Update Python templates for async and agent-to-agent communication

common/py/anthropic.py

@@ -1,16 +1,16 @@
 from agentuity import AgentRequest, AgentResponse, AgentContext
-from anthropic import Anthropic
+from anthropic import AsyncAnthropic
 
-client = Anthropic()
+client = AsyncAnthropic()
 
 
 async def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
-    result = client.messages.create(
+    result = await client.messages.create(
         max_tokens=1024,
         messages=[
             {
                 "role": "user",
-                "content": request.data.text or "Hello, Claude",
+                "content": await request.data.text() or "Hello, Claude",
             }
         ],
         model="claude-3-5-sonnet-latest",

common/py/crewai/agent.py

@@ -3,6 +3,7 @@
 
 
 async def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
-    inputs = {"topic": request.data.text or "AI LLMs"}
-    result = MyCrew().crew().kickoff(inputs=inputs)
+    inputs = {"topic": await request.data.text() or "AI LLMs"}
+    crew = MyCrew().crew()
+    result = await crew.kickoff_async(inputs=inputs)
     return response.text(str(result))

common/py/langchain/openai.py

@@ -18,6 +18,6 @@ async def run(request: AgentRequest, response: AgentResponse, context: AgentCont
     )
     output_parser = StrOutputParser()
     chain = prompt | llm | output_parser
-    result = chain.invoke({"input": request.data.text})
+    result = await chain.ainvoke({"input": await request.data.text() or "Tell me about AI"})
 
     return response.text(result)

common/py/litellm.py

@@ -1,8 +1,8 @@
-from litellm import completion
+from litellm import acompletion
 from agentuity import AgentRequest, AgentResponse, AgentContext
 
 
 async def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
-    messages = [{"content": request.data.text or "Hello, how are you?", "role": "user"}]
-    result = completion(model="openai/gpt-4o", messages=messages)
+    messages = [{"content": await request.data.text() or "Hello, how are you?", "role": "user"}]
+    result = await acompletion(model="openai/gpt-4o", messages=messages)
     return response.text(result.choices[0].message.content)

common/py/llamaindex/openai.py

@@ -18,5 +18,5 @@ def multiply(a: float, b: float) -> float:
 
 
 async def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
-    result = await agent.run(request.data.text or "What is 1234 * 4567?")
+    result = await agent.run(await request.data.text() or "What is 1234 * 4567?")
     return response.text(str(result))

common/py/openai.py

@@ -1,19 +1,19 @@
-from openai import OpenAI
+from openai import AsyncOpenAI
 from agentuity import AgentRequest, AgentResponse, AgentContext
 
-client = OpenAI()
+client = AsyncOpenAI()
 
 
 async def run(request: AgentRequest, response: AgentResponse, context: AgentContext):
-    chat_completion = client.chat.completions.create(
+    chat_completion = await client.chat.completions.create(
         messages=[
             {
                 "role": "system",
                 "content": "You are a friendly assistant!",
             },
             {
                 "role": "user",
-                "content": request.data.text or "Why is the sky blue?",
+                "content": await request.data.text() or "Why is the sky blue?",
             },
         ],
         model="gpt-4o",

python-uv/templates.yaml

@@ -52,7 +52,8 @@
       args:
         - add
         - --quiet
-        - llama-index
+        - llama-index==0.12.33
+        - llama-index-core==0.12.33
     - action: create_file
       filename: "agents/{{ .AgentName | safe_filename }}/agent.py"
       from: "common/py/llamaindex/openai.py"