mirror of
https://github.com/run-llama/llama-lab.git
synced 2026-07-01 20:14:02 -04:00
Logan
8bd7bd0129
* Refactor into python package * Add steamlit runner and example * Update frontpage readme * Update README * pin langchain + llama_index versions * Add some docstrings * Use dataclass instead of typed dict
88 lines
3.3 KiB
Python
88 lines
3.3 KiB
Python
import os
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import streamlit as st
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from langchain.agents import load_tools
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from langchain.chat_models import ChatOpenAI
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from langchain.llms import OpenAI
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from llama_agi.execution_agent import ToolExecutionAgent
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from llama_agi.runners import AutoStreamlitAGIRunner
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from llama_agi.task_manager import LlamaTaskManager
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from llama_agi.tools import search_notes, record_note, search_webpage
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from llama_index import ServiceContext, LLMPredictor
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st.set_page_config(layout="wide")
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st.header("🤖 Llama AGI 🦙")
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st.text("Use the setup tab to configure your LLM settings and initial objective+tasks.")
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st.text("Then use the Launch tab to run the AGI. Kill the process by clicking 'Stop' in the top right.")
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setup_tab, launch_tab = st.tabs(["Setup", "Launch"])
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with setup_tab:
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st.subheader("LLM Setup")
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col1, col2, col3 = st.columns(3)
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with col1:
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openai_api_key = st.text_input("Enter your OpenAI API key here", type="password")
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llm_name = st.selectbox(
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"Which LLM?", ["text-davinci-003", "gpt-3.5-turbo", "gpt-4"]
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)
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with col2:
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google_api_key = st.text_input("Enter your Google API key here", type="password")
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model_temperature = st.slider(
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"LLM Temperature", min_value=0.0, max_value=1.0, step=0.1, value=0.0
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)
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with col3:
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google_cse_id = st.text_input("Enter your Google CSE ID key here", type="password")
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max_tokens = st.slider(
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"LLM Max Tokens", min_value=256, max_value=1024, step=8, value=512
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)
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st.subheader("AGI Setup")
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objective = st.text_input("Objective:", value="Solve world hunger")
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initial_task = st.text_input("Initial Task:", value="Create a list of tasks")
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if st.button('Initialize?'):
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os.environ['OPENAI_API_KEY'] = openai_api_key
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os.environ['GOOGLE_API_KEY'] = google_api_key
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os.environ['GOOGLE_CSE_ID'] = google_cse_id
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if llm_name == "text-davinci-003":
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llm = OpenAI(
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temperature=model_temperature, model_name=llm_name, max_tokens=max_tokens
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)
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else:
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llm= ChatOpenAI(
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temperature=model_temperature, model_name=llm_name, max_tokens=max_tokens
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)
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service_context = ServiceContext.from_defaults(
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llm_predictor=LLMPredictor(llm=llm), chunk_size_limit=512
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)
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st.session_state['task_manager'] = LlamaTaskManager(
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[initial_task], task_service_context=service_context
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)
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tools = load_tools(["google-search-results-json"])
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tools = tools + [search_notes, record_note, search_webpage]
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st.session_state['execution_agent'] = ToolExecutionAgent(llm=llm, tools=tools)
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st.session_state['initial_task'] = initial_task
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st.session_state['objective'] = objective
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st.session_state['init'] = True
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st.success("Initialized!")
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with launch_tab:
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st.subheader("AGI Status")
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if st.button("Launch"):
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if st.session_state.get('init', False):
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# launch the auto runner
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with st.spinner("Running!"):
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runner = AutoStreamlitAGIRunner(st.session_state['task_manager'], st.session_state['execution_agent'])
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runner.run(st.session_state['objective'], st.session_state['initial_task'], 2)
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