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refactor: Add OpenAI assistants API endpoints to memgpt server (#1006)
This commit is contained in:
Sarah Wooders
GitHub
parent
326923b578
commit
9c39e8cefd
@ -45,15 +45,7 @@ Start the server with:
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poetry run uvicorn assistants:app --reload --port 8080
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"""
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interface: QueuingInterface = QueuingInterface()
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server: SyncServer = SyncServer(default_interface=interface)
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# router = APIRouter()
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app = FastAPI()
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user_id = uuid.UUID(MemGPTConfig.load().anon_clientid)
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print(f"User ID: {user_id}")
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router = APIRouter()
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class CreateAssistantRequest(BaseModel):
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@ -167,366 +159,359 @@ class SubmitToolOutputsToRunRequest(BaseModel):
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# TODO: implement mechanism for creating/authenticating users associated with a bearer token
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def setup_openai_assistant_router(server: SyncServer, interface: QueuingInterface):
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# TODO: remove this (when we have user auth)
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user_id = uuid.UUID(MemGPTConfig.load().anon_clientid)
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print(f"User ID: {user_id}")
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# create assistant (MemGPT agent)
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@router.post("/assistants", tags=["assistants"], response_model=OpenAIAssistant)
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def create_assistant(request: CreateAssistantRequest = Body(...)):
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# TODO: create preset
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return OpenAIAssistant(
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id=DEFAULT_PRESET,
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name="default_preset",
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description=request.description,
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created_at=int(datetime.now().timestamp()),
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model=request.model,
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instructions=request.instructions,
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tools=request.tools,
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file_ids=request.file_ids,
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metadata=request.metadata,
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)
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@app.get("/v1/health", tags=["assistant"])
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def get_health():
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return {"status": "healthy"}
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@router.post("/assistants/{assistant_id}/files", tags=["assistants"], response_model=AssistantFile)
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def create_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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request: CreateAssistantFileRequest = Body(...),
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):
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# TODO: add file to assistant
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return AssistantFile(
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id=request.file_id,
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created_at=int(datetime.now().timestamp()),
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assistant_id=assistant_id,
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)
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@router.get("/assistants", tags=["assistants"], response_model=List[OpenAIAssistant])
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def list_assistants(
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limit: int = Query(1000, description="How many assistants to retrieve."),
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order: str = Query("asc", description="Order of assistants to retrieve (either 'asc' or 'desc')."),
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after: str = Query(
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
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),
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before: str = Query(
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
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),
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):
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# TODO: implement list assistants (i.e. list available MemGPT presets)
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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# create assistant (MemGPT agent)
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@app.post("/v1/assistants", tags=["assistants"], response_model=OpenAIAssistant)
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def create_assistant(request: CreateAssistantRequest = Body(...)):
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# TODO: create preset
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return OpenAIAssistant(
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id=DEFAULT_PRESET,
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name="default_preset",
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description=request.description,
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created_at=int(datetime.now().timestamp()),
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model=request.model,
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instructions=request.instructions,
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tools=request.tools,
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file_ids=request.file_ids,
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metadata=request.metadata,
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)
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@router.get("/assistants/{assistant_id}/files", tags=["assistants"], response_model=List[AssistantFile])
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def list_assistant_files(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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limit: int = Query(1000, description="How many files to retrieve."),
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order: str = Query("asc", description="Order of files to retrieve (either 'asc' or 'desc')."),
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after: str = Query(
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
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),
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before: str = Query(
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
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),
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):
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# TODO: list attached data sources to preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.get("/assistants/{assistant_id}", tags=["assistants"], response_model=OpenAIAssistant)
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def retrieve_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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):
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# TODO: get and return preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.post("/v1/assistants/{assistant_id}/files", tags=["assistants"], response_model=AssistantFile)
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def create_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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request: CreateAssistantFileRequest = Body(...),
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):
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# TODO: add file to assistant
