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134 lines
4.1 KiB
Go
134 lines
4.1 KiB
Go
/*
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* Copyright 2025 CloudWeGo Authors
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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 main
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import (
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"context"
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"io"
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"strings"
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"github.com/cloudwego/eino/compose"
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"github.com/cloudwego/eino/schema"
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"github.com/cloudwego/eino-examples/internal/logs"
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)
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// demonstrates the stream field mapping ability of eino workflow.
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// It's modified from 2_field_mapping.
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func main() {
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type counter struct {
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FullStr string // exported because we will do field mapping for this field
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SubStr string // exported because we will do field mapping for this field
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}
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// wordCounter is a transformable lambda function that
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// count occurrences of SubStr within FullStr, for each trunk.
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wordCounter := func(ctx context.Context, c *schema.StreamReader[counter]) (
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*schema.StreamReader[int], error) {
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var subStr, cachedStr string
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return schema.StreamReaderWithConvert(c, func(co counter) (int, error) {
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if len(co.SubStr) > 0 {
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// static values will not always come in the first chunk,
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// so before the static value (SubStr) comes in,
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// we need to cache the full string
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subStr = co.SubStr
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fullStr := cachedStr + co.FullStr
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cachedStr = ""
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return strings.Count(fullStr, subStr), nil
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}
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if len(subStr) > 0 {
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return strings.Count(co.FullStr, subStr), nil
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}
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cachedStr += co.FullStr
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return 0, schema.ErrNoValue
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}), nil
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}
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// create a workflow just like a Graph
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wf := compose.NewWorkflow[*schema.Message, map[string]int]()
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// add lambda c1 just like in Graph
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wf.AddLambdaNode("c1", compose.TransformableLambda(wordCounter)).
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AddInput(compose.START, // add an input from START, specifying 2 field mappings
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// map START's Message's Content field to lambda c1's FullStr field
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compose.MapFields("Content", "FullStr")).
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// we can set static values even if the input will be stream
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SetStaticValue([]string{"SubStr"}, "o")
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// add lambda c2 just like in Graph
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wf.AddLambdaNode("c2", compose.TransformableLambda(wordCounter)).
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AddInput(compose.START, // add an input from START, specifying 2 field mappings
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// map START's Message's ReasoningContent field to lambda c1's FullStr field
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compose.MapFields("ReasoningContent", "FullStr")).
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SetStaticValue([]string{"SubStr"}, "o")
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wf.End(). // Obtain the compose.END for method chaining
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// add an input from c1,
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// mapping full output of c1 to the map key 'content_count'
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AddInput("c1", compose.ToField("content_count")).
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// also add an input from c2,
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// mapping full output of c2 to the map key 'reasoning_content_count'
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AddInput("c2", compose.ToField("reasoning_content_count"))
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// compile the workflow just like compiling a Graph
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run, err := wf.Compile(context.Background())
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if err != nil {
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logs.Errorf("workflow compile error: %v", err)
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return
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}
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// call the workflow using Transform just like calling a Graph with Transform
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result, err := run.Transform(context.Background(),
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schema.StreamReaderFromArray([]*schema.Message{
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{
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Role: schema.Assistant,
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ReasoningContent: "I need to say something meaningful",
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},
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{
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Role: schema.Assistant,
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Content: "Hello world!",
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},
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}))
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if err != nil {
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logs.Errorf("workflow run err: %v", err)
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return
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}
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var contentCount, reasoningCount int
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for {
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chunk, err := result.Recv()
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if err != nil {
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if err == io.EOF {
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result.Close()
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break
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}
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logs.Errorf("workflow receive err: %v", err)
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return
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}
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logs.Infof("%v", chunk)
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contentCount += chunk["content_count"]
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reasoningCount += chunk["reasoning_content_count"]
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}
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logs.Infof("content count: %d", contentCount)
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logs.Infof("reasoning count: %d", reasoningCount)
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}
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