Merge pull request #601 from openchatai/feat/parsing

Feat/parsing

llm-server/routes/chat/implementation/chain_strategy.py

@@ -49,20 +49,26 @@ async def handle_request(
 
         top_documents = select_top_documents(actions + flows + knowledgebase)
 
-        emit(
-            f"{session_id}_info", "Checking if actionable ... \n"
-        ) if is_streaming else None
+        (
+            emit(f"{session_id}_info", "Checking if actionable ... \n")
+            if is_streaming
+            else None
+        )
         next_step = get_next_response_type(
             user_message=text,
             session_id=session_id,
             chat_history=conversations_history,
             top_documents=top_documents,
         )
 
-        emit(
-            f"{session_id}_info",
-            f"Is next step actionable: {next_step.actionable}... \n",
-        ) if is_streaming else None
+        (
+            emit(
+                f"{session_id}_info",
+                f"Is next step actionable: {next_step.actionable}... \n",
+            )
+            if is_streaming
+            else None
+        )
         if next_step.actionable and next_step.api:
             # if the LLM given operationID is actually exist, then use it, otherwise fallback to the highest vector space document
             llm_predicted_operation_id = (
@@ -78,9 +84,11 @@ async def handle_request(
                     [VectorCollections.actions, VectorCollections.flows],
                 )
             # now run it
-            emit(
-                f"{session_id}_info", "Executing the actionable item... \n"
-            ) if is_streaming else None
+            (
+                emit(f"{session_id}_info", "Executing the actionable item... \n")
+                if is_streaming
+                else None
+            )
             response = await run_actionable_item(
                 bot_id=bot_id,
                 actionable_item=actionable_item,
@@ -92,20 +100,26 @@ async def handle_request(
             )
 
             response.api_called = True
-            add_action_call(
-                operation_id=actionable_item["actions"][0].document.metadata.get(
-                    "operation_id", ""
-                ),
-                session_id=session_id,
-                bot_id=bot_id,
-            )
+            if (
+                actionable_item
+                and "actions" in actionable_item
+                and actionable_item["actions"]
+            ):
+                action = actionable_item["actions"][0]
+                operation_id = action.document.metadata.get("operation_id", "")
+                add_action_call(
+                    operation_id=operation_id, session_id=session_id, bot_id=bot_id
+                )
             return response
+
         else:
             # it means that the user query is "informative" and can be answered using text only
             # get the top knowledgeable documents (if any)
-            emit(
-                f"{session_id}_info", "Running informative action... \n"
-            ) if is_streaming else None
+            (
+                emit(f"{session_id}_info", "Running informative action... \n")
+                if is_streaming
+                else None
+            )
             response = await run_informative_item(
                 informative_item=top_documents,
                 base_prompt=base_prompt,

llm-server/routes/flow/utils/run_workflow.py

@@ -60,5 +60,5 @@ async def run_flow(
         error=output["error"],
         message=output["response"],
         api_called=True,
-        action_ids=flow.get_all_action_ids(),
+        operation_ids=flow.get_all_action_ids(),
     )

llm-server/utils/llm_consts.py

@@ -80,5 +80,5 @@ def get_mysql_uri():
 max_pages_to_crawl = int(os.getenv("MAX_PAGES_TO_CRAWL", "15"))
 
 enable_followup_questions = (
-    True if os.getenv("ENABLE_FOLLOWUP_QUESTIONS", "YES") == "YES" else False
+    True if os.getenv("ENABLE_FOLLOWUP_QUESTIONS", "NO") == "YES" else False
 )

llm-server/utils/swagger_parser.py

@@ -18,15 +18,15 @@
 
 class Endpoint:
     def __init__(
-            self,
-            operation_id,
-            endpoint_type,
-            name,
-            description,
-            request_body,
-            parameters,
-            response,
-            path,
+        self,
+        operation_id,
+        endpoint_type,
+        name,
+        description,
+        request_body,
+        parameters,
+        response,
+        path,
     ):
         self.operation_id = operation_id
         self.type = endpoint_type
@@ -233,9 +233,24 @@ def get_all_actions(self, bot_id: str):
                 # Process the payload to resolve any $ref references
                 processed_payload = self.process_payload(payload)
 
+                name = method_data.get(
+                    "operation_id",
+                    method_data.get(
+                        "name",
+                        method_data.get("summary", method_data.get("description")),
+                    ),
+                )
+                if name is None:
+                    logger.error(
+                        "operation_id_not_found",
+                        bot_id=bot_id,
+                        path=path,
+                        method=method,
+                    )
+
                 action_dto = ActionDTO(
                     api_endpoint=base_uri + path,
-                    name=method_data.get("name", method_data.get("summary", method_data.get('description'))),
+                    name=name,
                     description=method_data.get("description"),
                     request_type=method.upper(),
                     payload=processed_payload,
@@ -263,8 +278,8 @@ def gather_metadata(self, api_data: dict) -> DefaultDict[str, Dict[str, str]]:
 
         for path, path_item in api_data["paths"].items():
             for http_verb, http_details in path_item.items():
-                summary = http_details.get("summary") or ""
-                description = http_details.get("description") or ""
+                summary = http_details.get("summary", "")
+                description = http_details.get("description", "")
                 # inconsistent tag behaviour..
                 # tags = (
                 #     ", ".join([t["name"] for t in http_details.get("tags", [])])