diff --git a/.env.example b/.env.example index 7f47d65a..d1c2b535 100644 --- a/.env.example +++ b/.env.example @@ -2,11 +2,19 @@ # ------------------------------------------------------------ MONGODB_CONNECTION_STRING=mongodb://127.0.0.1:27017/rowboat OPENAI_API_KEY= -AUTH0_SECRET= + + +# Uncomment to enable auth using Auth0 +# ------------------------------------------------------------ +# USE_AUTH=true + +# Even though auth is disabled by default, these test values are needed for the auth0 imports +# -------------------------------------------------------------------------------------------- +AUTH0_SECRET=test_secret AUTH0_BASE_URL=http://localhost:3000 -AUTH0_ISSUER_BASE_URL= -AUTH0_CLIENT_ID= -AUTH0_CLIENT_SECRET= +AUTH0_ISSUER_BASE_URL=https://test.com +AUTH0_CLIENT_ID=test +AUTH0_CLIENT_SECRET=test # Uncomment to enable RAG: # ------------------------------------------------------------ diff --git a/README.md b/README.md index 59ff1441..579d818b 100644 --- a/README.md +++ b/README.md @@ -1,27 +1,7 @@ # RowBoat [![RowBoat Logo](/assets/rb-logo.png)](https://www.rowboatlabs.com/) -This guide will help you set up and run the RowBoat applications locally using Docker. Please see our [docs](https://docs.rowboatlabs.com/) for more details. - -RowBoat offers several optional services that can be enabled using Docker Compose profiles. You can run multiple profiles simultaneously using: -```bash -docker compose --profile rag_urls_worker --profile chat_widget --profile tools_webhook up -d -``` -See the relevant sections below for details on each service. - -## Table of Contents -- [Prerequisites](#prerequisites) -- [Local Development Setup](#local-development-setup) - - [Python SDK](#option-1-python-sdk) - - [HTTP API](#option-2-http-api) -- [Optional Features](#enable-rag) - - [Enable RAG](#enable-rag) - - [URL Scraping](#url-scraping) - - [File Uploads](#file-uploads) - - [Enable Chat Widget](#enable-chat-widget) - - [Enable Tools Webhook](#enable-tools-webhook) -- [Troubleshooting](#troubleshooting) -- [Attribution](#attribution) +RowBoat is the fastest way to build production-ready multi-agent systems with OpenAI's Agents SDK. ## Prerequisites @@ -34,29 +14,15 @@ Before running RowBoat, ensure you have: - Obtain from your OpenAI account. 3. **MongoDB** - - **Option 1**: Use an existing MongoDB deployment with your connection string. - - **Option 2**: Install MongoDB locally: + - macOS (Homebrew) ```bash brew tap mongodb/brew brew install mongodb-community@8.0 brew services start mongodb-community@8.0 ``` + - Other platforms: Refer to the MongoDB documentation for details. -4. **Auth0 Account and Application Setup** - - **Create an Auth0 Account**: Sign up at [Auth0](https://auth0.com). - - **Create a New Application**: Choose "Regular Web Application", select "Next.js" as the application type, and name it "RowBoat". - - **Configure Application**: - - **Allowed Callback URLs**: In the Auth0 Dashboard, go to your "RowBoat" application settings and set `http://localhost:3000/api/auth/callback` as an Allowed Callback URL. - - **Get Credentials**: Collect the following from your Auth0 application settings: - - **Domain**: Copy your Auth0 domain (ensure you append `https://` to the Domain that the Auth0 dashboard shows you) - - **Client ID**: Your application's unique identifier - - **Client Secret**: Your application's secret key - - **Generate secret**: Generate a session encryption secret in your terminal and note the output for later: - ```bash - openssl rand -hex 32 - ``` - -## Local Development Setup +## Quickstart 1. **Clone the Repository** ```bash @@ -69,24 +35,11 @@ Before running RowBoat, ensure you have: ```bash cp .env.example .env ``` - - Update your `.env` file with the following configurations: + - Open the new .env file and update the OPENAI_API_KEY: ```ini # OpenAI Configuration OPENAI_API_KEY=your-openai-api-key - - # Auth0 Configuration - AUTH0_SECRET=your-generated-secret # Generated using openssl command - AUTH0_BASE_URL=http://localhost:3000 # Your application's base URL - AUTH0_ISSUER_BASE_URL=https://example.auth0.com # Your Auth0 domain (ensure it is prefixed with https://) - AUTH0_CLIENT_ID=your-client-id - AUTH0_CLIENT_SECRET=your-client-secret - - # MongoDB Configuration (choose one based on your setup) - # For local MongoDB - MONGODB_CONNECTION_STRING=mongodb://host.docker.internal:27017/rowboat - # or, for remote MongoDB - MONGODB_CONNECTION_STRING=mongodb+srv://:@.mongodb.net/rowboat ``` 3. **Start the App** @@ -97,82 +50,6 @@ Before running RowBoat, ensure you have: 4. **Access the App** - Visit [http://localhost:3000](http://localhost:3000). -5. **Interact with RowBoat** - - There are two ways to interact with RowBoat: - - ### Option 1: Python SDK - - For Python applications, we provide an official SDK for easier integration: - ```bash - pip install rowboat - ``` - - ```python - from rowboat import Client - - client = Client( - host="http://localhost:3000", - project_id="", - api_key="" # Generate this from /projects//config - ) - - # Simple chat interaction - messages = [{"role": "user", "content": "Tell me the weather in London"}] - response_messages, state = client.chat(messages=messages) - ``` - - For more details, see the [Python SDK documentation](./apps/python-sdk/README.md). - - ### Option 2: HTTP API - - You can use the API directly at [http://localhost:3000/api/v1/](http://localhost:3000/api/v1/) - - Project ID is available in the URL of the project page - - API Key can be generated from the project config page at `/projects//config` - - ```bash - curl --location 'http://localhost:3000/api/v1//chat' \ - --header 'Content-Type: application/json' \ - --header 'Authorization: Bearer ' \ - --data '{ - "messages": [ - { - "role": "user", - "content": "tell me the weather in london in metric units" - } - ] - }' - ``` - which gives: - ```json - { - "messages": [ - { - "role": "assistant", - "tool_calls": [ - { - "function": { - "arguments": "{\"location\":\"London\",\"units\":\"metric\"}", - "name": "weather_lookup_tool" - }, - "id": "call_r6XKuVxmGRogofkyFZIacdL0", - "type": "function" - } - ], - "agenticSender": "Example Agent", - "agenticResponseType": "internal" - } - ], - "state": { - // .. state data - } - } - ``` - -6. **Documentation** - - The documentation site is available at [http://localhost:8000](http://localhost:8000) - ## Enable RAG RowBoat supports RAG capabilities to enhance responses with your custom knowledge base. To enable RAG, you'll need: @@ -298,32 +175,6 @@ Enable file upload support (PDF, DOCX, TXT) for your knowledge base: After enabling RAG and starting the required workers, you can manage your knowledge base through the RowBoat UI at `/projects//sources`. -## Enable Chat Widget - -RowBoat provides an embeddable chat widget that you can add to any website. To enable and use the chat widget: - -1. **Generate JWT Secret** - Generate a secret for securing chat widget sessions: - ```bash - openssl rand -hex 32 - ``` - -2. **Update Environment Variables** - ```ini - USE_CHAT_WIDGET=true - CHAT_WIDGET_SESSION_JWT_SECRET= - ``` - -3. **Start the Chat Widget Service** - ```bash - docker compose --profile chat_widget up -d - ``` - -4. **Add Widget to Your Website** - You can find the chat-widget embed code under `/projects//config` - -After setup, the chat widget will appear on your website and connect to your RowBoat project. - ## Enable Tools Webhook RowBoat includes a built-in webhook service that allows you to implement custom tool functions. To use this feature: @@ -371,6 +222,135 @@ RowBoat includes a built-in webhook service that allows you to implement custom The webhook service handles all the security and parameter validation, allowing you to focus on implementing your tool logic. +## Enable Chat Widget + +RowBoat provides an embeddable chat widget that you can add to any website. To enable and use the chat widget: + +1. **Generate JWT Secret** + Generate a secret for securing chat widget sessions: + ```bash + openssl rand -hex 32 + ``` + +2. **Update Environment Variables** + ```ini + USE_CHAT_WIDGET=true + CHAT_WIDGET_SESSION_JWT_SECRET= + ``` + +3. **Start the Chat Widget Service** + ```bash + docker compose --profile chat_widget up -d + ``` + +4. **Add Widget to Your Website** + You can find the chat-widget embed code under `/projects//config` + +After setup, the chat widget will appear on your website and connect to your RowBoat project. + +## Enable Authentication + +By default, RowBoat runs without authentication. To enable user authentication using Auth0: + +1. **Auth0 Setup** + - **Create an Auth0 Account**: Sign up at [Auth0](https://auth0.com). + - **Create a New Application**: Choose "Regular Web Application", select "Next.js" as the application type, and name it "RowBoat". + - **Configure Application**: + - **Allowed Callback URLs**: In the Auth0 Dashboard, go to your "RowBoat" application settings and set `http://localhost:3000/api/auth/callback` as an Allowed Callback URL. + - **Get Credentials**: Collect the following from your Auth0 application settings: + - **Domain**: Copy your Auth0 domain (ensure you append `https://` to the Domain that the Auth0 dashboard shows you) + - **Client ID**: Your application's unique identifier + - **Client Secret**: Your application's secret key + - **Generate secret**: Generate a session encryption secret in your terminal and note the output for later: + ```bash + openssl rand -hex 32 + ``` + +2. **Update Environment Variables** + Add the following to your `.env` file: + ```ini + USE_AUTH=true + AUTH0_SECRET=your-generated-secret # Generated using openssl command + AUTH0_BASE_URL=http://localhost:3000 # Your application's base URL + AUTH0_ISSUER_BASE_URL=https://example.auth0.com # Your Auth0 domain (ensure it is prefixed with https://) + AUTH0_CLIENT_ID=your-client-id + AUTH0_CLIENT_SECRET=your-client-secret + ``` + +After enabling authentication, users will need to sign in to access the application. + +## Interact with RowBoat API + +There are two ways to interact with RowBoat's API: + +1. **Option 1: Python SDK** + + + For Python applications, we provide an official SDK for easier integration: + ```bash + pip install rowboat + ``` + + ```python + from rowboat import Client + + client = Client( + host="http://localhost:3000", + project_id="", + api_key="" # Generate this from /projects//config + ) + + # Simple chat interaction + messages = [{"role": "user", "content": "Tell me the weather in London"}] + response_messages, state = client.chat(messages=messages) + ``` + + For more details, see the [Python SDK documentation](./apps/python-sdk/README.md). + +1. **Option 2: HTTP API** + You can use the API directly at [http://localhost:3000/api/v1/](http://localhost:3000/api/v1/) + - Project ID is available in the URL of the project page + - API Key can be generated from the project config page at `/projects//config` + + ```bash + curl --location 'http://localhost:3000/api/v1//chat' \ + --header 'Content-Type: application/json' \ + --header 'Authorization: Bearer ' \ + --data '{ + "messages": [ + { + "role": "user", + "content": "tell me the weather in london in metric units" + } + ] + }' + ``` + which gives: + ```json + { + "messages": [ + { + "role": "assistant", + "tool_calls": [ + { + "function": { + "arguments": "{\"location\":\"London\",\"units\":\"metric\"}", + "name": "weather_lookup_tool" + }, + "id": "call_r6XKuVxmGRogofkyFZIacdL0", + "type": "function" + } + ], + "agenticSender": "Example Agent", + "agenticResponseType": "internal" + } + ], + "state": { + // .. state data + } + } + ``` + ## Troubleshooting 1. **MongoDB Connection Issues** diff --git a/apps/agents/poetry.lock b/apps/agents/poetry.lock deleted file mode 100644 index b960a8b4..00000000 --- a/apps/agents/poetry.lock +++ /dev/null @@ -1,1658 +0,0 @@ -# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. - 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{file = "wheel-0.44.0-py3-none-any.whl", hash = "sha256:2376a90c98cc337d18623527a97c31797bd02bad0033d41547043a1cbfbe448f"}, - {file = "wheel-0.44.0.tar.gz", hash = "sha256:a29c3f2817e95ab89aa4660681ad547c0e9547f20e75b0562fe7723c9a2a9d49"}, -] - -[package.extras] -test = ["pytest (>=6.0.0)", "setuptools (>=65)"] - -[metadata] -lock-version = "2.1" -python-versions = ">=3.10,<4.0" -content-hash = "ef220af6b184e760ccc9b45e26ec9f58a54cb9327c562a612798433a7f9c08e4" diff --git a/apps/agents/pyproject.toml b/apps/agents/pyproject.toml deleted file mode 100644 index 872c69a5..00000000 --- a/apps/agents/pyproject.toml +++ /dev/null @@ -1,67 +0,0 @@ -[tool.poetry] -name = "agents" -version = "0.1.0" -description = "RowBoat Labs Agent OS" -authors = ["Akhilesh "] -license = "MIT" -readme = "README.md" -homepage = "https://github.com/rowboatlabs/agents" -package-mode = false - -[tool.poetry.dependencies] -# Python -python = ">=3.10,<4.0" - -# Dependencies -annotated-types = "^0.7.0" -anyio = "^4.6.2" -beautifulsoup4 = "^4.12.3" -blinker = "^1.8.2" -certifi = "^2024.8.30" -charset-normalizer = "^3.4.0" -click = "^8.1.7" -distro = "^1.9.0" -dnspython = "^2.7.0" -et_xmlfile = "^2.0.0" -eval_type_backport = "^0.2.0" -firecrawl = "^1.4.0" -Flask = "^3.0.3" -h11 = "^0.14.0" -httpcore = "^1.0.6" -httpx = "^0.27.2" -idna = "^3.10" -itsdangerous = "^2.2.0" -Jinja2 = "^3.1.4" -jiter = "^0.6.1" -jsonpath-python = "^1.0.6" -lxml = "^5.3.0" -markdownify = "^0.13.1" -MarkupSafe = "^3.0.2" -mypy-extensions = "^1.0.0" -nest-asyncio = "^1.6.0" -numpy = "^2.1.2" -openai = "^1.52.2" -openpyxl = "^3.1.5" -pandas = "^2.2.3" -pydantic = "^2.9.2" -pydantic_core = "^2.23.4" -pymongo = "^4.10.1" -python-dateutil = "^2.8.2" -python-docx = "^1.1.2" -python-dotenv = "^1.0.1" -pytz = "^2024.2" -requests = "^2.32.3" -setuptools = "^75.1.0" -six = "^1.16.0" -sniffio = "^1.3.1" -soupsieve = "^2.6" -tabulate = "^0.9.0" -tqdm = "^4.66.5" -typing-inspect = "^0.9.0" -typing_extensions = "^4.12.2" -tzdata = "^2024.2" -urllib3 = "^2.2.3" -websockets = "^13.1" -Werkzeug = "^3.0.5" -wheel = "^0.44.0" -gunicorn = "^23.0.0" diff --git a/apps/agents/src/app/main.py b/apps/agents/src/app/main.py deleted file mode 100644 index 86cf9201..00000000 --- a/apps/agents/src/app/main.py +++ /dev/null @@ -1,106 +0,0 @@ -from flask import Flask, request, jsonify -from datetime import datetime -from functools import wraps -import os - -from src.graph.core import run_turn -from src.graph.tools import RAG_TOOL, CLOSE_CHAT_TOOL - -from src.utils.common import common_logger, read_json_from_file -logger = common_logger - -app = Flask(__name__) - -@app.route("/health", methods=["GET"]) -def health(): - return jsonify({"status": "ok"}) - -@app.route("/") -def home(): - return "Hello, World!" - -def require_api_key(f): - @wraps(f) - def decorated(*args, **kwargs): - auth_header = request.headers.get('Authorization') - if not auth_header or not auth_header.startswith('Bearer '): - return jsonify({'error': 'Missing or invalid authorization header'}), 401 - - token = auth_header.split('Bearer ')[1] - actual = os.environ.get('API_KEY', '').strip() - if actual and token != actual: - return jsonify({'error': 'Invalid API key'}), 403 - - return f(*args, **kwargs) - return decorated - -@app.route("/chat", methods=["POST"]) -@require_api_key -def chat(): - print('='*200) - logger.info('='*200) - try: - data = request.get_json() - print('Complete request:') - logger.info('Complete request') - print(data) - logger.info(data) - - print('-'*200) - logger.info('-'*200) - - start_time = datetime.now() - config = read_json_from_file("./configs/default_config.json") - - resp_messages, resp_tokens_used, resp_state = run_turn( - messages=data.get("messages", []), - start_agent_name=data.get("startAgent", ""), - agent_configs=data.get("agents", []), - tool_configs=data.get("tools", []), - localize_history=config.get("localize_history", True), - return_diff_messages=config.get("return_diff_messages", True), - prompt_configs=data.get("prompts", []), - start_turn_with_start_agent=config.get("start_turn_with_start_agent", False), - children_aware_of_parent=config.get("children_aware_of_parent", False), - parent_has_child_history=config.get("parent_has_child_history", True), - state=data.get("state", {}), - additional_tool_configs=[RAG_TOOL, CLOSE_CHAT_TOOL], - max_messages_per_turn=config.get("max_messages_per_turn", 2), - max_messages_per_error_escalation_turn=config.get("max_messages_per_error_escalation_turn", 2), - escalate_errors=config.get("escalate_errors", True), - max_overall_turns=config.get("max_overall_turns", 10) - ) - - print('-'*200) - logger.info('-'*200) - - out = { - "messages": resp_messages, - "tokens_used": resp_tokens_used, - "state": resp_state, - } - - print("Output: ") - logger.info(f"Output: ") - for k, v in out.items(): - print(f"{k}: {v}") - print('*'*200) - logger.info(f"{k}: {v}") - logger.info('*'*200) - - print("Processing time:") - print('='*200) - logger.info('='*200) - print(f"Processing time: {datetime.now() - start_time}") - logger.info(f"Processing time: {datetime.now() - start_time}") - - return jsonify(out) - - except Exception as e: - print(e) - logger.error(f"Error: {e}") - return jsonify({"error": str(e)}), 500 - -if __name__ == "__main__": - print("Starting Flask server...") - app.run(port=4040, debug=True) \ No newline at end of file diff --git a/apps/agents/src/graph/core.py b/apps/agents/src/graph/core.py deleted file mode 100644 index 074fe86b..00000000 --- a/apps/agents/src/graph/core.py +++ /dev/null @@ -1,504 +0,0 @@ -import os -import sys -from copy import deepcopy - -from src.swarm.types import Agent -from src.swarm.core import Swarm - -from .guardrails import post_process_response -from .tools import create_error_tool_call -from .types import AgentRole, PromptType, ErrorType -from .helpers.access import get_agent_data_by_name, get_agent_by_name, get_agent_config_by_name, get_tool_config_by_name, get_tool_config_by_type, get_external_tools, get_prompt_by_type, pop_agent_config_by_type, get_agent_by_type -from .helpers.transfer import create_transfer_function_to_agent, create_transfer_function_to_parent_agent -from .helpers.state import add_recent_messages_to_history, construct_state_from_response, reset_current_turn, reset_current_turn_agent_history -from .helpers.instructions import add_transfer_instructions_to_child_agents, add_transfer_instructions_to_parent_agents, add_rag_instructions_to_agent, add_error_escalation_instructions, get_universal_system_message, add_universal_system_message_to_agent -from .helpers.control import get_latest_assistant_msg, get_latest_non_assistant_messages, get_last_agent_name -from src.swarm.types import Response - -from src.utils.common import common_logger -logger = common_logger - -def order_messages(messages): - # Arrange keys in specified order - ordered_messages = [] - for msg in messages: - ordered = {} - msg = {k: v for k, v in msg.items() if v is not None} - # Add keys in specified order if they exist - for key in ['role', 'sender', 'content', 'created_at', 'timestamp']: - if key in msg: - ordered[key] = msg[key] - # Add remaining keys in alphabetical order - for key in sorted(msg.keys()): - if key not in ['role', 