Upload 4 files

.env

@@ -0,0 +1,2 @@
+PHI_API_KEY=""
+GROQ_API_KEY=""

Dockerfile

@@ -0,0 +1,22 @@
+# Use the official Python image
+FROM python:3.9-slim
+
+# Set the working directory
+WORKDIR /app
+
+# Copy files
+COPY requirements.txt requirements.txt
+COPY .env .env
+COPY main.py main.py
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Expose the application port
+EXPOSE 7860
+
+# Debugging: Show files and env variables
+RUN ls -al && cat .env
+
+# Run the FastAPI application using uvicorn
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

@@ -0,0 +1,73 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from phi.agent import Agent
+from phi.model.groq import Groq
+from phi.tools.yfinance import YFinanceTools
+from phi.tools.duckduckgo import DuckDuckGo
+import os
+from dotenv import load_dotenv
+
+import logging
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Load environment variables
+load_dotenv()
+gorq_api_key = os.getenv("GROQ_API_KEY")
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Define input schema
+class QueryRequest(BaseModel):
+    input_text: str
+
+# Web Search Agent
+web_search_agent = Agent(
+    name="Web Search Agent",
+    role="Search the web for the information",
+    model=Groq(id="llama-3.3-70b-versatile"),
+    tools=[DuckDuckGo()],
+    instructions=["Always include sources"],
+    show_tools_calls=True,
+    markdown=True,
+)
+
+# Financial Agent
+finance_agent = Agent(
+    name="Finance AI Agent",
+    model=Groq(
+        id="llama-3.3-70b-versatile",
+        api_key=gorq_api_key,
+        role="Get financial data",
+    ),
+    tools=[
+        YFinanceTools(
+            stock_price=True,
+            analyst_recommendations=True,
+            stock_fundamentals=True,
+            company_news=True,
+        ),
+    ],
+    instructions=["Use tables to display the data"],
+    show_tool_calls=True,
+    markdown=True,
+)
+
+# Multi-Agent
+multi_ai_agent = Agent(
+    team=[web_search_agent, finance_agent],
+    instructions=["Always include sources", "Use tables to display the data"],
+    show_tool_calls=True,
+    markdown=True,
+)
+
+@app.post("/query")
+async def process_query(request: QueryRequest):
+    try:
+        response = multi_ai_agent.run(request.input_text)
+        return {"response": response}
+    except Exception as e:
+        logger.error(f"Error processing query: {e}")
+        return {"error": f"An error occurred: {str(e)}"}

requirements.txt

@@ -0,0 +1,9 @@
+phidata 
+python-dotenv
+yfinance
+packaging
+duckduckgo-search
+fastapi
+uvicorn
+groq
+openai