代码
ref/recipe_rag_image.py
"""Example: Multi-Modal RAG & Image Agent
An agent that uses Llama 4 for multi-modal RAG and OpenAITools to create a visual, step-by-step image manual for a recipe.
Run: `pip install openai agno groq cohere` to install the dependencies
"""
from pathlib import Path
from agno.agent import Agent
from agno.embedder.cohere import CohereEmbedder
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.models.groq import Groq
from agno.tools.openai import OpenAITools
from agno.utils.media import download_image
from agno.vectordb.pgvector import PgVector
knowledge_base = PDFUrlKnowledgeBase(
urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
vector_db=PgVector(
db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
table_name="embed_vision_documents",
embedder=CohereEmbedder(
id="embed-v4.0",
),
),
)
knowledge_base.load()
agent = Agent(
name="EmbedVisionRAGAgent",
model=Groq(id="meta-llama/llama-4-scout-17b-16e-instruct"),
tools=[OpenAITools()],
knowledge=knowledge_base,
instructions=[
"You are a specialized recipe assistant.",
"When asked for a recipe:",
"1. Search the knowledge base to retrieve the relevant recipe details.",
"2. Analyze the retrieved recipe steps carefully.",
"3. Use the `generate_image` tool to create a visual, step-by-step image manual for the recipe.",
"4. Present the recipe text clearly and mention that you have generated an accompanying image manual. Add instructions while generating the image.",
],
markdown=True,
debug_mode=True,
)
agent.print_response(
"What is the recipe for a Thai curry?",
)
response = agent.run_response
if response.images:
download_image(response.images[0].url, Path("tmp/recipe_image.png"))
用法
1
安装依赖
pip install openai agno groq cohere
2
运行示例
python ref/recipe_rag_image.py
tmp/recipe_image.png。