feat(source): implement advanced search engine source

[frinkleko]

Description

This pull request introduces a new SearchSource that enables fetching and processing content from the DuckDuckGo search engine. This new source is designed to be a robust and flexible way to incorporate web search results into the QuantMind framework. This PR complete part of the demand in #35

The key features of this implementation are:

• A SearchSource class that queries the DuckDuckGo search engine.
• A corresponding SearchContent data model to standardize the search results.
• Support for advanced search operators, including site:, filetype:, and date-range filtering, which can be configured or passed directly to the search method.
• Comprehensive integration tests to ensure the reliability of both basic and advanced search functionalities.

Checklist

• The PR title starts with $CATEGORY(xx): xxx (such as feat(tool): xxx, fix(source): xxx, docs(README): xxx)
• Related issue is referred in this PR
• The markdown and latex are rendered correctly.
• The code in PR is well-documented.
• x] The PR is complete and small, read the [Google eng practice (CL equals to PR) (https://google.github.io/eng-practices/review/developer/small-cls.html) to understand more about small PR.

[wanghaoxue0]

looks good from my side

[WinstonLiyt]

What is the function of meta_info?

[WinstonLiyt]

What if the datetime format is wrong?

Add something like this?

@field_validator("start_date", "end_date")
@classmethod
def _validate_date(cls, v):
    if v is None:
        return v
    if not re.match(r"^\d{4}-\d{2}-\d{2}$", v):
        raise ValueError("date must be YYYY-MM-DD")
    return v