Add support for other providers - litellm, openrouter

README.md

@@ -31,6 +31,8 @@ Powered by OpenAI's Agents SDK, Rowboat is the fastest way to build multi-agents
 
 3. Access the app at [http://localhost:3000](http://localhost:3000).
 
+Note: See the [Using custom LLM providers](https://docs.rowboatlabs.com/setup/#using-custom-llm-providers) section of our docs for using custom providers like OpenRouter and LiteLLM.
+
 ## Demo
 
 #### Create a multi-agent assistant with MCP tools by chatting with Rowboat

apps/copilot/app.py

@@ -1,7 +1,7 @@
 from flask import Flask, request, jsonify, Response, stream_with_context
 from pydantic import BaseModel, ValidationError
 from typing import List
-from copilot import UserMessage, AssistantMessage, get_response, openai_client
+from copilot import UserMessage, AssistantMessage, get_response
 from streaming import get_streaming_response
 from lib import AgentContext, PromptContext, ToolContext, ChatContext
 import os

apps/copilot/client.py

@@ -0,0 +1,24 @@
+import os
+from openai import OpenAI
+import dotenv
+dotenv.load_dotenv()
+
+PROVIDER_BASE_URL = os.getenv('PROVIDER_BASE_URL', '')
+PROVIDER_API_KEY = os.getenv('PROVIDER_API_KEY', os.getenv('OPENAI_API_KEY', ''))
+PROVIDER_DEFAULT_MODEL = os.getenv('PROVIDER_DEFAULT_MODEL', 'gpt-4.1')
+
+if not PROVIDER_API_KEY:
+    raise ValueError("No LLM Provider API key found")
+
+completions_client = None
+if PROVIDER_BASE_URL:
+    print(f"Using provider {PROVIDER_BASE_URL}, for completions")
+    completions_client = OpenAI(
+        base_url=PROVIDER_BASE_URL, 
+        api_key=PROVIDER_API_KEY
+    )
+else:
+    print(f"Using OpenAI directly for completions")
+    completions_client = OpenAI(
+        api_key=PROVIDER_API_KEY
+    )

apps/copilot/copilot.py

@@ -4,9 +4,8 @@ from pydantic import BaseModel, ValidationError
 from typing import List, Dict, Any, Literal
 import json
 from lib import AgentContext, PromptContext, ToolContext, ChatContext
-
+from client import PROVIDER_DEFAULT_MODEL
-openai_client = OpenAI()
+from client import completions_client
-MODEL_NAME = "gpt-4.1"  # OpenAI model name
 
 class UserMessage(BaseModel):
     role: Literal["user"]
@@ -75,8 +74,8 @@ User: {last_message.content}
         message.model_dump() for message in messages
     ]
 
-    response = openai_client.chat.completions.create(
+    response = completions_client.chat.completions.create(
-        model=MODEL_NAME,
+        model=PROVIDER_DEFAULT_MODEL,
         messages=updated_msgs,
         temperature=0.0,
         response_format={"type": "json_object"}

apps/copilot/requirements.txt

@@ -18,6 +18,7 @@ openai==1.61.0
 packaging==24.2
 pydantic==2.10.3
 pydantic_core==2.27.1
+python-dotenv
 sniffio==1.3.1
 tqdm==4.67.1
 typing_extensions==4.12.2

apps/copilot/streaming.py

@@ -4,9 +4,8 @@ from pydantic import BaseModel, ValidationError
 from typing import List, Dict, Any, Literal
 import json
 from lib import AgentContext, PromptContext, ToolContext, ChatContext
-
+from client import PROVIDER_DEFAULT_MODEL
-openai_client = OpenAI()
+from client import completions_client
-MODEL_NAME = "gpt-4.1"  # OpenAI model name
 
 class UserMessage(BaseModel):
     role: Literal["user"]
@@ -90,8 +89,8 @@ User: {last_message.content}
         message.model_dump() for message in messages
     ]
 
-    return openai_client.chat.completions.create(
+    return completions_client.chat.completions.create(
-        model=MODEL_NAME,
+        model=PROVIDER_DEFAULT_MODEL,
         messages=updated_msgs,
         temperature=0.0,
         stream=True