'sender', 'content', 'created_at', 'timestamp']: - ordered[key] = msg[key] - ordered_messages.append(ordered) - - return ordered_messages - -def clean_up_history(agent_data): - for data in agent_data: - data["history"] = order_messages(data["history"]) - return agent_data - -def clear_agent_fields(agent): - agent.children = {} - agent.parent_function = None - agent.candidate_parent_functions = {} - agent.child_functions = {} - if agent.most_recent_parent: - agent.history = [] - - return agent - -def get_agents(agent_configs, tool_configs, localize_history, available_tool_mappings, agent_data, start_turn_with_start_agent, children_aware_of_parent, universal_sys_msg): - # Create Agent objects - agents = [] - - if not isinstance(agent_configs, list): - raise ValueError("Agents config is not a list in get_agents") - - if not isinstance(tool_configs, list): - raise ValueError("Tools config is not a list in get_agents") - - for agent_config in agent_configs: - logger.debug(f"Processing config for agent: {agent_config['name']}") - - # Get tools for this agent - external_tools = [] - internal_tools = [] - candidate_parent_functions = {} - child_functions = {} - - logger.debug(f"Finding tools for agent {agent_config['name']}") - logger.debug(f"Agent {agent_config['name']} has {len(agent_config['tools'])} configured tools") - - if agent_config.get("hasRagSources", False): - rag_tool_name = get_tool_config_by_type(tool_configs, "rag").get("name", "") - agent_config["tools"].append(rag_tool_name) - agent_config = add_rag_instructions_to_agent(agent_config, rag_tool_name) - - for tool_name in agent_config["tools"]: - logger.debug(f"Looking for tool config: {tool_name}") - tool_config = get_tool_config_by_name(tool_configs, tool_name) - if tool_config: - if tool_name in available_tool_mappings: - internal_tools.append(available_tool_mappings[tool_name]) - else: - external_tools.append({ - "type": "function", - "function": tool_config - }) - logger.debug(f"Added tool {tool_name} to agent {agent_config['name']}") - else: - logger.warning(f"Tool {tool_name} not found in tool_configs") - - history = [] - this_agent_data = get_agent_data_by_name(agent_config["name"], agent_data) - if this_agent_data: - if localize_history: - history = this_agent_data.get("history", []) - - # Create agent - logger.debug(f"Creating Agent object for {agent_config['name']}") - logger.debug(f"Using model: {agent_config['model']}") - logger.debug(f"Number of tools being added: Internal - {len(internal_tools)} | External - {len(external_tools)}") - - try: - agent = Agent( - name=agent_config["name"], - type=agent_config.get("type", "default"), - instructions=agent_config["instructions"], - description=agent_config.get("description", ""), - internal_tools=internal_tools, - external_tools=external_tools, - candidate_parent_functions=candidate_parent_functions, - child_functions=child_functions, - model=agent_config["model"], - respond_to_user=agent_config.get("respond_to_user", False), - history=history, - children_names=agent_config.get("connectedAgents", []), - most_recent_parent=None - ) - - agents.append(agent) - logger.debug(f"Successfully created agent: {agent_config['name']}") - except Exception as e: - logger.error(f"Failed to create agent {agent_config['name']}: {str(e)}") - raise - - # Adding most recent parents to agents - for agent in agents: - most_recent_parent = None - this_agent_data = get_agent_data_by_name(agent.name, agent_data) - if this_agent_data: - most_recent_parent_name = this_agent_data.get("most_recent_parent_name", "") - if most_recent_parent_name: - most_recent_parent = get_agent_by_name(most_recent_parent_name, agents) if most_recent_parent_name else None - if most_recent_parent: - agent.most_recent_parent = most_recent_parent - - # Adding children agents to parent agents - logger.info("Adding children agents to parent agents") - for agent in agents: - agent.children = {agent_.name: agent_ for agent_ in agents if agent_.name in agent.children_names} - - # Generate transfer functions for transferring to children agents - logger.info("Generating transfer functions for transferring to children agents") - transfer_functions = { - agent.name: create_transfer_function_to_agent(agent) - for agent in agents - } - - # Add transfer functions for parents to transfer to children - logger.info("Adding transfer functions for parents to transfer to children") - for agent in agents: - for child in agent.children.values(): - agent.child_functions[child.name] = transfer_functions[child.name] - - # Add transfer-related instructions to parent agents - logger.info("Adding child transfer-related instructions to parent agents") - for agent in agents: - if agent.children: - agent = add_transfer_instructions_to_parent_agents(agent, agent.children, transfer_functions) - - # Generate and append duplicate transfer functions for children to transfer to parent agents - logger.info("Generating duplicate transfer functions for children to transfer to parent agents") - for agent in agents: - for child in agent.children.values(): - func = create_transfer_function_to_parent_agent( - parent_agent=agent, - children_aware_of_parent=children_aware_of_parent, - transfer_functions=transfer_functions - ) - child.candidate_parent_functions[agent.name] = func - - for agent in agents: - if agent.candidate_parent_functions and agent.type != "escalation": - agent = add_transfer_instructions_to_child_agents( - child=agent, - children_aware_of_parent=children_aware_of_parent - ) - - for agent in agents: - if agent.most_recent_parent: - assert agent.most_recent_parent.name in agent.candidate_parent_functions, f"Most recent parent {agent.most_recent_parent.name} not found in candidate parent functions for agent {agent.name}" - agent.parent_function = agent.candidate_parent_functions[agent.most_recent_parent.name] - - for agent in agents: - agent = add_universal_system_message_to_agent(agent, universal_sys_msg) - - return agents - -def check_request_validity(messages, agent_configs, tool_configs, prompt_configs, max_overall_turns): - - error_msg = "" - error_type = ErrorType.ESCALATE.value - - # Limits checks - external_messages_count = sum(1 for msg in messages if msg.get("response_type") == "external") - if external_messages_count >= max_overall_turns: - error_msg = f"Max overall turns reached: {max_overall_turns}" - - # Empty checks - if not messages: - error_msg = "Messages list is empty" - - # Empty checks --> Fatal - if not agent_configs: - error_msg = "Agent configs list is empty" - error_type = ErrorType.FATAL.value - - # Type checks --> Fatal - for arg in [messages, agent_configs, tool_configs, prompt_configs]: - if not isinstance(arg, list): - error_msg = f"{arg} is not a list" - error_type = ErrorType.FATAL.value - - # Post processing agent, guardrails and escalation agent check - there should be at max one agent with type "post_processing_agent", "guardrails_agent" and "escalation_agent" respectively --> Fatal - post_processing_agent_count = sum(1 for ac in agent_configs if ac.get("type", "") == AgentRole.POST_PROCESSING.value) - guardrails_agent_count = sum(1 for ac in agent_configs if ac.get("type", "") == AgentRole.GUARDRAILS.value) - escalation_agent_count = sum(1 for ac in agent_configs if ac.get("type", "") == AgentRole.ESCALATION.value) - if post_processing_agent_count > 1 or guardrails_agent_count > 1 or escalation_agent_count > 1: - error_msg = "Invalid post processing agent or guardrails agent count - expected at most 1" - error_type = ErrorType.FATAL.value - - # All agent config should have: name, instructions, model --> Fatal - for agent_config in agent_configs: - if not all(key in agent_config for key in ["name", "instructions", "model"]): - missing_keys = [key for key in ["name", "instructions", "tools", "model"] if key not in agent_config] - error_msg = f"Invalid agent config - missing keys: {missing_keys}" - error_type = ErrorType.FATAL.value - - # All tool configs should have: name, parameters --> Fatal - for tool_config in tool_configs: - if not all(key in tool_config for key in ["name", "parameters"]): - missing_keys = [key for key in ["name", "parameters"] if key not in tool_config] - error_msg = f"Invalid tool config - missing keys: {missing_keys}" - error_type = ErrorType.FATAL.value - - # Check for cycles in the agent config graph. Raise error if cycle is found, along with the agents involved in the cycle. - def find_cycles(agent_name, agent_configs, visited=None, path=None): - if visited is None: - visited = set() - if path is None: - path = [] - - visited.add(agent_name) - path.append(agent_name) - - agent_config = get_agent_config_by_name(agent_name, agent_configs) - if not agent_config: - return None - - for child_name in agent_config.get("connectedAgents", []): - if child_name in path: - cycle = path[path.index(child_name):] - cycle.append(child_name) - return cycle - - if child_name not in visited: - cycle = find_cycles(child_name, agent_configs, visited, path) - if cycle: - return cycle - - path.pop() - return None - - for agent_config in agent_configs: - if agent_config.get("name") in agent_config.get("connectedAgents", []): - error_msg = f"Cycle detected in agent config graph - agent {agent_config.get('name')} is connected to itself" - - cycle = find_cycles(agent_config.get("name"), agent_configs) - if cycle: - cycle_str = " -> ".join(cycle) - error_msg = f"Cycle detected in agent config graph: {cycle_str}" - - return error_msg, error_type - -def handle_error(error_tool_call, error_msg, return_diff_messages, messages, turn_messages, state, tokens_used): - resp_messages = turn_messages if return_diff_messages else messages + turn_messages - resp_messages.extend([create_error_tool_call(error_msg)]) - if error_tool_call: - return resp_messages, tokens_used, state - else: - raise ValueError(error_msg) - -def run_turn(messages, start_agent_name, agent_configs, tool_configs, available_tool_mappings={}, localize_history=True, return_diff_messages=True, prompt_configs=[], start_turn_with_start_agent=False, children_aware_of_parent=False, parent_has_child_history=True, state={}, additional_tool_configs=[], error_tool_call=True, max_messages_per_turn=10, max_messages_per_error_escalation_turn=4, escalate_errors=True, max_overall_turns=10): - - logger.info("Running stateless turn") - turn_messages = [] - tokens_used = {} - messages = order_messages(messages) - tool_configs = tool_configs + additional_tool_configs - - validation_error_msg, validation_error_type = check_request_validity( - messages=messages, - agent_configs=agent_configs, - tool_configs=tool_configs, - prompt_configs=prompt_configs, - max_overall_turns=max_overall_turns - ) - - if validation_error_msg and validation_error_type == ErrorType.FATAL.value: - logger.error(validation_error_msg) - return handle_error( - error_tool_call=error_tool_call, - error_msg=validation_error_msg, - return_diff_messages=return_diff_messages, - messages=messages, - turn_messages=turn_messages, - state=state, - tokens_used=tokens_used - ) - - post_processing_agent_config, agent_configs = pop_agent_config_by_type(agent_configs, AgentRole.POST_PROCESSING.value) - guardrails_agent_config, agent_configs = pop_agent_config_by_type(agent_configs, AgentRole.GUARDRAILS.value) - - latest_assistant_msg = get_latest_assistant_msg(messages) - universal_sys_msg = get_universal_system_message(messages) - latest_non_assistant_msgs = get_latest_non_assistant_messages(messages) - msg_type = latest_non_assistant_msgs[-1]["role"] - - last_agent_name = get_last_agent_name( - state=state, - agent_configs=agent_configs, - start_agent_name=start_agent_name, - msg_type=msg_type, - latest_assistant_msg=latest_assistant_msg, - start_turn_with_start_agent=start_turn_with_start_agent - ) - - logger.info("Localizing message history") - agent_data = state.get("agent_data", []) - if msg_type == "user": - messages = reset_current_turn(messages) - agent_data = reset_current_turn_agent_history(agent_data, [last_agent_name]) - agent_data = clean_up_history(agent_data) - agent_data = add_recent_messages_to_history( - recent_messages=latest_non_assistant_msgs, - last_agent_name=last_agent_name, - agent_data=agent_data, - messages=messages, - parent_has_child_history=parent_has_child_history - ) - state["agent_data"] = agent_data - - logger.info("Initializing agents") - all_agents = get_agents( - agent_configs=agent_configs, - tool_configs=tool_configs, - available_tool_mappings=available_tool_mappings, - agent_data=state.get("agent_data", []), - localize_history=localize_history, - start_turn_with_start_agent=start_turn_with_start_agent, - children_aware_of_parent=children_aware_of_parent, - universal_sys_msg=universal_sys_msg - ) - if not all_agents: - logger.error("No agents initialized") - return handle_error( - error_tool_call=error_tool_call, - error_msg="No agents initialized" - ) - - error_escalation_agent = deepcopy(get_agent_by_type(all_agents, AgentRole.ESCALATION.value)) - if not error_escalation_agent: - logger.error("Escalation agent not found") - return handle_error( - error_tool_call=error_tool_call, - error_msg="Escalation agent not found", - return_diff_messages=return_diff_messages, - messages=messages, - turn_messages=turn_messages, - state=state, - tokens_used=tokens_used - ) - - error_escalation_agent = clear_agent_fields(error_escalation_agent) - error_escalation_agent = add_error_escalation_instructions(error_escalation_agent) - - logger.info(f"Initialized {len(all_agents)} agents") - - logger.debug("Getting last agent") - last_agent = get_agent_by_name(last_agent_name, all_agents) - - if not last_agent: - logger.error("Last agent not found") - return handle_error( - error_tool_call=error_tool_call, - error_msg="Last agent not found", - return_diff_messages=return_diff_messages, - messages=messages, - state=state - ) - - external_tools = get_external_tools(tool_configs) - logger.info(f"Found {len(external_tools)} external tools") - - logger.debug("Initializing Swarm client") - swarm_client = Swarm() - - if not validation_error_msg: - response = swarm_client.run( - agent=last_agent, - messages=messages, - execute_tools=True, - external_tools=external_tools, - localize_history=localize_history, - parent_has_child_history=parent_has_child_history, - max_messages_per_turn=max_messages_per_turn, - tokens_used=tokens_used - ) - tokens_used = response.tokens_used - last_agent = response.agent - response.messages = order_messages(response.messages) - turn_messages.extend(response.messages) - logger.info(f"Completed run of agent: {last_agent.name}") - - if validation_error_msg and validation_error_type == ErrorType.ESCALATE.value or response.error_msg: - logger.info(f"Error raised in turn: {response.error_msg}") - response_sender_agent_name = response.agent.name - if escalate_errors and response_sender_agent_name != error_escalation_agent.name: - response = client.run( - agent=error_escalation_agent, - messages=[], - execute_tools=True, - external_tools=external_tools, - localize_history=False, - parent_has_child_history=False, - max_messages_per_turn=max_messages_per_error_escalation_turn, - tokens_used=tokens_used - ) - tokens_used = response.tokens_used - last_agent = response.agent - response.messages = order_messages(response.messages) - turn_messages.extend(response.messages) - logger.info(f"Completed run of escalation agent: {error_escalation_agent.name}") - - if response.error_msg: - logger.info(f"Error raised in escalation turn: {response.error_msg}") - return handle_error( - error_tool_call=error_tool_call, - error_msg=response.error_msg, - return_diff_messages=return_diff_messages, - messages=messages, - turn_messages=turn_messages, - state=state, - tokens_used=tokens_used - ) - else: - logger.info(f"Error raised in turn: {response.error_msg}") - return handle_error( - error_tool_call=error_tool_call, - error_msg=response.error_msg, - return_diff_messages=return_diff_messages, - messages=messages, - turn_messages=turn_messages, - state=state, - tokens_used=tokens_used - ) - - if post_processing_agent_config: - response = post_process_response( - messages=turn_messages, - post_processing_agent_name=post_processing_agent_config.get("name", "Post Processing agent"), - post_process_instructions=post_processing_agent_config.get("instructions", ""), - style_prompt=get_prompt_by_type(prompt_configs, PromptType.STYLE.value), - context='', - model=post_processing_agent_config.get("model", "gpt-4o"), - tokens_used=tokens_used, - last_agent=last_agent - ) - tokens_used = response.tokens_used - response.messages = order_messages(response.messages) - turn_messages.extend(response.messages) - logger.info("Response post-processed") - - else: - logger.info("No post-processing agent found. Duplicating last response and setting to external.") - duplicate_msg = deepcopy(turn_messages[-1]) - duplicate_msg["response_type"] = "external" - duplicate_msg["sender"] = duplicate_msg["sender"] + ' >> External' - response = Response( - messages=[duplicate_msg], - tokens_used=tokens_used, - agent=last_agent, - error_msg='' - ) - response.messages = order_messages(response.messages) - turn_messages.extend(response.messages) - logger.info("Last response duplicated and set to external") - - if guardrails_agent_config: - logger.info("Guardrails agent not implemented (ignoring)") - pass - - if not state or not state.get("last_agent_name"): - logger.error("State is empty or last agent name is not set") - raise ValueError("State is empty or last agent name is not set") - - response.messages = turn_messages if return_diff_messages else messages + turn_messages - response.tokens_used = tokens_used - new_state = construct_state_from_response(response, all_agents) - return response.messages, response.tokens_used, new_state \ No newline at end of file diff --git a/apps/agents/src/swarm/__init__.py b/apps/agents/src/swarm/__init__.py deleted file mode 100644 index a47b6210..00000000 --- a/apps/agents/src/swarm/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .core import Swarm -from .types import Agent, Response - -__all__ = ["Swarm", "Agent", "Response"] diff --git a/apps/agents/src/swarm/core.py b/apps/agents/src/swarm/core.py deleted file mode 100644 index 663e5894..00000000 --- a/apps/agents/src/swarm/core.py +++ /dev/null @@ -1,275 +0,0 @@ -# Standard library imports -import copy -import json -from collections import defaultdict -from typing import List, Callable, Union -from datetime import datetime - -# Package/library imports -from openai import OpenAI -import random - -# Local imports -from .util import * -from .types import ( - Agent, - AgentFunction, - ChatCompletionMessage, - ChatCompletionMessageToolCall, - Function, - Response, - Result, -) - -__CTX_VARS_NAME__ = "context_variables" - - -class Swarm: - def __init__(self, client=None): - if not client: - client = OpenAI(api_key=OPENAI_API_KEY) - self.client = client - self.history = defaultdict(lambda : []) - - def get_chat_completion( - self, - agent: Agent, - history: List, - context_variables: dict, - model_override: str, - stream: bool, - debug: bool, - temperature: float - ) -> ChatCompletionMessage: - context_variables = defaultdict(str, context_variables) - instructions = ( - agent.instructions(context_variables) - if callable(agent.instructions) - else agent.instructions - ) - messages = [{"role": "system", "content": instructions}] + history - debug_print(debug, "Getting chat completion for...:", messages) - - all_functions = list(agent.child_functions.values()) + ([agent.parent_function] if agent.parent_function else []) - all_tools = agent.external_tools + agent.internal_tools - funcs_and_tools = [function_to_json(f) for f in all_functions] + [t for t in all_tools] - # hide context_variables from model - for tool in funcs_and_tools: - params = tool["function"]["parameters"] - params["properties"].pop(__CTX_VARS_NAME__, None) - if __CTX_VARS_NAME__ in params.get("required", []): - params["required"].remove(__CTX_VARS_NAME__) - - create_params = { - "model": model_override or agent.model, - "messages": messages, - "tools": funcs_and_tools or None, - "tool_choice": agent.tool_choice, - "stream": stream, - "temperature": temperature - } - - if funcs_and_tools: - create_params["parallel_tool_calls"] = agent.parallel_tool_calls - - return self.client.chat.completions.create(**create_params) - - def handle_function_result(self, result, debug) -> Result: - # Check if result is already a Result instance - if isinstance(result, Result): - return result - - # Check if result is an Agent instance - if isinstance(result, Agent): - return Result( - value=json.dumps({"assistant": result.name}), - agent=result, - ) - - # Handle all other cases - try: - return Result(value=str(result)) - except Exception as e: - error_message = f"Failed to cast response to string: {result}. Make sure agent functions return a string or Result object. Error: {str(e)}" - debug_print(debug, error_message) - raise TypeError(error_message) - - def handle_function_calls( - self, - tool_calls: List[ChatCompletionMessageToolCall], - functions: List[AgentFunction], - context_variables: dict, - debug: bool, - ) -> Response: - function_map = {f.