Langroid

* Chainlit callback -- add option to not show sub-task response
* Task adjustments for non-interactive mode:
- do not create dummy user response when non-interactive
- if non-interactive and user not explicitly addressed in pending msg, then `can_respond(e)` returns False when `e = user`

Adds an "all" extra to get all the common dependencies.

* Improve how`ToolMessage.examples()` is used -- until now, only a random example from these examples was picked to insert a 1-shot example for the LLM. With this change, _all_ examples will be used.
* Improve pytest workflow -- first run all tests with gpt-4o, then re-run only failed ones with gpt-4

Add pyyaml dependency

* All doc-parsers are now extra dependencies, and won't be installed with core langroid. As a convenience, extras can be installed in groups,
e.g.
- `doc-chat` will get all document parsers, and
- `db` will get all database-related dependencies

For example, you can get both these groups using


pip install "langroid[doc-chat,db]"

* Slim down langroid -- Make several dependencies optional, to be installed via "extras". See `pyproject.toml`. This should help reduce build size for production use, as well as improve script startup times. In DocChatAgent, if LanceDB is available, we use it, else we use QdrantDB (which is installed with core langroid).
* ToolMessage.examples(): each example can now either be a tool instance, or a tuple (description, tool_instance),
where the description is a natural language "thought" that leads to the tool usage. In some scenarios this
can enhance reliability of tool-generation.