finetuned system1

Author: aboutphilippe

agent_stream/schedule_agent.py

@@ -3,6 +3,7 @@
 import time
 
 from restack_ai import Restack
+from restack_ai.event import AgentEvent
 from src.agents.agent import AgentStream
 
 
@@ -11,7 +12,12 @@ async def main() -> None:
 
     agent_id = f"{int(time.time() * 1000)}-{AgentStream.__name__}"
     run_id = await client.schedule_agent(
-        agent_name=AgentStream.__name__, agent_id=agent_id
+        agent_name=AgentStream.__name__,
+        agent_id=agent_id,
+        event=AgentEvent(
+            name="messages",
+            input={"messages": [{"role": "user", "content": "Tell me a joke"}]},
+        ),
     )
 
     await client.get_agent_result(agent_id=agent_id, run_id=run_id)

agent_video/pipecat/agent/pyproject.toml

@@ -10,7 +10,7 @@ dependencies = [
     "python-dotenv>=1.0.1",
     "pydantic>=2.10.6",
     "watchfiles>=1.0.4",
-    "restack-ai>=0.0.85",]
+    "restack-ai>=0.0.87",]
 
 [project.scripts]
 dev = "src.services:watch_services"

agent_video/pipecat/agent/src/agents/agent.py

@@ -4,24 +4,26 @@
 from pydantic import BaseModel
 from restack_ai.agent import (
     NonRetryableError,
+    RetryPolicy,
     agent,
     import_functions,
     log,
-    RetryPolicy,
-    uuid
+    uuid,
 )
 
-
 from src.workflows.logic import LogicWorkflow, LogicWorkflowInput
 
 with import_functions():
     from src.functions.context_docs import context_docs
+    from src.functions.daily_send_data import (
+        DailySendDataInput,
+        daily_send_data,
+    )
     from src.functions.llm_chat import (
         LlmChatInput,
         Message,
         llm_chat,
     )
-    from src.functions.daily_send_data import daily_send_data, DailySendDataInput
     from src.functions.llm_talk import LlmTalkInput, llm_talk
 
 
@@ -32,15 +34,18 @@ class MessagesEvent(BaseModel):
 class EndEvent(BaseModel):
     end: bool
 
+
 class AgentInput(BaseModel):
     room_url: str
-    model: Literal['restack', 'gpt-4o-mini', 'gpt-4o'] = 'restack'
+    model: Literal["restack", "gpt-4o-mini", "gpt-4o"] = "restack"
     interactive_prompt: str | None = None
     reasoning_prompt: str | None = None
 
+
 class ContextEvent(BaseModel):
     context: str
 
+
 class DailyMessageEvent(BaseModel):
     message: str
     recipient: str | None = None
@@ -52,7 +57,9 @@ def __init__(self) -> None:
         self.end = False
         self.messages: list[Message] = []
         self.room_url = ""
-        self.model: Literal['restack', 'gpt-4o-mini', 'gpt-4o'] = "restack"
+        self.model: Literal[
+            "restack", "gpt-4o-mini", "gpt-4o"
+        ] = "restack"
         self.interactive_prompt = ""
         self.reasoning_prompt = ""
         self.context = ""
@@ -84,7 +91,7 @@ async def messages(
                         messages=self.messages[-3:],
                         context=str(self.context),
                         mode="default",
-                        model='gpt-4o-mini',
+                        model="ft:gpt-4o-mini-2024-07-18:restack::BJymdMm8",
                         interactive_prompt=self.interactive_prompt,
                     ),
                     start_to_close_timeout=timedelta(seconds=3),
@@ -104,7 +111,7 @@ async def messages(
                     ),
                     start_to_close_timeout=timedelta(seconds=120),
                 )
-            
+
         except Exception as e:
             error_message = f"llm_chat function failed: {e}"
             raise NonRetryableError(error_message) from e
@@ -122,21 +129,26 @@ async def end(self, end: EndEvent) -> EndEvent:
         log.info("Received end")
         self.end = True
         return end
-    
+
     @agent.event
     async def context(self, context: ContextEvent) -> str:
         log.info("Received context")
         self.context = context.context
         return self.context
 
