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b2ea2b4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 | import { describe, expect, it } from "vitest";
import { LOCAL_APPS } from "./local-apps.js";
import type { ModelData } from "./model-data.js";
describe("local-apps", () => {
it("llama.cpp conversational", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["llama.cpp"];
const model: ModelData = {
id: "bartowski/Llama-3.2-3B-Instruct-GGUF",
tags: ["conversational"],
inference: "",
};
const snippet = snippetFunc(model);
expect(snippet[0].content).toEqual([
`# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bartowski/Llama-3.2-3B-Instruct-GGUF:{{QUANT_TAG}}`,
`# Run inference directly in the terminal:
llama-cli -hf bartowski/Llama-3.2-3B-Instruct-GGUF:{{QUANT_TAG}}`,
]);
});
it("llama.cpp non-conversational", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["llama.cpp"];
const model: ModelData = {
id: "mlabonne/gemma-2b-GGUF",
tags: [],
inference: "",
};
const snippet = snippetFunc(model);
expect(snippet[0].content).toEqual([
`# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mlabonne/gemma-2b-GGUF:{{QUANT_TAG}}`,
`# Run inference directly in the terminal:
llama-cli -hf mlabonne/gemma-2b-GGUF:{{QUANT_TAG}}`,
]);
});
it("vLLM conversational llm", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["vllm"];
const model: ModelData = {
id: "meta-llama/Llama-3.2-3B-Instruct",
pipeline_tag: "text-generation",
tags: ["conversational"],
inference: "",
};
const snippet = snippetFunc(model);
expect((snippet[0].content as string[]).join("\n")).toEqual(`# Start the vLLM server:
vllm serve "meta-llama/Llama-3.2-3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \\
-H "Content-Type: application/json" \\
--data '{
"model": "meta-llama/Llama-3.2-3B-Instruct",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'`);
});
it("vLLM non-conversational llm", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["vllm"];
const model: ModelData = {
id: "meta-llama/Llama-3.2-3B",
tags: [""],
inference: "",
};
const snippet = snippetFunc(model);
expect((snippet[0].content as string[]).join("\n")).toEqual(`# Start the vLLM server:
vllm serve "meta-llama/Llama-3.2-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \\
-H "Content-Type: application/json" \\
--data '{
"model": "meta-llama/Llama-3.2-3B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'`);
});
it("vLLM conversational vlm", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["vllm"];
const model: ModelData = {
id: "meta-llama/Llama-3.2-11B-Vision-Instruct",
pipeline_tag: "image-text-to-text",
tags: ["conversational"],
inference: "",
};
const snippet = snippetFunc(model);
expect((snippet[0].content as string[]).join("\n")).toEqual(`# Start the vLLM server:
vllm serve "meta-llama/Llama-3.2-11B-Vision-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \\
-H "Content-Type: application/json" \\
--data '{
"model": "meta-llama/Llama-3.2-11B-Vision-Instruct",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Describe this image in one sentence."
},
{
"type": "image_url",
"image_url": {
"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
}
}
]
}
]
}'`);
});
it("docker model runner", async () => {
const { snippet: snippetFunc } = LOCAL_APPS["docker-model-runner"];
const model: ModelData = {
id: "bartowski/Llama-3.2-3B-Instruct-GGUF",
tags: ["conversational"],
gguf: { total: 1, context_length: 4096 },
inference: "",
};
const snippet = snippetFunc(model);
expect(snippet).toEqual(`docker model run hf.co/bartowski/Llama-3.2-3B-Instruct-GGUF:{{QUANT_TAG}}`);
});
});
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