OpenAI .NET πΎ
The OpenAI .NET library provides convenient access to the OpenAI REST API from .NET applications.βοΈ
The full API of this library can be found in the api.md file, and there are many code examples to help. For instance, the following snippet illustrates the basic use of the chat completions API:
The library is organized into several namespaces corresponding to OpenAI feature areas. Each namespace contains a corresponding client class:
β’ AssistantClient
β’ AudioClient
β’ BatchClient
β’ ChatClient
β’ EmbeddingClient
β’ FineTuningClient
β’ FileClient
β’ ImageClient
β’ ModelClient
β’ ModerationClient
β’ VectorStoreClient
[ GitHub ] : https://github.com/openai/openai-dotnet
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#AI #OpenAI #DotNet #CSharp
@ProgrammingTip
The OpenAI .NET library provides convenient access to the OpenAI REST API from .NET applications.
The full API of this library can be found in the api.md file, and there are many code examples to help. For instance, the following snippet illustrates the basic use of the chat completions API:
ChatClient client = new(model: "gpt-4o", "OPENAI_API_KEY");
ChatCompletion completion = client.CompleteChat("Say 'this is a test.'");
Console.WriteLine($"[ASSISTANT]: {completion}");
The library is organized into several namespaces corresponding to OpenAI feature areas. Each namespace contains a corresponding client class:
β’ AssistantClient
β’ AudioClient
β’ BatchClient
β’ ChatClient
β’ EmbeddingClient
β’ FineTuningClient
β’ FileClient
β’ ImageClient
β’ ModelClient
β’ ModerationClient
β’ VectorStoreClient
[ GitHub ] : https://github.com/openai/openai-dotnet
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#AI #OpenAI #DotNet #CSharp
@ProgrammingTip
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π OpenAI just dropped Sora 2 β and itβs insane.
Every frame of the video youβll see is fully generated by AI. No cameras, no actors, no sets. Just prompts β video!
[ Blog ] : https://openai.com/index/sora-2
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#AI #OpenAI #Sora
@ProgrammingTip
Every frame of the video youβll see is fully generated by AI. No cameras, no actors, no sets. Just prompts β video!
[ Blog ] : https://openai.com/index/sora-2
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#AI #OpenAI #Sora
@ProgrammingTip
GPT-6 Astra is OpenAI's new work model π
OpenAI shipped GPT-6 Astra. They are calling it the next generation in intelligence for work.
Not a research teaser. A work model. Expect the name in agent stacks and coding tools.
Why you care:
β New flagship name to put on your eval harness
β Pitched for workplace tasks, not playground chat
β If you pin model ids in config, read this before you swap anything
Start with the official writeup. Then decide if your coding agents still belong on last week's snapshot. I would not change production on a blog title alone. Run your own traces.
[ Read More ] :
https://openai.com/index/gpt-6-astra-next-generation-work
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#AI #LLM #OpenAI
@ProgrammingTip
OpenAI shipped GPT-6 Astra. They are calling it the next generation in intelligence for work.
Not a research teaser. A work model. Expect the name in agent stacks and coding tools.
Why you care:
β New flagship name to put on your eval harness
β Pitched for workplace tasks, not playground chat
β If you pin model ids in config, read this before you swap anything
Start with the official writeup. Then decide if your coding agents still belong on last week's snapshot. I would not change production on a blog title alone. Run your own traces.
[ Read More ] :
https://openai.com/index/gpt-6-astra-next-generation-work
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#AI #LLM #OpenAI
@ProgrammingTip
OpenAI
GPT-6 Astra: The next generation in intelligence for work
Meet GPT-6 Astra, OpenAIβs most capable model for business, with advanced reasoning, computer use, and stronger writing and design judgment.
GPT-6 Sol and GPT-6 Luna are in the API π
OpenAI shipped GPT-6 Sol and GPT-6 Luna for API developers, alongside their availability in Codex and ChatGPT.
This is a two-model release, so do not blindly swap your existing production model. Put both behind the same eval set first: tool calls, structured output, long-context retrieval, refusal behavior, and latency under your real prompt size.
What to do this week:
β’ Add Sol and Luna as versioned model options in your config.
β’ Run replay traffic against a fixed golden set.
