add a chain that applies a prompt to all inputs and then returns not
only an answer but scores it
add examples for question answering and question answering with sources
Add
[`logit_bias`](https://beta.openai.com/docs/api-reference/completions/create#completions/create-logit_bias)
params to OpenAI
See [here](https://beta.openai.com/tokenizer) for the tokenizer.
NB: I see that others (like Cohere) have the same parameter, but since I
don't have an access to it, I don't want to make a mistake.
---
Just to make sure the default "{}" works for openai:
```
from langchain.llms import OpenAI
OPENAI_API_KEY="XXX"
llm = OpenAI(openai_api_key=OPENAI_API_KEY)
llm.generate('Write "test":')
llm = OpenAI(openai_api_key=OPENAI_API_KEY, logit_bias={'9288': -100, '1332': -100, '14402': -100, '6208': -100})
llm.generate('Write "test":')
```
Add `finish_reason` to `Generation` as well as extend
`BaseOpenAI._generate` to include it in the output. This can be useful
for usage in downstream tasks when we need to filter for only
generations that finished because of `"stop"` for example. Maybe we
should add this to `LLMChain` as well?
For more details, see
https://beta.openai.com/docs/guides/completion/best-practices
Signed-off-by: Diwank Singh Tomer <diwank.singh@gmail.com>
this is the second PR of #519.
in #519 I suggested deleting Extra.forbid.
I was very confused but I replaced Extra.forbid to Extra.ignore, which
is the default of pydantic.
Since the
[BaseLLM](4b7b8229de/langchain/llms/base.py (L20))
from which it is inherited is set in Extra.forbid, I wanted to avoid
having the Extra.forbid settings inherited by simply deleting it.
As talking #519, I made 2 PRs.
this is the first PR for adding a logger.
I am concerned about the following two points and would appreciate your
opinion.
1. Since the logger is not formatted, the statement itself is output
like a print statement, and I thought it was difficult to understand
that it was a warning, so I put WARNING! at the beginning of the warning
statement. After the logger formatting is done properly, the word
WARNING can be repeated.
2. Statement `Please confirm that {field_name} is what you intended.`
can be replaced like `If {field_name} is intended parameters, enter it
to model_kwargs`
thank you!
Yongtae
Big docs refactor! Motivation is to make it easier for people to find
resources they are looking for. To accomplish this, there are now three
main sections:
- Getting Started: steps for getting started, walking through most core
functionality
- Modules: these are different modules of functionality that langchain
provides. Each part here has a "getting started", "how to", "key
concepts" and "reference" section (except in a few select cases where it
didnt easily fit).
- Use Cases: this is to separate use cases (like summarization, question
answering, evaluation, etc) from the modules, and provide a different
entry point to the code base.
There is also a full reference section, as well as extra resources
(glossary, gallery, etc)
Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
I was honored by the twitter mention, so used PyCharm to try and... help
docs even a little bit.
Mostly typo-s and correct spellings.
PyCharm really complains about "really good" being used all the time and
recommended alternative wordings haha
Hi! This PR adds support for the Azure OpenAI service to LangChain.
I've tried to follow the contributing guidelines.
Co-authored-by: Keiji Kanazawa <{ID}+{username}@users.noreply.github.com>
https://github.com/hwchase17/langchain/issues/354
Add support for running your own HF pipeline locally. This would allow
you to get a lot more dynamic with what HF features and models you
support since you wouldn't be beholden to what is hosted in HF hub. You
could also do stuff with HF Optimum to quantize your models and stuff to
get pretty fast inference even running on a laptop.
Created a generic SQLAlchemyCache class to plug any database supported
by SQAlchemy. (I am using Postgres).
I also based the class SQLiteCache class on this class SQLAlchemyCache.
As a side note, I'm questioning the need for two distinct class
LLMCache, FullLLMCache. Shouldn't we merge both ?
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>