fix inputs

Author: aboutphilippe

production_demo/README.md

@@ -67,7 +67,7 @@ And for each child workflow, for each step you can see how long the function sta
 
 ## Start LM stduio for local LLM provider
 
-Start local server with Meta Llama 3.1 8B Instruct 4bit model
+Start local server with an open source model like llama-3.3-70b-instruct.
 
 https://lmstudio.ai
 

production_demo/src/functions/evaluate.py

@@ -8,7 +8,7 @@ class EvaluateInput(BaseModel):
 @function.defn()
 async def llm_evaluate(input: EvaluateInput) -> str:
     try:
-        client = OpenAI(base_url="http://192.168.4.142:1234/v1/",api_key="llmstudio")
+        client = OpenAI(base_url="http://192.168.205.1:1234/v1/",api_key="llmstudio")
     except Exception as e:
         log.error(f"Failed to create LLM client {e}")
         raise FunctionFailure(f"Failed to create OpenAI client {e}", non_retryable=True) from e
@@ -27,7 +27,7 @@ async def llm_evaluate(input: EvaluateInput) -> str:
 
     try:
         response = client.chat.completions.create(
-            model="llama-3.2-3b-instruct",
+            model="llama-3.3-70b-instruct",
             messages=[
                 {
                     "role": "user",

production_demo/src/functions/generate.py

@@ -10,14 +10,14 @@ class GenerateInput(BaseModel):
 async def llm_generate(input: GenerateInput) -> str:
 
     try:
-        client = OpenAI(base_url="http://192.168.4.142:1234/v1/",api_key="llmstudio")
+        client = OpenAI(base_url="http://192.168.205.1:1234/v1/",api_key="llmstudio")
     except Exception as e:
         log.error(f"Failed to create LLM client {e}")
         raise FunctionFailure(f"Failed to create OpenAI client {e}", non_retryable=True) from e
 
     try:
         response = client.chat.completions.create(
-            model="llama-3.2-3b-instruct",
+            model="llama-3.3-70b-instruct",
             messages=[
                 {
                     "role": "user",

production_demo/src/workflows/child.py

@@ -4,8 +4,8 @@
 
 with import_functions():
     from src.functions.function import example_function
-    from src.functions.generate import llm_generate
-    from src.functions.evaluate import llm_evaluate
+    from src.functions.generate import llm_generate, GenerateInput
+    from src.functions.evaluate import llm_evaluate, EvaluateInput
 
 class ChildWorkflowInput(BaseModel):
     name: str = Field(default='John Doe')
@@ -21,14 +21,14 @@ async def run(self, input: ChildWorkflowInput):
 
         generated_text = await workflow.step(
             llm_generate,
-            "Generate a random joke in max 20 words.",
+            GenerateInput(prompt="Generate a random joke in max 20 words."),
             task_queue="llm",
             start_to_close_timeout=timedelta(minutes=2)
         )
 
         evaluation = await workflow.step(
             llm_evaluate,
-            generated_text,
+            EvaluateInput(generated_text=generated_text),
             task_queue="llm",
             start_to_close_timeout=timedelta(minutes=2)
         )

production_demo/src/workflows/workflow.py

@@ -5,7 +5,7 @@
 from .child import ChildWorkflow, ChildWorkflowInput
 
 with import_functions():
-    from src.functions.generate import llm_generate 
+    from src.functions.generate import llm_generate, GenerateInput
 
 class ExampleWorkflowInput(BaseModel):
     amount: int = Field(default=50)
@@ -35,7 +35,7 @@ async def run(self, input: ExampleWorkflowInput):
 
         generated_text = await workflow.step(
             llm_generate,
-            f"Give me the top 3 unique jokes according to the results. {results}",
+            GenerateInput(prompt=f"Give me the top 3 unique jokes according to the results. {results}"),
             task_queue="llm",
             start_to_close_timeout=timedelta(minutes=2)
         )