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return AssistantFile(
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id=request.file_id,
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created_at=int(datetime.now().timestamp()),
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assistant_id=assistant_id,
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)
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@router.get("/assistants/{assistant_id}/files/{file_id}", tags=["assistants"], response_model=AssistantFile)
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def retrieve_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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file_id: str = Path(..., description="The unique identifier of the file."),
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):
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# TODO: return data source attached to preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.post("/assistants/{assistant_id}", tags=["assistants"], response_model=OpenAIAssistant)
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def modify_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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request: CreateAssistantRequest = Body(...),
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):
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# TODO: modify preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.get("/v1/assistants", tags=["assistants"], response_model=List[OpenAIAssistant])
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def list_assistants(
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limit: int = Query(1000, description="How many assistants to retrieve."),
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order: str = Query("asc", description="Order of assistants to retrieve (either 'asc' or 'desc')."),
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after: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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before: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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):
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# TODO: implement list assistants (i.e. list available MemGPT presets)
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.delete("/assistants/{assistant_id}", tags=["assistants"], response_model=DeleteAssistantResponse)
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def delete_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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):
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# TODO: delete preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.delete("/assistants/{assistant_id}/files/{file_id}", tags=["assistants"], response_model=DeleteAssistantFileResponse)
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def delete_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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file_id: str = Path(..., description="The unique identifier of the file."),
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):
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# TODO: delete source on preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.get("/v1/assistants/{assistant_id}/files", tags=["assistants"], response_model=List[AssistantFile])
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def list_assistant_files(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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limit: int = Query(1000, description="How many files to retrieve."),
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order: str = Query("asc", description="Order of files to retrieve (either 'asc' or 'desc')."),
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after: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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before: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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):
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# TODO: list attached data sources to preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.post("/threads", tags=["threads"], response_model=OpenAIThread)
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def create_thread(request: CreateThreadRequest = Body(...)):
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# TODO: use requests.description and requests.metadata fields
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# TODO: handle requests.file_ids and requests.tools
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# TODO: eventually allow request to override embedding/llm model
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print("Create thread/agent", request)
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# create a memgpt agent
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agent_state = server.create_agent(
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user_id=user_id,
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agent_config={
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"user_id": user_id,
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},
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)
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# TODO: insert messages into recall memory
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return OpenAIThread(
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id=str(agent_state.id),
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created_at=int(agent_state.created_at.timestamp()),
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)
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@app.get("/v1/assistants/{assistant_id}", tags=["assistants"], response_model=OpenAIAssistant)
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def retrieve_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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):
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# TODO: get and return preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.get("/threads/{thread_id}", tags=["threads"], response_model=OpenAIThread)
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def retrieve_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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):
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agent = server.get_agent(uuid.UUID(thread_id))
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return OpenAIThread(
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id=str(agent.id),
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created_at=int(agent.created_at.timestamp()),
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)
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@router.get("/threads/{thread_id}", tags=["threads"], response_model=OpenAIThread)
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def modify_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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request: ModifyThreadRequest = Body(...),
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):
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# TODO: add agent metadata so this can be modified
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.get("/v1/assistants/{assistant_id}/files/{file_id}", tags=["assistants"], response_model=AssistantFile)
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def retrieve_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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file_id: str = Path(..., description="The unique identifier of the file."),
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):
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# TODO: return data source attached to preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.delete("/threads/{thread_id}", tags=["threads"], response_model=DeleteThreadResponse)
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def delete_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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):
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# TODO: delete agent
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@router.post("/threads/{thread_id}/messages", tags=["messages"], response_model=OpenAIMessage)
