Merge pull request #834 from TransformerOptimus/iteration_workflow

Iteration workflow

gui/pages/Content/Agents/ActionConsole.js

@@ -11,7 +11,9 @@ function ActionBox({action, index, denied, reasons, handleDeny, handleSelection,
     <div key={action.id} className={styles.history_box}
          style={{background: '#272335', padding: '16px', cursor: 'default'}}>
       <div style={{display: 'flex', flexDirection: 'column'}}>
-        <div>Tool <b>{action.tool_name}</b> is seeking for Permissions</div>
+        {action.question && (<div className={styles.feed_title}>{action.question}</div>)}
+        {!action.question && (<div>Tool <b>{action.tool_name}</b> is seeking for Permissions</div>)}
+
         {isDenied && (
           <div style={{marginTop: '26px'}}>
             <div>Provide Feedback <span style={{color: '#888888'}}>(Optional)</span></div>

gui/pages/Content/Agents/AgentCreate.js

@@ -9,7 +9,7 @@ import {
   getOrganisationConfig,
   getLlmModels,
   updateExecution,
-  uploadFile
+  uploadFile, getAgentWorkflows
 } from "@/pages/api/DashboardService";
 import {
   formatBytes,
@@ -68,8 +68,12 @@ export default function AgentCreate({
   const modelRef = useRef(null);
   const [modelDropdown, setModelDropdown] = useState(false);
 
-  const agentTypes = ["Don't Maintain Task Queue", "Maintain Task Queue", "Fixed Task Queue"]
+  // const agentTypes = ["Goal Based Workflow",
+  //   "Dynamic Task Workflow", "Fixed Task Workflow", "Sales Research Workflow", "SuperCoder", "DocSuperCoder", "Research & send email"]
+  // const agentTypes = ["Don't Maintain Task Queue", "Maintain Task Queue", "Fixed Task Queue"]
+  const [agentTypes, setAgentTypes] = useState('');
   const [agentType, setAgentType] = useState(agentTypes[0]);
+
   const agentRef = useRef(null);
   const [agentDropdown, setAgentDropdown] = useState(false);
 
@@ -156,6 +160,21 @@ export default function AgentCreate({
         console.error('Error fetching models:', error);
       });
 
+    getAgentWorkflows()
+      .then((response) => {
+        const agentTypes = response.data || [];
+        const selectedAgentType = localStorage.getItem("agent_type_" + String(internalId)) || '';
+        setAgentTypes(agentTypes);
+        if (agentTypes.length > 0 && !selectedAgentType) {
+          setLocalStorageValue("agent_type_" + String(internalId), agentTypes[0], setAgentType);
+        } else {
+          setAgentType(selectedAgentType);
+        }
+      })
+      .catch((error) => {
+        console.error('Error fetching agent workflows:', error);
+      });
+
     if (template !== null) {
       setLocalStorageValue("agent_name_" + String(internalId), template.name, setAgentName);
       setLocalStorageValue("agent_description_" + String(internalId), template.description, setAgentDescription);

gui/pages/Content/Agents/AgentWorkspace.js

@@ -426,7 +426,7 @@ export default function AgentWorkspace({env, agentId, agentName, selectedView, a
       <div style={{width: '40%'}}>
         <div className={styles.detail_top}>
           <div style={{display: 'flex', overflowX: 'scroll'}}>
-            {agentDetails && agentDetails.permission_type.includes('RESTRICTED') && <div>
+            {agentDetails && pendingPermission > 0 && <div>
               <button onClick={() => setRightPanel('action_console')} className={styles.tab_button}
                       style={rightPanel === 'action_console' ? {background: '#454254'} : {background: 'transparent'}}>
                 <Image style={{marginTop: '-1px'}} width={14} height={14} src="/images/action_console.svg"
@@ -465,7 +465,7 @@ export default function AgentWorkspace({env, agentId, agentName, selectedView, a
           </div>
         </div>
         <div className={styles.detail_body} style={{paddingRight: '0'}}>
-          {rightPanel === 'action_console' && agentDetails && agentDetails?.permission_type !== 'God Mode' && (
+          {rightPanel === 'action_console' && agentDetails && pendingPermission > 0 && (
             <div className={styles.detail_content}>
               <ActionConsole key={JSON.stringify(fetchedData)} actions={fetchedData}
                              pendingPermission={pendingPermission} setPendingPermissions={setPendingPermissions}/>

gui/pages/api/DashboardService.js

@@ -232,6 +232,10 @@ export const getLlmModels = () => {
   return api.get(`organisations/llm_models`);
 };
 
