jorel
Version:
A unified wrapper for working with LLMs from multiple providers, including streams, images, documents & automatic tool use.
273 lines (272 loc) • 11.4 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.MistralProvider = void 0;
const mistralai_1 = require("@mistralai/mistralai");
const providers_1 = require("../../providers");
const shared_1 = require("../../shared");
const tools_1 = require("../../tools");
const convert_inputs_1 = require("./convert-inputs");
const convert_llm_message_1 = require("./convert-llm-message");
/** Provides access to OpenAI and other compatible services */
class MistralProvider {
constructor({ apiKey, retryConfig, timeout } = {}) {
this.name = MistralProvider.defaultName;
this.client = new mistralai_1.Mistral({
apiKey: apiKey ?? process.env.MISTRAL_API_KEY,
retryConfig,
timeoutMs: timeout,
});
}
async generateResponse(model, messages, config = {}) {
const start = Date.now();
const temperature = config.temperature ?? undefined;
let response;
try {
response = await this.client.chat.complete({
model,
messages: await (0, convert_llm_message_1.convertLlmMessagesToMistralMessages)(messages),
temperature,
responseFormat: (0, convert_inputs_1.jsonResponseToMistral)(config.json),
maxTokens: config.maxTokens,
toolChoice: (0, convert_inputs_1.toolChoiceToMistral)(config.toolChoice),
tools: config.tools?.asLlmFunctions?.map((f) => ({
type: "function",
function: {
name: f.function.name,
description: f.function.description,
parameters: {
type: f.function.parameters?.type ?? "object",
properties: f.function.parameters?.properties ?? {},
required: f.function.parameters?.required ?? [],
},
},
})),
}, config.abortSignal ? { fetchOptions: { signal: config.abortSignal } } : undefined);
}
catch (error) {
if (error.name === "AbortError" || (error.message && error.message.toLowerCase().includes("aborted"))) {
throw new shared_1.JorElAbortError("Request was aborted");
}
throw error;
}
const durationMs = Date.now() - start;
const inputTokens = response.usage?.promptTokens;
const outputTokens = response.usage?.completionTokens;
const message = response.choices ? (0, shared_1.firstEntry)(response.choices)?.message : undefined;
const content = Array.isArray(message?.content)
? message.content.map((c) => (c.type === "text" ? c.text : "")).join("")
: (message?.content ?? null);
const reasoningContent = Array.isArray(message?.content)
? message.content.map((c) => (c.type === "thinking" ? c.thinking : "")).join("")
: null;
const toolCalls = message?.toolCalls?.map((call) => {
return {
id: (0, shared_1.generateUniqueId)(),
request: {
id: call.id ?? (0, shared_1.generateUniqueId)(),
function: {
name: call.function.name,
arguments: typeof call.function.arguments == "string"
? tools_1.LlmToolKit.deserialize(call.function.arguments)
: call.function.arguments,
},
},
approvalState: config.tools?.getTool(call.function.name)?.requiresConfirmation
? "requiresApproval"
: "noApprovalRequired",
executionState: "pending",
result: null,
error: null,
};
});
const provider = this.name;
return {
...(0, providers_1.generateAssistantMessage)(content, reasoningContent, toolCalls),
meta: {
model,
provider,
temperature,
durationMs,
inputTokens,
outputTokens,
},
};
}
async *generateResponseStream(model, messages, config = {}) {
const start = Date.now();
const temperature = config.temperature ?? undefined;
let response;
try {
response = await this.client.chat.stream({
model,
messages: await (0, convert_llm_message_1.convertLlmMessagesToMistralMessages)(messages),
temperature,
responseFormat: (0, convert_inputs_1.jsonResponseToMistral)(config.json),
maxTokens: config.maxTokens,
stream: true,
tools: config.tools?.asLlmFunctions?.map((f) => ({
type: "function",
function: {
name: f.function.name,
description: f.function.description,
parameters: {
type: f.function.parameters?.type ?? "object",
