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("\n" + "=" * 50 + "\n")
                print("enter code:")

                # collect code input
                code_lines = []
                while true:
                    line = input()
                    if line == "###":
                        break
                    code_lines.append(line)

                code = "\n".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("\n")

            except exception as e:
                logger.error(f"unexpected error: {e}")
                print("\nan 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