β’ Log model ID, token use, tool errors, and task success separately.
A model migration is an engineering change, not a dropdown change.
[ Read More ] :
https://openai.com/index/introducing-gpt-6-sol-and-luna/
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#AI #OpenAI #LLM #API
@ProgrammingTip
OpenAI shipped GPT-6 Sol and GPT-6 Luna for API developers, alongside their availability in Codex and ChatGPT.
This is a two-model release, so do not blindly swap your existing production model. Put both behind the same eval set first: tool calls, structured output, long-context retrieval, refusal behavior, and latency under your real prompt size.
What to do this week:
β’ Add Sol and Luna as versioned model options in your config.
β’ Run replay traffic against a fixed golden set.
β’ Log model ID, token use, tool errors, and task success separately.
A model migration is an engineering change, not a dropdown change.
[ Read More ] :
https://openai.com/index/introducing-gpt-6-sol-and-luna/
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#AI #OpenAI #LLM #API
@ProgrammingTip
OpenAI
Introducing GPT-6 Sol and Luna
Meet GPT-6 Sol and Luna, two models that bring frontier intelligence to everyday work with different balances of capability and cost.
OpenAI introduced Dots, always-on agents π
OpenAI introduced Dots, its take on always-on agents.
This is not a one-prompt, one-answer workflow. The pitch is an agent that can stay active around work instead of waiting for you to reopen a chat and restate the task.
Why this matters:
β’ Long-running work: agents need durable context, not a pile of copied prompts.
β’ Real handoff points: a useful agent should surface decisions and results, not silently keep doing things.
β’ Agent ops: permissions, logs, cancellation, and cost limits become product features.
If you build agent workflows, the hard part is no longer getting a model to call a tool. It is making an autonomous process observable enough that somebody will trust it.
[ Read More ] :
https://openai.com/index/introducing-dots/
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#AI #Agents #OpenAI
@ProgrammingTip
OpenAI introduced Dots, its take on always-on agents.
This is not a one-prompt, one-answer workflow. The pitch is an agent that can stay active around work instead of waiting for you to reopen a chat and restate the task.
Why this matters:
β’ Long-running work: agents need durable context, not a pile of copied prompts.
β’ Real handoff points: a useful agent should surface decisions and results, not silently keep doing things.
β’ Agent ops: permissions, logs, cancellation, and cost limits become product features.
If you build agent workflows, the hard part is no longer getting a model to call a tool. It is making an autonomous process observable enough that somebody will trust it.
[ Read More ] :
https://openai.com/index/introducing-dots/
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#AI #Agents #OpenAI
@ProgrammingTip
OpenAI
Introducing dots
Dots by OpenAI are proactive assistants that can keep working across complex projects and everyday tasks. Learn how dots help you stay in control while work moves forward.
GPT-6 Astra gets an Ultrafast API tier π
OpenAI added an Ultrafast speed tier for GPT-6 Astra in Codex and the API.
The important bit is real-time work. Astra can now run Responses API workflows over WebSockets, which is a much better fit for interactive coding assistants, live agent status, and UI flows where waiting on a full request feels bad.
What to check:
β’ Responses API: use it for the agent loop and tool calls.
β’ WebSockets: keep one live connection instead of polling.
β’ Ultrafast tier: test it where latency matters more than squeezing every last token of quality.
If your app streams agent work to a browser, this is worth benchmarking against your current model setup.
[ Article ] :
https://community.openai.com/t/build-ultrafast-with-astra-in-codex-and-the-api/1402393
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#AI #OpenAI #API #LLM
@ProgrammingTip
OpenAI added an Ultrafast speed tier for GPT-6 Astra in Codex and the API.
The important bit is real-time work. Astra can now run Responses API workflows over WebSockets, which is a much better fit for interactive coding assistants, live agent status, and UI flows where waiting on a full request feels bad.
What to check:
β’ Responses API: use it for the agent loop and tool calls.
β’ WebSockets: keep one live connection instead of polling.
β’ Ultrafast tier: test it where latency matters more than squeezing every last token of quality.
If your app streams agent work to a browser, this is worth benchmarking against your current model setup.