+export const getAgentWorkflows = () => {
+  return api.get(`organisations/agent_workflows`);
+};
+
 export const fetchVectorDBList = () => {
   return api.get(`/vector_dbs/get/list`);
 };

main.py

@@ -1,7 +1,3 @@
-import os
-import pickle
-from datetime import datetime, timedelta
-
 import requests
 from fastapi import FastAPI, HTTPException, Depends, Request, status, Query
 from fastapi.middleware.cors import CORSMiddleware
@@ -15,12 +11,9 @@
 from sqlalchemy.orm import sessionmaker
 
 import superagi
-import urllib.parse
-import json
-import http.client as http_client
-from superagi.helper.twitter_tokens import TwitterTokens
-from datetime import datetime, timedelta
+from datetime import timedelta, datetime
 from superagi.agent.agent_prompt_builder import AgentPromptBuilder
+from superagi.agent.workflow_seed import IterationWorkflowSeed, AgentWorkflowSeed
 from superagi.config.config import get_config
 from superagi.controllers.agent import router as agent_router
 from superagi.controllers.agent_config import router as agent_config_router
@@ -51,16 +44,14 @@
 from superagi.lib.logger import logger
 from superagi.llms.google_palm import GooglePalm
 from superagi.llms.openai import OpenAi
-from superagi.helper.auth import get_current_user
-from superagi.models.agent_workflow import AgentWorkflow
-from superagi.models.agent_workflow_step import AgentWorkflowStep
+from superagi.models.agent_template import AgentTemplate
 from superagi.models.organisation import Organisation
-from superagi.models.tool_config import ToolConfig
-from superagi.models.toolkit import Toolkit
-from superagi.models.oauth_tokens import OauthTokens
 from superagi.models.types.login_request import LoginRequest
 from superagi.models.types.validate_llm_api_key_request import ValidateAPIKeyRequest
 from superagi.models.user import User
+from superagi.models.workflows.agent_workflow import AgentWorkflow
+from superagi.models.workflows.iteration_workflow import IterationWorkflow
+from superagi.models.workflows.iteration_workflow_step import IterationWorkflowStep
 
 app = FastAPI()
 
@@ -161,6 +152,26 @@ def authjwt_exception_handler(request: Request, exc: AuthJWTException):
     )
 
 
+def replace_old_iteration_workflows(session):
+    dateTimeObj = datetime.strptime("4-August-2023", "%d-%B-%Y")
+    templates = session.query(AgentTemplate).filter(AgentTemplate.created_at <= dateTimeObj).all()
+    for template in templates:
+        iter_workflow = IterationWorkflow.find_by_id(session, template.agent_workflow_id)
+        if iter_workflow.name == "Fixed Task Queue":
+            agent_workflow = AgentWorkflow.find_by_name(session, "Fixed Task Workflow")
+            template.agent_workflow_id = agent_workflow.id
+            session.commit()
+
+        if iter_workflow.name == "Maintain Task Queue":
+            agent_workflow = AgentWorkflow.find_by_name(session, "Dynamic Task Workflow")
+            template.agent_workflow_id = agent_workflow.id
+            session.commit()
+
+        if iter_workflow.name == "Don't Maintain Task Queue" or iter_workflow.name == "Goal Based Agent":
+            agent_workflow = AgentWorkflow.find_by_name(session, "Goal Based Workflow")
+            template.agent_workflow_id = agent_workflow.id
+            session.commit()
+
 @app.on_event("startup")
 async def startup_event():
     # Perform startup tasks here
@@ -174,158 +185,6 @@ async def startup_event():
         logger.info(organisation)
         register_toolkits(session, organisation)
 
