Merge pull request #78 from OpenBB-finance/feat/add-agent-dashboard-widgets-example

Author: DidierRLopes

20-financial-prompt-optimizer/README.md

@@ -0,0 +1,60 @@
+# Example agent for financial prompt optimization
+
+This is a minimal example agent, powered by OpenAI, that optimizes a user's
+financial prompt for clarity, specificity, and actionability. It has no widget
+integration and focuses solely on improving prompts.
+
+## Getting started
+
+Here's how to get your agent up and running:
+
+### Prerequisites
+
+Ensure you have poetry, a tool for dependency management and packaging in
+Python, as well as your OpenAI API key.
+
+### Installation and Running
+
+1. Clone this repository to your local machine.
+
+2. Install the necessary dependencies:
+
+    ```sh
+    poetry install --no-root
+    ```
+
+3. Set the OpenAI API key as an environment variable:
+
+    ```sh
+    export OPENAI_API_KEY=<your-api-key>
+    ```
+
+4. Start the API server:
+
+    ```sh
+    cd financial-prompt-optimizer
+    poetry run uvicorn main:app --port 7777 --reload
+    ```
+
+This command runs the FastAPI application, making it accessible on your network.
+
+### Accessing the Documentation
+
+Once the API server is running, you can view the documentation and interact with
+the API by visiting: [http://localhost:7777/docs](http://localhost:7777/docs)
+
+### Using with OpenBB Workspace (Optional)
+
+- The agent descriptor is available at: [http://localhost:7777/agents.json](http://localhost:7777/agents.json)
+- Features are set to:
+  - `streaming: true`
+  - `widget-dashboard-select: false`
+  - `widget-dashboard-search: false`
+
+### Expected Behavior
+
+When you send a user message, the agent streams a single answer containing two
+sections:
+
+- `Optimized Prompt: <single improved prompt>`
+- `Rationale: <1–3 short bullets on what changed and why>`

20-financial-prompt-optimizer/main.py

@@ -0,0 +1,100 @@
+from typing import AsyncGenerator
+import openai
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from sse_starlette.sse import EventSourceResponse
+
+from openbb_ai.models import MessageChunkSSE, QueryRequest
+from openbb_ai import message_chunk
+
+from openai.types.chat import (
+    ChatCompletionMessageParam,
+    ChatCompletionUserMessageParam,
+    ChatCompletionAssistantMessageParam,
+    ChatCompletionSystemMessageParam,
+)
+
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+@app.get("/agents.json")
+def get_copilot_description():
+    """Agent descriptor for the OpenBB Workspace."""
+    return JSONResponse(
+        content={
+            "financial_prompt_optimizer": {
+                "name": "Financial Prompt Optimizer",
+                "description": "Optimizes a user's prompt for finance: clearer, more specific, and actionable.",
+                "image": "https://github.com/OpenBB-finance/copilot-for-terminal-pro/assets/14093308/7da2a512-93b9-478d-90bc-b8c3dd0cabcf",
+                "endpoints": {"query": "http://localhost:7777/v1/query"},
+                "features": {
+                    "streaming": True,
+                    "widget-dashboard-select": False,
+                    "widget-dashboard-search": False,
+                },
+            }
+        }
+    )
+
+
+@app.post("/v1/query")
+async def query(request: QueryRequest) -> EventSourceResponse:
+    """Stream a concise optimized prompt and rationale."""
+
+    openai_messages: list[ChatCompletionMessageParam] = [
+        ChatCompletionSystemMessageParam(
+            role="system",
+            content=(
+                "You are a concise Financial Prompt Optimizer.\n"
+                "Rewrite the user's prompt to be clearer, more specific, and immediately actionable for financial analysis.\n"
+                "Always return exactly the improved prompt:\n"
+                "Optimized Prompt: <detailed improved prompt with step-by-step>\n"
+            ),
+        )
+    ]
+
+    for message in request.messages:
+        if message.role == "human":
+            openai_messages.append(
+                ChatCompletionUserMessageParam(role="user", content=message.content)
+            )
+        elif message.role == "ai" and isinstance(message.content, str):
+            openai_messages.append(
+                ChatCompletionAssistantMessageParam(
+                    role="assistant", content=message.content
+                )
+            )
+
+    async def execution_loop() -> AsyncGenerator[MessageChunkSSE, None]:
+        client = openai.AsyncOpenAI()
+        async for event in await client.chat.completions.create(
+            model="gpt-4o",
+            messages=openai_messages,
+            stream=True,
+        ):
+            if chunk := event.choices[0].delta.content:
+                yield message_chunk(chunk)
+
+    return EventSourceResponse(
+        content=(
+            event.model_dump(exclude_none=True) async for event in execution_loop()
+        ),
+        media_type="text/event-stream",
+    )
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run("main:app", host="0.0.0.0", port=7777, reload=True)

30-vanilla-agent-raw-widget-data/vanilla_agent_raw_context/main.py

@@ -60,6 +60,10 @@ async def query(request: QueryRequest) -> EventSourceResponse:
         and request.widgets.primary
     ):
         widget_requests: list[WidgetRequest] = []
+        # Note: If we wanted to iterate through the widgets on the dashboard
+        # rather than on the widgets on the explicit context
+        # then we would need to iterate through request.widgets.secondary
+        # and the agents.json would need "widget-dashboard-search": True
         for widget in request.widgets.primary:
             widget_requests.append(
                 WidgetRequest(

