diff --git a/.gitignore b/.gitignore index 3e9fec9..13334fb 100644 --- a/.gitignore +++ b/.gitignore @@ -72,3 +72,5 @@ www/.vercel www/*.tsbuildinfo www/next-env.d.ts .vercel + +.yarn/ diff --git a/CHANGELOG.md b/CHANGELOG.md index 89bfc78..60b2db4 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,17 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/) and this project adheres to [Semantic Versioning](http://semver.org/). +## [0.6.0] + +### Added + +- Honcho + +### Changed + +- Using mirascope instead of langchain for a smaller package size + + ## [0.5.2] - 2023-12-20 ### Fixed diff --git a/agent/cache.py b/agent/cache.py index a68c968..4b64548 100644 --- a/agent/cache.py +++ b/agent/cache.py @@ -3,44 +3,10 @@ in OrderedDict data structure. """ from collections import OrderedDict -from .mediator import SupabaseMediator -import uuid -from typing import List, Tuple, Dict -from langchain.schema import BaseMessage -import sentry_sdk - -class Conversation: - "Wrapper Class for storing contexts between channels. Using an object to pass by reference avoid additional cache hits" - @sentry_sdk.trace - def __init__(self, mediator: SupabaseMediator, user_id: str, conversation_id: str = str(uuid.uuid4()), location_id: str = "web", metadata: Dict = {}): - self.mediator: SupabaseMediator = mediator - self.user_id: str = user_id - self.conversation_id: str = conversation_id - self.location_id: str = location_id - self.metadata: Dict = metadata - - @sentry_sdk.trace - def add_message(self, message_type: str, message: BaseMessage,) -> None: - self.mediator.add_message(self.conversation_id, self.user_id, message_type, message) - - @sentry_sdk.trace - def messages(self, message_type: str, limit: Tuple[bool, int | None] = (True, 10)) -> List[BaseMessage]: - return self.mediator.messages(self.conversation_id, self.user_id, message_type, limit=limit) - @sentry_sdk.trace - def delete(self) -> None: - self.mediator.delete_conversation(self.conversation_id) - - @sentry_sdk.trace - def messages(self, message_type: str, limit: Tuple[bool, int | None] = (True, 10)) -> List[BaseMessage]: - return self.mediator.messages(self.conversation_id, self.user_id, message_type, limit=limit) - - @sentry_sdk.trace - def restart(self) -> None: - self.delete() - representation = self.mediator.add_conversation(user_id=self.user_id, location_id=self.location_id) - self.conversation_id: str = representation["id"] - self.metadata = representation["metadata"] +from typing import Dict +import sentry_sdk +from honcho import AsyncSession, AsyncHoncho as Honcho class LRUCache: @@ -59,7 +25,7 @@ def get(self, key: str): return self.cache[key] @sentry_sdk.trace - def put(self, key: str, value: Conversation): + def put(self, key: str, value: AsyncSession): if key in self.cache: # If the key already exists, move it to the end and update the value self.cache.move_to_end(key) @@ -71,47 +37,67 @@ def put(self, key: str, value: Conversation): # Add or update the key-value pair at the end of the OrderedDict self.cache[key] = value + class LayeredLRUCache: """A Conversation LRU Cache that bases keys on the location of a conversation. The assumption is that the location is a unique identifier""" + @sentry_sdk.trace - def __init__(self, capacity, mediator: SupabaseMediator): + def __init__(self, capacity: int, honcho: Honcho): # TODO add type indicator + # def __init__(self, capacity, mediator: SupabaseMediator): self.capacity = capacity self.memory_cache = OrderedDict() - self.mediator = mediator + self.honcho = honcho + # self.mediator = mediator @sentry_sdk.trace - def get(self, user_id: str, location_id: str) -> None | Conversation: - key = location_id+user_id + def get(self, user_id: str, location_id: str) -> None | AsyncSession: + key = location_id + user_id if key in self.memory_cache: return self.memory_cache[key] - conversation = self.mediator.conversations(location_id=location_id, user_id=user_id) + conversation = self.mediator.conversations( + location_id=location_id, user_id=user_id + ) if conversation: conversation_id = conversation[0]["id"] metadata = conversation[0]["metadata"] # Add the conversation data to the memory_cache if len(self.memory_cache) >= self.capacity: self.memory_cache.popitem(last=False) - self.memory_cache[key] = Conversation(self.mediator, location_id=location_id, user_id=user_id, conversation_id=conversation_id, metadata=metadata) + self.memory_cache[key] = AsyncSession( + location_id=location_id, + user_id=user_id, + conversation_id=conversation_id, + metadata=metadata, + ) return self.memory_cache[key] return None @sentry_sdk.trace - def put(self, user_id: str, location_id: str) -> Conversation: + def put(self, user_id: str, location_id: str) -> AsyncSession: # Add the conversation data to the postgres via the mediator - representation: Dict = self.mediator.add_conversation(location_id=location_id, user_id=user_id) + representation: Dict = self.mediator.add_conversation( + location_id=location_id, user_id=user_id + ) conversation_id = representation["id"] metadata = representation["metadata"] - key: str = location_id+user_id + key: str = location_id + user_id if len(self.memory_cache) >= self.capacity: # Remove the least recently used item from the memory cache self.memory_cache.popitem(last=False) - self.memory_cache[key] = Conversation(self.mediator, location_id=location_id, user_id=user_id, conversation_id=conversation_id, metadata=metadata) + self.memory_cache[key] = AsyncSession( + location_id=location_id, + user_id=user_id, + conversation_id=conversation_id, + metadata=metadata, + ) return self.memory_cache[key] @sentry_sdk.trace - def get_or_create(self, user_id: str, location_id: str, restart: bool = False) -> Conversation: - cache: None | Conversation = self.get(location_id=location_id, user_id=user_id) + def get_or_create( + self, user_id: str, location_id: str, restart: bool = False + ) -> AsyncSession: + cache: None | AsyncSession = self.get(location_id=location_id, user_id=user_id) if cache is None: cache = self.put(location_id=location_id, user_id=user_id) elif restart: diff --git a/agent/chain.py b/agent/chain.py index 1ce7f1c..73f6185 100644 --- a/agent/chain.py +++ b/agent/chain.py @@ -1,172 +1,103 @@ import os -from langchain.chat_models import ChatOpenAI, AzureChatOpenAI -from langchain.prompts import ( - SystemMessagePromptTemplate, -) -from langchain.prompts import load_prompt, ChatPromptTemplate -from langchain.schema import