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CodeCompanion.AI
CodeMap4AI helps AI understand your entire codebase by generating a structured map of your project. It minimizes hallucinations, improves code suggestions, and boosts productivityโespecially when using ChatGPT, Claude, or other AI assistants outside your IDE.
GitHub CodeMap4AICodeMap4AI's answer:
CodeMap4AI creates a lightweight, structured JSON map of your entire project that can be instantly understood by AI assistants like ChatGPT. Unlike most AI tooling, it works independently of your IDE, and itโs purpose-built to reduce AI hallucinations and improve the accuracy of code-related prompts.
CodeMap4AI's answer:
Because it provides clean, AI-ready context without requiring IDE integration or sending code to external servers. Itโs fast, private, and works well in any setup โ from local terminals to AI chat interfaces. Itโs also helpful for humans, offering a high-level view of any codebase in seconds.
CodeMap4AI's answer:
Developers who use AI tools (like ChatGPT, Claude, or Copilot) to write, refactor, or understand code โ especially those working on large, unfamiliar, or legacy projects. Also ideal for freelancers, indie developers, and teams onboarding new engineers.
CodeMap4AI's answer:
CodeMap4AI started as a personal tool to stop ChatGPT from hallucinating when working on real-world PHP/JS projects. The creator realized that by giving the AI a clear map of all files, classes, and DB logic, its answers became dramatically better โ so the tool was refined and released for public use.
CodeMap4AI's answer:
CodeMap4AI's answer:
As of now, CodeMap4AI is growing and used mostly by indie developers, freelancers, and small teams. Named enterprise customers are not publicly listed, but early adopters include: - Freelance web developers - AI engineers building full-stack apps - PHP legacy code maintainers - Small software agencies
Based on our record, GitHub seems to be more popular. It has been mentiond 2476 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.
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 3 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 4 days ago
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 / 9 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 / 16 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 / 16 days ago
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Continue.dev - Continue is the leading open-source AI code assistant. You can connect any models and any context to build custom autocomplete and chat experiences inside VS Code and JetBrains.
