diff --git a/typescript-sdk/apps/dojo/e2e/tests/llamaIndexTests/agenticGenUI.spec.ts b/typescript-sdk/apps/dojo/e2e/tests/llamaIndexTests/agenticGenUI.spec.ts index 26eee678d..67438721e 100644 --- a/typescript-sdk/apps/dojo/e2e/tests/llamaIndexTests/agenticGenUI.spec.ts +++ b/typescript-sdk/apps/dojo/e2e/tests/llamaIndexTests/agenticGenUI.spec.ts @@ -3,7 +3,7 @@ import { AgenticGenUIPage } from "../../pages/llamaIndexPages/AgenticUIGenPage"; test.describe("Agent Generative UI Feature", () => { // Fails. Issue with integration or something. - test.fixme("[LlamaIndex] should interact with the chat to get a planner on prompt", async ({ + test("[LlamaIndex] should interact with the chat to get a planner on prompt", async ({ page, }) => { const genUIAgent = new AgenticGenUIPage(page); @@ -37,7 +37,7 @@ test.describe("Agent Generative UI Feature", () => { }); // Fails. Issue with integration or something. - test.fixme("[LlamaIndex] should interact with the chat using predefined prompts and perform steps", async ({ + test("[LlamaIndex] should interact with the chat using predefined prompts and perform steps", async ({ page, }) => { const genUIAgent = new AgenticGenUIPage(page); diff --git a/typescript-sdk/apps/dojo/src/files.json b/typescript-sdk/apps/dojo/src/files.json index 25ffe46c3..0c5db02df 100644 --- a/typescript-sdk/apps/dojo/src/files.json +++ b/typescript-sdk/apps/dojo/src/files.json @@ -1263,7 +1263,7 @@ }, { "name": "agentic_generative_ui.py", - "content": "import asyncio\nimport copy\nimport jsonpatch\nfrom pydantic import BaseModel\n\nfrom llama_index.core.workflow import Context\nfrom llama_index.llms.openai import OpenAI\nfrom llama_index.protocols.ag_ui.router import get_ag_ui_workflow_router\nfrom llama_index.protocols.ag_ui.events import StateDeltaWorkflowEvent, StateSnapshotWorkflowEvent\n\nclass Step(BaseModel):\n description: str\n\nclass Task(BaseModel):\n steps: list[Step]\n\n# Genrative UI demo\nasync def run_task(\n ctx: Context, task: Task,\n) -> str:\n \"\"\"Execute any list of steps needed to complete a task. Useful for anything the user wants to do.\"\"\"\n state = await ctx.get(\"state\", default={})\n task = Task.model_validate(task)\n\n state = {\n \"steps\": [\n {\n \"description\": step.description,\n \"status\": \"pending\"\n }\n for step in task.steps\n ]\n }\n\n # Send initial state snapshot\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n # Sleep for 1 second\n await asyncio.sleep(1.0)\n\n # Create a copy to track changes for JSON patches\n previous_state = copy.deepcopy(state)\n\n # Update each step and send deltas\n for i, step in enumerate(state[\"steps\"]):\n step[\"status\"] = \"completed\"\n \n # Generate JSON patch from previous state to current state\n patch = jsonpatch.make_patch(previous_state, state)\n \n # Send state delta event\n ctx.write_event_to_stream(\n StateDeltaWorkflowEvent(\n delta=patch.patch\n )\n )\n \n # Update previous state for next iteration\n previous_state = copy.deepcopy(state)\n \n # Sleep for 1 second\n await asyncio.sleep(1.0)\n\n # Optionally send a final snapshot to the client\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n return \"Done!\"\n\n\nagentic_generative_ui_router = get_ag_ui_workflow_router(\n llm=OpenAI(model=\"gpt-4.1\"),\n frontend_tools=[run_task],\n initial_state={},\n system_prompt=(\n \"You are a helpful assistant that can help the user with their task. \"\n \"If the user asks you to do any task, use the run_task tool to do it. \"\n \"Use your best judgement to describe the steps.