removed prefect support

deploy/docker/osbot-llms/Dockerfile

@@ -1,7 +1,7 @@
 FROM python:3.12-slim
 
 RUN pip install mangum uvicorn httpx openai numpy
-RUN pip install osbot-aws osbot-fast-api osbot-prefect
+RUN pip install osbot-aws osbot-fast-api
 
 COPY --from=public.ecr.aws/awsguru/aws-lambda-adapter:0.8.4 /lambda-adapter /opt/extensions/lambda-adapter
 

osbot_llms/fast_api/routes/Routes__Chat.py

@@ -2,21 +2,18 @@
 import traceback
 
 from fastapi                                                                import Request
-from fastapi.params import Header, Body
-from osbot_prefect.flows.Flow_Events__To__Prefect_Server import Flow_Events__To__Prefect_Server
-from osbot_utils.helpers.Random_Guid import Random_Guid
-from osbot_utils.helpers.flows.Flow import Flow
-from osbot_utils.helpers.flows.decorators.flow import flow
-from osbot_utils.helpers.flows.models.Flow__Config import Flow__Config
-from osbot_utils.utils.Dev import pprint
+from fastapi.params                                                         import Header
+from osbot_utils.helpers.flows.Flow                                         import Flow
+from osbot_utils.helpers.flows.decorators.flow                              import flow
+from osbot_utils.helpers.flows.models.Flow_Run__Config                      import Flow_Run__Config
 from starlette.responses                                                    import StreamingResponse
 from osbot_fast_api.api.Fast_API_Routes                                     import Fast_API_Routes
 from osbot_utils.context_managers.capture_duration                          import capture_duration
 from osbot_llms.OSBot_LLMs__Shared_Objects                                  import osbot_llms__shared_objects
 from osbot_llms.fast_api.routes.Routes__OpenAI                              import Routes__OpenAI
 from osbot_llms.llms.chats.LLM__Chat_Completion__Resolve_Engine             import LLM__Chat_Completion__Resolve_Engine
 from osbot_llms.llms.storage.Chats_Storage__S3_Minio                        import Chats_Storage__S3_Minio
-from osbot_llms.models.LLMs__Chat_Completion import LLMs__Chat_Completion, SWAGGER_EXAMPLE__LLMs__Chat_Completion
+from osbot_llms.models.LLMs__Chat_Completion                                import LLMs__Chat_Completion, SWAGGER_EXAMPLE__LLMs__Chat_Completion
 
 ROUTES_PATHS__CONFIG        = ['/config/status', '/config/version']
 HEADER_NAME__CHAT_ID        = 'osbot-llms-chat-id'
@@ -36,38 +33,35 @@ def execute_llm_request(self, llm_chat_completion):
         return 'no engine'
 
     async def handle_other_llms(self, llm_chat_completion: LLMs__Chat_Completion, request: Request, request_id: str):
-        @flow(flow_config=Flow__Config(log_to_console=True))
+        @flow(flow_config=Flow_Run__Config(log_to_console=True))
         def handle_other_llms__streamer() -> Flow:
             print("in handle_other_llms__streamer")
             print(llm_chat_completion.json())
             return StreamingResponse(self.handle_other_llms__streamer(llm_chat_completion, request, request_id),media_type='text/event-stream"; charset=utf-8')
 
         stream = llm_chat_completion.stream
         if stream:
-            with Flow_Events__To__Prefect_Server():
-                with handle_other_llms__streamer() as _:
-                    _.execute_flow()
-                    return _.flow_return_value
+            with handle_other_llms__streamer() as _:
+                _.execute_flow()
+                return _.flow_return_value
         else:
             return await self.handle_other_llms__no_stream(llm_chat_completion, request, request_id)
 
     async def handle_other_llms__no_stream(self, llm_chat_completion: LLMs__Chat_Completion, request: Request, request_id: str):
-        @flow(flow_config=Flow__Config(log_to_console=True))
+        @flow(flow_config=Flow_Run__Config(log_to_console=True))
         def flow_handle_other_llms__no_stream() -> Flow:
             print("in handle_other_llms__streamer")
             print(llm_chat_completion.json())
             complete_answer =  self.execute_llm_request(llm_chat_completion)
             try:
-                #request_headers = {key: value for key, value in request.headers.items()}
                 llm_chat_completion.llm_answer = complete_answer
             except:
                 pass
             return complete_answer
 
-        with Flow_Events__To__Prefect_Server() :
-            with flow_handle_other_llms__no_stream() as _:
-                _.execute_flow()
-                return _.flow_return_value
+        with flow_handle_other_llms__no_stream() as _:
+            _.execute_flow()
+            return _.flow_return_value
 
 
     async def handle_other_llms__streamer(self, llm_chat_completion: LLMs__Chat_Completion, request: Request,  request_id: str):

pyproject.toml

@@ -1,5 +1,3 @@
-# poetry install didn't work because of pendulum (which is a dependency of prefect)
-# pip install prefect did work
 [tool.poetry]
 name        = "osbot_llms"
 version     = "v0.2.12"
@@ -14,7 +12,6 @@ repository  = "https://github.com/owasp-sbot/OSBot-LLMs"
 python          = "^3.11"
 osbot-aws       = "*"
 osbot-fast-api  = "*"
-osbot-prefect   = "*"
 mangum          = "*"
 uvicorn         = "*"
 httpx           = "*"