apps/docs/docs/setup.md

@@ -0,0 +1,127 @@
+## Getting started
+
+- ✨ **Start from an idea → Copilot builds your multi-agent workflows**  
+  E.g. "Build me an assistant for a food delivery company to handle delivery status and missing items. Include the necessary tools."
+- 🌐 **Connect MCP servers**  
+  Add the MCP servers in Settings → import the tools into Rowboat.
+- 📞 **Integrate into your app using the HTTP API or Python SDK**  
+  Grab the Project ID and generated API Key from Settings and use the API.
+
+Powered by OpenAI's Agents SDK, Rowboat is the fastest way to build multi-agents!
+
+## Quick start
+
+Step 1. Set your OpenAI key:
+
+```bash
+export OPENAI_API_KEY=your-openai-api-key
+```
+      
+Step 2. Clone the repository and start Rowboat docker
+
+```bash
+git clone git@github.com:rowboatlabs/rowboat.git
+cd rowboat
+docker-compose up --build
+```
+
+Step 3. Access the app at [http://localhost:3000](http://localhost:3000).
+
+Note: See the [Using custom LLM providers](#using-custom-llm-providers) section below for using custom providers like OpenRouter and LiteLLM.
+
+## Demo
+
+#### Create a multi-agent assistant with MCP tools by chatting with Rowboat
+[![Screenshot 2025-04-23 at 00 25 31](https://github.com/user-attachments/assets/c8a41622-8e0e-459f-becb-767503489866)](https://youtu.be/YRTCw9UHRbU)
+
+## Integrate with Rowboat agents
+
+There are 2 ways to integrate with the agents you create in Rowboat
+
+**Option #1: HTTP API**
+
+You can use the API directly at [http://localhost:3000/api/v1/](http://localhost:3000/api/v1/). See [API Docs](https://docs.rowboatlabs.com/using_the_api/) for details.
+
+```bash
+curl --location 'http://localhost:3000/api/v1/<PROJECT_ID>/chat' \
+--header 'Content-Type: application/json' \
+--header 'Authorization: Bearer <API_KEY>' \
+--data '{
+    "messages": [
+        {
+            "role": "user",
+            "content": "tell me the weather in london in metric units"
+        }
+    ],
+    "state": null
+}'
+```
+   
+
+**Option #2: Python SDK**
+   
+You can use the included Python SDK to interact with the Agents
+
+```python
+from rowboat import Client, StatefulChat
+from rowboat.schema import UserMessage, SystemMessage
+
+# Initialize the client
+client = Client(
+    host="http://localhost:3000",
+    project_id="<PROJECT_ID>",
+    api_key="<API_KEY>"
+)
+
+# Create a stateful chat session (recommended)
+chat = StatefulChat(client)
+response = chat.run("What's the weather in London?")
+print(response)
+
+# Or use the low-level client API
+messages = [
+    SystemMessage(role='system', content="You are a helpful assistant"),
+    UserMessage(role='user', content="Hello, how are you?")
+]
+
+# Get response
+response = client.chat(messages=messages)
+print(response.messages[-1].content)
+```
+
+## Using custom LLM providers
+By default, Rowboat uses OpenAI LLMs (gpt-4o, gpt-4.1, etc.) for both agents and copilot, when you export your OPENAI_API_KEY. 
+
+However, you can also configure custom LLM providers (e.g. LiteLLM, OpenRouter) to use any of the hundreds of available LLMs beyond OpenAI, such as Claude, DeepSeek, Ollama LLMs and so on.
+
+**Step 1:** Set up your custom LLM provider using the variables below, for example (assuming LiteLLM):
+
+```bash
+export PROVIDER_BASE_URL=http://host.docker.internal:4000/
+export PROVIDER_API_KEY=sk-1234
+```
+
+Rowboat uses "gpt-4.1" as the default model for agents and copilot but this can be overridden as follows, for example (assuming LiteLLM):
+
+```bash
+export PROVIDER_DEFAULT_MODEL=claude-3-7-sonnet-latest
+export PROVIDER_COPILOT_MODEL=gpt-4o
+```
+
+**Notes:**
+
+- Copilot is optimized for gpt-4o/gpt-4.1. We strongly recommend using these models for best performance.
+- You can specify different models for the copilot and each agent, but all of them must belong to the same provider (e.g. LiteLLM)
+- The integration is provider-agnostic and should work with any service that implements the OpenAI messages format.
+- OpenAI-specific tools (e.g., web_search) will not work with non-OpenAI providers. If you get an error, remove these tools.
+
+**Step 2 (No change):** Clone the repository and start Rowboat docker
+
+```bash
+git clone git@github.com:rowboatlabs/rowboat.git
+cd rowboat
+docker-compose up --build
+```
+
+**Step 3 (No change):** Access the app at [http://localhost:3000](http://localhost:3000).
+

apps/docs/mkdocs.yml

@@ -4,6 +4,7 @@ theme:
   name: material
   favicon: img/favicon.ico
 nav:
+  - Getting Started: setup.md
   - Overview:
     - Introduction: index.md
     - Open Source License: license.md

apps/rowboat/app/lib/project_templates.ts

@@ -1,6 +1,8 @@
 import { WorkflowTemplate } from "./types/workflow_types";
 import { z } from 'zod';
 
+const DEFAULT_MODEL = process.env.PROVIDER_DEFAULT_MODEL || "gpt-4.1";
+
 export const templates: { [key: string]: z.infer<typeof WorkflowTemplate> } = {
     // Default template
     'default': {
@@ -37,7 +39,7 @@ You are an helpful customer support assistant
 
 ❌ Don'ts:
 - don't ask user any other detail than email`,
-                model: "gpt-4o",
+                model: DEFAULT_MODEL,
                 toggleAble: true,
                 ragReturnType: "chunks",
                 ragK: 3,

apps/rowboat/app/lib/types/workflow_types.ts

@@ -10,12 +10,7 @@ export const WorkflowAgent = z.object({
     disabled: z.boolean().default(false).optional(),
     instructions: z.string(),
     examples: z.string().optional(),
-    model: z.union([
+    model: z.string(),
-        z.literal('gpt-4.1'),
-        z.literal('gpt-4o'),
-        z.literal('gpt-4.1-mini'),
-        z.literal('gpt-4o-mini'),
-    ]),
     locked: z.boolean().default(false).describe('Whether this agent is locked and cannot be deleted').optional(),
     toggleAble: z.boolean().default(true).describe('Whether this agent can be enabled or disabled').optional(),
     global: z.boolean().default(false).describe('Whether this agent is a global agent, in which case it cannot be connected to other agents').optional(),

apps/rowboat/app/projects/[projectId]/entities/agent_config.tsx

@@ -20,6 +20,8 @@ import { Button as CustomButton } from "@/components/ui/button";
 import clsx from "clsx";
 import { EditableField } from "@/app/lib/components/editable-field";
 import { USE_TRANSFER_CONTROL_OPTIONS } from "@/app/lib/feature_flags";
+import { Input } from "@/components/ui/input";
+import { Info } from "lucide-react";
 