__name__: f for f in functions} - partial_response = Response( - messages=[], agent=None, context_variables={}) - - for tool_call in tool_calls: - name = tool_call.function.name - # handle missing tool case, skip to next tool - if name not in function_map: - debug_print(debug, f"Tool {name} not found in function map.") - partial_response.messages.append( - { - "role": "tool", - "tool_call_id": tool_call.id, - "tool_name": name, - "content": f"Error: Tool {name} not found.", - } - ) - continue - args = json.loads(tool_call.function.arguments) - debug_print( - debug, f"Processing tool call: {name} with arguments {args}") - - func = function_map[name] - # pass context_variables to agent functions - if __CTX_VARS_NAME__ in func.__code__.co_varnames: - args[__CTX_VARS_NAME__] = context_variables - raw_result = function_map[name](**args) - - result: Result = self.handle_function_result(raw_result, debug) - partial_response.messages.append( - { - "role": "tool", - "tool_call_id": tool_call.id, - "tool_name": name, - "content": result.value, - } - ) - partial_response.context_variables.update(result.context_variables) - if result.agent: - partial_response.agent = result.agent - - return partial_response - - def run( - self, - agent: Agent, - messages: List, - context_variables: dict = {}, - model_override: str = None, - stream: bool = False, - debug: bool = False, - max_messages_per_turn: int = 10, - execute_tools: bool = True, - external_tools: List[str] = [], - localize_history: bool = True, - parent_has_child_history: bool = True, - tokens_used: dict = {}, - temperature: float = 0.0 - ) -> Response: - - active_agent = agent - context_variables = copy.deepcopy(context_variables) - global_history = copy.deepcopy(messages) - init_len = len(messages) - - while len(global_history) - init_len < max_messages_per_turn and active_agent: - history = active_agent.history if localize_history else global_history - history = arrange_messages_keys_in_order(history) - - parent = active_agent.most_recent_parent - - children_names_backup, children_backup, child_functions_backup = copy.deepcopy(active_agent.children_names), copy.deepcopy(active_agent.children), copy.deepcopy(active_agent.child_functions) - - active_agent = check_and_remove_repeat_tool_call_to_child(active_agent, history) - - # get completion with current history, agent - completion = self.get_chat_completion( - agent=active_agent, - history=history, - context_variables=context_variables, - model_override=model_override, - stream=stream, - debug=debug, - temperature=temperature - ) - tokens_used = update_tokens_used(provider="openai", model=model_override or active_agent.model, tokens_used=tokens_used, completion=completion) - - # Restore children and child functions - active_agent.children_names, active_agent.children, active_agent.child_functions = children_names_backup, children_backup, child_functions_backup - - message = completion.choices[0].message - debug_print(debug, "Received completion:", message) - message.sender = active_agent.name - message_json = json.loads(message.model_dump_json()) - message_json = add_message_metadata(message_json, active_agent) - - if localize_history: - active_agent = update_histories(active_agent, message_json) - if parent and parent_has_child_history: - parent = update_histories(parent, message_json) - global_history.append(message_json) - - external_tool_calls = [] - internal_tool_calls = [] - - if message.tool_calls: - message_json["response_type"] = "internal" - for tool_call in message.tool_calls: - tool_name = tool_call.function.name - if tool_name in external_tools: - external_tool_calls.append(tool_call) - else: - internal_tool_calls.append(tool_call) - message.tool_calls = internal_tool_calls - - if not message.tool_calls or not execute_tools: - if external_tool_calls: - message.tool_calls.extend(external_tool_calls) - debug_print(debug, "Ending turn.") - break - - # handle function calls, updating context_variables, and switching agents - all_functions = list(active_agent.child_functions.values()) + ([active_agent.parent_function] if active_agent.parent_function else []) - partial_response = self.handle_function_calls( - message.tool_calls, all_functions, context_variables, debug - ) - for msg in partial_response.messages: - msg = add_message_metadata(msg, active_agent) - if localize_history: - active_agent = update_histories(active_agent, msg) - if parent and parent_has_child_history: - parent = update_histories(parent, msg) - - global_history.extend(partial_response.messages) - context_variables.update(partial_response.context_variables) - - # Parent to child transfer - if partial_response.agent: - prev_agent = active_agent - active_agent = partial_response.agent - - # Parent to child transfer - if active_agent.name in prev_agent.children_names: - active_agent.most_recent_parent = prev_agent - active_agent.parent_function = active_agent.candidate_parent_functions[active_agent.most_recent_parent.name] - if localize_history: - if not parent_has_child_history: - prev_agent.history = remove_irrelevant_messages(prev_agent.history) - new_active_agent_history = get_current_turn_messages(global_history, only_user = True) - active_agent.history.extend(new_active_agent_history) - - # Child to parent transfer - else: - assert parent == active_agent, "Parent and active agent do not match when active agent is not a child of previous agent" - child = prev_agent - if localize_history: - child.history = remove_irrelevant_messages(child.history) - - - return_messages = global_history[init_len:] - error_msg = "" - - if len(global_history) - init_len >= max_messages_per_turn: - error_msg = "Max messages per turn reached" - - return Response( - messages=return_messages, - agent=active_agent, - context_variables=context_variables, - error_msg=error_msg, - tokens_used=tokens_used - ) diff --git a/apps/agents/src/swarm/repl/__init__.py b/apps/agents/src/swarm/repl/__init__.py deleted file mode 100644 index 2a1cb40c..00000000 --- a/apps/agents/src/swarm/repl/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .repl import run_demo_loop diff --git a/apps/agents/src/swarm/repl/repl.py b/apps/agents/src/swarm/repl/repl.py deleted file mode 100644 index 50c3d0ee..00000000 --- a/apps/agents/src/swarm/repl/repl.py +++ /dev/null @@ -1,87 +0,0 @@ -import json - -from swarm import Swarm - - -def process_and_print_streaming_response(response): - content = "" - last_sender = "" - - for chunk in response: - if "sender" in chunk: - last_sender = chunk["sender"] - - if "content" in chunk and chunk["content"] is not None: - if not content and last_sender: - print(f"\033[94m{last_sender}:\033[0m", end=" ", flush=True) - last_sender = "" - print(chunk["content"], end="", flush=True) - content += chunk["content"] - - if "tool_calls" in chunk and chunk["tool_calls"] is not None: - for tool_call in chunk["tool_calls"]: - f = tool_call["function"] - name = f["name"] - if not name: - continue - print(f"\033[94m{last_sender}: \033[95m{name}\033[0m()") - - if "delim" in chunk and chunk["delim"] == "end" and content: - print() # End of response message - content = "" - - if "response" in chunk: - return chunk["response"] - - -def pretty_print_messages(messages) -> None: - for message in messages: - if message["role"] != "assistant": - continue - - # print agent name in blue - print(f"\033[94m{message['sender']}\033[0m:", end=" ") - - # print response, if any - if message["content"]: - print(message["content"]) - - # print tool calls in purple, if any - tool_calls = message.get("tool_calls") or [] - if len(tool_calls) > 1: - print() - for tool_call in tool_calls: - f = tool_call["function"] - name, args = f["name"], f["arguments"] - arg_str = json.dumps(json.loads(args)).replace(":", "=") - print(f"\033[95m{name}\033[0m({arg_str[1:-1]})") - - -def run_demo_loop( - starting_agent, context_variables=None, stream=False, debug=False -) -> None: - client = Swarm() - print("Starting Swarm CLI 🐝") - - messages = [] - agent = starting_agent - - while True: - user_input = input("\033[90mUser\033[0m: ") - messages.append({"role": "user", "content": user_input}) - - response = client.run( - agent=agent, - messages=messages, - context_variables=context_variables or {}, - stream=stream, - debug=debug, - ) - - if stream: - response = process_and_print_streaming_response(response) - else: - pretty_print_messages(response.messages) - - messages.extend(response.messages) - agent = response.agent diff --git a/apps/agents/src/swarm/types.py b/apps/agents/src/swarm/types.py deleted file mode 100644 index 1c6b87de..00000000 --- a/apps/agents/src/swarm/types.py +++ /dev/null @@ -1,54 +0,0 @@ -from __future__ import annotations - -from openai.types.chat import ChatCompletionMessage -from openai.types.chat.chat_completion_message_tool_call import ( - ChatCompletionMessageToolCall, - Function, -) -from typing import List, Callable, Union, Optional, Dict - -# Third-party imports -from pydantic import BaseModel - -AgentFunction = Callable[[], Union[str, "Agent", dict]] - -class Agent(BaseModel): - name: str = "Agent" - model: str = "gpt-4o" - type: str = "" - instructions: Union[str, Callable[[], str]] = "You are a helpful agent.", - description: str = "This is a helpful agent." - candidate_parent_functions: Dict[str, AgentFunction] = {} - parent_function: AgentFunction = None - child_functions: Dict[str, AgentFunction] = {} - internal_tools: List[Dict] = [] - external_tools: List[Dict] = [] - tool_choice: str = None - parallel_tool_calls: bool = True - respond_to_user: bool = True - history: List[Dict] = [] - children_names: List[str] = [] - children: Dict[str, "Agent"] = {} - most_recent_parent: Optional["Agent"] = None - parent: "Agent" = None - -class Response(BaseModel): - messages: List = [] - agent: Optional[Agent] = None - context_variables: dict = {} - error_msg: Optional[str] = "" - tokens_used: dict = {} - -class Result(BaseModel): - """ - Encapsulates the possible return values for an agent function. - - Attributes: - value (str): The result value as a string. - agent (Agent): The agent instance, if applicable. - context_variables (dict): A dictionary of context variables. - """ - - value: str = "" - agent: Optional[Agent] = None - context_variables: dict = {} \ No newline at end of file diff --git a/apps/agents/src/swarm/util.py b/apps/agents/src/swarm/util.py deleted file mode 100644 index d2a3fc2f..00000000 --- a/apps/agents/src/swarm/util.py +++ /dev/null @@ -1,175 +0,0 @@ -import inspect -import json -from datetime import datetime -import os -from dotenv import load_dotenv -from src.utils.common import read_json_from_file, get_api_key - -load_dotenv() -OPENAI_API_KEY = get_api_key("OPENAI_API_KEY") - -def debug_print(debug: bool, *args: str) -> None: - if not debug: - return - timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - message = " ".join(map(str, args)) - print(f"\033[97m[\033[90m{timestamp}\033[97m]\033[90m {message}\033[0m") - -def merge_fields(target, source): - for key, value in source.items(): - if isinstance(value, str): - target[key] += value - elif value is not None and isinstance(value, dict): - merge_fields(target[key], value) - - -def merge_chunk(final_response: dict, delta: dict) -> None: - delta.pop("role", None) - merge_fields(final_response, delta) - - tool_calls = delta.get("tool_calls") - if tool_calls and len(tool_calls) > 0: - index = tool_calls[0].pop("index") - merge_fields(final_response["tool_calls"][index], tool_calls[0]) - - -def function_to_json(func) -> dict: - """ - Converts a Python function into a JSON-serializable dictionary - that describes the function's signature, including its name, - description, and parameters. - - Args: - func: The function to be converted. - - Returns: - A dictionary representing the function's signature in JSON format. - """ - type_map = { - str: "string", - int: "integer", - float: "number", - bool: "boolean", - list: "array", - dict: "object", - type(None): "null", - } - - try: - signature = inspect.signature(func) - except ValueError as e: - raise ValueError( - f"Failed to get signature for function {func.__name__}: {str(e)}" - ) - - parameters = {} - for param in signature.parameters.values(): - try: - param_type = type_map.get(param.annotation, "string") - except KeyError as e: - raise KeyError( - f"Unknown type annotation {param.annotation} for parameter {param.name}: {str(e)}" - ) - parameters[param.name] = {"type": param_type} - - required = [ - param.name - for param in signature.parameters.values() - if param.default == inspect._empty - ] - - return { - "type": "function", - "function": { - "name": func.__name__, - "description": func.__doc__ or "", - "parameters": { - "type": "object", - "properties": parameters, - "required": required, - }, - }, - } - -def get_current_turn_messages(messages, only_user = False): - if only_user: - return [msg for msg in messages if msg.get("current_turn") and msg.get("role") == "user"] - else: - return [msg for msg in messages if msg.get("current_turn")] - -def arrange_messages_keys_in_order(messages): - """Arranges message keys in a specific order: id, role, sender, relevant_agents, content, created_at, timestamp, followed by rest alphabetically""" - key_order = ['role', 'sender', 'content', 'created_at'] - - def sort_keys(message): - # Create new dict with specified key order - ordered = {} - # Add keys in specified order if they exist - for key in key_order: - if key in message: - ordered[key] = message[key] - # Add remaining keys in alphabetical order - for key in sorted(message.keys()): - if key not in key_order: - ordered[key] = message[key] - return ordered - - return [sort_keys(message) for message in messages] - -def remove_irrelevant_messages(messages): - """Removes all messages from and including the latest user message""" - for i in range(len(messages)-1, -1, -1): - if messages[i].get("role") == "user": - return messages[:i] - return messages - -def update_histories(active_agent, message): - active_agent.history.append(message) - return active_agent - -def remove_none_fields(message): - return {k: v for k, v in message.items() if v is not None} - -def add_message_metadata(message, active_agent): - message = remove_none_fields(message) - message["created_at"] = datetime.now().isoformat() - message["current_turn"] = True - - if active_agent.respond_to_user: - message["response_type"] = "external" - else: - message["response_type"] = "internal" - - return message - -def check_and_remove_repeat_tool_call_to_child(agent, messages): - # If in the current turn, the most recent assistant message (need not be the last message overall, just needs to be the last message with role as assistant) is a tool call from a child agent, which transfers control to the agent using its parent function, then remove the tool call to transfer to that child again from this agent. This is to prevent back and forth between this agent and the child agent. - for message in reversed(messages): - if message.get("role") == "assistant" and message.get("sender") in agent.children_names and message.get("tool_calls"): - tool_call = message.get("tool_calls")[0] - child_agent = agent.children.get(message.get("sender"), None) - if not child_agent: - continue - child_agent_name = child_agent.name - if tool_call.get("function").get("name") == child_agent.parent_function: - agent.children_names.remove(child_agent_name) - agent.children.pop(child_agent_name) - agent.child_functions.pop(child_agent_name) - break - return agent - -def update_tokens_used(provider, model, tokens_used, completion): - provider_model = f"{provider}/{model}" - input_tokens = completion.usage.prompt_tokens - output_tokens = completion.usage.completion_tokens - - if provider_model not in tokens_used: - tokens_used[provider_model] = { - 'input_tokens': 0, - 'output_tokens': 0, - } - - tokens_used[provider_model]['input_tokens'] += input_tokens - tokens_used[provider_model]['output_tokens'] += output_tokens - - return tokens_used \ No newline at end of file diff --git a/apps/agents/tests/sample_requests/default_example.json b/apps/agents/tests/sample_requests/default_example.json deleted file mode 100644 index 88a07eae..00000000 --- a/apps/agents/tests/sample_requests/default_example.json +++ /dev/null @@ -1,424 +0,0 @@ -{ - "lastRequest": { - "messages": [ - { - "content": "hi", - "role": "user", - "sender": null, - "tool_calls": null, - "tool_call_id": null, - "tool_name": null - }, - { - "content": "Hello! How can I assist you today with your XYZ Bike?", - "role": "assistant", - "sender": "Main agent", - "tool_calls": null, - "tool_call_id": null, - "tool_name": null, - "response_type": "internal" - }, - { - "content": "Hello! How can I assist you today with your XYZ Bike?", - "role": "assistant", - "sender": "Main agent >> Post process", - "tool_calls": null, - "tool_call_id": null, - "tool_name": null, - "response_type": "external" - }, - { - "content": "i want to know about the range", - "role": "user", - "sender": null, - "tool_calls": null, - "tool_call_id": null, - "tool_name": null - }, - { - "content": null, - "role": "assistant", - "sender": "Main