streamlit_app.py

# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========

import os

import streamlit as st
from camel.configs import ChatGPTConfig
from camel.loaders.base_io import read_file
from camel.models.openai_model import OpenAIModel
from camel.types import ModelType

# Import functions and data related to the Streamlit user interface
from apps.streamlit_ui.multi_agent_communication_ui import main

# Set the title for the Streamlit app
st.title("🐫 CAMEL Multi-Agent")

# Create a sidebar with form elements
with st.sidebar:
    with st.form(key="form_1"):
        # Input field for API Keys
        openai_api_key = st.text_input(
            "OpenAI API Key", key="api_key_openai", type="password"
        )
        os.environ["OPENAI_API_KEY"] = openai_api_key

        # Enable functionality of the web browsing
        search_enabled = st.checkbox("Enable Web Browsing (it may take time)")
        if search_enabled:
            google_api_key = st.text_input(
                "Google API Key", key="api_key_google", type="password"
            )
            search_engine_id = st.text_input(
                "Search Engine ID", key="search_engine_id", type="password"
            )
            os.environ["GOOGLE_API_KEY"] = google_api_key
            os.environ["SEARCH_ENGINE_ID"] = search_engine_id

        # File uploader for users to upload a document
        uploaded_file = st.file_uploader(
            "Upload a file", type=("txt", "docx", "pdf", "json", "html")
        )

        # If a file is uploaded, extract content from it
        if uploaded_file:
            article = read_file(uploaded_file)
            normal_string = article.docs[0]["page_content"]

            # Create an instance of the OpenAI model
            my_openai_model = OpenAIModel(
                model_type=ModelType.GPT_3_5_TURBO,
                model_config_dict=ChatGPTConfig().__dict__,
            )

            # Create a task prompt based on the uploaded content
            messages_task_prompt = [
                {
                    "role": "system",
                    "content": """You are a helpful assistant to extract and
                     re-organize information from provided information.
                     below is the content for you:"""
                    + "\n"
                    + normal_string,
                },
                {
                    "role": "user",
                    "content": """Please create a prompt for the task to be
                     performed described in the given information.""",
                },
            ]

            # Get a response for the task prompt
            response_task_prompt = my_openai_model.run(messages=messages_task_prompt)[
                "choices"
            ][0]
            content_task_prompt = response_task_prompt["message"]["content"]

            # Create a context content based on the uploaded content
            messages_context_content = [
                {
                    "role": "system",
                    "content": """You are a helpful assistant to extract and
                     re-organize information from provided information.
                     below is the content for you:"""
                    + "\n"
                    + normal_string,
                },
                {
                    "role": "user",
                    "content": """Please extract the context content for the task to
                     be performed described in the given information.""",
                },
            ]

            # Get a response for the context content
            response_context_content = my_openai_model.run(
                messages=messages_context_content
            )["choices"][0]
            content_context_content = response_context_content["message"]["content"]

            # Set task prompt and context content as inputs in the form
            task_prompt = st.text_area(
                "Your task prompt extracted from the file", value=content_task_prompt
            )
            context_content = st.text_area(
                "Your context content extracted from the file",
                value=content_context_content,
            )
        else:
            # Set default values for task prompt and context content
            with open("examples/task_prompt_business_novel.txt", "r") as file:
                task_prompt_business_novel = file.read()
            with open("examples/task_prompt_business_novel.txt", "r") as file:
                context_content_business_novel = file.read()
            task_prompt = st.text_area(
                "Insert the task here", value=task_prompt_business_novel
            )
            context_text = st.text_area(
                "Insert the context here", value=context_content_business_novel
            )

        # Create a submit button in the form
        submit_button = st.form_submit_button(label="Submit")

# Check if all required inputs are provided and the submit button is clicked
if openai_api_key and task_prompt and context_text and submit_button:
    if search_enabled and (google_api_key is None or search_engine_id is None):
        st.warning(
            "Please provide Google API Key and Search Engine ID to "
            "enable the web browsing."
        )
        search_enabled = False

    # Clean the previous outputs
    with open("downloads/CAMEL_multi_agent_output.md", "w") as file:
        file.write("")

    # Call the 'main' function with the task prompt and context content
    num_roles = 5  # num_roles could be null or a number
    main(
        task_prompt=task_prompt,
        context_text=context_text,
        num_roles=num_roles,
        search_enabled=search_enabled,
    )

    # Export the outputs of the form
    with open("downloads/CAMEL_multi_agent_output.md", "r") as file:
        st.download_button(
            "Export the output to markdown",
            file,
            file_name="CAMEL_multi_agent_output.md",
        )