AIMessage, HumanMessage, BaseMessage - -from openai import BadRequestError +from typing import List +from mirascope.openai import OpenAICall, OpenAICallParams, azure_client_wrapper +from mirascope.base import BaseConfig from dotenv import load_dotenv -from collections.abc import AsyncIterator -from .cache import Conversation +from honcho import Honcho + +from pydantic import ConfigDict import sentry_sdk load_dotenv() -SYSTEM_THOUGHT = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/thought.yaml')) -SYSTEM_RESPONSE = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/response.yaml')) -SYSTEM_USER_PREDICTION_THOUGHT = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/user_prediction_thought.yaml')) - - -class BloomChain: - "Wrapper class for encapsulating the multiple different chains used in reasoning for the tutor's thoughts" - # llm: ChatOpenAI = ChatOpenAI(model_name = "gpt-4", temperature=1.2) - llm: AzureChatOpenAI | ChatOpenAI - if (os.environ.get("OPENAI_API_TYPE") == "azure"): - llm = AzureChatOpenAI(deployment_name = os.environ['OPENAI_API_DEPLOYMENT_NAME'], temperature=1.2, model_kwargs={"top_p": 0.5}) - else: - llm = ChatOpenAI(model_name = "gpt-4", temperature=1.2, model_kwargs={"top_p": 0.5}) - - system_thought: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_THOUGHT) - system_response: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_RESPONSE) - system_user_prediction_thought: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_USER_PREDICTION_THOUGHT) - - def __init__(self) -> None: - pass - # def __init__(self, llm: AzureChatOpenAI = AzureChatOpenAI(deployment_name = "vineeth-gpt35-16k-230828", temperature=1.2), verbose: bool = True) -> None: - # self.llm = llm - # self.verbose = verbose - - # setup prompts - # self.system_thought = SystemMessagePromptTemplate(prompt=SYSTEM_THOUGHT) - # self.system_response = SystemMessagePromptTemplate(prompt=SYSTEM_RESPONSE) - - @classmethod - @sentry_sdk.trace - def think(cls, cache: Conversation, input: str): - """Generate Bloom's thought on the user.""" - # load message history - thought_prompt = ChatPromptTemplate.from_messages([ - cls.system_thought, - *cache.messages("thought"), - HumanMessage(content=input) - ]) - chain = thought_prompt | cls.llm - - def save_new_messages(ai_response): - cache.add_message("thought", HumanMessage(content=input)) - cache.add_message("thought", AIMessage(content=ai_response)) - - return Streamable(chain.astream({}, {"tags": ["thought"], "metadata": {"conversation_id": cache.conversation_id, "user_id": cache.user_id}}), save_new_messages) - - @classmethod - @sentry_sdk.trace - def respond(cls, cache: Conversation, thought: str, input: str): - """Generate Bloom's response to the user.""" - response_prompt = ChatPromptTemplate.from_messages([ - cls.system_response, - *cache.messages("response"), - HumanMessage(content=input) - ]) - chain = response_prompt | cls.llm - - def save_new_messages(ai_response): - cache.add_message("response", HumanMessage(content=input)) - cache.add_message("response", AIMessage(content=ai_response)) - - return Streamable(chain.astream({ "thought": thought }, {"tags": ["response"], "metadata": {"conversation_id": cache.conversation_id, "user_id": cache.user_id}}), save_new_messages) - - @classmethod - @sentry_sdk.trace - async def think_user_prediction(cls, cache: Conversation): - """Generate a thought about what the user is going to say""" - - messages = ChatPromptTemplate.from_messages([ - cls.system_user_prediction_thought, - ]) - chain = messages | cls.llm - - history = unpack_messages(cache.messages('response')) - - user_prediction_thought = await chain.ainvoke( - {"history": history}, - {"tags": ["user_prediction_thought"], "metadata": {"conversation_id": cache.conversation_id, "user_id": cache.user_id}} - ) - - cache.add_message("user_prediction_thought", user_prediction_thought) - - - - @classmethod - @sentry_sdk.trace - async def chat(cls, cache: Conversation, inp: str ) -> tuple[str, str]: - thought_iterator = cls.think(cache, inp) - thought = await thought_iterator() - response_iterator = cls.respond(cache, thought, inp) - response = await response_iterator() +class HonchoCall(OpenAICall): + model_config = ConfigDict(arbitrary_types_allowed=True) - await cls.think_user_prediction(cache) + call_params = OpenAICallParams(model=os.getenv("AZURE_OPENAI_DEPLOYMENT")) + configuration = BaseConfig( + client_wrappers=[ + azure_client_wrapper( + api_key=os.getenv("AZURE_OPENAI_API_KEY"), + api_version=os.getenv("AZURE_OPENAI_API_VERSION"), + azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"), + ) + ] + ) - return thought, response + user_input: str + app_id: str + user_id: str + session_id: str + honcho: Honcho +class ThinkCall(HonchoCall): + prompt_template = """ + SYSTEM: + You are Bloom, a subversive-minded learning companion. Your job is to employ your theory of mind skills to predict the user’s mental state. -class Streamable: - "A async iterator wrapper for langchain streams that saves on completion via callback" - - def __init__(self, iterator: AsyncIterator[BaseMessage], callback): - self.iterator = iterator - self.callback = callback - self.content = "" - self.stream_error = False - - def __aiter__(self): - return self - - async def __anext__(self): - try: - if self.stream_error: - raise StopAsyncIteration - - data = await self.iterator.__anext__() - self.content += data.content - return data.content - except StopAsyncIteration as e: - self.callback(self.content) - raise StopAsyncIteration - except BadRequestError as e: - if e.code == "content_filter": - self.stream_error = True - self.message = "Sorry, your message was flagged as inappropriate. Please try again." - - return self.message - else: - raise Exception(e) - except Exception as e: - sentry_sdk.capture_exception(e) - - self.stream_error = True - self.message = "Sorry, an error occurred while streaming the response. Please try again." - - return self.message + Generate a thought that makes a prediction about the user's needs given current dialogue and also lists other pieces of data that would help improve your prediction - async def __call__(self): - async for _ in self: - pass - return self.content - -@sentry_sdk.trace -def unpack_messages(messages): - unpacked = "" - for message in messages: - if isinstance(message, HumanMessage): - unpacked += f"User: {message.content}\n" - elif isinstance(message, AIMessage): - unpacked += f"AI: {message.content}\n" - # Add more conditions here if you're using other message types - return unpacked + previous commentary: {history} + + USER: {user_input} + """ + user_input: str + + @property + def history(self) -> List[dict]: + """Get the conversation history from Honcho""" + history_list = [] + iter = self.honcho.apps.users.sessions.messages.list( + session_id=self.session_id, + app_id=self.app_id, + user_id=self.user_id, + reverse=True, + ) + meta_iter = self.honcho.apps.users.sessions.metamessages.list( + session_id=self.session_id, + app_id=self.app_id, + user_id=self.user_id, + metamessage_type="thought", + reverse=True, + ) + past_thoughts = {m.message_id: m.content for m in meta_iter.items} + for message in iter.items[::-1]: + if message.is_user: + history_list.append({"role": "user", "content": message.content}) + history_list.append( + {"role": "assistant", "content": past_thoughts[message.id]} + ) + return history_list + + +class RespondCall(HonchoCall): + prompt_template = """ + SYSTEM: You are Bloom, a subversive-minded learning companion with deep expertise in Socratic dialogue. Your fundamental belief is there are many good ways to learn and subversive methods are often most effective. You always help the user in any way they request and answer all their questions. + + {thought} + + You must produce an appropriate response to the user input. Format equations in LaTeX and wrap in dollar signs like this: $\LaTeX$. Use markdown code syntax. Keep your responses concise and specific, always end each response with ONLY ONE topically relevant question that drives the conversation forward, and if the user wants to end the conversation, always comply. + MESSAGES: {history} + USER: {user_input} + """ + + thought: str + + @property + def history(self) -> List[dict]: + """Get the conversation history from Honcho""" + history_list = [] + iter = self.honcho.apps.users.sessions.messages.list( + session_id=self.session_id, app_id=self.app_id, user_id=self.user_id + ) + for message in iter: + if message.is_user: + history_list.append({"role": "user", "content": message.content}) + else: + history_list.append({"role": "assistant", "content": message.content}) + return history_list diff --git a/agent/mediator.py b/agent/mediator.py deleted file mode 100644 index dbd8813..0000000 --- a/agent/mediator.py +++ /dev/null @@ -1,101 +0,0 @@ -from langchain.schema.messages import BaseMessage, _message_to_dict, messages_from_dict -import uuid -import os -import sentry_sdk -from dotenv import load_dotenv -# Supabase for Postgres Management -from supabase.client import create_client, Client -from supabase.lib.client_options import ClientOptions -from typing import List, Tuple, Dict -load_dotenv() - -class SupabaseMediator: - @sentry_sdk.trace - def __init__(self): - # Change the network db timeout to 60 seconds since the default is only 5 seconds - timeout_client_options = ClientOptions(postgrest_client_timeout=60) - self.supabase: Client = create_client(os.environ['SUPABASE_URL'], os.environ['SUPABASE_KEY'], timeout_client_options) - - self.memory_table = os.environ["MEMORY_TABLE"] - self.conversation_table = os.environ["CONVERSATION_TABLE"] - - @sentry_sdk.trace - def messages(self, session_id: str, user_id: str, message_type: str, limit: Tuple[bool, int | None] = (True,10)) -> List[BaseMessage]: # type: ignore - query = self.supabase.table(self.memory_table).select("message").eq("session_id", session_id).eq("user_id", user_id).eq("message_type", message_type).order("id", desc=True) - if limit[0]: - query = query.limit(limit[1]) - response = query.execute() - items = [record["message"] for record in response.data] - messages = messages_from_dict(items) - return messages[::-1] - - @sentry_sdk.trace - def add_message(self, session_id: str, user_id: str, message_type: str, message: BaseMessage) -> None: - payload = { - "session_id": session_id, - "user_id": user_id, - "message_type": message_type, - "message": _message_to_dict(message) - } - self.supabase.table(self.memory_table).insert(payload).execute() - - @sentry_sdk.trace - def conversations(self, location_id: str, user_id: str, single: bool = True) -> List[Dict] | None: - try: - response = self.supabase.table(self.conversation_table).select(*["id", "metadata"], count="exact").eq("location_id", location_id).eq("user_id", user_id).eq("isActive", True).order("created_at", desc=True).execute() - if response is not None and response.count is not None: - if (response.count > 1) and single: - # If there is more than 1 active conversation mark the rest for deletion - conversation_ids = [record["id"] for record in response.data[1:]] - self._cleanup_conversations(conversation_ids) # type: ignore - return [response.data[0]] - else: - return response.data - return None - except Exception as e: - print("========================================") - print(e) - print("========================================") - return None - - - @sentry_sdk.trace - def conversation(self, session_id: str) -> Dict | None: - response = self.supabase.table(self.conversation_table).select("*").eq("id", session_id).eq("isActive", True).maybe_single().execute() - if response: - return response.data - return None - - @sentry_sdk.trace - def _cleanup_conversations(self, conversation_ids: List[str]) -> None: - for conversation_id in conversation_ids: - self.supabase.table(self.conversation_table).update({"isActive": False}).eq("id", conversation_id).execute() - - @sentry_sdk.trace - def add_conversation(self, location_id: str, user_id: str, metadata: Dict = {}) -> Dict: - conversation_id = str(uuid.uuid4()) - payload = { - "id": conversation_id, - "user_id": user_id, - "location_id": location_id, - "metadata": metadata, - } - representation = self.supabase.table(self.conversation_table).insert(payload, returning="representation").execute() # type: ignore - print("========================================") - print(representation) - print("========================================") - return representation.data[0] - - @sentry_sdk.trace - def delete_conversation(self, conversation_id: str) -> None: - self.supabase.table(self.conversation_table).update({"isActive": False}).eq("id", conversation_id).execute() - - @sentry_sdk.trace - def update_conversation(self, conversation_id: str, metadata: Dict) -> None: - cur = self.supabase.table(self.conversation_table).select("metadata").eq("id", conversation_id).single().execute() - if cur.data['metadata'] is