diff --git a/README.md b/README.md index 1879dc8640a4cf5ad2f97a6f573c1870ebcedcd1..42189e3c62dea36cbebb59219b0b4a4ad9eda0ca 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,11 @@ # LynxKite 2024 -This is an experimental rewrite of [LynxKite](https://github.com/lynxkite/lynxkite). -It is not compatible with the original LynxKite. The primary goals of this rewrite are: -- Target GPU clusters instead of Hadoop clusters. - We use Python instead of Scala, RAPIDS instead of Apache Spark. -- More extensible backend. Make it easy to add new LynxKite boxes. - Make it easy to use our frontend for other purposes, configuring and executing other pipelines. +This is an experimental rewrite of [LynxKite](https://github.com/lynxkite/lynxkite). It is not compatible with the +original LynxKite. The primary goals of this rewrite are: + +- Target GPU clusters instead of Hadoop clusters. We use Python instead of Scala, RAPIDS instead of Apache Spark. +- More extensible backend. Make it easy to add new LynxKite boxes. Make it easy to use our frontend for other purposes, + configuring and executing other pipelines. Current status: **PROTOTYPE** @@ -15,6 +15,7 @@ To run the backend: ```bash pip install -r requirements.txt +PYTHONPATH=. pydantic2ts --module server.workspace --output ./web/src/apiTypes.ts uvicorn server.main:app --reload ``` diff --git a/requirements.txt b/requirements.txt index 27039bf01b470b6a7836abfdf116ad67da66cf66..81cbc1213a59657f4bf75d1478c5edb1679fd074 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,6 +4,7 @@ networkx numpy orjson pandas +pydantic-to-typescript scipy uvicorn[standard] pycrdt diff --git a/server/crdt.py b/server/crdt.py index 66c31751220a165143cfee43b92e027031e86686..9eca7fdc79b10b4bce17c8b836a3e6f428ca4671 100644 --- a/server/crdt.py +++ b/server/crdt.py @@ -1,42 +1,57 @@ -'''CRDT is used to synchronize workspace state for backend and frontend(s).''' +"""CRDT is used to synchronize workspace state for backend and frontend(s).""" + import asyncio import contextlib +import enum import fastapi import os.path import pycrdt import pycrdt_websocket - import pycrdt_websocket.ystore +import uvicorn +import builtins router = fastapi.APIRouter() + def ws_exception_handler(exception, log): - print('exception', exception) - log.exception(exception) + if isinstance(exception, builtins.ExceptionGroup): + for ex in exception.exceptions: + if not isinstance(ex, uvicorn.protocols.utils.ClientDisconnected): + log.exception(ex) + else: + log.exception(exception) return True + class WebsocketServer(pycrdt_websocket.WebsocketServer): async def init_room(self, name): - ystore = pycrdt_websocket.ystore.FileYStore(f'crdt_data/{name}.crdt') + ystore = pycrdt_websocket.ystore.FileYStore(f"crdt_data/{name}.crdt") ydoc = pycrdt.Doc() - ydoc['workspace'] = ws = pycrdt.Map() + ydoc["workspace"] = ws = pycrdt.Map() # Replay updates from the store. try: - for update, timestamp in [(item[0], item[-1]) async for item in ystore.read()]: + for update, timestamp in [ + (item[0], item[-1]) async for item in ystore.read() + ]: ydoc.apply_update(update) except pycrdt_websocket.ystore.YDocNotFound: pass - if 'nodes' not in ws: - ws['nodes'] = pycrdt.Array() - if 'edges' not in ws: - ws['edges'] = pycrdt.Array() - if 'env' not in ws: - ws['env'] = 'unset' + if "nodes" not in ws: + ws["nodes"] = pycrdt.Array() + if "edges" not in ws: + ws["edges"] = pycrdt.Array() + if "env" not in ws: + ws["env"] = "unset" try_to_load_workspace(ws, name) - room = pycrdt_websocket.YRoom(ystore=ystore, ydoc=ydoc) + room = pycrdt_websocket.YRoom( + ystore=ystore, ydoc=ydoc, exception_handler=ws_exception_handler + ) room.ws = ws + def on_change(changes): - asyncio.create_task(workspace_changed(changes, ws)) + asyncio.create_task(workspace_changed(name, changes, ws)) + ws.observe_deep(on_change) return room @@ -47,19 +62,21 @@ class WebsocketServer(pycrdt_websocket.WebsocketServer): await self.start_room(room) return room -websocket_server = WebsocketServer(exception_handler=ws_exception_handler, auto_clean_rooms=False) -asgi_server = pycrdt_websocket.ASGIServer(websocket_server) last_ws_input = None + + def clean_input(ws_pyd): for node in ws_pyd.nodes: node.data.display = None + node.data.error = None node.position.x = 0 node.position.y = 0 if node.model_extra: for key in list(node.model_extra.keys()): delattr(node, key) + def crdt_update(crdt_obj, python_obj, boxes=set()): if isinstance(python_obj, dict): for key, value in python_obj.items(): @@ -73,6 +90,8 @@ def crdt_update(crdt_obj, python_obj, boxes=set()): if crdt_obj.get(key) is None: crdt_obj[key] = pycrdt.Array() crdt_update(crdt_obj[key], value, boxes) + elif isinstance(value, enum.Enum): + crdt_obj[key] = str(value) else: crdt_obj[key] = value elif isinstance(python_obj, list): @@ -91,41 +110,82 @@ def crdt_update(crdt_obj, python_obj, boxes=set()): else: crdt_obj[i] = value else: - raise ValueError('Invalid type:', python_obj) + raise ValueError("Invalid type:", python_obj) def try_to_load_workspace(ws, name): from . import workspace - json_path = f'data/{name}' + + json_path = f"data/{name}" if os.path.exists(json_path): ws_pyd = workspace.load(json_path) - crdt_update(ws, ws_pyd.model_dump(), boxes={'display'}) + crdt_update(ws, ws_pyd.model_dump(), boxes={"display"}) + -async def workspace_changed(e, ws_crdt): - global last_ws_input +last_known_versions = {} +delayed_executions = {} + + +async def workspace_changed(name, changes, ws_crdt): from . import workspace + ws_pyd = workspace.Workspace.model_validate(ws_crdt.to_py()) + # Do not trigger execution for superficial changes. + # This is a quick solution until we build proper caching. clean_input(ws_pyd) - if ws_pyd == last_ws_input: + if ws_pyd == last_known_versions.get(name): return - last_ws_input = ws_pyd.model_copy(deep=True) + last_known_versions[name] = ws_pyd.model_copy(deep=True) + # Frontend changes that result from typing are delayed to avoid + # rerunning the workspace for every keystroke. + if name in delayed_executions: + delayed_executions[name].cancel() + delay = min( + getattr(change, "keys", {}).get("__execution_delay", {}).get("newValue", 0) + for change in changes + ) + if delay: + task = asyncio.create_task(execute(ws_crdt, ws_pyd, delay)) + delayed_executions[name] = task + else: + await execute(ws_crdt, ws_pyd) + + +async def execute(ws_crdt, ws_pyd, delay=0): + from . import workspace + + if delay: + try: + await asyncio.sleep(delay) + except asyncio.CancelledError: + return await workspace.execute(ws_pyd) - for nc, np in zip(ws_crdt['nodes'], ws_pyd.nodes): - if 'data' not in nc: - nc['data'] = pycrdt.Map() - # Display is added as an opaque Box. - nc['data']['display'] = np.data.display - nc['data']['error'] = np.data.error + with ws_crdt.doc.transaction(): + for nc, np in zip(ws_crdt["nodes"], ws_pyd.nodes): + if "data" not in nc: + nc["data"] = pycrdt.Map() + # Display is added as an opaque Box. + nc["data"]["display"] = np.data.display + nc["data"]["error"] = np.data.error + @contextlib.asynccontextmanager async def lifespan(app): + global websocket_server + websocket_server = WebsocketServer( + auto_clean_rooms=False, + ) async with websocket_server: yield + print("closing websocket server") + def sanitize_path(path): return os.path.relpath(os.path.normpath(os.path.join("/", path)), "/") + @router.websocket("/ws/crdt/{room_name}") async def crdt_websocket(websocket: fastapi.WebSocket, room_name: str): room_name = sanitize_path(room_name) - await asgi_server({'path': room_name}, websocket._receive, websocket._send) + server = pycrdt_websocket.ASGIServer(websocket_server) + await server({"path": room_name}, websocket._receive, websocket._send) diff --git a/server/executors/one_by_one.py b/server/executors/one_by_one.py index 704f8ad3e6ca5b40c75c2af02741ea1b006464b3..c3c0dcb787a0bd708d10db3ccaea73910e1ff312 100644 --- a/server/executors/one_by_one.py +++ b/server/executors/one_by_one.py @@ -7,142 +7,166 @@ import traceback import inspect import typing + class Context(ops.BaseConfig): - '''Passed to operation functions as "_ctx" if they have such a parameter.''' - node: workspace.WorkspaceNode - last_result: typing.Any = None + """Passed to operation functions as "_ctx" if they have such a parameter.""" + + node: workspace.WorkspaceNode + last_result: typing.Any = None + class Output(ops.BaseConfig): - '''Return this to send values to specific outputs of a node.''' - output_handle: str - value: dict + """Return this to send values to specific outputs of a node.""" + + output_handle: str + value: dict def