properties: f.function.parameters?.properties ?? {},
required: f.function.parameters?.required ?? [],
},
},
})),
toolChoice: (0, convert_inputs_1.toolChoiceToMistral)(config.toolChoice),
}, config.abortSignal ? { fetchOptions: { signal: config.abortSignal } } : undefined);
}
catch (error) {
if (error.name === "AbortError" || (error.message && error.message.toLowerCase().includes("aborted"))) {
throw new shared_1.JorElAbortError("Request was aborted");
}
throw error;
}
let inputTokens;
let outputTokens;
const _toolCalls = [];
let content = "";
let reasoningContent = "";
for await (const chunk of response) {
const delta = (0, shared_1.firstEntry)(chunk.data.choices)?.delta;
if (delta?.content) {
const contentChunk = Array.isArray(delta.content)
? delta.content.map((c) => (c.type === "text" ? c.text : "")).join("")
: delta.content;
const reasoningChunk = Array.isArray(delta.content)
? delta.content.map((c) => (c.type === "thinking" ? c.thinking : "")).join("")
: null;
if (contentChunk) {
content += contentChunk;
const chunkId = (0, shared_1.generateUniqueId)();
yield {
type: "chunk",
content: contentChunk,
chunkId,
};
}
if (reasoningChunk) {
reasoningContent += reasoningChunk;
const chunkId = (0, shared_1.generateUniqueId)();
yield {
type: "reasoningChunk",
content: reasoningChunk,
chunkId,
};
}
}
if (delta?.toolCalls) {
for (const toolCall of delta.toolCalls) {
if (toolCall.index !== undefined) {
const _toolCall = _toolCalls[toolCall.index] || { id: "", function: { name: "", arguments: "" } };
if (toolCall.id)
_toolCall.id += toolCall.id;
if (toolCall.function) {
if (toolCall.function.name)
_toolCall.function.name += toolCall.function.name;
if (toolCall.function.arguments)
_toolCall.function.arguments += toolCall.function.arguments;
}
_toolCalls[toolCall.index] = _toolCall;
}
}
}
if (chunk.data.usage) {
inputTokens = chunk.data.usage?.promptTokens;
outputTokens = chunk.data.usage?.completionTokens;
}
}
const durationMs = Date.now() - start;
const provider = this.name;
const toolCalls = _toolCalls.map((call) => {
let parsedArgs = null;
let parseError = null;
try {
parsedArgs = tools_1.LlmToolKit.deserialize(call.function.arguments);
}
catch (e) {
parseError = e instanceof Error ? e : new Error("Unable to parse tool call arguments");
}
const approvalState = config.tools?.getTool(call.function.name)
?.requiresConfirmation
? "requiresApproval"
: "noApprovalRequired";
const base = {
id: (0, shared_1.generateUniqueId)(),
request: {
id: call.id,
function: {
name: call.function.name,
arguments: parsedArgs ?? {},
},
},
approvalState,
};
if (parseError) {
return {
...base,
executionState: "error",
result: null,
error: {
type: parseError.name || "ToolArgumentParseError",
message: parseError.message || "Invalid tool call arguments",
numberOfAttempts: 1,
lastAttempt: new Date(),
},
};
}
return {
...base,
executionState: "pending",
result: null,
error: null,
};
});
const meta = {
model,
provider,
temperature,
durationMs,
inputTokens,
outputTokens,
};
if (_toolCalls.length > 0) {
yield {
type: "response",
role: "assistant_with_tools",
content,
reasoningContent,
toolCalls,
meta,
};
}
else {
yield {
type: "response",
role: "assistant",
content,
reasoningContent,
meta,
};
}
}
async getAvailableModels() {
const models = await this.client.models.list();
return models.data?.map((model) => model.id) ?? [];
}
async createEmbedding(model, text, abortSignal) {
const response = await this.client.embeddings.create({
model,
inputs: text,
}, abortSignal ? { fetchOptions: { signal: abortSignal } } : undefined);
if (!response || !response.data || !response.data || response.data.length === 0 || !response.data[0].embedding) {
throw new Error("Failed to create embedding");
}
return response.data[0].embedding;
}
}
exports.MistralProvider = MistralProvider;
MistralProvider.defaultName = "mistral";