mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-09 00:10:10 +01:00
1f29cec918
* Remove LangchainJS for chat support chaining Implement runtime LLM selection Implement AzureOpenAI Support for LLM + Emebedding WIP on frontend Update env to reflect the new fields * Remove LangchainJS for chat support chaining Implement runtime LLM selection Implement AzureOpenAI Support for LLM + Emebedding WIP on frontend Update env to reflect the new fields * Replace keys with LLM Selection in settings modal Enforce checks for new ENVs depending on LLM selection
100 lines
2.9 KiB
JavaScript
100 lines
2.9 KiB
JavaScript
class AzureOpenAi {
|
|
constructor() {
|
|
const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
|
|
const openai = new OpenAIClient(
|
|
process.env.AZURE_OPENAI_ENDPOINT,
|
|
new AzureKeyCredential(process.env.AZURE_OPENAI_KEY)
|
|
);
|
|
this.openai = openai;
|
|
}
|
|
|
|
isValidChatModel(_modelName = "") {
|
|
// The Azure user names their "models" as deployments and they can be any name
|
|
// so we rely on the user to put in the correct deployment as only they would
|
|
// know it.
|
|
return true;
|
|
}
|
|
|
|
async isSafe(_input = "") {
|
|
// Not implemented by Azure OpenAI so must be stubbed
|
|
return { safe: true, reasons: [] };
|
|
}
|
|
|
|
async sendChat(chatHistory = [], prompt, workspace = {}) {
|
|
const model = process.env.OPEN_MODEL_PREF;
|
|
if (!model)
|
|
throw new Error(
|
|
"No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
|
|
);
|
|
|
|
const textResponse = await this.openai
|
|
.getChatCompletions(
|
|
model,
|
|
[
|
|
{ role: "system", content: "" },
|
|
...chatHistory,
|
|
{ role: "user", content: prompt },
|
|
],
|
|
{
|
|
temperature: Number(workspace?.openAiTemp ?? 0.7),
|
|
n: 1,
|
|
}
|
|
)
|
|
.then((res) => {
|
|
if (!res.hasOwnProperty("choices"))
|
|
throw new Error("OpenAI chat: No results!");
|
|
if (res.choices.length === 0)
|
|
throw new Error("OpenAI chat: No results length!");
|
|
return res.choices[0].message.content;
|
|
})
|
|
.catch((error) => {
|
|
console.log(error);
|
|
throw new Error(
|
|
`AzureOpenAI::getChatCompletions failed with: ${error.message}`
|
|
);
|
|
});
|
|
return textResponse;
|
|
}
|
|
|
|
async getChatCompletion(messages = [], { temperature = 0.7 }) {
|
|
const model = process.env.OPEN_MODEL_PREF;
|
|
if (!model)
|
|
throw new Error(
|
|
"No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
|
|
);
|
|
|
|
const data = await this.openai.getChatCompletions(model, messages, {
|
|
temperature,
|
|
});
|
|
if (!data.hasOwnProperty("choices")) return null;
|
|
return data.choices[0].message.content;
|
|
}
|
|
|
|
async embedTextInput(textInput) {
|
|
const result = await this.embedChunks(textInput);
|
|
return result?.[0] || [];
|
|
}
|
|
|
|
async embedChunks(textChunks = []) {
|
|
const textEmbeddingModel =
|
|
process.env.EMBEDDING_MODEL_PREF || "text-embedding-ada-002";
|
|
if (!textEmbeddingModel)
|
|
throw new Error(
|
|
"No EMBEDDING_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an embedding model."
|
|
);
|
|
|
|
const { data = [] } = await this.openai.getEmbeddings(
|
|
textEmbeddingModel,
|
|
textChunks
|
|
);
|
|
return data.length > 0 &&
|
|
data.every((embd) => embd.hasOwnProperty("embedding"))
|
|
? data.map((embd) => embd.embedding)
|
|
: null;
|
|
}
|
|
}
|
|
|
|
module.exports = {
|
|
AzureOpenAi,
|
|
};
|