OpenAI error handling

gui/pages/Content/Agents/AgentWorkspace.js

@@ -406,7 +406,7 @@ export default function AgentWorkspace({env, agentId, agentName, selectedView, a
                 {agentExecutions && agentExecutions.length > 1 && <li className="dropdown_item" onClick={() => {
                   updateRunStatus("TERMINATED")
                 }}>Delete Run</li>}
-                {agentExecutions && selectedRun && (selectedRun.status === 'CREATED' || selectedRun.status === 'PAUSED' || selectedRun.status === 'RUNNING' || agentExecutions.length > 1) && <div className={styles.dropdown_separator}/>}
+                {agentExecutions && selectedRun && (selectedRun.status === 'CREATED' || selectedRun.status === 'PAUSED' || selectedRun.status === 'RUNNING' || agentExecutions.length > 1 || selectedRun.status === 'ERROR_PAUSED') && <div className={styles.dropdown_separator}/>}
                 <li className="dropdown_item" onClick={() => saveAgentTemplate()}>Save as Template</li>
                 {agent && env === 'PROD' &&
                   <li className="dropdown_item" onClick={() => {

superagi/agent/agent_iteration_step_handler.py

@@ -77,6 +77,7 @@ def execute_step(self):
             agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=response['message'], feed_group_id=execution.current_feed_group_id)
             self.session.add(agent_feed)
             self.session.commit()
+
         if 'content' not in response or response['content'] is None:
             raise RuntimeError(f"Failed to get response from llm")
 

superagi/agent/agent_message_builder.py

@@ -119,6 +119,12 @@ def _build_ltm_summary(self, past_messages, output_token_limit) -> str:
                 {"role": "assistant", "content": ltm_prompt}]
         ltm_summary = self.llm.chat_completion(msgs)
 
+        execution = self.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in ltm_summary and ltm_summary['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=ltm_summary['message'], feed_group_id=execution.current_feed_group_id)
+            self.session.add(agent_feed)
+            self.session.commit()
+
         execution = AgentExecution(id=self.agent_execution_id)
         agent_execution_configs = {"ltm_summary": ltm_summary["content"]}
         AgentExecutionConfiguration.add_or_update_agent_execution_config(session=self.session, execution=execution,

superagi/agent/agent_tool_step_handler.py

@@ -105,6 +105,12 @@ def _process_input_instruction(self, agent_config, agent_execution_config, step_
         # print(messages)
         current_tokens = TokenCounter.count_message_tokens(messages, self.llm.get_model())
         response = self.llm.chat_completion(messages, TokenCounter(session=self.session, organisation_id=self.organisation.id).token_limit(self.llm.get_model()) - current_tokens)
+
+        execution = self.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in response and response['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=response['message'], feed_group_id=execution.current_feed_group_id)
+            self.session.add(agent_feed)
+            self.session.commit()
         # ModelsHelper(session=self.session, organisation_id=organisation.id).create_call_log(execution.name,agent_config['agent_id'],response['response'].usage.total_tokens,json.loads(response['content'])['tool']['name'],agent_config['model'])
         if 'content' not in response or response['content'] is None:
             raise RuntimeError(f"Failed to get response from llm")
@@ -137,6 +143,12 @@ def _process_output_instruction(self, final_response: str, step_tool: AgentWorkf
         current_tokens = TokenCounter.count_message_tokens(messages, self.llm.get_model())
         response = self.llm.chat_completion(messages,
                                             TokenCounter(session=self.session, organisation_id=self.organisation.id).token_limit(self.llm.get_model()) - current_tokens)
+        execution = self.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in response and response['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=response['message'], feed_group_id=execution.current_feed_group_id)
+            self.session.add(agent_feed)
+            self.session.commit()
+
         if 'content' not in response or response['content'] is None:
             raise RuntimeError(f"ToolWorkflowStepHandler: Failed to get output response from llm")
         total_tokens = current_tokens + TokenCounter.count_message_tokens(response, self.llm.get_model())

superagi/agent/queue_step_handler.py

@@ -90,6 +90,11 @@ def _process_input_instruction(self, step_tool):
                                   completion_prompt=step_tool.completion_prompt)
         current_tokens = TokenCounter.count_message_tokens(messages, self.llm.get_model())
         response = self.llm.chat_completion(messages, TokenCounter(session=self.session, organisation_id=self.organisation.id).token_limit(self.llm.get_model()) - current_tokens)
+        execution = self.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in response and response['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=response['message'], feed_group_id=execution.current_feed_group_id)
+            self.session.add(agent_feed)
+            self.session.commit()
         if 'content' not in response or response['content'] is None:
             raise RuntimeError(f"Failed to get response from llm")
         total_tokens = current_tokens + TokenCounter.count_message_tokens(response, self.llm.get_model())

superagi/controllers/agent_execution_feed.py

@@ -1,7 +1,9 @@
+import asyncio
 from datetime import datetime
+import time
 from typing import Optional
 
