feat(dashscope): support to load headers from the environment

[DavdGao]

AgentScope Version

[The version of AgentScope you are working on, e.g. import agentscope; print(agentscope.__version__)]

Description

[Please describe the background, purpose, changes made, and how to test this PR]

Checklist

Please check the following items before code is ready to be reviewed.

• Code has been formatted with pre-commit run --all-files command
• All tests are passing
• Docstrings are in Google style
• Related documentation has been updated (e.g. links, examples, etc.)
• Code is ready for review

[Copilot]

Pull request overview

This pull request adds support for loading HTTP headers from the DASHSCOPE_API_HEADERS environment variable for DashScope API calls. This allows users to configure custom headers without modifying code.

Key Changes

• Added environment variable loading for DASHSCOPE_API_HEADERS in the DashScopeChatModel initialization
• Headers from the environment variable are parsed as JSON and merged with explicitly provided headers in generate_kwargs
• Error handling ensures invalid JSON triggers a warning rather than failing initialization

[DavdGao]

/gemini review

[gemini-code-assist]

Code Review

This pull request adds a useful feature to load DashScope headers from an environment variable. The implementation is mostly correct, and the identified potential bug and suggested refactoring are valid and improve robustness. The original comment aligns with best practices and does not contradict any provided rules, so it has been kept as is.

[gemini-code-assist]

The current implementation for loading headers from the environment can be improved for robustness and clarity.

1. Potential Bug: The line headers.update(self.generate_kwargs["headers"]) assumes self.generate_kwargs["headers"] is a dictionary. If it's another type (e.g., a list or string, which is possible given the JSONSerializableObject type hint), this will raise an unhandled exception, crashing the application during model initialization.
2. Unconventional Error Handling: Manually raising json.JSONDecodeError for a type check is not standard practice. It's better to handle invalid types explicitly, which also allows for more specific error messages.
3. Redundancy: The str(headers) cast is unnecessary as os.getenv already returns a string.

I suggest refactoring this block to address these issues. The following code is more robust, handles potential type errors gracefully, and provides clearer log messages.

        # Load headers from environment variable if exists
        headers_env_str = os.getenv("DASHSCOPE_API_HEADERS")
        if headers_env_str:
            try:
                headers = json.loads(headers_env_str)
                if not isinstance(headers, dict):
                    raise TypeError(
                        "Value from DASHSCOPE_API_HEADERS is not a dict",
                    )

                kw_headers = self.generate_kwargs.get("headers")
                if isinstance(kw_headers, dict):
                    headers.update(kw_headers)
                elif kw_headers is not None:
                    logger.warning(
                        "The 'headers' in generate_kwargs is not a "
                        "dictionary and will be ignored.",
                    )

                self.generate_kwargs["headers"] = headers

            except (json.JSONDecodeError, TypeError) as e:
                logger.warning(
                    "Failed to load headers from DASHSCOPE_API_HEADERS "
                    "environment variable: %s. It should be a JSON object.",
                    e,
                )