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def create_message(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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request: CreateMessageRequest = Body(...),
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):
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agent_id = uuid.UUID(thread_id)
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# create message object
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message = Message(
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user_id=user_id,
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agent_id=agent_id,
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role=request.role,
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text=request.content,
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)
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agent = server._get_or_load_agent(user_id=user_id, agent_id=agent_id)
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# add message to agent
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agent._append_to_messages([message])
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@app.post("/v1/assistants/{assistant_id}", tags=["assistants"], response_model=OpenAIAssistant)
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def modify_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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request: CreateAssistantRequest = Body(...),
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):
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# TODO: modify preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.delete("/v1/assistants/{assistant_id}", tags=["assistants"], response_model=DeleteAssistantResponse)
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def delete_assistant(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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):
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# TODO: delete preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.delete("/v1/assistants/{assistant_id}/files/{file_id}", tags=["assistants"], response_model=DeleteAssistantFileResponse)
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def delete_assistant_file(
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assistant_id: str = Path(..., description="The unique identifier of the assistant."),
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file_id: str = Path(..., description="The unique identifier of the file."),
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):
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# TODO: delete source on preset
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.post("/v1/threads", tags=["assistants"], response_model=OpenAIThread)
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def create_thread(request: CreateThreadRequest = Body(...)):
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# TODO: use requests.description and requests.metadata fields
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# TODO: handle requests.file_ids and requests.tools
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# TODO: eventually allow request to override embedding/llm model
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print("Create thread/agent", request)
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# create a memgpt agent
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agent_state = server.create_agent(
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user_id=user_id,
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agent_config={
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"user_id": user_id,
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},
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)
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# TODO: insert messages into recall memory
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return OpenAIThread(
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id=str(agent_state.id),
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created_at=int(agent_state.created_at.timestamp()),
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)
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@app.get("/v1/threads/{thread_id}", tags=["assistants"], response_model=OpenAIThread)
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def retrieve_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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):
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agent = server.get_agent(uuid.UUID(thread_id))
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return OpenAIThread(
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id=str(agent.id),
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created_at=int(agent.created_at.timestamp()),
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)
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@app.get("/v1/threads/{thread_id}", tags=["assistants"], response_model=OpenAIThread)
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def modify_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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request: ModifyThreadRequest = Body(...),
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):
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# TODO: add agent metadata so this can be modified
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.delete("/v1/threads/{thread_id}", tags=["assistants"], response_model=DeleteThreadResponse)
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def delete_thread(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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):
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# TODO: delete agent
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raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
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@app.post("/v1/threads/{thread_id}/messages", tags=["assistants"], response_model=OpenAIMessage)
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def create_message(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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request: CreateMessageRequest = Body(...),
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):
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agent_id = uuid.UUID(thread_id)
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# create message object
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message = Message(
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user_id=user_id,
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agent_id=agent_id,
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role=request.role,
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text=request.content,
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)
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agent = server._get_or_load_agent(user_id=user_id, agent_id=agent_id)
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# add message to agent
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agent._append_to_messages([message])
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openai_message = OpenAIMessage(
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id=str(message.id),
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created_at=int(message.created_at.timestamp()),
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content=[Text(text=message.text)],
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role=message.role,
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thread_id=str(message.agent_id),
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assistant_id=DEFAULT_PRESET, # TODO: update this
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# file_ids=message.file_ids,
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# metadata=message.metadata,
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)
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return openai_message
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@app.get("/v1/threads/{thread_id}/messages", tags=["assistants"], response_model=ListMessagesResponse)
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def list_messages(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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limit: int = Query(1000, description="How many messages to retrieve."),