-from fastapi import APIRouter
+from fastapi import APIRouter, BackgroundTasks
 from fastapi import HTTPException, Depends
 from fastapi_jwt_auth import AuthJWT
 from fastapi_sqlalchemy import db
@@ -145,7 +147,7 @@ def update_agent_execution_feed(agent_execution_feed_id: int,
 
 @router.get("/get/execution/{agent_execution_id}")
 def get_agent_execution_feed(agent_execution_id: int,
-                             Authorize: AuthJWT = Depends(check_auth)):
+                                         Authorize: AuthJWT = Depends(check_auth)):
     """
     Get agent execution feed with other execution details.
 
@@ -171,7 +173,8 @@ def get_agent_execution_feed(agent_execution_id: int,
             if (agent_execution.last_shown_error_id is None) or (feed.id > agent_execution.last_shown_error_id):
                 #error occured
                 final_feeds.clear()
-                final_feeds.append(feed.error_message)
+                dict = {"error": feed.error_message}
+                final_feeds.append(dict)
                 agent_execution.last_shown_error_id = feed.id
                 agent_execution.status = "ERROR_PAUSED"
                 db.session.commit()
@@ -197,7 +200,6 @@ def get_agent_execution_feed(agent_execution_id: int,
         } for permission in execution_permissions
     ]
     logger.info(final_feeds)
-    logger.info(agent_execution_id)
     return {
         "status": agent_execution.status,
         "feeds": final_feeds,

superagi/tools/code/improve_code.py

@@ -8,9 +8,12 @@
 from superagi.helper.token_counter import TokenCounter
 from superagi.lib.logger import logger
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.resource_manager.file_manager import FileManager
 from superagi.tools.base_tool import BaseTool
 from superagi.tools.tool_response_query_manager import ToolResponseQueryManager
+from fastapi_sqlalchemy import db
 
 
 class ImproveCodeSchema(BaseModel):
@@ -29,6 +32,7 @@ class ImproveCodeTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     agent_id: int = None
+    agent_execution_id: int = None
     name = "ImproveCodeTool"
     description = (
         "This tool improves the generated code."
@@ -71,6 +75,11 @@ def _execute(self) -> str:
 
                 # Use LLM to generate improved code
                 result = self.llm.chat_completion([{'role': 'system', 'content': prompt}])
+                execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+                if result is not None and 'error' in result and result['message'] is not None:
+                    agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+                    db.session.add(agent_feed)
+                    db.session.commit()
 
                 # Extract the response first
                 response = result.get('response')

superagi/tools/code/write_code.py

@@ -8,10 +8,13 @@
 from superagi.helper.token_counter import TokenCounter
 from superagi.lib.logger import logger
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.resource_manager.file_manager import FileManager
 from superagi.tools.base_tool import BaseTool
 from superagi.tools.tool_response_query_manager import ToolResponseQueryManager
 from superagi.models.agent import Agent
+from fastapi_sqlalchemy import db
 
 class CodingSchema(BaseModel):
     code_description: str = Field(
@@ -34,6 +37,7 @@ class CodingTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     agent_id: int = None
+    agent_execution_id: int = None
     name = "CodingTool"
     description = (
         "You will get instructions for code to write. You will write a very long answer. "
@@ -75,6 +79,11 @@ def _execute(self, code_description: str) -> str:
         token_limit = TokenCounter(session=self.toolkit_config.session, organisation_id=organisation.id).token_limit(self.llm.get_model())
 
         result = self.llm.chat_completion(messages, max_tokens=(token_limit - total_tokens - 100))
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
 
         # Get all filenames and corresponding code blocks
         regex = r"(\S+?)\n```\S*\n(.+?)```"

superagi/tools/code/write_spec.py

@@ -7,9 +7,12 @@
 from superagi.helper.token_counter import TokenCounter
 from superagi.lib.logger import logger
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.resource_manager.file_manager import FileManager
 from superagi.tools.base_tool import BaseTool
 from superagi.models.agent import Agent
+from fastapi_sqlalchemy import db
 
 class WriteSpecSchema(BaseModel):
     task_description: str = Field(
@@ -37,6 +40,7 @@ class WriteSpecTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     agent_id: int = None
+    agent_execution_id: int = None
     name = "WriteSpecTool"
     description = (
         "A tool to write the spec of a program."
@@ -69,6 +73,11 @@ def _execute(self, task_description: str, spec_file_name: str) -> str:
         token_limit = TokenCounter(session=self.toolkit_config.session, organisation_id=organisation.id).token_limit(self.llm.get_model())
 
         result = self.llm.chat_completion(messages, max_tokens=(token_limit - total_tokens - 100))
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
 
