技能 人工智能 Cohere AI应用架构指南

Cohere AI应用架构指南

v20260423
cohere-reference-architecture
本指南提供了一个生产级的、分层架构设计,用于构建复杂的AI应用。它详细展示了如何使用Cohere API v2实现RAG流程、工具调用Agent和多模型编排。适用于需要建立标准AI系统架构或集成Cohere能力的开发者。
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概览

Cohere Reference Architecture

Overview

Production-ready architecture for Cohere API v2 applications covering RAG pipelines, tool-use agents, and multi-model orchestration.

Prerequisites

  • Understanding of layered architecture
  • cohere-ai SDK v7+
  • TypeScript project with vitest

Project Structure

my-cohere-app/
├── src/
│   ├── cohere/
│   │   ├── client.ts           # CohereClientV2 singleton
│   │   ├── models.ts           # Model selection logic
│   │   ├── types.ts            # Cohere-specific types
│   │   └── errors.ts           # Error classification
│   ├── services/
│   │   ├── chat.ts             # Chat completions + streaming
│   │   ├── rag.ts              # RAG pipeline (embed → rerank → chat)
│   │   ├── agents.ts           # Tool-use agent loops
│   │   ├── embed.ts            # Batch embedding + caching
│   │   ├── rerank.ts           # Document reranking
│   │   └── classify.ts         # Few-shot classification
│   ├── tools/                  # Tool definitions for agents
│   │   ├── registry.ts         # Tool name → executor mapping
│   │   ├── search.ts
│   │   └── calculator.ts
│   ├── api/
│   │   ├── chat.ts             # POST /api/chat (streaming)
│   │   ├── embed.ts            # POST /api/embed
│   │   └── health.ts           # GET /api/health
│   └── cache/
│       └── embeddings.ts       # LRU cache for embeddings
├── tests/
│   ├── unit/
│   │   ├── chat.test.ts
│   │   ├── rag.test.ts
│   │   └── fixtures/           # Mocked API responses
│   └── integration/
│       └── cohere.test.ts      # Real API tests (gated)
├── config/
│   ├── models.json             # Model selection per environment
│   └── tools.json              # Tool definitions
└── package.json

Layer Architecture

┌─────────────────────────────────────────┐
│             API Layer                    │
│   (Express/Next.js routes, SSE stream)  │
├─────────────────────────────────────────┤
│           Service Layer                  │
│  (RAG pipeline, agent loop, classify)   │
├─────────────────────────────────────────┤
│          Cohere Layer                    │
│   (CohereClientV2, retry, model select) │
├─────────────────────────────────────────┤
│         Infrastructure Layer             │
│    (Embed cache, tool registry, queue)   │
└─────────────────────────────────────────┘

Core Components

Client Layer

// src/cohere/client.ts
import { CohereClientV2, CohereError, CohereTimeoutError } from 'cohere-ai';

let instance: CohereClientV2 | null = null;

export function getCohere(): CohereClientV2 {
  if (!instance) {
    instance = new CohereClientV2({
      token: process.env.CO_API_KEY,
    });
  }
  return instance;
}

// src/cohere/models.ts
export const MODELS = {
  chat: {
    premium: 'command-a-03-2025',
    standard: 'command-r-08-2024',
    fast: 'command-r7b-12-2024',
  },
  embed: {
    latest: 'embed-v4.0',
    english: 'embed-english-v3.0',
    multilingual: 'embed-multilingual-v3.0',
  },
  rerank: {
    latest: 'rerank-v3.5',
  },
} as const;

RAG Service

// src/services/rag.ts
import { getCohere } from '../cohere/client';
import { MODELS } from '../cohere/models';

interface RAGResult {
  answer: string;
  citations: Array<{ start: number; end: number; text: string; sources: string[] }>;
  model: string;
}

export async function ragQuery(
  query: string,
  documents: Array<{ id: string; text: string }>,
  options?: { model?: string; topN?: number }
): Promise<RAGResult> {
  const cohere = getCohere();
  const model = options?.model ?? MODELS.chat.standard;

  // Step 1: Rerank documents
  const reranked = await cohere.rerank({
    model: MODELS.rerank.latest,
    query,
    documents: documents.map(d => d.text),
    topN: options?.topN ?? 5,
  });

  // Step 2: Chat with top documents
  const topDocs = reranked.results.map(r => ({
    id: documents[r.index].id,
    data: { text: documents[r.index].text },
  }));

  const response = await cohere.chat({
    model,
    messages: [{ role: 'user', content: query }],
    documents: topDocs,
  });

  return {
    answer: response.message?.content?.[0]?.text ?? '',
    citations: (response.message?.citations ?? []).map(c => ({
      start: c.start,
      end: c.end,
      text: c.text,
      sources: c.sources?.map((s: any) => s.id) ?? [],
    })),
    model,
  };
}