 // Common section header styles
 const sectionHeaderStyles = "text-xs font-medium uppercase tracking-wider text-gray-500 dark:text-gray-400";
@@ -405,20 +407,33 @@ export function AgentConfig({
                 )}
 
                 <div className="space-y-4">
-                    <label className={sectionHeaderStyles}>
+                    <div className="flex items-center">
-                        Model
+                        <label className={sectionHeaderStyles}>
-                    </label>
+                            Model
-                    <CustomDropdown
+                        </label>
+                        <div className="relative ml-2 group">
+                            <Info 
+                                className="w-4 h-4 text-gray-500 dark:text-gray-400 hover:text-gray-700 dark:hover:text-gray-300 cursor-pointer transition-colors"
+                            />
+                            <div className="absolute bottom-full left-0 mb-2 p-3 w-80 rounded-lg shadow-lg border border-gray-200 dark:border-gray-700 bg-white dark:bg-gray-800 text-gray-700 dark:text-gray-300 text-xs invisible group-hover:visible z-50">
+                                <div className="mb-1 font-medium">Model Configuration</div>
+                                Set this according to the PROVIDER_BASE_URL you have set in your .env file (such as your LiteLLM, gateway). 
+                                <br />
+                                <br />
+                                E.g. LiteLLM&apos;s naming convention is like: &apos;claude-3-7-sonnet-latest&apos;, but you may have set alias model names or might be using a different provider like openrouter, openai etc. 
+                                <br />
+                                <br />
+                                By default, the model is set to gpt-4.1, assuming your OpenAI API key is set in PROVIDER_API_KEY and PROVIDER_BASE_URL is not set.
+                                <div className="absolute h-2 w-2 bg-white dark:bg-gray-800 transform rotate-45 -bottom-1 left-4 border-r border-b border-gray-200 dark:border-gray-700"></div>
+                            </div>
+                        </div>
+                    </div>
+                    <Input
                         value={agent.model}
-                        options={WorkflowAgent.shape.model.options.map((model) => ({
+                        onChange={(e) => handleUpdate({
-                            key: model.value,
-                            label: model.value
-                        }))}
-                        onChange={(value) => handleUpdate({
                             ...agent,
-                            model: value as z.infer<typeof WorkflowAgent>['model']
+                            model: e.target.value as z.infer<typeof WorkflowAgent>['model']
                         })}
-                        className="w-40"
                     />
                 </div>
 

apps/rowboat/app/projects/[projectId]/playground/components/chat.tsx

@@ -202,6 +202,19 @@ export function Chat({
                 setLoadingAssistantResponse(false);
             });
 
+            eventSource.addEventListener('stream_error', (event) => {
+                if (eventSource) {
+                    eventSource.close();
+                }
+
+                console.error('SSE Error:', event);
+                if (!ignore) {
+                    setLoadingAssistantResponse(false);
+                    setFetchResponseError('Error: ' + JSON.parse(event.data).error);
+                    setOptimisticMessages(messages);
+                }
+            });
+
             eventSource.onerror = (error) => {
                 console.error('SSE Error:', error);
                 if (!ignore) {

apps/rowboat/app/projects/[projectId]/workflow/app.tsx

@@ -15,9 +15,11 @@ import { getProjectConfig } from "@/app/actions/project_actions";
 export function App({
     projectId,
     useRag,
+    defaultModel,
 }: {
     projectId: string;
     useRag: boolean;
+    defaultModel: string;
 }) {
     const [selectorKey, setSelectorKey] = useState(0);
     const [workflow, setWorkflow] = useState<WithStringId<z.infer<typeof Workflow>> | null>(null);
@@ -118,6 +120,7 @@ export function App({
             useRag={useRag}
             mcpServerUrls={mcpServerUrls}
             toolWebhookUrl={toolWebhookUrl}
+            defaultModel={defaultModel}
         />}
     </>
 }

apps/rowboat/app/projects/[projectId]/workflow/page.tsx

@@ -3,6 +3,7 @@ import { App } from "./app";
 import { USE_RAG } from "@/app/lib/feature_flags";
 import { projectsCollection } from "@/app/lib/mongodb";
 import { notFound } from "next/navigation";
+const DEFAULT_MODEL = process.env.PROVIDER_DEFAULT_MODEL || "gpt-4.1";
 
 export const metadata: Metadata = {
     title: "Workflow"
@@ -25,6 +26,7 @@ export default async function Page({
         <App
             projectId={params.projectId}
             useRag={USE_RAG}
+            defaultModel={DEFAULT_MODEL}
         />
     );
 }

apps/rowboat/app/projects/[projectId]/workflow/workflow_editor.tsx

@@ -263,7 +263,7 @@ function reducer(state: State, action: Action): State {
                                 description: "",
                                 disabled: false,
                                 instructions: "",
-                                model: "gpt-4o",
+                                model: "",
                                 locked: false,
                                 toggleAble: true,
                                 ragReturnType: "chunks",
@@ -552,7 +552,6 @@ function reducer(state: State, action: Action): State {
                 draft.currentIndex++;
                 draft.present = nextState;
             });
-
         }
     }
 
@@ -568,6 +567,7 @@ export function WorkflowEditor({
     useRag,
     mcpServerUrls,
     toolWebhookUrl,
+    defaultModel,
 }: {
     dataSources: WithStringId<z.infer<typeof DataSource>>[];
     workflow: WithStringId<z.infer<typeof Workflow>>;
@@ -577,6 +577,7 @@ export function WorkflowEditor({
     useRag: boolean;
     mcpServerUrls: Array<z.infer<typeof MCPServer>>;
     toolWebhookUrl: string;
+    defaultModel: string;
 }) {
     const [state, dispatch] = useReducer<Reducer<State, Action>>(reducer, {
         patches: [],
@@ -659,7 +660,11 @@ export function WorkflowEditor({
     }
 
     function handleAddAgent(agent: Partial<z.infer<typeof WorkflowAgent>> = {}) {
-        dispatch({ type: "add_agent", agent });
+        const agentWithModel = {
+            ...agent,
+            model: agent.model || defaultModel || "gpt-4o"
+        };
+        dispatch({ type: "add_agent", agent: agentWithModel });
     }
 
     function handleAddTool(tool: Partial<z.infer<typeof WorkflowTool>> = {}) {

apps/rowboat_agents/poetry.lock

@@ -984,14 +984,14 @@ files = [
 
 [[package]]
 name = "griffe"
-version = "1.6.2"
+version = "1.7.3"
 description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "griffe-1.6.2-py3-none-any.whl", hash = "sha256:6399f7e663150e4278a312a8e8a14d2f3d7bd86e2ef2f8056a1058e38579c2ee"},
+    {file = "griffe-1.7.3-py3-none-any.whl", hash = "sha256:c6b3ee30c2f0f17f30bcdef5068d6ab7a2a4f1b8bf1a3e74b56fffd21e1c5f75"},
-    {file = "griffe-1.6.2.tar.gz", hash = "sha256:3a46fa7bd83280909b63c12b9a975732a927dd97809efe5b7972290b606c5d91"},
+    {file = "griffe-1.7.3.tar.gz", hash = "sha256:52ee893c6a3a968b639ace8015bec9d36594961e156e23315c8e8e51401fa50b"},
 ]
 
 [package.dependencies]
@@ -1819,14 +1819,14 @@ files = [
 
 [[package]]
 name = "mcp"
-version = "1.5.0"
+version = "1.6.0"
 description = "Model Context Protocol SDK"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "mcp-1.5.0-py3-none-any.whl", hash = "sha256:51c3f35ce93cb702f7513c12406bbea9665ef75a08db909200b07da9db641527"},
+    {file = "mcp-1.6.0-py3-none-any.whl", hash = "sha256:7bd24c6ea042dbec44c754f100984d186620d8b841ec30f1b19eda9b93a634d0"},
-    {file = "mcp-1.5.0.tar.gz", hash = "sha256:5b2766c05e68e01a2034875e250139839498c61792163a7b221fc170c12f5aa9"},
+    {file = "mcp-1.6.0.tar.gz", hash = "sha256:d9324876de2c5637369f43161cd71eebfd803df5a95e46225cab8d280e366723"},
 ]
 
 [package.dependencies]
@@ -2151,14 +2151,14 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.68.0"
+version = "1.76.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "openai-1.68.0-py3-none-any.whl", hash = "sha256:20e279b0f3a78cb4a95f3eab2a180f3ee30c6a196aeebd6bf642a4f88ab85ee1"},
+    {file = "openai-1.76.0-py3-none-any.whl", hash = "sha256:a712b50e78cf78e6d7b2a8f69c4978243517c2c36999756673e07a14ce37dc0a"},
-    {file = "openai-1.68.0.tar.gz", hash = "sha256:c570c06c9ba10f98b891ac30a3dd7b5c89ed48094c711c7a3f35fb5ade6c0757"},
+    {file = "openai-1.76.0.tar.gz", hash = "sha256:fd2bfaf4608f48102d6b74f9e11c5ecaa058b60dad9c36e409c12477dfd91fb2"},
 ]
 
 [package.dependencies]
@@ -2166,37 +2166,42 @@ anyio = ">=3.5.0,<5"
 distro = ">=1.7.0,<2"
 httpx = ">=0.23.0,<1"
 jiter = ">=0.4.0,<1"
-numpy = ">=2.0.2"
 pydantic = ">=1.9.0,<3"
 sniffio = "*"
-sounddevice = ">=0.5.1"
 tqdm = ">4"
 typing-extensions = ">=4.11,<5"
 
 [package.extras]
 datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
-realtime = ["websockets (>=13,<15)"]
+realtime = ["websockets (>=13,<16)"]
+voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
 
 [[package]]
 name = "openai-agents"
-version = "0.0.4"
+version = "0.0.13"
 description = "OpenAI Agents SDK"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "openai_agents-0.0.4-py3-none-any.whl", hash = "sha256:5577c3ee994fe0bd200d7283e4f7a614b3af19afeebcfb07b6ca6039a8a50a5c"},
+    {file = "openai_agents-0.0.13-py3-none-any.whl", hash = "sha256:e11910679e74803e8a4237ce52a21ee6f9ef0848d866e8198f5c4fb8c6310204"},
-    {file = "openai_agents-0.0.4.tar.gz", hash = "sha256:297e8d5faeca753e1b303d860b7ac94d03a7e10382be738163dc6a10a3b7cc1c"},
+    {file = "openai_agents-0.0.13.tar.gz", hash = "sha256:6b80315e75c06b5302c5f2adba2f9ea3845f94615daed4706bfb871740f561a5"},
 ]
 
