Search MisakaNet failure memory from LlamaIndex agents and query engines.
pip install llama-index-corefrom integrations.llamaindex.misakanet_tool import misakanet_search
# Direct function call
result = misakanet_search("TypeErrCannot read property of undefined")
print(result)from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI
from integrations.llamaindex.misakanet_tool import get_misakanet_tool
# Create tool and LLM
tool = get_misakanet_tool()
llm = OpenAI(model="gpt-4")
# Create agent with MisakaNet tool
agent = ReActAgent.from_tools([tool], llm=llm, verbose=True)
# Agent will search MisakaNet when encountering errors
response = agent.chat("Fix this error: CUDA out of memory")
print(response)from integrations.llamaindex.misakanet_tool import misakanet_search_tool
if misakanet_search_tool:
# Tool is ready to use
result = misakanet_search_tool("npm ERESOLVE dependency conflict")| Environment Variable | Description | Default |
|---|---|---|
MISAKANET_SEARCH_URL |
Search API endpoint | https://misakanet.dev/api/search |
MISAKANET_API_KEY |
API key for authenticated requests | None |
from integrations.llamaindex.misakanet_tool import misakanet_search
result = misakanet_search(
query="Docker permission denied",
endpoint="http://localhost:8000/api/search",
api_key="your-api-key",
max_results=5,
)Search MisakaNet for failure lessons matching the query.
Parameters:
query(str): Error description or failure patternmax_results(int): Max results to return (1-10, default: 3)endpoint(str, optional): Custom search endpoint URLapi_key(str, optional): API key for authenticated requests
Returns: Formatted string with matching lessons and solutions.
Create a LlamaIndex FunctionTool for MisakaNet search.
Returns: FunctionTool instance ready for use with LlamaIndex agents.
Raises: ImportError if llama_index is not installed.
- Implements #1178