Merge pull request #8 from UiPath/sample/quickstart_agent

Sample/quickstart agent

Author: cristipufu

.gitignore

@@ -172,3 +172,8 @@ cython_debug/
 
 # PyPI configuration file
 .pypirc
+
+**/uipath.db
+**/.uipath
+**/**.nupkg
+**/__uipath/

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "uipath-llamaindex"
-version = "0.0.4"
+version = "0.0.5"
 description = "UiPath LlamaIndex SDK"
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.10"

samples/quickstart-agent/llama_index.json

@@ -1,7 +1,7 @@
 {
   "dependencies": ["."],
   "workflows": {
-    "agentic_w": "main.py:agent"
+    "agent": "main.py:agent"
   },
   "env": ".env"
 }

samples/quickstart-agent/main.py

@@ -8,6 +8,10 @@
 from llama_index.llms.openai import OpenAI
 
 
+class TopicEvent(StartEvent):
+    topic: str
+
+
 class JokeEvent(Event):
     joke: str
 
@@ -16,7 +20,7 @@ class JokeFlow(Workflow):
     llm = OpenAI()
 
     @step
-    async def generate_joke(self, ev: StartEvent) -> JokeEvent:
+    async def generate_joke(self, ev: TopicEvent) -> JokeEvent:
         topic = ev.topic
 
         prompt = f"Write your best joke about {topic}."

samples/quickstart-agent/pyproject.toml

@@ -1,7 +1,7 @@
 [project]
-name = "llama-demo"
-version = "0.0.1"
-description = "UiPath LlamaIndex SDK"
+name = "llama-quickstart-agent"
+version = "0.0.2"
+description = "UiPath LlamaIndex Quickstart Agent"
 authors = [{ name = "John Doe", email = "john.doe@myemail.com" }]
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.10"

samples/quickstart-agent/uipath.json

@@ -0,0 +1,30 @@
+{
+  "entryPoints": [
+    {
+      "filePath": "agent",
+      "uniqueId": "f646d823-434c-4ef6-b8fb-6a239ee08974",
+      "type": "agent",
+      "input": {
+        "type": "object",
+        "properties": {
+          "topic": {
+            "title": "Topic",
+            "type": "string"
+          }
+        },
+        "required": [
+          "topic"
+        ]
+      },
+      "output": {
+        "type": "object",
+        "properties": {},
+        "required": []
+      }
+    }
+  ],
+  "bindings": {
+    "version": "2.0",
+    "resources": []
+  }
+}

samples/quickstart-agent/uv.lock

@@ -2,7 +2,6 @@
 import logging
 from typing import Optional
 
-from llama_index.core.workflow import StartEvent
 from uipath import UiPath
 from uipath._cli._runtime._contracts import (
     UiPathBaseRuntime,
@@ -40,7 +39,9 @@ async def execute(self) -> Optional[UiPathRuntimeResult]:
         await self.validate()
 
         try:
-            ev = StartEvent(**self.context.input_json)
+            start_event_class = self.context.workflow._start_event_class
+
+            ev = start_event_class(**self.context.input_json)
 
             handler = self.context.workflow.run(start_event=ev)
 

src/uipath_llamaindex/_cli/_runtime/_runtime.py

@@ -1,12 +1,10 @@
 import asyncio
-import inspect
 import json
 import os
 import uuid
-from typing import Any, Dict, Optional, Type, get_type_hints
+from typing import Any, Dict
 
-from llama_index.core.workflow import Event, StartEvent, StopEvent, Workflow
-from llama_index.core.workflow.decorators import StepConfig
+from llama_index.core.workflow import StopEvent, Workflow
 from uipath._cli._utils._console import ConsoleLogger
 from uipath._cli._utils._parse_ast import generate_bindings_json  # type: ignore
 from uipath._cli.middlewares import MiddlewareResult
@@ -50,45 +48,6 @@ def process_nullable_types(properties: Dict[str, Any]) -> Dict[str, Any]:
     return result
 
 
-def find_event_types(workflow: Workflow, event_base_class: Type[Event]) -> Type[Event]:
-    """Find the StartEvent or StopEvent class in a workflow"""
-    event_classes = set()
-
-    # Get all steps from the workflow
-    steps = {}
-
-    # Get steps defined as methods
-    for name, method in inspect.getmembers(workflow, inspect.ismethod):
-        if hasattr(method, "__step_config"):
-            steps[name] = method
-
-    # Get steps defined as free functions
-    class_steps = getattr(workflow.__class__, "_step_functions", {})
-    steps.update(class_steps)
-
-    # Find all event types that are subclasses of event_base_class
-    for step_func in steps.values():
-        step_config: Optional[StepConfig] = getattr(step_func, "__step_config")
-
-        if event_base_class is StartEvent:
-            # Look in accepted_events for StartEvent
-            for event_type in step_config.accepted_events:
-                if issubclass(event_type, event_base_class):
-                    event_classes.add(event_type)
-        else:
-            # Look in return_types for StopEvent
-            for event_type in step_config.return_types:
-                if issubclass(event_type, event_base_class):
-                    event_classes.add(event_type)
-
-    if len(event_classes) == 1:
-        return event_classes.pop()
-    elif len(event_classes) > 1:
-        # Return the most specific one (the one with the most fields)
-        return max(event_classes, key=lambda cls: len(get_type_hints(cls)))
-    return event_base_class  # Default fallback
-
-
 def generate_schema_from_workflow(workflow: Workflow) -> Dict[str, Any]:
     """Extract input/output schema from a LlamaIndex workflow"""
     schema = {
@@ -97,8 +56,8 @@ def generate_schema_from_workflow(workflow: Workflow) -> Dict[str, Any]:
     }
 
     # Find the actual StartEvent and StopEvent classes used in this workflow
-    start_event_class = find_event_types(workflow, StartEvent)
-    stop_event_class = find_event_types(workflow, StopEvent)
+    start_event_class = workflow._start_event_class
+    stop_event_class = workflow._stop_event_class
 
     # Generate input schema from StartEvent using Pydantic's schema method
     try: