samagra-development / ai-tools Goto Github PK
View Code? Open in Web Editor NEWAI Tooling to bootstrap applications fast
AI Tooling to bootstrap applications fast
Add Prometheus server to the project and update the Docker Compose file to include the necessary configurations.
By adding Prometheus server and updating the Docker Compose file, the project will have monitoring capabilities. Prometheus will be able to scrape metrics from the services defined in the Docker Compose file, providing valuable insights into the performance and health of the system.
AI-tools
Samagra
Social Welfare
Docker, Prometheus
Medium
DevOps
Monitoring
Create a fine-grained access token that allows pushing Docker images to GitHub Packages.
The access token will provide the necessary credentials to push Docker images to GitHub Packages. By creating a fine-grained access token, you can ensure that it only has the required permissions and restrict access to specific repositories and packages, enhancing security and access control.
[List any technical details about the proposed implementation, including any specific technologies that will be used.]
[N/A]
AI-tools
Samagra
Social Welfare
GitHub, Docker
Medium
DevOps
Credentials Management
Use this - https://flask.palletsprojects.com/en/1.1.x/testing/#the-first-test
Sanjay
POST
/useCase/modelPOST
/healthPOST
/embeddings/modelSamvit
async def GPT3_farmer_prompt(data, context):
# df1 = pd.read_csv('df1.csv')
df1 = pd.read_csv('df_all_new_data.csv')
content = df1['Content']
actual_sentences = df1['sentence_constructed']
encoded_string = df1['encoded_sentence']
encoded = []
for en_str in encoded_string:
encoded.append(np.array(json.loads(en_str)))
encoded = np.array(encoded)
model = SentenceTransformer('bert-base-nli-mean-tokens')
def get_prediction(sent):
sim = cosine_similarity(
model.encode([sent]),
encoded
)
max_prob = np.argmax(sim)
max_sim = np.max(sim)
return actual_sentences[max_prob], content[max_prob], max_sim
We have to add this function as an async helper function (if possible) in the repo.
Karun
The CI should
When
Outputs
Karun
It appears that the readme file of the project is currently outdated and lacks documentation for contributors. Assuming that the project team wants to improve the documentation, they may welcome contributions from interested parties who have the necessary expertise. It is also possible that they may have a plan in place to update the documentation themselves, but have not yet had the resources or time to do so. Regardless of the reason, it is essential that the documentation is kept up-to-date to ensure effective collaboration and understanding among the contributors. Interested parties may want to reach out to the project team to inquire about the status of the documentation and offer their assistance if possible.
AI Toolchain is a collection of tools for quickly building and deploying machine learning models for various use cases. Currently, the toolchain includes a text translation model, and more models may be added in the future. It abstracts the dirty details of how a model works similar to Huggingface and gives a clean API that you can orchestrate at a BFF level.
Neural coreference resolution (overview) is a natural language processing (NLP) task that involves identifying when two or more words or phrases in a text refer to the same entity or concept. This process is crucial for understanding the context and meaning of a text, as it helps in resolving ambiguities and connecting different parts of a text.
For example:
Non-coreferenced conversation:
User : 'Can you tell me where are the shops for paddy seeds?'
User : 'What is the price for them?'
Coreferenced conversation:
User : 'Can you tell me where are the shops for paddy seeds?'
User : 'What is the price for paddy seeds?'
Neural coreference resolution models usually involve various components, such as:
Detecting the different parts of a sentence and their relationships with each other
Identifying potential words or phrases (mentions) that may be involved in coreference relations (they all refer to the same entity)
Computing a score for each pair of mentions, representing the likelihood that they corefer.
Grouping mentions into clusters, where each cluster represents a single entity or concept.
For the last message in the conversation (or for all messages succeeding the first), replace the phrases in each cluster by the common word that gives the entire picture.
Deploy the above setup as a part of ai-tools package such that it can be dockerized and then accessed through an API setup.
Hard
Python, NLP
8 Weeks
See the setup here
The setup here is just an example or baseline solution of how it could be carried out. We are currently focusing this project on using the Spacy model to carry out coreference. Exploration of other techniques is encouraged only if the this one fails.
https://galhever.medium.com/a-review-to-co-reference-resolution-models-f44b4360a00
https://explosion.ai/blog/coref
explosion/spaCy#11585 (reply in thread)
This issue is nominated for Code for GovTech (C4GT) 2023 edition.