not None: - new_metadata = cur.data['metadata'].copy() - new_metadata.update(metadata) - else: - new_metadata = metadata - self.supabase.table(self.conversation_table).update({"metadata": new_metadata}, returning="representation").eq("id", conversation_id).execute() # type: ignore diff --git a/agent/prompts/check_voe_list.yaml b/agent/prompts/check_voe_list.yaml new file mode 100644 index 0000000..782fc03 --- /dev/null +++ b/agent/prompts/check_voe_list.yaml @@ -0,0 +1,15 @@ +_type: prompt +input_variables: + ["existing_facts", "facts"] +template: > + Your job is to compare the following two lists and keep only unique items: + + Old: """ + {existing_facts} + """ + + New: """ + {facts} + """ + + Remove redundant information from the new list and output the remaining facts. Your response should be a numbered list with each fact on a new line, for example: `\n\n1. foo\n\n2. bar\n\n3. baz`. If there's nothing to remove (i.e. the statements are sufficiently different), print "None". diff --git a/agent/prompts/thought_revision.yaml b/agent/prompts/thought_revision.yaml new file mode 100644 index 0000000..85c2581 --- /dev/null +++ b/agent/prompts/thought_revision.yaml @@ -0,0 +1,19 @@ +_type: prompt +input_variables: + ["thought", "retrieved_vectors"] +template: > + You are tasked with revising theory of mind assessments about your user. Here is a thought generated by Bloom, the subversive learning companion: + + Thought: """ + {thought} + """ + + Based on this thought, the following personal data has been retrieved: + + Personal Data: """ + {retrieved_vectors} + """ + + Given the thought and personal data, revise the thought. + + thought revision: diff --git a/agent/prompts/user_prediction_thought_revision.yaml b/agent/prompts/user_prediction_thought_revision.yaml new file mode 100644 index 0000000..2df0229 --- /dev/null +++ b/agent/prompts/user_prediction_thought_revision.yaml @@ -0,0 +1,25 @@ +_type: prompt +input_variables: + ["history", "user_prediction_thought", "retrieved_vectors"] +template: > + You are tasked with revising theory of mind "thoughts" about what the user is going to say. Here is the thought generated previously: + + Thought: """ + {user_prediction_thought} + """ + + Based on this thought, the following personal data has been retrieved: + + Personal Data: """ + {retrieved_vectors} + """ + + And here's the conversation history that was used to generate the original thought: + + History: """ + {history} + """ + + Given the thought, conversation history, and personal data, revise the thought if you believe there are changes to be made. + + thought revision: diff --git a/agent/prompts/voe.yaml b/agent/prompts/voe.yaml new file mode 100644 index 0000000..5ab412d --- /dev/null +++ b/agent/prompts/voe.yaml @@ -0,0 +1,23 @@ +_type: prompt +input_variables: + ["ai_message", "user_prediction_thought_revision", "actual", "voe_thought"] +template: > + Below is the most recent AI message we sent to a user, a "thought" about what the user was going to say to that, what the user actually responded with, and a theory of mind prediction about the user's response. Derive a fact (or list of facts) about the user based on the difference between the original thought and their actual response plus the theory of mind prediction about that response. + + Most recent AI message: """ + {ai_message} + """ + + Thought about what they were going to say: """ + {user_prediction_thought_revision} + """ + + Actual response: """ + {actual} + """ + + Theory of mind prediction about that response: """ + {voe_thought} + """ + + Provide the fact(s) solely in reference to the Actual response and theory of mind prediction about that response; i.e. do not derive a fact that negates the thought about what they were going to say. Do not speculate anything about the user. Each fact must contain enough specificity to stand alone. If there are many facts, list them out. Your response should be a numbered list with each item on a new line, for example: `\n\n1. foo\n\n2. bar\n\n3. baz`. If there's nothing to derive (i.e. the statements are sufficiently similar), print "None". diff --git a/agent/prompts/voe_thought.yaml b/agent/prompts/voe_thought.yaml new file mode 100644 index 0000000..4467129 --- /dev/null +++ b/agent/prompts/voe_thought.yaml @@ -0,0 +1,15 @@ +_type: prompt +input_variables: + ["user_prediction_thought_revision", "actual"] +template: > + Below is a "thought" about what the user was going to say, and then what the user actually said. Generate a theory of mind prediction about the user based on the difference between the "thought" and actual response. + + Thought: """ + {user_prediction_thought_revision} + """ + + Actual: """ + {actual} + """ + + Provide the theory of mind prediction solely in reference to the Actual statement, i.e. do not generate something that negates the thought. Do not speculate anything about the user. diff --git a/api/__init__.py b/api/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/api/dependencies.py b/api/dependencies.py new file mode 100644 index 0000000..3d2ac1f --- /dev/null +++ b/api/dependencies.py @@ -0,0 +1,10 @@ +from honcho import Honcho +from os import getenv +from dotenv import load_dotenv +import asyncio + +load_dotenv(override=True) + +LOCK = asyncio.Lock() +honcho = Honcho(base_url=getenv("HONCHO_URL")) +app = honcho.apps.get_or_create("Tutor-GPT") diff --git a/api/main.py b/api/main.py index 332815d..03c5e77 100644 --- a/api/main.py +++ b/api/main.py @@ -1,196 +1,33 @@ -from fastapi import FastAPI, HTTPException -from pydantic import BaseModel -import requests -from requests.exceptions import ChunkedEncodingError - -from common import init -from agent.chain import BloomChain -from agent.cache import Conversation -from fastapi.responses import StreamingResponse +from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware -# from fastapi.staticfiles import StaticFiles - -from langchain.schema import _message_to_dict import sentry_sdk import os -import random from dotenv import load_dotenv +from api.routers import conversation, chat, messages load_dotenv() - rate = 0.2 if os.getenv("SENTRY_ENVIRONMENT") == "production" else 1.0 sentry_sdk.init( - dsn=os.environ['SENTRY_DSN_API'], - traces_sample_rate=rate, - profiles_sample_rate=rate + dsn=os.environ["SENTRY_DSN_API"], traces_sample_rate=rate, profiles_sample_rate=rate ) app = FastAPI() -# Note this URL should not have a trailing slash will cause errors - app.add_middleware( CORSMiddleware, - allow_origin_regex=os.environ['URL'], - allow_credentials=True, + allow_origin_regex=os.environ["URL"], + allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) -__, LOCK, MEDIATOR, _ = init() - -honcho_url = os.getenv("HONCHO_URL") -class ConversationInput(BaseModel): - conversation_id: str - user_id: str - message: str +app.include_router(conversation.router) +app.include_router(chat.router) +app.include_router(messages.router) -class ConversationDefinition(BaseModel): - conversation_id: str - name: str @app.get("/api/test") async def test(): return {"test": "test"} - -@app.get("/api/conversations/get") -async def get_conversations(user_id: str): - async with LOCK: - conversations = MEDIATOR.conversations(location_id="web", user_id=user_id, single=False) - acc = [] - if conversations: - for convo in conversations: - instance = {} - instance["conversation_id"] = convo["id"] - instance["name"] = "" - if convo["metadata"] is not None and "name" in convo["metadata"].keys(): - instance["name"] = convo["metadata"]["name"] - acc.append(instance) - - return { - "conversations": acc - } - -@app.get("/api/conversations/delete") -async def delete_conversation(conversation_id: str): - async with LOCK: - MEDIATOR.delete_conversation(conversation_id) - return - -@app.get("/api/conversations/insert") -async def add_conversation(user_id: str, location_id: str = "web"): - async with LOCK: - # metadata = /B": False} - # if not user_id.startswith("anon_"): - # metadata["A/B"] = bool(random.getrandbits(1)) - # metadata["A/B"] = True - representation = MEDIATOR.add_conversation(location_id=location_id, user_id=user_id) - conversation_id = representation["id"] - return { - "conversation_id": conversation_id - } - -@app.post("/api/conversations/update") -async def update_conversations(change: ConversationDefinition): - async with LOCK: - MEDIATOR.update_conversation(conversation_id=change.conversation_id, metadata={"name": change.name}) - return - -@app.get("/api/messages") -async def get_messages(user_id: str, conversation_id: str): - async with LOCK: - messages = MEDIATOR.messages(user_id=user_id, session_id=conversation_id, message_type="response", limit=(False, None)) - converted_messages = [_message_to_dict(_message) for _message in messages] - return { - "messages": converted_messages - } - -@app.post("/api/chat") -async def chat(inp: ConversationInput): - if inp.user_id.startswith("anon_"): - return HTTPException(status_code=401, detail="unauthorized please sign in") - async with LOCK: - conversation = Conversation(MEDIATOR, user_id=inp.user_id, conversation_id=inp.conversation_id) - # conversation_data = MEDIATOR.conversation(session_id=inp.conversation_id) - if honcho_url: - # metadata = conversation_data["metadata"] - # if "A/B" in metadata.keys() and metadata["A/B"]: - response = requests.post(f'{honcho_url}/chat', json={ - "user_id": inp.user_id, - "conversation_id": inp.conversation_id, - "message": inp.message - }, stream=True) - print(response) - return response - if conversation is None: - raise HTTPException(status_code=404, detail="Item not found") - thought, response = await BloomChain.chat(conversation, inp.message) - return { - "thought": thought, - "response": response - } - - -@app.post("/api/stream") -async def stream(inp: ConversationInput): - """Stream the response too the user, currently only used by the Web UI and has integration to be able to use Honcho is not anonymous""" - if inp.user_id.startswith("anon_"): - return HTTPException(status_code=401, detail="unauthorized please sign in") - async with LOCK: - conversation = Conversation(MEDIATOR, user_id=inp.user_id, conversation_id=inp.conversation_id) - # conversation_data = MEDIATOR.conversation(session_id=inp.conversation_id) - if honcho_url and not inp.user_id.startswith("anon_"): - # metadata = conversation_data["metadata"] - # if "A/B" in metadata.keys() and metadata["A/B"]: - response = requests.post(f'{honcho_url}/stream', json={ - "user_id": inp.user_id, - "conversation_id": inp.conversation_id, - "message": inp.message - }, stream=True) - - def generator(): - try: - for chunk in response.iter_content(chunk_size=8192): - # print(f"Received chunk: {chunk}") - if chunk: - yield chunk - except ChunkedEncodingError as e: - print(f"Chunked encoding error occurred: {e}") - print(response) - print(response.headers) - # Optionally yield an error message to the client - yield b"An error occurred while streaming the response." - except Exception as e: - print(f"An unexpected error occurred: {e}") - # Optionally yield an error message to the client - yield b"An unexpected error occurred." - - return StreamingResponse(generator()) - if conversation is None: - raise HTTPException(status_code=404, detail="Item not found") - - async def thought_and_response(): - try: - thought_iterator = BloomChain.think(conversation, inp.message) - thought = "" - async for item in thought_iterator: - # escape ❀ if present - item = item.replace("❀", "🌸") - thought += item - yield item - yield "❀" - response_iterator = BloomChain.respond(conversation, thought, inp.message) - - async for item in response_iterator: - # if "❀" in item: - item = item.replace("❀", "🌸") - yield item - - await BloomChain.think_user_prediction(conversation) - finally: - yield "❀" - - return StreamingResponse(thought_and_response()) - diff --git a/api/routers/__init__.py b/api/routers/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/api/routers/chat.py b/api/routers/chat.py new file mode 100644 index 0000000..e73d15a --- /dev/null +++ b/api/routers/chat.py @@ -0,0 +1,70 @@ +from fastapi import APIRouter +from fastapi.responses import StreamingResponse + +from api import schemas +from api.dependencies import app, honcho + +from agent.chain import ThinkCall, RespondCall + +router = APIRouter(prefix="/api", tags=["chat"]) + + +@router.post("/stream") +async def stream( + inp: schemas.ConversationInput, +): + """Stream the response too the user, currently only used by the Web UI and has integration to be able to use Honcho is not anonymous""" + user = honcho.apps.users.get_or_create(app_id=app.id, name=inp.user_id) + + def convo_turn(): + thought_stream = ThinkCall( + user_input=inp.message, + app_id=app.id, + user_id=user.id, + session_id=str(inp.conversation_id), + honcho=honcho, + ).stream() + thought = "" + for chunk in thought_stream: + thought += chunk.content + yield chunk.content + + yield "❀" + response_stream = RespondCall( + user_input=inp.message, + thought=thought, + app_id=app.id, + user_id=user.id, + session_id=str(inp.conversation_id), + honcho=honcho, + ).stream() + response = "" + for chunk in response_stream: + response += chunk.content + yield chunk.content + yield "❀" + + new_message = honcho.apps.users.sessions.messages.create( + is_user=True, + session_id=str(inp.conversation_id), + app_id=app.id, + user_id=user.id, + content=inp.message, + ) + honcho.apps.users.sessions.metamessages.create( + app_id=app.id, + session_id=str(inp.conversation_id), + user_id=user.id, + message_id=new_message.id, + metamessage_type="thought", + content=thought, + ) + honcho.apps.users.sessions.messages.create( + is_user=False, + session_id=str(inp.conversation_id), + app_id=app.id, + user_id=user.id, + content=response, + ) + + return StreamingResponse(convo_turn()) diff --git a/api/routers/conversation.py b/api/routers/conversation.py new file mode 100644 index 0000000..d5d9250 --- /dev/null +++ b/api/routers/conversation.py @@ -0,0 +1,90 @@ +from fastapi import APIRouter, HTTPException + +# from pydantic import BaseModel +import uuid +from api import schemas + +from api.dependencies import honcho, app + +router = APIRouter(prefix="/api/conversations", tags=["conversations"]) + + +async def unpack(gen): + result = [] + async for item in gen: + result.append(item) + return result + + +@router.get("/get") +async def get_conversations(user_id: str): + # async with LOCK: + # user = honcho.apps.users.get_or_create(user_id, app_id=app.id) + # sessions = list(user.get_sessions_generator(is_active=True)) + user = honcho.apps.users.get_or_create(app_id=app.id, name=user_id) + print(user) + acc = [] + for convo in honcho.apps.users.sessions.list( + app_id=app.id, user_id=user.id, is_active=True + ): + instance = {} + instance["conversation_id"] = convo.id + instance["name"] = "" + if convo.metadata is not None and "name" in convo.metadata.keys(): + instance["name"] = convo.metadata["name"] + acc.append(instance) + + print(acc) + return {"conversations": acc} + + +@router.get("/delete") +async def delete_conversation(user_id: str, conversation_id: uuid.UUID): + # async with LOCK: + # user = honcho.apps.users.get_or_create(user_id, app_id=app.id) + # user = honcho.get_or_create_user(user_id) + try: + # session = user.get_session(conversation_id) + # session.close() + user = honcho.apps.users.get_or_create(app_id=app.id, name=user_id) + honcho.apps.users.sessions.delete( + session_id=str(conversation_id), app_id=app.id, user_id=user.id + ) + except Exception: + raise HTTPException(status_code=404, detail="Item not found") from None + + +@router.get("/insert") +async def add_conversation(user_id: str, location_id: str = "web"): + print("help") + # async with LOCK: + # user = honcho.get_or_create_user(user_id) + # user = honcho.apps.users.get_or_create(user_id, app_id=app.id) + try: + print(user_id) + print(f"App_ID {app.id}") + print(f"location_id {location_id}") + + user = honcho.apps.users.get_or_create(name=user_id, app_id=app.id) + session = honcho.apps.users.sessions.create(user_id=user.id, app_id=app.id) + except Exception as e: + print(e) + raise HTTPException(status_code=404, detail="Item not found") from None + # session = user.create_session(location_id=location_id) + return {"conversation_id": session.id} + + +@router.post("/update") +async def update_conversations(change: schemas.ConversationDefinition): + # async with LOCK: + # user = honcho.get_or_create_user(change.user_id) + user = honcho.apps.users.get_or_create(change.user_id, app_id=app.id) + # session = user.get_session(change.conversation_id) + honcho.apps.users.sessions.update( + session_id=str(change.conversation_id), + app_id=app.id, + user_id=user.id, + metadata={"name": change.name}, + ) + # session.update({"name": change.name}) + return diff --git a/api/routers/messages.py b/api/routers/messages.py new file mode 100644 index 0000000..970b99f --- /dev/null +++ b/api/routers/messages.py @@ -0,0 +1,29 @@ +from fastapi import APIRouter, HTTPException +import uuid +from honcho import NotFoundError + +from api.dependencies import honcho, app + +router = APIRouter(prefix="/api/messages", tags=["conversations"]) + + +@router.get("") +async def get_messages(user_id: str, conversation_id: uuid.UUID): + try: + user = honcho.apps.users.get_or_create(app_id=app.id, name=user_id) + session = honcho.apps.users.sessions.get( + session_id=str(conversation_id), app_id=app.id, user_id=user.id + ) + except NotFoundError: + raise HTTPException(status_code=404, detail="Item not found") + messages = [ + { + "id": message.id, + "content": message.content, + "isUser": message.is_user, + } + for message in honcho.apps.users.sessions.messages.list( + app_id=app.id, user_id=user.id, session_id=str(conversation_id) + ) + ] + return {"messages": messages} diff --git a/api/schemas.py b/api/schemas.py new file mode 100644 index 0000000..219ac10 --- /dev/null +++ b/api/schemas.py @@ -0,0 +1,14 @@ +from pydantic import BaseModel +import uuid + + +class ConversationInput(BaseModel): + user_id: str + conversation_id: uuid.UUID + message: str + + +class ConversationDefinition(BaseModel): + user_id: str + conversation_id: uuid.UUID + name: str diff --git a/bot/app.py b/bot/app.py index 6e2fa7b..6d272d3 100644 --- a/bot/app.py +++ b/bot/app.py @@ -1,10 +1,11 @@ import discord import sentry_sdk import os +import asyncio from common import init from dotenv import load_dotenv - + load_dotenv() rate = 0.2 if os.getenv("SENTRY_ENVIRONMENT") == "production" else 1.0 @@ -12,11 +13,15 @@ sentry_sdk.init( dsn=os.getenv("SENTRY_DSN_DISCORD"), traces_sample_rate=rate, - profiles_sample_rate=rate + profiles_sample_rate=rate, ) CACHE, LOCK, _, (THOUGHT_CHANNEL, TOKEN) = init() +THOUGHT_CHANNEL = os.environ["THOUGHT_CHANNEL_ID"] +TOKEN = os.environ["BOT_TOKEN"] +LOCK = asyncio.Lock() + intents = discord.Intents.default() intents.messages = True intents.message_content = True diff --git a/bot/core.py b/bot/core.py index a7d70da..8bbbf8a 100644 --- a/bot/core.py +++ b/bot/core.py @@ -9,7 +9,7 @@ ) from discord.ext import commands from typing import Optional -from agent.chain import BloomChain +from agent.chain import BloomChain from langchain.schema import AIMessage import sentry_sdk @@ -20,7 +20,9 @@ def __init__(self, bot) -> None: @commands.Cog.listener() async def on_member_join(self, member): - with