 [package.dependencies]
 griffe = ">=1.5.6,<2"
-openai = ">=1.66.2"
+mcp = {version = ">=1.6.0,<2", markers = "python_version >= \"3.10\""}
+openai = ">=1.76.0"
 pydantic = ">=2.10,<3"
 requests = ">=2.0,<3"
 types-requests = ">=2.0,<3"
 typing-extensions = ">=4.12.2,<5"
 
+[package.extras]
+litellm = ["litellm (>=1.65.0,<2)"]
+viz = ["graphviz (>=0.17)"]
+voice = ["numpy (>=2.2.0,<3) ; python_version >= \"3.10\"", "websockets (>=15.0,<16)"]
+
 [[package]]
 name = "openpyxl"
 version = "3.1.5"
@@ -3223,27 +3228,6 @@ files = [
     {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
 ]
 
-[[package]]
-name = "sounddevice"
-version = "0.5.1"
-description = "Play and Record Sound with Python"
-optional = false
-python-versions = ">=3.7"
-groups = ["main"]
-files = [
-    {file = "sounddevice-0.5.1-py3-none-any.whl", hash = "sha256:e2017f182888c3f3c280d9fbac92e5dbddac024a7e3442f6e6116bd79dab8a9c"},
-    {file = "sounddevice-0.5.1-py3-none-macosx_10_6_x86_64.macosx_10_6_universal2.whl", hash = "sha256:d16cb23d92322526a86a9490c427bf8d49e273d9ccc0bd096feecd229cde6031"},
-    {file = "sounddevice-0.5.1-py3-none-win32.whl", hash = "sha256:d84cc6231526e7a08e89beff229c37f762baefe5e0cc2747cbe8e3a565470055"},
-    {file = "sounddevice-0.5.1-py3-none-win_amd64.whl", hash = "sha256:4313b63f2076552b23ac3e0abd3bcfc0c1c6a696fc356759a13bd113c9df90f1"},
-    {file = "sounddevice-0.5.1.tar.gz", hash = "sha256:09ca991daeda8ce4be9ac91e15a9a81c8f81efa6b695a348c9171ea0c16cb041"},
-]
-
-[package.dependencies]
-CFFI = ">=1.0"
-
-[package.extras]
-numpy = ["NumPy"]
-
 [[package]]
 name = "soupsieve"
 version = "2.6"
@@ -3417,14 +3401,14 @@ files = [
 
 [[package]]
 name = "types-requests"
-version = "2.32.0.20250306"
+version = "2.32.0.20250328"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "types_requests-2.32.0.20250306-py3-none-any.whl", hash = "sha256:25f2cbb5c8710b2022f8bbee7b2b66f319ef14aeea2f35d80f18c9dbf3b60a0b"},
+    {file = "types_requests-2.32.0.20250328-py3-none-any.whl", hash = "sha256:72ff80f84b15eb3aa7a8e2625fffb6a93f2ad5a0c20215fc1dcfa61117bcb2a2"},
-    {file = "types_requests-2.32.0.20250306.tar.gz", hash = "sha256:0962352694ec5b2f95fda877ee60a159abdf84a0fc6fdace599f20acb41a03d1"},
+    {file = "types_requests-2.32.0.20250328.tar.gz", hash = "sha256:c9e67228ea103bd811c96984fac36ed2ae8da87a36a633964a21f199d60baf32"},
 ]
 
 [package.dependencies]
@@ -4009,4 +3993,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "4b3828121cfa1e7657d9f4ecd4635d0a952c81ad77c7ec2d71c8415c90506f2c"
+content-hash = "9b132012b1e894f31b66796668c874f0c81ca3077c67e12878b00ccc3e8242ac"

apps/rowboat_agents/pyproject.toml

@@ -62,7 +62,6 @@ mypy-extensions = "^1.0.0"
 nest-asyncio = "^1.6.0"
 numpy = "^2.2.1"
 openai = "*"
-openai-agents = "*"
 openpyxl = "^3.1.5"
 packaging = "^24.2"
 pandas = "^2.2.3"
@@ -104,6 +103,7 @@ websockets = "^13.1"
 Werkzeug = "^3.1.3"
 wheel = "^0.44.0"
 xattr = "^1.1.4"
+openai-agents = "^0.0.13"
 
 [build-system]
 requires = ["poetry-core"]

