enhance workflow code for Python

.changeset/light-parrots-work.md

@@ -0,0 +1,5 @@
+---
+"create-llama": patch
+---
+
+Optimize generated workflow code for Python

e2e/shared/multiagent_template.spec.ts

@@ -18,14 +18,18 @@ const templateUI: TemplateUI = "shadcn";
 const templatePostInstallAction: TemplatePostInstallAction = "runApp";
 const appType: AppType = templateFramework === "nextjs" ? "" : "--frontend";
 const userMessage = "Write a blog post about physical standards for letters";
-const templateAgents = ["financial_report", "blog"];
+const templateAgents = ["financial_report", "blog", "form_filling"];
 
 for (const agents of templateAgents) {
   test.describe(`Test multiagent template ${agents} ${templateFramework} ${dataSource} ${templateUI} ${appType} ${templatePostInstallAction}`, async () => {
     test.skip(
       process.platform !== "linux" || process.env.DATASOURCE === "--no-files",
       "The multiagent template currently only works with files. We also only run on Linux to speed up tests.",
     );
+    test.skip(
+      agents === "form_filling" && templateFramework !== "fastapi",
+      "Form filling is currently only supported with FastAPI.",
+    );
     let port: number;
     let externalPort: number;
     let cwd: string;
@@ -68,6 +72,10 @@ for (const agents of templateAgents) {
     test("Frontend should be able to submit a message and receive the start of a streamed response", async ({
       page,
     }) => {
+      test.skip(
+        agents === "financial_report" || agents === "form_filling",
+        "Skip chat tests for financial report and form filling.",
+      );
       await page.goto(`http://localhost:${port}`);
       await page.fill("form textarea", userMessage);
 

templates/components/agents/python/blog/README-template.md

@@ -8,9 +8,9 @@ This example is using three agents to generate a blog post:
 
 There are three different methods how the agents can interact to reach their goal:
 
-1. [Choreography](./app/examples/choreography.py) - the agents decide themselves to delegate a task to another agent
-1. [Orchestrator](./app/examples/orchestrator.py) - a central orchestrator decides which agent should execute a task
-1. [Explicit Workflow](./app/examples/workflow.py) - a pre-defined workflow specific for the task is used to execute the tasks
+1. [Choreography](./app/agents/choreography.py) - the agents decide themselves to delegate a task to another agent
+1. [Orchestrator](./app/agents/orchestrator.py) - a central orchestrator decides which agent should execute a task
+1. [Explicit Workflow](./app/agents/workflow.py) - a pre-defined workflow specific for the task is used to execute the tasks
 
 ## Getting Started
 

templates/components/agents/python/blog/app/workflows/__init__.py

@@ -0,0 +1,3 @@
+from .blog import create_workflow
+
+__all__ = ["create_workflow"]

templates/components/agents/python/blog/app/engine/engine.py → templates/components/agents/python/blog/app/workflows/blog.py

@@ -4,25 +4,26 @@
 
 from app.agents.choreography import create_choreography
 from app.agents.orchestrator import create_orchestrator
-from app.agents.workflow import create_workflow
+from app.agents.workflow import create_workflow as create_blog_workflow
 from llama_index.core.chat_engine.types import ChatMessage
 from llama_index.core.workflow import Workflow
 
 logger = logging.getLogger("uvicorn")
 
 
-def get_chat_engine(
+def create_workflow(
     chat_history: Optional[List[ChatMessage]] = None, **kwargs
 ) -> Workflow:
-    # TODO: the EXAMPLE_TYPE could be passed as a chat config parameter?
+    # Chat filters are not supported yet
+    kwargs.pop("filters", None)
     agent_type = os.getenv("EXAMPLE_TYPE", "").lower()
     match agent_type:
         case "choreography":
             agent = create_choreography(chat_history, **kwargs)
         case "orchestrator":
             agent = create_orchestrator(chat_history, **kwargs)
         case _:
-            agent = create_workflow(chat_history, **kwargs)
+            agent = create_blog_workflow(chat_history, **kwargs)
 
     logger.info(f"Using agent pattern: {agent_type}")
 

templates/components/multiagent/python/app/workflows/single.py → templates/components/agents/python/blog/app/workflows/single.py

@@ -42,9 +42,9 @@ def to_response(self) -> dict:
         return {
             "type": "agent",
             "data": {
-                "name": self.name,
+                "agent": self.name,
                 "type": self.event_type.value,
-                "msg": self.msg,
+                "text": self.msg,
                 "data": self.data,
             },
         }

templates/components/agents/python/financial_report/README-template.md

@@ -33,7 +33,7 @@ curl --location 'localhost:8000/api/chat' \
 --data '{ "messages": [{ "role": "user", "content": "Create a report comparing the finances of Apple and Tesla" }] }'
 ```
 
-You can start editing the API by modifying `app/api/routers/chat.py` or `app/financial_report/workflow.py`. The API auto-updates as you save the files.
+You can start editing the API by modifying `app/api/routers/chat.py` or `app/workflows/financial_report.py`. The API auto-updates as you save the files.
 
 Open [http://localhost:8000/docs](http://localhost:8000/docs) with your browser to see the Swagger UI of the API.