C4GT is India's first annual coding program to create a community that can build and contribute to global Digital Public Goods. If you want to use Open Source GovTech to create impact, then this is the opportunity for you! More about C4GT here: https://codeforgovtech.in/
The scope of this ticket has now expanded to make it the 'enabling conversation' part of 'FAQ bot'.
The FAQ bot allows a user to be able to provide content input in the form on csvs, free text, pdfs, audio, video and the bot is able to add it to a 'Content DB'. The user is then able to interact with the bot via text/speech on related content and the bot is able to identify relevant content using RAG techniques and be able to be able to respond to the user in a conversational manner.
This ticket covers the enabling conversation +small model deployment/finetuning pipeline. It includes the following tasks in its scope:
Alternatives
Rotated at an instance level injected by Infra. Load balancing - round robin through NginX.
Sanjay
I found some small issues in the src/text_translation/ai4bharat/deploy.sh file.
#!/bin/bash
Remote service onboarding should not include code changes. They should be onboarded directly through repository.private.json
which overrides the repository.json
Add a header to the response when it comes from a cached function to indicate its origin.
ai-tools-cached
, to indicate that the response is from a cached functionBy adding a header to the response from a cached function, it becomes possible to differentiate between responses served from cache and those generated in real-time. This information can be useful for debugging and monitoring purposes, allowing developers to understand the performance and behavior of the cached functions.
ai-tools-cached
, in the response when it comes from a cached functionAI-tools
Samagra
Social Welfare
Backend Development
Medium
Backend
API Development
Gitpod setup for faster hacking and contributions.
Use Case | Model | Status |
---|---|---|
Use Case 1 | Model 1 | Add ticket reference here |
Need to separate out componets such that GPU required and no required ones can be hosted separately and each component can be deployed in individual docker containers
Webhook on the server => listen for push to master => docker container build => deploy through docker compose
text_translation/bhashini/remote
model specifically)Evaluate Sagemaker as a potential solution for deploying AI-tools and provide documentation to guide users in deploying all models to Sagemaker.
sagemaker.md
guideBy evaluating Sagemaker for deploying AI-tools and documenting the deployment process, users will have clear instructions on how to deploy all models to Sagemaker. This enables the easy adoption and usage of AI-tools in a Sagemaker environment.
sagemaker.md
guide is created, providing instructions for deploying AI-tools on SagemakerAI-tools
Samagra
Social Welfare
AWS Sagemaker, AI-tools
Hard
Deployment
Infrastructure
Something like this but for quart.
The server doesn't restart when changes to src folder happens.
Use this for any external dependent services.
Python decorator over an API Call
Input
Implementation Details
Output
I found some small issues in the deploy.sh file.
#!/bin/bash
Line 3 in e8c41e3
Current sizes
root@e25f48a1466e:/usr/local/lib/python3.8/site-packages# du -sh * | sort -hr
2.6G nvidia
1.3G torch
184M triton
87M torchvision
80M plotly
76M scipy
65M cmake
49M pandas
35M sklearn
35M scipy.libs
35M numpy.libs
34M sympy
Dependency Graph
aiohttp 3.8.4 Async http client/server framework (asyncio)
├── aiosignal >=1.1.2
│ └── frozenlist >=1.1.0
├── async-timeout >=4.0.0a3,<5.0
├── attrs >=17.3.0
├── charset-normalizer >=2.0,<4.0
├── frozenlist >=1.1.1
├── multidict >=4.5,<7.0
└── yarl >=1.0,<2.0
├── idna >=2.0
└── multidict >=4.0
async-cache 1.1.1 An asyncio Cache
asyncio 3.4.3 reference implementation of PEP 3156
en-coreference-web-trf 3.4.0a2 English transformer pipeline to demonstrate the experimental coreference components. Components: sentencizer, transfomer, coref, span_resolver, span_cleaner.
