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Feat - Agent chat tab (#13061)

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Co-authored-by: Félix Malfait <felix.malfait@gmail.com>
Co-authored-by: Marie <51697796+ijreilly@users.noreply.github.com>
Co-authored-by: Antoine Moreaux <moreaux.antoine@gmail.com>
Co-authored-by: Raphaël Bosi <71827178+bosiraphael@users.noreply.github.com>
This commit is contained in:
Abdul Rahman
2025-07-08 02:17:41 +05:30
committed by GitHub
parent 29f7b74756
commit 51d02c13bf
40 changed files with 2777 additions and 127 deletions
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114
packages/twenty-server/src/engine/metadata-modules/agent/agent-execution.service.ts
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@ -1,8 +1,10 @@
import { Injectable } from '@nestjs/common';
import { InjectRepository } from '@nestjs/typeorm';
import { createAnthropic } from '@ai-sdk/anthropic';
import { createOpenAI } from '@ai-sdk/openai';
import { generateObject, generateText } from 'ai';
import { CoreMessage, generateObject, generateText, streamText } from 'ai';
import { Repository } from 'typeorm';
import {
ModelId,
@ -10,6 +12,10 @@ import {
} from 'src/engine/core-modules/ai/constants/ai-models.const';
import { getAIModelById } from 'src/engine/core-modules/ai/utils/get-ai-model-by-id';
import { TwentyConfigService } from 'src/engine/core-modules/twenty-config/twenty-config.service';
import {
AgentChatMessageEntity,
AgentChatMessageRole,
} from 'src/engine/metadata-modules/agent/agent-chat-message.entity';
import { AgentToolService } from 'src/engine/metadata-modules/agent/agent-tool.service';
import { AGENT_CONFIG } from 'src/engine/metadata-modules/agent/constants/agent-config.const';
import { AGENT_SYSTEM_PROMPTS } from 'src/engine/metadata-modules/agent/constants/agent-system-prompts.const';
@ -37,9 +43,13 @@ export class AgentExecutionService {
constructor(
private readonly twentyConfigService: TwentyConfigService,
private readonly agentToolService: AgentToolService,
@InjectRepository(AgentEntity, 'core')
private readonly agentRepository: Repository<AgentEntity>,
@InjectRepository(AgentChatMessageEntity, 'core')
private readonly agentChatmessageRepository: Repository<AgentChatMessageEntity>,
) {}
private getModel = (modelId: ModelId, provider: ModelProvider) => {
getModel = (modelId: ModelId, provider: ModelProvider) => {
switch (provider) {
case ModelProvider.OPENAI: {
const OpenAIProvider = createOpenAI({
@ -79,7 +89,6 @@ export class AgentExecutionService {
AgentExceptionCode.AGENT_EXECUTION_FAILED,
);
}
if (!apiKey) {
throw new AgentException(
`${provider.toUpperCase()} API key not configured`,
@ -88,6 +97,76 @@ export class AgentExecutionService {
}
}
async prepareAIRequestConfig({
messages,
prompt,
system,
agent,
}: {
system: string;
agent: AgentEntity;
prompt?: string;
messages?: CoreMessage[];
}) {
const aiModel = getAIModelById(agent.modelId);
if (!aiModel) {
throw new AgentException(
`AI model with id ${agent.modelId} not found`,
AgentExceptionCode.AGENT_EXECUTION_FAILED,
);
}
const provider = aiModel.provider;
await this.validateApiKey(provider);
const tools = await this.agentToolService.generateToolsForAgent(
agent.id,
agent.workspaceId,
);
return {
system,
tools,
model: this.getModel(agent.modelId, aiModel.provider),
...(messages && { messages }),
...(prompt && { prompt }),
maxSteps: AGENT_CONFIG.MAX_STEPS,
};
}
async streamChatResponse({
agentId,
userMessage,
messages,
}: {
agentId: string;
userMessage: string;
messages: AgentChatMessageEntity[];
}) {
const agent = await this.agentRepository.findOneOrFail({
where: { id: agentId },
});
const llmMessages: CoreMessage[] = messages.map(({ role, content }) => ({
role,
content,
}));
llmMessages.push({
role: AgentChatMessageRole.USER,
content: userMessage,
});
const aiRequestConfig = await this.prepareAIRequestConfig({
system: `${AGENT_SYSTEM_PROMPTS.AGENT_CHAT}\n\n${agent.prompt}`,
agent,
messages: llmMessages,
});
return streamText(aiRequestConfig);
}
async executeAgent({
agent,
context,
@ -98,31 +177,12 @@ export class AgentExecutionService {
schema: OutputSchema;
}): Promise<AgentExecutionResult> {
try {
const aiModel = getAIModelById(agent.modelId);
if (!aiModel) {
throw new AgentException(
`AI model with id ${agent.modelId} not found`,
AgentExceptionCode.AGENT_EXECUTION_FAILED,
);
}
const provider = aiModel.provider;
await this.validateApiKey(provider);
const tools = await this.agentToolService.generateToolsForAgent(
agent.id,
agent.workspaceId,
);
const textResponse = await generateText({
const aiRequestConfig = await this.prepareAIRequestConfig({
system: AGENT_SYSTEM_PROMPTS.AGENT_EXECUTION,
model: this.getModel(agent.modelId, provider),
agent,
prompt: resolveInput(agent.prompt, context) as string,
tools,
maxSteps: AGENT_CONFIG.MAX_STEPS,
});
const textResponse = await generateText(aiRequestConfig);
if (Object.keys(schema).length === 0) {
return {
@ -130,10 +190,9 @@ export class AgentExecutionService {
usage: textResponse.usage,
};
}
const output = await generateObject({
system: AGENT_SYSTEM_PROMPTS.OUTPUT_GENERATOR,
model: this.getModel(agent.modelId, provider),
model: aiRequestConfig.model,
prompt: `Based on the following execution results, generate the structured output according to the schema:
Execution Results: ${textResponse.text}
@ -163,7 +222,6 @@ export class AgentExecutionService {
if (error instanceof AgentException) {
throw error;
}
throw new AgentException(
error instanceof Error ? error.message : 'Agent execution failed',
AgentExceptionCode.AGENT_EXECUTION_FAILED,