- **Description:** Existing model used for Prompt Injection is quite
outdated but we fine-tuned and open-source a new model based on the same
model deberta-v3-base from Microsoft -
[laiyer/deberta-v3-base-prompt-injection](https://huggingface.co/laiyer/deberta-v3-base-prompt-injection).
It supports more up-to-date injections and less prone to
false-positives.
- **Dependencies:** No
- **Tag maintainer:** -
- **Twitter handle:** @alex_yaremchuk
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** The experimental package needs to be compatible with
the usage of importing agents
For example, if i use `from langchain.agents import
create_pandas_dataframe_agent`, running the program will prompt the
following information:
```
Traceback (most recent call last):
File "/Users/dongwm/test/main.py", line 1, in <module>
from langchain.agents import create_pandas_dataframe_agent
File "/Users/dongwm/test/venv/lib/python3.11/site-packages/langchain/agents/__init__.py", line 87, in __getattr__
raise ImportError(
ImportError: create_pandas_dataframe_agent has been moved to langchain experimental. See https://github.com/langchain-ai/langchain/discussions/11680 for more information.
Please update your import statement from: `langchain.agents.create_pandas_dataframe_agent` to `langchain_experimental.agents.create_pandas_dataframe_agent`.
```
But when I changed to `from langchain_experimental.agents import
create_pandas_dataframe_agent`, it was actually wrong:
```python
Traceback (most recent call last):
File "/Users/dongwm/test/main.py", line 2, in <module>
from langchain_experimental.agents import create_pandas_dataframe_agent
ImportError: cannot import name 'create_pandas_dataframe_agent' from 'langchain_experimental.agents' (/Users/dongwm/test/venv/lib/python3.11/site-packages/langchain_experimental/agents/__init__.py)
```
I should use `from langchain_experimental.agents.agent_toolkits import
create_pandas_dataframe_agent`. In order to solve the problem and make
it compatible, I added additional import code to the
langchain_experimental package. Now it can be like this Used `from
langchain_experimental.agents import create_pandas_dataframe_agent`
- **Twitter handle:** [lin_bob57617](https://twitter.com/lin_bob57617)
- **Description:** Adds a tqdm progress bar to OllamaEmbeddings when
embedding a list.
- **Issue:** Related to #13637, but extended to Ollama.
- **Dependencies:** `tqdm` made a necessary dependency.
Thanks to @ugm2 for helping identify a common problem. Embeddings take a
very long time to finish on local machines, and require a progress bar
to help identify if one should even attempt the workload.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** Added a line to pass the tenant parameter to
add_data_object
- **Issue:** An extra line added from the fix for #9956
- **Dependencies:** n/a
- **Tag maintainer:** @baskaryan
Tested locally, works as expected with the line change.
---------
Co-authored-by: Simon Dai <simon6752@gmail.com>
Description: Some Elastic indexes do not return a 'metadata' field in
'_source'. However, prior to this PR, the code assumed there always is a
'metadata' field. This PR adds support for cases where the field is
missing by adding it manually.
Issue: #13869
**Description:**
This PR adds Databricks Vector Search as a new vector store in
LangChain.
- [x] Add `DatabricksVectorSearch` in `langchain/vectorstores/`
- [x] Unit tests
- [x] Add
[`databricks-vectorsearch`](https://pypi.org/project/databricks-vectorsearch/)
as a new optional dependency
We ran the following checks:
- `make format` passed ✅
- `make lint` failed but the failures were caused by other files
+ Files touched by this PR passed the linter ✅
- `make test` passed ✅
- `make coverage` failed but the failures were caused by other files.
Tests added by or related to this PR all passed
+ langchain/vectorstores/databricks_vector_search.py test coverage 94% ✅
- `make spell_check` passed ✅
The example notebook and updates to the [provider's documentation
page](https://github.com/langchain-ai/langchain/blob/master/docs/docs/integrations/providers/databricks.md)
will be added later in a separate PR.
**Dependencies:**
Optional dependency:
[`databricks-vectorsearch`](https://pypi.org/project/databricks-vectorsearch/)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This pull request addresses an issue found in the example code within
the docstring of `libs/core/langchain_core/runnables/passthrough.py`
The original code snippet caused a `NameError` due to the missing import
of `RunnableLambda`. The error was as follows:
```
12 return "completion"
13
---> 14 chain = RunnableLambda(fake_llm) | {
15 'original': RunnablePassthrough(), # Original LLM output
16 'parsed': lambda text: text[::-1] # Parsing logic
NameError: name 'RunnableLambda' is not defined
```
To resolve this, I have modified the example code to include the
necessary import statement for `RunnableLambda`. Additionally, I have
adjusted the indentation in the code snippet to ensure consistency and
readability.
The modified code now successfully defines and utilizes
`RunnableLambda`, ensuring that users referencing the docstring will
have a functional and clear example to follow.
There are no related GitHub issues for this particular change.
Modified Code:
```python
from langchain_core.runnables import RunnablePassthrough, RunnableParallel
from langchain_core.runnables import RunnableLambda
runnable = RunnableParallel(
origin=RunnablePassthrough(),
modified=lambda x: x+1
)
runnable.invoke(1) # {'origin': 1, 'modified': 2}
def fake_llm(prompt: str) -> str: # Fake LLM for the example
return "completion"
chain = RunnableLambda(fake_llm) | {
'original': RunnablePassthrough(), # Original LLM output
'parsed': lambda text: text[::-1] # Parsing logic
}
chain.invoke('hello') # {'original': 'completion', 'parsed': 'noitelpmoc'}
```
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Added a retriever for the Outline API to ask
questions on knowledge base
- **Issue:** resolves#11814
- **Dependencies:** None
- **Tag maintainer:** @baskaryan
- **Description:** Simple change, I just added title metadata to
GoogleDriveLoader for optional File Loaders
- **Dependencies:** no dependencies
- **Tag maintainer:** @hwchase17
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This PR provides idiomatic implementations for the exact-match and the
semantic LLM caches using Astra DB as backend through the database's
HTTP JSON API. These caches require the `astrapy` library as dependency.
Comes with integration tests and example usage in the `llm_cache.ipynb`
in the docs.
@baskaryan this is the Astra DB counterpart for the Cassandra classes
you merged some time ago, tagging you for your familiarity with the
topic. Thank you!
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This PR adds a chat message history component that uses Astra DB for
persistence through the JSON API.
The `astrapy` package is required for this class to work.
I have added tests and a small notebook, and updated the relevant
references in the other docs pages.
(@rlancemartin this is the counterpart of the Cassandra equivalent class
you so helpfully reviewed back at the end of June)
Thank you!
- **Description:** This commit fixed the problem that Redis vector store
will change the value of a metadata from 0 to empty when saving the
document, which should be an un-intended behavior.
- **Issue:** N/A
- **Dependencies:** N/A
**Description:** Currently, if we pass in a ToolMessage back to the
chain, it crashes with error
`Got unsupported message type: `
This fixes it.
Tested locally
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** BaseStringMessagePromptTemplate.from_template was
passing the value of partial_variables into cls(...) via **kwargs,
rather than passing it to PromptTemplate.from_template. Which resulted
in those *partial_variables being* lost and becoming required
*input_variables*.
Co-authored-by: Josep Pon Farreny <josep.pon-farreny@siemens.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Fix some circular deps:
- move PromptValue into top level module bc both PromptTemplates and
OutputParsers import
- move tracer context vars to `tracers.context` and import them in
functions in `callbacks.manager`
- add core import tests
