document fix

superagi/agent/output_parser.py

@@ -42,4 +42,3 @@ def parse(self, response: str) -> AgentGPTAction:
             )
         except BaseException as e:
             logger.info(f"AgentSchemaOutputParser: Error parsing JSON respons {e}")
-            return {}

superagi/agent/super_agi.py

@@ -210,7 +210,7 @@ def execute(self, workflow_step: AgentWorkflowStep):
     def handle_tool_response(self, session, assistant_reply):
         action = self.output_parser.parse(assistant_reply)
         tools = {t.name.lower().replace(" ", ""): t for t in self.tools}
-        action_name = action.name.lower().replace(" ", "")
+        action_name = action.name.lower().replace(" ", "") if action is not None else ""
         agent = session.query(Agent).filter(Agent.id == self.agent_config["agent_id"],).first()
         organisation = agent.get_agent_organisation(session)
         if action_name == FINISH or action.name == "":

superagi/resource_manager/llama_document_summary.py

@@ -22,6 +22,8 @@ def generate_summary_of_document(self, documents: list[Document]):
         :param documents: list of Document objects
         :return: summary of the documents
         """
+        if documents is None or not documents:
+            return
         from llama_index import LLMPredictor, ServiceContext, ResponseSynthesizer, DocumentSummaryIndex
         os.environ["OPENAI_API_KEY"] = get_config("OPENAI_API_KEY", "") or self.model_api_key
         llm_predictor_chatgpt = LLMPredictor(llm=self._build_llm())

superagi/resource_manager/resource_manager.py

@@ -31,9 +31,9 @@ def create_llama_document(self, file_path: str):
         """
         if file_path is None:
             raise Exception("file_path must be provided")
-        documents = SimpleDirectoryReader(input_files=[file_path]).load_data()
-
-        return documents
+        if os.path.exists(file_path):
+            documents = SimpleDirectoryReader(input_files=[file_path]).load_data()
+            return documents
 
     def create_llama_document_s3(self, file_path: str):
         """
@@ -44,6 +44,7 @@ def create_llama_document_s3(self, file_path: str):
         """
         if file_path is None:
             raise Exception("file_path must be provided")
+        temporary_file_path = ""
         try:
             import boto3
             s3 = boto3.client(
@@ -61,12 +62,12 @@ def create_llama_document_s3(self, file_path: str):
                 f.write(contents)
 
             documents = SimpleDirectoryReader(input_files=[temporary_file_path]).load_data()
+            return documents
         except Exception as e:
             logger.error("superagi/resource_manager/resource_manager.py - create_llama_document_s3 threw : ", e)
         finally:
             if os.path.exists(temporary_file_path):
                 os.remove(temporary_file_path)
-        return documents
 
     def save_document_to_vector_store(self, documents: list, resource_id: str, mode_api_key: str = None,
                                       model_source: str = ""):

superagi/resource_manager/resource_summary.py

@@ -67,7 +67,8 @@ def generate_agent_summary(self, agent_id: int, generate_all: bool = False) -> s
                     documents = ResourceManager(str(agent_id)).create_llama_document_s3(file_path)
                 else:
                     documents = ResourceManager(str(agent_id)).create_llama_document(file_path)
-                summary_texts.append(LlamaDocumentSummary(model_api_key=model_api_key, model_source=model_source).generate_summary_of_document(documents))
+                if documents is not None and len(documents) > 0:
+                    summary_texts.append(LlamaDocumentSummary(model_api_key=model_api_key, model_source=model_source).generate_summary_of_document(documents))
 
         agent_last_resource = self.session.query(AgentConfiguration). \
             filter(AgentConfiguration.agent_id == agent_id,