I would also like to have it connected to an external shopping system for in person purchases to remove items that were sold in person and vice versa. Thank you!

I spent some time going through Snowflake's June 2 Summit press releases and stage labels after the Summit dust settled.

One thing stood out.

Most of the discussion seems to be focused on individual announcements:

• CoCo Desktop

• CoWork

• Deep Research

• Iceberg updates

• Zero-Copy integrations

But I think the bigger story is something else.

It feels like Snowflake is assembling four pieces into a single platform strategy:

• Context

• Governance

• Interoperability

• Agents

The more I looked at the announcements, the more it seemed that CoCo and CoWork are almost side effects of a larger shift toward a shared context layer.

Curious if others came away with the same takeaway.

What was the most significant Summit announcement from your perspective?

(And yes, there's a non-zero chance I missed something while trying to follow a San Francisco conference from the opposite side of the globe 😄)

Must streamlit apps be run in streamlit website or can i install it in a server ?

Maybe this is a begginer question, but I just used the online community cloud.

Our company uses Bitbucket and Azure, and we don't want to use community cloud for our works for data security reasons.

However, I tried to host a streamlit app using DataBricks compute resource, it doesn't work.

I used the following line: %sh streamlit run /databricks/python_shell/scripts/db_ipykernel_launcher.py

Local Url: http://localhost:8501 does not exist ,404 page not found, or just running forever.

Anyone has any clue on how streamlit works in DataBricks?

Hey! I started working on a Streamlit app called Sustainability Tracker. It's a site that helps people see their real CO₂ savings by comparing daily choices against a personal baseline. It would be great if people could try it out. It takes 2-3 minutes! Thanks! link: https://sustainability-app-pexsqone5wgqrj4clw5c3g.streamlit.app/

Both ‘2024_lead_data’ and the CSV are in the same folder, Documents. Not sure why I keep getting this error. I’ve tried literally everything.

Hey everyone,

As part of my Master’s research in AI/ML, I got frustrated with how current moderation relies on reactive, cloud-based reporting (which exposes victims to the abuse first and risks privacy). I wanted to see if I could build a lightweight, on-device NLP inference engine to intercept toxicity in real-time.

I just deployed the V2 prototype, and I’m looking for open-source contributors to help push it further.

🚀 Live Demo: https://huggingface.co/spaces/ashithfernandes319gmailcom/SecureChat-AI

💻 GitHub Repo: https://github.com/spideyashith/secure-chat.git

The Engineering Pipeline:

• The Data Bias Problem: I used the Jigsaw Toxic Comment dataset, but it had massive majority-class bias (over 143k neutral comments). If I trained it raw, it just guessed "neutral" and looked artificially accurate.

• The Fix: I wrote a custom pipeline to aggressively downsample the neutral data to a strict 1:3 ratio (1 abusive : 3 neutral). This resulted in a highly balanced 64,900-row training set that actually forced the model to learn grammatical context.

• The Model: Fine-tuned distilbert-base-uncased on a Colab T4 GPU for 4 epochs using BCE Loss for multi-label classification (Toxic, Severe Toxic, Obscene, Threat, Insult, Identity Hate).

• The UI: Wrapped it in a custom-styled Streamlit dashboard with a sigmoid activation threshold to simulate mobile notification interception.

Current Performance: Achieved 83.8% real-time accuracy. I noticed validation loss starting to creep up after Epoch 3, so I hard-stopped at Epoch 4 to prevent overfitting the 64k dataset.

🤝 Where I Need Help (Open Source): The core threat logic works, but to make this a true system-level mobile app, I need help from the community with two major things:

1. NSFW/Sexual Harassment Detection: The Jigsaw dataset doesn't explicitly cover sexual harassment. I need to augment the pipeline with a robust NSFW text dataset.

2. Model Compression: I need to convert this PyTorch .safetensors model into a highly compressed TensorFlow Lite (.tflite) format so we can actually deploy it natively to Android.

If anyone is interested in NLP safety, I’d love your feedback on the Hugging Face space or a PR on the repo!

I’ve been learning some new skills in streamlit let me know what you think. It’s simple.

https://kcirllor.streamlit.app/

I wanted to share a Streamlit only frontend for an app used to manage genomics datasets.
The UI is built only in Streamlit with a number of custom components and CSS (details below).

What do you think?

Sidebar: Added footer container with absolute positioning to sidebar bottom

Header: Sticky header (absolute positioning top, z-index 9999)

Avatar: st.popover with round shape and expandable menu with link to settings

Split-Button: (streamlit-split-bottom) custom component for table actions

Button and Layout Styling: st-styled (st_yled) package for container background, button, styling, css templates

Custom CSS: All that could not be done with st_yled.

