageContent, 0, len(r.Inputs))
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for _, input := range r.Inputs {
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role := conversation.ConvertLangchainRole(input.Role)
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messages = append(messages, llms.MessageContent{
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Role: role,
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Parts: []llms.ContentPart{
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llms.TextPart(input.Message),
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},
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})
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}
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opts := []llms.CallOption{}
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if r.Temperature > 0 {
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opts = append(opts, conversation.LangchainTemperature(r.Temperature))
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}
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resp, err := o.llm.GenerateContent(ctx, messages, opts...)
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if err != nil {
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return nil, err
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}
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outputs := make([]conversation.ConversationResult, 0, len(resp.Choices))
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for i := range resp.Choices {
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outputs = append(outputs, conversation.ConversationResult{
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Result: resp.Choices[i].Content,
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Parameters: r.Parameters,
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})
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}
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res = &conversation.ConversationResponse{
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Outputs: outputs,
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}
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return res, nil
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}
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func (o *Ollama) Close() error {
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return nil
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}
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