start of some start of agents work

agents.py

@@ -0,0 +1,50 @@
+from helper_functions import create_team_agent
+import models
+
+search_agent = create_team_agent(
+    models.gpt4o,
+    [tavily_tool],
+    "You are a research assistant who can search for up-to-date info using the tavily search engine.",
+    "Search",
+    ["Search", "PaperInformationRetriever"]
+)
+
+research_agent = create_team_agent(
+    models.gpt4o,
+    [retrieve_information],
+    "You are a research assistant who can provide specific information on the provided paper: 'murthy-loneliness.pdf'. You must only respond with information about the paper related to the request.",
+    "PaperInformationRetriever",
+    ["Search", "PaperInformationRetriever"]
+)
+
+doc_writer_agent = create_team_agent(
+    models.gpt4o,
+    [write_document, edit_document, read_document],
+    "You are an expert writing technical social media posts.",
+    "DocWriter",
+    ["DocWriter", "NoteTaker", "CopyEditor", "VoiceEditor"]
+)
+
+note_taking_agent = create_team_agent(
+    models.gpt4o,
+    [create_outline, read_document],
+    "You are an expert senior researcher tasked with writing a social media post outline and taking notes to craft a social media post.",
+    "NoteTaker",
+    ["DocWriter", "NoteTaker", "CopyEditor", "VoiceEditor"]
+)
+
+copy_editor_agent = create_team_agent(
+    models.gpt4o,
+    [write_document, edit_document, read_document],
+    "You are an expert copy editor who focuses on fixing grammar, spelling, and tone issues.",
+    "CopyEditor",
+    ["DocWriter", "NoteTaker", "CopyEditor", "VoiceEditor"]
+)
+
+voice_editor_agent = create_team_agent(
+    models.gpt4o,
+    [write_document, edit_document, read_document],
+    "You are an expert in crafting and refining the voice and tone of social media posts. You edit the document to ensure it has a consistent, professional, and engaging voice appropriate for social media platforms.",
+    "VoiceEditor",
+    ["DocWriter", "NoteTaker", "CopyEditor", "VoiceEditor"]
+)

constants.py

@@ -1,7 +1,12 @@
-OPENAI_API_KEY = "";
-ANTRHOPIC_API_KEY = "";
-LANGCHAIN_API_KEY = "";
-LANGCHAIN_TRACING_V2=True;
-LANGCHAIN_ENDPOINT='https://api.smith.langchain.com';
-QDRANT_API_KEY="";
-QDRANT_ENDPOINT="";
+import os
+from dotenv import load_dotenv, find_dotenv
+
+load_dotenv(find_dotenv())
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
+ANTRHOPIC_API_KEY = os.environ.get("ANTRHOPIC_API_KEY")
+LANGCHAIN_API_KEY = os.environ.get("LANGCHAIN_API_KEY")
+LANGCHAIN_TRACING_V2=True
+LANGCHAIN_ENDPOINT='https://api.smith.langchain.com'
+QDRANT_API_KEY = os.environ.get("QDRANT_API_KEY")
+QDRANT_ENDPOINT = os.environ.get("QDRANT_ENDPOINT")
+TAVILY_API_KEY = os.environ.get("TAVILY_API_KEY")

helper_functions.py

@@ -1,6 +1,12 @@
+from typing import List
 from langchain_community.document_loaders import PyMuPDFLoader, TextLoader, WebBaseLoader
+from langchain.agents import AgentExecutor, create_openai_functions_agent
 from langchain_community.vectorstores import Qdrant
+from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.language_models import BaseLanguageModel
 import os
+import functools
 
