add rerank model success for LocalAI, but no show in system

[edisonzf2020]

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Dify version

0.6.8

Cloud or Self Hosted

Self Hosted (Docker)

Steps to reproduce

1. add rerank model mxbai-rerank-large-v1 success.
2. can not display in system .

✔️ Expected Behavior

No response

❌ Actual Behavior

No response

[dosubot]

To address the issue with the "mxbai-rerank-large-v1" model not showing up in the Dify system after adding it to your self-hosted LocalAI, please ensure the following steps have been correctly executed:

1. Model and Configuration: Confirm that the model is saved in the models directory and a correct YAML configuration file is created for it within the same directory.
2. Restart LocalAI: Make sure LocalAI has been restarted to load the new model configuration.
3. Dify Integration: In Dify, navigate to Settings > Model Providers > LocalAI and add the new model with its details to ensure it's integrated properly.

Check for these potential issues:

• Model Compatibility: The model should be compatible with the ggml format and supported by Dify.
• Network Configuration: Verify that the Dify container can access the LocalAI endpoint. Use the host IP address or a LAN IP address instead of localhost.

If the model still doesn't appear, review the integration process in Dify, especially the updateModelList function, to ensure the model list is refreshed correctly. Also, look out for any error messages during the process, as they can provide specific clues to the problem.

For a detailed guide on adding models to LocalAI and troubleshooting, refer to the LocalAI model configuration documentation.

If after these checks the issue persists, please share more details about the steps you've taken and any error messages encountered for further assistance.

Details

Sources

• en/tutorials/model-configuration/localai.md
• api/core/model_runtime/model_providers/localai/localai.yaml
• web/app/components/header/account-setting/model-provider-page/system-model-selector/index.tsx
• api/core/model_runtime/model_providers/localai/rerank/rerank.py
• en/getting-started/readme/specifications-and-technical-features.md
• api/tests/integration_tests/model_runtime/localai/test_rerank.py
• zh_CN/learn-more/extended-reading/retrieval-augment/rerank.md

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[gakugaku]

After configuring LocalAI ReRank, running SELECT * FROM provider_models on the Dify DB returns the following result, indicating that it is configured correctly.

... | ...  | localai       | <<model_name>> | reranking       | {"server_url": "http://xxx.xxx.xxx.xxx/v1"} | t        | 2024-05-17 17:10:23 | 2024-05-23 07:26:34.66699

However, it does not show up in the model provider settings and cannot be used as a model.

It seems like the API endpoint console/api/workspaces/current/models/model-types/rerank is not functioning with the registered LocalAI Reranker.

Request: http://xxx/console/api/workspaces/current/models/model-types/rerank
Response:

{data: [{provider: "nvidia", label: {zh_Hans: "API Catalog", en_US: "API Catalog"},…},…]}
0: {provider: "nvidia", label: {zh_Hans: "API Catalog", en_US: "API Catalog"},…}
1: {provider: "cohere", label: {zh_Hans: "Cohere", en_US: "Cohere"},…}
2: {provider: "jina", label: {zh_Hans: "Jina", en_US: "Jina"},…}

Environment:

• Dify version: 0.6.8
• LocalAI version: 2.15.0

[Sarmingsteiner]

@edisonzf2020 : Could you please point me out how you managed to install the reranking model mxbai-rerank-large-v1 in LocalAI?

@gakugaku : Which reranking model did you install in LocalAI and how did you manage it? Thank you in advance.

[gakugaku]

@Sarmingsteiner
This issue has been resolved in #4652, and it should work correctly in the latest version.

Here is how I managed to install a reranking model in LocalAI. Example for Docker and Japanese Reranker model.

LocalAI Configuration

compose.yaml

services:
  local-ai:
    image: localai/localai:v2.16.0
    environment:
      MODELS_PATH: /models
    volumes:
      - ./data/LocalAI/models:/models:cached

./data/LocalAI/models/reranker.yaml
You can find more details in the 📈 Reranker | LocalAI documentation.

name: japanese-reranker
backend: rerankers
parameters:
  model: hotchpotch/japanese-reranker-cross-encoder-small-v1

When you start and run this configuration, the model will be downloaded automatically.

Dify Configuration

Select the LocalAI provider and configure it as follows:

• Model Type: Rerank
• Model Name: In the example above, it would be japanese-reranker
• Server URL: http://<your-server>/v1 (make sure to include /v1)