df_to_list(df): - return df.to_dict(orient='records') + return df.to_dict(orient="records") + def has_ctx(op): - sig = inspect.signature(op.func) - return '_ctx' in sig.parameters + sig = inspect.signature(op.func) + return "_ctx" in sig.parameters + CACHES = {} + def register(env: str, cache: bool = True): - '''Registers the one-by-one executor.''' - if cache: - CACHES[env] = {} - cache = CACHES[env] - else: - cache = None - ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache) + """Registers the one-by-one executor.""" + if cache: + CACHES[env] = {} + cache = CACHES[env] + else: + cache = None + ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache) + def get_stages(ws, catalog): - '''Inputs on top/bottom are batch inputs. We decompose the graph into a DAG of components along these edges.''' - nodes = {n.id: n for n in ws.nodes} - batch_inputs = {} - inputs = {} - for edge in ws.edges: - inputs.setdefault(edge.target, []).append(edge.source) - node = nodes[edge.target] - op = catalog[node.data.title] - i = op.inputs[edge.targetHandle] - if i.position in 'top or bottom': - batch_inputs.setdefault(edge.target, []).append(edge.source) - stages = [] - for bt, bss in batch_inputs.items(): - upstream = set(bss) - new = set(bss) - while new: - n = new.pop() - for i in inputs.get(n, []): - if i not in upstream: - upstream.add(i) - new.add(i) - stages.append(upstream) - stages.sort(key=lambda s: len(s)) - stages.append(set(nodes)) - return stages + """Inputs on top/bottom are batch inputs. We decompose the graph into a DAG of components along these edges.""" + nodes = {n.id: n for n in ws.nodes} + batch_inputs = {} + inputs = {} + for edge in ws.edges: + inputs.setdefault(edge.target, []).append(edge.source) + node = nodes[edge.target] + op = catalog[node.data.title] + i = op.inputs[edge.targetHandle] + if i.position in "top or bottom": + batch_inputs.setdefault(edge.target, []).append(edge.source) + stages = [] + for bt, bss in batch_inputs.items(): + upstream = set(bss) + new = set(bss) + while new: + n = new.pop() + for i in inputs.get(n, []): + if i not in upstream: + upstream.add(i) + new.add(i) + stages.append(upstream) + stages.sort(key=lambda s: len(s)) + stages.append(set(nodes)) + return stages def _default_serializer(obj): - if isinstance(obj, pydantic.BaseModel): - return obj.dict() - return {"__nonserializable__": id(obj)} + if isinstance(obj, pydantic.BaseModel): + return obj.dict() + return {"__nonserializable__": id(obj)} + def make_cache_key(obj): - return orjson.dumps(obj, default=_default_serializer) + return orjson.dumps(obj, default=_default_serializer) + EXECUTOR_OUTPUT_CACHE = {} + async def await_if_needed(obj): - if inspect.isawaitable(obj): - return await obj - return obj + if inspect.isawaitable(obj): + return await obj + return obj + async def execute(ws, catalog, cache=None): - nodes = {n.id: n for n in ws.nodes} - contexts = {n.id: Context(node=n) for n in ws.nodes} - edges = {n.id: [] for n in ws.nodes} - for e in ws.edges: - edges[e.source].append(e) - tasks = {} - NO_INPUT = object() # Marker for initial tasks. - for node in ws.nodes: - node.data.error = None - op = catalog[node.data.title] - # Start tasks for nodes that have no non-batch inputs. - if all([i.position in 'top or bottom' for i in op.inputs.values()]): - tasks[node.id] = [NO_INPUT] - batch_inputs = {} - # Run the rest until we run out of tasks. - stages = get_stages(ws, catalog) - for stage in stages: - next_stage = {} - while tasks: - n, ts = tasks.popitem() - if n not in stage: - next_stage.setdefault(n, []).extend(ts) - continue - node = nodes[n] - data = node.data - op = catalog[data.title] - params = {**data.params} - if has_ctx(op): - params['_ctx'] = contexts[node.id] - results = [] - for task in ts: - try: - inputs = [ - batch_inputs[(n, i.name)] if i.position in 'top or bottom' else task - for i in op.inputs.values()] - if cache is not None: - key = make_cache_key((inputs, params)) - if key not in cache: - cache[key] = await await_if_needed(op(*inputs, **params)) - result = cache[key] - else: - result = await await_if_needed(op(*inputs, **params)) - except Exception as e: - traceback.print_exc() - data.error = str(e) - break - contexts[node.id].last_result = result - # Returned lists and DataFrames are considered multiple tasks. - if isinstance(result, pd.DataFrame): - result = df_to_list(result) - elif not isinstance(result, list): - result = [result] - results.extend(result) - else: # Finished all tasks without errors. - if op.type == 'visualization' or op.type == 'table_view' or op.type == 'image': - data.display = results[0] - for edge in edges[node.id]: - t = nodes[edge.target] - op = catalog[t.data.title] - i = op.inputs[edge.targetHandle] - if i.position in 'top or bottom': - batch_inputs.setdefault((edge.target, edge.targetHandle), []).extend(results) - else: - tasks.setdefault(edge.target, []).extend(results) - tasks = next_stage - return contexts + nodes = {n.id: n for n in ws.nodes} + contexts = {n.id: Context(node=n) for n in ws.nodes} + edges = {n.id: [] for n in ws.nodes} + for e in ws.edges: + edges[e.source].append(e) + tasks = {} + NO_INPUT = object() # Marker for initial tasks. + for node in ws.nodes: + node.data.error = None + op = catalog.get(node.data.title) + if op is None: + node.data.error = f'Operation "{node.data.title}" not found.' + continue + # Start tasks for nodes that have no non-batch inputs. + if all([i.position in "top or bottom" for i in op.inputs.values()]): + tasks[node.id] = [NO_INPUT] + batch_inputs = {} + # Run the rest until we run out of tasks. + stages = get_stages(ws, catalog) + for stage in stages: + next_stage = {} + while tasks: + n, ts = tasks.popitem() + if n not in stage: + next_stage.setdefault(n, []).extend(ts) + continue + node = nodes[n] + data = node.data + op = catalog[data.title] + params = {**data.params} + if has_ctx(op): + params["_ctx"] = contexts[node.id] + results = [] + for task in ts: + try: + inputs = [ + batch_inputs[(n, i.name)] + if i.position in "top or bottom" + else task + for i in op.inputs.values() + ] + if cache is not None: + key = make_cache_key((inputs, params)) + if key not in cache: + cache[key] = await await_if_needed(op(*inputs, **params)) + result = cache[key] + else: + result = await await_if_needed(op(*inputs, **params)) + except Exception as e: + traceback.print_exc() + data.error = str(e) + break + contexts[node.id].last_result = result + # Returned lists and DataFrames are considered multiple tasks. + if isinstance(result, pd.DataFrame): + result = df_to_list(result) + elif not isinstance(result, list): + result = [result] + results.extend(result) + else: # Finished all tasks without errors. + if ( + op.type == "visualization" + or op.type == "table_view" + or op.type == "image" + ): + data.display = results[0] + for edge in edges[node.id]: + t = nodes[edge.target] + op = catalog[t.data.title] + i = op.inputs[edge.targetHandle] + if i.position in "top or bottom": + batch_inputs.setdefault( + (edge.target, edge.targetHandle), [] + ).extend(results) + else: + tasks.setdefault(edge.target, []).extend(results) + tasks = next_stage + return contexts diff --git a/server/llm_ops.py b/server/llm_ops.py index 08007d71e4fefc348b7237c251488d6d3ae1e311..4da118014928480d19f3837199f34181b5d6a198 100644 --- a/server/llm_ops.py +++ b/server/llm_ops.py @@ -1,4 +1,5 @@ -'''For specifying an LLM agent logic flow.''' +"""For specifying an LLM agent logic flow.""" + from . import ops import chromadb import enum @@ -14,177 +15,205 @@ embedding_client = openai.OpenAI(base_url="http://localhost:7997/") jinja = jinja2.Environment() chroma_client = chromadb.Client() LLM_CACHE = {} -ENV = 'LLM logic' +ENV = "LLM logic" one_by_one.register(ENV) op = ops.op_registration(ENV) + def chat(*args, **kwargs): - key = json.dumps({'method': 'chat', 'args': args, 'kwargs': kwargs}) - if key not in LLM_CACHE: - completion = chat_client.chat.completions.create(*args, **kwargs) - LLM_CACHE[key] = [c.message.content for c in completion.choices] - return LLM_CACHE[key] + key = json.dumps({"method": "chat", "args": args, "kwargs": kwargs}) + if key not in LLM_CACHE: + completion = chat_client.chat.completions.create(*args, **kwargs) + LLM_CACHE[key] = [c.message.content for c in completion.choices] + return LLM_CACHE[key] + def embedding(*args, **kwargs): - key = json.dumps({'method': 'embedding', 'args': args, 'kwargs': kwargs}) - if key not in LLM_CACHE: - res = embedding_client.embeddings.create(*args, **kwargs) - [data] = res.data - LLM_CACHE[key] = data.embedding - return