diff --git a/README.md b/README.md index 3568c19a..0bea57b6 100644 --- a/README.md +++ b/README.md @@ -91,7 +91,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", @@ -157,7 +156,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", @@ -287,7 +285,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -397,7 +394,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -453,7 +449,6 @@ agent = Agent( max_loops=3, autosave=True, dashboard=False, - streaming_on=True, verbose=True, interactive=True, # Set the output type to the tool schema which is a BaseModel @@ -722,7 +717,6 @@ director = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -738,7 +732,6 @@ worker1 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -753,7 +746,6 @@ worker2 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -836,7 +828,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -850,7 +841,6 @@ accountant1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -864,7 +854,6 @@ accountant2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/docs/applications/business-analyst-agent.md b/docs/applications/business-analyst-agent.md index a28e6da8..d5d75125 100644 --- a/docs/applications/business-analyst-agent.md +++ b/docs/applications/business-analyst-agent.md @@ -129,7 +129,7 @@ agent = Agent( max_loops=1, autosave=True, dashboard=False, - streaming_on=True, + verbose=True, interactive=False, # Set the output type to the tool schema which is a BaseModel @@ -618,7 +618,6 @@ worker_agent = WorkerAgent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, diff --git a/docs/swarms/structs/agent.md b/docs/swarms/structs/agent.md index 39076a5e..e5f63cf6 100644 --- a/docs/swarms/structs/agent.md +++ b/docs/swarms/structs/agent.md @@ -48,7 +48,6 @@ Swarm Agent is a powerful autonomous agent framework designed to connect Languag | `preset_stopping_token` | A boolean indicating whether the agent should use a preset stopping token. | | `traceback` | An object used for traceback handling. | | `traceback_handlers` | A list of traceback handlers. | -| `streaming_on` | A boolean indicating whether the agent should stream its responses. | | `docs` | A list of document paths or contents to be ingested. | | `docs_folder` | The path to a folder containing documents to be ingested. | | `verbose` | A boolean indicating whether the agent should print verbose output. | diff --git a/docs/swarms/structs/agent_rearrange.md b/docs/swarms/structs/agent_rearrange.md index 2cfe5703..0f8c34e2 100644 --- a/docs/swarms/structs/agent_rearrange.md +++ b/docs/swarms/structs/agent_rearrange.md @@ -123,7 +123,6 @@ director = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -137,7 +136,6 @@ worker1 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -151,7 +149,6 @@ worker2 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/docs/swarms/structs/agent_registry.md b/docs/swarms/structs/agent_registry.md index 82afc1f1..b69be8bc 100644 --- a/docs/swarms/structs/agent_registry.md +++ b/docs/swarms/structs/agent_registry.md @@ -160,7 +160,6 @@ growth_agent1 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="marketing_specialist.json", stopping_token="Stop!", interactive=True, @@ -176,7 +175,6 @@ growth_agent2 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="sales_specialist.json", stopping_token="Stop!", interactive=True, @@ -192,7 +190,6 @@ growth_agent3 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="product_development_specialist.json", stopping_token="Stop!", interactive=True, @@ -208,7 +205,6 @@ growth_agent4 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="customer_service_specialist.json", stopping_token="Stop!", interactive=True, diff --git a/docs/swarms/structs/index.md b/docs/swarms/structs/index.md index 88eb756a..392fe999 100644 --- a/docs/swarms/structs/index.md +++ b/docs/swarms/structs/index.md @@ -241,7 +241,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -297,7 +296,6 @@ agent = Agent( max_loops=3, autosave=True, dashboard=False, - streaming_on=True, verbose=True, interactive=True, # Set the output type to the tool schema which is a BaseModel diff --git a/docs/swarms/structs/majorityvoting.md b/docs/swarms/structs/majorityvoting.md index 84ac02c8..8d072ee4 100644 --- a/docs/swarms/structs/majorityvoting.md +++ b/docs/swarms/structs/majorityvoting.md @@ -95,7 +95,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -112,7 +111,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -129,7 +127,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -165,7 +162,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -182,7 +178,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, @@ -199,7 +194,6 @@ agents = [ max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, diff --git a/docs/swarms/structs/moa.md b/docs/swarms/structs/moa.md index 6c0f5959..d196e4df 100644 --- a/docs/swarms/structs/moa.md +++ b/docs/swarms/structs/moa.md @@ -178,7 +178,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -192,7 +191,6 @@ accountant1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -206,7 +204,6 @@ accountant2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -235,7 +232,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -249,7 +245,6 @@ accountant1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -263,7 +258,6 @@ accountant2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -296,7 +290,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -310,7 +303,6 @@ accountant1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -324,7 +316,6 @@ accountant2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/docs/swarms/structs/round_robin_swarm.md b/docs/swarms/structs/round_robin_swarm.md index d788eb85..1c874a9e 100644 --- a/docs/swarms/structs/round_robin_swarm.md +++ b/docs/swarms/structs/round_robin_swarm.md @@ -66,7 +66,6 @@ sales_agent1 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) @@ -79,7 +78,6 @@ sales_agent2 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) @@ -92,7 +90,6 @@ sales_agent3 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) diff --git a/docs/swarms_cloud/agent_api.md b/docs/swarms_cloud/agent_api.md index 5d0fa9d0..8bab094f 100644 --- a/docs/swarms_cloud/agent_api.md +++ b/docs/swarms_cloud/agent_api.md @@ -68,7 +68,6 @@ This endpoint handles the completion request for an agent configured with the gi "dynamic_temperature_enabled": false, "dashboard": false, "verbose": false, - "streaming_on": true, "saved_state_path": null, "sop": null, "sop_list": null, @@ -93,7 +92,6 @@ This endpoint handles the completion request for an agent configured with the gi "dynamic_temperature_enabled": false, "dashboard": false, "verbose": false, - "streaming_on": true, "saved_state_path": null, "sop": null, "sop_list": null, @@ -140,7 +138,6 @@ class AgentInput(BaseModel): dynamic_temperature_enabled: bool = False dashboard: bool = False verbose: bool = False - streaming_on: bool = True saved_state_path: str = None sop: str = None sop_list: List[str] = None @@ -171,7 +168,6 @@ The `AgentInput` class defines the structure of the input data required to confi | `dynamic_temperature_enabled` | `bool` | `False` | Whether dynamic temperature adjustment is enabled. | | `dashboard` | `bool` | `False` | Whether to enable the dashboard feature. | | `verbose` | `bool` | `False` | Whether to enable verbose logging. | -| `streaming_on` | `bool` | `True` | Whether to enable streaming of responses. | | `saved_state_path` | `str` or `None` | `None` | Path to save the agent's state. | | `sop` | `str` or `None` | `None` | Standard operating procedures for the agent. | | `sop_list` | `List[str]` or `None` | `None` | A list of standard operating procedures. | diff --git a/example.py b/example.py index 5975b667..bb306c8f 100644 --- a/example.py +++ b/example.py @@ -15,7 +15,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/multi_agent_collab_demo.py b/multi_agent_collab_demo.py index 468ebc59..9da6603a 100644 --- a/multi_agent_collab_demo.py +++ b/multi_agent_collab_demo.py @@ -16,7 +16,6 @@ fiancial_analyst = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", @@ -50,7 +49,6 @@ fiancial_director = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/agents/agent_with_basemodel_output_type.py b/playground/agents/agent_with_basemodel_output_type.py index b1977d8e..3c40f8bc 100644 --- a/playground/agents/agent_with_basemodel_output_type.py +++ b/playground/agents/agent_with_basemodel_output_type.py @@ -41,7 +41,6 @@ agent = Agent( ), llm=OpenAIChat(), max_loops=1, - streaming_on=True, verbose=True, # List of schemas that the agent can handle list_base_models=[Schema], diff --git a/playground/agents/agents_and_memory/finance_agent_with_memory b/playground/agents/agents_and_memory/finance_agent_with_memory index 4064b303..f2e479c4 100644 --- a/playground/agents/agents_and_memory/finance_agent_with_memory +++ b/playground/agents/agents_and_memory/finance_agent_with_memory @@ -27,7 +27,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/agents/amazon_review_agent.py b/playground/agents/amazon_review_agent.py index 3fb3bc40..7d16c2bf 100644 --- a/playground/agents/amazon_review_agent.py +++ b/playground/agents/amazon_review_agent.py @@ -11,7 +11,6 @@ agent = Agent( ), autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, diff --git a/playground/agents/devin.py b/playground/agents/devin.py index cd264337..94c5d408 100644 --- a/playground/agents/devin.py +++ b/playground/agents/devin.py @@ -92,7 +92,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, diff --git a/playground/agents/first_agent_example.py b/playground/agents/first_agent_example.py index efd4310f..3f3dcf1d 100644 --- a/playground/agents/first_agent_example.py +++ b/playground/agents/first_agent_example.py @@ -16,7 +16,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/agents/gpt4o_mini_demo/financial_agent_gpt4o_mini.py b/playground/agents/gpt4o_mini_demo/financial_agent_gpt4o_mini.py index 76229cc2..b966fdbb 100644 --- a/playground/agents/gpt4o_mini_demo/financial_agent_gpt4o_mini.py +++ b/playground/agents/gpt4o_mini_demo/financial_agent_gpt4o_mini.py @@ -22,7 +22,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/agents/multion_examples/buy_abunch_of_cybertrucks.py b/playground/agents/multion_examples/buy_abunch_of_cybertrucks.py index c8238726..33196fb3 100644 --- a/playground/agents/multion_examples/buy_abunch_of_cybertrucks.py +++ b/playground/agents/multion_examples/buy_abunch_of_cybertrucks.py @@ -30,7 +30,6 @@ agent1 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, tools=[browser_automation], ) @@ -43,7 +42,6 @@ agent2 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, tools=[browser_automation], ) @@ -56,7 +54,6 @@ agent3 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, tools=[browser_automation], ) diff --git a/playground/agents/tools/devin_agent.py b/playground/agents/tools/devin_agent.py index b10d1c14..7515b26d 100644 --- a/playground/agents/tools/devin_agent.py +++ b/playground/agents/tools/devin_agent.py @@ -88,7 +88,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", interactive=True, diff --git a/playground/agents/tools/full_stack_agent.py b/playground/agents/tools/full_stack_agent.py index 0db12ad3..21ff11b0 100644 --- a/playground/agents/tools/full_stack_agent.py +++ b/playground/agents/tools/full_stack_agent.py @@ -20,7 +20,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", tools=[search_api], diff --git a/playground/demos/account_management_swarm_workshop/account_management.py b/playground/demos/account_management_swarm_workshop/account_management.py index 7928b954..fab20e61 100644 --- a/playground/demos/account_management_swarm_workshop/account_management.py +++ b/playground/demos/account_management_swarm_workshop/account_management.py @@ -147,7 +147,6 @@ def select_agent_and_send_task(name: str = None, task: str = None): max_loops=2, autosave=True, dashboard=False, - streaming_on=True, verbose=True, output_type=str, metadata_output_type="json", @@ -197,7 +196,6 @@ agent = Agent( interactive=True, autosave=True, dashboard=False, - streaming_on=True, # interactive=True, # tools=[search_weather], # or list of tools verbose=True, diff --git a/playground/demos/business_analysis_swarm/business-analyst-agent.ipynb b/playground/demos/business_analysis_swarm/business-analyst-agent.ipynb index bc4a9489..ad747772 100644 --- a/playground/demos/business_analysis_swarm/business-analyst-agent.ipynb +++ b/playground/demos/business_analysis_swarm/business-analyst-agent.ipynb @@ -189,7 +189,6 @@ " max_loops=1,\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " interactive=False,\n", " # Set the output type to the tool schema which is a BaseModel\n", @@ -803,7 +802,6 @@ " max_loops=\"auto\",\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", " interactive=True,\n", diff --git a/playground/demos/email_phiser/email_swarm.py b/playground/demos/email_phiser/email_swarm.py index 7ce62c42..bf5b3448 