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[metadata] lock-version = "2.0" -python-versions = "^3.8.1" -content-hash = "8b93ddec633ee5bdd76f4de18d7ef4eb48b167c88983e67c88a32b0bb4170149" +python-versions = "^3.9" +content-hash = "7f35bbdd2708308a7a4af0ba9f34fc8e3202894ceeea867a85a070989448e9d3" diff --git a/pyproject.toml b/pyproject.toml index e5131d5..1fd791b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,7 +6,7 @@ authors = ["Plastic Labs "] readme = "README.md" [tool.poetry.dependencies] -python = "^3.8.1" +python = "^3.9" fastapi = "^0.109.0" uvicorn = "^0.24.0.post1" python-dotenv = "^1.0.0" @@ -25,11 +25,10 @@ opentelemetry-instrumentation-logging = "^0.44b0" greenlet = "^3.0.3" realtime = "^1.0.2" psycopg = {extras = ["binary"], version = "^3.1.18"} -langchain = "^0.1.12" -langchain-openai = "^0.0.8" httpx = "^0.27.0" uvloop = "^0.19.0" httptools = "^0.6.1" +mirascope = {extras = ["openai"], version = "^0.12.3"} [tool.ruff.lint] # from https://docs.astral.sh/ruff/linter/#rule-selection example diff --git a/src/agent.py b/src/agent.py index 2cedd9d..43e770e 100644 --- a/src/agent.py +++ b/src/agent.py @@ -3,12 +3,7 @@ from typing import Optional from dotenv import load_dotenv -from langchain_core.prompts import ( - ChatPromptTemplate, - SystemMessagePromptTemplate, - load_prompt, -) -from langchain_openai import ChatOpenAI +from mirascope.openai import OpenAICall, OpenAICallParams from sqlalchemy.ext.asyncio import AsyncSession from . import crud, schemas @@ -17,21 +12,25 @@ # from supabase import Client -SYSTEM_DIALECTIC = load_prompt( - os.path.join(os.path.dirname(__file__), "prompts/dialectic.yaml") -) -system_dialectic: SystemMessagePromptTemplate = SystemMessagePromptTemplate( - prompt=SYSTEM_DIALECTIC -) +class Dialectic(OpenAICall): + prompt_template = """ + You are tasked with responding to the query based on the context provided. + --- + query: {agent_input} + context: {retrieved_facts} + --- + Provide a brief, matter-of-fact, and appropriate response to the query based on the context provided. If the context provided doesn't aid in addressing the query, return None. + """ + agent_input: str + retrieved_facts: str -llm: ChatOpenAI = ChatOpenAI(model_name="gpt-4") + call_params = OpenAICallParams(model="gpt-4o-2024-05-13") async def prep_inference( db: AsyncSession, app_id: uuid.UUID, user_id: uuid.UUID, - session_id: uuid.UUID, query: str, ): collection = await crud.get_collection_by_name(db, app_id, user_id, "honcho") @@ -56,27 +55,20 @@ async def prep_inference( if len(retrieved_documents) > 0: retrieved_facts = retrieved_documents[0].content - dialectic_prompt = ChatPromptTemplate.from_messages([system_dialectic]) - chain = dialectic_prompt | llm - return (chain, retrieved_facts) + chain = Dialectic(agent_input=query, retrieved_facts=retrieved_facts if retrieved_facts else "None") + return chain async def chat( app_id: uuid.UUID, user_id: uuid.UUID, - session_id: uuid.UUID, query: str, db: AsyncSession, ): - (chain, retrieved_facts) = await prep_inference( - db, app_id, user_id, session_id, query - ) - response = await chain.ainvoke( - { - "agent_input": query, - "retrieved_facts": retrieved_facts if retrieved_facts else "None", - } + chain = await prep_inference( + db, app_id, user_id, query ) + response = await chain.call_async() return schemas.AgentChat(content=response.content) @@ -88,12 +80,7 @@ async def stream( query: str, db: AsyncSession, ): - (chain, retrieved_facts) = await prep_inference( - db, app_id, user_id, session_id, query - ) - return chain.astream( - { - "agent_input": query, - "retrieved_facts": retrieved_facts if retrieved_facts else "None", - } + chain = await prep_inference( + db, app_id, user_id, query ) + return chain.stream_async() diff --git a/src/deriver.py b/src/deriver.py index 60d0f41..aab911f 100644 --- a/src/deriver.py +++ b/src/deriver.py @@ -1,18 +1,14 @@ import asyncio -import os +import os, re import time import uuid from typing import List import sentry_sdk from dotenv import load_dotenv -from langchain_core.output_parsers import NumberedListOutputParser -from langchain_core.prompts import ( - ChatPromptTemplate, - SystemMessagePromptTemplate, - load_prompt, -) -from langchain_openai import ChatOpenAI + +from mirascope.openai import OpenAICall, OpenAICallParams + from realtime.connection import Socket from sqlalchemy import select from sqlalchemy.orm import selectinload @@ -34,23 +30,35 @@ SUPABASE_ID = os.getenv("SUPABASE_ID") SUPABASE_API_KEY = os.getenv("SUPABASE_API_KEY") -llm = ChatOpenAI(model_name="gpt-3.5-turbo") -output_parser = NumberedListOutputParser() +class DeriveFacts(OpenAICall): + prompt_template = """ + You are tasked with deriving discrete facts about the user based on their input. The goal is to only extract absolute facts from the message, do not make inferences beyond the text provided. + + chat history: ```{chat_history}``` + user input: ```{user_input}``` + + Output the facts as a numbered list. + """ + + chat_history: str + user_input: str + + call_params = OpenAICallParams(model="gpt-4o-2024-05-13") + +class CheckDups(OpenAICall): + prompt_template = """ + Your job is to determine if the new fact exists in the old: -SYSTEM_DERIVE_FACTS = load_prompt( - os.path.join(os.path.dirname(__file__), "prompts/derive_facts.yaml") -) -SYSTEM_CHECK_DUPS = load_prompt( - os.path.join(os.path.dirname(__file__), "prompts/check_dup_facts.yaml") -) + Old: ```{existing_facts}``` -system_check_dups: SystemMessagePromptTemplate = SystemMessagePromptTemplate( - prompt=SYSTEM_CHECK_DUPS -) + New: ```{facts}``` + + If the new fact is sufficiently represented in the old list, return False. Otherwise, if the fact is indeed new, return True. + """ + existing_facts: List[str] + fact: str -system_derive_facts: SystemMessagePromptTemplate = SystemMessagePromptTemplate( - prompt=SYSTEM_DERIVE_FACTS -) + call_params = OpenAICallParams(model="gpt-4o-2024-05-13") async def callback(payload): @@ -106,6 +114,9 @@ async def process_user_message( collection_id: uuid.UUID, message_id: uuid.UUID, ): + """ + Process a user message and derive facts from it (check for duplicates before writing to the collection). + """ async with SessionLocal() as db: messages_stmt = await crud.get_messages( db=db, app_id=app_id, user_id=user_id, session_id=session_id, reverse=True @@ -117,16 +128,15 @@ async def process_user_message( # contents = [m.content for m in messages] # print(contents) - facts = await derive_facts(messages, content) + chat_history_str = "\n".join([f"user: {m.content}" if m.is_user else f"ai: {m.content}" for m in messages]) + facts_response = await DeriveFacts(chat_history=chat_history_str, user_input=content).call_async() + facts = re.findall(r"\d+\.\s([^\n]+)", facts_response.content) + print("===================") print(f"DERIVED FACTS: {facts}") print("===================") new_facts = await check_dups(app_id, user_id, collection_id, facts) - print("===================") - print(f"CHECKED FOR DUPLICATES: {new_facts}") - print("===================") - for fact in new_facts: create_document = schemas.DocumentCreate(content=fact) async with SessionLocal() as db: @@ -146,77 +156,50 @@ async def process_user_message( # print(f"Created fact: {fact}") -async def derive_facts(chat_history, input: str) -> List[str]: - """Derive facts from the user input""" - - fact_derivation = ChatPromptTemplate.from_messages([system_derive_facts]) - chain = fact_derivation | llm - response = await chain.ainvoke( - { - "chat_history": [ - ( - "user: " + message.content - if message.is_user - else "ai: " + message.content - ) - for message in chat_history - ], - "user_input": input, - } - ) - facts = output_parser.parse(response.content) - - return facts - async def check_dups( app_id: uuid.UUID, user_id: uuid.UUID, collection_id: uuid.UUID, facts: List[str] ): """Check that we're not storing duplicate facts""" - check_duplication = ChatPromptTemplate.from_messages([system_check_dups]) - query = " ".join(facts) + check_duplication = CheckDups(existing_facts=[], fact="") result = None - async with SessionLocal() as db: - result = await crud.query_documents( - db=db, - app_id=app_id, - user_id=user_id, - collection_id=collection_id, - query=query, - top_k=10, - ) - # result = collection.query(query=query, top_k=10) - existing_facts = [document.content for document in result] - print("===================") - print(f"Existing Facts {existing_facts}") - print("===================") - if len(existing_facts) == 0: - return facts - chain = check_duplication | llm - response = await chain.ainvoke({"existing_facts": existing_facts, "facts": facts}) - new_facts = output_parser.parse(response.content) + new_facts = [] + global_existing_facts = [] # for debugging + for fact in facts: + async with SessionLocal() as db: + result = await crud.query_documents( + db=db, + app_id=app_id, + user_id=user_id, + collection_id=collection_id, + query=fact, + top_k=5, + ) + existing_facts = [document.content for document in result] + if len(existing_facts) == 0: + new_facts.append(fact) + print(f"New Fact: {fact}") + continue + + global_existing_facts.extend(existing_facts) # for debugging + + check_duplication.existing_facts = existing_facts + check_duplication.fact = fact + response = await check_duplication.call_async() + if response.content == "True": + new_facts.append(fact) + print(f"New Fact: {fact}") + continue + + print("===================") - print(f"New Facts {facts}") + print(f"Existing Facts: {global_existing_facts}") + print(f"Net New Facts {new_facts}") print("===================") return new_facts -# def listen_to_websocket(url): -# while True: -# try: -# s = Socket(url) -# s.connect() -# channel = s.set_channel("realtime:public:messages") -# channel.join().on( -# "INSERT", lambda payload: asyncio.create_task(callback(payload)) -# ) - -# s.listen() -# except ConnectionClosedError: -# print("Connection closed, attempting to reconnect...") -# time.sleep(5) - if __name__ == "__main__": URL = f"wss://{SUPABASE_ID}.supabase.co/realtime/v1/websocket?apikey={SUPABASE_API_KEY}&vsn=1.0.0"