LLM_CACHE[key] + key = json.dumps({"method": "embedding", "args": args, "kwargs": kwargs}) + if key not in LLM_CACHE: + res = embedding_client.embeddings.create(*args, **kwargs) + [data] = res.data + LLM_CACHE[key] = data.embedding + return LLM_CACHE[key] + @op("Input CSV") def input_csv(*, filename: ops.PathStr, key: str): - return pd.read_csv(filename).rename(columns={key: 'text'}) + return pd.read_csv(filename).rename(columns={key: "text"}) + @op("Input document") def input_document(*, filename: ops.PathStr): - with open(filename) as f: - return {'text': f.read()} + with open(filename) as f: + return {"text": f.read()} + @op("Input chat") def input_chat(*, chat: str): - return {'text': chat} + return {"text": chat} + @op("Split document") -def split_document(input, *, delimiter: str = '\\n\\n'): - delimiter = delimiter.encode().decode('unicode_escape') - chunks = input['text'].split(delimiter) - return pd.DataFrame(chunks, columns=['text']) +def split_document(input, *, delimiter: str = "\\n\\n"): + delimiter = delimiter.encode().decode("unicode_escape") + chunks = input["text"].split(delimiter) + return pd.DataFrame(chunks, columns=["text"]) + @ops.input_position(input="top") @op("Build document graph") def build_document_graph(input): - return [{'source': i, 'target': i+1} for i in range(len(input)-1)] + return [{"source": i, "target": i + 1} for i in range(len(input) - 1)] + @ops.input_position(nodes="top", edges="top") @op("Predict links") def predict_links(nodes, edges): - '''A placeholder for a real algorithm. For now just adds 2-hop neighbors.''' - edge_map = {} # Source -> [Targets] - for edge in edges: - edge_map.setdefault(edge['source'], []) - edge_map[edge['source']].append(edge['target']) - new_edges = [] - for edge in edges: - for t in edge_map.get(edge['target'], []): - new_edges.append({'source': edge['source'], 'target': t}) - return edges + new_edges + """A placeholder for a real algorithm. For now just adds 2-hop neighbors.""" + edge_map = {} # Source -> [Targets] + for edge in edges: + edge_map.setdefault(edge["source"], []) + edge_map[edge["source"]].append(edge["target"]) + new_edges = [] + for edge in edges: + for t in edge_map.get(edge["target"], []): + new_edges.append({"source": edge["source"], "target": t}) + return edges + new_edges + @ops.input_position(nodes="top", edges="top") @op("Add neighbors") def add_neighbors(nodes, edges, item): - nodes = pd.DataFrame(nodes) - edges = pd.DataFrame(edges) - matches = item['rag'] - additional_matches = [] - for m in matches: - node = nodes[nodes['text'] == m].index[0] - neighbors = edges[edges['source'] == node]['target'].to_list() - additional_matches.extend(nodes.loc[neighbors, 'text']) - return {**item, 'rag': matches + additional_matches} + nodes = pd.DataFrame(nodes) + edges = pd.DataFrame(edges) + matches = item["rag"] + additional_matches = [] + for m in matches: + node = nodes[nodes["text"] == m].index[0] + neighbors = edges[edges["source"] == node]["target"].to_list() + additional_matches.extend(nodes.loc[neighbors, "text"]) + return {**item, "rag": matches + additional_matches} + @op("Create prompt") -def create_prompt(input, *, save_as='prompt', template: ops.LongStr): - assert template, 'Please specify the template. Refer to columns using the Jinja2 syntax.' - t = jinja.from_string(template) - prompt = t.render(**input) - return {**input, save_as: prompt} +def create_prompt(input, *, save_as="prompt", template: ops.LongStr): + assert ( + template + ), "Please specify the template. Refer to columns using the Jinja2 syntax." + t = jinja.from_string(template) + prompt = t.render(**input) + return {**input, save_as: prompt} + @op("Ask LLM") def ask_llm(input, *, model: str, accepted_regex: str = None, max_tokens: int = 100): - assert model, 'Please specify the model.' - assert 'prompt' in input, 'Please create the prompt first.' - options = {} - if accepted_regex: - options['extra_body'] = { - "guided_regex": accepted_regex, - } - results = chat( - model=model, - max_tokens=max_tokens, - messages=[ - {"role": "user", "content": input['prompt']}, - ], - **options, - ) - return [{**input, 'response': r} for r in results] + assert model, "Please specify the model." + assert "prompt" in input, "Please create the prompt first." + options = {} + if accepted_regex: + options["extra_body"] = { + "guided_regex": accepted_regex, + } + results = chat( + model=model, + max_tokens=max_tokens, + messages=[ + {"role": "user", "content": input["prompt"]}, + ], + **options, + ) + return [{**input, "response": r} for r in results] + @op("View", view="table_view") def view(input, *, _ctx: one_by_one.Context): - v = _ctx.last_result - if v: - columns = v['dataframes']['df']['columns'] - v['dataframes']['df']['data'].append([input[c] for c in columns]) - else: - columns = [str(c) for c in input.keys() if not str(c).startswith('_')] - v = { - 'dataframes': { 'df': { - 'columns': columns, - 'data': [[input[c] for c in columns]], - }} - } - return v + v = _ctx.last_result + if v: + columns = v["dataframes"]["df"]["columns"] + v["dataframes"]["df"]["data"].append([input[c] for c in columns]) + else: + columns = [str(c) for c in input.keys() if not str(c).startswith("_")] + v = { + "dataframes": { + "df": { + "columns": columns, + "data": [[input[c] for c in columns]], + } + } + } + return v + @ops.input_position(input="right") @ops.output_position(output="left") @op("Loop") def loop(input, *, max_iterations: int = 3, _ctx: one_by_one.Context): - '''Data can flow back here max_iterations-1 times.''' - key = f'iterations-{_ctx.node.id}' - input[key] = input.get(key, 0) + 1 - if input[key] < max_iterations: - return input + """Data can flow back here max_iterations-1 times.""" + key = f"iterations-{_ctx.node.id}" + input[key] = input.get(key, 0) + 1 + if input[key] < max_iterations: + return input + -@op('Branch', outputs=['true', 'false']) +@op("Branch", outputs=["true", "false"]) def branch(input, *, expression: str): - res = eval(expression, input) - return one_by_one.Output(output_handle=str(bool(res)).lower(), value=input) + res = eval(expression, input) + return one_by_one.Output(output_handle=str(bool(res)).lower(), value=input) + class RagEngine(enum.Enum): - Chroma = 'Chroma' - Custom = 'Custom' + Chroma = "Chroma" + Custom = "Custom" + @ops.input_position(db="top") -@op('RAG') +@op("RAG") def rag( - input, db, *, - engine: RagEngine = RagEngine.Chroma, - input_field='text', db_field='text', num_matches: int = 10, - _ctx: one_by_one.Context): - if engine == RagEngine.Chroma: - last = _ctx.last_result - if last: - collection = last['_collection'] - else: - collection_name = _ctx.node.id.replace(' ', '_') - for c in chroma_client.list_collections(): - if c.name == collection_name: - chroma_client.delete_collection(name=collection_name) - collection = chroma_client.create_collection(name=collection_name) - collection.add( - documents=[r[db_field] for r in db], - ids=[str(i) for i in range(len(db))], - ) - results = collection.query( - query_texts=[input[input_field]], - n_results=num_matches, - ) - results = [db[int(r)] for r in results['ids'][0]] - return {**input, 'rag': results, '_collection': collection} - if engine == RagEngine.Custom: - model = 'google/gemma-2-2b-it' - chat = input[input_field] - embeddings = [embedding(input=[r[db_field]], model=model) for r in db] - q = embedding(input=[chat], model=model) - def cosine_similarity(a, b): - return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b)) - scores = [(i, cosine_similarity(q, e)) for i, e in enumerate(embeddings)] - scores.sort(key=lambda x: -x[1]) - matches = [db[i][db_field] for i, _ in scores[:num_matches]] - return {**input, 'rag': matches} - -@op('Run Python') + input, + db, + *, + engine: RagEngine = RagEngine.Chroma, + input_field="text", + db_field="text", + num_matches: int = 10, + _ctx: one_by_one.Context, +): + if engine == RagEngine.Chroma: + last = _ctx.last_result + if last: + collection = last["_collection"] + else: + collection_name = _ctx.node.id.replace(" ", "_") + for c in chroma_client.list_collections(): + if c.name == collection_name: + chroma_client.delete_collection(name=collection_name) + collection = chroma_client.create_collection(name=collection_name) + collection.add( + documents=[r[db_field] for r in db], + ids=[str(i) for i in range(len(db))], + ) + results = collection.query( + query_texts=[input[input_field]], + n_results=num_matches, + ) + results = [db[int(r)] for r in results["ids"][0]] + return {**input, "rag": results, "_collection": collection} + if engine == RagEngine.Custom: + model = "google/gemma-2-2b-it" + chat = input[input_field] + embeddings = [embedding(input=[r[db_field]], model=model) for r in db] + q = embedding(input=[chat], model=model) + + def cosine_similarity(a, b): + return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b)) + + scores = [(i, cosine_similarity(q, e)) for i, e in enumerate(embeddings)] + scores.sort(key=lambda x: -x[1]) + matches = [db[i][db_field] for i, _ in scores[:num_matches]] + return {**input, "rag": matches} + + +@op("Run Python") def run_python(input, *, template: str): - '''TODO: Implement.''' - return input + """TODO: Implement.""" + return input diff --git a/server/lynxkite_ops.py b/server/lynxkite_ops.py index 800908a745cefcf2f0630d9e488b11e5071f81c7..d9fc93520fb4ea7a4c0ec2a9f3fe3dcb5f924b54 100644 --- a/server/lynxkite_ops.py +++ b/server/lynxkite_ops.py @@ -1,4 +1,5 @@ -'''Some operations. To be split into separate files when we have more.''' +"""Some operations. To be split into separate files when we have more.""" + from . import ops from collections import deque import dataclasses @@ -9,72 +10,85 @@ import pandas as pd import traceback import typing -op = ops.op_registration('LynxKite') +op = ops.op_registration("LynxKite") + @dataclasses.dataclass class RelationDefinition: - '''Defines a set of edges.''' - df: str # The DataFrame that contains the edges. - source_column: str # The column in the edge DataFrame that contains the source node ID. - target_column: str # The column in the edge DataFrame that contains the target node ID. - source_table: str # The DataFrame that contains the source nodes. - target_table: str # The DataFrame that contains the target nodes. - source_key: str # The column in the source table that contains the node ID. - target_key: str # The column in the target table that contains the node ID. + """Defines a set of edges.""" + + df: str # The DataFrame that contains the edges. + source_column: ( + str # The column in the edge DataFrame that contains the source node ID. + ) + target_column: ( + str # The column in the edge DataFrame that contains the target node ID. + ) + source_table: str # The DataFrame that contains the source nodes. + target_table: str # The DataFrame that contains the target nodes. + source_key: str # The column in the source table that contains the node ID. + target_key: str # The column in the target table that contains the node ID. + @dataclasses.dataclass class Bundle: - '''A collection of DataFrames and other data. - - Can efficiently represent a knowledge graph (homogeneous or heterogeneous) or tabular data. - It can also carry other data, such as a trained model. - ''' - dfs: dict[str, pd.DataFrame] = dataclasses.field(default_factory=dict) - relations: list[RelationDefinition] = dataclasses.field(default_factory=list) - other: dict[str, typing.Any] = None - - @classmethod - def from_nx(cls, graph: nx.Graph): - edges = nx.to_pandas_edgelist(graph) - d = dict(graph.nodes(data=True)) - nodes = pd.DataFrame(d.values(), index=d.keys()) - nodes['id'] = nodes.index - return cls( - dfs={'edges': edges, 'nodes': nodes}, - relations=[ - RelationDefinition( - df='edges', - source_column='source', - target_column='target', - source_table='nodes', - target_table='nodes', - source_key='id', - target_key='id', + """A collection of DataFrames and other data. + + Can efficiently represent a knowledge graph (homogeneous or heterogeneous) or tabular data. + It can also carry other data, such as a trained model. + """ + + dfs: dict[str, pd.DataFrame] = dataclasses.field(default_factory=dict) + relations: list[RelationDefinition] = dataclasses.field(default_factory=list) + other: dict[str, typing.Any] = None + + @classmethod + def from_nx(cls, graph: nx.Graph): + edges = nx.to_pandas_edgelist(graph) + d = dict(graph.nodes(data=True)) + nodes = pd.DataFrame(d.values(), index=d.keys()) + nodes["id"] = nodes.index + return cls( + dfs={"edges": edges, "nodes": nodes}, + relations=[ + RelationDefinition( + df="edges", + source_column="source", + target_column="target", + source_table="nodes", + target_table="nodes", + source_key="id", + target_key="id", + ) + ], ) - ] - ) - def to_nx(self): - graph = nx.from_pandas_edgelist(self.dfs['edges']) - nx.set_node_attributes(graph, self.dfs['nodes'].set_index('id').to_dict('index')) - return graph + def to_nx(self): + graph = nx.from_pandas_edgelist(self.dfs["edges"]) + nx.set_node_attributes( + graph, self.dfs["nodes"].set_index("id").to_dict("index") + ) + return graph def nx_node_attribute_func(name): - '''Decorator for wrapping a function that adds a NetworkX node attribute.''' - def decorator(func): - @functools.wraps(func) - def wrapper(graph: nx.Graph, **kwargs): - graph = graph.copy() - attr = func(graph, **kwargs) - nx.set_node_attributes(graph, attr, name) - return graph - return wrapper - return decorator + """Decorator for wrapping a function that adds a NetworkX node attribute.""" + + def decorator(func): + @functools.wraps(func) + def wrapper(graph: nx.Graph, **kwargs): + graph = graph.copy() + attr = func(graph, **kwargs) + nx.set_node_attributes(graph, attr, name) + return graph + + return wrapper + + return decorator def disambiguate_edges(ws): - '''If an input plug is connected to multiple edges, keep only the last edge.''' + """If an input plug is connected to multiple edges, keep only the last edge.""" seen = set() for edge in reversed(ws.edges): if (edge.target, edge.targetHandle) in seen: @@ -82,20 +96,15 @@ def disambiguate_edges(ws): seen.add((edge.target, edge.targetHandle)) -@ops.register_executor('LynxKite') +@ops.register_executor("LynxKite") async def execute(ws): - catalog = ops.CATALOGS['LynxKite'] + catalog = ops.CATALOGS["LynxKite"] # Nodes are responsible for interpreting/executing their child nodes. - nodes = [n for n in ws.nodes if not n.parentId] disambiguate_edges(ws) - children = {} - for n in ws.nodes: - if n.parentId: - children.setdefault(n.parentId, []).append(n) outputs = {} failed = 0 - while len(outputs) + failed < len(nodes): - for node in nodes: + while len(outputs) + failed < len(ws.nodes): + for node in ws.nodes: if node.id in outputs: continue # TODO: Take the input/output handles into account. @@ -107,118 +116,138 @@ async def execute(ws): params = {**data.params} # Convert inputs. for i, (x, p) in enumerate(zip(inputs, op.inputs.values())): - if p.type == nx.Graph and isinstance(x, Bundle): - inputs[i] = x.to_nx() - elif p.type == Bundle and isinstance(x, nx.Graph): - inputs[i] = Bundle.from_nx(x) + if p.type == nx.Graph and isinstance(x, Bundle): + inputs[i] = x.to_nx() + elif p.type == Bundle and isinstance(x, nx.Graph): + inputs[i] = Bundle.from_nx(x) try: - output = op(*inputs, **params) + output = op(*inputs, **params) except Exception as e: - traceback.print_exc() - data.error = str(e) - failed += 1 - continue - if len(op.inputs) == 1 and op.inputs.get('multi') == '*': + traceback.print_exc() + data.error = str(e) + failed += 1 + continue + if len(op.inputs) == 1 and op.inputs.get("multi") == "*": # It's a flexible input. Create n+1 handles. - data.inputs = {f'input{i}': None for i in range(len(inputs) + 1)} + data.inputs = {f"input{i}": None for i in range(len(inputs) + 1)} data.error = None outputs[node.id] = output - if op.type == 'visualization' or op.type == 'table_view' or op.type == 'image': + if ( + op.type == "visualization" + or op.type == "table_view" + or op.type == "image" + ): data.display = output + @op("Import Parquet") def import_parquet(*, filename: str): - '''Imports a parquet file.''' - return pd.read_parquet(filename) + """Imports a parquet file.""" + return pd.read_parquet(filename) + @op("Create scale-free graph") def create_scale_free_graph(*, nodes: int = 10): - '''Creates a scale-free graph with the given number of nodes.''' - return nx.scale_free_graph(nodes) + """Creates a scale-free graph with the given number of nodes.""" + return nx.scale_free_graph(nodes) + @op("Compute PageRank") -@nx_node_attribute_func('pagerank') +@nx_node_attribute_func("pagerank") def compute_pagerank(graph: nx.Graph, *, damping=0.85, iterations=100): - return nx.pagerank(graph, alpha=damping, max_iter=iterations) + return nx.pagerank(graph, alpha=damping, max_iter=iterations) + @op("Discard loop edges") def discard_loop_edges(graph: nx.Graph): - graph = graph.copy() - graph.remove_edges_from(nx.selfloop_edges(graph)) - return graph + graph = graph.copy() + graph.remove_edges_from(nx.selfloop_edges(graph)) + return graph + @op("Sample graph") def sample_graph(graph: nx.Graph, *, nodes: int = 