diff --git a/README.md b/README.md index b9c9ea55..bb29d002 100644 --- a/README.md +++ b/README.md @@ -116,7 +116,7 @@ Almost any Python project can become an Actor, including projects for: - **Web scraping and crawling** — The SDK is fully compatible with [Crawlee](https://crawlee.dev/python), which makes Apify a natural place to deploy and scale your crawlers (see the [Crawlee guide](https://docs.apify.com/sdk/python/docs/guides/crawlee)). It also works with other popular scraping libraries, such as [Scrapy](https://docs.apify.com/sdk/python/docs/guides/scrapy), [Scrapling](https://docs.apify.com/sdk/python/docs/guides/scrapling), or [Crawl4AI](https://docs.apify.com/sdk/python/docs/guides/crawl4ai). - **Browser automation** — Drive a real browser with [Playwright](https://docs.apify.com/sdk/python/docs/guides/playwright) or [Selenium](https://docs.apify.com/sdk/python/docs/guides/selenium), or with higher-level tools such as [Browser Use](https://docs.apify.com/sdk/python/docs/guides/browser-use). - **Web servers and APIs** — Run a [web server](https://docs.apify.com/sdk/python/docs/guides/running-webserver) inside an Actor to serve HTTP requests, for example to expose your scraper as a live API. -- **AI agents** — Host agents built with your framework of choice. Ready-made Actor templates cover [PydanticAI](https://apify.com/templates/python-pydanticai), [CrewAI](https://apify.com/templates/python-crewai), [LangGraph](https://apify.com/templates/python-langgraph), [LlamaIndex](https://apify.com/templates/python-llamaindex-agent), and [Smolagents](https://apify.com/templates/python-smolagents). +- **AI agents** — Host agents built with your framework of choice (see the [AI agents guide](https://docs.apify.com/sdk/python/docs/guides/ai-agents)). Ready-made Actor templates cover [LangGraph](https://apify.com/templates/python-langgraph), [CrewAI](https://apify.com/templates/python-crewai), [PydanticAI](https://apify.com/templates/python-pydanticai), [LlamaIndex](https://apify.com/templates/python-llamaindex-agent), and [Smolagents](https://apify.com/templates/python-smolagents). - **MCP servers** — Deploy a Python MCP server as an Actor and make its tools available to any MCP client. See [MCP server](https://apify.com/templates/python-mcp-empty) and [MCP proxy](https://apify.com/templates/python-mcp-proxy) templates Whatever you build, the Apify SDK doesn't lock you into a particular framework. Bring the libraries you already use, and let Apify run your project in the cloud. @@ -199,7 +199,7 @@ The full SDK documentation lives at **[docs.apify.com/sdk/python](https://docs.a | [Overview](https://docs.apify.com/sdk/python/docs/overview) | What the SDK is, what Actors are, and how the pieces fit together. | | [Quick start](https://docs.apify.com/sdk/python/docs/quick-start) | Create, run, and deploy your first Python Actor. | | [Concepts](https://docs.apify.com/sdk/python/docs/concepts/actor-lifecycle) | Actor lifecycle, input, storages, events, proxy management, interacting with other Actors, webhooks, accessing the Apify API, logging, configuration, and pay-per-event. | -| [Guides](https://docs.apify.com/sdk/python/docs/guides/beautifulsoup-httpx) | Integrations with BeautifulSoup, Parsel, Playwright, Selenium, Crawlee, Scrapy, Scrapling, Crawl4AI, and Browser Use, plus running a web server and using uv. | +| [Guides](https://docs.apify.com/sdk/python/docs/guides/beautifulsoup-httpx) | Integrations with BeautifulSoup, Parsel, Playwright, Selenium, Crawlee, Scrapy, Scrapling, Crawl4AI, and Browser Use, plus hosting AI agents, running a web server, and using uv. | | [Upgrading](https://docs.apify.com/sdk/python/docs/upgrading/upgrading-to-v4) | Migrating between major versions. | | [API reference](https://docs.apify.com/sdk/python/reference) | Generated