codesnippets.ai
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The Code Snippets AI desktop app is an enhanced chat interface for the most popular Open and Closed-Source LLMs.
Enabling developers to chat with the latest AI models Including OpenAI GPT-4, Mixtral 8x7B, Capybara 7B.
Use the FREE Desktop app with any IDE, simply index the folder where your project is located, and Code Snippets AI will index your project for the AI's context.
Code Snippets AI listens to changes in your codebase, feeding the latest changes to your chat context.
It can help generate and refactor code, improve readability, and detect and correct errors. It also provides secure and private storage for code snippets, allowing developers to collaborate with their team members.
Code Snippets AI also provides an IDE extension, making it faster and easier to write code that just works.
In addition, it offers code analysis, error detection and correction, and code explanation features to help developers understand the structure and relationships within code, making it easier to maintain.
Code Snippets AI offers a free plan for individual users, and paid plans for teams with additional features and tokens.
These tokens can be used for AI code generation, code review, refactoring and debugging.
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codesnippets.ai's answer
The Code Snippets AI desktop app is an enhanced chat interface for the most popular Open and Closed-Source LLMs. Enabling developers to chat with the latest AI models Including OpenAI GPT-4, Claude2, Mixtral 8x7B, Capybara 7B.
Multiple Open-Source and Closed-Source models can be used in same chat, in our desktop app. So long as the model you are switching to has a sufficient token context window to support the current chat length.
Contextual awareness is achieved through local codebase indexing and vectorization with computed embeddings from OpenAI.
codesnippets.ai's answer
All written-input interactions with AI models are monitored for safety as per OpenAI guidelines.
We never use, view, or have access to records of your code input/output.
We NEVER share or use your code to further train any AI Models.
ALL code that you send in requests to the AI models we offer, and store within your Code Snippets Library, is only visible to you.
codesnippets.ai's answer
NextJS, Chrome Extension, Mac app, Windows App
codesnippets.ai's answer
Microsoft, HeyCater, Rhombico Games, Orange
Based on our record, GitHub seems to be more popular. It has been mentiond 2474 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 2 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 9 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 10 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 10 days ago
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 20 days ago
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