agent", - "tool_calls": [ - { - "function": { - "arguments": "{\"args\":\"\",\"kwargs\":\"\"}", - "name": "transfer_to_product_info_agent" - }, - "id": "call_0MJHin0XCMyEJjA7T2FTJLZL", - "type": "function" - } - ], - "tool_call_id": null, - "tool_name": null, - "response_type": "internal" - }, - { - "content": "{\"assistant\": \"Product info agent\"}", - "role": "tool", - "sender": null, - "tool_calls": null, - "tool_call_id": "call_0MJHin0XCMyEJjA7T2FTJLZL", - "tool_name": "transfer_to_product_info_agent" - }, - { - "content": null, - "role": "assistant", - "sender": "Product info agent", - "tool_calls": [ - { - "function": { - "arguments": "{\"question\":\"XYZ Bike travel range\"}", - "name": "getArticleInfo" - }, - "id": "call_CcNzb2N3lBt4JOCVrzyHdpdL", - "type": "function" - } - ], - "tool_call_id": null, - "tool_name": null, - "response_type": "internal" - }, - { - "content": "{\"results\":[{\"title\":\"XYZ Electric Bike\",\"content\":\"# XYZ Electric Bike\\n\\n### Transforming Transportation with the XYZ Electric Bike ### Revolutionizing Urban Mobility XYZ Electric Bike reimagines how we navigate cities, offering a seamless, stress-free alternative to traffic jams, pricey rideshares, rigid schedules, and the hassle of finding parking. --- #### **Instant Foldability** With a single press, XYZ's proprietary hinge mechanism folds the bike smoothly and securely in one swift motion. This innovation makes carrying and storing the bike effortless—outperforming the competition in both speed and ease of use. --- #### **Exceptional Handlebars** The sleek magnesium alloy handlebars are a marvel of design, housing intuitive controls for acceleration, braking, the horn, and LED lights, all within a streamlined, wire-free structure. Magnesium's lightweight properties—33% lighter than aluminum—make XYZ one of the most portable electric bikes available. --- #### **Unmatched Frame Design** Crafted with precision using TORAY carbon fiber, the frame achieves the perfect balance between strength and minimal weight. The material, meticulously layered for durability, is the same advanced composite used in aerospace engineering. --- #### **Impressive Range** Powered by premium electric batteries, XYZ bikes are designed for extended use with fast charging times. Their energy management system ensures long-lasting performance, providing ranges of up to 25 miles per charge, depending on riding conditions. --- #### **Dynamic Power** Equipped with dual motors delivering up to 1,000 watts at peak output, XYZ effortlessly handles steep inclines and challenging terrains. Rare-earth magnets and thermal regulation technology ensure high efficiency and reliability. --- #### **Puncture-Proof Tires** Say goodbye to flat tires. XYZ's solid rubber tires incorporate innovative air pockets for built-in shock absorption, delivering a smooth yet responsive ride across various surfaces. --- #### **Advanced Braking System** XYZ's braking system combines electronic anti-lock functionality with a user-friendly friction brake. Riders can enjoy a customizable braking experience, whether relying on fingertip controls or a traditional foot brake. --- #### **Durable and Comfortable Deck** The single-piece aluminum deck integrates a silicon surface for superior grip, eliminating unnecessary bulk or harsh finishes for a clean, modern look. --- #### **Invisible Kickstand** XYZ's custom-designed kickstand is seamlessly integrated, providing stability without disrupting the bike's sleek aesthetics. --- ### Models Comparison #### **XYZ Classic** - Price: $990 - Range: Up to 12 miles - Charge Time: 3.5 hours (80%) - Weight: 28.5 lbs #### **XYZ Voyager** - Price: $1,490 - Range: Up to 25 miles - Charge Time: 2 hours (80%) - Weight: 29.6 lbs - Features: App integration for enhanced control and ride stats --- XYZ Electric Bike is not just a mode of transport—it's the future of urban mobility, combining cutting-edge technology, top-tier materials, and unparalleled design for a ride that's as stylish as it is functional.\"}]}", - "role": "tool", - "sender": null, - "tool_calls": null, - "tool_call_id": "call_CcNzb2N3lBt4JOCVrzyHdpdL", - "tool_name": "getArticleInfo" - } - ], - "state": { - "agent_data": [ - { - "child_functions": [ - "transfer_to_product_info_agent", - "transfer_to_delivery_info_agent", - "transfer_to_subscriptions_agent" - ], - "external_tools": [], - "history": [ - { - "content": "hi", - "current_turn": false, - "role": "user" - }, - { - "content": "Hello! How can I assist you today with your XYZ Bike?", - "created_at": "2024-12-18T07:45:03.670088", - "current_turn": false, - "response_type": "internal", - "role": "assistant", - "sender": "Main agent" - }, - { - "content": "i want to know about the range", - "current_turn": true, - "role": "user" - }, - { - "created_at": "2024-12-18T07:45:13.240846", - "current_turn": true, - "response_type": "internal", - "role": "assistant", - "sender": "Main agent", - "tool_calls": [ - { - "function": { - "arguments": "{\"args\":\"\",\"kwargs\":\"\"}", - "name": "transfer_to_product_info_agent" - }, - "id": "call_0MJHin0XCMyEJjA7T2FTJLZL", - "type": "function" - } - ] - }, - { - "content": "{\"assistant\": \"Product info agent\"}", - "created_at": "2024-12-18T07:45:13.241184", - "current_turn": true, - "response_type": "internal", - "role": "tool", - "tool_call_id": "call_0MJHin0XCMyEJjA7T2FTJLZL", - "tool_name": "transfer_to_product_info_agent" - }, - { - "created_at": "2024-12-18T07:45:13.821351", - "current_turn": true, - "response_type": "internal", - "role": "assistant", - "sender": "Product info agent", - "tool_calls": [ - { - "function": { - "arguments": "{\"question\":\"XYZ Bike travel range\"}", - "name": "getArticleInfo" - }, - "id": "call_CcNzb2N3lBt4JOCVrzyHdpdL", - "type": "function" - } - ] - } - ], - "instructions": "Role:\nYou are a customer support agent for XYZ Bikes. Your primary task is to facilitate conversations by passing control to specialized worker agents when needed.\n\n---\n\nTasks to Follow:\n- Engage in small talk if no specific question is asked.\n- Pass control to the appropriate worker agents for specialized conversations.\n\n---\n\nSmall Talk:\nYou are welcome to engage in basic small talk to build rapport.\n\n---\n\nExamples:\n\n---\nIn Scope Example 1:\nUser: How are you?\nAnswer: \"I'm doing well, thank you! How can I assist you today?\"\n\n---\nIn Scope Example 2:\nUser: What can you do?\nAnswer: \"I can help with customer support-related issues for XYZ Bikes. Let me know if you have any questions.\"\n\n---\nIn Scope Example 3:\nUser: I want a XYZ Bike.\nAnswer: \"What would you like to know about XYZ Bikes?\"\n\n---\nPass Control Example 1:\nUser: Tell me about the product features.\nAction: Pass control to the Product info agent.\n\n---\nPass Control Example 2:\nUser: Where is my scooter?\nAction: Pass control to the Delivery info agent.\n\n---\nPass Control Example 3:\nUser: I need help with my return.\nAction: Pass control to the Returns agent.\n\n---\nPass Control Example 4:\nUser: How does the Unagi subscription work?\nAction: Pass control to the Subscriptions agent.\n\n---\n✅ Dos:\n- Engage in small talk when necessary.\n- Pass control to the appropriate agent based on the user's query.\n\n---\n❌ Don'ts:\n- Do not focus excessively on greetings during ongoing conversations.\n- Do not continue the conversation if you suspect the user is confused or uninterested in Unagi support.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Main agent", - "parent_function": null - }, - { - "child_functions": [], - "external_tools": [ - "getArticleInfo" - ], - "history": [ - { - "content": "i want to know about the range", - "current_turn": true, - "role": "user" - }, - { - "created_at": "2024-12-18T07:45:13.821351", - "current_turn": true, - "response_type": "internal", - "role": "assistant", - "sender": "Product info agent", - "tool_calls": [ - { - "function": { - "arguments": "{\"question\":\"XYZ Bike travel range\"}", - "name": "getArticleInfo" - }, - "id": "call_CcNzb2N3lBt4JOCVrzyHdpdL", - "type": "function" - } - ] - } - ], - "instructions": "🧑‍💼 Role:\nYou are a product information agent for XYZ Bikes. Your job is to answer search for the right article and answer questions strictly based on the article about Unagi products. Feel free to ask the user clarification questions if needed.\n\n---\n\n📜 Instructions:\n\n✅ In Scope:\n- Answer questions strictly about Unagi product information.\n\n❌ Out of Scope:\n- Questions about delivery, returns, subscriptions, and promotions.\n- Any topic unrelated to Unagi products.\n- If a question is out of scope, call give_up_control and do not attempt to answer it.\n\n---\n\n✔️ Dos:\n- Stick to the facts provided in the articles.\n- Provide complete and direct answers to the user's questions.\n- Call the Greeting agent after each interaction.\n\n---\n\n🚫 Don'ts:\n- Do not partially answer questions or direct users to a URL for more information.\n- Do not provide information outside of the given context.\n\n---\n\n📝 Examples:\n\n---\nIn Scope Example 1:\nUser: What is the maximum speed of the Unagi E500?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 2:\nUser: How long does it take to charge a XYZ Bike fully?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 3:\nUser: Can you tell me about the weight-carrying capacity of XYZ Bikes?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 4:\nUser: What are the differences between the E250 and E500 models?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 5:\nUser: How far can I travel on a single charge with the E500?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 6:\nUser: Is the scooter waterproof?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 7:\nUser: Does the scooter have any safety features?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 8:\nUser: What materials are used to make XYZ Bikes?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 9:\nUser: Can the scooter be used off-road?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 10:\nUser: Are spare parts available for purchase?\nAction: Call get_article_info followed by .\n\n---\nOut of Scope Example 1:\nUser: What is the status of my order delivery?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 2:\nUser: How do I process a return?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 3:\nUser: Can you tell me more about the subscription plans?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 4:\nUser: Are there any promotions or discounts?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 5:\nUser: Who won the last election?\nAction: Call give_up_control.\n\nProvide your output in the following structured JSON format:\n\n{\n \"steps_completed\": ,\n \"current_step\": ,\n \"reasoning\": \"\",\n \"error_count\": ,\n \"response_to_user\": \"\"\n}\n\nAlways ensure that all pertinent details, including tables or structured lists, are contained within the response_to_user field to maintain clarity and a comprehensive response for the user.\n\nRetrieval instructions:\n\nIn every turn, retrieve a relevant article and use the information from that article to answer the user's question.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "Main agent", - "name": "Product info agent", - "parent_function": "give_up_chat_control" - }, - { - "child_functions": [], - "external_tools": [ - "get_delivery_details", - "getArticleInfo" - ], - "history": [], - "instructions": "Role:\nYou are responsible for providing delivery information to the user.\n\n---\n\n⚙️ Steps to Follow:\n1. Fetch the delivery details using the function: get_shipping_details.\n2. Answer the user's question based on the fetched delivery details.\n3. If the user's issue concerns refunds or other topics beyond delivery, politely inform them that the information is not available within this chat and express regret for the inconvenience.\n\n---\n\n✅ In Scope:\nQuestions about delivery status, shipping timelines, and delivery processes.\nGeneric delivery/shipping-related questions where answers can be sourced from articles.\n\n---\n\n❌ Out of Scope:\nQuestions unrelated to delivery or shipping.\nQuestions about products features, returns, subscriptions, or promotions.\nIf a question is out of scope, politely inform the user and avoid providing an answer.\n\n---\n\nExample 1:\nUser: What is the status of my delivery?\nAction: Call get_delivery_details to fetch the current delivery status and inform the user.\n\nExample 2:\nUser: Can you explain the delivery process?\nAction: Provide a detailed answer and clarify any user questions based on the articles.\n\nExample 3:\nUser: I have a question about product features such as range, durability etc.\nAction: give_up_control as this is not in your scope.\n\n---\n\n✅ Dos:\nUse get_shipping_details to fetch accurate delivery information.\nProvide complete and clear answers based on the delivery details.\nFor generic delivery questions, refer to relevant articles if necessary.\nStick to factual information when answering.\n\n---\n\n❌ Don'ts:\nDo not provide answers without fetching delivery details when required.\nDo not leave the user with partial information.\nRefrain from phrases like 'please contact support'; instead, relay information limitations gracefully.\n\nProvide your output in the following structured JSON format:\n\n{\n \"steps_completed\": ,\n \"current_step\": ,\n \"reasoning\": \"\",\n \"error_count\": ,\n \"response_to_user\": \"\"\n}\n\nAlways ensure that all pertinent details, including tables or structured lists, are contained within the response_to_user field to maintain clarity and a comprehensive response for the user.\n\nRetrieval instructions:\n\nIn every turn, retrieve a relevant article and use the information from that article to answer the user's question.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Delivery info agent", - "parent_function": null - }, - { - "child_functions": [], - "external_tools": [], - "history": [], - "instructions": "talk about returns\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Returns agent", - "parent_function": null - }, - { - "child_functions": [], - "external_tools": [], - "history": [], - "instructions": "talk about subscriptions\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Subscriptions agent", - "parent_function": null - }, - { - "child_functions": [], - "external_tools": [], - "history": [], - "instructions": "Talk about promotions\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Promotions agent", - "parent_function": null - }, - { - "child_functions": [], - "external_tools": [], - "history": [], - "instructions": "Role:\nYou are a test agent for XYZ Bikes. Your job is to help test the functionality of different operations within the system.\n\n---\n\nTasks to Follow:\n- Assist in simulating various scenarios and operations to ensure smooth functioning.\n- Report any discrepancies or issues observed during testing.\n\n---\n\nIn Scope:\n- Conduct user interaction tests.\n- Evaluate agent response accuracy.\n- Validate agent transition accuracy.\n\n---\n\nOut of Scope:\n- Direct customer interactions outside of test scenarios.\n- Handling of live customer support queries.\n\n---\n\nDos:\n- Conduct comprehensive tests to cover all expected operations and scenarios.\n- Document test outcomes clearly.\n\n---\n\nDon'ts:\n- Do not intervene in live interactions unless part of a test scenario.\n- Ensure test operations do not affect live customer service functions.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "internal_tools": [], - "most_recent_parent_name": "", - "name": "Test agent", - "parent_function": null - } - ], - "last_agent_name": "Product info agent" - }, - "agents": [ - { - "name": "Main agent", - "type": "conversation", - "description": "The Main agent orchestrates interactions between various specialized worker agents to ensure efficient handling of user queries and support needs.", - "instructions": "Role:\nYou are a customer support agent for XYZ Bikes. Your primary task is to facilitate conversations by passing control to specialized worker agents when needed.\n\n---\n\nTasks to Follow:\n- Engage in small talk if no specific question is asked.\n- Pass control to the appropriate worker agents for specialized conversations.\n\n---\n\nSmall Talk:\nYou are welcome to engage in basic small talk to build rapport.\n\n---\n\nExamples:\n\n---\nIn Scope Example 1:\nUser: How are you?\nAnswer: \"I'm doing well, thank you! How can I assist you today?\"\n\n---\nIn Scope Example 2:\nUser: What can you do?\nAnswer: \"I can help with customer support-related issues for XYZ Bikes. Let me know if you have any questions.\"\n\n---\nIn Scope Example 3:\nUser: I want a XYZ Bike.\nAnswer: \"What would you like to know about XYZ Bikes?\"\n\n---\nPass Control Example 1:\nUser: Tell me about the product features.\nAction: Pass control to the Product info agent.\n\n---\nPass Control Example 2:\nUser: Where is my scooter?\nAction: Pass control to the Delivery info agent.\n\n---\nPass Control Example 3:\nUser: I need help with my return.\nAction: Pass control to the Returns agent.\n\n---\nPass Control Example 4:\nUser: How does the Unagi subscription work?\nAction: Pass control to the Subscriptions agent.\n\n---\n✅ Dos:\n- Engage in small talk when necessary.\n- Pass control to the appropriate agent based on the user's query.\n\n---\n❌ Don'ts:\n- Do not focus excessively on greetings during ongoing conversations.\n- Do not continue the conversation if you suspect the user is confused or uninterested in Unagi support.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [ - "Product info agent", - "Delivery info agent", - "Subscriptions agent" - ], - "controlType": "retain" - }, - { - "name": "Post process", - "type": "post_process", - "instructions": "- Extract the response_to_user field from the provided structured JSON and ensure that this is the only content you use for the final output.\n- Ensure that the agent response covers all the details the user asked for.\n- When providing long details, use bullets to distinguish the different points. \n- Focus specifically on the response_to_user field in its input.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o", - "hasRagSources": false, - "connectedAgents": [] - }, - { - "name": "Product info agent", - "type": "conversation", - "description": "You assist with product-related questions by retrieving relevant articles and information.", - "instructions": "🧑‍💼 Role:\nYou are a product information agent for XYZ Bikes. Your job is to answer search for the right article and answer questions strictly based on the article about Unagi products. Feel free to ask the user clarification questions if needed.\n\n---\n\n📜 Instructions:\n\n✅ In Scope:\n- Answer questions strictly about Unagi product information.\n\n❌ Out of Scope:\n- Questions about delivery, returns, subscriptions, and promotions.\n- Any topic unrelated to Unagi products.\n- If a question is out of scope, call give_up_control and do not attempt to answer it.\n\n---\n\n✔️ Dos:\n- Stick to the facts provided in the articles.