How to use langchain and openai API with multiple models
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Description
I want to use EMBEDDING of 2 different models separately using OpenAIEmbedding, how do I change my command
python -m fastchat.serve.controller
python -m fastchat.serve.multi_model_worker --model-names "gpt-3.5-turbo,text-davinci-003,text-embedding-ada-002" --model-path llama\llama2-7b --load-8bit --model-names "gpt-3.5-turbo-instruct,text-davinci-003,text-embedding-ada-002" --model-path llama\Llama-2-7b-chat-hf --load-8bit
python -m fastchat.serve.openai_api_server --host localhost --port 8000
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the command entry points mentioned in the issue: fastchat.serve.multi_model_worker and fastchat.serve.openai_api_server. Determine whether separate embedding models can be configured in the shown multi-model setup; done would be a documented, working command or a clear statement of the supported limitation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100