We recently renamed `MLflow Deployments Server` to `MLflow AI Gateway`
in mlflow. This PR updates the relevant notebooks to use `MLflow AI
gateway`
---
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---------
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
docs:integrations:vectorstores:chroma:fix_typo
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with
- **Description:** fix_typo in docs:integrations:vectorstores:chroma
https://python.langchain.com/docs/integrations/vectorstores/chroma/
- **Issue:** https://github.com/langchain-ai/langchain/issues/26561
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…omSelfQueryRetriever`
This commit corrects an issue in the `_get_docs_with_query` method of
the `CustomSelfQueryRetriever` class. The method was incorrectly using
`self.vectorstore.similarity_search_with_score(query, **search_kwargs)`
without including the `self` argument, which is required for proper
method invocation.
The `self` argument is necessary for calling instance methods and
accessing instance attributes. By including `self` in the method call,
we ensure that the method is correctly executed in the context of the
current instance, allowing it to function as intended.
No other changes were made to the method's logic or functionality.
Thank you for contributing to LangChain!
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Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
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Co-authored-by: Erick Friis <erick@langchain.dev>
Firecrawl integration is currently on v0 - which is supported until
version 0.0.20.
@rafaelsideguide is working on a pr for v1 but meanwhile we should fix
the docs.
Thank you for contributing to LangChain!
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- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, please
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1. a test for the integration, preferably unit tests that do not rely on
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- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
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Additional guidelines:
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- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
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---------
Co-authored-by: Jess Ou <jessou@jesss-mbp.local.meter>
Co-authored-by: Erick Friis <erick@langchain.dev>
While going through the chatbot tutorial, I noticed a couple of typos
and grammatical issues. Also, the pip install command for
langchain_community was commented out, but the document mentions
installing it.
---------
Co-authored-by: Erick Friis <erickfriis@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
docs:tutorials:llm_chain:fix typo
- [ ] **PR message**:
fix typo in llm chain tutorial
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include
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Additional guidelines:
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Co-authored-by: Erick Friis <erick@langchain.dev>
Hello,
fix: https://github.com/langchain-ai/langchain/issues/26183
Adding documentation regarding SQL like filter for Google BigQuery
Vector Search coming in next langchain-google-community 1.0.9 release.
Note: langchain-google-community==1.0.9 is not yet released
Question: There is no way to warn the user int the doc about the
availability of a feature after a specific package version ?
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Thank you for contributing to LangChain!
- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
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- [x] **PR message**: ***Delete this entire checklist*** and replace
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- **Description:** Fix docstring for two functions that look like have
docstrings carried over from other functions.
- **Issue:** Not found issue reporting the miss-leading docstrings.
- **Dependencies:** None
- **Twitter handle:**
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Additional guidelines:
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- Please do not add dependencies to pyproject.toml files (even optional
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---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Changed
> "At a high-level, the steps of constructing a knowledge are from text
are:"
to
> "At a high-level, the steps of constructing a knowledge graph from
text are:"
Co-authored-by: Erick Friis <erick@langchain.dev>
This PR fixes a minor typo in the ScrapflyLoader documentation. The word
"passigng" was changed to "passing."
Before: passigng
After: passing
This change improves the clarity and professionalism of the
documentation.
Co-authored-by: Ashar <asharmalik.ds193@gmail.com>
Updating the gateway pages in the documentation to name the
`langchain-databricks` integration.
---------
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **PR title**: "community: add Jina Search tool"
- **Description:** Added the Jina Search tool for querying the Jina
search API. This includes the implementation of the JinaSearchAPIWrapper
and the JinaSearch tool, along with a Jupyter notebook example
demonstrating its usage.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** [Twitter
handle](https://x.com/yashp3020?t=7wM0gQ7XjGciFoh9xaBtqA&s=09)
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include
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---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Thank you for contributing to LangChain!
- [ ] **PR title**:
docs: fix typo in summarization_tutorial
- [ ] **PR message**:
docs: fix couple of typos in summarization_tutorial
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**Description:** [IPEX-LLM](https://github.com/intel-analytics/ipex-llm)
is a PyTorch library for running LLM on Intel CPU and GPU (e.g., local
PC with iGPU, discrete GPU such as Arc, Flex and Max) with very low
latency. This PR adds Intel GPU support to `ipex-llm` llm integration.
**Dependencies:** `ipex-llm`
**Contribution maintainer**: @ivy-lv11 @Oscilloscope98
**tests and docs**:
- Add: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/docs/docs/integrations/llms/ipex_llm_gpu.ipynb
- Update: langchain/libs/community/tests/llms/test_ipex_llm.py
---------
Co-authored-by: ivy-lv11 <zhicunlv@gmail.com>
Thank you for contributing to LangChain!
**Description:**
The current documentation of using the Huggingface with Langchain needs
to set return_full_text as False otherwise pipeline by default returns
both the prompt and response as output.
Code to reproduce:
```python
from langchain_huggingface import ChatHuggingFace, HuggingFacePipeline
from langchain_core.messages import (
HumanMessage,
SystemMessage,
)
llm = HuggingFacePipeline.from_model_id(
model_id="microsoft/Phi-3.5-mini-instruct",
task="text-generation",
pipeline_kwargs=dict(
max_new_tokens=512,
do_sample=False,
repetition_penalty=1.03,
# return_full_text=False
),
device=0
)
chat_model = ChatHuggingFace(llm=llm)
messages = [
SystemMessage(content="You're a helpful assistant"),
HumanMessage(
content="What happens when an unstoppable force meets an immovable object?"
),
]
ai_msg = chat_model.invoke(messages)
print(ai_msg.content)
```
Output:
```
<|system|>
You're a helpful assistant<|end|>
<|user|>
What happens when an unstoppable force meets an immovable object?<|end|>
<|assistant|>
The scenario of an "unstoppable force" meeting an "immovable object" is a classic paradox that has puzzled philosophers, scientists, and thinkers for centuries. In physics, however, there are no such things as truly unstoppable forces or immovable objects because all physical entities have mass and interact with other masses through fundamental forces (like gravity).
When we consider the laws of motion, particularly Newton's third law which states that for every action, there is an equal and opposite reaction, it becomes clear that if one were to exist, the other would necessarily be negated by the interaction. For example, if you push against a solid wall with great force, the wall exerts an equal and opposite force back on you, preventing your movement.
In theoretical discussions, this paradox often serves as a thought experiment to explore concepts like determinism versus free will, the limits of physical laws, and the nature of reality itself. However, in practical terms, any force applied to an object will result in some form of deformation, transfer of energy, or movement, depending on the properties of both the force and the object.
So while the idea of an unstoppable force and an immovable object remains a fascinating philosophical conundrum, it does not hold up under the scrutiny of physical laws as we understand them.
```
---------
Co-authored-by: Kirushikesh D B kirushi@ibm.com <kirushi@cccxl012.pok.ibm.com>