-    def build_single_step_agent():
-        agent_workflow = session.query(AgentWorkflow).filter(AgentWorkflow.name == "Goal Based Agent").first()
-
-        if agent_workflow is None:
-            agent_workflow = AgentWorkflow(name="Goal Based Agent", description="Goal based agent")
-            session.add(agent_workflow)
-            session.commit()
-
-        # step will have a prompt
-        # output of step is either tasks or set commands
-        first_step = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "gb1").first()
-        output = AgentPromptBuilder.get_super_agi_single_prompt()
-        if first_step is None:
-            first_step = AgentWorkflowStep(unique_id="gb1",
-                                           prompt=output["prompt"], variables=str(output["variables"]),
-                                           agent_workflow_id=agent_workflow.id, output_type="tools",
-                                           step_type="TRIGGER",
-                                           history_enabled=True,
-                                           completion_prompt="Determine which next tool to use,and respond with only valid JSON conforming to the above schema")
-            session.add(first_step)
-            session.commit()
-        else:
-            first_step.prompt = output["prompt"]
-            first_step.variables = str(output["variables"])
-            first_step.output_type = "tools"
-            first_step.completion_prompt = "Determine which next tool to use,and respond with only valid JSON conforming to the above schema"
-            session.commit()
-        first_step.next_step_id = first_step.id
-        session.commit()
-
-    def build_task_based_agents():
-        agent_workflow = session.query(AgentWorkflow).filter(AgentWorkflow.name == "Task Queue Agent With Seed").first()
-        if agent_workflow is None:
-            agent_workflow = AgentWorkflow(name="Task Queue Agent With Seed", description="Task queue based agent")
-            session.add(agent_workflow)
-            session.commit()
-
-        output = AgentPromptBuilder.start_task_based()
-
-        workflow_step1 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "tb1").first()
-        if workflow_step1 is None:
-            workflow_step1 = AgentWorkflowStep(unique_id="tb1",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="TRIGGER",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="tasks")
-            session.add(workflow_step1)
-        else:
-            workflow_step1.prompt = output["prompt"]
-            workflow_step1.variables = str(output["variables"])
-            workflow_step1.output_type = "tasks"
-            session.commit()
-
-        workflow_step2 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "tb2").first()
-        output = AgentPromptBuilder.create_tasks()
-        if workflow_step2 is None:
-            workflow_step2 = AgentWorkflowStep(unique_id="tb2",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="NORMAL",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="tasks")
-            session.add(workflow_step2)
-        else:
-            workflow_step2.prompt = output["prompt"]
-            workflow_step2.variables = str(output["variables"])
-            workflow_step2.output_type = "tasks"
-            session.commit()
-
-        workflow_step3 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "tb3").first()
-
-        output = AgentPromptBuilder.analyse_task()
-        if workflow_step3 is None:
-            workflow_step3 = AgentWorkflowStep(unique_id="tb3",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="NORMAL",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="tools")
-
-            session.add(workflow_step3)
-        else:
-            workflow_step3.prompt = output["prompt"]
-            workflow_step3.variables = str(output["variables"])
-            workflow_step3.output_type = "tools"
-            session.commit()
-
-        workflow_step4 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "tb4").first()
-        output = AgentPromptBuilder.prioritize_tasks()
-        if workflow_step4 is None:
-            workflow_step4 = AgentWorkflowStep(unique_id="tb4",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="NORMAL",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="replace_tasks")
-
-            session.add(workflow_step4)
-        else:
-            workflow_step4.prompt = output["prompt"]
-            workflow_step4.variables = str(output["variables"])
-            workflow_step4.output_type = "replace_tasks"
-            session.commit()
-        session.commit()
-        workflow_step1.next_step_id = workflow_step3.id
-        workflow_step3.next_step_id = workflow_step2.id
-        workflow_step2.next_step_id = workflow_step4.id
-        workflow_step4.next_step_id = workflow_step3.id
-        session.commit()
-
-    def build_action_based_agents():
-        agent_workflow = session.query(AgentWorkflow).filter(AgentWorkflow.name == "Fixed Task Queue").first()
-        if agent_workflow is None:
-            agent_workflow = AgentWorkflow(name="Fixed Task Queue", description="Fixed Task Queue")
-            session.add(agent_workflow)
-            session.commit()
-
-        output = AgentPromptBuilder.start_task_based()
-
-        workflow_step1 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "ab1").first()
-        if workflow_step1 is None:
-            workflow_step1 = AgentWorkflowStep(unique_id="ab1",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="TRIGGER",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="tasks")
-            session.add(workflow_step1)
-        else:
-            workflow_step1.prompt = output["prompt"]
-            workflow_step1.variables = str(output["variables"])
-            workflow_step1.output_type = "tasks"
-            workflow_step1.agent_workflow_id = agent_workflow.id
-            session.commit()
-
-        workflow_step2 = session.query(AgentWorkflowStep).filter(AgentWorkflowStep.unique_id == "ab2").first()
-        output = AgentPromptBuilder.analyse_task()
-        if workflow_step2 is None:
-            workflow_step2 = AgentWorkflowStep(unique_id="ab2",
-                                               prompt=output["prompt"], variables=str(output["variables"]),
-                                               step_type="NORMAL",
-                                               agent_workflow_id=agent_workflow.id, next_step_id=-1,
-                                               output_type="tools")
-            session.add(workflow_step2)
-        else:
-            workflow_step2.prompt = output["prompt"]
-            workflow_step2.variables = str(output["variables"])
-            workflow_step2.output_type = "tools"
-            workflow_step2.agent_workflow_id = agent_workflow.id
-            session.commit()
-
-        session.commit()
-        workflow_step1.next_step_id = workflow_step2.id
-        workflow_step2.next_step_id = workflow_step2.id
-        session.commit()
-
     def register_toolkit_for_all_organisation():
         organizations = session.query(Organisation).all()
         for organization in organizations:
@@ -339,9 +198,21 @@ def register_toolkit_for_master_organisation():
         if marketplace_organisation is not None:
             register_marketplace_toolkits(session, marketplace_organisation)
 
