from openai import OpenAI

# 獲取環境變量中的 API 密鑰
XAI_API_KEY = os.getenv("XAI_API_KEY")
client = OpenAI(
api_key=XAI_API_KEY,
base_url="https://api.x.ai/v1",
)

# 發起請求
completion = client.chat.completions.create(
model="grok-2-latest",
messages=[
{
"role": "system",
"content": "You are Grok, a chatbot inspired by the Hitchhikers Guide to the Galaxy."
},
{
"role": "user",
"content": "What is the meaning of life, the universe, and everything?"
},
],
temperature=0.7
)

# 打印回答
print(completion.choices[0].message.content)

2. 代碼調試與優化

Python復制

import os
from openai import OpenAI

# 獲取環境變量中的 API 密鑰
XAI_API_KEY = os.getenv("XAI_API_KEY")
client = OpenAI(
api_key=XAI_API_KEY,
base_url="https://api.x.ai/v1",
)

# 發起代碼優化請求
completion = client.chat.completions.create(
model="grok-2-latest",
messages=[
{
"role": "system",
"content": "You are a helpful assistant for debugging and optimizing code."
},
{
"role": "user",
"content": "Here is a Python function I'm working on. Can you suggest any improvements?\n\n``python\ndef factorial(n):\n if n == 0:\n return 1\n else:\n return n * factorial(n - 1)\n``" }, ], temperature=0.5 ) # 打印優化建議 print(completion.choices[0].message.content)

3. 圖像分析

Python復制

import os
from openai import OpenAI

# 獲取環境變量中的 API 密鑰
XAI_API_KEY = os.getenv("XAI_API_KEY")
client = OpenAI(
api_key=XAI_API_KEY,
base_url="https://api.x.ai/v1",
)

# 圖像 URL 示例(替換為實際圖像鏈接)
image_url = "https://example.com/path/to/image.png"

# 發起圖像分析請求
completion = client.chat.completions.create(
model="grok-2-vision-latest",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": image_url,
"detail": "high"
}
},
{
"type": "text",
"text": "What can you see in this image?"
}
]
}
],
temperature=0.01
)

# 打印分析結果
print(completion.choices[0].message.content)

4. 自定義系統角色

Python復制

import os
from openai import OpenAI

# 獲取環境變量中的 API 密鑰
XAI_API_KEY = os.getenv("XAI_API_KEY")
client = OpenAI(
api_key=XAI_API_KEY,
base_url="https://api.x.ai/v1",
)

# 自定義系統角色
system_role = """
You are a senior software engineer specializing in Python development.
Your task is to assist with code reviews, debugging, and optimization suggestions.
"""

# 發起請求
completion = client.chat.completions.create(
model="grok-2-latest",
messages=[
{
"role": "system",
"content": system_role
},
{
"role": "user",
"content": "Can you help me review this code snippet for potential issues?\n\n``python\ndef add(a, b):\n return a + b\n``" } ], temperature=0.2 ) # 打印回答 print(completion.choices[0].message.content)

限制和考慮

結論

Grok 不僅僅是另一個 AI 工具;它是為技術愛好者和專業人士設計的、不斷發展的伙伴,旨在推動軟件工程的可能性邊界。通過將 Grok 整合到你的工作流程中,你不僅能夠增強解決問題的能力,還能在快速發展的技術世界中保持領先。繼續探索,繼續提問,讓 Grok 成為你的開發伙伴。記住,正如 Grok 自己會說的,“別慌!” —— 擁抱學習曲線,你會發現 Grok 在你的編碼冒險中是一個無價的資產。

上一篇:

如何使用 xAI 的 Grok:全面解析 Grok 3 的功能與優勢

下一篇:

如何使用 Grok AI:綜合指南
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