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feat(tracing): Integrate Langfuse for LLM call tracing and add documentation

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This commit is contained in:
Willie Zutz 2025-08-10 10:05:42 -06:00
parent 9670003970
commit 7b4a7a531e
17 changed files with 183 additions and 36 deletions
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2
src/app/api/dashboard/process-widget/route.ts
View file

@ -16,6 +16,7 @@ import { allTools } from '@/lib/tools';
import { Source } from '@/lib/types/widget';
import { WidgetProcessRequest } from '@/lib/types/api';
import axios from 'axios';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
// Helper function to fetch content from a single source
async function fetchSourceContent(
@ -149,6 +150,7 @@ async function processWithLLM(
},
{
recursionLimit: 15, // Limit recursion depth to prevent infinite loops
...getLangfuseCallbacks(),
},
);

5
src/app/api/uploads/route.ts
View file

@ -17,6 +17,7 @@ import { ChatOpenAI } from '@langchain/openai';
import { ChatOllama } from '@langchain/ollama';
import { z } from 'zod';
import { withStructuredOutput } from '@/lib/utils/structuredOutput';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
interface FileRes {
fileName: string;
@ -71,7 +72,9 @@ Generate topics that describe what this document is about, its domain, and key s
name: 'generate_topics',
});
const result = await structuredLlm.invoke(prompt);
const result = await structuredLlm.invoke(prompt, {
...getLangfuseCallbacks(),
});
console.log('Generated topics:', result.topics);
// Filename is included for context
return filename + ', ' + result.topics.join(', ');

2
src/app/layout.tsx
View file

@ -25,7 +25,7 @@ export default function RootLayout({
children: React.ReactNode;
}>) {
return (
<html className="h-full" lang="en" suppressHydrationWarning>
<html className="h-full" lang="en" suppressHydrationWarning>
<head>
<link
rel="search"

3
src/lib/chains/imageSearchAgent.ts
View file

@ -10,6 +10,7 @@ import LineOutputParser from '../outputParsers/lineOutputParser';
import { searchSearxng } from '../searxng';
import { formatDateForLLM } from '../utils';
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
const imageSearchChainPrompt = `
# Instructions
@ -140,7 +141,7 @@ const handleImageSearch = (
systemInstructions?: string,
) => {
const imageSearchChain = createImageSearchChain(llm, systemInstructions);
return imageSearchChain.invoke(input);
return imageSearchChain.invoke(input, { ...getLangfuseCallbacks() });
};
export default handleImageSearch;

5
src/lib/chains/suggestionGeneratorAgent.ts
View file

@ -5,6 +5,7 @@ import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { ChatOpenAI } from '@langchain/openai';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
const suggestionGeneratorPrompt = `
You are an AI suggestion generator for an AI powered search engine.
@ -74,7 +75,9 @@ const generateSuggestions = (
llm,
systemInstructions,
);
return suggestionGeneratorChain.invoke(input);
return suggestionGeneratorChain.invoke(input, {
...getLangfuseCallbacks(),
});
};
export default generateSuggestions;

3
src/lib/chains/videoSearchAgent.ts
View file

@ -10,6 +10,7 @@ import LineOutputParser from '../outputParsers/lineOutputParser';
import { searchSearxng } from '../searxng';
import { formatDateForLLM } from '../utils';
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
const VideoSearchChainPrompt = `
# Instructions
@ -147,7 +148,7 @@ const handleVideoSearch = (
systemInstructions?: string,
) => {
const VideoSearchChain = createVideoSearchChain(llm, systemInstructions);
return VideoSearchChain.invoke(input);
return VideoSearchChain.invoke(input, { ...getLangfuseCallbacks() });
};
export default handleVideoSearch;

3
src/lib/search/simplifiedAgent.ts
View file

@ -19,6 +19,7 @@ import {
import { formatDateForLLM } from '../utils';
import { getModelName } from '../utils/modelUtils';
import { removeThinkingBlocks } from '../utils/contentUtils';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
/**
* Normalize usage metadata from different LLM providers
@ -511,12 +512,14 @@ Use all available tools strategically to provide comprehensive, well-researched,
},
recursionLimit: 25, // Allow sufficient iterations for tool use
signal: this.signal,
...getLangfuseCallbacks(),
};
// Use streamEvents to capture both tool calls and token-level streaming
const eventStream = agent.streamEvents(initialState, {
...config,
version: 'v2',
...getLangfuseCallbacks(),
});
let finalResult: any = null;