\n- Provide complete and direct answers to the user's questions.\n- Call the Greeting agent after each interaction.\n\n---\n\n🚫 Don’ts:\n- Do not partially answer questions or direct users to a URL for more information.\n- Do not provide information outside of the given context.\n\n---\n\n📝 Examples:\n\n---\nIn Scope Example 1:\nUser: What is the maximum speed of the Unagi E500?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 2:\nUser: How long does it take to charge a XYZ Bike fully?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 3:\nUser: Can you tell me about the weight-carrying capacity of XYZ Bikes?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 4:\nUser: What are the differences between the E250 and E500 models?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 5:\nUser: How far can I travel on a single charge with the E500?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 6:\nUser: Is the scooter waterproof?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 7:\nUser: Does the scooter have any safety features?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 8:\nUser: What materials are used to make XYZ Bikes?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 9:\nUser: Can the scooter be used off-road?\nAction: Call get_article_info followed by .\n\n---\nIn Scope Example 10:\nUser: Are spare parts available for purchase?\nAction: Call get_article_info followed by .\n\n---\nOut of Scope Example 1:\nUser: What is the status of my order delivery?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 2:\nUser: How do I process a return?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 3:\nUser: Can you tell me more about the subscription plans?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 4:\nUser: Are there any promotions or discounts?\nAction: Call give_up_control.\n\n---\nOut of Scope Example 5:\nUser: Who won the last election?\nAction: Call give_up_control.\n\nProvide your output in the following structured JSON format:\n\n{\n \"steps_completed\": ,\n \"current_step\": ,\n \"reasoning\": \"\",\n \"error_count\": ,\n \"response_to_user\": \"\"\n}\n\nAlways ensure that all pertinent details, including tables or structured lists, are contained within the response_to_user field to maintain clarity and a comprehensive response for the user.\n\nRetrieval instructions:\n\nIn every turn, retrieve a relevant article and use the information from that article to answer the user's question.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": true, - "connectedAgents": [], - "controlType": "relinquish_to_parent" - }, - { - "name": "Delivery info agent", - "type": "conversation", - "description": "You are responsible for providing accurate delivery status and shipping details for orders.", - "instructions": "Role:\nYou are responsible for providing delivery information to the user.\n\n---\n\n⚙️ Steps to Follow:\n1. Fetch the delivery details using the function: get_shipping_details.\n2. Answer the user's question based on the fetched delivery details.\n3. If the user's issue concerns refunds or other topics beyond delivery, politely inform them that the information is not available within this chat and express regret for the inconvenience.\n\n---\n\n✅ In Scope:\nQuestions about delivery status, shipping timelines, and delivery processes.\nGeneric delivery/shipping-related questions where answers can be sourced from articles.\n\n---\n\n❌ Out of Scope:\nQuestions unrelated to delivery or shipping.\nQuestions about products features, returns, subscriptions, or promotions.\nIf a question is out of scope, politely inform the user and avoid providing an answer.\n\n---\n\nExample 1:\nUser: What is the status of my delivery?\nAction: Call get_delivery_details to fetch the current delivery status and inform the user.\n\nExample 2:\nUser: Can you explain the delivery process?\nAction: Provide a detailed answer and clarify any user questions based on the articles.\n\nExample 3:\nUser: I have a question about product features such as range, durability etc.\nAction: give_up_control as this is not in your scope.\n\n---\n\n✅ Dos:\nUse get_shipping_details to fetch accurate delivery information.\nProvide complete and clear answers based on the delivery details.\nFor generic delivery questions, refer to relevant articles if necessary.\nStick to factual information when answering.\n\n---\n\n❌ Don’ts:\nDo not provide answers without fetching delivery details when required.\nDo not leave the user with partial information.\nRefrain from phrases like 'please contact support'; instead, relay information limitations gracefully.\n\nProvide your output in the following structured JSON format:\n\n{\n \"steps_completed\": ,\n \"current_step\": ,\n \"reasoning\": \"\",\n \"error_count\": ,\n \"response_to_user\": \"\"\n}\n\nAlways ensure that all pertinent details, including tables or structured lists, are contained within the response_to_user field to maintain clarity and a comprehensive response for the user.\n\nRetrieval instructions:\n\nIn every turn, retrieve a relevant article and use the information from that article to answer the user's question.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [ - "get_delivery_details" - ], - "model": "gpt-4o-mini", - "hasRagSources": true, - "connectedAgents": [], - "controlType": "retain" - }, - { - "name": "Returns agent", - "type": "conversation", - "description": "You provide assistance for inquiries and processes related to product returns.", - "instructions": "talk about returns\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [] - }, - { - "name": "Subscriptions agent", - "type": "conversation", - "description": "You handle all subscription-related queries from customers.", - "instructions": "talk about subscriptions\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [] - }, - { - "name": "Promotions agent", - "type": "conversation", - "description": "You provide current promotions and discounts details to the customers.", - "instructions": "Talk about promotions\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [] - }, - { - "name": "Test agent", - "type": "conversation", - "description": "Your job is to simulate various customer interactions and test system operations for quality assurance purposes.", - "instructions": "Role:\nYou are a test agent for XYZ Bikes. Your job is to help test the functionality of different operations within the system.\n\n---\n\nTasks to Follow:\n- Assist in simulating various scenarios and operations to ensure smooth functioning.\n- Report any discrepancies or issues observed during testing.\n\n---\n\nIn Scope:\n- Conduct user interaction tests.\n- Evaluate agent response accuracy.\n- Validate agent transition accuracy.\n\n---\n\nOut of Scope:\n- Direct customer interactions outside of test scenarios.\n- Handling of live customer support queries.\n\n---\n\nDos:\n- Conduct comprehensive tests to cover all expected operations and scenarios.\n- Document test outcomes clearly.\n\n---\n\nDon’ts:\n- Do not intervene in live interactions unless part of a test scenario.\n- Ensure test operations do not affect live customer service functions.\n\nSelf Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'.", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [] - }, - { - "name": "Escalation", - "type": "escalation", - "description": "", - "instructions": "Get the user's contact information and let them know that their request has been escalated.\n\n", - "tools": [], - "model": "gpt-4o-mini", - "hasRagSources": false, - "connectedAgents": [], - "controlType": "retain" - } - ], - "tools": [ - { - "name": "get_delivery_details", - "description": "Return a estimated delivery date for the XYZ Bike.", - "parameters": { - "type": "object", - "properties": {}, - "required": [] - } - }, - { - "name": "get_subscription_plan_details", - "description": "Return details of the available subscription plans for XYZ Bikes.", - "parameters": { - "type": "object", - "properties": {}, - "required": [] - } - }, - { - "name": "get_current_date", - "description": "Return the current date.", - "parameters": { - "type": "object", - "properties": {}, - "required": [] - } - } - ], - "prompts": [ - { - "name": "Style prompt", - "type": "style_prompt", - "prompt": "You should be empathetic and helpful." - }, - { - "name": "reasoning_output", - "type": "base_prompt", - "prompt": "Give your output in the following format:\n\nreason : \n\nresponse_to_user : " - }, - { - "name": "get_delivery_details", - "type": "base_prompt", - "prompt": "Return a estimated delivery date for XYZ Bike." - }, - { - "name": "structured_output", - "type": "base_prompt", - "prompt": "Provide your output in the following structured JSON format:\n\n{\n \"steps_completed\": ,\n \"current_step\": ,\n \"reasoning\": \"\",\n \"error_count\": ,\n \"response_to_user\": \"\"\n}\n\nAlways ensure that all pertinent details, including tables or structured lists, are contained within the response_to_user field to maintain clarity and a comprehensive response for the user." - }, - { - "name": "rag_article_prompt", - "type": "base_prompt", - "prompt": "Retrieval instructions:\n\nIn every turn, retrieve a relevant article and use the information from that article to answer the user's question." - }, - { - "name": "self_support_prompt", - "type": "base_prompt", - "prompt": "Self Support Guidance:\n\nThe bot should not suggest phrases like 'let me connect you to support' or 'you can reach out to support'. Instead, the agent is the customer support. It can say 'I apologize, but I don't have the right information'." - } - ], - "startAgent": "Main agent" - } -} \ No newline at end of file diff --git a/apps/chat_widget/app/app.tsx b/apps/chat_widget/app/app.tsx index 650a9824..9d9af2c3 100644 --- a/apps/chat_widget/app/app.tsx +++ b/apps/chat_widget/app/app.tsx @@ -322,7 +322,7 @@ export function App({ chat, messages: allMessages, }; - }, [sessionId]); + }, [sessionId, apiUrl]); async function resetState() { setChatId(null); diff --git a/apps/chat_widget/package-lock.json b/apps/chat_widget/package-lock.json index 14efe01a..8c76e5fa 100644 --- a/apps/chat_widget/package-lock.json +++ b/apps/chat_widget/package-lock.json @@ -10,7 +10,7 @@ "dependencies": { "@nextui-org/react": "^2.4.8", "framer-motion": "^11.11.11", - "next": "^14.2.16", + "next": "^14.2.25", "react": "^18.3.1", "react-dom": "^18.3.1", "react-markdown": "^9.0.1", @@ -308,9 +308,9 @@ } }, "node_modules/@next/env": { - "version": "14.2.16", - "resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.16.tgz", - "integrity": "sha512-fLrX5TfJzHCbnZ9YUSnGW63tMV3L4nSfhgOQ0iCcX21Pt+VSTDuaLsSuL8J/2XAiVA5AnzvXDpf6pMs60QxOag==" + "version": "14.2.25", + "resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.25.tgz", + "integrity": "sha512-JnzQ2cExDeG7FxJwqAksZ3aqVJrHjFwZQAEJ9gQZSoEhIow7SNoKZzju/AwQ+PLIR4NY8V0rhcVozx/2izDO0w==" }, "node_modules/@next/eslint-plugin-next": { "version": "15.0.2", @@ -322,9 +322,9 @@ } }, "node_modules/@next/swc-darwin-arm64": { - "version": "14.2.16", - "resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.16.tgz", - "integrity": "sha512-uFT34QojYkf0+nn6MEZ4gIWQ5aqGF11uIZ1HSxG+cSbj+Mg3+tYm8qXYd3dKN5jqKUm5rBVvf1PBRO/MeQ6rxw==", + "version": "14.2.25", + "resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.25.tgz", + "integrity": "sha512-09clWInF1YRd6le00vt750s3m7SEYNehz9C4PUcSu3bAdCTpjIV4aTYQZ25Ehrr83VR1rZeqtKUPWSI7GfuKZQ==", "cpu": [ "arm64" ], @@ -337,9 +337,9 @@ } }, "node_modules/@next/swc-darwin-x64": { - "version": "14.2.16", - "resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.16.tgz", - "integrity": "sha512-mCecsFkYezem0QiZlg2bau3Xul77VxUD38b/auAjohMA22G9KTJneUYMv78vWoCCFkleFAhY1NIvbyjj1ncG9g==", + "version": "14.2.25", + "resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.25.tgz", + "integrity": "sha512-V+iYM/QR+aYeJl3/FWWU/7Ix4b07ovsQ5IbkwgUK29pTHmq+5UxeDr7/dphvtXEq5pLB/PucfcBNh9KZ8vWbug==", "cpu": [ "x64" ], @@ -352,9 +352,9 @@ } }, "node_modules/@next/swc-linux-arm64-gnu": { - "version": "14.2.16", - "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.16.tgz", - "integrity": "sha512-yhkNA36+ECTC91KSyZcgWgKrYIyDnXZj8PqtJ+c2pMvj45xf7y/HrgI17hLdrcYamLfVt7pBaJUMxADtPaczHA==", + "version": "14.2.25", + "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.25.tgz", + "integrity": "sha512-LFnV2899PJZAIEHQ4IMmZIgL0FBieh5keMnriMY1cK7ompR+JUd24xeTtKkcaw8QmxmEdhoE5Mu9dPSuDBgtTg==", "cpu": [ "arm64" ], @@ -367,9 +367,9 @@ } }, "node_modules/@next/swc-linux-arm64-musl": { - 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"version": "14.2.16", - "resolved": "https://registry.npmjs.org/next/-/next-14.2.16.tgz", - "integrity": "sha512-LcO7WnFu6lYSvCzZoo1dB+IO0xXz5uEv52HF1IUN0IqVTUIZGHuuR10I5efiLadGt+4oZqTcNZyVVEem/TM5nA==", + "version": "14.2.25", + "resolved": "https://registry.npmjs.org/next/-/next-14.2.25.tgz", + "integrity": "sha512-N5M7xMc4wSb4IkPvEV5X2BRRXUmhVHNyaXwEM86+voXthSZz8ZiRyQW4p9mwAoAPIm6OzuVZtn7idgEJeAJN3Q==", "dependencies": { - "@next/env": "14.2.16", + "@next/env": "14.2.25", "@swc/helpers": "0.5.5", "busboy": "1.6.0", "caniuse-lite": "^1.0.30001579", @@ -7518,15 +7518,15 @@ "node": ">=18.17.0" }, "optionalDependencies": { - "@next/swc-darwin-arm64": "14.2.16", - "@next/swc-darwin-x64": "14.2.16", - "@next/swc-linux-arm64-gnu": "14.2.16", - "@next/swc-linux-arm64-musl": "14.2.16", - "@next/swc-linux-x64-gnu": "14.2.16", - "@next/swc-linux-x64-musl": "14.2.16", - "@next/swc-win32-arm64-msvc": "14.2.16", - "@next/swc-win32-ia32-msvc": "14.2.16", - "@next/swc-win32-x64-msvc": "14.2.16" + "@next/swc-darwin-arm64": "14.2.25", + "@next/swc-darwin-x64": "14.2.25", + "@next/swc-linux-arm64-gnu": "14.2.25", + "@next/swc-linux-arm64-musl": "14.2.25", + "@next/swc-linux-x64-gnu": "14.2.25", + "@next/swc-linux-x64-musl": "14.2.25", + "@next/swc-win32-arm64-msvc": "14.2.25", + "@next/swc-win32-ia32-msvc": "14.2.25", + "@next/swc-win32-x64-msvc": "14.2.25" }, "peerDependencies": { "@opentelemetry/api": "^1.1.0", diff --git a/apps/chat_widget/package.json b/apps/chat_widget/package.json index 43e43be8..20611d49 100644 --- a/apps/chat_widget/package.json +++ b/apps/chat_widget/package.json @@ -11,7 +11,7 @@ "dependencies": { "@nextui-org/react": "^2.4.8", "framer-motion": "^11.11.11", - "next": "^14.2.16", + "next": "^14.2.25", "react": "^18.3.1", "react-dom": "^18.3.1", "react-markdown": "^9.0.1", diff --git a/apps/copilot/app.py b/apps/copilot/app.py index b7953641..5d629435 100644 --- a/apps/copilot/app.py +++ b/apps/copilot/app.py @@ -51,6 +51,7 @@ def health(): def chat(): try: request_data = ApiRequest(**request.json) + print(f"received /chat request: {request_data}") validate_request(request_data) response = get_response( @@ -61,7 +62,7 @@ def chat(): copilot_instructions=copilot_instructions ) api_response = ApiResponse(response=response).model_dump() - + print(f"sending /chat response: {api_response}") return jsonify(api_response) except ValidationError as ve: @@ -88,6 +89,7 @@ def chat(): def edit_agent_instructions(): try: request_data = ApiRequest(**request.json) + print(f"received /edit_agent_instructions request: {request_data}") validate_request(request_data) response = get_response( @@ -99,6 +101,7 @@ def edit_agent_instructions(): ) api_response = ApiResponse(response=response).model_dump() + print(f"sending /edit_agent_instructions response: {api_response}") return jsonify(api_response) except ValidationError as ve: diff --git a/apps/copilot/copilot.py b/apps/copilot/copilot.py index 2266cfe8..ac108654 100644 --- a/apps/copilot/copilot.py +++ b/apps/copilot/copilot.py @@ -20,7 +20,7 @@ copilot_instructions = """ ## Overview -You are a helpful co-pilot for building and deploying customer support AI agents. Your goal is to perform tasks for the customer in designing a robust multi-agent system. You can perform the following tasks: +You are a helpful co-pilot for building and deploying multi-agent systems. Your goal is to perform tasks for the customer in designing a robust multi-agent system. You can perform the following tasks: 1. Plan and creating a multi-agent system 2. Create a new agent @@ -44,7 +44,7 @@ You are not equipped to perform the following tasks: Agents in the system be of the following types: 1. Conversation - Carries out the core customer support related conversations. All new agents you create should be of type 'Conversation'. + Carries out the core customer conversations. All new agents you create should be of type 'Conversation'. 2. Post-processing Ensures the output aligns with specific format and style requirements. @@ -257,22 +257,11 @@ Note : Always add a text section that describes the changes before each action. **NOTE**: The output should be a valid JSON object. Do not include any other text or comments. Do not wrap the output in a code block. -## Section 11: State of the Current Multi-Agent System - -The design of the multi-agent system is represented by the following JSON schema: - -``` -{workflow_schema} -``` - -If the workflow has an 'Example Agent' as the main agent, it means the user is yet to create the main agent. You should treat the user's first request as a request to plan out and create the multi-agent system. - - -## Section 12: Examples +## Section 11: Examples ### Example 1: -User: create a system to handle 2fa related customer support queries. The queries can be: 1. setting up 2fa : ask the users preferred methods 2. changing 2fa : chaing the 2fa method 3. troubleshooting : not getting 2fa codes etc. +User: create a system to handle 2fa related customer support queries for a banking app. The queries can be: 1. setting up 2fa : ask the users preferred methods 2. changing 2fa : chaing the 2fa method 3. troubleshooting : not getting 2fa codes etc. Copilot output: @@ -297,6 +286,7 @@ Copilot output: "config_changes": { "name": "get_current_2fa_method", "description": "Tool to fetch the user's current 2FA method.", + "mockInstructions": "Return a random 2FA method for a banking app.", "parameters": { "type": "object", "properties": { @@ -327,7 +317,7 @@ Copilot output: "name": "2FA Setup", "type": "conversation", "description": "Agent to guide users in setting up 2FA.", - "instructions": "## 🧑‍💼 Role:\nHelp users set up their 2FA preferences.\n\n---\n## ⚙️ Steps to Follow:\n1. Ask the user about their preferred 2FA method (e.g., SMS, Email).\n2. Confirm the setup method with the user.\n3. Guide them through the setup steps.\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Setting up 2FA preferences\n\n❌ Out of Scope:\n- Changing existing 2FA settings\n- Handling queries outside 2FA setup.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Clearly explain setup options and steps.\n\n🚫 Don'ts:\n- Assume preferences without user confirmation.\n- Extend the conversation beyond 2FA setup.", + "instructions": "## 🧑‍💼 Role:\nHelp users set up their 2FA preferences.\n\n---\n## ⚙️ Steps to Follow:\n1. Ask the user about their preferred 2FA method (e.g., SMS, Email).\n2. Confirm the setup method with the user.\n3. Guide them through the setup steps.