100644 --- a/playground/demos/email_phiser/email_swarm.py +++ b/playground/demos/email_phiser/email_swarm.py @@ -19,7 +19,6 @@ agent1 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, ) agent2 = Agent( @@ -32,7 +31,6 @@ agent2 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, ) agent3 = Agent( @@ -45,7 +43,6 @@ agent3 = Agent( metadata="json", function_calling_format_type="OpenAI", function_calling_type="json", - streaming_on=True, ) diff --git a/playground/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb b/playground/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb index 303f7978..6ce9d1a2 100644 --- a/playground/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb +++ b/playground/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb @@ -1,56 +1,39 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [], - "machine_shape": "hm", - "gpuType": "L4" - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" - }, "cells": [ { "cell_type": "markdown", + "metadata": { + "id": "Qf8eZIT71wba" + }, "source": [ "# Entry for SwarmsHackathon 2024\n", "\n" - ], - "metadata": { - "id": "Qf8eZIT71wba" - } + ] }, { "cell_type": "markdown", - "source": [ - "## Install Swarms" - ], "metadata": { "id": "-rBXNMWV4EWN" - } + }, + "source": [ + "## Install Swarms" + ] }, { "cell_type": "code", "execution_count": 1, "metadata": { - "id": "w4FoSEyP1q_x", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, + "id": "w4FoSEyP1q_x", "outputId": "ea6b15e7-c53c-47aa-86c6-b24d4aff041b" }, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Collecting swarms\n", " Downloading swarms-5.1.4-py3-none-any.whl (338 kB)\n", @@ -214,19 +197,19 @@ ] }, { - "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { + "id": "43b664ed28b2464da4f7c30cb0f343ce", "pip_warning": { "packages": [ "PIL", "asyncio" ] - }, - "id": "43b664ed28b2464da4f7c30cb0f343ce" + } } }, - "metadata": {} + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -235,60 +218,57 @@ }, { "cell_type": "markdown", - "source": [ - "Import keys" - ], "metadata": { "id": "QTMXxRxw7yR5" - } + }, + "source": [ + "Import keys" + ] }, { "cell_type": "code", - "source": [ - "from google.colab import userdata\n", - "anthropic_api_key = userdata.get('ANTHROPIC_API_KEY')" - ], + "execution_count": 1, "metadata": { "id": "lzSnwHw-7z8B" }, - "execution_count": 1, - "outputs": [] + "outputs": [], + "source": [ + "from google.colab import userdata\n", + "anthropic_api_key = userdata.get('ANTHROPIC_API_KEY')" + ] }, { "cell_type": "markdown", - "source": [ - "## Devin like" - ], "metadata": { "id": "eD0PkNm25SVT" - } + }, + "source": [ + "## Devin like" + ] }, { "cell_type": "markdown", - "source": [ - "This example requires the anthropic library which is not installed by default." - ], "metadata": { "id": "0Shm1vrS-YFZ" - } + }, + "source": [ + "This example requires the anthropic library which is not installed by default." + ] }, { "cell_type": "code", - "source": [ - "!pip install anthropic" - ], + "execution_count": 2, "metadata": { - "id": "aZG6eSjr-U7J", "colab": { "base_uri": "https://localhost:8080/" }, + "id": "aZG6eSjr-U7J", "outputId": "b5460b70-5db9-45d7-d66a-d2eb596b86b7" }, - "execution_count": 2, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Collecting anthropic\n", " Using cached anthropic-0.28.0-py3-none-any.whl (862 kB)\n", @@ -324,23 +304,26 @@ "Successfully installed anthropic-0.28.0 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 jiter-0.4.1\n" ] } + ], + "source": [ + "!pip install anthropic" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { - "id": "NyroG92H1m2G", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, + "id": "NyroG92H1m2G", "outputId": "69f4ff8b-39c7-41db-c876-4694336d812e" }, "outputs": [ { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:32:00.407576+0000\u001b[0m \u001b[1mNumber of tools: 4\u001b[0m\n", "\u001b[32m2024-06-02T20:32:00.407998+0000\u001b[0m \u001b[1mTools provided, Automatically converting to OpenAI function\u001b[0m\n", @@ -351,8 +334,8 @@ ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Initializing Autonomous Agent Devin...\n", "Autonomous Agent Activated.\n", @@ -506,9 +489,9 @@ ] }, { - "output_type": "error", "ename": "KeyboardInterrupt", "evalue": "Interrupted by user", + "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", @@ -613,7 +596,6 @@ " max_loops=\"auto\",\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", " interactive=True,\n", @@ -629,71 +611,7 @@ }, { "cell_type": "code", - "source": [ - "from swarms import Agent, AgentRearrange, rearrange\n", - "from typing import List\n", - "\n", - "llm = Anthropic(\n", - " temperature=0.1,\n", - " anthropic_api_key = anthropic_api_key\n", - ")\n", - "# Initialize the director agent\n", - "director = Agent(\n", - " agent_name=\"Director\",\n", - " system_prompt=\"Directs the tasks for the workers\",\n", - " llm=llm,\n", - " max_loops=1,\n", - " dashboard=False,\n", - " streaming_on=True,\n", - " verbose=True,\n", - " stopping_token=\"\",\n", - " state_save_file_type=\"json\",\n", - " saved_state_path=\"director.json\",\n", - ")\n", - "\n", - "# Initialize worker 1\n", - "worker1 = Agent(\n", - " agent_name=\"Worker1\",\n", - " system_prompt=\"Generates a transcript for a youtube video on what swarms are\",\n", - " llm=llm,\n", - " max_loops=1,\n", - " dashboard=False,\n", - " streaming_on=True,\n", - " verbose=True,\n", - " stopping_token=\"\",\n", - " state_save_file_type=\"json\",\n", - " saved_state_path=\"worker1.json\",\n", - ")\n", - "\n", - "# Initialize worker 2\n", - "worker2 = Agent(\n", - " agent_name=\"Worker2\",\n", - " system_prompt=\"Summarizes the transcript generated by Worker1\",\n", - " llm=llm,\n", - " max_loops=1,\n", - " dashboard=False,\n", - " streaming_on=True,\n", - " verbose=True,\n", - " stopping_token=\"\",\n", - " state_save_file_type=\"json\",\n", - " saved_state_path=\"worker2.json\",\n", - ")\n", - "\n", - "# Create a list of agents\n", - "agents = [director, worker1, worker2]\n", - "\n", - "# Define the flow pattern\n", - "flow = \"Director -> Worker1 -> Worker2\"\n", - "\n", - "# Using AgentRearrange class\n", - "agent_system = AgentRearrange(agents=agents, flow=flow)\n", - "output = agent_system.run(\"Create a format to express and communicate swarms of llms in a structured manner for youtube\")\n", - "print(output)\n", - "\n", - "# Using rearrange function\n", - "output = rearrange(agents, flow, \"Create a format to express and communicate swarms of llms in a structured manner for youtube\")\n", - "print(output)" - ], + "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -701,19 +619,18 @@ "id": "1j3RgVk1ol6G", "outputId": "a365266e-7c11-4c2d-9e31-19842483b165" }, - "execution_count": 7, "outputs": [ { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:34:54.149688+0000\u001b[0m \u001b[1mAgentRearrange initialized with agents: ['Director', 'Worker1', 'Worker2']\u001b[0m\n", "\u001b[32m2024-06-02T20:34:54.151361+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Director']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "Flow is valid.