Perplexity Search

pip install -U "ag2[openai]"

import os
import autogen
from autogen import AssistantAgent, UserProxyAgent, LLMConfig
from autogen.tools.experimental import PerplexitySearchTool

llm_config = LLMConfig(api_type="openai", model="gpt-4o-mini")

assistant = AssistantAgent(
    name="assistant",
    llm_config=llm_config,
)

user_proxy = UserProxyAgent(
    name="user_proxy",
    human_input_mode="NEVER"
)

perplexity_search_tool = PerplexitySearchTool(
    api_key=os.getenv("PERPLEXITY_API_KEY"),
    max_tokens=1000
)

# Register the tool for LLM recommendation and execution.
perplexity_search_tool.register_for_llm(assistant)
perplexity_search_tool.register_for_execution(user_proxy)

response = user_proxy.initiate_chat(
    recipient=assistant,
    message="What is AG2?",
    max_turns=2,
)
````

### Output

```console
user_proxy (to assistant):

What is AG2?

--------------------------------------------------------------------------------
assistant (to user_proxy):

***** Suggested tool call (call_kOW9AP9YmrCJbxhnnqiNjXVz): perplexity-search *****
Arguments:
{"query":"What is AG2?"}
**********************************************************************************

--------------------------------------------------------------------------------

>>>>>>>> EXECUTING FUNCTION perplexity-search...
Call ID: call_kOW9AP9YmrCJbxhnnqiNjXVz
Input arguments: {'query': 'What is AG2?'}
user_proxy (to assistant):

***** Response from calling tool (call_kOW9AP9YmrCJbxhnnqiNjXVz) *****
{"content":"AG2 is an open-source framework for building AI-powered agents, originally a community-driven fork of the AutoGen project. It is led by Dr. Chi Wang of Google DeepMind and Dr. Qingyun Wu of Penn State University. AG2 focuses on **multi-agent systems**, enabling autonomous agents to collaborate and solve complex problems across various domains such as education, enterprise workflows, and healthcare[1][3][5]. It provides tools for enhanced Large Language Model (LLM) inference and optimization, facilitating the creation of diverse applications[3][4].","citations":["https://www.forwardfuture.ai/p/agents-in-action-the-rise-of-ag2-and-the-future-of-intelligent-agents","https://www.youtube.com/watch?v=UItthyY71UU","https://docs.ag2.ai/docs/home/home","https://docs.ag2.ai/latest/docs/home/home/","https://cloud.google.com/vertex-ai/generative-ai/docs/agent-engine/develop/ag2","https://atmosphericg2.com/homepage/products/ag2data/","https://atmosphericg2.com/ag2trader/"]}
**********************************************************************

--------------------------------------------------------------------------------
assistant (to user_proxy):

AG2 is an open-source framework for building AI-powered agents, initially a community-driven fork of the AutoGen project. It is led by researchers Dr. Chi Wang of Google DeepMind and Dr. Qingyun Wu of Penn State University. AG2 emphasizes **multi-agent systems**, allowing autonomous agents to collaborate and tackle complex problems in various fields, including education, enterprise workflows, and healthcare.

The framework provides tools for improved Large Language Model (LLM) inference and optimization, facilitating the development of diverse applications.

For more detailed information, you can explore the following resources:
- [Forward Future Article](https://www.forwardfuture.ai/p/agents-in-action-the-rise-of-ag2-and-the-future-of-intelligent-agents)
- [Official Documentation](https://docs.ag2.ai/docs/home/home)

TERMINATE

--------------------------------------------------------------------------------

>>>>>>>> TERMINATING RUN (2ab104c4-cfe6-4ce7-88e3-fb83b9623a7a): Maximum turns (2) reached

Process finished with exit code 0
````

### Key Considerations

#### Cost Management

**Free Tier Limits**:
- 100 daily queries included.
- Monitor usage via [Perplexity Dashboard](https://www.perplexity.ai/settings/api).

#### Performance Optimizations

**Best Practices**:

- Start with smaller response lengths by setting the `max_tokens` parameter.
- Filter search domains with `search_domain_filter` parameter to restrict the search results to specific domains.
```python
optimized_tool = PerplexitySearchTool(
    api_key=os.getenv("PERPLEXITY_API_KEY"),
    max_tokens=1000,
    search_domain_filter=["arxiv.org", "towardsdatascience.com"],
)