代码助手是 Ollama 的典型应用场景，可以帮助生成代码、解释代码、调试问题等。
import ollama
class CodeAssistant:
def __init__(self, model='codellama'):
self.model = model
self.system_prompt = """你是一个专业的编程助手。你的任务是：
1. 编写清晰、高效的代码
2. 添加必要的注释
3. 遵循最佳实践
4. 考虑边界情况和错误处理"""
def generate_code(self, prompt, language='Python'):
response = ollama.chat(
model=self.model,
messages=[
{'role': 'system', 'content': self.system_prompt},
{'role': 'user', 'content': f'用 {language} 实现：{prompt}'}
]
)
return response['message']['content']
def explain_code(self, code):
response = ollama.chat(
model=self.model,
messages=[
{'role': 'system', 'content': '你是一个代码解释专家，用简洁易懂的语言解释代码。'},
{'role': 'user', 'content': f'请解释以下代码：\n\n```\n{code}\n```'}
]
)
return response['message']['content']
def debug_code(self, code, error=None):
prompt = f'请检查以下代码是否有问题'
if error:
prompt += f'，错误信息：\n{error}'
prompt += f'：\n\n```\n{code}\n```'
response = ollama.chat(
model=self.model,
messages=[
{'role': 'system', 'content': '你是一个代码调试专家，帮助找出代码问题并提供修复建议。'},
{'role': 'user', 'content': prompt}
]
)
return response['message']['content']
def optimize_code(self, code):
response = ollama.chat(
model=self.model,
messages=[
{'role': 'system', 'content': '你是一个代码优化专家，帮助优化代码性能和可读性。'},
{'role': 'user', 'content': f'请优化以下代码：\n\n```\n{code}\n```'}
]
)
return response['message']['content']
# 使用
assistant = CodeAssistant()
code = assistant.generate_code('一个快速排序算法')
print("生成的代码：")
print(code)
explanation = assistant.explain_code(code)
print("\n代码解释：")
print(explanation)
import ollama
from rich.console import Console
from rich.panel import Panel
from rich.syntax import Syntax
from rich.markdown import Markdown
console = Console()
class InteractiveCodeAssistant:
def __init__(self, model='codellama'):
self.model = model
self.history = []
def send(self, message, stream=True):
self.history.append({'role': 'user', 'content': message})
if stream:
return self._stream_response()
else:
return self._sync_response()
def _stream_response(self):
stream = ollama.chat(
model=self.model,
messages=self.history,
stream=True
)
full_response = ""
for chunk in stream:
text = chunk['message']['content']
if text:
console.print(text, end="")
full_response += text
console.print()
self.history.append({'role': 'assistant', 'content': full_response})
return full_response
def _sync_response(self):
response = ollama.chat(
model=self.model,
messages=self.history
)
reply = response['message']['content']
self.history.append({'role': 'assistant', 'content': reply})
return reply
def clear(self):
self.history = []
def main():
assistant = InteractiveCodeAssistant()
console.print(Panel.fit("代码助手", style="bold green"))
console.print("命令: /clear 清空对话, /exit 退出\n")
while True:
try:
user_input = console.input("[bold blue]你:[/] ").strip()
except KeyboardInterrupt:
console.print("\n再见！")
break
if not user_input:
continue
if user_input == '/exit':
console.print("再见！")
break
elif user_input == '/clear':
assistant.clear()
console.print("[yellow]对话已清空[/]\n")
continue
console.print("[bold green]助手:[/]", end=" ")
assistant.send(user_input)
console.print()
if __name__ == "__main__":
main()
import ollama
from flask import Flask, request, jsonify
app = Flask(__name__)
def complete_code(prefix, language='python'):
response = ollama.generate(
model='codellama',
prompt=f'<PRE> {prefix} <SUF>',
options={
'temperature': 0.2,
'num_predict': 100
}
)
return response['response']
@app.route('/complete', methods=['POST'])
def complete():
data = request.json
prefix = data.get('prefix', '')
language = data.get('language', 'python')
completion = complete_code(prefix, language)
return jsonify({
'completion': completion
})
@app.route('/explain', methods=['POST'])
def explain():
data = request.json
code = data.get('code', '')
response = ollama.chat(
model='codellama',
messages=[
{'role': 'user', 'content': f'解释这段代码：\n```\n{code}\n```'}
]
)
return jsonify({
'explanation': response['message']['content']
})
if __name__ == '__main__':
app.run(port=5000)
import ollama
class MultiLanguageCodeAssistant:
LANGUAGE_PROMPTS = {
'python': 'Python',
'javascript': 'JavaScript',
'go': 'Go',
'java': 'Java',
'rust': 'Rust',
'cpp': 'C++',
'typescript': 'TypeScript'
}
def __init__(self, model='codellama'):
self.model = model
def generate(self, description, language='python'):
lang_name = self.LANGUAGE_PROMPTS.get(language, language)
response = ollama.chat(
model=self.model,
messages=[
{
'role': 'system',
'content': f'你是一个{lang_name}编程专家。只输出代码，不要解释。'
},
{
'role': 'user',
'content': f'用{lang_name}实现：{description}'
}
]
)
return response['message']['content']
def translate(self, code, from_lang, to_lang):
from_name = self.LANGUAGE_PROMPTS.get(from_lang, from_lang)
to_name = self.LANGUAGE_PROMPTS.get(to_lang, to_lang)
response = ollama.chat(
model=self.model,
messages=[
{
'role': 'system',
'content': f'你是一个代码翻译专家，将{from_name}代码翻译成{to_name}。'
},
{
'role': 'user',
'content': f'将以下{from_name}代码翻译成{to_name}：\n```\n{code}\n```'
}
]
)
return response['message']['content']
def add_tests(self, code, language='python'):
lang_name = self.LANGUAGE_PROMPTS.get(language, language)
response = ollama.chat(
model=self.model,
messages=[
{
'role': 'system',
'content': f'你是一个{lang_name}测试专家，为代码编写单元测试。'
},
{
'role': 'user',
'content': f'为以下{lang_name}代码编写单元测试：\n```\n{code}\n```'
}
]
)
return response['message']['content']
def add_documentation(self, code, language='python'):
lang_name = self.LANGUAGE_PROMPTS.get(language, language)
response = ollama.chat(
model=self.model,
messages=[
{
'role': 'system',
'content': f'你是一个{lang_name}文档专家，为代码添加文档注释。'
},
{
'role': 'user',
'content': f'为以下{lang_name}代码添加文档注释：\n```\n{code}\n```'
}
]
)
return response['message']['content']
# 使用
assistant = MultiLanguageCodeAssistant()
python_code = assistant.generate('一个快速排序算法', 'python')
print("Python 代码：")
print(python_code)
go_code = assistant.translate(python_code, 'python', 'go')
print("\nGo 代码：")
print(go_code)