\n", "Initializing Autonomous Agent Director...\n", @@ -728,15 +645,15 @@ ] }, { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:35:02.526464+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Worker1']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "\n", "Llm Swarm Video Format\n", @@ -771,15 +688,15 @@ ] }, { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:35:07.814536+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Worker2']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "\n", "[Swarm Name] Llm Swarm\n", @@ -810,16 +727,16 @@ ] }, { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:35:11.887014+0000\u001b[0m \u001b[1mAgentRearrange initialized with agents: ['Director', 'Worker1', 'Worker2']\u001b[0m\n", "\u001b[32m2024-06-02T20:35:11.889429+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Director']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "\n", "[Swarm Name] Llm Swarm\n", @@ -868,15 +785,15 @@ ] }, { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:35:18.085897+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Worker1']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "\n", "Llm Swarm Video Format\n", @@ -912,15 +829,15 @@ ] }, { - "output_type": "stream", "name": "stderr", + "output_type": "stream", "text": [ "\u001b[32m2024-06-02T20:35:23.508710+0000\u001b[0m \u001b[1mRunning agents sequentially: ['Worker2']\u001b[0m\n" ] }, { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "\n", "[Swarm Name] Llm Swarm\n", @@ -993,7 +910,86 @@ "I think focusing on presenting uplifting dialogue between AI systems is a thoughtful idea. This script outlines a respectful approach. Please let me know if you would like me to modify or expand on anything! I'm happy to help further.\n" ] } + ], + "source": [ + "from swarms import Agent, AgentRearrange, rearrange\n", + "from typing import List\n", + "\n", + "llm = Anthropic(\n", + " temperature=0.1,\n", + " anthropic_api_key = anthropic_api_key\n", + ")\n", + "# Initialize the director agent\n", + "director = Agent(\n", + " agent_name=\"Director\",\n", + " system_prompt=\"Directs the tasks for the workers\",\n", + " llm=llm,\n", + " max_loops=1,\n", + " dashboard=False,\n", + " verbose=True,\n", + " stopping_token=\"\",\n", + " state_save_file_type=\"json\",\n", + " saved_state_path=\"director.json\",\n", + ")\n", + "\n", + "# Initialize worker 1\n", + "worker1 = Agent(\n", + " agent_name=\"Worker1\",\n", + " system_prompt=\"Generates a transcript for a youtube video on what swarms are\",\n", + " llm=llm,\n", + " max_loops=1,\n", + " dashboard=False,\n", + " verbose=True,\n", + " stopping_token=\"\",\n", + " state_save_file_type=\"json\",\n", + " saved_state_path=\"worker1.json\",\n", + ")\n", + "\n", + "# Initialize worker 2\n", + "worker2 = Agent(\n", + " agent_name=\"Worker2\",\n", + " system_prompt=\"Summarizes the transcript generated by Worker1\",\n", + " llm=llm,\n", + " max_loops=1,\n", + " dashboard=False,\n", + " verbose=True,\n", + " stopping_token=\"\",\n", + " state_save_file_type=\"json\",\n", + " saved_state_path=\"worker2.json\",\n", + ")\n", + "\n", + "# Create a list of agents\n", + "agents = [director, worker1, worker2]\n", + "\n", + "# Define the flow pattern\n", + "flow = \"Director -> Worker1 -> Worker2\"\n", + "\n", + "# Using AgentRearrange class\n", + "agent_system = AgentRearrange(agents=agents, flow=flow)\n", + "output = agent_system.run(\"Create a format to express and communicate swarms of llms in a structured manner for youtube\")\n", + "print(output)\n", + "\n", + "# Using rearrange function\n", + "output = rearrange(agents, flow, \"Create a format to express and communicate swarms of llms in a structured manner for youtube\")\n", + "print(output)" ] } - ] -} \ No newline at end of file + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuType": "L4", + "machine_shape": "hm", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/playground/demos/fintech/main.py b/playground/demos/fintech/main.py index 2a562afd..d82a0edd 100644 --- a/playground/demos/fintech/main.py +++ b/playground/demos/fintech/main.py @@ -9,7 +9,6 @@ agent_risk_analysis = Agent( max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -22,7 +21,6 @@ agent_compliance_check = Agent( max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -35,7 +33,6 @@ agent_report_generation = Agent( max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) diff --git a/playground/demos/jamba_swarm/main.ipynb b/playground/demos/jamba_swarm/main.ipynb index 1f54c5c6..61febe6e 100644 --- a/playground/demos/jamba_swarm/main.ipynb +++ b/playground/demos/jamba_swarm/main.ipynb @@ -201,7 +201,6 @@ " dynamic_temperature_enabled=True,\n", " dashboard=False,\n", " verbose=True,\n", - " streaming_on=True,\n", " # interactive=True, # Set to False to disable interactive mode\n", " saved_state_path=\"accounting_agent.json\",\n", " # tools=[calculate_profit, generate_report],\n", @@ -335,7 +334,6 @@ " dynamic_temperature_enabled=True,\n", " dashboard=False,\n", " verbose=True,\n", - " streaming_on=True,\n", " # interactive=True, # Set to False to disable interactive mode\n", " saved_state_path=f\"{name}_agent.json\",\n", " # tools=[calculate_profit, generate_report],\n", @@ -380,7 +378,6 @@ " dynamic_temperature_enabled=True,\n", " dashboard=False,\n", " verbose=True,\n", - " streaming_on=True,\n", " # interactive=True, # Set to False to disable interactive mode\n", " saved_state_path=\"boss_director_agent.json\",\n", " # tools=[calculate_profit, generate_report],\n", diff --git a/playground/demos/jamba_swarm/main.py b/playground/demos/jamba_swarm/main.py index 0286ade3..c2bcb93a 100644 --- a/playground/demos/jamba_swarm/main.py +++ b/playground/demos/jamba_swarm/main.py @@ -48,7 +48,6 @@ def create_and_execute_swarm( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path=f"{name}_agent.json", # tools=[calculate_profit, generate_report], @@ -81,7 +80,6 @@ planning_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="accounting_agent.json", # tools=[calculate_profit, generate_report], @@ -102,7 +100,6 @@ boss_agent_creator = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="boss_director_agent.json", # tools=[calculate_profit, generate_report], diff --git a/playground/demos/jamba_swarm/simple_jamba_swarm.py b/playground/demos/jamba_swarm/simple_jamba_swarm.py index a66fc9e6..eb06dc11 100644 --- a/playground/demos/jamba_swarm/simple_jamba_swarm.py +++ b/playground/demos/jamba_swarm/simple_jamba_swarm.py @@ -65,7 +65,6 @@ app_designer = Agent( llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, context_length=150000, state_save_file_type="json", @@ -79,7 +78,6 @@ feature_engineer = Agent( llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, context_length=150000, state_save_file_type="json", @@ -93,7 +91,6 @@ code_generator = Agent( llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, context_length=150000, state_save_file_type="json", @@ -107,7 +104,6 @@ quality_assurance = Agent( llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, context_length=150000, state_save_file_type="json", diff --git a/playground/demos/langchain_example/langchain_example.py b/playground/demos/langchain_example/langchain_example.py index 0e47684e..5252d8a6 100644 --- a/playground/demos/langchain_example/langchain_example.py +++ b/playground/demos/langchain_example/langchain_example.py @@ -20,7 +20,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, ) diff --git a/playground/demos/plant_biologist_swarm/agricultural_swarm.py b/playground/demos/plant_biologist_swarm/agricultural_swarm.py index e35b0048..58112da4 100644 --- a/playground/demos/plant_biologist_swarm/agricultural_swarm.py +++ b/playground/demos/plant_biologist_swarm/agricultural_swarm.py @@ -37,12 +37,10 @@ diagnoser_agent = Agent( llm=llm, max_loops=1, dashboard=False, - # streaming_on=True, # verbose=True, # saved_state_path="diagnoser.json", multi_modal=True, autosave=True, - streaming_on=True, ) # Initialize Harvester Agent @@ -52,12 +50,10 @@ harvester_agent = Agent( llm=llm, max_loops=1, dashboard=False, - # streaming_on=True, # verbose=True, # saved_state_path="harvester.json", multi_modal=True, autosave=True, - streaming_on=True, ) # Initialize Growth Predictor Agent @@ -67,12 +63,10 @@ growth_predictor_agent = Agent( llm=llm, max_loops=1, dashboard=False, - # streaming_on=True, # verbose=True, # saved_state_path="growth_predictor.json", multi_modal=True, autosave=True, - streaming_on=True, ) # Initialize Treatment Recommender Agent @@ -82,12 +76,10 @@ treatment_recommender_agent = Agent( llm=llm, max_loops=1, dashboard=False, - # streaming_on=True, # verbose=True, # saved_state_path="treatment_recommender.json", multi_modal=True, autosave=True, - streaming_on=True, ) # Initialize Disease Detector Agent @@ -97,12 +89,10 @@ disease_detector_agent = Agent( llm=llm, max_loops=1, dashboard=False, - # streaming_on=True, # verbose=True, # saved_state_path="disease_detector.json", multi_modal=True, autosave=True, - streaming_on=True, ) agents = [ diagnoser_agent, diff --git a/playground/demos/plant_biologist_swarm/using_concurrent_workflow.py b/playground/demos/plant_biologist_swarm/using_concurrent_workflow.py index 35b1374c..3dcb93a2 100644 --- a/playground/demos/plant_biologist_swarm/using_concurrent_workflow.py +++ b/playground/demos/plant_biologist_swarm/using_concurrent_workflow.py @@ -31,7 +31,6 @@ diagnoser_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="diagnoser.json", multi_modal=True, @@ -45,7 +44,6 @@ harvester_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="harvester.json", multi_modal=True, @@ -59,7 +57,6 @@ growth_predictor_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="growth_predictor.json", multi_modal=True, @@ -73,7 +70,6 @@ treatment_recommender_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="treatment_recommender.json", multi_modal=True, @@ -87,7 +83,6 @@ disease_detector_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="disease_detector.json", multi_modal=True, diff --git a/playground/demos/social_media_content_generators_swarm/agents.py b/playground/demos/social_media_content_generators_swarm/agents.py index 0ee20cff..afe2355d 100644 --- a/playground/demos/social_media_content_generators_swarm/agents.py +++ b/playground/demos/social_media_content_generators_swarm/agents.py @@ -110,7 +110,6 @@ twitter_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="twitter_agent.json", context_length=8192, # long_term_memory=memory, @@ -126,7 +125,6 @@ linkedin_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="linkedin_agent.json", context_length=8192, # long_term_memory=memory, @@ -142,7 +140,6 @@ instagram_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="instagram_agent.json", context_length=8192, # long_term_memory=memory, @@ -158,7 +155,6 @@ facebook_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="facebook_agent.json", context_length=8192, # long_term_memory=memory, @@ -174,7 +170,6 @@ tiktok_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="tiktok_agent.json", context_length=8192, # long_term_memory=memory, diff --git a/playground/demos/social_media_content_generators_swarm/social_media_swarm_agents.py b/playground/demos/social_media_content_generators_swarm/social_media_swarm_agents.py index ba18260d..63bbdb4e 100644 --- a/playground/demos/social_media_content_generators_swarm/social_media_swarm_agents.py +++ b/playground/demos/social_media_content_generators_swarm/social_media_swarm_agents.py @@ -237,7 +237,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -250,7 +249,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, tools=[post_to_twitter], dynamic_temperature_enabled=True, @@ -264,7 +262,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -278,7 +275,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -291,7 +287,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -304,7 +299,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -317,7 +311,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -330,7 +323,6 @@ for prompt in prompts: llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", @@ -347,7 +339,6 @@ final_agent = Agent( llm=model, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, dynamic_temperature_enabled=True, stopping_token="", diff --git