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order: str = Query("asc", description="Order of messages to retrieve (either 'asc' or 'desc')."),
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after: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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before: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
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):
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after_uuid = uuid.UUID(after) if before else None
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before_uuid = uuid.UUID(before) if before else None
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agent_id = uuid.UUID(thread_id)
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reverse = True if (order == "desc") else False
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cursor, json_messages = server.get_agent_recall_cursor(
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user_id=user_id,
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agent_id=agent_id,
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limit=limit,
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after=after_uuid,
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before=before_uuid,
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order_by="created_at",
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reverse=reverse,
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)
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print(json_messages[0]["text"])
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# convert to openai style messages
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openai_messages = [
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OpenAIMessage(
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id=str(message["id"]),
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created_at=int(message["created_at"].timestamp()),
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content=[Text(text=message["text"])],
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role=message["role"],
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thread_id=str(message["agent_id"]),
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assistant_id=DEFAULT_PRESET # TODO: update this
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openai_message = OpenAIMessage(
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id=str(message.id),
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created_at=int(message.created_at.timestamp()),
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content=[Text(text=message.text)],
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role=message.role,
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thread_id=str(message.agent_id),
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assistant_id=DEFAULT_PRESET, # TODO: update this
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# file_ids=message.file_ids,
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# metadata=message.metadata,
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)
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for message in json_messages
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]
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print("MESSAGES", openai_messages)
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# TODO: cast back to message objects
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return ListMessagesResponse(messages=openai_messages)
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return openai_message
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@router.get("/threads/{thread_id}/messages", tags=["messages"], response_model=ListMessagesResponse)
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def list_messages(
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thread_id: str = Path(..., description="The unique identifier of the thread."),
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limit: int = Query(1000, description="How many messages to retrieve."),
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order: str = Query("asc", description="Order of messages to retrieve (either 'asc' or 'desc')."),
|
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after: str = Query(
|
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
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),
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before: str = Query(
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None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
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),
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):
|
||||
after_uuid = uuid.UUID(after) if before else None
|
||||
before_uuid = uuid.UUID(before) if before else None
|
||||
agent_id = uuid.UUID(thread_id)
|
||||
reverse = True if (order == "desc") else False
|
||||
cursor, json_messages = server.get_agent_recall_cursor(
|
||||
user_id=user_id,
|
||||
agent_id=agent_id,
|
||||
limit=limit,
|
||||
after=after_uuid,
|
||||
before=before_uuid,
|
||||
order_by="created_at",
|
||||
reverse=reverse,
|
||||
)
|
||||
print(json_messages[0]["text"])
|
||||
# convert to openai style messages
|
||||
openai_messages = [
|
||||
OpenAIMessage(
|
||||
id=str(message["id"]),
|
||||
created_at=int(message["created_at"].timestamp()),
|
||||
content=[Text(text=message["text"])],
|
||||
role=message["role"],
|
||||
thread_id=str(message["agent_id"]),
|
||||
assistant_id=DEFAULT_PRESET # TODO: update this
|
||||
# file_ids=message.file_ids,
|
||||
# metadata=message.metadata,
|
||||
)
|
||||
for message in json_messages
|
||||
]
|
||||
print("MESSAGES", openai_messages)
|
||||
# TODO: cast back to message objects
|
||||
return ListMessagesResponse(messages=openai_messages)
|
||||
|
||||
app.get("/v1/threads/{thread_id}/messages/{message_id}", tags=["assistants"], response_model=OpenAIMessage)
|
||||
router.get("/threads/{thread_id}/messages/{message_id}", tags=["messages"], response_model=OpenAIMessage)
|
||||
|
||||
def retrieve_message(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
):
|
||||
message_id = uuid.UUID(message_id)
|
||||
agent_id = uuid.UUID(thread_id)
|
||||
message = server.get_agent_message(agent_id, message_id)
|
||||
return OpenAIMessage(
|
||||
id=str(message.id),
|
||||
created_at=int(message.created_at.timestamp()),
|
||||
content=[Text(text=message.text)],
|
||||
role=message.role,
|
||||
thread_id=str(message.agent_id),
|
||||
assistant_id=DEFAULT_PRESET, # TODO: update this
|
||||
# file_ids=message.file_ids,
|
||||
# metadata=message.metadata,
|
||||
)
|
||||
|
||||
def retrieve_message(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
):
|
||||
message_id = uuid.UUID(message_id)
|
||||
agent_id = uuid.UUID(thread_id)
|
||||
message = server.get_agent_message(agent_id, message_id)
|
||||
return OpenAIMessage(
|
||||
id=str(message.id),
|
||||
created_at=int(message.created_at.timestamp()),
|
||||
content=[Text(text=message.text)],
|
||||
role=message.role,
|
||||
thread_id=str(message.agent_id),
|
||||
assistant_id=DEFAULT_PRESET, # TODO: update this
|
||||
# file_ids=message.file_ids,
|
||||
# metadata=message.metadata,
|
||||
)
|
||||
@router.get("/threads/{thread_id}/messages/{message_id}/files/{file_id}", tags=["messages"], response_model=MessageFile)
|
||||
def retrieve_message_file(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
file_id: str = Path(..., description="The unique identifier of the file."),
|
||||
):
|
||||
# TODO: implement?
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@router.post("/threads/{thread_id}/messages/{message_id}", tags=["messages"], response_model=OpenAIMessage)
|
||||
def modify_message(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
request: ModifyMessageRequest = Body(...),
|
||||
):
|
||||
# TODO: add metada field to message so this can be modified
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@app.get("/v1/threads/{thread_id}/messages/{message_id}/files/{file_id}", tags=["assistants"], response_model=MessageFile)
|
||||
def retrieve_message_file(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
file_id: str = Path(..., description="The unique identifier of the file."),
|
||||
):
|
||||
# TODO: implement?
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
@router.post("/threads/{thread_id}/runs", tags=["runs"], response_model=OpenAIRun)
|
||||
def create_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
request: CreateRunRequest = Body(...),
|
||||
):