100): - '''Takes a (preferably connected) subgraph.''' - sample = set() - to_expand = deque([0]) - while to_expand and len(sample) < nodes: - node = to_expand.pop() - for n in graph.neighbors(node): - if n not in sample: - sample.add(n) - to_expand.append(n) - if len(sample) == nodes: - break - return nx.Graph(graph.subgraph(sample)) + """Takes a (preferably connected) subgraph.""" + sample = set() + to_expand = deque([0]) + while to_expand and len(sample) < nodes: + node = to_expand.pop() + for n in graph.neighbors(node): + if n not in sample: + sample.add(n) + to_expand.append(n) + if len(sample) == nodes: + break + return nx.Graph(graph.subgraph(sample)) + def _map_color(value): - cmap = matplotlib.cm.get_cmap('viridis') - value = (value - value.min()) / (value.max() - value.min()) - rgba = cmap(value) - return ['#{:02x}{:02x}{:02x}'.format(int(r*255), int(g*255), int(b*255)) for r, g, b in rgba[:, :3]] + cmap = matplotlib.cm.get_cmap("viridis") + value = (value - value.min()) / (value.max() - value.min()) + rgba = cmap(value) + return [ + "#{:02x}{:02x}{:02x}".format(int(r * 255), int(g * 255), int(b * 255)) + for r, g, b in rgba[:, :3] + ] + @op("Visualize graph", view="visualization") def visualize_graph(graph: Bundle, *, color_nodes_by: ops.NodeAttribute = None): - nodes = graph.dfs['nodes'].copy() - if color_nodes_by: - nodes['color'] = _map_color(nodes[color_nodes_by]) - nodes = nodes.to_records() - edges = graph.dfs['edges'].drop_duplicates(['source', 'target']) - edges = edges.to_records() - pos = nx.spring_layout(graph.to_nx(), iterations=max(1, int(10000/len(nodes)))) - v = { - 'animationDuration': 500, - 'animationEasingUpdate': 'quinticInOut', - 'series': [ - { - 'type': 'graph', - 'roam': True, - 'lineStyle': { - 'color': 'gray', - 'curveness': 0.3, - }, - 'emphasis': { - 'focus': 'adjacency', - 'lineStyle': { - 'width': 10, - } - }, - 'data': [ - { - 'id': str(n.id), - 'x': float(pos[n.id][0]), 'y': float(pos[n.id][1]), - # Adjust node size to cover the same area no matter how many nodes there are. - 'symbolSize': 50 / len(nodes) ** 0.5, - 'itemStyle': {'color': n.color} if color_nodes_by else {}, - } - for n in nodes], - 'links': [ - {'source': str(r.source), 'target': str(r.target)} - for r in edges], - }, - ], - } - return v + nodes = graph.dfs["nodes"].copy() + if color_nodes_by: + nodes["color"] = _map_color(nodes[color_nodes_by]) + nodes = nodes.to_records() + edges = graph.dfs["edges"].drop_duplicates(["source", "target"]) + edges = edges.to_records() + pos = nx.spring_layout(graph.to_nx(), iterations=max(1, int(10000 / len(nodes)))) + v = { + "animationDuration": 500, + "animationEasingUpdate": "quinticInOut", + "series": [ + { + "type": "graph", + "roam": True, + "lineStyle": { + "color": "gray", + "curveness": 0.3, + }, + "emphasis": { + "focus": "adjacency", + "lineStyle": { + "width": 10, + }, + }, + "data": [ + { + "id": str(n.id), + "x": float(pos[n.id][0]), + "y": float(pos[n.id][1]), + # Adjust node size to cover the same area no matter how many nodes there are. + "symbolSize": 50 / len(nodes) ** 0.5, + "itemStyle": {"color": n.color} if color_nodes_by else {}, + } + for n in nodes + ], + "links": [ + {"source": str(r.source), "target": str(r.target)} for r in edges + ], + }, + ], + } + return v + @op("View tables", view="table_view") def view_tables(bundle: Bundle): - v = { - 'dataframes': { name: { - 'columns': [str(c) for c in df.columns], - 'data': df.values.tolist(), - } for name, df in bundle.dfs.items() }, - 'relations': bundle.relations, - 'other': bundle.other, - } - return v + v = { + "dataframes": { + name: { + "columns": [str(c) for c in df.columns], + "data": df.values.tolist(), + } + for name, df in bundle.dfs.items() + }, + "relations": bundle.relations, + "other": bundle.other, + } + return v diff --git a/server/ops.py b/server/ops.py index 7686315813c0e68ec4e2fad3f8efbc4c2f4db686..79134a2fa7c291d3119f3485fe9da90c44499d15 100644 --- a/server/ops.py +++ b/server/ops.py @@ -1,4 +1,5 @@ -'''API for implementing LynxKite operations.''' +"""API for implementing LynxKite operations.""" + from __future__ import annotations import enum import functools @@ -10,180 +11,214 @@ from typing_extensions import Annotated CATALOGS = {} EXECUTORS = {} -typeof = type # We have some arguments called "type". +typeof = type # We have some arguments called "type". + + def type_to_json(t): - if isinstance(t, type) and issubclass(t, enum.Enum): - return {'enum': list(t.__members__.keys())} - if getattr(t, '__metadata__', None): - return t.__metadata__[-1] - return {'type': str(t)} -Type = Annotated[ - typing.Any, pydantic.PlainSerializer(type_to_json, return_type=dict) -] -LongStr = Annotated[ - str, {'format': 'textarea'} -] -PathStr = Annotated[ - str, {'format': 'path'} -] -CollapsedStr = Annotated[ - str, {'format': 'collapsed'} -] -NodeAttribute = Annotated[ - str, {'format': 'node attribute'} -] -EdgeAttribute = Annotated[ - str, {'format': 'edge attribute'} -] + if isinstance(t, type) and issubclass(t, enum.Enum): + return {"enum": list(t.__members__.keys())} + if getattr(t, "__metadata__", None): + return t.__metadata__[-1] + return {"type": str(t)} + + +Type = Annotated[typing.Any, pydantic.PlainSerializer(type_to_json, return_type=dict)] +LongStr = Annotated[str, {"format": "textarea"}] +PathStr = Annotated[str, {"format": "path"}] +CollapsedStr = Annotated[str, {"format": "collapsed"}] +NodeAttribute = Annotated[str, {"format": "node attribute"}] +EdgeAttribute = Annotated[str, {"format": "edge attribute"}] + + class BaseConfig(pydantic.BaseModel): - model_config = pydantic.ConfigDict( - arbitrary_types_allowed=True, - ) + model_config = pydantic.ConfigDict( + arbitrary_types_allowed=True, + ) class Parameter(BaseConfig): - '''Defines a parameter for an operation.''' - name: str - default: typing.Any - type: Type = None - - @staticmethod - def options(name, options, default=None): - e = enum.Enum(f'OptionsFor_{name}', options) - return Parameter.basic(name, e[default or options[0]], e) - - @staticmethod - def collapsed(name, default, type=None): - return Parameter.basic(name, default, CollapsedStr) - - @staticmethod - def basic(name, default=None, type=None): - if default is inspect._empty: - default = None - if type is None or type is inspect._empty: - type = typeof(default) if default is not None else None - return Parameter(name=name, default=default, type=type) + """Defines a parameter for an operation.""" + + name: str + default: typing.Any + type: Type = None + + @staticmethod + def options(name, options, default=None): + e = enum.Enum(f"OptionsFor_{name}", options) + return Parameter.basic(name, e[default or options[0]], e) + + @staticmethod + def collapsed(name, default, type=None): + return Parameter.basic(name, default, CollapsedStr) + + @staticmethod + def basic(name, default=None, type=None): + if default is inspect._empty: + default = None + if type is None or type is inspect._empty: + type = typeof(default) if default is not None else None + return Parameter(name=name, default=default, type=type) + class Input(BaseConfig): - name: str - type: Type - position: str = 'left' + name: str + type: Type + position: str = "left" + class Output(BaseConfig): - name: str - type: Type - position: str = 'right' + name: str + type: Type + position: str = "right" + + +MULTI_INPUT = Input(name="multi", type="*") + -MULTI_INPUT = Input(name='multi', type='*') def basic_inputs(*names): - return {name: Input(name=name, type=None) for name in names} + return {name: Input(name=name, type=None) for name in names} + + def basic_outputs(*names): - return {name: Output(name=name, type=None) for name in names} + return {name: Output(name=name, type=None) for name in names} class Op(BaseConfig): - func: typing.Callable = pydantic.Field(exclude=True) - name: str - params: dict[str, Parameter] - inputs: dict[str, Input] - outputs: dict[str, Output] - type: str = 'basic' # The UI to use for this operation. - sub_nodes: list[Op] = None # If set, these nodes can be placed inside the operation's node. - - def __call__(self, *inputs, **params): - # Convert parameters. - for p in params: - if p in self.params: - if self.params[p].type == int: - params[p] = int(params[p]) - elif self.params[p].type == float: - params[p] = float(params[p]) - elif isinstance(self.params[p].type, enum.EnumMeta): - params[p] = self.params[p].type[params[p]] - res = self.func(*inputs, **params) - return res - - -def op(env: str, name: str, *, view='basic', sub_nodes=None, outputs=None): - '''Decorator for defining an operation.''' - def decorator(func): - sig = inspect.signature(func) - # Positional arguments are inputs. - inputs = { - name: Input(name=name, type=param.annotation) - for name, param in sig.parameters.items() - if param.kind != param.KEYWORD_ONLY} - params = {} - for n, param in sig.parameters.items(): - if param.kind == param.KEYWORD_ONLY and not n.startswith('_'): - params[n] = Parameter.basic(n, param.default, param.annotation) - if outputs: - _outputs = {name: Output(name=name, type=None) for name in outputs} - else: - _outputs = {'output': Output(name='output', type=None)} if view == 'basic' else {} - op = Op(func=func, name=name, params=params, inputs=inputs, outputs=_outputs, type=view) - if sub_nodes is not None: - op.sub_nodes = sub_nodes - op.type = 'sub_flow' - CATALOGS.setdefault(env, {}) - CATALOGS[env][name] = op - func.