a/playground/demos/society_of_agents/accountant_team.py b/playground/demos/society_of_agents/accountant_team.py index 882890b1..e74349ce 100644 --- a/playground/demos/society_of_agents/accountant_team.py +++ b/playground/demos/society_of_agents/accountant_team.py @@ -16,7 +16,6 @@ receipt_analyzer_agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", @@ -48,7 +47,6 @@ analyst_agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/demos/society_of_agents/hallucination_swarm.py b/playground/demos/society_of_agents/hallucination_swarm.py index 3f6764ba..169c9914 100644 --- a/playground/demos/society_of_agents/hallucination_swarm.py +++ b/playground/demos/society_of_agents/hallucination_swarm.py @@ -16,7 +16,6 @@ hallucinator = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="hallucinator_agent.json", stopping_token="Stop!", @@ -196,7 +195,6 @@ agent_evaluator = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="evaluator.json", stopping_token="Stop!", diff --git a/playground/demos/society_of_agents/probate_agent.py b/playground/demos/society_of_agents/probate_agent.py index 04660860..c9df8fa5 100644 --- a/playground/demos/society_of_agents/probate_agent.py +++ b/playground/demos/society_of_agents/probate_agent.py @@ -140,7 +140,6 @@ agent = Agent( # dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", diff --git a/playground/strcutured_output/output_validator.py b/playground/strcutured_output/output_validator.py index 9dc11a9a..da1471f0 100644 --- a/playground/strcutured_output/output_validator.py +++ b/playground/strcutured_output/output_validator.py @@ -57,7 +57,6 @@ agent = Agent( ), llm=OpenAIChat(), max_loops=1, - streaming_on=False, # TODO code breaks when this is True verbose=True, # List of schemas that the agent can handle list_base_models=[StockInfo], diff --git a/playground/strcutured_output/simple_structured_output.py b/playground/strcutured_output/simple_structured_output.py new file mode 100644 index 00000000..67c6e045 --- /dev/null +++ b/playground/strcutured_output/simple_structured_output.py @@ -0,0 +1,67 @@ +""" +* WORKING + +What this script does: +Structured output example + +Requirements: +Add the folowing API key(s) in your .env file: + - OPENAI_API_KEY (this example works best with Openai bc it uses openai function calling structure) + +Note: +If you are running playground examples in the project files directly (without swarms installed via PIP), +make sure to add the project root to your PYTHONPATH by running the following command in the project's root directory: + 'export PYTHONPATH=$(pwd):$PYTHONPATH' +""" + +################ Adding project root to PYTHONPATH ################################ +# If you are running playground examples in the project files directly, use this: + +import sys +import os + +sys.path.insert(0, os.getcwd()) + +################ Adding project root to PYTHONPATH ################################ + +from pydantic import BaseModel, Field +from swarms import Agent, OpenAIChat + +import agentops + +agentops.start_session() + +# Initialize the schema for the person's information +class PersonInfo(BaseModel): + """ + This is a pydantic model describing the format of a structured output + """ + name: str = Field(..., title="Name of the person") + agent: int = Field(..., title="Age of the person") + is_student: bool = Field(..., title="Whether the person is a student") + courses: list[str] = Field( + ..., title="List of courses the person is taking" + ) + +# Initialize the agent +agent = Agent( + agent_name="Person Information Generator", + system_prompt=( + "Generate a person's information" + ), + llm=OpenAIChat(), + max_loops=1, + verbose=True, + # List of pydantic models that the agent can use + list_base_models=[PersonInfo], + output_validation=True +) + +# Define the task to generate a person's information +task = "Generate a person's information" + +# Run the agent to generate the person's information +generated_data = agent.run(task) + +# Print the generated data +print(f"Generated data: {generated_data}") diff --git a/playground/structs/agent/basic_agent_with_azure_openai.py b/playground/structs/agent/basic_agent_with_azure_openai.py index 76135a9f..cd23e075 100644 --- a/playground/structs/agent/basic_agent_with_azure_openai.py +++ b/playground/structs/agent/basic_agent_with_azure_openai.py @@ -6,7 +6,6 @@ agent = Agent( max_loops="auto", autosave=True, dashboard=False, - streaming_on=True, verbose=True, ) diff --git a/playground/structs/agent/custom_model_with_agent.py b/playground/structs/agent/custom_model_with_agent.py index c0511bec..d63b9b59 100644 --- a/playground/structs/agent/custom_model_with_agent.py +++ b/playground/structs/agent/custom_model_with_agent.py @@ -18,7 +18,6 @@ agent = Agent( max_loops="auto", # Set the maximum number of loops to "auto" autosave=True, # Enable autosave feature dashboard=False, # Disable the dashboard - streaming_on=True, # Enable streaming verbose=True, # Enable verbose mode stopping_token="", # Set the stopping token to "" interactive=True, # Enable interactive mode diff --git a/playground/structs/agent/easy_example.py b/playground/structs/agent/easy_example.py index bebdb11a..a0062053 100644 --- a/playground/structs/agent/easy_example.py +++ b/playground/structs/agent/easy_example.py @@ -6,7 +6,6 @@ agent = Agent( max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, ) diff --git a/playground/structs/agent_registry.py b/playground/structs/agent_registry.py index cf8b6c99..35298f00 100644 --- a/playground/structs/agent_registry.py +++ b/playground/structs/agent_registry.py @@ -13,7 +13,6 @@ growth_agent1 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="marketing_specialist.json", stopping_token="Stop!", interactive=True, @@ -29,7 +28,6 @@ growth_agent2 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="sales_specialist.json", stopping_token="Stop!", interactive=True, @@ -45,7 +43,6 @@ growth_agent3 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="product_development_specialist.json", stopping_token="Stop!", interactive=True, @@ -61,7 +58,6 @@ growth_agent4 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, saved_state_path="customer_service_specialist.json", stopping_token="Stop!", interactive=True, diff --git a/playground/structs/multi_agent_collaboration/agent_rearrange.py b/playground/structs/multi_agent_collaboration/agent_rearrange.py index 8dc75fbf..02470e8c 100644 --- a/playground/structs/multi_agent_collaboration/agent_rearrange.py +++ b/playground/structs/multi_agent_collaboration/agent_rearrange.py @@ -9,7 +9,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -25,7 +24,6 @@ worker1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -40,7 +38,6 @@ worker2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/playground/structs/multi_agent_collaboration/agent_rearrange_human_in_loop.py b/playground/structs/multi_agent_collaboration/agent_rearrange_human_in_loop.py index 0cc59880..803811f6 100644 --- a/playground/structs/multi_agent_collaboration/agent_rearrange_human_in_loop.py +++ b/playground/structs/multi_agent_collaboration/agent_rearrange_human_in_loop.py @@ -9,7 +9,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -25,7 +24,6 @@ worker1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -40,7 +38,6 @@ worker2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/playground/structs/multi_agent_collaboration/round_robin_example.py b/playground/structs/multi_agent_collaboration/round_robin_example.py index 80a444ca..cda75d4a 100644 --- a/playground/structs/multi_agent_collaboration/round_robin_example.py +++ b/playground/structs/multi_agent_collaboration/round_robin_example.py @@ -8,7 +8,6 @@ director = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -22,7 +21,6 @@ worker1 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -36,7 +34,6 @@ worker2 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/playground/structs/multi_agent_collaboration/round_robin_swarm_example.py b/playground/structs/multi_agent_collaboration/round_robin_swarm_example.py index f3a463ad..d9d4fb07 100644 --- a/playground/structs/multi_agent_collaboration/round_robin_swarm_example.py +++ b/playground/structs/multi_agent_collaboration/round_robin_swarm_example.py @@ -15,7 +15,6 @@ sales_agent1 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) @@ -28,7 +27,6 @@ sales_agent2 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) @@ -41,7 +39,6 @@ sales_agent3 = Agent( autosave=True, dashboard=False, verbose=True, - streaming_on=True, context_length=1000, ) diff --git a/playground/structs/multi_agent_collaboration/society_of_agents.py b/playground/structs/multi_agent_collaboration/society_of_agents.py index a2a11322..8223a1cd 100644 --- a/playground/structs/multi_agent_collaboration/society_of_agents.py +++ b/playground/structs/multi_agent_collaboration/society_of_agents.py @@ -9,7 +9,6 @@ director = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -25,7 +24,6 @@ worker1 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -40,7 +38,6 @@ worker2 = Agent( llm=Anthropic(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/playground/structs/swarms/build_a_swarm.py b/playground/structs/swarms/build_a_swarm.py index c17469ed..69fa0da0 100644 --- a/playground/structs/swarms/build_a_swarm.py +++ b/playground/structs/swarms/build_a_swarm.py @@ -28,7 +28,6 @@ class MarketingSwarm(BaseSwarm): meax_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -41,7 +40,6 @@ class MarketingSwarm(BaseSwarm): max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -54,7 +52,6 @@ class MarketingSwarm(BaseSwarm): max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) diff --git a/playground/structs/swarms/geo_economic_forecast_docs/rag_doc_agent.py b/playground/structs/swarms/geo_economic_forecast_docs/rag_doc_agent.py index a39b57aa..140e8e4c 100644 --- a/playground/structs/swarms/geo_economic_forecast_docs/rag_doc_agent.py +++ b/playground/structs/swarms/geo_economic_forecast_docs/rag_doc_agent.py @@ -36,7 +36,6 @@ agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="accounting_agent.json", # tools=[calculate_profit, generate_report], @@ -67,7 +66,6 @@ forecaster_agent = Agent( dynamic_temperature_enabled=True, dashboard=False, verbose=True, - streaming_on=True, # interactive=True, # Set to False to disable interactive mode saved_state_path="forecaster_agent.json", # tools=[calculate_profit, generate_report], diff --git a/playground/structs/swarms/groupchat_example.py b/playground/structs/swarms/groupchat_example.py index ed49167e..84f1c243 100644 --- a/playground/structs/swarms/groupchat_example.py +++ b/playground/structs/swarms/groupchat_example.py @@ -100,7 +100,6 @@ agent = Agent( max_loops=1, autosave=False, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", tools=[terminal, browser, file_editor, create_file], @@ -118,7 +117,6 @@ agent_two = Agent( max_loops=1, autosave=False, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", tools=[terminal, browser, file_editor, create_file], diff --git a/playground/structs/swarms/mixture_of_agents.py b/playground/structs/swarms/mixture_of_agents.py index 2d57cb88..fa757f31 100644 --- a/playground/structs/swarms/mixture_of_agents.py +++ b/playground/structs/swarms/mixture_of_agents.py @@ -8,7 +8,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -22,7 +21,6 @@ accountant1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -36,7 +34,6 @@ accountant2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", diff --git a/playground/structs/swarms/swarm_example.py b/playground/structs/swarms/swarm_example.py index e6f5980b..c20425d2 100644 --- a/playground/structs/swarms/swarm_example.py +++ b/playground/structs/swarms/swarm_example.py @@ -14,7 +14,6 @@ class MySwarm(BaseSwarm): max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -25,7 +24,6 @@ class MySwarm(BaseSwarm): max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) @@ -36,7 +34,6 @@ class MySwarm(BaseSwarm): max_loops=1, autosave=True, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", ) diff --git a/playground/swarms_example.ipynb b/playground/swarms_example.ipynb index c0f52ed1..578b6cef 100644 --- a/playground/swarms_example.ipynb +++ b/playground/swarms_example.ipynb @@ -215,7 +215,6 @@ " max_loops=3,\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", " interactive=True, # Set to True\n", @@ -331,7 +330,6 @@ " max_loops=\"auto\",\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", " interactive=True,\n", @@ -397,7 +395,6 @@ " max_loops=3,\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " interactive=True,\n", " # Set the output type to the tool schema which is a BaseModel\n", @@ -1405,7 +1402,6 @@ " max_loops=1,\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", ")\n", @@ -1421,7 +1417,6 @@ " system_prompt=\"Summarize the transcript\",\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", ")\n", @@ -1437,7 +1432,6 @@ " system_prompt=\"Finalize