|
||||
# TODO: add request.instructions as a message?
|
||||
agent_id = uuid.UUID(thread_id)
|
||||
# TODO: override preset of agent with request.assistant_id
|
||||
agent = server._get_or_load_agent(user_id=user_id, agent_id=agent_id)
|
||||
agent.step(user_message=None) # already has messages added
|
||||
run_id = str(uuid.uuid4())
|
||||
create_time = int(datetime.now().timestamp())
|
||||
return OpenAIRun(
|
||||
id=run_id,
|
||||
created_at=create_time,
|
||||
thread_id=str(agent_id),
|
||||
assistant_id=DEFAULT_PRESET, # TODO: update this
|
||||
status="completed", # TODO: eventaully allow offline execution
|
||||
expires_at=create_time,
|
||||
model=agent.agent_state.llm_config.model,
|
||||
instructions=request.instructions,
|
||||
)
|
||||
|
||||
@router.post("/threads/runs", tags=["runs"], response_model=OpenAIRun)
|
||||
def create_thread_and_run(
|
||||
request: CreateThreadRunRequest = Body(...),
|
||||
):
|
||||
# TODO: add a bunch of messages and execute
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@app.post("/v1/threads/{thread_id}/messages/{message_id}", tags=["assistants"], response_model=OpenAIMessage)
|
||||
def modify_message(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
message_id: str = Path(..., description="The unique identifier of the message."),
|
||||
request: ModifyMessageRequest = Body(...),
|
||||
):
|
||||
# TODO: add metada field to message so this can be modified
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
@router.get("/threads/{thread_id}/runs", tags=["runs"], response_model=List[OpenAIRun])
|
||||
def list_runs(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
limit: int = Query(1000, description="How many runs to retrieve."),
|
||||
order: str = Query("asc", description="Order of runs to retrieve (either 'asc' or 'desc')."),
|
||||
after: str = Query(
|
||||
None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
||||
),
|
||||
before: str = Query(
|
||||
None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
||||
),
|
||||
):
|
||||
# TODO: store run information in a DB so it can be returned here
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@router.get("/threads/{thread_id}/runs/{run_id}/steps", tags=["runs"], response_model=List[OpenAIRunStep])
|
||||
def list_run_steps(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
limit: int = Query(1000, description="How many run steps to retrieve."),
|
||||
order: str = Query("asc", description="Order of run steps to retrieve (either 'asc' or 'desc')."),
|
||||
after: str = Query(
|
||||
None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
||||
),
|
||||
before: str = Query(
|
||||
None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."
|
||||
),
|
||||
):
|
||||
# TODO: store run information in a DB so it can be returned here
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@app.post("/v1/threads/{thread_id}/runs", tags=["assistants"], response_model=OpenAIRun)
|
||||
def create_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
request: CreateRunRequest = Body(...),
|
||||
):
|
||||
# TODO: add request.instructions as a message?
|
||||
agent_id = uuid.UUID(thread_id)
|
||||
# TODO: override preset of agent with request.assistant_id
|
||||
agent = server._get_or_load_agent(user_id=user_id, agent_id=agent_id)
|
||||
agent.step(user_message=None) # already has messages added
|
||||
run_id = str(uuid.uuid4())
|
||||
create_time = int(datetime.now().timestamp())
|
||||
return OpenAIRun(
|
||||
id=run_id,
|
||||
created_at=create_time,
|
||||
thread_id=str(agent_id),
|
||||
assistant_id=DEFAULT_PRESET, # TODO: update this
|
||||
status="completed", # TODO: eventaully allow offline execution
|
||||
expires_at=create_time,
|
||||
model=agent.agent_state.llm_config.model,
|
||||
instructions=request.instructions,
|
||||
)
|
||||
@router.get("/threads/{thread_id}/runs/{run_id}", tags=["runs"], response_model=OpenAIRun)
|
||||
def retrieve_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@router.get("/threads/{thread_id}/runs/{run_id}/steps/{step_id}", tags=["runs"], response_model=OpenAIRunStep)
|
||||
def retrieve_run_step(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
step_id: str = Path(..., description="The unique identifier of the run step."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@app.post("/v1/threads/runs", tags=["assistants"], response_model=OpenAIRun)
|
||||
def create_thread_and_run(
|
||||
request: CreateThreadRunRequest = Body(...),
|
||||
):
|
||||
# TODO: add a bunch of messages and execute
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
@router.post("/threads/{thread_id}/runs/{run_id}", tags=["runs"], response_model=OpenAIRun)
|
||||
def modify_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
request: ModifyRunRequest = Body(...),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@router.post("/threads/{thread_id}/runs/{run_id}/submit_tool_outputs", tags=["runs"], response_model=OpenAIRun)