├── spacy >=3.3.0,<3.5.0
│ ├── catalogue >=2.0.6,<2.1.0
│ ├── cymem >=2.0.2,<2.1.0
│ ├── jinja2 *
│ │ └── markupsafe >=2.0
│ ├── langcodes >=3.2.0,<4.0.0
│ ├── murmurhash >=0.28.0,<1.1.0
│ ├── numpy >=1.15.0
│ ├── packaging >=20.0
│ ├── pathy >=0.3.5
│ │ ├── smart-open >=5.2.1,<7.0.0
│ │ └── typer >=0.3.0,<1.0.0
│ │ └── click >=7.1.1,<9.0.0
│ │ └── colorama *
│ ├── preshed >=3.0.2,<3.1.0
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ └── murmurhash >=0.28.0,<1.1.0 (circular dependency aborted here)
│ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0
│ │ └── typing-extensions >=4.2.0
│ ├── requests >=2.13.0,<3.0.0
│ │ ├── certifi >=2017.4.17
│ │ ├── charset-normalizer >=2,<4
│ │ ├── idna >=2.5,<4
│ │ └── urllib3 >=1.21.1,<1.27
│ ├── setuptools *
│ ├── smart-open >=5.2.1,<7.0.0 (circular dependency aborted here)
│ ├── spacy-legacy >=3.0.10,<3.1.0
│ ├── spacy-loggers >=1.0.0,<2.0.0
│ ├── srsly >=2.4.3,<3.0.0
│ │ └── catalogue >=2.0.3,<2.1.0 (circular dependency aborted here)
│ ├── thinc >=8.1.0,<8.2.0
│ │ ├── blis >=0.7.8,<0.8.0
│ │ │ └── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── catalogue >=2.0.4,<2.1.0 (circular dependency aborted here)
│ │ ├── confection >=0.0.1,<1.0.0
│ │ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ │ └── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ ├── murmurhash >=1.0.2,<1.1.0 (circular dependency aborted here)
│ │ ├── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── packaging >=20.0 (circular dependency aborted here)
│ │ ├── preshed >=3.0.2,<3.1.0 (circular dependency aborted here)
│ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ ├── setuptools * (circular dependency aborted here)
│ │ ├── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ └── wasabi >=0.8.1,<1.2.0
│ ├── tqdm >=4.38.0,<5.0.0
│ │ └── colorama * (circular dependency aborted here)
│ ├── typer >=0.3.0,<0.8.0 (circular dependency aborted here)
│ └── wasabi >=0.9.1,<1.1.0 (circular dependency aborted here)
├── spacy-experimental >=0.6.1,<0.7.0
│ └── spacy >=3.3.0,<3.6.0
│ ├── catalogue >=2.0.6,<2.1.0
│ ├── cymem >=2.0.2,<2.1.0
│ ├── jinja2 *
│ │ └── markupsafe >=2.0
│ ├── langcodes >=3.2.0,<4.0.0
│ ├── murmurhash >=0.28.0,<1.1.0
│ ├── numpy >=1.15.0
│ ├── packaging >=20.0
│ ├── pathy >=0.3.5
│ │ ├── smart-open >=5.2.1,<7.0.0
│ │ └── typer >=0.3.0,<1.0.0
│ │ └── click >=7.1.1,<9.0.0
│ │ └── colorama *
│ ├── preshed >=3.0.2,<3.1.0
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ └── murmurhash >=0.28.0,<1.1.0 (circular dependency aborted here)
│ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0
│ │ └── typing-extensions >=4.2.0
│ ├── requests >=2.13.0,<3.0.0
│ │ ├── certifi >=2017.4.17
│ │ ├── charset-normalizer >=2,<4
│ │ ├── idna >=2.5,<4
│ │ └── urllib3 >=1.21.1,<1.27
│ ├── setuptools *
│ ├── smart-open >=5.2.1,<7.0.0 (circular dependency aborted here)
│ ├── spacy-legacy >=3.0.10,<3.1.0
│ ├── spacy-loggers >=1.0.0,<2.0.0
│ ├── srsly >=2.4.3,<3.0.0
│ │ └── catalogue >=2.0.3,<2.1.0 (circular dependency aborted here)
│ ├── thinc >=8.1.0,<8.2.0
│ │ ├── blis >=0.7.8,<0.8.0
│ │ │ └── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── catalogue >=2.0.4,<2.1.0 (circular dependency aborted here)
│ │ ├── confection >=0.0.1,<1.0.0
│ │ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ │ └── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ ├── murmurhash >=1.0.2,<1.1.0 (circular dependency aborted here)
│ │ ├── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── packaging >=20.0 (circular dependency aborted here)
│ │ ├── preshed >=3.0.2,<3.1.0 (circular dependency aborted here)
│ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ ├── setuptools * (circular dependency aborted here)
│ │ ├── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ └── wasabi >=0.8.1,<1.2.0
│ ├── tqdm >=4.38.0,<5.0.0
│ │ └── colorama * (circular dependency aborted here)
│ ├── typer >=0.3.0,<0.8.0 (circular dependency aborted here)
│ └── wasabi >=0.9.1,<1.1.0 (circular dependency aborted here)
└── spacy-transformers >=1.1.2,<1.2.0
├── spacy >=3.4.0,<4.0.0
│ ├── catalogue >=2.0.6,<2.1.0
│ ├── cymem >=2.0.2,<2.1.0
│ ├── jinja2 *
│ │ └── markupsafe >=2.0