     @agent.event
-    async def daily_message(self, daily_message: DailyMessageEvent) -> bool:
+    async def daily_message(
+        self, daily_message: DailyMessageEvent
+    ) -> bool:
         log.info("Received message", daily_message=daily_message)
         await agent.step(
             function=daily_send_data,
             function_input=DailySendDataInput(
                 room_url=self.room_url,
-                data={"text": daily_message.message, "author": "agent"},
+                data={
+                    "text": daily_message.message,
+                    "author": "agent",
+                },
                 recipient=daily_message.recipient,
             ),
         )
@@ -147,15 +159,17 @@ async def run(self, agent_input: AgentInput) -> None:
         try:
             self.room_url = agent_input.room_url
             self.model = agent_input.model
-            self.interactive_prompt = agent_input.interactive_prompt
+            self.interactive_prompt = (
+                agent_input.interactive_prompt
+            )
             self.reasoning_prompt = agent_input.reasoning_prompt
             docs = await agent.step(function=context_docs)
         except Exception as e:
             error_message = f"context_docs function failed: {e}"
             raise NonRetryableError(error_message) from e
         else:
             system_prompt = f"""
-            You can answer questions about the following documentation:
+            You are an AI assistant for Restack. You can answer questions about the following documentation:
             {docs}
             {self.interactive_prompt}
             """

agent_video/pipecat/agent/src/functions/daily_create_room.py

@@ -32,7 +32,6 @@ async def daily_create_room(
     function_input: DailyRoomInput,
 ) -> DailyRoomOutput:
     try:
-        
         api_key = os.getenv("DAILYCO_API_KEY")
         if not api_key:
             raise ValueError(

agent_video/pipecat/agent/src/functions/daily_send_data.py

@@ -11,29 +11,35 @@
 
 load_dotenv()
 
-async def send_data_to_room(room_name: str, data: dict, recipient: str | None = "*") -> bool:
+
+async def send_data_to_room(
+    room_name: str, data: dict, recipient: str | None = "*"
+) -> bool:
     """Send a message to a Daily room."""
     api_key = os.getenv("DAILYCO_API_KEY")
     if not api_key:
-        raise ValueError("DAILYCO_API_KEY not set in environment.")
+        raise ValueError(
+            "DAILYCO_API_KEY not set in environment."
+        )
 
     headers = {
         "Authorization": f"Bearer {api_key}",
-        "Content-Type": "application/json"
+        "Content-Type": "application/json",
     }
 
     url = f"https://api.daily.co/v1/rooms/{room_name}/send-app-message"
     recipient = recipient or "*"
-    data = {
-        "data": data,
-        "recipient": recipient
-    }
+    data = {"data": data, "recipient": recipient}
 
     async with aiohttp.ClientSession() as session:
-        async with session.post(url, headers=headers, json=data) as response:
+        async with session.post(
+            url, headers=headers, json=data
+        ) as response:
             if response.status != 200:
                 text = await response.text()
-                raise Exception(f"Failed to send message (status: {response.status}): {text}")
+                raise Exception(
+                    f"Failed to send message (status: {response.status}): {text}"
+                )
 
     return True
 
@@ -43,15 +49,16 @@ class DailySendDataInput(BaseModel):
     data: dict
     recipient: str | None = "*"
 
+
 @function.defn(name="daily_send_data")
 async def daily_send_data(
     function_input: DailySendDataInput,
 ) -> bool:
     try:
         return await send_data_to_room(
-            room_name=function_input.room_url.split('/')[-1],
+            room_name=function_input.room_url.split("/")[-1],
             data=function_input.data,
-            recipient=function_input.recipient
+            recipient=function_input.recipient,
         )
     except Exception as e:
         log.error("Error sending message to daily room", error=e)

agent_video/pipecat/agent/src/functions/llm_chat.py

@@ -25,7 +25,7 @@ class Message(BaseModel):
 
 class LlmChatInput(BaseModel):
     system_content: str | None = None
-    model: Literal['gpt-4o-mini', 'gpt-4o']
+    model: Literal["gpt-4o-mini", "gpt-4o"]
     messages: list[Message] = Field(default_factory=list)
     stream: bool = True
 

agent_video/pipecat/agent/src/functions/llm_logic.py

@@ -1,11 +1,13 @@
 import os
 from typing import Literal
 
-from openai import OpenAI
+from openai import AsyncOpenAI
 from pydantic import BaseModel
 from restack_ai.function import NonRetryableError, function
+
 from src.functions.llm_chat import Message
 
+
 class LlmLogicResponse(BaseModel):
     """Structured AI decision output used to interrupt conversations."""
 