\n4. If the user request is out of scope, pass control to [@agent:2FA Hub](#mention)\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Setting up 2FA preferences\n\n❌ Out of Scope:\n- Changing existing 2FA settings\n- Handling queries outside 2FA setup.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Clearly explain setup options and steps.\n\n🚫 Don'ts:\n- Assume preferences without user confirmation.\n- Extend the conversation beyond 2FA setup.", "examples": "- **User** : I'd like to set up 2FA for my account.\n - **Agent response**: Sure, can you tell me your preferred method for 2FA? Options include SMS, Email, or an Authenticator App.\n\n- **User** : I want to use SMS for 2FA.\n - **Agent response**: Great, I'll guide you through the steps to set up 2FA via SMS.\n\n- **User** : How about using an Authenticator App?\n - **Agent response**: Sure, let's set up 2FA with an Authenticator App. I'll walk you through the necessary steps.\n\n- **User** : Can you help me set up 2FA through Email?\n - **Agent response**: No problem, I'll explain how to set up 2FA via Email now.\n\n- **User** : I changed my mind, can we start over?\n - **Agent response**: Of course, let's begin again. Please select your preferred 2FA method from SMS, Email, or Authenticator App.", "model": "gpt-4o", "toggleAble": true, @@ -350,7 +340,7 @@ Copilot output: "name": "2FA Change", "type": "conversation", "description": "Agent to assist users in changing their 2FA method.", - "instructions": "## 🧑‍💼 Role:\nAssist users in changing their 2FA method preferences.\n\n---\n## ⚙️ Steps to Follow:\n1. Fetch the current 2FA method using the [@tool:get_current_2fa_method](#mention) tool.\n2. Confirm with the user if they want to change the method.\n3. Guide them through the process of changing the method.\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Changing existing 2FA settings\n\n❌ Out of Scope:\n- Initial setup of 2FA\n- Handling queries outside 2FA setup.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Ensure the user is aware of the current method before change.\n\n🚫 Don'ts:\n- Change methods without explicit user confirmation.\n- Extend the conversation beyond 2FA change.", + "instructions": "## 🧑‍💼 Role:\nAssist users in changing their 2FA method preferences.\n\n---\n## ⚙️ Steps to Follow:\n1. Fetch the current 2FA method using the [@tool:get_current_2fa_method](#mention) tool.\n2. Confirm with the user if they want to change the method.\n3. Guide them through the process of changing the method.\n4. If the user request is out of scope, pass control to [@agent:2FA Hub](#mention)\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Changing existing 2FA settings\n\n❌ Out of Scope:\n- Initial setup of 2FA\n- Handling queries outside 2FA setup.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Ensure the user is aware of the current method before change.\n\n🚫 Don'ts:\n- Change methods without explicit user confirmation.\n- Extend the conversation beyond 2FA change.", "examples": "- **User** : I want to change my 2FA method from SMS to Email.\n - **Agent response**: I can help with that. Let me fetch your current 2FA setting first.\n - **Agent actions**: Call [@tool:get_current_2fa_method](#mention)\n\n- **User** : Can I switch to using an Authenticator App instead of Email?\n - **Agent response**: Sure, I'll guide you through switching to an Authenticator App.\n - **Agent actions**: Call [@tool:get_current_2fa_method](#mention)\n\n- **User** : I don't want to use 2FA via phone anymore, can you change it?\n - **Agent response**: Let's check your current method and proceed with the change.\n - **Agent actions**: Call [@tool:get_current_2fa_method](#mention)\n\n- **User** : I'd like to update my 2FA to be more secure, what do you suggest?\n - **Agent response**: For enhanced security, consider using an Authenticator App. Let's fetch your current method and update it.\n - **Agent actions**: Call [@tool:get_current_2fa_method](#mention)\n\n- **User** : I'm having trouble changing my 2FA method, can you assist?\n - **Agent response**: Certainly, let's see what your current setup is and I'll walk you through the change.", "model": "gpt-4o", "toggleAble": true, @@ -373,7 +363,7 @@ Copilot output: "name": "2FA Troubleshooting", "type": "conversation", "description": "Agent to troubleshoot issues related to not receiving 2FA codes.", - "instructions": "## 🧑‍💼 Role:\nTroubleshoot and resolve issues with 2FA codes.\n\n---\n## ⚙️ Steps to Follow:\n1. Confirm the contact details for 2FA are correct.\n2. Ask about the issue specifics (e.g., not receiving codes at all, delayed codes).\n3. Provide troubleshooting steps or escalate if unresolved.\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Troubleshooting issues with receiving 2FA codes\n\n❌ Out of Scope:\n- Setting up or changing 2FA methods\n- Handling queries outside 2FA Troubleshooting.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Verify contact information for accuracy.\n\n🚫 Don'ts:\n- Extend the conversation beyond 2FA change.", + "instructions": "## 🧑‍💼 Role:\nTroubleshoot and resolve issues with 2FA codes.\n\n---\n## ⚙️ Steps to Follow:\n1. Confirm the contact details for 2FA are correct.\n2. Ask about the issue specifics (e.g., not receiving codes at all, delayed codes).\n3. Provide troubleshooting steps or escalate if unresolved.\n4. If the user request is out of scope, pass control to [@agent:2FA Hub](#mention)\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Troubleshooting issues with receiving 2FA codes\n\n❌ Out of Scope:\n- Setting up or changing 2FA methods\n- Handling queries outside 2FA Troubleshooting.\n- General knowledge queries.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- Verify contact information for accuracy.\n\n🚫 Don'ts:\n- Extend the conversation beyond 2FA change.", "examples": "- **User** : I haven't received my 2FA code.\n - **Agent response**: Let's ensure your contact details are correct. Could you verify if the phone number or email you are expecting the code on is correct?\n\n- **User** : My 2FA codes are always delayed.\n - **Agent response**: I apologize for the inconvenience. Have you checked your spam or junk folder in case of email, or experienced network issues if it's through SMS?\n\n- **User** : The codes aren't coming to my phone.\n - **Agent response**: Let's confirm the number on file for you. Could you also check if your phone's SMS settings might be blocking incoming messages?\n\n- **User** : I'm facing issues with receiving 2FA codes via email.\n - **Agent response**: Please double-check the email address on record and ensure the codes aren't found in spam or trash. I can assist further if needed.\n\n- **User** : My codes are coming to the wrong email address.\n - **Agent response**: I recommend updating your 2FA contact information. Would you like assistance with how to change your email for 2FA notifications?", "model": "gpt-4o", "toggleAble": true, @@ -417,6 +407,16 @@ Copilot output: "response": "" } ``` + +## Section 12: State of the Current Multi-Agent System + +The design of the multi-agent system is represented by the following JSON schema: + +``` +{workflow_schema} +``` + +If the workflow has an 'Example Agent' as the main agent, it means the user is yet to create the main agent. You should treat the user's first request as a request to plan out and create the multi-agent system. """ copilot_instructions_edit_agent = """ @@ -540,7 +540,6 @@ User: {last_message.content} updated_msgs = [{"role": "system", "content": sys_prompt}] + [ message.model_dump() for message in messages ] - print(json.dumps(updated_msgs, indent=2)) response = openai_client.chat.completions.create( model=MODEL_NAME, diff --git a/apps/python-sdk/pyproject.toml b/apps/python-sdk/pyproject.toml index f03b944f..6d1cabdc 100644 --- a/apps/python-sdk/pyproject.toml +++ b/apps/python-sdk/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "rowboat" -version = "1.0.6" +version = "2.1.0" authors = [ { name = "Your Name", email = "your.email@example.com" }, ] diff --git a/apps/python-sdk/src/rowboat/client.py b/apps/python-sdk/src/rowboat/client.py index f0ad3b31..2997ed08 100644 --- a/apps/python-sdk/src/rowboat/client.py +++ b/apps/python-sdk/src/rowboat/client.py @@ -38,7 +38,8 @@ class Client: workflowId=workflow_id, testProfileId=test_profile_id ) - response = requests.post(self.base_url, headers=self.headers, data=request.model_dump_json()) + json_data = request.model_dump() + response = requests.post(self.base_url, headers=self.headers, json=json_data) if not response.status_code == 200: raise ValueError(f"Error: {response.status_code} - {response.text}") @@ -90,7 +91,7 @@ class Client: ) -> Tuple[List[ApiMessage], Optional[Dict[str, Any]]]: """Stateless chat method that handles a single conversation turn with multiple tool call rounds""" - current_messages = messages + current_messages = messages[:] current_state = state turns = 0 diff --git a/apps/rowboat/app/actions/actions.ts b/apps/rowboat/app/actions/actions.ts index eb694019..a9596788 100644 --- a/apps/rowboat/app/actions/actions.ts +++ b/apps/rowboat/app/actions/actions.ts @@ -1,30 +1,28 @@ 'use server'; -import { convertFromAgenticAPIChatMessages } from "../lib/types/agents_api_types"; +import { AgenticAPIInitStreamResponse, convertFromAgenticAPIChatMessages } from "../lib/types/agents_api_types"; import { AgenticAPIChatRequest } from "../lib/types/agents_api_types"; -import { WorkflowAgent } from "../lib/types/workflow_types"; -import { EmbeddingRecord } from "../lib/types/datasource_types"; import { WebpageCrawlResponse } from "../lib/types/tool_types"; -import { GetInformationToolResult } from "../lib/types/tool_types"; -import { EmbeddingDoc } from "../lib/types/datasource_types"; -import { generateObject, generateText, embed } from "ai"; -import { dataSourceDocsCollection, dataSourcesCollection, embeddingsCollection, webpagesCollection } from "../lib/mongodb"; +import { webpagesCollection } from "../lib/mongodb"; import { z } from 'zod'; -import { openai } from "@ai-sdk/openai"; import FirecrawlApp, { ScrapeResponse } from '@mendable/firecrawl-js'; -import { embeddingModel } from "../lib/embedding"; import { apiV1 } from "rowboat-shared"; import { Claims, getSession } from "@auth0/nextjs-auth0"; -import { callClientToolWebhook, getAgenticApiResponse, mockToolResponse, runRAGToolCall } from "../lib/utils"; +import { getAgenticApiResponse, getAgenticResponseStreamId } from "../lib/utils"; import { check_query_limit } from "../lib/rate_limiting"; import { QueryLimitError } from "../lib/client_utils"; import { projectAuthCheck } from "./project_actions"; -import { qdrantClient } from "../lib/qdrant"; -import { ObjectId } from "mongodb"; -import { TestProfile } from "../lib/types/testing_types"; +import { USE_AUTH } from "../lib/feature_flags"; const crawler = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY || '' }); export async function authCheck(): Promise { + if (!USE_AUTH) { + return { + email: 'guestuser@rowboatlabs.com', + email_verified: true, + sub: 'guest_user', + }; + } const { user } = await getSession() || {}; if (!user) { throw new Error('User not authenticated'); @@ -76,17 +74,14 @@ export async function scrapeWebpage(url: string): Promise, -): Promise<{ +export async function getAssistantResponse(request: z.infer): Promise<{ messages: z.infer[], state: unknown, rawRequest: unknown, rawResponse: unknown, }> { - await projectAuthCheck(projectId); - if (!await check_query_limit(projectId)) { + await projectAuthCheck(request.projectId); + if (!await check_query_limit(request.projectId)) { throw new QueryLimitError(); } @@ -99,95 +94,12 @@ export async function getAssistantResponse( }; } -export async function suggestToolResponse(toolId: string, projectId: string, messages: z.infer[], mockInstructions: string): Promise { - await projectAuthCheck(projectId); - if (!await check_query_limit(projectId)) { +export async function getAssistantResponseStreamId(request: z.infer): Promise> { + await projectAuthCheck(request.projectId); + if (!await check_query_limit(request.projectId)) { throw new QueryLimitError(); } - return await mockToolResponse(toolId, messages, mockInstructions); -} - -export async function getInformationTool( - projectId: string, - query: string, - sourceIds: string[], - returnType: z.infer['ragReturnType'], - k: number, -): Promise> { - await projectAuthCheck(projectId); - - return await runRAGToolCall(projectId, query, sourceIds, returnType, k); -} - -export async function simulateUserResponse( - projectId: string, - messages: z.infer[], - scenario: string, -): Promise { - await projectAuthCheck(projectId); - if (!await check_query_limit(projectId)) { - throw new QueryLimitError(); - } - - const scenarioPrompt = ` -# Your Specific Task: - -## Context: - -Here is a scenario: - -Scenario: - -{{scenario}} - - -## Task definition: - -Pretend to be a user reaching out to customer support. Chat with the -customer support assistant, assuming your issue is based on this scenario. -Ask follow-up questions and make it real-world like. Don't do dummy -conversations. Your conversation should be a maximum of 5 user turns. - -As output, simply provide your (user) turn of conversation. - -After you are done with the chat, keep replying with a single word EXIT -in all capitals. -`; - - await projectAuthCheck(projectId); - - // flip message assistant / user message - // roles from chat messages - // use only text response messages - const flippedMessages: { role: 'user' | 'assistant', content: string }[] = messages - .filter(m => m.role == 'assistant' || m.role == 'user') - .map(m => ({ - role: m.role == 'assistant' ? 'user' : 'assistant', - content: m.content || '', - })); - - // simulate user call - let prompt; - prompt = scenarioPrompt - .replace('{{scenario}}', scenario); - - const { text } = await generateText({ - model: openai("gpt-4o"), - system: prompt || '', - messages: flippedMessages, - }); - - return text.replace(/\. EXIT$/, '.'); -} - -export async function executeClientTool( - toolCall: z.infer['tool_calls'][number], - messages: z.infer[], - projectId: string, -): Promise { - await projectAuthCheck(projectId); - - const result = await callClientToolWebhook(toolCall, messages, projectId); - return result; + const response = await getAgenticResponseStreamId(request); + return response; } \ No newline at end of file diff --git a/apps/rowboat/app/actions/copilot_actions.ts b/apps/rowboat/app/actions/copilot_actions.ts index d677d599..dcb8a68c 100644 --- a/apps/rowboat/app/actions/copilot_actions.ts +++ b/apps/rowboat/app/actions/copilot_actions.ts @@ -36,7 +36,7 @@ export async function getCopilotResponse( current_workflow_config: JSON.stringify(convertToCopilotWorkflow(current_workflow_config)), context: context ? convertToCopilotApiChatContext(context) : null, }; - console.log(`copilot request`, JSON.stringify(request, null, 2)); + console.log(`sending copilot request`, JSON.stringify(request)); // call copilot api const response = await fetch(process.env.COPILOT_API_URL + '/chat', { @@ -54,7 +54,7 @@ export async function getCopilotResponse( // parse and return response const json: z.infer = await response.json(); - console.log(`copilot response`, JSON.stringify(json, null, 2)); + console.log(`received copilot response`, JSON.stringify(json)); if ('error' in json) { throw new Error(`Failed to call copilot api: ${json.error}`); } @@ -182,7 +182,7 @@ export async function getCopilotAgentInstructions( agentName: agentName, } }; - console.log(`copilot request`, JSON.stringify(request, null, 2)); + console.log(`sending copilot agent instructions request`, JSON.stringify(request)); // call copilot api const response = await fetch(process.env.COPILOT_API_URL + '/edit_agent_instructions', { @@ -201,7 +201,7 @@ export async function getCopilotAgentInstructions( // parse and return response const json = await response.json(); - console.log(`copilot response`, JSON.stringify(json, null, 2)); + console.log(`received copilot agent instructions response`, JSON.stringify(json)); let copilotResponse: z.infer; let agent_instructions: string; try { diff --git a/apps/rowboat/app/actions/mcp_actions.ts b/apps/rowboat/app/actions/mcp_actions.ts new file mode 100644 index 00000000..9ca6668f --- /dev/null +++ b/apps/rowboat/app/actions/mcp_actions.ts @@ -0,0 +1,83 @@ +"use server"; +import { z } from "zod"; +import { WorkflowTool } from "../lib/types/workflow_types"; +import { Client } from "@modelcontextprotocol/sdk/client/index.js"; +import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse.js"; +import { projectAuthCheck } from "./project_actions"; +import { projectsCollection } from "../lib/mongodb"; +import { Project } from "../lib/types/project_types"; +import { MCPServer } from "../lib/types/types"; + +export async function fetchMcpTools(projectId: string): Promise[]> { + await projectAuthCheck(projectId); + + const project = await projectsCollection.findOne({ + _id: projectId, + }); + + const mcpServers = project?.mcpServers ?? []; + + const tools: z.infer[] = []; + + for (const mcpServer of mcpServers) { + try { + const transport = new SSEClientTransport(new URL(mcpServer.url)); + + const client = new Client( + { + name: "rowboat-client", + version: "1.0.0" + }, + { + capabilities: { + prompts: {}, + resources: {}, + tools: {} + } + } + ); + + await client.connect(transport); + + // List tools + const result = await client.listTools(); + + await client.close(); + + tools.push(...result.tools.map((mcpTool) => { + let props = mcpTool.inputSchema.properties as Record; + const tool: z.infer = { + name: mcpTool.name, + description: mcpTool.description ?? "", + parameters: { + type: "object", + properties: props ?? {}, + required: mcpTool.inputSchema.required as string[] ?? [], + }, + isMcp: true, + mcpServerName: mcpServer.name, + } + return tool; + })); + } catch (e) { + console.error(`Error fetching MCP tools from ${mcpServer.name}: ${e}`); + } + } + + return tools; +} + +export async function updateMcpServers(projectId: string, mcpServers: z.infer['mcpServers']): Promise { + await projectAuthCheck(projectId); + await projectsCollection.updateOne({ + _id: projectId, + }, { $set: { mcpServers } }); +} + +export async function listMcpServers(projectId: string): Promise[]> { + await projectAuthCheck(projectId); + const project = await projectsCollection.findOne({ + _id: projectId, + }); + return project?.mcpServers ?? []; +} \ No newline at end of file diff --git a/apps/rowboat/app/actions/project_actions.ts b/apps/rowboat/app/actions/project_actions.ts index 163501cf..0090aec9 100644 --- a/apps/rowboat/app/actions/project_actions.ts +++ b/apps/rowboat/app/actions/project_actions.ts @@ -10,8 +10,12 @@ import { authCheck } from "./actions"; import { WithStringId } from "../lib/types/types"; import { ApiKey } from "../lib/types/project_types"; import { Project } from "../lib/types/project_types"; +import { USE_AUTH } from "../lib/feature_flags"; export async function projectAuthCheck(projectId: string) { + if (!USE_AUTH) { + return; + } const user = await authCheck(); const membership = await projectMembersCollection.findOne({ projectId, @@ -21,11 +25,9 @@ export async function projectAuthCheck(projectId: string) { throw