diff --git a/.circleci/config.yml b/.circleci/config.yml index 5f4628d26..736bb8e8a 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -202,6 +202,7 @@ jobs: -e REDIS_PORT=$REDIS_PORT \ -e AZURE_FRANCE_API_KEY=$AZURE_FRANCE_API_KEY \ -e AZURE_EUROPE_API_KEY=$AZURE_EUROPE_API_KEY \ + -e MISTRAL_API_KEY=$MISTRAL_API_KEY \ -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \ -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \ -e AWS_REGION_NAME=$AWS_REGION_NAME \ diff --git a/litellm/proxy/proxy_config.yaml b/litellm/proxy/proxy_config.yaml index 3c6b2f201..a21378f31 100644 --- a/litellm/proxy/proxy_config.yaml +++ b/litellm/proxy/proxy_config.yaml @@ -14,10 +14,9 @@ model_list: litellm_params: model: openai/* api_key: os.environ/OPENAI_API_KEY - - model_name: my-triton-model + - model_name: mistral-embed litellm_params: - model: triton/any" - api_base: https://exampleopenaiendpoint-production.up.railway.app/triton/embeddings + model: mistral/mistral-embed general_settings: master_key: sk-1234 diff --git a/proxy_server_config.yaml b/proxy_server_config.yaml index f9f77c05a..f1853dc83 100644 --- a/proxy_server_config.yaml +++ b/proxy_server_config.yaml @@ -85,6 +85,9 @@ model_list: litellm_params: model: openai/* api_key: os.environ/OPENAI_API_KEY + - model_name: mistral-embed + litellm_params: + model: mistral/mistral-embed - model_name: gpt-instruct # [PROD TEST] - tests if `/health` automatically infers this to be a text completion model litellm_params: model: text-completion-openai/gpt-3.5-turbo-instruct diff --git a/tests/test_openai_endpoints.py b/tests/test_openai_endpoints.py index 83d387ffb..e2f600b76 100644 --- a/tests/test_openai_endpoints.py +++ b/tests/test_openai_endpoints.py @@ -22,6 +22,7 @@ async def generate_key( "text-embedding-ada-002", "dall-e-2", "fake-openai-endpoint-2", + "mistral-embed", ], ): url = "http://0.0.0.0:4000/key/generate" @@ -197,14 +198,14 @@ async def completion(session, key): return response -async def embeddings(session, key): +async def embeddings(session, key, model="text-embedding-ada-002"): url = "http://0.0.0.0:4000/embeddings" headers = { "Authorization": f"Bearer {key}", "Content-Type": "application/json", } data = { - "model": "text-embedding-ada-002", + "model": model, "input": ["hello world"], } @@ -408,6 +409,9 @@ async def test_embeddings(): key_2 = key_gen["key"] await embeddings(session=session, key=key_2) + # embedding request with non OpenAI model + await embeddings(session=session, key=key, model="mistral-embed") + @pytest.mark.asyncio async def test_image_generation():