DeepSeek V4: The Complete Developer Guide (API, Pricing, Local Setup & Migration 2026)

pip install openai  # DeepSeek uses the OpenAI SDK

from openai import OpenAI

client = OpenAI(
    api_key="your-deepseek-api-key",
    base_url="https://api.deepseek.com"
)

response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain MoE architecture in 3 sentences."}
    ]
)
print(response.choices[0].message.content)

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get current weather",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string"}},
            "required": ["city"]
        }
    }
}]

response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[{"role": "user", "content": "Weather in Tokyo?"}],
    tools=tools,
    tool_choice="auto"
)
tc = response.choices[0].message.tool_calls[0]
print(tc.function.name, tc.function.arguments)

import os

DEPRECATED = [
    "deepseek-chat-v3",
    "deepseek-chat-v3-0324",
    "deepseek-reasoner-r1",
    "deepseek-reasoner-r1-0528",
]

for root, _, files in os.walk("."):
    for f in files:
        if f.endswith(".py"):
            content = open(os.path.join(root, f)).read()
            for dep in DEPRECATED:
                if dep in content:
                    print(f"FOUND: {dep} in {os.path.join(root, f)}")

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Pull DeepSeek R1 7B (~4.7 GB)
ollama pull deepseek-r1:7b
ollama run deepseek-r1:7b

client = OpenAI(
    base_url="http://localhost:11434/v1",
    api_key="ollama"
)
response = client.chat.completions.create(
    model="deepseek-r1:7b",
    messages=[{"role": "user", "content": "Hello!"}]
)

import json
from openai import OpenAI

client = OpenAI(api_key="your-key", base_url="https://api.deepseek.com")

def run_agent(user_input, max_turns=5):
    messages = [{"role": "user", "content": user_input}]

    for _ in range(max_turns):
        resp = client.chat.completions.create(
            model="deepseek-chat",
            messages=messages,
            tools=tools,
            tool_choice="auto"
        )
        msg = resp.choices[0].message
        messages.append(msg)

        if not msg.tool_calls:
            return msg.content  # Final answer

        for tc in msg.tool_calls:
            result = execute_tool(tc)  # Your tool logic
            messages.append({
                "role": "tool",
                "tool_call_id": tc.id,
                "content": result
            })

    return "Max turns reached"

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="deepseek-chat",
    api_key="your-key",
    base_url="https://api.deepseek.com",
    temperature=0
)
# Works with all LangChain agents, chains, and tools unchanged

import litellm

response = litellm.completion(
    model="deepseek/deepseek-chat",
    messages=messages,
    fallbacks=["gpt-4o-mini", "claude-haiku-3-5"]
)