Package Health Score

87 / 100

security
No known security issues
popularity
Small
maintenance
Healthy
community
Active

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48

Popularity

Small

GitHub Stars: 96.7K
Forks: 15.74K
Contributors: 490

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package langchain-qdrant, we found that it has been starred 96,702 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 5, 2024
Direct Vulnerabilities: 0
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0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

Yes

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Maintenance

Healthy

Commit Frequency

Open Issues: 415
Open PR: 38
Last Release: 2 months ago
Last Commit: 22 hours ago

Further analysis of the maintenance status of langchain-qdrant based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that langchain-qdrant demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 490
Funding: No

A good and healthy external contribution signal for langchain-qdrant project, which invites more than one hundred open source maintainers to collaborate on the repository.

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Package

Python Versions Compatibility: <4,>=3.9

Age: 8 months
Latest Release: 2 months ago
Dependencies: 0 Direct
Versions: 8
Maintainers: 2
Wheels: OS Independent

Readme

langchain-qdrant

This package contains the LangChain integration with Qdrant.

Installation

pip install -U langchain-qdrant

Usage

The Qdrant class exposes the connection to the Qdrant vector store.

from langchain_qdrant import Qdrant

embeddings = ... # use a LangChain Embeddings class

vectorstore = Qdrant.from_existing_collection(
    embeddings=embeddings,
    collection_name="",
    url="http://localhost:6333",
)

FAQs

What is langchain-qdrant?

An integration package connecting Qdrant and LangChain. Visit Snyk Advisor to see a full health score report for langchain-qdrant, including popularity, security, maintenance & community analysis.

Is langchain-qdrant popular?

We’re still processing downloads data for the python package langchain-qdrant. Visit the popularity section on Snyk Advisor to see the full popularity analysis.

Is langchain-qdrant well maintained?

We found that langchain-qdrant demonstrated a healthy version release cadence and project activity. It has a community of 490 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is langchain-qdrant safe to use?

The python package langchain-qdrant was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 25 December-2024, at 12:41 (UTC).

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langchain-qdrant

An integration package connecting Qdrant and LangChain For more information about how to use this package see README

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Package

Readme

langchain-qdrant

Installation

Usage

FAQs

What is langchain-qdrant?

Is langchain-qdrant popular?

Is langchain-qdrant well maintained?

Is langchain-qdrant safe to use?

Build a secure application checklist

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Scan your app for vulnerabilities

Fix identified vulnerabilities

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Package Health Score

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Security and license risk for latest version

Commit Frequency

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Readme

langchain-qdrant

Installation

Usage

FAQs

What is langchain-qdrant?

Is langchain-qdrant popular?

Is langchain-qdrant well maintained?

Is langchain-qdrant safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

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