|
||||
def submit_tool_outputs_to_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
request: SubmitToolOutputsToRunRequest = Body(...),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
@app.get("/v1/threads/{thread_id}/runs", tags=["assistants"], response_model=List[OpenAIRun])
|
||||
def list_runs(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
limit: int = Query(1000, description="How many runs to retrieve."),
|
||||
order: str = Query("asc", description="Order of runs to retrieve (either 'asc' or 'desc')."),
|
||||
after: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
|
||||
before: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
|
||||
):
|
||||
# TODO: store run information in a DB so it can be returned here
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
@router.post("/threads/{thread_id}/runs/{run_id}/cancel", tags=["runs"], response_model=OpenAIRun)
|
||||
def cancel_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.get("/v1/threads/{thread_id}/runs/{run_id}/steps", tags=["assistants"], response_model=List[OpenAIRunStep])
|
||||
def list_run_steps(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
limit: int = Query(1000, description="How many run steps to retrieve."),
|
||||
order: str = Query("asc", description="Order of run steps to retrieve (either 'asc' or 'desc')."),
|
||||
after: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
|
||||
before: str = Query(None, description="A cursor for use in pagination. `after` is an object ID that defines your place in the list."),
|
||||
):
|
||||
# TODO: store run information in a DB so it can be returned here
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.get("/v1/threads/{thread_id}/runs/{run_id}", tags=["assistants"], response_model=OpenAIRun)
|
||||
def retrieve_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.get("/v1/threads/{thread_id}/runs/{run_id}/steps/{step_id}", tags=["assistants"], response_model=OpenAIRunStep)
|
||||
def retrieve_run_step(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
step_id: str = Path(..., description="The unique identifier of the run step."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.post("/v1/threads/{thread_id}/runs/{run_id}", tags=["assistants"], response_model=OpenAIRun)
|
||||
def modify_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
request: ModifyRunRequest = Body(...),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.post("/v1/threads/{thread_id}/runs/{run_id}/submit_tool_outputs", tags=["assistants"], response_model=OpenAIRun)
|
||||
def submit_tool_outputs_to_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
request: SubmitToolOutputsToRunRequest = Body(...),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
|
||||
|
||||
@app.post("/v1/threads/{thread_id}/runs/{run_id}/cancel", tags=["assistants"], response_model=OpenAIRun)
|
||||
def cancel_run(
|
||||
thread_id: str = Path(..., description="The unique identifier of the thread."),
|
||||
run_id: str = Path(..., description="The unique identifier of the run."),
|
||||
):
|
||||
raise HTTPException(status_code=404, detail="Not yet implemented (coming soon)")
|
||||
return router
|
||||
|
||||
@ -16,6 +16,7 @@ from memgpt.server.rest_api.config.index import setup_config_index_router
|
||||
from memgpt.server.rest_api.humans.index import setup_humans_index_router
|
||||
from memgpt.server.rest_api.personas.index import setup_personas_index_router
|
||||
from memgpt.server.rest_api.models.index import setup_models_index_router
|
||||
from memgpt.server.rest_api.openai_assistants.assistants import setup_openai_assistant_router
|
||||
from memgpt.server.server import SyncServer
|
||||
from memgpt.server.rest_api.interface import QueuingInterface
|
||||
from memgpt.server.rest_api.static_files import mount_static_files
|
||||
@ -33,6 +34,7 @@ server: SyncServer = SyncServer(default_interface=interface)
|
||||
|
||||
|
||||
API_PREFIX = "/api"
|
||||
OPENAI_API_PREFIX = "/v1"
|
||||
|
||||
CORS_ORIGINS = [
|
||||
"http://localhost:4200",
|
||||
@ -65,6 +67,8 @@ app.include_router(setup_personas_index_router(server, interface), prefix=API_PR
|
||||
app.include_router(setup_models_index_router(server, interface), prefix=API_PREFIX)
|
||||
# /api/config endpoints
|
||||
app.include_router(setup_config_index_router(server, interface), prefix=API_PREFIX)
|
||||
# /v1/assistants endpoints
|
||||
app.include_router(setup_openai_assistant_router(server, interface), prefix=OPENAI_API_PREFIX)
|
||||
# / static files
|
||||
mount_static_files(app)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ from fastapi.testclient import TestClient
|
||||
import uuid
|
||||
|
||||
from memgpt.server.server import SyncServer
|
||||
from memgpt.server.rest_api.openai_assistants.assistants import app
|
||||
from memgpt.server.rest_api.server import app
|
||||
from memgpt.constants import DEFAULT_PRESET
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user