new Error('User not a member of project'); } } -export async function createProject(formData: FormData) { - const user = await authCheck(); - // ensure that projects created by this user is less than - // configured limit +async function createBaseProject(name: string, user: any) { + // Check project limits const projectsLimit = Number(process.env.MAX_PROJECTS_PER_USER) || 0; if (projectsLimit > 0) { const count = await projectsCollection.countDocuments({ @@ -36,16 +38,14 @@ export async function createProject(formData: FormData) { } } - const name = formData.get('name') as string; - const templateKey = formData.get('template') as string; const projectId = crypto.randomUUID(); const chatClientId = crypto.randomBytes(16).toString('base64url'); const secret = crypto.randomBytes(32).toString('hex'); - // create project + // Create project await projectsCollection.insertOne({ _id: projectId, - name: name, + name, createdAt: (new Date()).toISOString(), lastUpdatedAt: (new Date()).toISOString(), createdByUserId: user.sub, @@ -55,7 +55,28 @@ export async function createProject(formData: FormData) { testRunCounter: 0, }); - // add first workflow version + // Add user to project + await projectMembersCollection.insertOne({ + userId: user.sub, + projectId: projectId, + createdAt: (new Date()).toISOString(), + lastUpdatedAt: (new Date()).toISOString(), + }); + + // Add first api key + await createApiKey(projectId); + + return projectId; +} + +export async function createProject(formData: FormData) { + const user = await authCheck(); + const name = formData.get('name') as string; + const templateKey = formData.get('template') as string; + + const projectId = await createBaseProject(name, user); + + // Add first workflow version with specified template const { agents, prompts, tools, startAgent } = templates[templateKey]; await agentWorkflowsCollection.insertOne({ projectId, @@ -68,17 +89,6 @@ export async function createProject(formData: FormData) { name: `Version 1`, }); - // add user to project - await projectMembersCollection.insertOne({ - userId: user.sub, - projectId: projectId, - createdAt: (new Date()).toISOString(), - lastUpdatedAt: (new Date()).toISOString(), - }); - - // add first api key - await createApiKey(projectId); - redirect(`/projects/${projectId}/workflow`); } @@ -212,3 +222,25 @@ export async function deleteProject(projectId: string) { redirect('/projects'); } + +export async function createProjectFromPrompt(formData: FormData) { + const user = await authCheck(); + const name = formData.get('name') as string; + + const projectId = await createBaseProject(name, user); + + // Add first workflow version with default template + const { agents, prompts, tools, startAgent } = templates['default']; + await agentWorkflowsCollection.insertOne({ + projectId, + agents, + prompts, + tools, + startAgent, + createdAt: (new Date()).toISOString(), + lastUpdatedAt: (new Date()).toISOString(), + name: `Version 1`, + }); + + return { id: projectId }; +} diff --git a/apps/rowboat/app/actions/testing_actions.ts b/apps/rowboat/app/actions/testing_actions.ts index c697b483..ed6ee745 100644 --- a/apps/rowboat/app/actions/testing_actions.ts +++ b/apps/rowboat/app/actions/testing_actions.ts @@ -170,6 +170,7 @@ export async function createSimulation( projectId: string, data: { name: string; + description?: string; scenarioId: string; profileId: string | null; passCriteria: string; @@ -195,6 +196,7 @@ export async function updateSimulation( simulationId: string, updates: { name?: string; + description?: string; scenarioId?: string; profileId?: string | null; passCriteria?: string; @@ -268,7 +270,6 @@ export async function deleteProfile(projectId: string, profileId: string): Promi await testProfilesCollection.deleteOne({ _id: new ObjectId(profileId), projectId, - default: false, }); } @@ -449,6 +450,15 @@ export async function updateRun( ); } +export async function cancelRun(projectId: string, runId: string): Promise { + await projectAuthCheck(projectId); + + await testRunsCollection.updateOne( + { _id: new ObjectId(runId), projectId }, + { $set: { status: 'cancelled' } } + ); +} + export async function listResults( projectId: string, runId: string, @@ -510,6 +520,7 @@ export async function createResult( simulationId: string; result: 'pass' | 'fail'; details: string; + transcript: string; } ): Promise>> { await projectAuthCheck(projectId); @@ -544,4 +555,56 @@ export async function updateResult( $set: updates, } ); +} + +export async function getSimulationResult( + projectId: string, + runId: string, + simulationId: string +): Promise> | null> { + await projectAuthCheck(projectId); + + const result = await testResultsCollection.findOne({ + projectId, + runId, + simulationId + }); + + if (!result) { + return null; + } + + const { _id, ...rest } = result; + return { + ...rest, + _id: _id.toString(), + }; +} + +export async function listRunSimulations( + projectId: string, + simulationIds: string[] +): Promise>[]> { + await projectAuthCheck(projectId); + + const simulations = await testSimulationsCollection + .find({ + _id: { $in: simulationIds.map(id => new ObjectId(id)) }, + projectId + }) + .toArray(); + + // Fetch associated scenario and profile names + const enrichedSimulations = await Promise.all(simulations.map(async (simulation) => { + const scenario = simulation.scenarioId ? await testScenariosCollection.findOne({ _id: new ObjectId(simulation.scenarioId) }) : null; + const profile = simulation.profileId ? await testProfilesCollection.findOne({ _id: new ObjectId(simulation.profileId) }) : null; + return { + ...simulation, + _id: simulation._id.toString(), + scenarioName: scenario?.name || 'Unknown', + profileName: profile?.name || 'None', + }; + })); + + return enrichedSimulations; } \ No newline at end of file diff --git a/apps/rowboat/app/actions/voice_actions.ts b/apps/rowboat/app/actions/voice_actions.ts new file mode 100644 index 00000000..52a3622f --- /dev/null +++ b/apps/rowboat/app/actions/voice_actions.ts @@ -0,0 +1,280 @@ +'use server'; + +import { TwilioConfigParams, TwilioConfigResponse, TwilioConfig, InboundConfigResponse } from "../lib/types/voice_types"; +import { twilioConfigsCollection } from "../lib/mongodb"; +import { ObjectId } from "mongodb"; +import twilio from 'twilio'; +import { Twilio } from 'twilio'; + +// Helper function to serialize MongoDB documents +function serializeConfig(config: any) { + return { + ...config, + _id: config._id.toString(), + createdAt: config.createdAt.toISOString(), + }; +} + +// Real implementation for configuring Twilio number +export async function configureTwilioNumber(params: TwilioConfigParams): Promise { + console.log('configureTwilioNumber - Received params:', params); + try { + const client = twilio(params.account_sid, params.auth_token); + + try { + // List all phone numbers and find the matching one + const numbers = await client.incomingPhoneNumbers.list(); + console.log('Twilio numbers for this account:', numbers); + const phoneExists = numbers.some( + number => number.phoneNumber === params.phone_number + ); + + if (!phoneExists) { + throw new Error('Phone number not found in this account'); + } + } catch (error) { + console.error('Error verifying phone number:', error); + throw new Error( + error instanceof Error + ? error.message + : 'Invalid phone number or phone number does not belong to this account' + ); + } + + // Save to MongoDB after successful validation + const savedConfig = await saveTwilioConfig(params); + console.log('configureTwilioNumber - Saved config result:', savedConfig); + + return { success: true }; + } catch (error) { + console.error('Error in configureTwilioNumber:', error); + return { + success: false, + error: error instanceof Error ? error.message : 'Failed to configure Twilio number' + }; + } +} + +// Save Twilio configuration to MongoDB +export async function saveTwilioConfig(params: TwilioConfigParams): Promise { + console.log('saveTwilioConfig - Incoming params:', { + ...params, + label: { + value: params.label, + type: typeof params.label, + length: params.label?.length, + isEmpty: params.label === '' + } + }); + + // First, list all configs to see what's in the database + const allConfigs = await twilioConfigsCollection + .find({ status: 'active' as const }) + .toArray(); + console.log('saveTwilioConfig - All active configs in DB:', allConfigs); + + // Find existing config for this project + const existingConfig = await twilioConfigsCollection.findOne({ + project_id: params.project_id, + status: 'active' as const + }); + console.log('saveTwilioConfig - Existing config search by project:', { + searchCriteria: { + project_id: params.project_id, + status: 'active' + }, + found: existingConfig + }); + + const configToSave = { + phone_number: params.phone_number, + account_sid: params.account_sid, + auth_token: params.auth_token, + label: params.label || '', // Use empty string instead of undefined + project_id: params.project_id, + workflow_id: params.workflow_id, + createdAt: existingConfig?.createdAt || new Date(), + status: 'active' as const + }; + console.log('saveTwilioConfig - Config to save:', configToSave); + + try { + // Configure inbound calls first + await configureInboundCall( + params.phone_number, + params.account_sid, + params.auth_token, + params.workflow_id + ); + + // Then save/update the config in database + if (existingConfig) { + console.log('saveTwilioConfig - Updating existing config:', existingConfig._id); + const result = await twilioConfigsCollection.updateOne( + { _id: existingConfig._id }, + { $set: configToSave } + ); + console.log('saveTwilioConfig - Update result:', result); + } else { + console.log('saveTwilioConfig - No existing config found, creating new'); + const result = await twilioConfigsCollection.insertOne(configToSave); + console.log('saveTwilioConfig - Insert result:', result); + } + + const savedConfig = await twilioConfigsCollection.findOne({ + project_id: params.project_id, + status: 'active' + }); + + if (!savedConfig) { + throw new Error('Failed to save Twilio configuration'); + } + + console.log('configureTwilioNumber - Saved config result:', savedConfig); + return savedConfig; + + } catch (error) { + console.error('Error saving Twilio config:', error); + throw error; + } +} + +// Get Twilio configuration for a workflow +export async function getTwilioConfigs(projectId: string) { + console.log('getTwilioConfigs - Fetching for projectId:', projectId); + const configs = await twilioConfigsCollection + .find({ + project_id: projectId, + status: 'active' as const + }) + .sort({ createdAt: -1 }) + .limit(1) + .toArray(); + + console.log('getTwilioConfigs - Raw configs:', configs); + const serializedConfigs = configs.map(serializeConfig); + console.log('getTwilioConfigs - Serialized configs:', serializedConfigs); + return serializedConfigs; +} + +// Delete a Twilio configuration (soft delete) +export async function deleteTwilioConfig(projectId: string, configId: string) { + console.log('deleteTwilioConfig - Deleting config:', { projectId, configId }); + const result = await twilioConfigsCollection.updateOne( + { + _id: new ObjectId(configId), + project_id: projectId + }, + { + $set: { status: 'deleted' as const } + } + ); + console.log('deleteTwilioConfig - Delete result:', result); + return result; +} + +// Mock implementation for testing/development +export async function mockConfigureTwilioNumber(params: TwilioConfigParams): Promise { + await new Promise(resolve => setTimeout(resolve, 1000)); + await saveTwilioConfig(params); + return { success: true }; +} + +export async function configureInboundCall( + phone_number: string, + account_sid: string, + auth_token: string, + workflow_id: string +): Promise { + try { + // Normalize phone number format + if (!phone_number.startsWith('+')) { + phone_number = '+' + phone_number; + } + + console.log('Configuring inbound call for:', { + phone_number, + workflow_id + }); + + // Initialize Twilio client + const client = new Twilio(account_sid, auth_token); + + // Find the phone number in Twilio account + const incomingPhoneNumbers = await client.incomingPhoneNumbers.list({ phoneNumber: phone_number }); + console.log('Found Twilio numbers:', incomingPhoneNumbers.map(n => ({ + phoneNumber: n.phoneNumber, + currentVoiceUrl: n.voiceUrl, + currentStatusCallback: n.statusCallback, + sid: n.sid + }))); + + if (!incomingPhoneNumbers.length) { + throw new Error(`Phone number ${phone_number} not found in Twilio account`); + } + + const phoneSid = incomingPhoneNumbers[0].sid; + const currentVoiceUrl = incomingPhoneNumbers[0].voiceUrl; + const wasPreviouslyConfigured = Boolean(currentVoiceUrl); + + // Get base URL from environment - MUST be a public URL + const baseUrl = process.env.VOICE_API_URL; + if (!baseUrl) { + throw new Error('Voice service URL not configured. Please set VOICE_API_URL environment variable.'); + } + + // Validate URL is not localhost + if (baseUrl.includes('localhost')) { + throw new Error('Voice service must use a public URL, not localhost.'); + } + + const inboundUrl = `${baseUrl}/inbound?workflow_id=${workflow_id}`; + console.log('Setting up webhooks:', { + voiceUrl: inboundUrl, + statusCallback: `${baseUrl}/call-status`, + currentConfig: { + voiceUrl: currentVoiceUrl, + statusCallback: incomingPhoneNumbers[0].statusCallback + } + }); + + // Update the phone number configuration + const updatedNumber = await client.incomingPhoneNumbers(phoneSid).update({ + voiceUrl: inboundUrl, + voiceMethod: 'POST', + statusCallback: `${baseUrl}/call-status`, + statusCallbackMethod: 'POST' + }); + + console.log('Webhook configuration complete:', { + phoneNumber: updatedNumber.phoneNumber, + newVoiceUrl: updatedNumber.voiceUrl, + newStatusCallback: updatedNumber.statusCallback, + success: updatedNumber.voiceUrl === inboundUrl + }); + + return { + status: wasPreviouslyConfigured ? 'reconfigured' : 'configured', + phone_number: phone_number, + workflow_id: workflow_id, + previous_webhook: wasPreviouslyConfigured ? currentVoiceUrl : undefined + }; + + } catch (err: unknown) { + console.error('Error configuring inbound call:', err); + + // Type guard for error with message property + if (err instanceof Error) { + if (err.message.includes('localhost')) { + throw new Error('Voice service needs to be accessible from the internet. Please check your configuration.'); + } + // Type guard for Twilio error + if ('code' in err && err.code === 21402) { + throw new Error('Invalid voice service URL. Please make sure it\'s a public, secure URL.'); + } + } + + // If we can't determine the specific error, throw a generic one + throw new Error('Failed to configure phone number. Please check your settings and try again.'); + } +} \ No newline at end of file diff --git a/apps/rowboat/app/api/v1/[projectId]/chat/route.ts b/apps/rowboat/app/api/v1/[projectId]/chat/route.ts index f4d9c4fc..9671ab1c 100644 --- a/apps/rowboat/app/api/v1/[projectId]/chat/route.ts +++ b/apps/rowboat/app/api/v1/[projectId]/chat/route.ts @@ -4,10 +4,9 @@ import { z } from "zod"; import { ObjectId } from "mongodb"; import { authCheck } from "../../utils"; import { ApiRequest, ApiResponse } from "../../../../lib/types/types"; -import { AgenticAPIChatRequest, AgenticAPIChatMessage, convertFromAgenticApiToApiMessages, convertFromApiToAgenticApiMessages, convertWorkflowToAgenticAPI } from "../../../../lib/types/agents_api_types"; -import { getAgenticApiResponse, callClientToolWebhook, runRAGToolCall, mockToolResponse } from "../../../../lib/utils"; +import { AgenticAPIChatRequest, convertFromAgenticApiToApiMessages, convertFromApiToAgenticApiMessages, convertWorkflowToAgenticAPI } from "../../../../lib/types/agents_api_types"; +import { getAgenticApiResponse } from "../../../../lib/utils"; import { check_query_limit } from "../../../../lib/rate_limiting"; -import { apiV1 } from "rowboat-shared"; import { PrefixLogger } from "../../../../lib/utils"; import { TestProfile } from "@/app/lib/types/testing_types"; @@ -70,7 +69,7 @@ export async function POST( logger.log(`Workflow ${workflowId} not found for project ${projectId}`); return Response.json({ error: "Workflow not found" }, { status: 404 }); } - + // if test profile is provided in the request, use it let testProfile: z.infer | null = null; if (result.data.testProfileId) { @@ -84,134 +83,30 @@ export async function POST( } } - // if profile has a context available, overwrite the system message in the request (if there is one) - let currentMessages = reqMessages; - if (testProfile?.context) { - // if there is a system message, overwrite it - const systemMessageIndex = reqMessages.findIndex(m => m.role === "system"); - if (systemMessageIndex !== -1) { - currentMessages[systemMessageIndex].content = testProfile.context; - } else { - // if there is no system message, add one - currentMessages.unshift({ role: "system", content: testProfile.context }); - } - } - - const MAX_TURNS = result.data.maxTurns ?? 