\"\n )\n)\n", + "content": "import asyncio\nimport copy\nimport jsonpatch\nfrom pydantic import BaseModel\n\nfrom llama_index.core.workflow import Context\nfrom llama_index.llms.openai import OpenAI\nfrom llama_index.protocols.ag_ui.router import get_ag_ui_workflow_router\nfrom llama_index.protocols.ag_ui.events import StateDeltaWorkflowEvent, StateSnapshotWorkflowEvent\n\nclass Step(BaseModel):\n description: str\n\nclass Task(BaseModel):\n steps: list[Step]\n\n# Genrative UI demo\nasync def run_task(\n ctx: Context, task: Task,\n) -> str:\n \"\"\"Execute any list of steps needed to complete a task. Useful for anything the user wants to do.\"\"\"\n\n async with ctx.store.edit_state() as global_state:\n state = global_state.get(\"state\", {})\n task = Task.model_validate(task)\n\n state = {\n \"steps\": [\n {\n \"description\": step.description,\n \"status\": \"pending\"\n }\n for step in task.steps\n ]\n }\n\n # Send initial state snapshot\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n # Sleep for 1 second\n await asyncio.sleep(1.0)\n\n # Create a copy to track changes for JSON patches\n previous_state = copy.deepcopy(state)\n\n # Update each step and send deltas\n for i, step in enumerate(state[\"steps\"]):\n step[\"status\"] = \"completed\"\n \n # Generate JSON patch from previous state to current state\n patch = jsonpatch.make_patch(previous_state, state)\n \n # Send state delta event\n ctx.write_event_to_stream(\n StateDeltaWorkflowEvent(\n delta=patch.patch\n )\n )\n \n # Update previous state for next iteration\n previous_state = copy.deepcopy(state)\n \n # Sleep for 1 second\n await asyncio.sleep(1.0)\n\n # Optionally send a final snapshot to the client\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n global_state[\"state\"] = state\n\n return \"Task Done!\"\n\n\nagentic_generative_ui_router = get_ag_ui_workflow_router(\n llm=OpenAI(model=\"gpt-4.1\"),\n backend_tools=[run_task],\n initial_state={},\n system_prompt=(\n \"You are a helpful assistant that can help the user with their task. \"\n \"If the user asks you to do any task, use the run_task tool to do it. \"\n \"Use your best judgement to describe the steps.\"\n )\n)\n", "language": "python", "type": "file" } @@ -1289,7 +1289,7 @@ }, { "name": "shared_state.py", - "content": "from typing import Literal, List\nfrom pydantic import BaseModel\n\nfrom llama_index.core.workflow import Context\nfrom llama_index.llms.openai import OpenAI\nfrom llama_index.protocols.ag_ui.events import StateSnapshotWorkflowEvent\nfrom llama_index.protocols.ag_ui.router import get_ag_ui_workflow_router\n\n\nclass Ingredient(BaseModel):\n icon: str\n name: str\n amount: str\n\nclass Recipe(BaseModel):\n skill_level: str\n special_preferences: List[str]\n cooking_time: str\n ingredients: List[Ingredient]\n instructions: List[str]\n\n\nasync def update_recipe(ctx: Context, recipe: Recipe) -> str:\n \"\"\"Useful for recording a recipe to shared state.\"\"\"\n recipe = Recipe.model_validate(recipe)\n\n state = await ctx.get(\"state\")\n if state is None:\n state = {}\n\n state[\"recipe\"] = recipe.model_dump()\n\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n await ctx.set(\"state\", state)\n\n return \"Recipe updated!