[Feature Request] Add integration tests (Or at least a simple automated check CAMEL works with minimal dependencies)

[CaelumF]

Required prerequisites

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Motivation

To ensure that CAMEL always works out of the box for projects using it or where it is part of a dependency graph, it is important that the optional dependencies are really optional and that CAMEL is known to work outside the context of the global dependencies of developers' machines or with all optionals installed.

For example, right now this will fail:

git clone https://github.com/camel-ai/camel
cd camel
pip install uv
uv venv .venv --python=3.10
source .venv/bin/activate
uv pip install -e "."
python examples/tasks/task_generation.py

With these errors:

Traceback (most recent call last):
  File "/Users/caelum/PycharmProjects/camel_min/examples/tasks/task_generation.py", line 15, in <module>
    from camel.agents import ChatAgent
  File "/Users/caelum/PycharmProjects/camel_min/camel/agents/__init__.py", line 15, in <module>
    from .chat_agent import ChatAgent
  File "/Users/caelum/PycharmProjects/camel_min/camel/agents/chat_agent.py", line 41, in <module>
    from camel.agents._types import ModelResponse, ToolCallRequest
  File "/Users/caelum/PycharmProjects/camel_min/camel/agents/_types.py", line 19, in <module>
    from camel.messages import BaseMessage
  File "/Users/caelum/PycharmProjects/camel_min/camel/messages/__init__.py", line 47, in <module>
    from .base import BaseMessage  # noqa: E402
  File "/Users/caelum/PycharmProjects/camel_min/camel/messages/base.py", line 20, in <module>
    import numpy as np
ModuleNotFoundError: No module named 'numpy'

with uv add numpy, or pip install . the next error is related to 'PIL'.
(I expect the situation is the same if you're just installing CAMEL via pip install from pypi but correct me if I'm wrong)

Upstream breakages (future work ideas)

It is also possible that CAMEL's dependencies can break CAMEL without any changes being made to CAMEL. I think this is an unavoidable hazard of having so many dependencies and being a python project (until Python allows deep version locking with multiple versions of same libraries and eliminates an over dependence on native libraries).

But the hazard can be greatly reduced with some steps, here are some ideas:

• Feature flags / increasing the number of optional dependencies. e.g. whenever a third party SDK is used for a loader or tool, it might better become an optional dependency, so that if it breaks everything then it can only impact actual users of that tool
• Move tools and loaders to MCP servers and let network boundaries handle this
• Frequently re-testing with a dependency graph output saved, so that when a breaking upstream change is detected, the requirement version ranges can be re-specified to avoid the breaking change

Solution

I think it would be very valuable to run those above commands as part of the merge checks.

Alternatives

See future work. I expect those to be harder but if for some reason this isn't viable they can yield some of the same benefits of doing this.

Additional context

No response