3; let currentState: unknown = reqState ?? { last_agent_name: workflow.agents[0].name }; - let turns = 0; - let hasToolCalls = false; - do { - hasToolCalls = false; - // get assistant response - const { agents, tools, prompts, startAgent } = convertWorkflowToAgenticAPI(workflow); - const request: z.infer = { - messages: convertFromApiToAgenticApiMessages(currentMessages), - state: currentState, - agents, - tools, - prompts, - startAgent, - }; + // get assistant response + const { agents, tools, prompts, startAgent } = convertWorkflowToAgenticAPI(workflow); + const request: z.infer = { + projectId, + messages: convertFromApiToAgenticApiMessages(reqMessages), + state: currentState, + agents, + tools, + prompts, + startAgent, + testProfile: testProfile ?? undefined, + mcpServers: project.mcpServers ?? undefined, + toolWebhookUrl: project.webhookUrl ?? undefined, + }; - console.log(`turn ${turns}: sending agentic request from /chat api`, JSON.stringify(request, null, 2)); - logger.log(`Processing turn ${turns} for conversation`); - const { messages: agenticMessages, state } = await getAgenticApiResponse(request); - - const newMessages = convertFromAgenticApiToApiMessages(agenticMessages); - currentState = state; - - // if tool calls are to be skipped, return immediately - if (result.data.skipToolCalls) { - logger.log('Skipping tool calls as requested'); - const responseBody: z.infer = { - messages: newMessages, - state: currentState, - }; - return Response.json(responseBody); - } - - // get last message to check for tool calls - const lastMessage = newMessages[newMessages.length - 1]; - if (lastMessage?.role === "assistant" && - 'tool_calls' in lastMessage && - lastMessage.tool_calls?.length > 0) { - hasToolCalls = true; - const toolCallResultMessages: z.infer[] = []; - - // Process tool calls - for (const toolCall of lastMessage.tool_calls) { - let result: unknown; - if (toolCall.function.name === "getArticleInfo") { - logger.log(`Running RAG tool call for agent ${lastMessage.agenticSender}`); - // find the source ids attached to this agent in the workflow - const agent = workflow.agents.find(a => a.name === lastMessage.agenticSender); - if (!agent) { - return Response.json({ error: "Agent not found" }, { status: 404 }); - } - const sourceIds = agent.ragDataSources; - if (!sourceIds) { - return Response.json({ error: "Agent has no data sources" }, { status: 404 }); - } - try { - result = await runRAGToolCall(projectId, toolCall.function.arguments, sourceIds, agent.ragReturnType, agent.ragK); - logger.log(`RAG tool call completed for agent ${lastMessage.agenticSender}`); - } catch (e) { - logger.log(`Error running RAG tool call: ${e}`); - return Response.json({ error: "Error running RAG tool call" }, { status: 500 }); - } - } else { - logger.log(`Running client tool webhook for tool ${toolCall.function.name}`); - - try { - // if tool is supposed to be mocked, mock it - const workflowTool = workflow.tools.find(t => t.name === toolCall.function.name); - if (testProfile?.mockTools || workflowTool?.mockTool) { - logger.log(`Mocking tool call ${toolCall.function.name}`); - result = await mockToolResponse(toolCall.id, currentMessages, testProfile?.mockPrompt || workflowTool?.mockInstructions || ''); - } else { - // else run the tool call by calling the client tool webhook - logger.log(`Running client tool webhook for tool ${toolCall.function.name}`); - result = await callClientToolWebhook( - toolCall, - currentMessages, - projectId, - ); - } - } catch (e) { - logger.log(`Error in tool call ${toolCall.function.name}: ${e}`); - return Response.json({ error: `Error in tool call ${toolCall.function.name}` }, { status: 500 }); - } - logger.log(`Tool call ${toolCall.function.name} completed`); - } - - toolCallResultMessages.push({ - role: "tool", - tool_call_id: toolCall.id, - content: JSON.stringify(result), - tool_name: toolCall.function.name, - }); - } - - // Add new messages to the conversation - currentMessages = [...currentMessages, ...newMessages, ...toolCallResultMessages]; - } else { - // No tool calls, just add the new messages - currentMessages = [...currentMessages, ...newMessages]; - } - - turns++; - if (turns >= MAX_TURNS && hasToolCalls) { - logger.log(`Max turns (${MAX_TURNS}) reached for conversation`); - return Response.json({ error: "Max turns reached" }, { status: 429 }); - } - - } while (hasToolCalls); + const { messages: agenticMessages, state } = await getAgenticApiResponse(request); + const newMessages = convertFromAgenticApiToApiMessages(agenticMessages); + const newState = state; const responseBody: z.infer = { - messages: currentMessages.slice(reqMessages.length), - state: currentState, + messages: newMessages, + state: newState, }; return Response.json(responseBody); }); diff --git a/apps/rowboat/app/api/v1/stream-response/[streamId]/route.ts b/apps/rowboat/app/api/v1/stream-response/[streamId]/route.ts new file mode 100644 index 00000000..563db7bb --- /dev/null +++ b/apps/rowboat/app/api/v1/stream-response/[streamId]/route.ts @@ -0,0 +1,45 @@ +export async function GET(request: Request, { params }: { params: { streamId: string } }) { + // Replace with your actual upstream SSE endpoint. + const upstreamUrl = `${process.env.AGENTS_API_URL}/chat_stream/${params.streamId}`; + console.log('upstreamUrl', upstreamUrl); + + // Fetch the upstream SSE stream. + const upstreamResponse = await fetch(upstreamUrl, { + headers: { + 'Authorization': `Bearer ${process.env.AGENTS_API_KEY || 'test'}`, + }, + cache: 'no-store', + }); + + // If the upstream request fails, return a 502 Bad Gateway. + if (!upstreamResponse.ok || !upstreamResponse.body) { + return new Response("Error connecting to upstream SSE stream", { status: 502 }); + } + + const reader = upstreamResponse.body.getReader(); + + const stream = new ReadableStream({ + async start(controller) { + try { + // Read from the upstream stream continuously. + while (true) { + const { done, value } = await reader.read(); + if (done) break; + // Immediately enqueue each received chunk. + controller.enqueue(value); + } + controller.close(); + } catch (error) { + controller.error(error); + } + }, + }); + + return new Response(stream, { + headers: { + "Content-Type": "text/event-stream", + "Cache-Control": "no-cache", + "Connection": "keep-alive", + }, + }); +} \ No newline at end of file diff --git a/apps/rowboat/app/api/widget/v1/chats/[chatId]/turn/route.ts b/apps/rowboat/app/api/widget/v1/chats/[chatId]/turn/route.ts index 19a19edc..8d136e58 100644 --- a/apps/rowboat/app/api/widget/v1/chats/[chatId]/turn/route.ts +++ b/apps/rowboat/app/api/widget/v1/chats/[chatId]/turn/route.ts @@ -8,13 +8,10 @@ import { convertFromAgenticAPIChatMessages } from "../../../../../../lib/types/a import { convertToAgenticAPIChatMessages } from "../../../../../../lib/types/agents_api_types"; import { convertWorkflowToAgenticAPI } from "../../../../../../lib/types/agents_api_types"; import { AgenticAPIChatRequest } from "../../../../../../lib/types/agents_api_types"; -import { callClientToolWebhook, getAgenticApiResponse, runRAGToolCall, mockToolResponse } from "../../../../../../lib/utils"; +import { getAgenticApiResponse } from "../../../../../../lib/utils"; import { check_query_limit } from "../../../../../../lib/rate_limiting"; import { PrefixLogger } from "../../../../../../lib/utils"; -// Add max turns constant at the top with other constants -const MAX_TURNS = 3; - // get next turn / agent response export async function POST( req: NextRequest, @@ -23,7 +20,7 @@ export async function POST( return await authCheck(req, async (session) => { const { chatId } = await params; const logger = new PrefixLogger(`widget-chat:${chatId}`); - + logger.log(`Processing turn request for chat ${chatId}`); // check query limit @@ -95,101 +92,33 @@ export async function POST( // get assistant response const { agents, tools, prompts, startAgent } = convertWorkflowToAgenticAPI(workflow); const unsavedMessages: z.infer[] = [userMessage]; - let resolvingToolCalls = true; - let state: unknown = chat.agenticState ?? {last_agent_name: startAgent}; - let turns = 0; // Add turns counter + let state: unknown = chat.agenticState ?? { last_agent_name: startAgent }; - while (resolvingToolCalls) { - if (turns >= MAX_TURNS) { - logger.log(`Max turns (${MAX_TURNS}) reached for chat ${chatId}`); - throw new Error("Max turns reached"); - } - turns++; - - const request: z.infer = { - messages: convertToAgenticAPIChatMessages([systemMessage, ...messages, ...unsavedMessages]), - state, - agents, - tools, - prompts, - startAgent, - }; - logger.log(`Turn ${turns}: sending agentic request`); - const response = await getAgenticApiResponse(request); - state = response.state; - if (response.messages.length === 0) { - throw new Error("No messages returned from assistant"); - } - const convertedMessages = convertFromAgenticAPIChatMessages(response.messages); - unsavedMessages.push(...convertedMessages.map(m => ({ - ...m, - version: 'v1' as const, - chatId, - createdAt: new Date().toISOString(), - }))); - - // if the last messages is tool call, execute them - const lastMessage = convertedMessages[convertedMessages.length - 1]; - if (lastMessage.role === 'assistant' && 'tool_calls' in lastMessage) { - logger.log(`Processing ${lastMessage.tool_calls.length} tool calls`); - const toolCallResults = await Promise.all(lastMessage.tool_calls.map(async toolCall => { - logger.log(`Executing tool call: ${toolCall.function.name}`); - try { - if (toolCall.function.name === "getArticleInfo") { - logger.log(`Processing RAG tool call for agent ${lastMessage.agenticSender}`); - const agent = workflow.agents.find(a => a.name === lastMessage.agenticSender); - if (!agent || !agent.ragDataSources) { - throw new Error("Agent not found or has no data sources"); - } - return await runRAGToolCall( - session.projectId, - toolCall.function.arguments, - agent.ragDataSources, - agent.ragReturnType, - agent.ragK - ); - } - - const workflowTool = workflow.tools.find(t => t.name === toolCall.function.name); - if (workflowTool?.mockTool) { - logger.log(`Using mock response for tool: ${toolCall.function.name}`); - return await mockToolResponse( - toolCall.id, - [...messages, ...unsavedMessages], - workflowTool.mockInstructions || '' - ); - } - - logger.log(`Calling webhook for tool: ${toolCall.function.name}`); - return await callClientToolWebhook( - toolCall, - [...messages, ...unsavedMessages], - session.projectId, - ); - } catch (error) { - logger.log(`Error executing tool call ${toolCall.id}: ${error}`); - return { error: "Tool execution failed" }; - } - })); - unsavedMessages.push(...toolCallResults.map((result, index) => ({ - version: 'v1' as const, - chatId, - createdAt: new Date().toISOString(), - role: 'tool' as const, - tool_call_id: lastMessage.tool_calls[index].id, - tool_name: lastMessage.tool_calls[index].function.name, - content: JSON.stringify(result), - }))); - } else { - // ensure that the last message is from an assistant - // and is of an external type - if (lastMessage.role !== 'assistant' || lastMessage.agenticResponseType !== 'external') { - throw new Error("Last message is not from an assistant and is not of an external type"); - } - resolvingToolCalls = false; - break; - } + const request: z.infer = { + projectId: session.projectId, + messages: convertToAgenticAPIChatMessages([systemMessage, ...messages, ...unsavedMessages]), + state, + agents, + tools, + prompts, + startAgent, + mcpServers: projectSettings.mcpServers ?? undefined, + toolWebhookUrl: projectSettings.webhookUrl ?? undefined, + testProfile: undefined, + }; + logger.log(`Sending agentic request`); + const response = await getAgenticApiResponse(request); + state = response.state; + if (response.messages.length === 0) { + throw new Error("No messages returned from assistant"); } + const convertedMessages = convertFromAgenticAPIChatMessages(response.messages); + unsavedMessages.push(...convertedMessages.map(m => ({ + ...m, + version: 'v1' as const, + chatId, + createdAt: new Date().toISOString(), + }))); logger.log(`Saving ${unsavedMessages.length} new messages and updating chat state`); await chatMessagesCollection.insertMany(unsavedMessages); diff --git a/apps/rowboat/app/lib/components/datasource-icon.tsx b/apps/rowboat/app/lib/components/datasource-icon.tsx index 7b445061..18543b51 100644 --- a/apps/rowboat/app/lib/components/datasource-icon.tsx +++ b/apps/rowboat/app/lib/components/datasource-icon.tsx @@ -1,10 +1,10 @@ -import { FileIcon, FilesIcon, GlobeIcon } from "lucide-react"; +import { FileIcon, FilesIcon, FileTextIcon, GlobeIcon } from "lucide-react"; export function DataSourceIcon({ type = undefined, size = "sm", }: { - type?: "crawl" | "urls" | "files" | undefined; + type?: "crawl" | "urls" | "files" | "text" | undefined; size?: "sm" | "md"; }) { const sizeClass = size === "sm" ? "w-4 h-4" : "w-6 h-6"; @@ -13,5 +13,6 @@ export function DataSourceIcon({ {type == "crawl" && } {type == "urls" && } {type == "files" && } + {type == "text" && } ; } diff --git a/apps/rowboat/app/lib/components/editable-field-with-immediate-save.tsx b/apps/rowboat/app/lib/components/editable-field-with-immediate-save.tsx new file mode 100644 index 00000000..472053ac --- /dev/null +++ b/apps/rowboat/app/lib/components/editable-field-with-immediate-save.tsx @@ -0,0 +1,204 @@ +import { Button, Input, Textarea } from "@heroui/react"; +import { useEffect, useRef, useState } from "react"; +import { useClickAway } from "../../../hooks/use-click-away"; +import MarkdownContent from "./markdown-content"; +import clsx from "clsx"; +import { Label } from "./label"; +import { SparklesIcon } from "lucide-react"; + +interface EditableFieldProps { + value: string; + onChange: (value: string) => void; + label?: string; + placeholder?: string; + markdown?: boolean; + multiline?: boolean; + locked?: boolean; + className?: string; + validate?: (value: string) => { valid: boolean; errorMessage?: string }; + light?: boolean; + error?: string | null; + inline?: boolean; + showGenerateButton?: { + show: boolean; + setShow: (show: boolean) => void; + }; + disabled?: boolean; + type?: string; +} + +export function EditableField({ + value, + onChange, + label, + placeholder = "Click to edit...", + markdown = false, + multiline = false, + locked = false, + className = "flex flex-col gap-1 w-full", + validate, + light = false, + error, + inline = false, + showGenerateButton, + disabled = false, + type = "text", +}: EditableFieldProps) { + const [isEditing, setIsEditing] = useState(false); + const [localValue, setLocalValue] = useState(value); + const ref = useRef(null); + + const validationResult = validate?.(localValue); + const isValid = !validate || validationResult?.valid; + + useEffect(() => { + setLocalValue(value); + }, [value]); + + useClickAway(ref, () => { + if (isEditing) { + if (isValid && localValue !== value) { + onChange(localValue); + } else { + setLocalValue(value); + } + setIsEditing(false); + } + }); + + const onValueChange = (newValue: string) => { + setLocalValue(newValue); + onChange(newValue); // Always save immediately + }; + + const commonProps = { + autoFocus: true, + value: localValue, + onValueChange: onValueChange, + variant: "bordered" as const, + labelPlacement: "outside" as const, + placeholder: markdown ? '' : placeholder, + classNames: { + input: "rounded-md", + inputWrapper: "rounded-md border-medium" + }, + radius: "md" as const, + isInvalid: !isValid, + errorMessage: validationResult?.errorMessage, + onKeyDown: (e: React.KeyboardEvent) => { + if (!multiline && e.key === "Enter") { + e.preventDefault(); + if (isValid && localValue !== value) { + onChange(localValue); + } + setIsEditing(false); + } + if (e.key === "Escape") { + setLocalValue(value); + setIsEditing(false); + } + }, + }; + + if (isEditing) { + return ( +
+ {label && ( +
+
+ )} + {multiline && - -
} ; } @@ -594,65 +231,61 @@ function ExpandableContent({ function SystemMessage({ content, onChange, - locked + locked = false, }: { content: string, onChange: (content: string) => void, - locked: boolean + locked?: boolean, }) { - return ( -
-
CONTEXT
- -
- ); + return
+ +
; } export function Messages({ projectId, - systemMessage, messages, toolCallResults, - handleToolCallResults, loadingAssistantResponse, - loadingUserResponse, workflow, - testProfile=null, + testProfile = null, + systemMessage, onSystemMessageChange, }: { projectId: string; - systemMessage: string | undefined; messages: z.infer[]; toolCallResults: Record>; - handleToolCallResults: (results: z.infer[]) => void; loadingAssistantResponse: boolean; - loadingUserResponse: boolean; workflow: z.infer; testProfile: z.infer | null; + systemMessage: string | undefined; onSystemMessageChange: (message: string) => void; }) { const messagesEndRef = useRef(null); let lastUserMessageTimestamp = 0; + let userMessageSeen = false; // scroll to bottom on new messages useEffect(() => { messagesEndRef.current?.scrollIntoView({ behavior: "smooth" }) - }, [messages, loadingAssistantResponse, loadingUserResponse]); + }, [messages, loadingAssistantResponse]); return
0} + locked={testProfile !== null} /> {messages.map((message, index) => { if (message.role === 'assistant') { @@ -661,7 +294,6 @@ export function Messages({ key={index} toolCalls={message.tool_calls} results={toolCallResults} - handleResults={handleToolCallResults} projectId={projectId} messages={messages} sender={message.agenticSender} @@ -671,7 +303,11 @@ export function Messages({ />; } else { // the assistant message createdAt is an ISO string timestamp - const latency = new Date(message.createdAt).getTime() - lastUserMessageTimestamp; + let latency = new Date(message.createdAt).getTime() - lastUserMessageTimestamp; + // if this is the first message, set the latency to 0 + if (!userMessageSeen) { + latency = 0; + } if (message.agenticResponseType === 'internal') { return ( ; } return <>; })} {loadingAssistantResponse && } - {loadingUserResponse && }
; diff --git a/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/source-page.tsx b/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/source-page.tsx index 1e65495e..81b5a642 100644 --- a/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/source-page.tsx +++ b/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/source-page.tsx @@ -13,6 +13,7 @@ import { TableLabel, TableValue } from "./shared"; import { ScrapeSource } from "./scrape-source"; import { FilesSource } from "./files-source"; import { getDataSource } from "../../../../actions/datasource_actions"; +import { TextSource } from "./text-source"; export function SourcePage({ sourceId, @@ -118,6 +119,10 @@ export function SourcePage({
File upload
} + {source.data.type === 'text' &&
+ +
Text
+
} @@ -131,6 +136,7 @@ export function SourcePage({ {source.data.type === 'urls' && } {source.data.type === 'files' && } + {source.data.type === 'text' && }
diff --git a/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/text-source.tsx b/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/text-source.tsx new file mode 100644 index 00000000..d16549f6 --- /dev/null +++ b/apps/rowboat/app/projects/[projectId]/sources/[sourceId]/text-source.tsx @@ -0,0 +1,128 @@ +"use client"; +import { PageSection } from "../../../../lib/components/page-section"; +import { WithStringId } from "../../../../lib/types/types"; +import { DataSource } from "../../../../lib/types/datasource_types"; +import { z } from "zod"; +import { useState, useEffect } from "react"; +import { Textarea } from "@heroui/react"; +import { FormStatusButton } from "../../../../lib/components/form-status-button"; +import { Spinner } from "@heroui/react"; +import { addDocsToDataSource, deleteDocsFromDataSource, listDocsInDataSource } from "../../../../actions/datasource_actions"; + +export function TextSource({ + projectId, + dataSource, + handleReload, +}: { + projectId: string, + dataSource: WithStringId>, + handleReload: () => void; +}) { + const [content, setContent] = useState(""); + const [docId, setDocId] = useState(null); + const [isLoading, setIsLoading] = useState(true); + const [isSaving, setIsSaving] = useState(false); + + useEffect(() => { + let ignore = false; + + async function fetchContent() { + setIsLoading(true); + try { + const { files } = await listDocsInDataSource({ + projectId, + sourceId: dataSource._id, + limit: 1, + }); + + console.log('got data', files); + + if (!ignore && files.length > 0) { + const doc = files[0]; + if (doc.data.type === 'text') { + setContent(doc.data.content); + setDocId(doc._id); + } + } + } catch (error) { + console.error('Error fetching content:', error); + } finally { + setIsLoading(false); + } + } + + fetchContent(); + return () => { + ignore = true; + }; + }, [projectId, dataSource._id]); + + async function handleSubmit(formData: FormData) { + setIsSaving(true); + try { + const newContent = formData.get('content') as string; + + // Delete existing doc if it exists + if (docId) { + await deleteDocsFromDataSource({ + projectId, + sourceId: dataSource._id, + docIds: [docId], + }); + } + + // Add new doc + await addDocsToDataSource({ + projectId, + sourceId: dataSource._id, + docData: [{ + name: 'text', + data: { + type: 'text', + content: newContent, + }, + }], + }); + + handleReload(); + } finally { + setIsSaving(false); + } + } + + if (isLoading) { + return ( + +
+ +

Loading content...

+
+ + ); + } + + return ( + +
+