> For the complete documentation index, see [llms.txt](https://docs.aimlapi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aimlapi.com/integrations/ragflow.md).
# RAGFlow
Add AI/ML API as a model provider in RAGFlow and use it for chat, embeddings, and vision across your knowledge bases and agents.
## About
[RAGFlow](https://github.com/infiniflow/ragflow) is an open-source Retrieval-Augmented Generation (RAG) engine that pairs deep document understanding with agent capabilities. You upload documents into knowledge bases, and RAGFlow chunks, embeds, retrieves, and answers over them.
AI/ML API is a **built-in model provider** in RAGFlow. It shipped upstream in [PR #17311](https://github.com/infiniflow/ragflow/pull/17311) (merged July 24, 2026) and is available to users from release **v0.27.0** onward — add it in **Model providers** with one key and use AI/ML API models across chat, embedding, and image-to-text tasks.
## Quick start
{% stepper %}
{% step %}
## Run RAGFlow v0.27.0 or newer
Earlier releases do not include the provider. Check your version in the RAGFlow UI or pull a current image.
{% endstep %}
{% step %}
## Open Model providers
Click your avatar in the top-right corner, then open **Model providers**.
{% endstep %}
{% step %}
## Add aimlapi.com
Find **aimlapi.com** under the providers to be added and click **Add the LLM**.
{% endstep %}
{% step %}
## Fill in the model and key
Choose the model type, pick a model, paste your AI/ML API key, and save.
{% endstep %}
{% step %}
## Set your system defaults
In **Set default models**, select the AI/ML API models RAGFlow should use for chat, embedding, and image-to-text.
{% endstep %}
{% endstepper %}
## When to use AI/ML API with RAGFlow
AI/ML API works well with RAGFlow when you want:
* one key covering the chat, embedding, and vision models a RAG pipeline needs
* to change the answering model without re-embedding your knowledge bases
* to compare models from different vendors inside the same RAGFlow instance
## Prerequisites
Before you start, make sure you have:
* RAGFlow **v0.27.0** or newer (see [github.com/infiniflow/ragflow](https://github.com/infiniflow/ragflow))
* an AI/ML API key from [aimlapi.com/app/keys](https://aimlapi.com/app/keys)
* a model ID from [aimlapi.com/models](https://aimlapi.com/models)
The base URL is:
```
https://api.aimlapi.com/v1
```
Need a key first? Use [API Key Management](broken://pages/cdd447f8b558d5268491de41a1a02c07771cac9b).
## Supported model types
The provider registers three model types in RAGFlow:
| RAGFlow model type | Used for |
| ------------------ | --------------------------------------- |
| Chat | answering, agents, and assistants |
| Embedding | indexing documents into knowledge bases |
| Img2txt | reading images and scanned pages |
Video, audio, and image-generation models are not exposed through this provider.
## Model selection
The provider ships a short preset list, and you can add any other AI/ML API model by its exact ID.
### Good starting models
* `openai/gpt-4o` — chat and image-to-text
* `anthropic/claude-opus-4-8` — long-context answering
* `google/gemini-2.5-flash` — lower latency and lower cost
* `openai/text-embedding-3-small` — embeddings
For the full catalog, use [All Model IDs](broken://pages/9db43b2a9ecf64fedb7fcfc447a3ace848669984).
## Config checklist
Make sure these values are set:
* provider: **aimlapi.com** in **Model providers**
* API key: your AI/ML API key
* base URL: `https://api.aimlapi.com/v1` (built in; override with `AIMLAPI_API_URL` if you run through a proxy)
* default models: set under **Set default models**
## Troubleshooting
aimlapi.com is not in the provider list
The provider ships from RAGFlow **v0.27.0**. Upgrade your deployment — on v0.26.x and earlier the entry does not exist.
A model I want is not in the dropdown
The preset list is short by design. Add the model by its exact AI/ML API ID instead — the provider accepts any OpenAI-compatible chat or embedding model ID from the catalog.
I get an auth error
Check that:
* the key is valid at [aimlapi.com/app/keys](https://aimlapi.com/app/keys)
* your balance is sufficient at [aimlapi.com/app](https://aimlapi.com/app)
* the model ID matches the catalog exactly, including the vendor prefix
Retrieval quality dropped after switching the embedding model
Changing the embedding model changes the vector space. Re-parse the affected knowledge bases so the documents are re-embedded with the new model.
## Links
* [All Model IDs](broken://pages/9db43b2a9ecf64fedb7fcfc447a3ace848669984)
* [AI/ML API keys](https://aimlapi.com/app/keys)
* [AI/ML API model catalog](https://aimlapi.com/models)
* [RAGFlow repository](https://github.com/infiniflow/ragflow)
* [RAGFlow documentation](https://ragflow.io/docs)
---
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