sentry_sdk.start_transaction(op="on_member_join", name="discord.on_member_join"): + with sentry_sdk.start_transaction( + op="on_member_join", name="discord.on_member_join" + ): welcome_message = """ Hello! Thanks for joining the Bloom server. @@ -51,13 +53,15 @@ async def on_message(self, message): user_id = f"discord_{str(message.author.id)}" # Get cache for conversation async with LOCK: - CONVERSATION = CACHE.get_or_create(location_id=str(message.channel.id), user_id=user_id) + CONVERSATION = CACHE.get_or_create( + location_id=str(message.channel.id), user_id=user_id + ) # Get the message content but remove any mentions - inp = message.content.replace(str('<@' + str(self.bot.user.id) + '>'), '') + inp = message.content.replace(str("<@" + str(self.bot.user.id) + ">"), "") n = 1800 - async def respond(reply = True, forward_thought = True): + async def respond(reply=True, forward_thought=True): "Generate response too user" async with message.channel.typing(): # thought = "" @@ -81,25 +85,33 @@ async def respond(reply = True, forward_thought = True): thought_channel = self.bot.get_channel(int(THOUGHT_CHANNEL)) # Thought Forwarding - if (forward_thought): + if forward_thought: link = f"https://discord.com/channels/{message.guild.id}/{message.channel.id}/{message.id}" if len(thought) > n: - chunks = [thought[i:i+n] for i in range(0, len(thought), n)] + chunks = [ + thought[i : i + n] for i in range(0, len(thought), n) + ] for i in range(len(chunks)): - await thought_channel.send(f"{link}\n```\nThought #{i}: {chunks[i]}\n```") + await thought_channel.send( + f"{link}\n```\nThought #{i}: {chunks[i]}\n```" + ) else: - await thought_channel.send(f"{link}\n```\nThought: {thought}\n```") + await thought_channel.send( + f"{link}\n```\nThought: {thought}\n```" + ) - # Response Forwarding + # Response Forwarding if len(response) > n: - chunks = [response[i:i+n] for i in range(0, len(response), n)] + chunks = [ + response[i : i + n] for i in range(0, len(response), n) + ] for chunk in chunks: - if (reply): + if reply: await message.reply(chunk) else: await message.channel.send(chunk) else: - if (reply): + if reply: await message.reply(response) else: await message.channel.send(response) @@ -116,14 +128,17 @@ async def respond(reply = True, forward_thought = True): # If the bot was replied to in the message if not isinstance(message.channel, discord.channel.DMChannel): if message.reference is not None: - reply_msg = await self.bot.get_channel(message.channel.id).fetch_message(message.reference.message_id) + reply_msg = await self.bot.get_channel( + message.channel.id + ).fetch_message(message.reference.message_id) if reply_msg.author == self.bot.user: if reply_msg.content.startswith("https://discord.com"): return - if message.content.startswith("!no") or message.content.startswith("!No"): + if message.content.startswith( + "!no" + ) or message.content.startswith("!No"): return await respond(forward_thought=True) - @commands.slash_command(description="Help using the bot") async def help(self, ctx: discord.ApplicationContext): @@ -157,7 +172,9 @@ async def help(self, ctx: discord.ApplicationContext): await ctx.respond(help_message) @commands.slash_command(description="Restart the conversation with the tutor") - async def restart(self, ctx: discord.ApplicationContext, respond: Optional[bool] = True): + async def restart( + self, ctx: discord.ApplicationContext, respond: Optional[bool] = True + ): with sentry_sdk.start_transaction(op="restart", name="discord.restart"): """ Clears the conversation history and reloads the chains @@ -166,7 +183,11 @@ async def restart(self, ctx: discord.ApplicationContext, respond: Optional[bool] ctx: context, necessary for bot commands """ async with LOCK: - CONVERSATION = CACHE.get_or_create(location_id=str(ctx.channel_id), user_id=f"discord_{str(ctx.author.id)}", restart=True) + CONVERSATION = CACHE.get_or_create( + location_id=str(ctx.channel_id), + user_id=f"discord_{str(ctx.author.id)}", + restart=True, + ) if respond: msg = "Great! The conversation has been restarted. What would you like to talk about?" diff --git a/common/__init__.py b/common/__init__.py deleted file mode 100644 index 78dec45..0000000 --- a/common/__init__.py +++ /dev/null @@ -1,14 +0,0 @@ -import os -from agent.cache import LayeredLRUCache -from agent.mediator import SupabaseMediator -import asyncio - - -def init(): - THOUGHT_CHANNEL = os.environ["THOUGHT_CHANNEL_ID"] - TOKEN = os.environ['BOT_TOKEN'] - MEDIATOR = SupabaseMediator() - CACHE = LayeredLRUCache(50, MEDIATOR) # Support 50 concurrent active conversations cached in memory - LOCK = asyncio.Lock() - - return CACHE, LOCK, MEDIATOR, (THOUGHT_CHANNEL, TOKEN) diff --git a/poetry.lock b/poetry.lock index 0123ba5..5bb7b4d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,112 +1,127 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. + +[[package]] +name = "aiohappyeyeballs" +version = "2.4.0" 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-2093,5 +1770,5 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" -python-versions = "^3.10" -content-hash = "9fe9ef40d2de2669c4d0be84af96fda16fdb9de6481b8fa180468decdc2d27c8" +python-versions = "^3.9" +content-hash = "564fa60893ef875a634f89ad7dbeeb375f1c0895873bbd8685aff356cfc92308" diff --git a/pyproject.toml b/pyproject.toml index 067d773..299a6db 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,21 +4,20 @@ version = "0.5.2" description = "LangChain LLM application. Dynamic few-shot metaprompting for the task of tutoring." authors = ["vintro ", "VVoruganti prev + "\n" + value + "\n"); continue; } setThought((prev) => prev + value); // mutateMessages(newMessages, { revalidate: false }); } else { + // if (value.includes("❀Response❀")) { + // // a bloom delimiter + // isThinking = true; + // continue; + // } if (value.includes("❀")) { setCanSend(true); // Bloom delimeter continue; @@ -248,18 +255,18 @@ export default function Home() { -
-

- Help inform the future of Bloom by filling out this{" "} - - survey - -

-
+ {/*
*/} + {/*

*/} + {/* Help inform the future of Bloom by filling out this{" "} */} + {/* */} + {/* survey */} + {/* */} + {/*

*/} + {/*
*/}