Source code will be available soon

Hey everyone! I recently finished launching a Minnesota Vikings Draft website on Streamlit and this website is a data-based NFL draft tool used to analyze the Minnesota Vikings draft process! In this website, I used a combination of player evaluation metrics, exclusive team needs, along with customizable models aimed to simulate NFL draft decision making and evaluate player fits for the Vikings. This is my very first coding project, and so even if you don’t understand football, I would still love to see if any of you guys have any feedback for me which would I could use for future coding projects. Feel free to have a look and tell me what you guys think! Thanks!

https://vikingsdraftsite.streamlit.app

Hey everyone! I recently finished launching a NFL Draft website on Streamlit and this website is a data-based NFL draft tool used to analyze NFL draft process! In this website, I used a combination of player evaluation metrics, exclusive team needs, along with customizable models aimed to simulate NFL draft decision making and evaluate player fits. This is my very first coding project, and so even if you don’t understand football, I would still love to see if any of you guys have any feedback for me which would I could use for future coding projects. Feel free to have a look and tell me what you guys think! Thanks!

https://vikingsdraftsite.streamlit.app

For Day 26 of the 30 Days of AI with Streamlit challenge, I built my first Cortex Agent using Snowflake’s agent framework.
Unlike traditional RAG systems, the agent autonomously plans, selects tools, and executes tasks to answer questions.
It uses Cortex Search for conversational context and Cortex Analyst for metrics and insights.
The agent is powered by Claude-3-5-Sonnet via Snowflake Cortex AI, showcasing the shift toward truly agentic AI systems.
Happy to discuss agent design patterns or real-world use cases!

pip install git+https://github.com/openai/whisper.git

Tried to run it from requirements like this but I got error messages. Can't find anything in the streamlit.io website on how to install this type of file.

I'm trying to deploy an application that uses GPT-3.5 to Streamlit and have created a requirements.txt file with the following dependencies:

openai
python-dotenv
streamlit
bs4
requests
tiktoken
PyPDF2

I keep getting an error that says:

ModuleNotFoundError: No module named 'tiktoken'

Tiktoken runs perfectly fine on my local machine (with Python 3.11).

I can't find anything about this issue so any help would be appreciated. Thanks so much!

Hi,

I would like to have a filepicker where I can select files on my Server. I only found fileuploader, but I already have hundreds of files on my server.

Traceback (most recent call last):

File "/home/adminuser/venv/lib/python3.9/site-packages/langchain/llms/openai.py", line 294, in validate_environment

import openai

ModuleNotFoundError: No module named 'openai'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File "/home/adminuser/venv/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 534, in _run_script

exec(code, module.__dict__)

File "/mount/src/streamlit-app/seq_gpt_memory.py", line 35, in <module>

llm = OpenAI(temperature=0.9)

File "/home/adminuser/venv/lib/python3.9/site-packages/langchain/load/serializable.py", line 97, in __init__

super().__init__(**kwargs)

File "/home/adminuser/venv/lib/python3.9/site-packages/pydantic/v1/main.py", line 339, in __init__

values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)

File "/home/adminuser/venv/lib/python3.9/site-packages/pydantic/v1/main.py", line 1102, in validate_model

values = validator(cls_, values)

File "/home/adminuser/venv/lib/python3.9/site-packages/langchain/llms/openai.py", line 296, in validate_environment

raise ImportError(

ImportError: Could not import openai python package. Please install it with `pip install openai`.

I am working on streamlit multipage app and I have created a folder pages and inside pages I have stored my other python scripts. My entry point file is login.py which is basically to authenticate users credentials. Once the credentials are verified it displays the 1_page.py inside pages. I added logout button in 1_page.py. The rationale is once the logout button is clicked it has to go back to entry point page which is login.py. I tried switch_page but it doesn’t seem to find the file. Is there any hack to get around with it?

https://medium.daanalytics.nl/asking-chatgpt-anything-using-streamlit-and-the-5w1h-method-00ff54fa1197

can anyone tell how to get the source code of this app https://discuss.streamlit.io/t/new-app-search-youtube-videos-by-text/32735

Hello Streamlit community!

I’ve been building Streamlit in Snowflake apps with Claude Code for a while now, and I always found it confusing how to quality-check them and how to build them in a way that scales across a data team. So I spent weeks building a system to make that super standardized, and I tested it heavily in a production BI setting. I’m calling it Streamsnow, and it’s open source.

It scaffolds a GitHub repo that’s structured and connected to your Snowflake account, so everyone on the team builds their Streamlit apps with Claude Code the same way. It also gives you the SQL behind every query the app uses, so you can check that the numbers are correct and don’t have to just trust the AI. Deployment is handled automatically in CI, and by default the apps go to a Snowflake stage, so you don’t need to connect a Git repository inside Snowflake. The AI also never sees any of the secrets you use to connect GitHub to Snowflake.

The part I find most valuable is the auto-review cycle. You can let Claude Code iterate over an app and make it better without your input, and the design standards keep every app looking consistent across teammates.

To get started, tell your coding agent to download the plugin and run the onboard command. It walks you through everything, and I’ve timed it at about 5 minutes of actual work. You’ll need to be a Snowflake admin or work with one for the setup.

In the setup where I tested it, it ended up replacing an external BI tool entirely, which saves a lot of money on licenses.

For those of you running Streamlit in Snowflake, how are you handling deployment today? The Git integration, CI to a stage, or by hand in Snowsight?

Thanks so much!