\"\n\n\nshared_state_router = get_ag_ui_workflow_router(\n llm=OpenAI(model=\"gpt-4.1\"),\n frontend_tools=[update_recipe],\n initial_state={\n \"recipe\": None,\n }\n)\n\n\n", + "content": "from typing import Literal, List\nfrom pydantic import BaseModel\n\nfrom llama_index.core.workflow import Context\nfrom llama_index.llms.openai import OpenAI\nfrom llama_index.protocols.ag_ui.events import StateSnapshotWorkflowEvent\nfrom llama_index.protocols.ag_ui.router import get_ag_ui_workflow_router\n\n\nclass Ingredient(BaseModel):\n icon: str\n name: str\n amount: str\n\nclass Recipe(BaseModel):\n skill_level: str\n special_preferences: List[str]\n cooking_time: str\n ingredients: List[Ingredient]\n instructions: List[str]\n\n\nasync def update_recipe(ctx: Context, recipe: Recipe) -> str:\n \"\"\"Useful for recording a recipe to shared state.\"\"\"\n recipe = Recipe.model_validate(recipe)\n\n async with ctx.store.edit_state() as global_state:\n state = global_state.get(\"state\", {})\n if state is None:\n state = {}\n\n state[\"recipe\"] = recipe.model_dump()\n\n ctx.write_event_to_stream(\n StateSnapshotWorkflowEvent(\n snapshot=state\n )\n )\n\n global_state[\"state\"] = state\n\n return \"Recipe updated!\"\n\n\nshared_state_router = get_ag_ui_workflow_router(\n llm=OpenAI(model=\"gpt-4.1\"),\n frontend_tools=[update_recipe],\n initial_state={\n \"recipe\": None,\n }\n)\n\n\n", "language": "python", "type": "file" } diff --git a/typescript-sdk/integrations/llamaindex/server-py/pyproject.toml b/typescript-sdk/integrations/llamaindex/server-py/pyproject.toml index 737496655..6c323b06a 100644 --- a/typescript-sdk/integrations/llamaindex/server-py/pyproject.toml +++ b/typescript-sdk/integrations/llamaindex/server-py/pyproject.toml @@ -9,9 +9,9 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.9, <3.14" dependencies = [ - "llama-index-core>=0.12.41,<0.13", - "llama-index-agent-openai>=0.4.9,<0.5", - "llama-index-protocols-ag-ui>=0.1.2", + "llama-index-core>=0.14.0,<0.15", + "llama-index-llms-openai>=0.5.0,<0.6.0", + "llama-index-protocols-ag-ui>=0.2.2,<0.3", "jsonpatch>=1.33", "uvicorn>=0.27.0", "fastapi>=0.100.0", @@ -26,5 +26,8 @@ include = ["server/"] [tool.hatch.build.targets.wheel] include = ["server/"] +[tool.hatch.metadata] +allow-direct-references = true + [project.scripts] dev = "server:main" diff --git a/typescript-sdk/integrations/llamaindex/server-py/server/routers/agentic_generative_ui.py b/typescript-sdk/integrations/llamaindex/server-py/server/routers/agentic_generative_ui.py index cfd6ab4c2..3b2facd52 100644 --- a/typescript-sdk/integrations/llamaindex/server-py/server/routers/agentic_generative_ui.py +++ b/typescript-sdk/integrations/llamaindex/server-py/server/routers/agentic_generative_ui.py @@ -19,65 +19,69 @@ async def run_task( ctx: Context, task: Task, ) -> str: """Execute any list of steps needed to complete a task. Useful for anything the user wants to do.""" - state = await ctx.get("state", default={}) - task = Task.model_validate(task) - state = { - "steps": [ - { - "description": step.description, - "status": "pending" - } - for step in task.steps - ] - } + async with ctx.store.edit_state() as global_state: + state = global_state.get("state", {}) + task = Task.model_validate(task) - # Send initial state snapshot - ctx.write_event_to_stream( - StateSnapshotWorkflowEvent( - snapshot=state - ) - ) - - # Sleep for 1 second - await asyncio.sleep(1.0) - - # Create a copy to track changes for JSON patches - previous_state = copy.deepcopy(state) + state = { + "steps": [ + { + "description": step.description, + "status": "pending" + } + for step in task.steps + ] + } - # Update each step and send deltas - for i, step in enumerate(state["steps"]): - step["status"] = "completed" - - # Generate JSON patch from previous