{ - // return [ - // { - // source: "/api/:path*", - // destination: - // process.env.NODE_ENV === "development" - // ? "http://127.0.0.1:8000/api/:path*" - // : `${process.env.URL}/api/:path*`, - // }, - // ]; - // }, -}; - -module.exports = nextConfig - - -// Injected content via Sentry wizard below - -const { withSentryConfig } = require("@sentry/nextjs"); - -module.exports = withSentryConfig( - module.exports, - { - // For all available options, see: - // https://github.com/getsentry/sentry-webpack-plugin#options - - // Suppresses source map uploading logs during build - silent: true, - org: "plastic-labs", - project: "tutor-gpt-web", - }, - { - // For all available options, see: - // https://docs.sentry.io/platforms/javascript/guides/nextjs/manual-setup/ - - // Upload a larger set of source maps for prettier stack traces (increases build time) - widenClientFileUpload: true, - - // Transpiles SDK to be compatible with IE11 (increases bundle size) - transpileClientSDK: true, - - // Routes browser requests to Sentry through a Next.js rewrite to circumvent ad-blockers (increases server load) - tunnelRoute: "/monitoring", - - // Hides source maps from generated client bundles - hideSourceMaps: true, - - // Automatically tree-shake Sentry logger statements to reduce bundle size - disableLogger: true, - } -); diff --git a/www/next.config.mjs b/www/next.config.mjs new file mode 100644 index 0000000..58448ea --- /dev/null +++ b/www/next.config.mjs @@ -0,0 +1,53 @@ +// import MillionLint from '@million/lint'; +import { withSentryConfig } from "@sentry/nextjs"; +// const { +// withSentryConfig +// } = require("@sentry/nextjs"); + +/** @type {import('next').NextConfig} */ +const nextConfig = { + output: "standalone" + // rewrites: async () => { + // return [ + // { + // source: "/api/:path*", + // destination: + // process.env.NODE_ENV === "development" + // ? "http://127.0.0.1:8000/api/:path*" + // : `${process.env.URL}/api/:path*`, + // }, + // ]; + // }, +}; +// const millionConfig = { +// auto: true, +// } +// export default MillionLint.next({ rsc: true })(nextConfig, millionConfig) + +// module.exports = nextConfig; + +// Injected content via Sentry wizard below + +export default withSentryConfig(nextConfig, { + // For all available options, see: + // https://github.com/getsentry/sentry-webpack-plugin#options + + // Suppresses source map uploading logs during build + silent: true, + org: "plastic-labs", + project: "tutor-gpt-web" +}, { + // For all available options, see: + // https://docs.sentry.io/platforms/javascript/guides/nextjs/manual-setup/ + + // Upload a larger set of source maps for prettier stack traces (increases build time) + widenClientFileUpload: true, + // Transpiles SDK to be compatible with IE11 (increases bundle size) + transpileClientSDK: true, + // Routes browser requests to Sentry through a Next.js rewrite to circumvent ad-blockers (increases server load) + tunnelRoute: "/monitoring", + // Hides source maps from generated client bundles + hideSourceMaps: true, + // Automatically tree-shake Sentry logger statements to reduce bundle size + disableLogger: true +}); diff --git a/www/package.json b/www/package.json index 8540a9a..7fe873e 100644 --- a/www/package.json +++ b/www/package.json @@ -9,41 +9,41 @@ "lint": "next lint" }, "dependencies": { - "@sentry/nextjs": "^7.69.0", + "@sentry/nextjs": "^7.116.0", "@supabase/auth-helpers-nextjs": "^0.7.4", - "@supabase/supabase-js": "^2.33.1", - "@types/node": "20.5.4", - "@types/react": "18.2.21", - "@types/react-dom": "18.2.7", - "@types/uuid": "^9.0.2", - "autoprefixer": "10.4.15", - "katex": "^0.16.8", - "next": "13.4.19", - "postcss": "8.4.28", - "posthog-js": "^1.79.0", - "react": "18.2.0", + "@supabase/supabase-js": "^2.43.4", + "katex": "^0.16.10", + "next": "14.2.3", + "posthog-js": "^1.135.2", + "react": "18.3.1", "react-dom": "18.2.0", - "react-icons": "^4.10.1", - "react-loading-skeleton": "^3.3.1", + "react-icons": "^4.12.0", + "react-loading-skeleton": "^3.4.0", "react-markdown": "^8.0.7", "react-syntax-highlighter": "^15.5.0", "react-toggle-dark-mode": "^1.1.1", "rehype-katex": "^7.0.0", "remark-math": "^6.0.0", - "sharp": "^0.32.5", - "sweetalert2": "^11.7.27", + "sharp": "^0.32.6", + "sweetalert2": "^11.11.0", "sweetalert2-react-content": "^5.0.7", - "swr": "^2.2.4", - "tailwindcss": "3.3.3", - "typescript": "5.1.6", - "uuid": "^9.0.0" + "swr": "^2.2.5", + "uuid": "^9.0.1" }, "devDependencies": { - "@types/react-syntax-highlighter": "^15.5.7", + "@types/node": "20.5.4", + "@types/react": "18.2.21", + "@types/react-dom": "18.2.7", + "@types/react-syntax-highlighter": "^15.5.13", + "@types/uuid": "^9.0.8", + "autoprefixer": "10.4.15", "encoding": "^0.1.13", - "eslint": "^8.49.0", - "eslint-config-next": "^13.4.19", - "prettier": "^3.0.3", - "prettier-plugin-tailwindcss": "^0.5.4" + "eslint": "^8.57.0", + "eslint-config-next": "^13.5.6", + "postcss": "8.4.28", + "prettier": "^3.2.5", + "prettier-plugin-tailwindcss": "^0.5.14", + "tailwindcss": "3.3.3", + "typescript": "5.1.6" } } diff --git a/www/pnpm-lock.yaml b/www/pnpm-lock.yaml new file mode 100644 index 0000000..46175b4 --- /dev/null +++ b/www/pnpm-lock.yaml @@ -0,0 +1,10360 @@ +lockfileVersion: '9.0' + +settings: + autoInstallPeers: true + excludeLinksFromLockfile: false + +importers: + + .: + dependencies: + '@sentry/nextjs': + specifier: ^7.116.0 + version: 7.116.0(encoding@0.1.13)(next@14.2.3(@babel/core@7.24.6)(react-dom@18.2.0(react@18.3.1))(react@18.3.1))(react@18.3.1) + '@supabase/auth-helpers-nextjs': + specifier: ^0.7.4 + version: 0.7.4(@supabase/supabase-js@2.43.4) + '@supabase/supabase-js': + specifier: ^2.43.4 + version: 2.43.4 + katex: + specifier: ^0.16.10 + version: 0.16.10 + next: + specifier: 14.2.3 + version: 14.2.3(@babel/core@7.24.6)(react-dom@18.2.0(react@18.3.1))(react@18.3.1) + posthog-js: + specifier: 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9d771c8..a3d33e2 100644 --- a/www/utils/api.ts +++ b/www/utils/api.ts @@ -58,6 +58,7 @@ export class Conversation { method: "POST", body: JSON.stringify({ conversation_id: this.conversationId, + user_id: this.api.userId, name, }), headers: { @@ -133,6 +134,7 @@ export class API { if (conversations.length === 0) { return [await this.new()]; } + // console.log(conversations) return conversations.map( (conversation) => new Conversation({ @@ -152,12 +154,12 @@ export class API { }) ); const { messages: rawMessages } = await req.json(); - // console.log(rawMessages); + console.log(rawMessages); if (!rawMessages) return []; const messages: Message[] = rawMessages.map((rawMessage: any) => { return { - text: rawMessage.data.content, - isUser: rawMessage.type === "human", + text: rawMessage.content, + isUser: rawMessage.isUser, }; });