reference for every class and method. | | [Changelog](https://docs.apify.com/sdk/python/docs/changelog) | Release history and breaking changes. | diff --git a/docs/01_introduction/index.mdx b/docs/01_introduction/index.mdx index 133c6a47..60eae5e2 100644 --- a/docs/01_introduction/index.mdx +++ b/docs/01_introduction/index.mdx @@ -41,7 +41,7 @@ Almost any Python project can become an Actor, including projects for: - **Web scraping and crawling** - The SDK is fully compatible with [Crawlee](https://crawlee.dev/python), which makes Apify a natural place to deploy and scale your crawlers (see the [Crawlee guide](./guides/crawlee)). It also works with other popular scraping libraries, such as [Scrapy](./guides/scrapy), [Scrapling](./guides/scrapling), or [Crawl4AI](./guides/crawl4ai). - **Browser automation** - Drive a real browser with [Playwright](./guides/playwright) or [Selenium](./guides/selenium), or with higher-level tools such as [Browser Use](./guides/browser-use). - **Web servers and APIs** - Run a [web server](./guides/running-webserver) inside an Actor to serve HTTP requests, for example to expose your scraper as a live API. -- **AI agents** - Host agents built with your framework of choice. Ready-made Actor templates cover [PydanticAI](https://apify.com/templates/python-pydanticai), [CrewAI](https://apify.com/templates/python-crewai), [LangGraph](https://apify.com/templates/python-langgraph), [LlamaIndex](https://apify.com/templates/python-llamaindex-agent), and [Smolagents](https://apify.com/templates/python-smolagents). +- **AI agents** - Host agents built with your framework of choice (see the [AI agents guide](./guides/ai-agents)). Ready-made Actor templates cover [LangGraph](https://apify.com/templates/python-langgraph), [CrewAI](https://apify.com/templates/python-crewai), [PydanticAI](https://apify.com/templates/python-pydanticai), [LlamaIndex](https://apify.com/templates/python-llamaindex-agent), and [Smolagents](https://apify.com/templates/python-smolagents). - **MCP servers** - Deploy a Python MCP server as an Actor and make its tools available to any MCP client. See the [MCP server](https://apify.com/templates/python-mcp-empty) and [MCP proxy](https://apify.com/templates/python-mcp-proxy) templates. Whatever you build, the Apify SDK doesn't lock you into a particular framework. Bring the libraries you already use, and let Apify run your project in the cloud. diff --git a/docs/01_introduction/quick-start.mdx b/docs/01_introduction/quick-start.mdx index 289659bf..9bb53038 100644 --- a/docs/01_introduction/quick-start.mdx +++ b/docs/01_introduction/quick-start.mdx @@ -112,6 +112,7 @@ To see how you can integrate the Apify SDK with popular scraping libraries and f - [Adaptive scraping with Scrapling](./guides/scrapling) - [LLM-ready scraping with Crawl4AI](./guides/crawl4ai) - [Browser AI agents with Browser Use](./guides/browser-use) +- [Hosting AI agents](./guides/ai-agents) For other aspects of Actor development, explore these guides: diff --git a/docs/03_guides/14_ai_agents.mdx b/docs/03_guides/14_ai_agents.mdx new file mode 100644 index 00000000..e055dec3 --- /dev/null +++ b/docs/03_guides/14_ai_agents.mdx @@ -0,0 +1,206 @@ +--- +id: ai-agents +title: Hosting AI agents +description: Host AI agents built with LangGraph, CrewAI, PydanticAI, LlamaIndex, or Smolagents as Apify Actors. +--- + +import RunnableCodeBlock from '@site/src/components/RunnableCodeBlock'; + +import LanggraphExample from '!!raw-loader!roa-loader!./code/14_langgraph.py'; +import CrewaiExample from '!!raw-loader!roa-loader!./code/14_crewai.py'; +import PydanticaiExample from '!!raw-loader!roa-loader!./code/14_pydanticai.py'; +import LlamaindexExample from '!!raw-loader!roa-loader!./code/14_llamaindex.py'; +import SmolagentsExample from '!!raw-loader!roa-loader!./code/14_smolagents.py'; + +In this guide, you'll learn how to host an AI agent as an Apify Actor, using the agent framework of your choice. + +## Introduction + +An AI agent is a program that uses a large language model (LLM) to decide what to do next. Instead of following a fixed script, it reasons about a task, calls tools to gather information or take actions, and loops until the task is done. The Python ecosystem offers several frameworks for building such agents, and the Apify SDK doesn't lock you into any of them. + +Apify Actors are a natural home for agents: + +- An agent is just a Python program, so wrapping it in `async with Actor:` is all it takes to run it on the platform. +- The platform scales runs, schedules them, and keeps logs, so you don't operate any infrastructure yourself. +- The [Apify Store](https://apify.com/store) gives your agent thousands of ready-made tools. Any Actor (a scraper, a browser automation, an API wrapper) can become a tool the agent calls. +- The [Apify OpenRouter proxy](https://apify.com/apify/openrouter) lets the agent talk to an LLM without managing a provider API key. +- Pay-per-event charging lets you monetize the agent and pass LLM costs on to its users. + +## Choosing a framework + +Apify maintains a ready-made Actor template for each of the popular agent frameworks. Each template is a complete, deployable Actor that you can use as a starting point. Pick the one that matches the framework you already use, or the style of agent you want to build: + +| Framework | Good for | Template | +| --- | --- | --- | +| [LangGraph](#langgraph) | Graph-based agents with explicit state and control flow | [`python-langgraph`](https://apify.com/templates/python-langgraph) | +| [CrewAI](#crewai) | Multi-agent "crews" that collaborate on a task | [`python-crewai`](https://apify.com/templates/python-crewai) | +| [PydanticAI](#pydanticai) | Typed, Pydantic-native agents with tool calling | [`python-pydanticai`](https://apify.com/templates/python-pydanticai) | +| [LlamaIndex](#llamaindex) | Retrieval-augmented agents over your own data | [`python-llamaindex-agent`](https://apify.com/templates/python-llamaindex-agent) | +| [Smolagents](#smolagents) | Lightweight code-writing agents | [`python-smolagents`](https://apify.com/templates/python-smolagents) | + +All of these templates live in the [actor-templates repository](https://github.com/apify/actor-templates), and you can scaffold any of them with the [Apify CLI](https://docs.apify.com/cli), for example `apify create my-agent --template python-pydanticai`. + +## Connecting to an LLM + +Every agent needs an LLM, and there are two ways to provide one. + +The first is the [Apify OpenRouter proxy](https://apify.com/apify/openrouter), an OpenAI-compatible endpoint at `https://openrouter.apify.actor/api/v1` that fronts the full [OpenRouter](https://openrouter.ai) model catalog. The token usage is billed against the Apify account running the Actor, so no provider API key is required. The Actor authenticates with the proxy using the `APIFY_TOKEN` that the platform injects into every run. Any framework with an OpenAI-compatible client can point its base URL at the proxy, which is what every example below does. To switch models, change the `model` input to any [OpenRouter model slug](https://openrouter.ai/models), for example `openai/gpt-4o-mini`. + +The second is to call a provider such as OpenAI directly with your own API key. Keep the key out of the Actor input and source code. Read it from an environment variable, which on the platform you set as a [secret environment variable](https://docs.apify.com/platform/actors/development/programming-interface/environment-variables) and locally you export in your shell. + +Each section below shows a complete, single-file Actor for one