LLM Templates - Created startup technical ideas LLM chat app

agenta-cli/agenta/sdk/agenta_decorator.py

@@ -12,10 +12,9 @@
 import agenta
 from fastapi import Body, FastAPI, UploadFile
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.openapi.models import Server
 from fastapi.responses import JSONResponse
 
-from .context import get_contexts, save_context
+from .context import save_context
 from .router import router as router
 from .types import (
     Context,
@@ -345,7 +344,6 @@ def find_in_schema(schema: dict, param_name: str, xparam: str):
         f"Body_{func_name}_{endpoint}_post"
     ]["properties"]
     for param_name, param_val in params.items():
-        # print(param_name, param_val)
         if isinstance(param_val, MultipleChoiceParam):
             subschema = find_in_schema(schema_to_override, param_name, "choice")
             default = str(param_val)

agenta-cli/agenta/sdk/types.py

@@ -106,7 +106,7 @@ class Message(BaseModel):
 class MessagesInput(list):
     """Messages Input for Chat-completion.
 
-    Parameters:
+    Args:
         messages (List[Dict[str, str]]): The list of messages inputs.
         Required. Each message should be a dictionary with "role" and "content" keys.
 

examples/startup_technical_ideas/app.py

@@ -0,0 +1,37 @@
+import agenta as ag
+from agenta import FloatParam, MessagesInput, MultipleChoiceParam
+from openai import OpenAI
+
+client = OpenAI()
+
+SYSTEM_PROMPT = "You have expertise in offering technical ideas to startups."
+CHAT_LLM_GPT = [
+    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-0301",
+    "gpt-3.5-turbo-0613",
+    "gpt-3.5-turbo-16k-0613",
+    "gpt-4",
+]
+
+ag.init(app_name="technical_ideas", base_name="app")
+ag.config.default(
+    temperature=FloatParam(0.2),
+    model=MultipleChoiceParam("gpt-3.5-turbo", CHAT_LLM_GPT),
+    max_tokens=ag.IntParam(-1, -1, 4000),
+    prompt_system=ag.TextParam(SYSTEM_PROMPT),
+)
+
+
+@ag.entrypoint
+def chat(
+    messages: MessagesInput = MessagesInput(),
+) -> str:
+    messages = [{"role": "system", "content": ag.config.system_prompt}] + messages
+    max_tokens = ag.config.max_tokens if ag.config.max_tokens != -1 else None
+    chat_completion = client.chat.completions.create(
+        model=ag.config.model,
+        messages=messages,
+        temperature=ag.config.temperature,
+        max_tokens=max_tokens,
+    )
+    return chat_completion.choices[0].message.content