│ ├── langcodes >=3.2.0,<4.0.0
│ ├── murmurhash >=0.28.0,<1.1.0
│ ├── numpy >=1.15.0
│ ├── packaging >=20.0
│ ├── pathy >=0.3.5
│ │ ├── smart-open >=5.2.1,<7.0.0
│ │ └── typer >=0.3.0,<1.0.0
│ │ └── click >=7.1.1,<9.0.0
│ │ └── colorama *
│ ├── preshed >=3.0.2,<3.1.0
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ └── murmurhash >=0.28.0,<1.1.0 (circular dependency aborted here)
│ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0
│ │ └── typing-extensions >=4.2.0
│ ├── requests >=2.13.0,<3.0.0
│ │ ├── certifi >=2017.4.17
│ │ ├── charset-normalizer >=2,<4
│ │ ├── idna >=2.5,<4
│ │ └── urllib3 >=1.21.1,<1.27
│ ├── setuptools *
│ ├── smart-open >=5.2.1,<7.0.0 (circular dependency aborted here)
│ ├── spacy-legacy >=3.0.10,<3.1.0
│ ├── spacy-loggers >=1.0.0,<2.0.0
│ ├── srsly >=2.4.3,<3.0.0
│ │ └── catalogue >=2.0.3,<2.1.0 (circular dependency aborted here)
│ ├── thinc >=8.1.0,<8.2.0
│ │ ├── blis >=0.7.8,<0.8.0
│ │ │ └── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── catalogue >=2.0.4,<2.1.0 (circular dependency aborted here)
│ │ ├── confection >=0.0.1,<1.0.0
│ │ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ │ └── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ │ ├── murmurhash >=1.0.2,<1.1.0 (circular dependency aborted here)
│ │ ├── numpy >=1.15.0 (circular dependency aborted here)
│ │ ├── packaging >=20.0 (circular dependency aborted here)
│ │ ├── preshed >=3.0.2,<3.1.0 (circular dependency aborted here)
│ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ ├── setuptools * (circular dependency aborted here)
│ │ ├── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ │ └── wasabi >=0.8.1,<1.2.0
│ ├── tqdm >=4.38.0,<5.0.0
│ │ └── colorama * (circular dependency aborted here)
│ ├── typer >=0.3.0,<0.8.0 (circular dependency aborted here)
│ └── wasabi >=0.9.1,<1.1.0 (circular dependency aborted here)
├── spacy-alignments >=0.7.2,<1.0.0
├── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
├── torch >=1.6.0
│ ├── filelock *
│ ├── jinja2 * (circular dependency aborted here)
│ ├── networkx *
│ ├── nvidia-cublas-cu11 11.10.3.66
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel *
│ ├── nvidia-cuda-cupti-cu11 11.7.101
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cuda-nvrtc-cu11 11.7.99
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cuda-runtime-cu11 11.7.99
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cudnn-cu11 8.5.0.96
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cufft-cu11 10.9.0.58
│ ├── nvidia-curand-cu11 10.2.10.91
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cusolver-cu11 11.4.0.1
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-cusparse-cu11 11.7.4.91
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── nvidia-nccl-cu11 2.14.3
│ ├── nvidia-nvtx-cu11 11.7.91
│ │ ├── setuptools * (circular dependency aborted here)
│ │ └── wheel * (circular dependency aborted here)
│ ├── sympy *
│ │ └── mpmath >=0.19
│ ├── triton 2.0.0
│ │ ├── cmake *
│ │ ├── filelock * (circular dependency aborted here)
│ │ ├── lit *
│ │ └── torch * (circular dependency aborted here)
│ └── typing-extensions * (circular dependency aborted here)
└── transformers >=3.4.0,<4.26.0
├── filelock * (circular dependency aborted here)
├── huggingface-hub >=0.10.0,<1.0
│ ├── filelock * (circular dependency aborted here)
│ ├── packaging >=20.9 (circular dependency aborted here)
│ ├── pyyaml >=5.1
│ ├── requests * (circular dependency aborted here)
│ ├── tqdm >=4.42.1 (circular dependency aborted here)
│ └── typing-extensions >=3.7.4.3 (circular dependency aborted here)
├── numpy >=1.17 (circular dependency aborted here)
├── packaging >=20.0 (circular dependency aborted here)
├── pyyaml >=5.1 (circular dependency aborted here)
├── regex !=2019.12.17
├── requests * (circular dependency aborted here)
├── tokenizers >=0.11.1,<0.11.3 || >0.11.3,<0.14
└── tqdm >=4.27 (circular dependency aborted here)
flake8 6.0.0 the modular source code checker: pep8 pyflakes and co
├── mccabe >=0.7.0,<0.8.0
├── pycodestyle >=2.10.0,<2.11.0
└── pyflakes >=3.0.0,<3.1.0
flask 2.2.3 A simple framework for building complex web applications.
