Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/cohere-pack/skills/cohere-reference-architecture/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill cohere-reference-architecture. Copyright stays with the author (MIT).

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

Instructions

Define the data, retrieval, model, tool, and authorization boundaries first; implement the client/service layers in a staging environment; then verify grounding, error classification, observability, and rollback with a bounded workload. Keep model and tool access explicit and fail closed for unrecognized inputs, missing citations, cross-tenant data, or unsupported provider changes.

Examples

Build a small staging RAG path with a sanitized corpus, a single allow-listed tool, redacted traces, and a known fallback, then verify citation coverage and error behavior before scaling. If the design allows an unauthorized tool or retrieval result, halt promotion and correct the boundary rather than masking the failure in application code.

Error Handling

Resources

• Cohere API Reference
• RAG Guide
• Tool Use Guide

Next Steps

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