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Hive Tool for LlamaIndex

llama-index-integrations/tools/llama-index-tools-hive/readme.md

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Hive Tool for LlamaIndex

This tool provides integration with Hive Intelligence, enabling powerful crypto and Web3 intelligence capabilities.

Installation

Install the package using pip:

bash
pip install llama-index-tools-hive

Setup

Set your Hive API key as an environment variable:

bash
export HIVE_API_KEY=your_api_key_here

On Windows:

cmd
set HIVE_API_KEY=your_api_key_here

Basic Usage

Import and Initialize

python
from llama_index.tools.hive import HiveToolSpec, HiveSearchMessage

# Initialize with API key and optional search parameters
hive_tool = HiveToolSpec(
    api_key="your_api_key_here",  # or it will use HIVE_API_KEY env var
)
python
# Single prompt search
results = hive_tool.search(
    prompt="What is the current price of Ethereum?", include_data_sources=True
)
print("Search results:", results)

Chat-style Conversation

python
# Create conversation messages
chat_msgs = [
    HiveSearchMessage(role="user", content="Price of what?"),
    HiveSearchMessage(role="assistant", content="Please specify asset."),
    HiveSearchMessage(role="user", content="BTC"),
]

# Execute chat search
results = hive_tool.search(messages=chat_msgs, include_data_sources=True)
print("Chat response:", results)

Advanced Usage

Search with Custom Parameters

python
results = hive_tool.search(
    prompt="Analyze the latest trends in DeFi",
    include_data_sources=True,  # Include sources in response
)

API Reference

HiveToolSpec

__init__(self, api_key: str, temperature: Optional[float] = None, top_k: Optional[int] = None, top_p: Optional[float] = None)

  • api_key: Your Hive Intelligence API key
  • temperature: Controls randomness (0.0 to 1.0) - optional
  • top_k: Limit number of results returned - optional
  • top_p: Nucleus sampling parameter - optional

search(self, prompt: str = None, messages: List[HiveSearchMessage] = None, include_data_sources: bool = False) -> HiveSearchResponse

Parameters:

  • prompt: The search query or question (string)
  • messages: List of HiveSearchMessage objects for chat-style conversations
  • include_data_sources: Whether to include data sources in the response

Returns:

  • HiveSearchResponse containing the search results

Examples

Full Example Script

python
from llama_index.tools.hive import HiveToolSpec, HiveSearchMessage


def main():
    # Initialize with API key and search parameters
    hive = HiveToolSpec(api_key="your_api_key_here")

    # Simple search
    print("--- Simple Search ---")
    results = hive.search(
        prompt="What is the current price of Bitcoin?",
        include_data_sources=True,
    )
    print("Results:", results)

    # Chat conversation
    print("\n--- Chat Conversation ---")
    chat = [
        HiveSearchMessage(role="user", content="Tell me about"),
        HiveSearchMessage(
            role="assistant", content="What would you like to know about?"
        ),
        HiveSearchMessage(role="user", content="Ethereum upgrades"),
    ]
    results = hive.search(messages=chat)
    print("Chat response:", results)


if __name__ == "__main__":
    main()