├── click >=8.0
│ └── colorama *
├── importlib-metadata >=3.6.0
│ └── zipp >=0.5
├── itsdangerous >=2.0
├── jinja2 >=3.0
│ └── markupsafe >=2.0
└── werkzeug >=2.2.2
└── markupsafe >=2.1.1
inference 0.1
matplotlib 3.7.1 Python plotting package
├── contourpy >=1.0.1
│ └── numpy >=1.16
├── cycler >=0.10
├── fonttools >=4.22.0
├── importlib-resources >=3.2.0
│ └── zipp >=3.1.0
├── kiwisolver >=1.0.1
├── numpy >=1.20
├── packaging >=20.0
├── pillow >=6.2.0
├── pyparsing >=2.3.1
└── python-dateutil >=2.7
└── six >=1.5
numpy 1.24.2 Fundamental package for array computing in Python
openai 0.27.4 Python client library for the OpenAI API
├── aiohttp *
│ ├── aiosignal >=1.1.2
│ │ └── frozenlist >=1.1.0
│ ├── async-timeout >=4.0.0a3,<5.0
│ ├── attrs >=17.3.0
│ ├── charset-normalizer >=2.0,<4.0
│ ├── frozenlist >=1.1.1 (circular dependency aborted here)
│ ├── multidict >=4.5,<7.0
│ └── yarl >=1.0,<2.0
│ ├── idna >=2.0
│ └── multidict >=4.0 (circular dependency aborted here)
├── requests >=2.20
│ ├── certifi >=2017.4.17
│ ├── charset-normalizer >=2,<4
│ ├── idna >=2.5,<4
│ └── urllib3 >=1.21.1,<1.27
└── tqdm *
└── colorama *
openai-async 0.0.3 A light-weight, asynchronous client for OpenAI API - text completion, image generation and embeddings.
├── httpx *
│ ├── certifi *
│ ├── httpcore >=0.15.0,<0.18.0
│ │ ├── anyio >=3.0,<5.0
│ │ │ ├── idna >=2.8
│ │ │ └── sniffio >=1.1
│ │ ├── certifi * (circular dependency aborted here)
│ │ ├── h11 >=0.13,<0.15
│ │ └── sniffio >=1.0.0,<2.0.0 (circular dependency aborted here)
│ ├── idna * (circular dependency aborted here)
│ └── sniffio * (circular dependency aborted here)
└── pytest *
├── colorama *
├── exceptiongroup >=1.0.0rc8
├── iniconfig *
├── packaging *
├── pluggy >=0.12,<2.0
└── tomli >=1.0.0
pandas 2.0.0 Powerful data structures for data analysis, time series, and statistics
├── numpy >=1.20.3
├── numpy >=1.21.0
├── numpy >=1.23.2
├── python-dateutil >=2.8.2
│ └── six >=1.5
├── pytz >=2020.1
└── tzdata >=2022.1
pipdeptree 2.0.0 Command line utility to show dependency tree of packages
└── pip >=6.0.0
plotly 5.14.1 An open-source, interactive data visualization library for Python
├── packaging *
└── tenacity >=6.2.0
python-dotenv 1.0.0 Read key-value pairs from a .env file and set them as environment variables
quart 0.18.4 A Python ASGI web microframework with the same API as Flask
├── aiofiles *
├── blinker <1.6
├── click >=8.0.0
│ └── colorama *
├── hypercorn >=0.11.2
│ ├── h11 *
│ ├── h2 >=3.1.0
│ │ ├── hpack >=4.0,<5
│ │ └── hyperframe >=6.0,<7
│ ├── priority *
│ ├── toml *
│ └── wsproto >=0.14.0
│ └── h11 >=0.9.0,<1 (circular dependency aborted here)
├── importlib-metadata *
│ └── zipp >=0.5
├── itsdangerous *
├── jinja2 *
│ └── markupsafe >=2.0
├── markupsafe *
└── werkzeug >=2.2.0
└── markupsafe >=2.1.1
scikit-learn 1.2.2 A set of python modules for machine learning and data mining
├── joblib >=1.1.1
├── numpy >=1.17.3
├── scipy >=1.3.2
│ └── numpy >=1.18.5,<1.26.0
└── threadpoolctl >=2.0.0