apps/rowboat_agents/requirements.txt

@@ -6,6 +6,7 @@ annotated-types==0.7.0
 anyio==4.8.0
 asgiref==3.8.1
 attrs==25.3.0
+babel==2.16.0
 beautifulsoup4==4.12.3
 blinker==1.9.0
 build==1.2.2.post1
@@ -29,7 +30,9 @@ findpython==0.6.3
 firecrawl==1.9.0
 Flask==3.1.0
 frozenlist==1.5.0
-griffe==1.6.2
+fsspec==2025.3.2
+ghp-import==2.1.0
+griffe==1.7.3
 grpcio==1.71.0
 grpcio-tools==1.71.0
 gunicorn==23.0.0
@@ -39,9 +42,11 @@ hpack==4.1.0
 httpcore==1.0.7
 httpx==0.27.2
 httpx-sse==0.4.0
+huggingface-hub==0.30.2
 Hypercorn==0.17.3
 hyperframe==6.1.0
 idna==3.10
+importlib_metadata==8.6.1
 installer==0.7.0
 itsdangerous==2.2.0
 jaraco.classes==3.4.0
@@ -50,11 +55,21 @@ jaraco.functools==4.1.0
 Jinja2==3.1.5
 jiter==0.6.1
 jsonpath-python==1.0.6
+jsonschema==4.23.0
+jsonschema-specifications==2025.4.1
 keyring==25.6.0
+litellm==1.67.2
 lxml==5.3.0
+Markdown==3.7
 markdownify==0.13.1
 MarkupSafe==3.0.2
-mcp==1.5.0
+mcp==1.6.0
+mergedeep==1.3.4
+mistralai==1.2.3
+mkdocs==1.6.1
+mkdocs-get-deps==0.2.0
+mkdocs-material==9.5.50
+mkdocs-material-extensions==1.3.1
 more-itertools==10.6.0
 motor==3.7.0
 msgpack==1.1.0
@@ -62,11 +77,13 @@ multidict==6.2.0
 mypy-extensions==1.0.0
 nest-asyncio==1.6.0
 numpy==2.2.1
-openai==1.68.0
+openai==1.76.0
-openai-agents==0.0.4
+openai-agents==0.0.13
 openpyxl==3.1.5
 packaging==24.2
+paginate==0.5.7
 pandas==2.2.3
+pathspec==0.12.1
 pbs-installer==2025.3.17
 pkginfo==1.12.1.2
 platformdirs==4.3.7
@@ -80,18 +97,26 @@ pycparser==2.22
 pydantic==2.10.5
 pydantic-settings==2.8.1
 pydantic_core==2.27.2
+Pygments==2.19.1
 PyJWT==2.10.1
+pymdown-extensions==10.14.1
 pymongo==4.10.1
 pyproject_hooks==1.2.0
 python-dateutil==2.9.0.post0
 python-docx==1.1.2
 python-dotenv==1.0.1
 pytz==2024.2
+PyYAML==6.0.2
+pyyaml_env_tag==0.1
 qdrant-client==1.13.3
 Quart==0.20.0
 RapidFuzz==3.12.2
+redis==5.2.1
+referencing==0.36.2
+regex==2024.11.6
 requests==2.32.3
 requests-toolbelt==1.0.0
+rpds-py==0.24.0
 setuptools==75.8.0
 shellingham==1.5.4
 six==1.17.0
@@ -99,23 +124,30 @@ sniffio==1.3.1
 sounddevice==0.5.1
 soupsieve==2.6
 sse-starlette==2.2.1
+sseclient==0.0.27
+sseclient-py==1.8.0
 starlette==0.46.1
 tabulate==0.9.0
+tiktoken==0.9.0
+tokenizers==0.21.1
 tomlkit==0.13.2
 tqdm==4.67.1
 trove-classifiers==2025.3.19.19
-types-requests==2.32.0.20250306
+types-requests==2.32.0.20250328
 typing-inspect==0.9.0
+typing-inspection==0.4.0
 typing_extensions==4.12.2
 tzdata==2024.2
 urllib3==2.3.0
 uvicorn==0.34.0
 virtualenv==20.29.3
 waitress==2.1.2
+watchdog==6.0.0
 websockets==13.1
 Werkzeug==3.1.3
 wheel==0.44.0
 wsproto==1.2.0
 xattr==1.1.4
 yarl==1.18.3
+zipp==3.21.0
 zstandard==0.23.0

apps/rowboat_agents/src/app/main.py

@@ -91,6 +91,7 @@ async def chat():
             start_agent_name=data.get("startAgent", ""),
             agent_configs=data.get("agents", []),
             tool_configs=data.get("tools", []),
+            prompt_configs=data.get("prompts", []),
             start_turn_with_start_agent=config.get("start_turn_with_start_agent", False),
             state=data.get("state", {}),
             additional_tool_configs=[RAG_TOOL, CLOSE_CHAT_TOOL],
@@ -157,6 +158,7 @@ async def chat_stream():
                 start_agent_name=request_data.get("startAgent", ""),
                 agent_configs=request_data.get("agents", []),
                 tool_configs=request_data.get("tools", []),
+                prompt_configs=request_data.get("prompts", []),
                 start_turn_with_start_agent=config.get("start_turn_with_start_agent", False),
                 state=request_data.get("state", {}),
                 additional_tool_configs=[RAG_TOOL, CLOSE_CHAT_TOOL],
@@ -168,6 +170,9 @@ async def chat_stream():
                 elif event_type == 'done':
                     print("Yielding done:")
                     yield format_sse(event_data, "done")
+                elif event_type == 'error':
+                    print("Yielding error:")
+                    yield format_sse(event_data, "stream_error")
 
         except Exception as e:
             logger.error(f"Streaming error: {str(e)}")

apps/rowboat_agents/src/graph/core.py

@@ -7,6 +7,7 @@ import logging
 from .helpers.access import (
     get_agent_by_name,
     get_external_tools,
+    get_prompt_by_type
 )
 from .helpers.state import (
     construct_state_from_response
@@ -14,7 +15,8 @@ from .helpers.state import (
 from .helpers.control import get_latest_assistant_msg, get_latest_non_assistant_messages, get_last_agent_name
 from .swarm_wrapper import run as swarm_run, run_streamed as swarm_run_streamed, create_response, get_agents
 from src.utils.common import common_logger as logger
-import asyncio
+
+from .types import PromptType
 
 # Create a dedicated logger for swarm wrapper
 logger.setLevel(logging.INFO)
@@ -43,6 +45,26 @@ def order_messages(messages):
         ordered_messages.append(ordered)
     return ordered_messages
 
