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npentrel
68 lines
2.8 KiB
Plaintext
68 lines
2.8 KiB
Plaintext
```java Java
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import com.langchain.smith.tracing.RunType;
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import com.langchain.smith.tracing.TraceConfig;
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import com.langchain.smith.tracing.Tracing;
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import com.openai.client.OpenAIClient;
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import com.openai.client.okhttp.OpenAIOkHttpClient;
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import com.openai.models.ChatModel;
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import com.openai.models.chat.completions.ChatCompletion;
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import com.openai.models.chat.completions.ChatCompletionCreateParams;
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import com.openai.models.chat.completions.ChatCompletionMessageParam;
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import com.openai.models.chat.completions.ChatCompletionSystemMessageParam;
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import com.openai.models.chat.completions.ChatCompletionUserMessageParam;
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import java.util.Arrays;
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import java.util.List;
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import java.util.function.Function;
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public class TraceablePipeline {
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public static void main(String[] args) {
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new TraceablePipelineRunner().run();
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}
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private static final class TraceablePipelineRunner {
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private final OpenAIClient openai = OpenAIOkHttpClient.fromEnv();
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private final Function<String, List<ChatCompletionMessageParam>> formatPrompt =
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Tracing.traceFunction(
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subject ->
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Arrays.asList(
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ChatCompletionMessageParam.ofSystem(
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ChatCompletionSystemMessageParam.builder()
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.content("You are a helpful assistant.")
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.build()),
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ChatCompletionMessageParam.ofUser(
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ChatCompletionUserMessageParam.builder()
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.content("What's a good name for a store that sells " + subject + "?")
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.build())),
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TraceConfig.builder().name("format_prompt").build());
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private final Function<List<ChatCompletionMessageParam>, ChatCompletion> invokeLlm =
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Tracing.traceFunction(
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messages ->
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openai.chat()
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.completions()
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.create(
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ChatCompletionCreateParams.builder()
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.model(ChatModel.GPT_5_CHAT_LATEST)
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.messages(messages)
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.temperature(0.0)
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.build()),
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TraceConfig.builder().name("invoke_llm").runType(RunType.LLM).build());
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private final Function<ChatCompletion, String> parseOutput =
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Tracing.traceFunction(
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response -> response.choices().get(0).message().content().orElse(""),
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TraceConfig.builder().name("parse_output").build());
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private final Function<String, String> runPipeline =
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Tracing.traceFunction(
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subject -> parseOutput.apply(invokeLlm.apply(formatPrompt.apply(subject))),
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TraceConfig.builder().name("run_pipeline").build());
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void run() {
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runPipeline.apply("colorful socks");
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}
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}
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}
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```
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