-    build_single_step_agent()
-    build_task_based_agents()
-    build_action_based_agents()
+    IterationWorkflowSeed.build_single_step_agent(session)
+    IterationWorkflowSeed.build_task_based_agents(session)
+    IterationWorkflowSeed.build_action_based_agents(session)
+    IterationWorkflowSeed.build_initialize_task_workflow(session)
+
+    AgentWorkflowSeed.build_goal_based_agent(session)
+    AgentWorkflowSeed.build_task_based_agent(session)
+    AgentWorkflowSeed.build_fixed_task_based_agent(session)
+    AgentWorkflowSeed.build_sales_workflow(session)
+    AgentWorkflowSeed.build_recruitment_workflow(session)
+    AgentWorkflowSeed.build_coding_workflow(session)
+    # AgentWorkflowSeed.doc_search_and_code(session)
+    # AgentWorkflowSeed.build_research_email_workflow(session)
+    replace_old_iteration_workflows(session)
+
     if env != "PROD":
         register_toolkit_for_all_organisation()
     else:

migrations/versions/2fbd6472112c_add_feed_group_id_to_execution_and_feed.py

@@ -0,0 +1,26 @@
+"""add feed group id to execution and feed
+
+Revision ID: 2fbd6472112c
+Revises: 5184645e9f12
+Create Date: 2023-08-01 17:09:16.183863
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+# revision identifiers, used by Alembic.
+revision = '2fbd6472112c'
+down_revision = '5184645e9f12'
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column('agent_executions',
+                  sa.Column('current_feed_group_id', sa.String(), nullable=True, server_default="DEFAULT"))
+    op.add_column('agent_execution_feeds', sa.Column('feed_group_id', sa.String(), nullable=True))
+
+
+def downgrade() -> None:
+    op.drop_column('agent_executions', 'current_feed_group_id')
+    op.drop_column('agent_execution_feeds', 'feed_group_id')

migrations/versions/5184645e9f12_add_question_to_agent_execution_.py

@@ -0,0 +1,24 @@
+"""add question to agent execution permission
+
+Revision ID: 5184645e9f12
+Revises: 9419b3340af7
+Create Date: 2023-07-21 08:16:14.702389
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = '5184645e9f12'
+down_revision = '9419b3340af7'
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column('agent_execution_permissions', sa.Column('question', sa.Text(), nullable=True))
+
+
+def downgrade() -> None:
+    op.drop_column('agent_execution_permissions', "question")