使用 ClientAI 和 Ollama 构建本地 AI 代码审查器 - 第 2 部分

def create_review_tools() -> list[toolconfig]:     """create the tool configurations for code review."""     return [         toolconfig(             tool=analyze_python_code,             name="code_analyzer",             description=(                 "analyze python code structure and complexity. "                 "expects a 'code' parameter with the python code as a string."             ),             scopes=["observe"],         ),         toolconfig(             tool=check_style_issues,             name="style_checker",             description=(                 "check python code style issues. "                 "expects a 'code' parameter with the python code as a string."             ),             scopes=["observe"],         ),         toolconfig(             tool=generate_docstring,             name="docstring_generator",             description=(                 "generate docstring suggestions for python code. "                 "expects a 'code' parameter with the python code as a string."             ),             scopes=["act"],         ),     ] 

class codereviewassistant(agent):     """an agent that performs comprehensive python code review."""      @observe(         name="analyze_structure",         description="analyze code structure and style",         stream=true,     )     def analyze_structure(self, code: str) -> str:         """analyze the code structure, complexity, and style issues."""         self.context.state["code_to_analyze"] = code         return """         please analyze this python code structure and style:          the code to analyze has been provided in the context as 'code_to_analyze'.         use the code_analyzer and style_checker tools to evaluate:         1. code complexity and structure metrics         2. style compliance issues         3. function and class organization         4. import usage patterns         """ 

    @think(         name="suggest_improvements",         description="suggest code improvements based on analysis",         stream=true,     )     def suggest_improvements(self, analysis_result: str) -> str:         """generate improvement suggestions based on the analysis results."""         current_code = self.context.state.get("current_code", "")         return f"""         based on the code analysis of:          ``` {% endraw %} python         {current_code} {% raw %}          ```          and the analysis results:         {analysis_result}          please suggest specific improvements for:         1. reducing complexity where identified         2. fixing style issues         3. improving code organization         4. optimizing import usage         5. enhancing readability         6. enhancing explicitness         """ 

def main():     # 1. set up logging     logger = logging.getlogger(__name__)      # 2. configure ollama server     config = ollamaserverconfig(         host="127.0.0.1",  # local machine         port=11434,        # default ollama port         gpu_layers=35,     # adjust based on your gpu         cpu_threads=8,     # adjust based on your cpu     ) 

    # use context manager for ollama server     with ollamamanager(config) as manager:         # initialize clientai with ollama         client = clientai(             "ollama",              host=f"http://{config.host}:{config.port}"         )          # create code review assistant with tools         assistant = codereviewassistant(             client=client,             default_model="llama3",             tools=create_review_tools(),             tool_confidence=0.8,  # how confident the ai should be before using tools             max_tools_per_step=2, # maximum tools to use per step         ) 

        print("code review assistant (local ai)")         print("enter python code to review, or 'quit' to exit.")         print("end input with '###' on a new line.")          while true:             try:                 print(" " + "=" * 50 + " ")                 print("enter code:")                  # collect code input                 code_lines = []                 while true:                     line = input()                     if line == "###":                         break                     code_lines.append(line)                  code = " ".join(code_lines)                 if code.lower() == "quit":                     break                  # process the code                 result = assistant.run(code, stream=true)                  # handle both streaming and non-streaming results                 if isinstance(result, str):                     print(result)                 else:                     for chunk in result:                         print(chunk, end="", flush=true)                 print(" ")              except exception as e:                 logger.error(f"unexpected error: {e}")                 print(" an unexpected error occurred. please try again.") 

if __name__ == "__main__":     main() 

python code_analyzer.py 

def calculate_total(values,tax_rate):     Total = 0     for Val in values:         if Val > 0:             if tax_rate > 0:                 Total += Val + (Val * tax_rate)             else:                 Total += Val     return Total