16
src/lib/search/speedSearch.ts
View file

@ -23,6 +23,7 @@ import { formatDateForLLM } from '../utils';
import { getDocumentsFromLinks } from '../utils/documents';
import formatChatHistoryAsString from '../utils/formatHistory';
import { getModelName } from '../utils/modelUtils';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
export interface SpeedSearchAgentType {
searchAndAnswer: (
@ -103,7 +104,7 @@ class SpeedSearchAgent implements SpeedSearchAgentType {
this.emitProgress(emitter, 10, `Building search query`);
return RunnableSequence.from([
return RunnableSequence.from([
PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
llm,
this.strParser,
@ -235,8 +236,8 @@ class SpeedSearchAgent implements SpeedSearchAgentType {
</text>
Make sure to answer the query in the summary.
`,
{ signal },
`,
{ signal, ...getLangfuseCallbacks() },
);
const document = new Document({
@ -348,7 +349,7 @@ class SpeedSearchAgent implements SpeedSearchAgentType {
date,
systemInstructions,
},
{ signal: options?.signal },
{ signal: options?.signal, ...getLangfuseCallbacks() },
);
query = searchRetrieverResult.query;
@ -379,6 +380,7 @@ class SpeedSearchAgent implements SpeedSearchAgentType {
)
.withConfig({
runName: 'FinalSourceRetriever',
...getLangfuseCallbacks(),
})
.pipe(this.processDocs),
}),
@ -391,6 +393,7 @@ class SpeedSearchAgent implements SpeedSearchAgentType {
this.strParser,
]).withConfig({
runName: 'FinalResponseGenerator',
...getLangfuseCallbacks(),
});
}
@ -539,7 +542,7 @@ ${docs[index].metadata?.url.toLowerCase().includes('file') ? '' : '\n<url>' + do
personaInstructions,
);
const stream = answeringChain.streamEvents(
const stream = answeringChain.streamEvents(
{
chat_history: history,
query: message,
@ -547,7 +550,8 @@ ${docs[index].metadata?.url.toLowerCase().includes('file') ? '' : '\n<url>' + do
{
version: 'v1',
// Pass the abort signal to the LLM streaming chain
signal,
signal,
...getLangfuseCallbacks(),
},
);

2
src/lib/tools/agents/urlSummarizationTool.ts
View file

@ -7,6 +7,7 @@ import { removeThinkingBlocks } from '@/lib/utils/contentUtils';
import { Command, getCurrentTaskInput } from '@langchain/langgraph';
import { SimplifiedAgentStateType } from '@/lib/state/chatAgentState';
import { ToolMessage } from '@langchain/core/messages';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
// Schema for URL summarization tool input
const URLSummarizationToolSchema = z.object({
@ -144,6 +145,7 @@ Provide a comprehensive summary of the above web page content, focusing on infor
const result = await llm.invoke(summarizationPrompt, {
signal: config?.signal,
...getLangfuseCallbacks(),
});
finalContent = removeThinkingBlocks(result.content as string);

34
src/lib/tracing/langfuse.ts Normal file
View file

@ -0,0 +1,34 @@
// Centralized Langfuse tracing utility
// Provides a singleton CallbackHandler and a helper to attach callbacks
import type { Callbacks } from '@langchain/core/callbacks/manager';
import { CallbackHandler } from 'langfuse-langchain';
let handler: CallbackHandler | null = null;
export function getLangfuseHandler(): CallbackHandler | null {
// Only initialize on server
if (typeof window !== 'undefined') return null;
if (handler) return handler;
try {
// The handler reads LANGFUSE_* env vars by default. You can also pass keys here if desired.
handler = new CallbackHandler({
publicKey: process.env.LANGFUSE_PUBLIC_KEY,
secretKey: process.env.LANGFUSE_SECRET_KEY,
baseUrl: process.env.LANGFUSE_BASE_URL,
});
} catch (e) {
// If initialization fails (e.g., missing envs), disable tracing gracefully
handler = null;
}
return handler;
}
// Convenience helper to spread into LangChain invoke/config objects
export function getLangfuseCallbacks(): { callbacks?: Callbacks } {
const h = getLangfuseHandler();
return h ? { callbacks: [h] } : {};
}

5
src/lib/utils/analyzePreviewContent.ts
View file

@ -5,6 +5,7 @@ import { formatDateForLLM } from '../utils';
import { ChatOpenAI, OpenAIClient } from '@langchain/openai';
import { removeThinkingBlocks } from './contentUtils';
import { withStructuredOutput } from './structuredOutput';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
export type PreviewAnalysisResult = {
isSufficient: boolean;
@ -81,7 +82,7 @@ Snippet: ${content.snippet}
name: 'analyze_preview_content',
});
const analysisResult = await structuredLLM.invoke(
const analysisResult = await structuredLLM.invoke(
`You are a preview content analyzer, tasked with determining if search result snippets contain sufficient information to answer the Task Query.
# Instructions
@ -118,7 +119,7 @@ ${taskQuery}
# Search Result Previews to Analyze:
${formattedPreviewContent}
`,
{ signal },
{ signal, ...getLangfuseCallbacks() },
);
if (!analysisResult) {

8
src/lib/utils/summarizeWebContent.ts
View file

@ -6,6 +6,7 @@ import { getWebContent } from './documents';
import { removeThinkingBlocks } from './contentUtils';
import { setTemperature } from './modelUtils';
import { withStructuredOutput } from './structuredOutput';
import { getLangfuseCallbacks } from '@/lib/tracing/langfuse';
export type SummarizeResult = {
document: Document | null;
@ -95,7 +96,7 @@ Here is the query you need to answer: ${query}
Here is the content to analyze:
${contentToAnalyze}`,
{ signal },
{ signal, ...getLangfuseCallbacks() },
);
if (!relevanceResult) {
@ -168,7 +169,10 @@ Here is the query you need to answer: ${query}
Here is the content to summarize:
${i === 0 ? content.metadata.html : content.pageContent}`;
const result = await llm.invoke(prompt, { signal });
const result = await llm.invoke(prompt, {
signal,
...getLangfuseCallbacks(),
});
summary = removeThinkingBlocks(result.content as string);
break;
} catch (error) {