h/t to @lkuligin
- **Description:** added new models on VertexAI
- **Twitter handle:** @lkuligin
---------
Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This PR adds an example notebook for the Databricks Vector Search vector
store. It also adds an introduction to the Databricks Vector Search
product on the Databricks's provider page.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
When using local Chatglm2-6B by changing OPENAI_BASE_URL to localhost,
the token_usage in ChatOpenAI becomes None. This leads to an
AttributeError when trying to access token_usage.items().
This commit adds a check to ensure token_usage is not None before
accessing its items. This change prevents the AttributeError and allows
ChatOpenAI to work seamlessly with a local Chatglm2-6B model, aligning
with the way it operates with the OpenAI API.
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:** This PR fixes `HuggingFaceHubEmbeddings` by making the
API token optional (as in the client beneath). Most models don't require
one. I also updated the notebook for TEI (text-embeddings-inference)
accordingly as requested here #14288. In addition, I fixed a mistake in
the POST call parameters.
**Tag maintainers:** @baskaryan
## Description
New YAML output parser as a drop-in replacement for the Pydantic output
parser. Yaml is a much more token-efficient format than JSON, proving to
be **~35% faster and using the same percentage fewer completion
tokens**.
☑️ Formatted
☑️ Linted
☑️ Tested (analogous to the existing`test_pydantic_parser.py`)
The YAML parser excels in situations where a list of objects is
required, where the root object needs no key:
```python
class Products(BaseModel):
__root__: list[Product]
```
I ran the prompt `Generate 10 healthy, organic products` 10 times on one
chain using the `PydanticOutputParser`, the other one using
the`YamlOutputParser` with `Products` (see below) being the targeted
model to be created.
LLMs used were Fireworks' `lama-v2-34b-code-instruct` and OpenAI
`gpt-3.5-turbo`. All runs succeeded without validation errors.
```python
class Nutrition(BaseModel):
sugar: int = Field(description="Sugar in grams")
fat: float = Field(description="% of daily fat intake")
class Product(BaseModel):
name: str = Field(description="Product name")
stats: Nutrition
class Products(BaseModel):
"""A list of products"""
products: list[Product] # Used `__root__` for the yaml chain
```
Stats after 10 runs reach were as follows:
### JSON
ø time: 7.75s
ø tokens: 380.8
### YAML
ø time: 5.12s
ø tokens: 242.2
Looking forward to feedback, tips and contributions!
- **Description:** There is a bug in RedisNum filter that filter towards
value 0 will be parsed as "*". This is a fix to it.
- **Issue:** NA
- **Dependencies:** NA
- **Tag maintainer:** NA
- **Twitter handle:** NA
This PR updates RunnableWithMessage history to support user specific
configuration for the factory.
It extends support to passing multiple named arguments into the factory
if the factory takes more than a single argument.
TIL `**` globstar doesn't work in make
Makefile changes fix that.
`__getattr__` changes allow import of all files, but raise error when
accessing anything from the module.
file deletions were corresponding libs change from #14559
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
**Description**
The `SmartLLMChain` was was fixed to output key "resolution".
Unfortunately, this prevents the ability to use multiple `SmartLLMChain`
in a `SequentialChain` because of colliding output keys. This change
simply gives the option the customize the output key to allow for
sequential chaining. The default behavior is the same as the current
behavior.
Now, it's possible to do the following:
```
from langchain.chat_models import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain_experimental.smart_llm import SmartLLMChain
from langchain.chains import SequentialChain
joke_prompt = PromptTemplate(
input_variables=["content"],
template="Tell me a joke about {content}.",
)
review_prompt = PromptTemplate(
input_variables=["scale", "joke"],
template="Rate the following joke from 1 to {scale}: {joke}"
)
llm = ChatOpenAI(temperature=0.9, model_name="gpt-4-32k")
joke_chain = SmartLLMChain(llm=llm, prompt=joke_prompt, output_key="joke")
review_chain = SmartLLMChain(llm=llm, prompt=review_prompt, output_key="review")
chain = SequentialChain(
chains=[joke_chain, review_chain],
input_variables=["content", "scale"],
output_variables=["review"],
verbose=True
)
response = chain.run({"content": "chickens", "scale": "10"})
print(response)
```
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
This reverts commit 38813d7090. This is a
temporary fix, as I don't see a clear way on how to use multiple keys
with `Qdrant.from_texts`.
Context: #14378
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
---------
Co-authored-by: Brace Sproul <braceasproul@gmail.com>