sklearn 0.0.post4 deprecated sklearn package, use scikit-learn instead
spacy-experimental 0.6.2 Cutting-edge experimental spaCy components and features
└── spacy >=3.3.0,<3.6.0
├── catalogue >=2.0.6,<2.1.0
├── cymem >=2.0.2,<2.1.0
├── jinja2 *
│ └── markupsafe >=2.0
├── langcodes >=3.2.0,<4.0.0
├── murmurhash >=0.28.0,<1.1.0
├── numpy >=1.15.0
├── packaging >=20.0
├── pathy >=0.3.5
│ ├── smart-open >=5.2.1,<7.0.0
│ └── typer >=0.3.0,<1.0.0
│ └── click >=7.1.1,<9.0.0
│ └── colorama *
├── preshed >=3.0.2,<3.1.0
│ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ └── murmurhash >=0.28.0,<1.1.0 (circular dependency aborted here)
├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0
│ └── typing-extensions >=4.2.0
├── requests >=2.13.0,<3.0.0
│ ├── certifi >=2017.4.17
│ ├── charset-normalizer >=2,<4
│ ├── idna >=2.5,<4
│ └── urllib3 >=1.21.1,<1.27
├── setuptools *
├── smart-open >=5.2.1,<7.0.0 (circular dependency aborted here)
├── spacy-legacy >=3.0.10,<3.1.0
├── spacy-loggers >=1.0.0,<2.0.0
├── srsly >=2.4.3,<3.0.0
│ └── catalogue >=2.0.3,<2.1.0 (circular dependency aborted here)
├── thinc >=8.1.0,<8.2.0
│ ├── blis >=0.7.8,<0.8.0
│ │ └── numpy >=1.15.0 (circular dependency aborted here)
│ ├── catalogue >=2.0.4,<2.1.0 (circular dependency aborted here)
│ ├── confection >=0.0.1,<1.0.0
│ │ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ │ └── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ ├── cymem >=2.0.2,<2.1.0 (circular dependency aborted here)
│ ├── murmurhash >=1.0.2,<1.1.0 (circular dependency aborted here)
│ ├── numpy >=1.15.0 (circular dependency aborted here)
│ ├── packaging >=20.0 (circular dependency aborted here)
│ ├── preshed >=3.0.2,<3.1.0 (circular dependency aborted here)
│ ├── pydantic >=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<1.11.0 (circular dependency aborted here)
│ ├── setuptools * (circular dependency aborted here)
│ ├── srsly >=2.4.0,<3.0.0 (circular dependency aborted here)
│ └── wasabi >=0.8.1,<1.2.0
├── tqdm >=4.38.0,<5.0.0
│ └── colorama * (circular dependency aborted here)
├── typer >=0.3.0,<0.8.0 (circular dependency aborted here)
└── wasabi >=0.9.1,<1.1.0 (circular dependency aborted here)
tiktoken 0.3.3 tiktoken is a fast BPE tokeniser for use with OpenAI's models
├── regex >=2022.1.18
└── requests >=2.26.0
├── certifi >=2017.4.17
├── charset-normalizer >=2,<4
├── idna >=2.5,<4
└── urllib3 >=1.21.1,<1.27
Update the workflow to make a package public and automatically connect it to the repository in GitHub Packages.
The updated workflow will automatically make the package public and establish a connection to the repository in GitHub Packages. This ensures that the package is easily accessible and discoverable by users who can benefit from its functionalities.
AI-tools
Samagra
Social Welfare
GitHub Actions
Medium
DevOps
Maintenance
Add a header ai-tools-response-time: 289
which shows time taken for inference in ms.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.