Alternatives
Products that do what Embed Route does
One API for embedding providers
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Hi, I'm Ben, the co-creator of Embedbase. Embedbase lets you use OpenAI Embeddings and Pinecone seamlessly. For example, you can add Embedbase to your app and pair it with GPT3 to allow people to search using natural language (e.g. How many workouts did I complete last week?), or simply expanding your current search experience beyond full-text search (e.g. looking for "similar" documents in Notion to find other related information) Managing embeddings is uncharted territory, we needed to discover the best practices ourselves. Now we're happy to share our learnings with Embedbase. Shoot if…
2023 · embedbase.xyz
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Hi HN, we built an open source model gateway. It's a single place to manage our own self hosted, frontier, and open source models in one place. It’s is rust native, built for concurrency, and implements all the config quirks across models and providers (streaming formats, tool calls, model parameters, rate limits, and different error behavior). The gateway adds under 1 ms for BYOK requests and under 2 ms when Experiential supplies the provider key. It has every major inference provider, and 1000+ models refreshed daily via a codex agent that opens a PR. Compared to other similar projects…
10d ago · github.com
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Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…
2023 · github.com
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2016 · embedbox.io
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We built any-llm because we needed a lightweight router for LLM providers with minimal overhead. Switching between models is just a string change : update "openai/gpt-4" to "anthropic/claude-3" and you're done. It uses official provider SDKs when available, which helps since providers handle their own compatibility updates. No proxy or gateway service needed either, so getting started is pretty straightforward - just pip install and import. Currently supports 20+ providers including OpenAI, Anthropic, Google, Mistral, and AWS Bedrock. Would love to hear what you think!
2025 · github.com
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We open-sourced catsu, a Python client for embedding APIs. The problem: every embedding provider has a different SDK with different bugs. OpenAI has undocumented token limits. VoyageAI's retry logic was broken until September. Cohere breaks downstream libraries every release. LiteLLM's embedding support is minimal. catsu provides: - One API for 11 providers (OpenAI, Voyage, Cohere, Jina, Mistral, Gemini, etc.) - Bundled database of 50+ models with pricing, dimensions, and benchmark scores - Built-in retry with exponential backoff - Automatic cost tracking per request - Full async support…
Dec 2025 · catsu.dev
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I built this library because langchain was too bloated and I needed a simple abstraction to call multiple LLM APIs. litellm has two functions - completion(), embedding()
2023 · github.com
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>$ ziti – version v1.0.0 Following a few years of early adopter use, OpenZiti (Apache 2.0) graduated to 1.0 a couple weeks ago. OpenZiti enables you to spin up overlay networks, and embed them in your software. Embedding via the SDKs means your overlay network extends into the process space of your application. The network goes anywhere your software goes. What’s in the box + Overlay network endpoints, including the SDKs to integrate the overlay network endpoints into your software; customized agents for OT, IoT, edge and IT; as well as browsers, reverse proxies, modems and firewalls. +…
2024 · github.com
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