[CLEANUP] Docs & EXA

docs/examples/ma_swarm.md

@@ -25,21 +25,14 @@ To set up and run the M&A Advisory Swarm, follow these steps:
 
 ### Installation
 
-1.  **Clone the Swarms repository:**
+1.  **Install dependencies:**
-    ```bash
-    git clone https://github.com/kyegomez/swarms.git
-    cd swarms
-    ```
-    *(Note: The `ma_advisory.py` file is assumed to be in `examples/demos/apps/`)*
-
-2.  **Install dependencies:**
     The `ma_advisory.py` script relies on several libraries. These can be installed using the `requirements.txt` file located at the root of your project:
     ```bash
     pip install -r requirements.txt
     ```
     This will install `httpx`, `python-dotenv`, `loguru`, and other necessary packages.
 
-3.  **Set up Exa API Key:**
+2.  **Set up Exa API Key:**
     The `Market & Strategic Analysis Agent` utilizes the `exa_search` tool, which requires an `EXA_API_KEY`.
     Create a `.env` file in the root directory of your project (or wherever your application loads environment variables) and add your Exa API key:
     ```

examples/demos/apps/m&a_swarm.py

@@ -1,79 +1,9 @@
 from typing import List
-import os
-from dotenv import load_dotenv
 from loguru import logger
-import httpx
 from swarms.structs.agent import Agent
 from swarms.structs.conversation import Conversation
 from swarms.utils.history_output_formatter import history_output_formatter
-from swarms.utils.any_to_str import any_to_str
+from swarms_tools import exa_search
-
-# --- Exa Search Tool Integration ---
-def exa_search(
-    query: str,
-    characters: int = 1000,  # Increased for more detailed M&A research
-    sources: int = 5,  # More sources for comprehensive analysis
-) -> str:
-    """
-    Perform a highly summarized Exa web search for M&A market intelligence.
-
-    Args:
-        query (str): Search query for M&A research.
-        characters (int): Max characters for summary.
-        sources (int): Number of sources.
-
-    Returns:
-        str: Condensed summary of search results.
-    """
-    api_key = os.getenv("EXA_API_KEY")
-    if not api_key:
-        raise ValueError("EXA_API_KEY environment variable is not set")
-
-    headers = {
-        "x-api-key": api_key,
-        "content-type": "application/json",
-    }
-
-    payload = {
-        "query": query,
-        "type": "auto",
-        "numResults": sources,
-        "contents": {
-            "text": True,
-            "summary": {
-                "schema": {
-                    "type": "object",
-                    "required": ["answer"],
-                    "additionalProperties": False,
-                    "properties": {
-                        "answer": {
-                            "type": "string",
-                            "description": "Highly condensed summary of the M&A research result",
-                        }
-                    },
-                }
-            },
-            "context": {"maxCharacters": characters},
-        },
-    }
-
-    try:
-        logger.info(f"[SEARCH] Exa M&A research: {query[:50]}...")
-        response = httpx.post(
-            "https://api.exa.ai/search",
-            json=payload,
-            headers=headers,
-            timeout=30,
-        )
-        response.raise_for_status()
-        json_data = response.json()
-        return any_to_str(json_data)
-    except Exception as e:
-        logger.error(f"Exa search failed: {e}")
-        return f"Search failed: {str(e)}. Please try again."
-
-# Load environment variables
-load_dotenv()
 
 # System prompts for each agent
 INTAKE_AGENT_PROMPT = """