Intégration LangChain

npm install langchain @langchain/openai @edwinfom/ai-guard

import { ChatOpenAI } from '@langchain/openai';
import { PromptTemplate } from '@langchain/core/prompts';
import { StringOutputParser } from '@langchain/core/output_parsers';
import { Guardian } from '@edwinfom/ai-guard';
 
const guard = new Guardian({
  pii:       { targets: ['email', 'phone'], onOutput: true },
  injection: { enabled: true, sensitivity: 'medium' },
  budget:    { model: 'gpt-4o-mini', maxTokens: 2000 },
});
 
const model = new ChatOpenAI({ model: 'gpt-4o-mini' });
const prompt = PromptTemplate.fromTemplate('Réponds à cette question : {question}');
const parser = new StringOutputParser();
 
// Enveloppe l'invocation complète de la chaîne avec Guard
const chain = prompt.pipe(model).pipe(parser);
 
const result = await guard.protect(
  (safeQuestion) => chain.invoke({ question: safeQuestion }),
  userQuestion,
);
 
console.log(result.data);  // Réponse protégée

import { StructuredOutputParser } from 'langchain/output_parsers';
import { z } from 'zod';
 
const parser = StructuredOutputParser.fromZodSchema(
  z.object({
    answer:      z.string(),
    confidence:  z.number().min(0).max(1),
    sources:     z.array(z.string()),
  })
);
 
const guard = new Guardian({
  schema:    { validator: parser.getSchema() },
  injection: { enabled: true },
});
 
const chain = prompt.pipe(model).pipe(parser);
 
const result = await guard.protect(
  (safeInput) => chain.invoke({ question: safeInput }),
  userQuestion,
);
 
// Résultat entièrement typé
console.log(result.data.answer);     // string
console.log(result.data.confidence); // number

import { RunnableLambda } from '@langchain/core/runnables';
 
// Enveloppe Guard en tant que Runnable
const guardedRunnable = RunnableLambda.from(async (input: string) => {
  const result = await guard.protect(
    (safeInput) => chain.invoke({ question: safeInput }),
    input,
  );
  return result.data;
});
 
// À composer comme n'importe quel autre Runnable
const pipeline = guardedRunnable.pipe(postProcessRunnable);
const output = await pipeline.invoke(userInput);

import { createOpenAIFunctionsAgent, AgentExecutor } from 'langchain/agents';
 
const agent = await createOpenAIFunctionsAgent({ llm: model, tools, prompt });
const executor = new AgentExecutor({ agent, tools });
 
// Protège l'exécution entière de l'agent
const result = await guard.protect(
  (safeInput) => executor.invoke({ input: safeInput }),
  userInput,
);

import { createGuardedParser } from '@edwinfom/ai-guard/langchain';
 
// Enveloppe un OutputParser LangChain avec la réparation de schéma de Guard
const guardedParser = createGuardedParser(myParser, {
  repair:     true,
  maxRetries: 2,
});
 
const chain = prompt.pipe(model).pipe(guardedParser);