chore(versioning): versioning and linting changes

arcan/ai/agents/casters/researcher.py

@@ -27,14 +27,9 @@
 def search(query):
     url = "https://google.serper.dev/search"
 
-    payload = json.dumps({
-        "q": query
-    })
+    payload = json.dumps({"q": query})
 
-    headers = {
-        'X-API-KEY': serper_api_key,
-        'Content-Type': 'application/json'
-    }
+    headers = {"X-API-KEY": serper_api_key, "Content-Type": "application/json"}
 
     response = requests.request("POST", url, headers=headers, data=payload)
 
@@ -51,14 +46,12 @@ def scrape_website(objective: str, url: str):
     print("Scraping website...")
     # Define the headers for the request
     headers = {
-        'Cache-Control': 'no-cache',
-        'Content-Type': 'application/json',
+        "Cache-Control": "no-cache",
+        "Content-Type": "application/json",
     }
 
     # Define the data to be sent in the request
-    data = {
-        "url": url
-    }
+    data = {"url": url}
 
     # Convert Python object to JSON string
     data_json = json.dumps(data)
@@ -86,22 +79,24 @@ def summary(objective, content):
     llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-16k-0613")
 
     text_splitter = RecursiveCharacterTextSplitter(
-        separators=["\n\n", "\n"], chunk_size=10000, chunk_overlap=500)
+        separators=["\n\n", "\n"], chunk_size=10000, chunk_overlap=500
+    )
     docs = text_splitter.create_documents([content])
     map_prompt = """
     Write a summary of the following text for {objective}:
     "{text}"
     SUMMARY:
     """
     map_prompt_template = PromptTemplate(
-        template=map_prompt, input_variables=["text", "objective"])
+        template=map_prompt, input_variables=["text", "objective"]
+    )
 
     summary_chain = load_summarize_chain(
         llm=llm,
-        chain_type='map_reduce',
+        chain_type="map_reduce",
         map_prompt=map_prompt_template,
         combine_prompt=map_prompt_template,
-        verbose=True
+        verbose=True,
     )
 
     output = summary_chain.run(input_documents=docs, objective=objective)
@@ -111,8 +106,10 @@ def summary(objective, content):
 
 class ScrapeWebsiteInput(BaseModel):
     """Inputs for scrape_website"""
+
     objective: str = Field(
-        description="The objective & task that users give to the agent")
+        description="The objective & task that users give to the agent"
+    )
     url: str = Field(description="The url of the website to be scraped")
 
 
@@ -133,7 +130,7 @@ def _arun(self, url: str):
     Tool(
         name="Search",
         func=search,
-        description="useful for when you need to answer questions about current events, data. You should ask targeted questions"
+        description="useful for when you need to answer questions about current events, data. You should ask targeted questions",
     ),
     ScrapeWebsiteTool(),
 ]
@@ -158,7 +155,8 @@ def _arun(self, url: str):
 
 llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-16k-0613")
 memory = ConversationSummaryBufferMemory(
-    memory_key="memory", return_messages=True, llm=llm, max_token_limit=1000)
+    memory_key="memory", return_messages=True, llm=llm, max_token_limit=1000
+)
 
 agent = initialize_agent(
     tools,
@@ -201,5 +199,5 @@ class Query(BaseModel):
 def researchAgent(query: Query):
     query = query.query
     content = agent({"input": query})
-    actual_content = content['output']
-    return actual_content
+    actual_content = content["output"]
+    return actual_content

arcan/ai/graphs/__init__.py

@@ -31,7 +31,6 @@ def add(x: float, y: float) -> float:
 )
 
 
-
 import operator
 from typing import Annotated, Sequence, TypedDict
 
@@ -81,7 +80,7 @@ def call_tools(state):
 graph = workflow.compile()
 
 
-#%%
+# %%
 
 
 from typing import TypedDict, Annotated, List, Union
@@ -94,8 +93,10 @@ class AgentState(TypedDict):
     agent_out: Union[AgentAction, AgentFinish, None]
     intermediate_steps: Annotated[list[tuple[AgentAction, str]], operator.add]
 
+
 from langchain_core.tools import tool
 
+
 @tool("search")
 def search_tool(query: str):
     """Searches for information on the topic of artificial intelligence (AI).
@@ -104,16 +105,15 @@ def search_tool(query: str):
     # this is a "RAG" emulator
     return ehi_information
 
+
 @tool("final_answer")
-def final_answer_tool(
-    answer: str,
-    source: str
-):
+def final_answer_tool(answer: str, source: str):
     """Returns a natural language response to the user in `answer`, and a
     `source` which provides citations for where this information came from.
     """
     return ""
 
+
 import os
 from langchain.agents import create_openai_tools_agent
 from langchain import hub
@@ -126,39 +126,40 @@ def final_answer_tool(
 prompt = hub.pull("hwchase17/openai-functions-agent")
 
 query_agent_runnable = create_openai_tools_agent(
-    llm=llm,
-    tools=[final_answer_tool, search_tool],
-    prompt=prompt
+    llm=llm, tools=[final_answer_tool, search_tool], prompt=prompt
 )
 
 
 from langchain_core.agents import AgentFinish
 import json
 
+
 def run_query_agent(state: list):
     print("> run_query_agent")
     agent_out = query_agent_runnable.invoke(state)
     return {"agent_out": agent_out}
 