[ Article ] :
https://community.openai.com/t/build-ultrafast-with-astra-in-codex-and-the-api/1402393
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#AI #OpenAI #API #LLM
@ProgrammingTip
OpenAI Developer Community
Build Ultrafast with Astra in Codex and the API
Our premium speed tier, Ultrafast offers up to 8x faster token generation (300 tokens per second) in Codex and up to 6x in the API. In Codex, Ultrafast generates code faster, so you can move more quickly from idea to code to iteration π β¦
OpenAI Decisions API is in public beta π
OpenAI's Decisions API is now in public beta. It uses GPT-6 Luna to turn text or image input into structured decision results instead of another blob of prose.
What it returns:
β’ Predicates: true or false checks for policy, routing, or eligibility.
β’ Choices: select one option from a defined set.
β’ Scores: rank or grade an input on a scale you control.
This is useful when an LLM sits inside a real workflow. Send the result to an approval queue, a feature flag, or a C# switch expression. Keep the model's job narrow, validate the typed output, and do not make your app parse "I think yes".
[ Read More ] :
https://developers.openai.com/api/docs/guides/decisions
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#AI #OpenAI #LLM #API
@ProgrammingTip
OpenAI's Decisions API is now in public beta. It uses GPT-6 Luna to turn text or image input into structured decision results instead of another blob of prose.
What it returns:
β’ Predicates: true or false checks for policy, routing, or eligibility.
β’ Choices: select one option from a defined set.
β’ Scores: rank or grade an input on a scale you control.
This is useful when an LLM sits inside a real workflow. Send the result to an approval queue, a feature flag, or a C# switch expression. Keep the model's job narrow, validate the typed output, and do not make your app parse "I think yes".
[ Read More ] :
https://developers.openai.com/api/docs/guides/decisions
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#AI #OpenAI #LLM #API
@ProgrammingTip
OpenAI Developers
Decisions | OpenAI API
Use the Decisions API to check conditions, select from fixed options, and score text, images, and JSON against a rubric.
GPT-6 and Intelligent UI are rolling out π
OpenAI announced GPT-6 for everyone, alongside its new Intelligent UI direction.
This is worth watching even if you only ship API-backed apps. Model upgrades change what users expect from a product UI: fewer settings screens, more intent-driven actions, and interfaces that can adapt while the user works.
For developers:
β’ Keep your product actions explicit and observable.
β’ Make AI suggestions reversible, not magic state changes.
β’ Do not hide latency behind a clever UI. Show progress and let users interrupt.
The model is one part. The interaction contract around it is where apps get hard.
[ Read More ] :
https://openai.com/index/gpt-6-for-everyone/
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#AI #OpenAI #GPT6
@ProgrammingTip
OpenAI announced GPT-6 for everyone, alongside its new Intelligent UI direction.
This is worth watching even if you only ship API-backed apps. Model upgrades change what users expect from a product UI: fewer settings screens, more intent-driven actions, and interfaces that can adapt while the user works.
For developers:
β’ Keep your product actions explicit and observable.
β’ Make AI suggestions reversible, not magic state changes.
β’ Do not hide latency behind a clever UI. Show progress and let users interrupt.
The model is one part. The interaction contract around it is where apps get hard.
[ Read More ] :
https://openai.com/index/gpt-6-for-everyone/
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#AI #OpenAI #GPT6
@ProgrammingTip
OpenAI
GPT-6 and Intelligent UI for everyone
GPTβ6 is rolling out globally in ChatGPT with Intelligent UI, delivering faster responses with visuals and interactive experiences you can explore and use directly.
OpenAI shipped the Decisions API π
OpenAI's Decisions API is built for apps that need to react while work is still moving, not wait around for one giant model response.
The practical shift is architectural: treat a model run as a stream of decisions your app can act on. UI updates, tool work, and state changes can happen as the task progresses.
Why this matters:
β’ Faster-feeling apps: show useful progress instead of a spinner.
β’ Cleaner agent loops: connect decisions to tools and app state.
β’ Less fake streaming: do not make users wait for a fully composed answer before the app can respond.
If your agent UX still feels like request, long pause, giant blob, this API is worth a look.
