LibreChat/api/server/services/Endpoints/agents/initialize.js
Danny Avila ad74350036
🚧 chore: merge latest dev build (#4288)
* fix: agent initialization, add `collectedUsage` handling

* style: improve side panel styling

* refactor(loadAgent): Optimize order agent project ID retrieval

* feat: code execution

* fix: typing issues

* feat: ExecuteCode content part

* refactor: use local state for default collapsed state of analysis content parts

* fix: code parsing in ExecuteCode component

* chore: bump agents package, export loadAuthValues

* refactor: Update handleTools.js to use EnvVar for code execution tool authentication

* WIP

* feat: download code outputs

* fix(useEventHandlers): type issues

* feat: backend handling for code outputs

* Refactor: Remove console.log statement in Part.tsx

* refactor: add attachments to TMessage/messageSchema

* WIP: prelim handling for code outputs

* feat: attachments rendering

* refactor: improve attachments rendering

* fix: attachments, nullish edge case, handle attachments from event stream, bump agents package

* fix filename download

* fix: tool assignment for 'run code' on agent creation

* fix: image handling by adding attachments

* refactor: prevent agent creation without provider/model

* refactor: remove unnecessary space in agent creation success message

* refactor: select first model if selecting provider from empty on form

* fix: Agent avatar bug

* fix: `defaultAgentFormValues` causing boolean typing issue and typeerror

* fix: capabilities counting as tools, causing duplication of them

* fix: formatted messages edge case where consecutive content text type parts with the latter having tool_call_ids would cause consecutive AI messages to be created. furthermore, content could not be an array for tool_use messages (anthropic limitation)

* chore: bump @librechat/agents dependency to version 1.6.9

* feat: bedrock agents

* feat: new Agents icon

* feat: agent titling

* feat: agent landing

* refactor: allow sharing agent globally only if user is admin or author

* feat: initial AgentPanelSkeleton

* feat: AgentPanelSkeleton

* feat: collaborative agents

* chore: add potential authorName as part of schema

* chore: Remove unnecessary console.log statement

* WIP: agent model parameters

* chore: ToolsDialog typing and tool related localization chnages

* refactor: update tool instance type (latest langchain class), and rename google tool to 'google' proper

* chore: add back tools

* feat: Agent knowledge files upload

* refactor: better verbiage for disabled knowledge

* chore: debug logs for file deletions

* chore: debug logs for file deletions

* feat: upload/delete agent knowledge/file-search files

* feat: file search UI for agents

* feat: first pass, file search tool

* chore: update default agent capabilities and info
2024-09-30 17:17:57 -04:00

138 lines
4.1 KiB
JavaScript

// const {
// ErrorTypes,
// EModelEndpoint,
// resolveHeaders,
// mapModelToAzureConfig,
// } = require('librechat-data-provider');
// const { getUserKeyValues, checkUserKeyExpiry } = require('~/server/services/UserService');
// const { isEnabled, isUserProvided } = require('~/server/utils');
// const { getAzureCredentials } = require('~/utils');
// const { OpenAIClient } = require('~/app');
const { z } = require('zod');
const { tool } = require('@langchain/core/tools');
const { createContentAggregator } = require('@librechat/agents');
const {
EModelEndpoint,
getResponseSender,
providerEndpointMap,
} = require('librechat-data-provider');
const {
getDefaultHandlers,
createToolEndCallback,
} = require('~/server/controllers/agents/callbacks');
const initAnthropic = require('~/server/services/Endpoints/anthropic/initializeClient');
const initOpenAI = require('~/server/services/Endpoints/openAI/initializeClient');
const getBedrockOptions = require('~/server/services/Endpoints/bedrock/options');
const { loadAgentTools } = require('~/server/services/ToolService');
const AgentClient = require('~/server/controllers/agents/client');
const { getModelMaxTokens } = require('~/utils');
/* For testing errors */
const _getWeather = tool(
async ({ location }) => {
if (location === 'SAN FRANCISCO') {
return 'It\'s 60 degrees and foggy';
} else if (location.toLowerCase() === 'san francisco') {
throw new Error('Input queries must be all capitals');
} else {
throw new Error('Invalid input.');
}
},
{
name: 'get_weather',
description: 'Call to get the current weather',
schema: z.object({
location: z.string(),
}),
},
);
const providerConfigMap = {
[EModelEndpoint.openAI]: initOpenAI,
[EModelEndpoint.azureOpenAI]: initOpenAI,
[EModelEndpoint.anthropic]: initAnthropic,
[EModelEndpoint.bedrock]: getBedrockOptions,
};
const initializeClient = async ({ req, res, endpointOption }) => {
if (!endpointOption) {
throw new Error('Endpoint option not provided');
}
// TODO: use endpointOption to determine options/modelOptions
/** @type {Array<UsageMetadata>} */
const collectedUsage = [];
/** @type {ArtifactPromises} */
const artifactPromises = [];
const { contentParts, aggregateContent } = createContentAggregator();
const toolEndCallback = createToolEndCallback({ req, res, artifactPromises });
const eventHandlers = getDefaultHandlers({
res,
aggregateContent,
toolEndCallback,
collectedUsage,
});
if (!endpointOption.agent) {
throw new Error('No agent promise provided');
}
/** @type {Agent | null} */
const agent = await endpointOption.agent;
if (!agent) {
throw new Error('Agent not found');
}
const { tools, toolMap } = await loadAgentTools({
req,
tools: agent.tools,
agent_id: agent.id,
tool_resources: agent.tool_resources,
// openAIApiKey: process.env.OPENAI_API_KEY,
});
let modelOptions = { model: agent.model };
const getOptions = providerConfigMap[agent.provider];
if (!getOptions) {
throw new Error(`Provider ${agent.provider} not supported`);
}
// TODO: pass-in override settings that are specific to current run
endpointOption.model_parameters.model = agent.model;
const options = await getOptions({
req,
res,
endpointOption,
optionsOnly: true,
overrideEndpoint: agent.provider,
overrideModel: agent.model,
});
modelOptions = Object.assign(modelOptions, options.llmConfig);
const sender = getResponseSender({
...endpointOption,
model: endpointOption.model_parameters.model,
});
const client = new AgentClient({
req,
agent,
tools,
sender,
toolMap,
contentParts,
modelOptions,
eventHandlers,
collectedUsage,
artifactPromises,
endpoint: EModelEndpoint.agents,
configOptions: options.configOptions,
attachments: endpointOption.attachments,
maxContextTokens:
agent.max_context_tokens ??
getModelMaxTokens(modelOptions.model, providerEndpointMap[agent.provider]),
});
return { client };
};
module.exports = { initializeClient };