state to current state - patch = jsonpatch.make_patch(previous_state, state) - - # Send state delta event + # Send initial state snapshot ctx.write_event_to_stream( - StateDeltaWorkflowEvent( - delta=patch.patch + StateSnapshotWorkflowEvent( + snapshot=state ) ) - - # Update previous state for next iteration - previous_state = copy.deepcopy(state) - + # Sleep for 1 second await asyncio.sleep(1.0) - # Optionally send a final snapshot to the client - ctx.write_event_to_stream( - StateSnapshotWorkflowEvent( - snapshot=state + # Create a copy to track changes for JSON patches + previous_state = copy.deepcopy(state) + + # Update each step and send deltas + for i, step in enumerate(state["steps"]): + step["status"] = "completed" + + # Generate JSON patch from previous state to current state + patch = jsonpatch.make_patch(previous_state, state) + + # Send state delta event + ctx.write_event_to_stream( + StateDeltaWorkflowEvent( + delta=patch.patch + ) + ) + + # Update previous state for next iteration + previous_state = copy.deepcopy(state) + + # Sleep for 1 second + await asyncio.sleep(1.0) + + # Optionally send a final snapshot to the client + ctx.write_event_to_stream( + StateSnapshotWorkflowEvent( + snapshot=state + ) ) - ) - return "Done!" + global_state["state"] = state + + return "Task Done!" agentic_generative_ui_router = get_ag_ui_workflow_router( llm=OpenAI(model="gpt-4.1"), - frontend_tools=[run_task], + backend_tools=[run_task], initial_state={}, system_prompt=( "You are a helpful assistant that can help the user with their task. " diff --git a/typescript-sdk/integrations/llamaindex/server-py/server/routers/shared_state.py b/typescript-sdk/integrations/llamaindex/server-py/server/routers/shared_state.py index a81d5db25..cf29a0f7b 100644 --- a/typescript-sdk/integrations/llamaindex/server-py/server/routers/shared_state.py +++ b/typescript-sdk/integrations/llamaindex/server-py/server/routers/shared_state.py @@ -24,19 +24,20 @@ async def update_recipe(ctx: Context, recipe: Recipe) -> str: """Useful for recording a recipe to shared state.""" recipe = Recipe.model_validate(recipe) - state = await ctx.get("state") - if state is None: - state = {} + async with ctx.store.edit_state() as global_state: + state = global_state.get("state", {}) + if state is None: + state = {} - state["recipe"] = recipe.model_dump() + state["recipe"] = recipe.model_dump() - ctx.write_event_to_stream( - StateSnapshotWorkflowEvent( - snapshot=state + ctx.write_event_to_stream( + StateSnapshotWorkflowEvent( + snapshot=state + ) ) - ) - await ctx.set("state", state) + global_state["state"] = state return "Recipe updated!" diff --git a/typescript-sdk/integrations/llamaindex/server-py/uv.lock b/typescript-sdk/integrations/llamaindex/server-py/uv.lock index d1fa52c5b..72fbbd7fb 100644 --- a/typescript-sdk/integrations/llamaindex/server-py/uv.lock +++ b/typescript-sdk/integrations/llamaindex/server-py/uv.lock @@ -199,7 +199,7 @@ wheels = [ [[package]] name = "banks" -version = "2.1.2" +version = "2.2.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "deprecated" }, @@ -209,9 +209,9 @@ dependencies = [ { name = "platformdirs" }, { name = "pydantic" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/77/34/2b6697f02ffb68bee50e5fd37d6c64432244d3245603fd62950169dfed7e/banks-2.1.2.tar.gz", hash = "sha256:a0651db9d14b57fa2e115e78f68dbb1b36fe226ad6eef96192542908b1d20c1f", size = 173332, upload-time = "2025-04-20T07:09:21.674Z" } +sdist = { url = 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