[ Read More ] :
https://openai.com/index/decisions-api
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#AI #OpenAI #Agents #API
@ProgrammingTip
OpenAI's Decisions API is built for apps that need to react while work is still moving, not wait around for one giant model response.
The practical shift is architectural: treat a model run as a stream of decisions your app can act on. UI updates, tool work, and state changes can happen as the task progresses.
Why this matters:
β’ Faster-feeling apps: show useful progress instead of a spinner.
β’ Cleaner agent loops: connect decisions to tools and app state.
β’ Less fake streaming: do not make users wait for a fully composed answer before the app can respond.
If your agent UX still feels like request, long pause, giant blob, this API is worth a look.
[ Read More ] :
https://openai.com/index/decisions-api
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#AI #OpenAI #Agents #API
@ProgrammingTip
OpenAI
Build more responsive apps with the Decisions API
Fast, focused, low-cost decisions for any application.
How OpenAI stores data for 1B ChatGPT users π
OpenAI published part two of the storage work behind ChatGPT, Codex, and API workloads at billion-user scale.
Habitat is the storage platform in the middle. It uses Azure Cosmos DB multi-tenancy, caching, and data placement so workloads can scale without every product team rebuilding its own persistence layer.
What matters:
β’ Multi-tenancy: isolate customer and workload data without multiplying operational overhead.
β’ Cache-aware reads: keep hot data off the expensive path.
β’ Placement controls: put data near the workload that needs it.
This is the less glamorous half of AI infrastructure. Models get the headlines. Storage latency, tenancy boundaries, and cache hit rates decide whether the product survives traffic.
[ Read More ] :
https://openai.com/index/scaling-storage-one-billion-users-part-two/
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#AI #OpenAI #Azure #Storage
@ProgrammingTip
OpenAI published part two of the storage work behind ChatGPT, Codex, and API workloads at billion-user scale.
Habitat is the storage platform in the middle. It uses Azure Cosmos DB multi-tenancy, caching, and data placement so workloads can scale without every product team rebuilding its own persistence layer.
What matters:
β’ Multi-tenancy: isolate customer and workload data without multiplying operational overhead.
β’ Cache-aware reads: keep hot data off the expensive path.
β’ Placement controls: put data near the workload that needs it.
This is the less glamorous half of AI infrastructure. Models get the headlines. Storage latency, tenancy boundaries, and cache hit rates decide whether the product survives traffic.
[ Read More ] :
https://openai.com/index/scaling-storage-one-billion-users-part-two/
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#AI #OpenAI #Azure #Storage
@ProgrammingTip
OpenAI
Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)
Learn how OpenAI scaled Habitat with reliable multi-tenancy, global caching, and Azure Cosmos DB to deliver 12Γ faster reads for ChatGPT.
GPT-6.1 Terra is in the OpenAI API π
OpenAI introduced GPT-6.1 Terra for developers who need computer use without paying for a slower, heavier model on every task.
Call it as
What to test first:
β’ Long UI runs: can it recover after a modal, redirect, or failed click?
β’ Tool boundaries: keep payments, deletes, and production writes behind explicit approval.
β’ Cost per completed task: token price is not the whole bill when retries are involved.
Computer use is getting cheaper. Your eval suite now matters more than a demo.
[ Read More ] :
https://openai.com/index/introducing-gpt-6-1-terra/
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#AI #OpenAI #API #Agents
@ProgrammingTip
OpenAI introduced GPT-6.1 Terra for developers who need computer use without paying for a slower, heavier model on every task.
Call it as
gpt-6.1-terra. The pitch is fast UI interaction, capable multi-step work, and lower standard pricing. That makes it a practical model to test for browser agents, QA flows, back-office automation, and anything that has to click through a real app.What to test first:
β’ Long UI runs: can it recover after a modal, redirect, or failed click?
β’ Tool boundaries: keep payments, deletes, and production writes behind explicit approval.
β’ Cost per completed task: token price is not the whole bill when retries are involved.
Computer use is getting cheaper. Your eval suite now matters more than a demo.
[ Read More ] :
https://openai.com/index/introducing-gpt-6-1-terra/
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#AI #OpenAI #API #Agents
@ProgrammingTip
OpenAI
Introducing GPT-6.1 Terra
Delivering fast and capable computer use at scale