LangChain tool for semantic search over Federal Acquisition Regulations (FAR)
Project description
FAR Search Tool for LangChain
A LangChain tool for semantic search over Federal Acquisition Regulations (FAR).
Enable your AI agents to search and understand U.S. government contracting regulations, procurement rules, and compliance requirements.
Keywords: langchain, government contracting, FAR, federal acquisition regulations, procurement, compliance, AI agent tools, RAG, semantic search
Installation
pip install far-search-tool
🚀 Quick Start (30 seconds)
Step 1: Install
pip install far-search-tool
Step 2: Use It
from far_search import FARSearchTool
# Auto-registers on first use - no API key needed!
tool = FARSearchTool()
result = tool.invoke({"query": "small business set aside requirements"})
print(result)
That's it! On first use, you'll see:
============================================================
✅ FAR Search Tool - Auto-registered!
============================================================
📋 Your API key: far_live_abc123...
📊 Free tier: 500 queries/month
📖 Upgrade: https://rapidapi.com/yschang/api/far-rag-...
💾 Save your key: export FAR_API_KEY=far_live_abc123...
============================================================
With RapidAPI Key (Higher Limits)
For production use with higher rate limits, get an API key from RapidAPI.
from far_search import FARSearchTool
tool = FARSearchTool(rapidapi_key="your-rapidapi-key")
result = tool.invoke({
"query": "cybersecurity requirements for contractors"
})
Use with LangChain Agents
from langchain.agents import initialize_agent, AgentType
from langchain_openai import ChatOpenAI
from far_search import FARSearchTool
# Initialize LLM and tool
llm = ChatOpenAI(model="gpt-4")
tools = [FARSearchTool()]
# Create agent
agent = initialize_agent(
tools=tools,
llm=llm,
agent=AgentType.OPENAI_FUNCTIONS,
verbose=True
)
# Ask about regulations
response = agent.run(
"What are the FAR requirements for small business subcontracting plans?"
)
print(response)
Use with LangGraph
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from far_search import FARSearchTool
# Create agent with FAR search capability
agent = create_react_agent(
ChatOpenAI(model="gpt-4"),
tools=[FARSearchTool()]
)
# Query the agent
result = agent.invoke({
"messages": [("user", "What cybersecurity clauses should I include in a DoD contract?")]
})
Features
- Semantic Search: Find relevant regulations using natural language queries
- Pre-vectorized Data: 617 FAR clauses with pre-computed embeddings for fast search
- LLM-Optimized Output: Results formatted for easy consumption by language models
- Retry Logic: Built-in handling for transient failures
- Dual API Support: Free tier or RapidAPI for production use
API Reference
FARSearchTool
FARSearchTool(
rapidapi_key: str = None, # Optional RapidAPI key for paid tier
base_url: str = None, # Override API URL (for self-hosted)
timeout: int = 30, # Request timeout in seconds
max_retries: int = 2 # Retry attempts on failure
)
Input Schema
| Parameter | Type | Default | Description |
|---|---|---|---|
query |
str | required | Natural language search query |
top_k |
int | 5 | Number of results (1-20) |
Output
Returns a formatted string containing matching FAR clauses with:
- Clause ID and title
- Relevance score
- Source reference
- URL to official documentation
- Clause text (truncated if long)
Example Queries
- "Small business set aside requirements"
- "Cybersecurity contract clauses"
- "Payment terms for government contracts"
- "Contractor ethics and conduct rules"
- "Cost accounting standards"
- "Intellectual property rights in contracts"
- "Subcontracting plan requirements"
- "Contract termination procedures"
Pricing
| Tier | Rate Limit | Price |
|---|---|---|
| Free | 500 requests/month | $0 |
| Pro | 5,000 requests/month | $29/month |
| Ultra | 150,000 requests/month | $199/month |
Get your API key at RapidAPI.
Error Handling
from far_search import FARSearchTool, FARAPIError, FARRateLimitError
tool = FARSearchTool()
try:
result = tool.invoke({"query": "my query"})
except FARRateLimitError:
print("Rate limit exceeded. Upgrade your plan or wait.")
except FARAPIError as e:
print(f"API error: {e}")
Compliance & Audit Logging
For government contractors and regulated industries, maintain audit trails of all FAR searches using Agent Observability:
from far_search import FARSearchTool
from agent_observability import AgentLogger
# Initialize - auto-registers on first use, no API key needed!
far_tool = FARSearchTool()
logger = AgentLogger()
# Search and log for compliance
query = "cybersecurity requirements FAR 52.204"
results = far_tool.invoke({"query": query})
# Log the search for audit trail
logger.log("far_search", {
"query": query,
"results_count": len(results) if isinstance(results, list) else 1,
"contract": "GS-00F-0001X",
"purpose": "compliance_check"
})
# First log auto-registers and shows:
# ✅ Agent Observability - Auto-registered!
# 📋 Your API key: ao_live_abc123...
Why log FAR searches?
- DFARS Compliance: Government contracts often require audit trails
- Cost Tracking: Know how much time is spent on regulatory research
- Team Analytics: See what your team searches most frequently
- SOC 2 / ISO 27001: Demonstrate due diligence in compliance
Setup (30 seconds):
pip install agent-observability
That's it! No API key needed - auto-registers on first use. Free tier: 100K logs/month.
Learn more: Agent Observability
Requirements
- Python 3.9+
- langchain >= 0.1.0
- requests >= 2.28.0
- pydantic >= 2.0.0
License
MIT License - see LICENSE for details.
Links
Contributing
Contributions welcome! Please open an issue or submit a pull request.
Project details
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