+
 def execute_search(state: list):
     print("> execute_search")
     action = state["agent_out"]
     tool_call = action[-1].message_log[-1].additional_kwargs["tool_calls"][-1]
-    out = search_tool.invoke(
-        json.loads(tool_call["function"]["arguments"])
-    )
+    out = search_tool.invoke(json.loads(tool_call["function"]["arguments"]))
     return {"intermediate_steps": [{"search": str(out)}]}
 
+
 def router(state: list):
     print("> router")
     if isinstance(state["agent_out"], list):
         return state["agent_out"][-1].tool
     else:
         return "error"
 
+
 # finally, we will have a single LLM call that MUST use the final_answer structure
 final_answer_llm = llm.bind_tools([final_answer_tool], tool_choice="final_answer")
 
+
 # this forced final_answer LLM call will be used to structure output from our
 # RAG endpoint
 def rag_final_answer(state: list):
@@ -177,6 +178,7 @@ def rag_final_answer(state: list):
     function_call = out.additional_kwargs["tool_calls"][-1]["function"]["arguments"]
     return {"agent_out": function_call}
 
+
 # we use the same forced final_answer LLM call to handle incorrectly formatted
 # output from our query_agent
 def handle_error(state: list):
@@ -207,7 +209,4 @@ def handle_error(state: list):
 
 runnable = graph.compile()
 
-out = runnable.invoke({
-    "input": "what is AI?",
-    "chat_history": []
-})
+out = runnable.invoke({"input": "what is AI?", "chat_history": []})

arcan/ai/interface/app.py

@@ -1,5 +1,3 @@
-
-
 from typing import Optional
 
 import chainlit as cl
@@ -42,7 +40,9 @@ def auth_callback(
 def get_runnable():
     from langserve import RemoteRunnable
 
-    spells_runnable = RemoteRunnable("https://api.arcanai.tech/spells/", headers={"arcanai_api_key": '1234'})
+    spells_runnable = RemoteRunnable(
+        "https://api.arcanai.tech/spells/", headers={"arcanai_api_key": "1234"}
+    )
     return spells_runnable
 
 
@@ -52,23 +52,23 @@ def get_runnable():
 # response
 
 
-
-
 @cl.on_message
 async def on_msg(msg: cl.Message):
     res = await get_runnable().ainvoke(
-        {"input": msg.content,},
-        config={"configurable": {"user_id": "broomva"},}
+        {
+            "input": msg.content,
+        },
+        config={
+            "configurable": {"user_id": "broomva"},
+        },
     )
-    await cl.Message(content=res['output']).send()
-
-
+    await cl.Message(content=res["output"]).send()
 
 
 # @cl.on_message
 # async def on_msg(msg: cl.Message):
 #     msg = cl.Message(content="")
-        
+
 #     async for chunk in get_runnable().astream(
 #         {"input": msg.content, "chat_history": []},
 #         # config=RunnableConfig(callbacks=[cl.LangchainCallbackHandler()]),
@@ -83,4 +83,4 @@ async def on_msg(msg: cl.Message):
 #     res = await agent.ainvoke(
 #         message.content
 #     )
-#     await cl.Message(content=res).send()
+#     await cl.Message(content=res).send()

arcan/api/__init__.py

@@ -6,13 +6,17 @@
 from typing import Annotated, Any, Callable, Dict, List, Optional, Union
 
 from dotenv import load_dotenv
-from fastapi import (Depends, FastAPI, Form, Header, HTTPException, Request,
-                     status)
+from fastapi import Depends, FastAPI, Form, Header, HTTPException, Request, status
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import RedirectResponse
+
 # %%
-from fastapi.security import (HTTPAuthorizationCredentials, HTTPBearer,
-                              OAuth2PasswordBearer, OAuth2PasswordRequestForm)
+from fastapi.security import (
+    HTTPAuthorizationCredentials,
+    HTTPBearer,
+    OAuth2PasswordBearer,
+    OAuth2PasswordRequestForm,
+)
 from langchain_community.chat_message_histories import FileChatMessageHistory
 from langchain_core import __version__
 from langchain_core.chat_history import BaseChatMessageHistory
@@ -33,9 +37,15 @@
 from arcan.ai.llm import LLM
 from arcan.api.auth import fetch_session_from_header
 from arcan.datamodel.engine import session_scope  # , session_scope_context
-from arcan.datamodel.user import (ACCESS_TOKEN_EXPIRE_MINUTES, TokenModel,
-                                  UserModel, UserRepository, UserService,
-                                  oauth2_scheme, pwd_context)
+from arcan.datamodel.user import (
+    ACCESS_TOKEN_EXPIRE_MINUTES,
+    TokenModel,
+    UserModel,
+    UserRepository,
+    UserService,
+    oauth2_scheme,
+    pwd_context,
+)
 
 # from arcan.spells.vector_search import (get_per_user_retriever,
 #                                         per_req_config_modifier, pgVectorStore)
@@ -189,8 +199,6 @@ async def login_for_access_token(
     )
 
 
-
-
 async def get_current_active_user_from_request(
     request: Request, session: Session = Depends(session_scope)
 ) -> UserModel:

arcan/datamodel/user.py

@@ -8,8 +8,7 @@
 from jose import JWTError, jwt
 from passlib.context import CryptContext
 from pydantic import BaseModel
-from sqlalchemy import (Boolean, Column, DateTime, ForeignKey, Integer, String,
-                        Text)
+from sqlalchemy import Boolean, Column, DateTime, ForeignKey, Integer, String, Text
 from sqlalchemy.orm import Session, relationship
 
 from arcan.datamodel.engine import Base, engine, session_scope