Agent Service

// src/services/agents.ts
import { getCohere } from '../cohere/client';
import { MODELS } from '../cohere/models';
import { toolRegistry } from '../tools/registry';

export async function runAgent(
  userMessage: string,
  maxSteps = 5
): Promise<string> {
  const cohere = getCohere();
  const messages: any[] = [{ role: 'user', content: userMessage }];
  const tools = toolRegistry.getToolDefinitions();

  for (let step = 0; step < maxSteps; step++) {
    const response = await cohere.chat({
      model: MODELS.chat.premium,
      messages,
      tools,
    });

    if (response.finishReason !== 'TOOL_CALL') {
      return response.message?.content?.[0]?.text ?? '';
    }

    const toolCalls = response.message?.toolCalls ?? [];
    messages.push({ role: 'assistant', toolCalls });

    for (const tc of toolCalls) {
      const result = await toolRegistry.execute(
        tc.function.name,
        JSON.parse(tc.function.arguments)
      );
      messages.push({ role: 'tool', toolCallId: tc.id, content: result });
    }
  }

  return 'Agent reached max steps.';
}

Tool Registry

// src/tools/registry.ts
interface ToolDefinition {
  type: 'function';
  function: {
    name: string;
    description: string;
    parameters: Record<string, unknown>;
  };
}

class ToolRegistry {
  private tools: Map<string, {
    definition: ToolDefinition;
    executor: (args: any) => Promise<string>;
  }> = new Map();

  register(
    name: string,
    description: string,
    parameters: Record<string, unknown>,
    executor: (args: any) => Promise<string>
  ) {
    this.tools.set(name, {
      definition: {
        type: 'function',
        function: { name, description, parameters },
      },
      executor,
    });
  }

  getToolDefinitions(): ToolDefinition[] {
    return Array.from(this.tools.values()).map(t => t.definition);
  }

  async execute(name: string, args: any): Promise<string> {
    const tool = this.tools.get(name);
    if (!tool) return JSON.stringify({ error: `Unknown tool: ${name}` });
    try {
      return await tool.executor(args);
    } catch (err) {
      return JSON.stringify({ error: String(err) });
    }
  }
}

export const toolRegistry = new ToolRegistry();

Error Classification

// src/cohere/errors.ts
import { CohereError, CohereTimeoutError } from 'cohere-ai';

export type ErrorCategory = 'auth' | 'rate_limit' | 'bad_request' | 'server' | 'timeout' | 'unknown';

export function classifyError(err: unknown): {
  category: ErrorCategory;
  retryable: boolean;
  message: string;
} {
  if (err instanceof CohereTimeoutError) {
    return { category: 'timeout', retryable: true, message: 'Request timed out' };
  }
  if (err instanceof CohereError) {
    switch (err.statusCode) {
      case 401: return { category: 'auth', retryable: false, message: 'Invalid API key' };
      case 429: return { category: 'rate_limit', retryable: true, message: 'Rate limited' };
      case 400: return { category: 'bad_request', retryable: false, message: err.message };
      default:
        if (err.statusCode && err.statusCode >= 500) {
          return { category: 'server', retryable: true, message: err.message };
        }
    }
  }
  return { category: 'unknown', retryable: false, message: String(err) };
}

Data Flow

User Query
     │
     ▼
┌─────────────┐
│   API Route  │  POST /api/chat
└──────┬──────┘
       │
       ▼
┌─────────────┐    ┌─────────────┐
│  RAG Service │───▶│  Rerank     │  rerank-v3.5
│  or Agent   │    │  Service    │
└──────┬──────┘    └─────────────┘
       │
       ▼
┌─────────────┐    ┌─────────────┐
│ Chat/Stream  │───▶│  Embed      │  embed-v4.0
│  Service    │    │  Cache      │  (cached)
└──────┬──────┘    └─────────────┘
       │
       ▼
┌─────────────┐
│ CohereClient │  command-a-03-2025
│     V2      │
└─────────────┘

Output

  • Layered architecture separating API, service, and client concerns
  • RAG pipeline with rerank pre-filtering and grounded citations
  • Agent loop with pluggable tool registry
  • Error classification for retry/alert decisions
  • Model selection per environment and use case

Error Handling

Issue Cause Solution
Circular imports Wrong layering Services depend on client, not vice versa
Tool not found Missing registration Register tools at startup
Model mismatch Env config wrong Validate model IDs at startup
Cache miss storm TTL expired Stale-while-revalidate pattern

Resources

Next Steps

For multi-environment setup, see cohere-multi-env-setup.

信息
Category 人工智能
Name cohere-reference-architecture
版本 v20260423
大小 10.78KB
更新时间 2026-04-28
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