__op__ = op - return func - return decorator + func: typing.Callable = pydantic.Field(exclude=True) + name: str + params: dict[str, Parameter] + inputs: dict[str, Input] + outputs: dict[str, Output] + type: str = "basic" # The UI to use for this operation. + + def __call__(self, *inputs, **params): + # Convert parameters. + for p in params: + if p in self.params: + if self.params[p].type == int: + params[p] = int(params[p]) + elif self.params[p].type == float: + params[p] = float(params[p]) + elif isinstance(self.params[p].type, enum.EnumMeta): + params[p] = self.params[p].type[params[p]] + res = self.func(*inputs, **params) + return res + + +def op(env: str, name: str, *, view="basic", outputs=None): + """Decorator for defining an operation.""" + + def decorator(func): + sig = inspect.signature(func) + # Positional arguments are inputs. + inputs = { + name: Input(name=name, type=param.annotation) + for name, param in sig.parameters.items() + if param.kind != param.KEYWORD_ONLY + } + params = {} + for n, param in sig.parameters.items(): + if param.kind == param.KEYWORD_ONLY and not n.startswith("_"): + params[n] = Parameter.basic(n, param.default, param.annotation) + if outputs: + _outputs = {name: Output(name=name, type=None) for name in outputs} + else: + _outputs = ( + {"output": Output(name="output", type=None)} if view == "basic" else {} + ) + op = Op( + func=func, + name=name, + params=params, + inputs=inputs, + outputs=_outputs, + type=view, + ) + CATALOGS.setdefault(env, {}) + CATALOGS[env][name] = op + func.__op__ = op + return func + + return decorator + def input_position(**kwargs): - '''Decorator for specifying unusual positions for the inputs.''' - def decorator(func): - op = func.__op__ - for k, v in kwargs.items(): - op.inputs[k].position = v - return func - return decorator + """Decorator for specifying unusual positions for the inputs.""" + + def decorator(func): + op = func.__op__ + for k, v in kwargs.items(): + op.inputs[k].position = v + return func + + return decorator + def output_position(**kwargs): - '''Decorator for specifying unusual positions for the outputs.''' - def decorator(func): - op = func.__op__ - for k, v in kwargs.items(): - op.outputs[k].position = v - return func - return decorator + """Decorator for specifying unusual positions for the outputs.""" + + def decorator(func): + op = func.__op__ + for k, v in kwargs.items(): + op.outputs[k].position = v + return func + + return decorator + def no_op(*args, **kwargs): - if args: - return args[0] - return None - -def register_passive_op(env: str, name: str, inputs=[], outputs=['output'], params=[]): - '''A passive operation has no associated code.''' - op = Op( - func=no_op, - name=name, - params={p.name: p for p in params}, - inputs=dict( - (i, Input(name=i, type=None)) if isinstance(i, str) - else (i.name, i) for i in inputs), - outputs=dict( - (o, Output(name=o, type=None)) if isinstance(o, str) - else (o.name, o) for o in outputs)) - CATALOGS.setdefault(env, {}) - CATALOGS[env][name] = op - return op + if args: + return args[0] + return None + + +def register_passive_op(env: str, name: str, inputs=[], outputs=["output"], params=[]): + """A passive operation has no associated code.""" + op = Op( + func=no_op, + name=name, + params={p.name: p for p in params}, + inputs=dict( + (i, Input(name=i, type=None)) if isinstance(i, str) else (i.name, i) + for i in inputs + ), + outputs=dict( + (o, Output(name=o, type=None)) if isinstance(o, str) else (o.name, o) + for o in outputs + ), + ) + CATALOGS.setdefault(env, {}) + CATALOGS[env][name] = op + return op + def register_executor(env: str): - '''Decorator for registering an executor.''' - def decorator(func): - EXECUTORS[env] = func - return func - return decorator + """Decorator for registering an executor.""" + + def decorator(func): + EXECUTORS[env] = func + return func + + return decorator + def op_registration(env: str): - return functools.partial(op, env) + return functools.partial(op, env) + def passive_op_registration(env: str): - return functools.partial(register_passive_op, env) + return functools.partial(register_passive_op, env) + def register_area(env, name, params=[]): - '''A node that represents an area. It can contain other nodes, but does not restrict movement in any way.''' - op = Op(func=no_op, name=name, params={p.name: p for p in params}, inputs={}, outputs={}, type='area') - CATALOGS[env][name] = op + """A node that represents an area. It can contain other nodes, but does not restrict movement in any way.""" + op = Op( + func=no_op, + name=name, + params={p.name: p for p in params}, + inputs={}, + outputs={}, + type="area", + ) + CATALOGS[env][name] = op diff --git a/server/workspace.py b/server/workspace.py index 194cbea5fc9674cb4412e1e2213858430c93ae75..8227eae1327057e4f32a07d455136a34ed3776df 100644 --- a/server/workspace.py +++ b/server/workspace.py @@ -1,4 +1,5 @@ -'''For working with LynxKite workspaces.''' +"""For working with LynxKite workspaces.""" + from typing import Optional import dataclasses import os @@ -6,15 +7,18 @@ import pydantic import tempfile from . import ops + class BaseConfig(pydantic.BaseModel): model_config = pydantic.ConfigDict( - extra='allow', + extra="allow", ) + class Position(BaseConfig): x: float y: float + class WorkspaceNodeData(BaseConfig): title: str params: dict @@ -23,12 +27,13 @@ class WorkspaceNodeData(BaseConfig): # Also contains a "meta" field when going out. # This is ignored when coming back from the frontend. + class WorkspaceNode(BaseConfig): id: str type: str data: WorkspaceNodeData position: Position - parentId: Optional[str] = None + class WorkspaceEdge(BaseConfig): id: str @@ -37,8 +42,9 @@ class WorkspaceEdge(BaseConfig): sourceHandle: str targetHandle: str + class Workspace(BaseConfig): - env: str = '' + env: str = "" nodes: list[WorkspaceNode] = dataclasses.field(default_factory=list) edges: list[WorkspaceEdge] = dataclasses.field(default_factory=list) @@ -52,7 +58,9 @@ def save(ws: Workspace, path: str): j = ws.model_dump_json(indent=2) dirname, basename = os.path.split(path) # Create temp file in the same directory to make sure it's on the same filesystem. - with tempfile.NamedTemporaryFile('w', prefix=f'.{basename}.', dir=dirname, delete_on_close=False) as f: + with tempfile.NamedTemporaryFile( + "w", prefix=f".{basename}.", dir=dirname, delete_on_close=False + ) as f: f.write(j) f.close() os.replace(f.name, path) @@ -76,22 +84,13 @@ def _update_metadata(ws): if node.id in done: continue data = node.data - if node.parentId is None: - op = catalog.get(data.title) - elif node.parentId not in nodes: - data.error = f'Parent not found: {node.parentId}' - done.add(node.id) - continue - elif node.parentId in done: - op = nodes[node.parentId].data.meta.sub_nodes[data.title] - else: - continue + op = catalog.get(data.title) if op: data.meta = op node.type = op.type - if data.error == 'Unknown operation.': + if data.error == "Unknown operation.": data.error = None else: - data.error = 'Unknown operation.' + data.error = "Unknown operation." done.add(node.id) return ws diff --git a/web/.gitignore b/web/.gitignore index b82c32bc9cf3fcce1194b7b13fb846cc762d787a..a547bf36d8d11a4f89c59c144f24795749086dd1 100644 --- a/web/.gitignore +++ b/web/.gitignore @@ -11,3 +11,14 @@ node_modules dist dist-ssr *.