framework. They all read the input, run the agent, and store the result in the default dataset. + +## LangGraph + +[LangGraph](https://www.langchain.com/langgraph) builds an agent as a graph with explicit state, which makes complex, multi-step control flow easy to follow. It builds on [LangChain](https://www.langchain.com/), so any LangChain chat model and tool works. To install it, use: + +```bash +pip install langchain langchain-openai langgraph +``` + +The following Actor runs an agent with a single tool: + + + {LanggraphExample} + + +Note that: + +- `ChatOpenAI` points its `base_url` at the Apify OpenRouter proxy, so any LangChain chat model works without a provider key. +- The agent decides on its own when to call the `sum_numbers` tool, and the answer is read from the last message in the returned state. +- Add more LangChain tools to extend it, including Apify Actors (see [Using Apify Actors as tools](#using-apify-actors-as-tools)). + +## CrewAI + +[CrewAI](https://www.crewai.com/) models a problem as a "crew" of role-playing agents that work through tasks. To install it, use: + +```bash +pip install crewai +``` + +The following Actor defines a single analyst agent with one tool: + + + {CrewaiExample} + + +Note that: + +- CrewAI's `LLM` points its `base_url` at the Apify OpenRouter proxy. The `openai/` model prefix selects its OpenAI-compatible client, so no provider key is needed. +- `kickoff_async` runs the crew without blocking the Actor's event loop. +- The agent decides on its own when to call the `average` tool. Add more tools to extend it, including Apify Actors (see [Using Apify Actors as tools](#using-apify-actors-as-tools)). +- On a fresh container, CrewAI shows a one-time trace-consent prompt. The template sets `CREWAI_TESTING=true` to suppress it. Do the same in your Dockerfile. + +## PydanticAI + +[PydanticAI](https://ai.pydantic.dev/) is an agent framework from the team behind Pydantic. It's strongly typed and integrates naturally with the [Pydantic models](./input-validation) the Apify SDK already uses. To install it, use: + +```bash +pip install pydantic-ai +``` + +The following Actor generates a joke and returns it as a typed object: + + + {PydanticaiExample} + + +Note that: + +- The agent reaches the LLM through the Apify OpenRouter proxy via `OpenAIChatModel` and a custom `OpenAIProvider`, so no provider API key is needed. +- `output_type=Joke` makes the agent return a validated `Joke` instance, which maps directly onto a dataset row. Set `output_type=str` instead to get plain text back. + +## LlamaIndex + +[LlamaIndex](https://www.llamaindex.ai/) is built for retrieval-augmented agents that reason over your own data. To install it, use: + +```bash +pip install llama-index llama-index-llms-openai-like +``` + +The following Actor runs a `ReActAgent` with a single tool: + + + {LlamaindexExample} + + +Note that: + +- `OpenAILike` is the LlamaIndex LLM class for OpenAI-compatible endpoints such as the Apify OpenRouter proxy. It needs the `llama-index-llms-openai-like` package. +- The agent decides on its own when to call the `word_count` tool. Add `FunctionTool`s of your own to extend it. +- To reason over your own data, wrap an Apify Actor in a `FunctionTool` (see [Using Apify Actors as tools](#using-apify-actors-as-tools)), as the [LlamaIndex template](https://apify.com/templates/python-llamaindex-agent) does with a contact-details scraper. + +## Smolagents + +[Smolagents](https://github.com/huggingface/smolagents) is a lightweight framework from Hugging Face whose agents write and run Python code to solve a task. To install it, use: + +```bash +pip install "smolagents[openai]" +``` + +The following Actor runs a `CodeAgent`: + + + {SmolagentsExample} + + +Note that: + +- `OpenAIServerModel` points `api_base` at the Apify OpenRouter