 def process_file(file_or_url):
     if isinstance(file_or_url, str) and file_or_url.startswith(('http://', 'https://')):
@@ -33,4 +39,69 @@ def add_to_qdrant(documents, embeddings, qdrant_client, collection_name):
         url=qdrant_client.url,
         prefer_grpc=True,
         collection_name=collection_name,
-    )
+    )
+
+def agent_node(state, agent, name):
+    result = agent.invoke(state)
+    return {"messages": [HumanMessage(content=result["output"], name=name)]}
+
+def create_team_agent(llm, tools, system_prompt, agent_name, team_members):
+    return create_agent(
+        llm,
+        tools,
+        f"{system_prompt}\nBelow are files currently in your directory:\n{{current_files}}",
+        team_members
+    )
+
+def create_agent_node(agent, name):
+    return functools.partial(agent_node, agent=agent, name=name)
+
+def add_agent_to_graph(graph, agent_name, agent_node):
+    graph.add_node(agent_name, agent_node)
+    graph.add_edge(agent_name, "supervisor")
+
+def create_team_supervisor(llm, team_description, team_members):
+    return create_team_supervisor(
+        llm,
+        f"You are a supervisor tasked with managing a conversation between the"
+        f" following workers: {', '.join(team_members)}. {team_description}"
+        f" When all workers are finished, you must respond with FINISH.",
+        team_members
+    )
+
+def enter_chain(message: str, members: List[str]):
+    results = {
+        "messages": [HumanMessage(content=message)],
+        "team_members": ", ".join(members),
+    }
+    return results
+
+def create_team_chain(graph, team_members):
+    return (
+        functools.partial(enter_chain, members=team_members)
+        | graph.compile()
+    )
+
+def create_agent(
+    llm: BaseLanguageModel,
+    tools: list,
+    system_prompt: str,
+) -> str:
+    """Create a function-calling agent and add it to the graph."""
+    system_prompt += ("\nWork autonomously according to your specialty, using the tools available to you."
+    " Do not ask for clarification."
+    " Your other team members (and other teams) will collaborate with you with their own specialties."
+    " You are chosen for a reason! You are one of the following team members: {{team_members}}.")
+    prompt = ChatPromptTemplate.from_messages(
+        [
+            (
+                "system",
+                system_prompt,
+            ),
+            MessagesPlaceholder(variable_name="messages"),
+            MessagesPlaceholder(variable_name="agent_scratchpad"),
+        ]
+    )
+    agent = create_openai_functions_agent(llm, tools, prompt)
+    executor = AgentExecutor(agent=agent, tools=tools)
+    return executor

set_constants.py

@@ -1,17 +0,0 @@
-import constants
-import os
-from dotenv import load_dotenv, find_dotenv
-
-load_dotenv(find_dotenv())
-
-current_directory = os.path.dirname(os.path.abspath(__file__))
-file_path = os.path.join(current_directory, 'constants.py')
-constantsFile = open(file_path, "w")
-constantsFile.write("OPENAI_API_KEY='" + os.getenv("OPENAI_API_KEY") + "';\n");
-constantsFile.write("ANTRHOPIC_API_KEY='" + os.getenv("ANTRHOPIC_API_KEY") + "';\n");
-constantsFile.write("LANGCHAIN_API_KEY='" + os.getenv("LANGCHAIN_API_KEY") + "';\n");
-constantsFile.write("LANGCHAIN_TRACING_V2=True;\n");
-constantsFile.write("LANGCHAIN_ENDPOINT='https://api.smith.langchain.com';\n");
-constantsFile.write("QDRANT_API_KEY='" + os.getenv("QDRANT_API_KEY") + "';\n");
-constantsFile.write("QDRANT_ENDPOINT='" + os.getenv("QDRANT_ENDPOINT") + "';\n");
-constantsFile.close()

tools.py

@@ -0,0 +1,45 @@
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.tools import tool
+
+tavily_tool = TavilySearchResults(max_results=5)
+
+@tool
+def create_outline(points: List[str], file_name: str) -> str:
+    """Create and save an outline."""
+    with (WORKING_DIRECTORY / file_name).open("w") as file:
+        for i, point in enumerate(points):
+            file.write(f"{i + 1}. {point}\n")
+    return f"Outline saved to {file_name}"
+
+@tool
+def read_document(file_name: str, start: Optional[int] = None, end: Optional[int] = None) -> str:
+    """Read the specified document."""
+    with (WORKING_DIRECTORY / file_name).open("r") as file:
+        lines = file.readlines()
+    if start is not None:
+        start = 0
+    return "\n".join(lines[start:end])
+
+@tool
+def write_document(content: str, file_name: str) -> str:
+    """Create and save a text document."""
+    with (WORKING_DIRECTORY / file_name).open("w") as file:
+        file.write(content)
+    return f"Document saved to {file_name}"
+
+@tool
+def edit_document(file_name: str, inserts: Dict[int, str] = {}) -> str:
+    """Edit a document by inserting text at specific line numbers."""
+    with (WORKING_DIRECTORY / file_name).open("r") as file:
+        lines = file.readlines()
+    
+    sorted_inserts = sorted(inserts.items())
+    for line_number, text in sorted_inserts:
+        if 1 <= line_number <= len(lines) + 1:
+            lines.insert(line_number - 1, text + "\n")
+        else:
+            return f"Error: Line number {line_number} is out of range."
+    
+    with (WORKING_DIRECTORY / file_name).open("w") as file:
+        file.writelines(lines)
+    return f"Document edited and saved to {file_name}"