@@ -25,8 +27,9 @@ async def llm_logic(
     function_input: LlmLogicInput,
 ) -> LlmLogicResponse:
     try:
-        client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
-
+        client = AsyncOpenAI(
+            api_key=os.environ.get("OPENAI_API_KEY")
+        )
 
         if function_input.reasoning_prompt:
             system_prompt = (
@@ -36,12 +39,13 @@ async def llm_logic(
         else:
             system_prompt = (
                 "Analyze the developer's questions and determine if an interruption is needed. "
+                "For example, to ask a follow up question and keep the conversation going. "
                 "Use the Restack documentation for accurate answers. "
                 "Track what the developer has learned and update their belief state."
                 f"Restack Documentation: {function_input.documentation}"
             )
 
-        response = client.beta.chat.completions.parse(
+        response = await client.beta.chat.completions.parse(
             model="gpt-4o",
             messages=[
                 {

agent_video/pipecat/agent/src/functions/llm_talk.py

@@ -12,14 +12,20 @@
 from src.client import api_address
 from src.functions.llm_chat import Message
 
+
 class LlmTalkInput(BaseModel):
     messages: list[Message] = Field(default_factory=list)
     context: str | None = None  # Updated context from Slow AI
     mode: Literal["default", "interrupt"]
     stream: bool = True
-    model: Literal['gpt-4o-mini', 'gpt-4o']
+    model: Literal[
+        "gpt-4o-mini",
+        "gpt-4o",
+        "ft:gpt-4o-mini-2024-07-18:restack::BJymdMm8",
+    ]
     interactive_prompt: str | None = None
 
+
 @function.defn()
 async def llm_talk(function_input: LlmTalkInput) -> str:
     """Fast AI generates responses while checking for memory updates."""
@@ -31,12 +37,13 @@ async def llm_talk(function_input: LlmTalkInput) -> str:
         if interactive_prompt:
             system_prompt = (
                 interactive_prompt
-                + "Current context: " + function_input.context
+                + "Current context: "
+                + function_input.context
             )
 
         else:
             common_prompt = (
-                    "Your are an AI assistant helping developers build with restack: the backend framework for accurate & reliable AI agents."
+                "Your are an AI assistant helping developers build with restack: the backend framework for accurate & reliable AI agents."
                 "Your interface with users will be voice. Be friendly, helpful and avoid usage of unpronouncable punctuation."
                 "Always try to bring back the conversation to restack if the user is talking about something else. "
                 "Current context: " + function_input.context

agent_video/pipecat/agent/src/functions/tavus_create_room.py

@@ -16,6 +16,7 @@
 class TavusRoomOutput(BaseModel):
     room_url: str
 
+
 @function.defn(name="tavus_create_room")
 async def tavus_create_room() -> TavusRoomOutput:
     try:
@@ -28,13 +29,18 @@ async def tavus_create_room() -> TavusRoomOutput:
 
         async with aiohttp.ClientSession() as session:
             url = "https://tavusapi.com/v2/conversations"
-            headers = {"Content-Type": "application/json", "x-api-key": api_key}
+            headers = {
+                "Content-Type": "application/json",
+                "x-api-key": api_key,
+            }
             payload = {
                 "replica_id": replica_id,
                 "persona_id": "pipecat0",
             }
 
-            async with session.post(url, headers=headers, json=payload) as r:
+            async with session.post(
+                url, headers=headers, json=payload
+            ) as r:
                 r.raise_for_status()
                 response_json = await r.json()
 
@@ -47,4 +53,4 @@ async def tavus_create_room() -> TavusRoomOutput:
         log.error("Error creating Tavus room", error=e)
         raise NonRetryableError(
             f"Error creating Tavus room: {e}",
-        ) from e
+        ) from e

agent_video/pipecat/agent/src/services.py

@@ -3,21 +3,22 @@
 import webbrowser
 from pathlib import Path
 
+from restack_ai.restack import ServiceOptions
 from watchfiles import run_process
 
 from src.agents.agent import AgentVideo
 from src.client import client
 from src.functions.context_docs import context_docs
-from src.functions.llm_chat import llm_chat
-from src.workflows.room import RoomWorkflow
-from restack_ai.restack import ServiceOptions
 from src.functions.daily_create_room import daily_create_room
-from src.functions.tavus_create_room import tavus_create_room
 from src.functions.daily_send_data import daily_send_data
+from src.functions.llm_chat import llm_chat
+from src.functions.llm_logic import llm_logic
+from src.functions.llm_talk import llm_talk
 from src.functions.send_agent_event import send_agent_event
+from src.functions.tavus_create_room import tavus_create_room
 from src.workflows.logic import LogicWorkflow
-from src.functions.llm_talk import llm_talk
-from src.functions.llm_logic import llm_logic
+from src.workflows.room import RoomWorkflow
+
 
 async def main() -> None:
     await client.start_service(