+def set_sys_message(messages):
+    """
+    If the system message is empty, set it to the default message: "You are a helplful assistant."
+    """
+    if not any(msg.get("role") == "system" for msg in messages):
+        messages.insert(0, {
+            "role": "system",
+            "content": "You are a helpful assistant."
+        })
+        print("Inserted system message: ", messages[0])
+        logger.info("Inserted system message: ", messages[0])
+
+    elif messages[0].get("role") == "system" and messages[0].get("content") == "":
+        messages[0]["content"] = "You are a helpful assistant."
+        print("Updated system message: ", messages[0])
+        logger.info("Updated system message: ", messages[0])
+        print("Messages: ", messages)
+        # logger.info("Messages: ", messages)
+    
+    return messages
 
 def clean_up_history(agent_data):
     """
@@ -197,7 +219,6 @@ async def run_turn(
     logger.info(f"Completed run of agent: {last_new_agent.name}")
     print(f"Completed run of agent: {last_new_agent.name}")
 
-
     # Otherwise, duplicate the last response as external
     logger.info("No post-processing agent found. Duplicating last response and setting to external.")
     print("No post-processing agent found. Duplicating last response and setting to external.")
@@ -236,13 +257,41 @@ async def run_turn_streamed(
     start_agent_name,
     agent_configs,
     tool_configs,
+    prompt_configs,
     start_turn_with_start_agent,
     state={},
     additional_tool_configs=[],
     complete_request={}
 ):
+    messages = set_sys_message(messages)
+    is_greeting_turn = not any(msg.get("role") != "system" for msg in messages)
     final_state = None  # Initialize outside try block
     try:
+        greeting_prompt = get_prompt_by_type(prompt_configs, PromptType.GREETING)
+        if is_greeting_turn:
+            if not greeting_prompt:
+                greeting_prompt = "How can I help you today?"
+                print("Greeting prompt not found. Using default: ", greeting_prompt)
+            message = {
+                'content': greeting_prompt,
+                'role': 'assistant',
+                'sender': start_agent_name,
+                'tool_calls': None,
+                'tool_call_id': None,
+                'tool_name': None,
+                'response_type': 'external'
+            }
+            print("Yielding greeting message: ", message)
+            yield ('message', message)
+
+            final_state = {
+                "last_agent_name": start_agent_name if start_agent_name else None,
+                "tokens": {"total": 0, "prompt": 0, "completion": 0}
+            }
+            print("Yielding done message")
+            yield ('done', {'state': final_state})
+            return
+        
         # Initialize agents and get external tools
         new_agents = get_agents(agent_configs=agent_configs, tool_configs=tool_configs, complete_request=complete_request)
         last_agent_name = get_last_agent_name(
@@ -274,7 +323,7 @@ async def run_turn_streamed(
 
             # Handle raw response events and accumulate tokens
             if event.type == "raw_response_event":
-                if hasattr(event.data, 'type') and event.data.type == "response.completed":
+                if hasattr(event.data, 'type') and event.data.type == "response.completed" and event.data.response.usage:
                     if hasattr(event.data.response, 'usage'):
                         tokens_used["total"] += event.data.response.usage.total_tokens
                         tokens_used["prompt"] += event.data.response.usage.input_tokens
@@ -616,4 +665,5 @@ async def run_turn_streamed(
     except Exception as e:
         print(traceback.format_exc())
         print(f"Error in stream processing: {str(e)}")
+        print("Yielding error event:", {'error': str(e), 'state': final_state})
         yield ('error', {'error': str(e), 'state': final_state})  # Include final_state in error response

apps/rowboat_agents/src/graph/swarm_wrapper.py

@@ -3,6 +3,7 @@ import json
 import aiohttp
 import jwt
 import hashlib
+from agents import OpenAIChatCompletionsModel
 
 # Import helper functions needed for get_agents
 from .helpers.access import (
@@ -31,6 +32,8 @@ MONGO_URI = os.environ.get("MONGODB_URI", "mongodb://localhost:27017/rowboat").s
 mongo_client = MongoClient(MONGO_URI)
 db = mongo_client["rowboat"]
 
+from src.utils.client import client, PROVIDER_DEFAULT_MODEL
+
 class NewResponse(BaseModel):
     messages: List[Dict]
     agent: Optional[Any] = None
@@ -47,7 +50,9 @@ async def mock_tool(tool_name: str, args: str, description: str, mock_instructio
         ]
 
         print(f"Generating simulated response for tool: {tool_name}")
-        response_content = generate_openai_output(messages, output_type='text', model="gpt-4o")
+        response_content = None
+        response_content = generate_openai_output(messages, output_type='text', model=PROVIDER_DEFAULT_MODEL)
+        print("Custom provider client not found, using default model: gpt-4o")
         return response_content
     except Exception as e:
         logger.error(f"Error in mock_tool: {str(e)}")
@@ -173,8 +178,6 @@ def get_rag_tool(config: dict, complete_request: dict) -> FunctionTool:
     else:
         return None
 
