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Ollama.ts
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Ollama.ts
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import { BaseLLM } from "..";
import {
ChatMessage,
CompletionOptions,
LLMOptions,
ModelProvider,
} from "../..";
import { stripImages } from "../countTokens";
import { streamResponse } from "../stream";
class Ollama extends BaseLLM {
static providerName: ModelProvider = "ollama";
static defaultOptions: Partial<LLMOptions> = {
apiBase: "http://localhost:11434/",
model: "codellama-7b",
};
constructor(options: LLMOptions) {
super(options);
if (options.model === "AUTODETECT") {
return;
}
this.fetch(this.getEndpoint("api/show"), {
method: "POST",
headers: {},
body: JSON.stringify({ name: this._getModel() }),
})
.then(async (response) => {
if (response.status !== 200) {
console.warn(
"Error calling Ollama /api/show endpoint: ",
await response.text(),
);
return;
}
const body = await response.json();
if (body.parameters) {
const params = [];
for (let line of body.parameters.split("\n")) {
let parts = line.match(/^(\S+)\s+((?:".*")|\S+)$/);
if (parts.length < 2) {
continue;
}
let key = parts[1];
let value = parts[2];
switch (key) {
case "num_ctx":
this.contextLength = parseInt(value);
break;
case "stop":
if (!this.completionOptions.stop) {
this.completionOptions.stop = [];
}
try {
this.completionOptions.stop.push(JSON.parse(value));
} catch (e) {
console.warn(
'Error parsing stop parameter value "{value}: ${e}',
);
}
break;
default:
break;
}
}
}
})
.catch((e) => {
console.warn(`Error calling Ollama /api/show endpoint: ${e}`);
});
}
private _getModel() {
return (
{
"mistral-7b": "mistral:7b",
"mixtral-8x7b": "mixtral:8x7b",
"llama2-7b": "llama2:7b",
"llama2-13b": "llama2:13b",
"codellama-7b": "codellama:7b",
"codellama-13b": "codellama:13b",
"codellama-34b": "codellama:34b",
"codellama-70b": "codellama:70b",
"llama3-8b": "llama3:8b",
"llama3-70b": "llama3:70b",
"phi-2": "phi:2.7b",
"phind-codellama-34b": "phind-codellama:34b-v2",
"wizardcoder-7b": "wizardcoder:7b-python",
"wizardcoder-13b": "wizardcoder:13b-python",
"wizardcoder-34b": "wizardcoder:34b-python",
"zephyr-7b": "zephyr:7b",
"codeup-13b": "codeup:13b",
"deepseek-1b": "deepseek-coder:1.3b",
"deepseek-7b": "deepseek-coder:6.7b",
"deepseek-33b": "deepseek-coder:33b",
"neural-chat-7b": "neural-chat:7b-v3.3",
"starcoder-1b": "starcoder:1b",
"starcoder-3b": "starcoder:3b",
"starcoder2-3b": "starcoder2:3b",
"stable-code-3b": "stable-code:3b",
}[this.model] ?? this.model
);
}
private _convertMessage(message: ChatMessage) {
if (typeof message.content === "string") {
return message;
}
return {
role: message.role,
content: stripImages(message.content),
images: message.content
.filter((part) => part.type === "imageUrl")
.map((part) => part.imageUrl?.url.split(",").at(-1)),
};
}
private _convertArgs(
options: CompletionOptions,
prompt: string | ChatMessage[],
) {
const finalOptions: any = {
model: this._getModel(),
raw: true,
keep_alive: options.keepAlive ?? 60 * 30, // 30 minutes
options: {
temperature: options.temperature,
top_p: options.topP,
top_k: options.topK,
num_predict: options.maxTokens,
stop: options.stop,
num_ctx: this.contextLength,
mirostat: options.mirostat,
num_thread: options.numThreads,
},
};
if (typeof prompt === "string") {
finalOptions.prompt = prompt;
} else {
finalOptions.messages = prompt.map(this._convertMessage);
}
return finalOptions;
}
private getEndpoint(endpoint: string): URL {
let base = this.apiBase;
if (process.env.IS_BINARY) {
base = base?.replace("localhost", "127.0.0.1");
}
return new URL(endpoint, base);
}
protected async *_streamComplete(
prompt: string,
options: CompletionOptions,
): AsyncGenerator<string> {
const response = await this.fetch(this.getEndpoint("api/generate"), {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(this._convertArgs(options, prompt)),
});
let buffer = "";
for await (const value of streamResponse(response)) {
// Append the received chunk to the buffer
buffer += value;
// Split the buffer into individual JSON chunks
const chunks = buffer.split("\n");
buffer = chunks.pop() ?? "";
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk.trim() !== "") {
try {
const j = JSON.parse(chunk);
if ("response" in j) {
yield j["response"];
} else if ("error" in j) {
throw new Error(j["error"]);
}
} catch (e) {
throw new Error(`Error parsing Ollama response: ${e} ${chunk}`);
}
}
}
}
}
protected async *_streamChat(
messages: ChatMessage[],
options: CompletionOptions,
): AsyncGenerator<ChatMessage> {
const response = await this.fetch(this.getEndpoint("api/chat"), {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(this._convertArgs(options, messages)),
});
let buffer = "";
for await (const value of streamResponse(response)) {
// Append the received chunk to the buffer
buffer += value;
// Split the buffer into individual JSON chunks
const chunks = buffer.split("\n");
buffer = chunks.pop() ?? "";
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk.trim() !== "") {
try {
const j = JSON.parse(chunk);
if (j.message?.content) {
yield {
role: "assistant",
content: j.message.content,
};
} else if (j.error) {
throw new Error(j.error);
}
} catch (e) {
throw new Error(`Error parsing Ollama response: ${e} ${chunk}`);
}
}
}
}
}
async listModels(): Promise<string[]> {
const response = await this.fetch(
// localhost was causing fetch failed in pkg binary only for this Ollama endpoint
this.getEndpoint("api/tags"),
{
method: "GET",
},
);
const data = await response.json();
return data.models.map((model: any) => model.name);
}
}
export default Ollama;