proxy, so no provider API key is needed. +- The agent uses `WebSearchTool` to fetch the latest news, then writes and runs Python code to summarize it. +- Because a `CodeAgent` executes the code it generates, run it in the isolated Actor container rather than on your own machine. + +## Using Apify Actors as tools + +An agent becomes useful once it can act on the world. On Apify, any of the thousands of Actors in the [Apify Store](https://apify.com/store) can become a tool: a scraper that fetches data, a browser automation that fills a form, or an API wrapper that posts a message. + +Some frameworks ship a ready-made wrapper for this. For LangGraph and other [LangChain](https://www.langchain.com/)-based agents, the [`langchain-apify`](https://github.com/apify/langchain-apify) package exposes any Actor as a tool with a single line: + +```python +from langchain_apify import ApifyActorsTool + +# Let the agent scrape Instagram profiles by calling the apify/instagram-scraper Actor. +tools = [ApifyActorsTool('apify/instagram-scraper')] +``` + +CrewAI ships the same tool as `crewai_tools.ApifyActorsTool` in its `crewai[tools]` package. + +For any other framework, call the Actor directly through the Actor's preconfigured API client and read its dataset: + +```python +async def scrape_instagram(handle: str) -> list[dict]: + """Scrape recent posts from an Instagram profile.""" + run_input = {'directUrls': [f'https://www.instagram.com/{handle}/']} + run = await Actor.apify_client.actor('apify/instagram-scraper').call(run_input=run_input) + return (await Actor.apify_client.dataset(run['defaultDatasetId']).list_items()).items +``` + +For details on calling other Actors, see [Interacting with other Actors](../concepts/interacting-with-other-actors). + +## Running on the Apify platform + +Agents run on the standard [Apify Python base image](https://hub.docker.com/r/apify/actor-python), so no browser or extra system dependencies are needed. Add `apify` and the packages shown in your framework's section above to `requirements.txt`, then deploy the Actor as usual. + +To monetize the agent, use [pay-per-event charging](../concepts/pay-per-event). You define events such as `task-completed` in the Actor's monetization settings and trigger them from the code: + +```python +await Actor.charge('task-completed') +``` + +This lets you charge users directly from the Actor and cover the cost of execution and LLM tokens. It pairs naturally with the Apify OpenRouter proxy, which already bills the LLM usage to the account running the Actor. + +## Conclusion + +In this guide, you learned how to host an AI agent as an Apify Actor. You can now build an agent with LangGraph, CrewAI, PydanticAI, LlamaIndex, or Smolagents, connect it to an LLM through the Apify OpenRouter proxy, give it Apify Actors as tools, and monetize it with pay-per-event. To get started, see the [Actor templates](https://apify.com/templates/categories/python). If you have questions or need assistance, feel free to reach out on our [GitHub](https://github.com/apify/apify-sdk-python) or join our [Discord community](https://discord.com/invite/jyEM2PRvMU). Happy building! + +## Additional resources + +- [Apify: LangGraph template](https://apify.com/templates/python-langgraph) +- [Apify: CrewAI template](https://apify.com/templates/python-crewai) +- [Apify: PydanticAI template](https://apify.com/templates/python-pydanticai) +- [Apify: LlamaIndex template](https://apify.com/templates/python-llamaindex-agent) +- [Apify: Smolagents template](https://apify.com/templates/python-smolagents) +- [Apify: actor-templates repository](https://github.com/apify/actor-templates) +- [Apify: OpenRouter proxy](https://apify.com/apify/openrouter) +- [Apify: langchain-apify integration](https://github.com/apify/langchain-apify) +- [Apify blog: What are AI agents](https://blog.apify.com/what-are-ai-agents/) diff --git a/docs/03_guides/code/14_crewai.py b/docs/03_guides/code/14_crewai.py new file mode 100644 index 00000000..7fc02162 --- /dev/null +++ b/docs/03_guides/code/14_crewai.py @@ -0,0 +1,58 @@ +import asyncio +import os + +from crewai import LLM, Agent, Crew, Task +from crewai.tools import tool + +from apify import Actor + +OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1' + +# On a fresh container, CrewAI shows a one-time trace-consent prompt that blocks on +# stdin. `CREWAI_TESTING=true` is the only flag that suppresses it. +os.environ.setdefault('CREWAI_TESTING', 'true') + + +@tool('Average') +def average(numbers: list[float]) -> float: + """Return the arithmetic mean of a list of numbers.""" + return sum(numbers) / len(numbers) + + +async def main() -> None: + async with Actor: + actor_input = await Actor.get_input() or {} + query = actor_input.get('query', 'What is the average of 12, 18, and 30?') + model = actor_input.get('model', 'openai/gpt-4o-mini') + + # Route the LLM through the Apify OpenRouter proxy (no provider key needed). + # The `openai/` prefix selects CrewAI's OpenAI-compatible client. The rest + # is the OpenRouter model slug sent to the proxy. + llm = LLM( + model=f'openai/{model}', + base_url=OPENROUTER_BASE_URL, + api_key=os.environ['APIFY_TOKEN'], + ) + + # A one-agent crew: an analyst that answers using the `average` tool. + analyst = Agent( + role='Data Analyst', + goal='Answer numeric questions accurately.', + backstory='An analyst who turns raw numbers into clear answers.', + tools=[average], + llm=llm, + ) + task = Task( + description=query, + expected_output='A short, readable answer to the query.', + agent=analyst, + ) + + # `kickoff_async` keeps the Actor's event loop responsive. + result = await Crew(agents=[analyst], tasks=[task]).kickoff_async() + Actor.log.info(f'Crew result:\n{result.raw}') + await Actor.push_data({'query': query, 'answer': result.raw}) + + +if __name__ == '__main__': + asyncio.run(main()) diff --git a/docs/03_guides/code/14_langgraph.py b/docs/03_guides/code/14_langgraph.py new file mode 100644 index 00000000..0d990daa --- /dev/null +++ b/docs/03_guides/code/14_langgraph.py @@ -0,0 +1,41 @@ +import asyncio +import os + +from langchain.agents import create_agent +from langchain_core.tools import tool +from langchain_openai import ChatOpenAI + +from apify import Actor + +OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1' + + +@tool +def sum_numbers(numbers: list[int]) -> int: + """Return the sum of a list of numbers.""" + return sum(numbers) + + +async def main() -> None: + async with Actor: + actor_input = await Actor.get_input() or {} + query = actor_input.get('query', 'What is the sum of 128, 64, and 32?') + model = actor_input.get('model', 'openai/gpt-4o-mini') + + # Route the LLM through the Apify OpenRouter proxy (no provider key needed). + llm = ChatOpenAI( + model=model, + base_url=OPENROUTER_BASE_URL, + api_key=os.environ['APIFY_TOKEN'], + ) + # The agent decides on its own when to call the `sum_numbers` tool. + agent = create_agent(llm, tools=[sum_numbers]) + + result = await agent.ainvoke({'messages': [('user', query)]}) + answer = result['messages'][-1].content + Actor.log.info(f'Agent answer:\n{answer}') + await Actor.push_data({'query': query, 'answer': answer}) + + +if __name__ == '__main__': + asyncio.run(main()) diff --git a/docs/03_guides/code/14_llamaindex.py b/docs/03_guides/code/14_llamaindex.py new file mode 100644 index 00000000..ed75901b --- /dev/null +++ b/docs/03_guides/code/14_llamaindex.py @@ -0,0 +1,40 @@ +import asyncio +import os + +from llama_index.core.agent import ReActAgent +from llama_index.core.tools import FunctionTool +from llama_index.llms.openai_like import OpenAILike + +from apify import Actor + +OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1' + + +def word_count(text: str) -> int: + """Return the number of words in the given text.""" + return len(text.split()) + + +async def main() -> None: + async with Actor: + actor_input = await Actor.get_input() or {} + query = actor_input.get('query', 'How many words are in "Apify runs Actors"?') + model = actor_input.get('model', 'openai/gpt-4o-mini') + + # Route the LLM through the Apify OpenRouter proxy (no provider key needed). + # `OpenAILike` is the LlamaIndex class for OpenAI-compatible endpoints. + llm = OpenAILike( + model=model, + api_base=OPENROUTER_BASE_URL, + api_key=os.environ['APIFY_TOKEN'], + is_chat_model=True, + ) + agent = ReActAgent(tools=[FunctionTool.from_defaults(fn=word_count)], llm=llm) + + response = await agent.run(user_msg=query) + Actor.log.info(f'Agent answer:\n{response}') + await Actor.push_data({'query': query, 'answer': str(response)}) + + +if __name__ == '__main__': + asyncio.run(main()) diff --git a/docs/03_guides/code/14_pydanticai.py b/docs/03_guides/code/14_pydanticai.py new file mode 100644 index 00000000..083da4b5 --- /dev/null +++ b/docs/03_guides/code/14_pydanticai.py @@ -0,0 +1,47 @@ +import asyncio +import os + +from pydantic import BaseModel +from pydantic_ai import Agent +from pydantic_ai.models.openai import OpenAIChatModel +from pydantic_ai.providers.openai import OpenAIProvider + +from apify import Actor + +OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1' + + +class Joke(BaseModel): + """The agent's typed output: a joke split into its setup and punchline.""" + + setup: str + punchline: str + + +async def main() -> None: + async with Actor: + actor_input = await Actor.get_input() or {} + topic = actor_input.get('topic', 'bad weather') + model = actor_input.get('model', 'openai/gpt-4o-mini') + + # Route the LLM through the Apify OpenRouter proxy (no provider key needed). + provider = OpenAIProvider( + base_url=OPENROUTER_BASE_URL, + api_key=os.environ['APIFY_TOKEN'], + ) + # `output_type=Joke` makes the agent return a validated `Joke` instance. + agent = Agent( + OpenAIChatModel(model, provider=provider), + output_type=Joke, + system_prompt='You are a witty comedian. Write a single short joke.', + ) + + joke = (await agent.run(user_prompt=f'Tell me a joke about {topic}.')).output + Actor.log.info(f'Joke:\n{joke.setup}\n{joke.punchline}') + await Actor.push_data( + {'topic': topic, 'setup': joke.setup, 'punchline': joke.punchline} + ) + + +if __name__ == '__main__': + asyncio.run(main()) diff --git a/docs/03_guides/code/14_smolagents.py b/docs/03_guides/code/14_smolagents.py new file mode 100644 index 00000000..f5d29d31 --- /dev/null +++ b/docs/03_guides/code/14_smolagents.py @@ -0,0 +1,33 @@ +import asyncio +import os + +from smolagents import CodeAgent, OpenAIServerModel, WebSearchTool + +from apify import Actor + +OPENROUTER_BASE_URL = 'https://openrouter.apify.actor/api/v1' + + +async def main() -> None: + async with Actor: + actor_input = await Actor.get_input() or {} + topic = actor_input.get('topic', 'open source AI') + model = actor_input.get('model', 'openai/gpt-4o-mini') + + # Route the LLM through the Apify OpenRouter proxy (no provider key needed). + llm = OpenAIServerModel( + model_id=model, + api_base=OPENROUTER_BASE_URL, + api_key=os.environ['APIFY_TOKEN'], + ) + # A `CodeAgent` writes and runs Python code to solve the task. Here it uses + # `WebSearchTool` to gather the latest news before summarizing it. + agent = CodeAgent(tools=[WebSearchTool()], model=llm) + + result = agent.run(f'Find and summarize the latest news about {topic}.') + Actor.log.info(f'Summary:\n{result}') + await Actor.push_data({'topic': topic, 'summary': str(result)}) + + +if __name__ == '__main__': + asyncio.run(main())