         # Save the specification to a file
         write_result = self.resource_manager.write_file(spec_file_name, result["content"])

superagi/tools/code/write_test.py

@@ -8,10 +8,13 @@
 from superagi.helper.token_counter import TokenCounter
 from superagi.lib.logger import logger
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.resource_manager.file_manager import FileManager
 from superagi.tools.base_tool import BaseTool
 from superagi.tools.tool_response_query_manager import ToolResponseQueryManager
 from superagi.models.agent import Agent
+from fastapi_sqlalchemy import db
 
 class WriteTestSchema(BaseModel):
     test_description: str = Field(
@@ -38,6 +41,7 @@ class WriteTestTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     agent_id: int = None
+    agent_execution_id: int = None
     name = "WriteTestTool"
     description = (
         "You are a super smart developer using Test Driven Development to write tests according to a specification.\n"
@@ -86,6 +90,11 @@ def _execute(self, test_description: str, test_file_name: str) -> str:
         token_limit = TokenCounter(session=self.toolkit_config.session, organisation_id=organisation.id).token_limit(self.llm.get_model())
 
         result = self.llm.chat_completion(messages, max_tokens=(token_limit - total_tokens - 100))
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
 
         regex = r"(\S+?)\n```\S*\n(.+?)```"
         matches = re.finditer(regex, result["content"], re.DOTALL)

superagi/tools/duck_duck_go/duck_duck_go_search.py

@@ -8,8 +8,11 @@
 from itertools import islice
 from superagi.helper.token_counter import TokenCounter
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.tools.base_tool import BaseTool
 from superagi.helper.webpage_extractor import WebpageExtractor
+from fastapi_sqlalchemy import db
 
 #Const variables
 DUCKDUCKGO_MAX_ATTEMPTS = 3
@@ -33,6 +36,8 @@ class DuckDuckGoSearchTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     name = "DuckDuckGoSearch"
+    agent_id: int = None
+    agent_execution_id: int = None
     description = (
         "A tool for performing a DuckDuckGo search and extracting snippets and webpages."
         "Input should be a search query."
@@ -169,4 +174,9 @@ def summarise_result(self, query, snippets):
 
         messages = [{"role": "system", "content": summarize_prompt}]
         result = self.llm.chat_completion(messages, max_tokens=self.max_token_limit)
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
         return result["content"]

superagi/tools/github/review_pull_request.py

@@ -9,7 +9,10 @@
 from superagi.helper.token_counter import TokenCounter
 from superagi.llms.base_llm import BaseLlm
 from superagi.models.agent import Agent
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.tools.base_tool import BaseTool
+from fastapi_sqlalchemy import db
 
 
 class GithubReviewPullRequestSchema(BaseModel):
@@ -87,6 +90,11 @@ def run_code_review(self, github_helper, content, latest_commit_id, organisation
         token_limit = TokenCounter(session=self.toolkit_config.session,
                                    organisation_id=organisation.id).token_limit(self.llm.get_model())
         result = self.llm.chat_completion(messages, max_tokens=(token_limit - total_tokens - 100))
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
         response = result["content"]
         if response.startswith("```") and response.endswith("```"):
             response = "```".join(response.split("```")[1:-1])

superagi/tools/google_search/google_search.py

@@ -6,8 +6,10 @@
 from superagi.helper.google_search import GoogleSearchWrap
 from superagi.helper.token_counter import TokenCounter
 from superagi.llms.base_llm import BaseLlm
+from superagi.models.agent_execution import AgentExecution
+from superagi.models.agent_execution_feed import AgentExecutionFeed
 from superagi.tools.base_tool import BaseTool
-
+from fastapi_sqlalchemy import db
 
 class GoogleSearchSchema(BaseModel):
     query: str = Field(
@@ -26,6 +28,8 @@ class GoogleSearchTool(BaseTool):
     """
     llm: Optional[BaseLlm] = None
     name = "GoogleSearch"
+    agent_id: int = None
+    agent_execution_id: int = None
     description = (
         "A tool for performing a Google search and extracting snippets and webpages."
         "Input should be a search query."
@@ -88,4 +92,9 @@ def summarise_result(self, query, snippets):
 
         messages = [{"role": "system", "content": summarize_prompt}]
         result = self.llm.chat_completion(messages, max_tokens=self.max_token_limit)
+        execution = db.session.query(AgentExecution).filter(AgentExecution.id == self.agent_execution_id).first()
+        if 'error' in result and result['message'] is not None:
+            agent_feed = AgentExecutionFeed(agent_execution_id=self.agent_execution_id, agent_id=self.agent_id, role="system", feed="", error_message=result['message'], feed_group_id=execution.current_feed_group_id)
+            db.session.add(agent_feed)
+            db.session.commit()
         return result["content"]