31-vanilla-agent-reasoning-steps/vanilla_agent_reasoning_steps/main.py

@@ -21,7 +21,7 @@
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["https://pro.openbb.co"],
+    allow_origins=["*"],
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
@@ -101,13 +101,6 @@ async def execution_loop() -> AsyncGenerator[MessageChunkSSE, None]:
             if chunk := event.choices[0].delta.content:
                 yield message_chunk(chunk).model_dump()
 
-        # Reasoning steps can be yielded from anywhere, as long as they are
-        # yielded from the execution loop back to the OpenBB Workspace.
-        yield reasoning_step(
-            event_type="INFO",
-            message="Answering complete!",
-        ).model_dump()
-
     return EventSourceResponse(
         content=execution_loop(),
         media_type="text/event-stream",

36-vanilla-agent-pdf-citations/README.md

@@ -0,0 +1,57 @@
+# Example agent that can handle PDF data with citations
+
+This is an example agent, powered by OpenAI, that can perform question answering
+using data retrieved from widgets on OpenBB Workspace. It specifically demonstrates
+how to handle PDF data with citation support, including highlighting specific text passages. 
+
+## Getting started
+
+Here's how to get your agent up and running:
+
+### Prerequisites
+
+Ensure you have poetry, a tool for dependency management and packaging in
+Python, as well as your OpenAI API key.
+
+### Installation and Running
+
+1. Clone this repository to your local machine.
+
+2. Set the OpenAI API key as an environment variable in your .bashrc or .zshrc file:
+
+    ``` sh
+    # in .zshrc or .bashrc
+    export OPENAI_API_KEY=<your-api-key>
+    ```
+
+3. Install the necessary dependencies:
+
+``` sh
+poetry install --no-root
+```
+
+4.Start the API server:
+
+``` sh
+cd 36-vanilla-pdf-citations
+poetry run uvicorn vanilla_agent_pdf_citations.main:app --port 7777 --reload
+```
+
+This command runs the FastAPI application, making it accessible on your network.
+
+### Testing the Agent
+
+The example agent has a small, basic test suite to ensure it's
+working correctly. As you develop your agent, you are highly encouraged to
+expand these tests.
+
+You can run the tests with:
+
+```sh
+pytest tests
+```
+
+### Accessing the Documentation
+
+Once the API server is running, you can view the documentation and interact with
+the API by visiting: http://localhost:7777/docs

36-vanilla-agent-pdf-citations/tests/__init__.py

@@ -0,0 +1,85 @@
+import json
+from unittest import mock
+from fastapi.testclient import TestClient
+from vanilla_agent_pdf.main import app
+import pytest
+from pathlib import Path
+from openbb_ai.testing import CopilotResponse
+
+test_client = TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def reset_sse_starlette_appstatus_event():
+    """
+    Fixture that resets the appstatus event in the sse_starlette app.
+    Should be used on any test that uses sse_starlette to stream events.
+    """
+    # See https://github.com/sysid/sse-starlette/issues/59
+    from sse_starlette.sse import AppStatus
+
+    AppStatus.should_exit_event = None
+
+
+def test_query():
+    test_payload_path = (
+        Path(__file__).parent.parent.parent
+        / "testing"
+        / "test_payloads"
+        / "single_message.json"
+    )
+    test_payload = json.load(open(test_payload_path))
+
+    response = test_client.post("/v1/query", json=test_payload)
+    assert response.status_code == 200
+    copilot_response = CopilotResponse(response.text)
+    (copilot_response.has_any("copilotMessage", "2"))
+
+
+def test_query_conversation():
+    test_payload_path = (
+        Path(__file__).parent.parent.parent
+        / "testing"
+        / "test_payloads"
+        / "multiple_messages.json"
+    )
+    test_payload = json.load(open(test_payload_path))
+
+    response = test_client.post("/v1/query", json=test_payload)
+    assert response.status_code == 200
+    copilot_response = CopilotResponse(response.text)
+    (copilot_response.has_any("copilotMessage", "4"))
+
+
+def test_query_no_messages():
+    test_payload = {
+        "messages": [],
+    }
+    response = test_client.post("/v1/query", json=test_payload)
+    "messages list cannot be empty" in response.text
+
+
+def test_query_completes_remote_function_call_with_pdf_url():
+    test_payload_path = (
+        Path(__file__).parent.parent.parent
+        / "testing"
+        / "test_payloads"
+        / "message_with_primary_widget_and_tool_call_pdf_url.json"
+    )
+    test_payload = json.load(open(test_payload_path))
+
+    with open(
+        Path(__file__).parent.parent.parent
+        / "testing"
+        / "test_payloads"
+        / "openbb_story.pdf",
+        "rb",
+    ) as pdf:
+        pdf_content = pdf.read()
+
+    with mock.patch("vanilla_agent_pdf.main._download_file", return_value=pdf_content):
+        response = test_client.post("/v1/query", json=test_payload)
+
+    assert response.status_code == 200
+    copilot_response = CopilotResponse(response.text)
+    (copilot_response.starts("copilotMessage").with_("Didier Lopes").with_("Gamestonk"))