the transcript\",\n", " autosave=True,\n", " dashboard=False,\n", - " streaming_on=True,\n", " verbose=True,\n", " stopping_token=\"\",\n", ")\n", diff --git a/swarms/cli/parse_yaml.py b/swarms/cli/parse_yaml.py index e7ba841f..fa6ed243 100644 --- a/swarms/cli/parse_yaml.py +++ b/swarms/cli/parse_yaml.py @@ -18,7 +18,6 @@ class AgentInput(BaseModel): dynamic_temperature_enabled: bool = False dashboard: bool = False verbose: bool = False - streaming_on: bool = True saved_state_path: Optional[str] = None sop: Optional[str] = None sop_list: Optional[List[str]] = None @@ -65,7 +64,6 @@ def parse_yaml_to_json(yaml_str: str) -> str: # dynamic_temperature_enabled: true # dashboard: true # verbose: true -# streaming_on: false # saved_state_path: "/path/to/state" # sop: "Standard operating procedure" # sop_list: ["step1", "step2"] @@ -99,7 +97,6 @@ def create_agent_from_yaml(yaml_path: str) -> None: ), dashboard=agent_config.get("dashboard", False), verbose=agent_config.get("verbose", False), - streaming_on=agent_config.get("streaming_on", True), saved_state_path=agent_config.get("saved_state_path"), retry_attempts=agent_config.get("retry_attempts", 3), context_length=agent_config.get("context_length", 8192), diff --git a/swarms/marketplace/agricultural_optimization.py b/swarms/marketplace/agricultural_optimization.py index 5949648d..58d33444 100644 --- a/swarms/marketplace/agricultural_optimization.py +++ b/swarms/marketplace/agricultural_optimization.py @@ -125,7 +125,6 @@ diagnoser_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="diagnoser.json", multi_modal=True, @@ -139,7 +138,6 @@ harvester_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="harvester.json", multi_modal=True, @@ -153,7 +151,6 @@ growth_predictor_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="growth_predictor.json", multi_modal=True, @@ -167,7 +164,6 @@ treatment_recommender_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="treatment_recommender.json", multi_modal=True, @@ -181,7 +177,6 @@ disease_detector_agent = Agent( llm=llm, max_loops=1, dashboard=False, - streaming_on=True, verbose=True, # saved_state_path="disease_detector.json", multi_modal=True, diff --git a/swarms/structs/agent.py b/swarms/structs/agent.py index 94b8eb8c..22f72e40 100644 --- a/swarms/structs/agent.py +++ b/swarms/structs/agent.py @@ -128,7 +128,6 @@ class Agent(BaseStructure): preset_stopping_token (bool): Enable preset stopping token traceback (Any): The traceback traceback_handlers (Any): The traceback handlers - streaming_on (bool): Enable streaming Methods: run: Run the agent @@ -214,7 +213,6 @@ class Agent(BaseStructure): preset_stopping_token: Optional[bool] = False, traceback: Optional[Any] = None, traceback_handlers: Optional[Any] = None, - streaming_on: Optional[bool] = False, docs: List[str] = None, docs_folder: Optional[str] = None, verbose: Optional[bool] = False, @@ -303,7 +301,6 @@ class Agent(BaseStructure): self.preset_stopping_token = preset_stopping_token self.traceback = traceback self.traceback_handlers = traceback_handlers - self.streaming_on = streaming_on self.docs = docs self.docs_folder = docs_folder self.verbose = verbose @@ -780,10 +777,7 @@ class Agent(BaseStructure): response = self.llm(*response_args, **kwargs) # Print - if self.streaming_on is True: - response = self.stream_response(response) - else: - self.printtier(response) + self.printtier(response) # Add the response to the memory self.short_memory.add( @@ -1334,7 +1328,6 @@ class Agent(BaseStructure): "preset_stopping_token": self.preset_stopping_token, "traceback": self.traceback, "traceback_handlers": self.traceback_handlers, - "streaming_on": self.streaming_on, "docs": self.docs, "docs_folder": self.docs_folder, "verbose": self.verbose, @@ -1747,35 +1740,6 @@ class Agent(BaseStructure): return response - def stream_response(self, response: str, delay: float = 0.001) -> None: - """ - Streams the response token by token. - - Args: - response (str): The response text to be streamed. - delay (float, optional): Delay in seconds between printing each token. Default is 0.1 seconds. - - Raises: - ValueError: If the response is not provided. - Exception: For any errors encountered during the streaming process. - - Example: - response = "This is a sample response from the API." - stream_response(response) - """ - # Check for required inputs - if not response: - raise ValueError("Response is required.") - - try: - # Stream and print the response token by token - for token in response.split(): - print(token, end=" ", flush=True) - time.sleep(delay) - print() # Ensure a newline after streaming - except Exception as e: - print(f"An error occurred during streaming: {e}") - def dynamic_context_window(self): """ dynamic_context_window essentially clears everything execep diff --git a/swarms/structs/agent_base_model.py b/swarms/structs/agent_base_model.py index 5310abad..0bdcccc2 100644 --- a/swarms/structs/agent_base_model.py +++ b/swarms/structs/agent_base_model.py @@ -37,7 +37,6 @@ class AgentSchemaBaseModel(BaseModel): preset_stopping_token: Optional[bool] = False traceback: Optional[Any] = None traceback_handlers: Optional[Any] = None - streaming_on: Optional[bool] = False docs: Optional[List[str]] = None docs_folder: Optional[str] = None verbose: Optional[bool] = True diff --git a/swarms/structs/swarm_load_balancer.py b/swarms/structs/swarm_load_balancer.py index 6dce48d7..53958fab 100644 --- a/swarms/structs/swarm_load_balancer.py +++ b/swarms/structs/swarm_load_balancer.py @@ -287,7 +287,6 @@ class AgentLoadBalancer(BaseSwarm): # max_loops="auto", # autosave=True, # dashboard=False, -# streaming_on=True, # verbose=True, # stopping_token="", # interactive=True, @@ -301,7 +300,6 @@ class AgentLoadBalancer(BaseSwarm): # max_loops="auto", # autosave=True, # dashboard=False, -# streaming_on=True, # verbose=True, # stopping_token="", # interactive=True, diff --git a/tests/structs/test_multi_agent_collab.py b/tests/structs/test_multi_agent_collab.py index b0e5e117..808d806a 100644 --- a/tests/structs/test_multi_agent_collab.py +++ b/tests/structs/test_multi_agent_collab.py @@ -15,7 +15,6 @@ director = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -31,7 +30,6 @@ worker1 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json", @@ -46,7 +44,6 @@ worker2 = Agent( llm=OpenAIChat(), max_loops=1, dashboard=False, - streaming_on=True, verbose=True, stopping_token="", state_save_file_type="json",