-
-
 def get_agents(agent_configs, tool_configs, complete_request):
     """
     Creates and initializes Agent objects based on their configurations and connections.
@@ -246,12 +249,15 @@ def get_agents(agent_configs, tool_configs, complete_request):
         # add the name and description to the agent instructions
         agent_instructions = f"## Your Name\n{agent_config['name']}\n\n## Description\n{agent_config['description']}\n\n## Instructions\n{agent_config['instructions']}"
         try:
+            model_name = agent_config["model"] if agent_config["model"] else PROVIDER_DEFAULT_MODEL
+            print(f"Using model: {model_name}")
+            model=OpenAIChatCompletionsModel(model=model_name, openai_client=client) if client else agent_config["model"]
             new_agent = NewAgent(
                 name=agent_config["name"],
                 instructions=agent_instructions,
                 handoff_description=agent_config["description"],
                 tools=new_tools,
-                model=agent_config["model"],
+                model = model,
                 model_settings=ModelSettings(temperature=0.0)
             )
 

apps/rowboat_agents/src/utils/client.py

@@ -0,0 +1,32 @@
+import os
+import logging
+from openai import AsyncOpenAI, OpenAI
+import dotenv
+dotenv.load_dotenv()
+
+PROVIDER_BASE_URL = os.getenv('PROVIDER_BASE_URL', '')
+PROVIDER_API_KEY = os.getenv('PROVIDER_API_KEY', os.getenv('OPENAI_API_KEY', ''))
+PROVIDER_DEFAULT_MODEL = os.getenv('PROVIDER_DEFAULT_MODEL', 'gpt-4.1')
+
+client = None
+if not PROVIDER_API_KEY:
+    raise ValueError("No LLM Provider API key found")
+
+if PROVIDER_BASE_URL:
+    print(f"Using provider {PROVIDER_BASE_URL} with API key {PROVIDER_API_KEY}")
+    client = AsyncOpenAI(base_url=PROVIDER_BASE_URL, api_key=PROVIDER_API_KEY)
+else:
+    print("No provider base URL configured, using OpenAI directly")
+
+completions_client = None
+if PROVIDER_BASE_URL:
+    print(f"Using provider {PROVIDER_BASE_URL} for completions")
+    completions_client = OpenAI(
+        base_url=PROVIDER_BASE_URL, 
+        api_key=PROVIDER_API_KEY
+    )
+else:
+    print(f"Using OpenAI directly for completions")
+    completions_client = OpenAI(
+        api_key=PROVIDER_API_KEY
+    )

apps/rowboat_agents/src/utils/common.py

@@ -7,6 +7,7 @@ import time
 from dotenv import load_dotenv
 from openai import OpenAI
 
+from src.utils.client import completions_client
 load_dotenv()
 
 def setup_logger(name, log_file='./run.log', level=logging.INFO, log_to_file=False):
@@ -53,25 +54,22 @@ def get_api_key(key_name):
         raise ValueError(f"{key_name} not found. Did you set it in the .env file?")
     return api_key
 
-openai_client = OpenAI(
-    api_key=get_api_key("OPENAI_API_KEY")
-)
-
 def generate_gpt4o_output_from_multi_turn_conv(messages, output_type='json', model="gpt-4o"):
     return generate_openai_output(messages, output_type, model)
 
 def generate_openai_output(messages, output_type='not_json', model="gpt-4o", return_completion=False):
+    print(f"In generate_openai_output, using client: {completions_client} and model: {model}")
     try:
         if output_type == 'json':
-            chat_completion = openai_client.chat.completions.create(
+            chat_completion = completions_client.chat.completions.create(
-                messages=messages,
                 model=model,
+                messages=messages,
                 response_format={"type": "json_object"}
             )
         else:
-            chat_completion = openai_client.chat.completions.create(
+            chat_completion = completions_client.chat.completions.create(
-                messages=messages,
                 model=model,
+                messages=messages,
             )
         
         if return_completion:

docker-compose.yml

@@ -37,6 +37,7 @@ services:
       - MAX_QUERIES_PER_MINUTE=${MAX_QUERIES_PER_MINUTE}
       - MAX_PROJECTS_PER_USER=${MAX_PROJECTS_PER_USER}
       - VOICE_API_URL=${VOICE_API_URL}
+      - PROVIDER_DEFAULT_MODEL=${PROVIDER_DEFAULT_MODEL}
     restart: unless-stopped
 
   rowboat_agents:
@@ -52,6 +53,9 @@ services:
       - MONGODB_URI=mongodb://mongo:27017/rowboat
       - QDRANT_URL=${QDRANT_URL}
       - QDRANT_API_KEY=${QDRANT_API_KEY}
+      - PROVIDER_BASE_URL=${PROVIDER_BASE_URL}
+      - PROVIDER_API_KEY=${PROVIDER_API_KEY}
+      - PROVIDER_DEFAULT_MODEL=${PROVIDER_DEFAULT_MODEL}
     restart: unless-stopped
 
   copilot:
@@ -63,6 +67,9 @@ services:
     environment:
       - OPENAI_API_KEY=${OPENAI_API_KEY}
       - API_KEY=${COPILOT_API_KEY}
+      - PROVIDER_BASE_URL=${PROVIDER_BASE_URL}
+      - PROVIDER_API_KEY=${PROVIDER_API_KEY}
+      - PROVIDER_DEFAULT_MODEL=${PROVIDER_DEFAULT_MODEL}
     restart: unless-stopped
 
   # tools_webhook:
@@ -150,6 +157,7 @@ services:
       - MONGODB_CONNECTION_STRING=mongodb://mongo:27017/rowboat
       - QDRANT_URL=${QDRANT_URL}
       - QDRANT_API_KEY=${QDRANT_API_KEY}
+      - REDIS_URL=redis://redis:6379
     restart: unless-stopped
 
   # chat_widget: