If another file anywhere in `unit_tests` sets `langchain.verbose =
True`, it messes up all of the tests that check for no callbacks because
the `None` for verbose gets overridden by the global verbosity flag. By
explicitly setting it in unit tests, we bypass that potential issue
first pass at stdout callback
for the most part, went pretty smoothly. aside from the code here, here
are some comments/observations.
1.
should somehow default to stdouthandler so i dont have to do
```
from langchain.callbacks import get_callback_manager
from langchain.callbacks.stdout import StdOutCallbackHandler
get_callback_manager().add_handler(StdOutCallbackHandler())
```
2. I kept around the verbosity flag. 1) this is pretty important for
getting the stdout to look good for agents (and other things). 2) I
actually added this for LLM class since it didn't have it.
3. The only part that isn't basically perfectly moved over is the end of
the agent run. Here's a screenshot of the new stdout tracing
Noticing it is missing logging of the final thought, eg before this is
what it looked like
The reason its missing is that this was previously logged as part of
agent end (lines 205 and 206)
this is probably only relevant for the std out logger? any thoughts for
how to get it back in?
Love the project, a ton of fun!
I think the PR is pretty self-explanatory, happy to make any changes! I
am working on using it in an `LLMBashChain` and may update as that
progresses.
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Add MemoryChain and ConversationChain as chains that take a docstore in
addition to the prompt, and use the docstore to stuff context into the
prompt. This can be used to have an ongoing conversation with a chatbot.
Probably needs a bit of refactoring for code quality
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