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/web/.vscode/extensions.json b/web/.vscode/extensions.json deleted file mode 100644 index bdef82015138f5b7e152e7f52faa12e081de932b..0000000000000000000000000000000000000000 --- a/web/.vscode/extensions.json +++ /dev/null @@ -1,3 +0,0 @@ -{ - "recommendations": ["svelte.svelte-vscode"] -} diff --git a/web/README.md b/web/README.md index ff14cf2bf31ea9fe9639c767ee58be3145e689b6..e576f70106430c439677c6d5b3342c34ff5dacf1 100644 --- a/web/README.md +++ b/web/README.md @@ -1,27 +1,7 @@ -# Vite Svelte Flow Template +To set up: -This template creates a very basic [Svelte Flow](https://svelteflow.dev) app with [Vite](https://vite.dev). + npm i -## Get it! +To start dev server: -```sh -npx degit xyflow/vite-svelte-flow-template app-name -``` - -## Installation - -```sh -npm install -``` - -## Development - -```sh -npm run dev -``` - -## Build - -```sh -npm run build -``` + npm run dev diff --git a/web/eslint.config.js b/web/eslint.config.js new file mode 100644 index 0000000000000000000000000000000000000000..092408a9f09eae19150818b4f0db5d1b70744828 --- /dev/null +++ b/web/eslint.config.js @@ -0,0 +1,28 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' + +export default tseslint.config( + { ignores: ['dist'] }, + { + extends: [js.configs.recommended, ...tseslint.configs.recommended], + files: ['**/*.{ts,tsx}'], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + plugins: { + 'react-hooks': reactHooks, + 'react-refresh': reactRefresh, + }, + rules: { + ...reactHooks.configs.recommended.rules, + 'react-refresh/only-export-components': [ + 'warn', + { allowConstantExport: true }, + ], + }, + }, +) diff --git a/web/index.html b/web/index.html index 82518b727fa0a204c4d5a2b73dba6c7c2b6c2e07..27509497671372558a63c1aeb5d1af4fabd00c5c 100644 --- a/web/index.html +++ b/web/index.html @@ -2,12 +2,12 @@ - + - LynxKite 2024 + LynxKite 2025 -
- +
+ diff --git a/web/package-lock.json b/web/package-lock.json index 31fd8cc5941f1c9fb4c7529f6d399cc7d944ec39..52547fa50fbda26d5b11f23ebcc3ed32f9a36fe0 100644 --- a/web/package-lock.json +++ b/web/package-lock.json @@ -1,42 +1,67 @@ { - "name": "vite-svelte-flow-template", + "name": "lynxkite", "version": "0.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "vite-svelte-flow-template", + "name": "lynxkite", "version": "0.0.0", "dependencies": { - "@iconify-json/tabler": "1.2.5", - "@popperjs/core": "2.11.8", - "@sveltestack/svelte-query": "1.6.0", - "@xyflow/svelte": "0.1.21", - "bootstrap": "5.3.3", - "echarts": "5.5.1", - "fuse.js": "7.0.0", - "svelte-echarts": "^1.0.0-rc3" + "@iconify-json/tabler": "^1.2.10", + "@svgr/core": "^8.1.0", + "@svgr/plugin-jsx": "^8.1.0", + "@syncedstore/core": "^0.6.0", + "@syncedstore/react": "^0.6.0", + "@types/node": "^22.10.1", + "@xyflow/react": "^12.3.5", + "daisyui": "^4.12.20", + "echarts": "^5.5.1", + "fuse.js": "^7.0.0", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-markdown": "^9.0.1", + "react-router-dom": "^7.0.2", + "swr": "^2.2.5", + "unplugin-icons": "^0.21.0", + "y-websocket": "^2.0.4", + "yjs": "^13.6.20" }, "devDependencies": { - "@sveltejs/vite-plugin-svelte": "3.1.2", - "@syncedstore/core": "0.6.0", - "@syncedstore/svelte": "0.6.0", - "@tsconfig/svelte": "5.0.4", - "sass": "1.79.5", - "svelte": "4.2.19", - "svelte-check": "4.0.5", - "svelte-markdown": "^0.4.1", - "tslib": "2.7.0", - "typescript": "5.6.3", - "unplugin-icons": "0.19.3", - "vite": "5.4.9", - "y-websocket": "2.0.4" + "@eslint/js": "^9.15.0", + "@types/react": "^18.3.14", + "@types/react-dom": "^18.3.2", + "@vitejs/plugin-react-swc": "^3.5.0", + "autoprefixer": "^10.4.20", + "eslint": "^9.15.0", + "eslint-plugin-react-hooks": "^5.0.0", + "eslint-plugin-react-refresh": "^0.4.14", + "globals": "^15.12.0", + "postcss": "^8.4.49", + "tailwindcss": "^3.4.16", + "typescript": "~5.6.2", + "typescript-eslint": "^8.15.0", + "vite": "^6.0.1" + } + }, + "node_modules/@alloc/quick-lru": { + "version": "5.2.0", + "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", + "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=10" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" } }, "node_modules/@ampproject/remapping": { "version": "2.3.0", "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==", + "license": "Apache-2.0", "dependencies": { "@jridgewell/gen-mapping": "^0.3.5", "@jridgewell/trace-mapping": "^0.3.24" @@ -46,13 +71,13 @@ } }, "node_modules/@antfu/install-pkg": { - "version": "0.4.1", - "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-0.4.1.tgz", - "integrity": 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">=12" + }, + "funding": { + "url": "https://github.com/chalk/wrap-ansi?sponsor=1" + } + }, + "node_modules/wrap-ansi-cjs": { + "name": "wrap-ansi", + "version": "7.0.0", + "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz", + "integrity": "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==", + "dev": true, + "license": "MIT", + "dependencies": { + "ansi-styles": "^4.0.0", + "string-width": "^4.1.0", + "strip-ansi": "^6.0.0" + }, + "engines": { + "node": ">=10" + }, + "funding": { + "url": "https://github.com/chalk/wrap-ansi?sponsor=1" + } + }, + "node_modules/wrap-ansi-cjs/node_modules/ansi-regex": { + "version": "5.0.1", + "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz", + "integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=8" + } + }, + "node_modules/wrap-ansi-cjs/node_modules/emoji-regex": { + "version": "8.0.0", + "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz", + "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==", + "dev": true, + "license": "MIT" + }, + "node_modules/wrap-ansi-cjs/node_modules/string-width": { + "version": "4.2.3", + "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz", + "integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==", + "dev": true, + "license": "MIT", + "dependencies": { + "emoji-regex": "^8.0.0", + "is-fullwidth-code-point": "^3.0.0", + "strip-ansi": "^6.0.1" + }, + "engines": { + "node": ">=8" + } + }, + "node_modules/wrap-ansi-cjs/node_modules/strip-ansi": { + "version": "6.0.1", + "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz", + "integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==", + "dev": true, + "license": "MIT", + "dependencies": { + "ansi-regex": "^5.0.1" + }, + "engines": { + "node": ">=8" + } + }, + "node_modules/wrap-ansi/node_modules/ansi-styles": { + "version": "6.2.1", + "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.1.tgz", + "integrity": "sha512-bN798gFfQX+viw3R7yrGWRqnrN2oRkEkUjjl4JNn4E8GxxbjtG3FbrEIIY3l8/hrwUwIeCZvi4QuOTP4MErVug==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=12" + }, + "funding": { + "url": "https://github.com/chalk/ansi-styles?sponsor=1" + } }, "node_modules/ws": { "version": "6.2.3", "resolved": "https://registry.npmjs.org/ws/-/ws-6.2.3.tgz", "integrity": "sha512-jmTjYU0j60B+vHey6TfR3Z7RD61z/hmxBS3VMSGIrroOWXQEneK1zNuotOUrGyBHQj0yrpsLHPWtigEFd13ndA==", - "dev": true, + "license": "MIT", "optional": true, "dependencies": { "async-limiter": "~1.0.0" @@ -1806,7 +6096,7 @@ "version": "4.0.2", "resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.2.tgz", "integrity": "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ==", - "dev": true, + "license": "MIT", "optional": true, "engines": { "node": ">=0.4" @@ -1816,7 +6106,7 @@ "version": "0.1.2", "resolved": "https://registry.npmjs.org/y-leveldb/-/y-leveldb-0.1.2.tgz", "integrity": "sha512-6ulEn5AXfXJYi89rXPEg2mMHAyyw8+ZfeMMdOtBbV8FJpQ1NOrcgi6DTAcXof0dap84NjHPT2+9d0rb6cFsjEg==", - "dev": true, + "license": "MIT", "optional": true, "dependencies": { "level": "^6.0.1", @@ -1834,7 +6124,7 @@ "version": "1.0.6", "resolved": "https://registry.npmjs.org/y-protocols/-/y-protocols-1.0.6.tgz", "integrity": "sha512-vHRF2L6iT3rwj1jub/K5tYcTT/mEYDUppgNPXwp8fmLpui9f7Yeq3OEtTLVF012j39QnV+KEQpNqoN7CWU7Y9Q==", - "dev": true, + "license": "MIT", "dependencies": { "lib0": "^0.2.85" }, @@ -1854,7 +6144,7 @@ "version": "2.0.4", "resolved": "https://registry.npmjs.org/y-websocket/-/y-websocket-2.0.4.tgz", "integrity": "sha512-UbrkOU4GPNFFTDlJYAxAmzZhia8EPxHkngZ6qjrxgIYCN3gI2l+zzLzA9p4LQJ0IswzpioeIgmzekWe7HoBBjg==", - "dev": true, + "license": "MIT", "dependencies": { "lib0": "^0.2.52", "lodash.debounce": "^4.0.8", @@ -1880,12 +6170,30 @@ "yjs": "^13.5.6" } }, + "node_modules/yallist": { + "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", + "license": "ISC" + }, + "node_modules/yaml": { + "version": "2.6.1", + "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.6.1.tgz", + "integrity": "sha512-7r0XPzioN/Q9kXBro/XPnA6kznR73DHq+GXh5ON7ZozRO6aMjbmiBuKste2wslTFkC5d1dw0GooOCepZXJ2SAg==", + "dev": true, + "license": "ISC", + "bin": { + "yaml": "bin.mjs" + }, + "engines": { + "node": ">= 14" + } + }, "node_modules/yjs": { "version": "13.6.20", "resolved": "https://registry.npmjs.org/yjs/-/yjs-13.6.20.tgz", "integrity": "sha512-Z2YZI+SYqK7XdWlloI3lhMiKnCdFCVC4PchpdO+mCYwtiTwncjUbnRK9R1JmkNfdmHyDXuWN3ibJAt0wsqTbLQ==", - "dev": true, - "peer": true, + "license": "MIT", "dependencies": { "lib0": "^0.2.98" }, @@ -1898,18 +6206,65 @@ "url": "https://github.com/sponsors/dmonad" } }, + "node_modules/yocto-queue": { + "version": "0.1.0", + "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", + "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=10" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/zrender": { "version": "5.6.0", "resolved": "https://registry.npmjs.org/zrender/-/zrender-5.6.0.tgz", "integrity": "sha512-uzgraf4njmmHAbEUxMJ8Oxg+P3fT04O+9p7gY+wJRVxo8Ge+KmYv0WJev945EH4wFuc4OY2NLXz46FZrWS9xJg==", + "license": "BSD-3-Clause", "dependencies": { "tslib": "2.3.0" } }, - "node_modules/zrender/node_modules/tslib": { - "version": "2.3.0", - "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.3.0.tgz", - "integrity": "sha512-N82ooyxVNm6h1riLCoyS9e3fuJ3AMG2zIZs2Gd1ATcSFjSA23Q0fzjjZeh0jbJvWVDZ0cJT8yaNNaaXHzueNjg==" + "node_modules/zustand": { + "version": "4.5.5", + "resolved": "https://registry.npmjs.org/zustand/-/zustand-4.5.5.tgz", + "integrity": "sha512-+0PALYNJNgK6hldkgDq2vLrw5f6g/jCInz52n9RTpropGgeAf/ioFUCdtsjCqu4gNhW9D01rUQBROoRjdzyn2Q==", + "license": "MIT", + "dependencies": { + "use-sync-external-store": "1.2.2" + }, + "engines": { + "node": ">=12.7.0" + }, + "peerDependencies": { + "@types/react": ">=16.8", + "immer": ">=9.0.6", + "react": ">=16.8" + }, + "peerDependenciesMeta": { + "@types/react": { + "optional": true + }, + "immer": { + "optional": true + }, + "react": { + "optional": true + } + } + }, + "node_modules/zwitch": { + "version": "2.0.4", + "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", + "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } } } } diff --git a/web/package.json b/web/package.json index 31ac9a29c3c410c708fd34e8298d7275e5c6667a..20ee8bf4912f7c332c8a72199598a1ab3a422738 100644 --- a/web/package.json +++ b/web/package.json @@ -1,37 +1,48 @@ { - "name": "vite-svelte-flow-template", + "name": "lynxkite", "private": true, "version": "0.0.0", "type": "module", "scripts": { "dev": "vite", - "build": "vite build", - "preview": "vite preview", - "check": "svelte-check --tsconfig ./tsconfig.json" - }, - "devDependencies": { - "@sveltejs/vite-plugin-svelte": "3.1.2", - "@syncedstore/core": "0.6.0", - "@syncedstore/svelte": "0.6.0", - "@tsconfig/svelte": "5.0.4", - "sass": "1.79.5", - "svelte": "4.2.19", - "svelte-check": "4.0.5", - "svelte-markdown": "^0.4.1", - "tslib": "2.7.0", - "typescript": "5.6.3", - "unplugin-icons": "0.19.3", - "vite": "5.4.9", - "y-websocket": "2.0.4" + "build": "tsc -b && vite build", + "lint": "eslint .", + "preview": "vite preview" }, "dependencies": { - "@iconify-json/tabler": "1.2.5", - "@popperjs/core": "2.11.8", - "@sveltestack/svelte-query": "1.6.0", - "@xyflow/svelte": "0.1.21", - "bootstrap": "5.3.3", - "echarts": "5.5.1", - "fuse.js": "7.0.0", - "svelte-echarts": "^1.0.0-rc3" + "@iconify-json/tabler": "^1.2.10", + "@svgr/core": "^8.1.0", + "@svgr/plugin-jsx": "^8.1.0", + "@syncedstore/core": "^0.6.0", + "@syncedstore/react": "^0.6.0", + "@types/node": "^22.10.1", + "@xyflow/react": "^12.3.5", + "daisyui": "^4.12.20", + "echarts": "^5.5.1", + "fuse.js": "^7.0.0", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-markdown": "^9.0.1", + "react-router-dom": "^7.0.2", + "swr": "^2.2.5", + "unplugin-icons": "^0.21.0", + "y-websocket": "^2.0.4", + "yjs": "^13.6.20" + }, + "devDependencies": { + "@eslint/js": "^9.15.0", + "@types/react": "^18.3.14", + "@types/react-dom": "^18.3.2", + "@vitejs/plugin-react-swc": "^3.5.0", + "autoprefixer": "^10.4.20", + "eslint": "^9.15.0", + "eslint-plugin-react-hooks": "^5.0.0", + "eslint-plugin-react-refresh": "^0.4.14", + "globals": "^15.12.0", + "postcss": "^8.4.49", + "tailwindcss": "^3.4.16", + "typescript": "~5.6.2", + "typescript-eslint": "^8.15.0", + "vite": "^6.0.1" } } diff --git a/web/postcss.config.js b/web/postcss.config.js new file mode 100644 index 0000000000000000000000000000000000000000..2e7af2b7f1a6f391da1631d93968a9d487ba977d --- /dev/null +++ b/web/postcss.config.js @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/web/src/App.svelte b/web/src/App.svelte deleted file mode 100644 index 4bdd77ee10fb75fe63d41c9889cb1da4036595ef..0000000000000000000000000000000000000000 --- a/web/src/App.svelte +++ /dev/null @@ -1,22 +0,0 @@ - - - -{#if page === 'edit'} - -{:else} - -{/if} diff --git a/web/src/Directory.svelte b/web/src/Directory.svelte deleted file mode 100644 index 48a9f2a7d880e3b7f63f70767d4aa1ca630f7c52..0000000000000000000000000000000000000000 --- a/web/src/Directory.svelte +++ /dev/null @@ -1,177 +0,0 @@ - - -
- -
- {#await list} - - {:then list} -
- New workspace - New folder -
- {#if path}
{path}
{/if} - {#each list as item} - - {#if item.type === 'directory'} - - {:else} - - {/if} - {shortName(item)} - - {/each} - {:catch error} -

{error.message}

- {/await} -
-
- - diff --git a/web/src/Directory.tsx b/web/src/Directory.tsx new file mode 100644 index 0000000000000000000000000000000000000000..c6e0707037bfd8f4ab00582fc00a7ea95e9fdf50 --- /dev/null +++ b/web/src/Directory.tsx @@ -0,0 +1,88 @@ +// The directory browser. +import { useParams } from "react-router"; +import useSWR from 'swr' + +import logo from './assets/logo.png'; +// @ts-ignore +import Home from '~icons/tabler/home' +// @ts-ignore +import Folder from '~icons/tabler/folder' +// @ts-ignore +import FolderPlus from '~icons/tabler/folder-plus' +// @ts-ignore +import File from '~icons/tabler/file' +// @ts-ignore +import FilePlus from '~icons/tabler/file-plus' + +const fetcher = (url: string) => fetch(url).then((res) => res.json()); + +export default function () { + const { path } = useParams(); + const encodedPath = encodeURIComponent(path || ''); + const list = useSWR(`/api/dir/list?path=${encodedPath}`, fetcher) + function link(item: any) { + if (item.type === 'directory') { + return `/dir/${item.name}`; + } else { + return `/edit/${item.name}`; + } + } + function shortName(item: any) { + return item.name.split('/').pop(); + } + function newName(list: any[]) { + let i = 0; + while (true) { + const name = `Untitled${i ? ` ${i}` : ''}`; + if (!list.find(item => item.name === name)) { + return name; + } + i++; + } + } + function newWorkspaceIn(path: string, list: any[]) { + const pathSlash = path ? `${path}/` : ''; + return `/edit/${pathSlash}${newName(list)}`; + } + async function newFolderIn(path: string, list: any[]) { + const pathSlash = path ? `${path}/` : ''; + const name = newName(list); + const res = await fetch(`/api/dir/mkdir`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ path: pathSlash + name }), + }); + list = await res.json(); + } + + return ( +
+
+ LynxKite logo +
The Complete Graph Data Science Platform
+
+
+ {list.error &&

{list.error.message}

} + {list.isLoading && +
+ Loading... +
} + {list.data && + <> + + {path &&
{path}
} + {list.data.map((item: any) => + + {item.type === 'directory' ? : } + {shortName(item)} + + )} + + } +
+
+ ); +} diff --git a/web/src/EnvironmentSelector.svelte b/web/src/EnvironmentSelector.svelte deleted file mode 100644 index 6ff89fc10af1190499ffe445c63cf27fd4b014e2..0000000000000000000000000000000000000000 --- a/web/src/EnvironmentSelector.svelte +++ /dev/null @@ -1,14 +0,0 @@ - - - diff --git a/web/src/LynxKiteFlow.svelte b/web/src/LynxKiteFlow.svelte deleted file mode 100644 index 0feb0d89b199f9d86cfdd37a0103eb7796ae652a..0000000000000000000000000000000000000000 --- a/web/src/LynxKiteFlow.svelte +++ /dev/null @@ -1,230 +0,0 @@ - - -
- {#if $store.workspace !== undefined} -
-
- - {path} -
-
- { - $store.workspace.env = env; - }} - /> - - - -
-
-
- - - - {#if nodeSearchSettings} - - {/if} - -
- {/if} -
- - diff --git a/web/src/LynxKiteNode.svelte b/web/src/LynxKiteNode.svelte deleted file mode 100644 index d87a4ff527b3e340b44fe6219525b4242358bd82..0000000000000000000000000000000000000000 --- a/web/src/LynxKiteNode.svelte +++ /dev/null @@ -1,174 +0,0 @@ - - -
-
-
- {data.title} - {#if data.error}⚠️{/if} - {#if !expanded}⋯{/if} -
- {#if expanded} - {#if data.error} -
{data.error}
- {/if} - - {/if} - {#each handles as handle} - - {#if handle.showLabel}{handle.name.replace(/_/g, " ")}{/if} - - {/each} -
- {#if expanded} - updateNodeData(id, { beingResized: true })} - onResizeEnd={() => updateNodeData(id, { beingResized: false })} - > - - - {/if} -
- - diff --git a/web/src/NodeParameter.svelte b/web/src/NodeParameter.svelte deleted file mode 100644 index 53c7f29731a357354d9c19e30a3c988311a54b3b..0000000000000000000000000000000000000000 --- a/web/src/NodeParameter.svelte +++ /dev/null @@ -1,69 +0,0 @@ - - -