This integration is for the Respan gateway .
Overview
LangChain provides a powerful framework for building applications with language models. You can seamlessly integrate Respan with LangChain’s ChatOpenAI LLM with minimal code changes.
Quickstart
Step 1: Install LangChain
pip install langchain-openai
Step 2: Initialize LangChain with Respan
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
base_url = "https://api.respan.ai/api/" ,
api_key = "<Your Respan API Key>" ,
model = "gpt-3.5-turbo" ,
streaming = True ,
)
Step 3: Make Your First Request
response = llm.invoke( "Hello, world!" )
print (response)
Switch models
# OpenAI GPT models
model = "gpt-4o"
# model = "claude-3-5-sonnet-20241022"
# model = "gemini-1.5-pro"
llm = ChatOpenAI(
base_url = "https://api.respan.ai/api/" ,
api_key = "<Your Respan API Key>" ,
model = model,
)
Supported parameters
OpenAI parameters
We support all the OpenAI parameters . You can pass them directly in the LangChain configuration.
llm = ChatOpenAI(
base_url = "https://api.respan.ai/api/" ,
api_key = "<Your Respan API Key>" ,
model = "gpt-4o-mini" ,
temperature = 0.7 , # Control randomness
max_tokens = 1000 , # Limit response length
streaming = True , # Enable streaming
)
Respan Parameters
Respan parameters can be passed using extra_body for better handling and customization.
llm = ChatOpenAI(
base_url = "https://api.respan.ai/api/" ,
api_key = "<Your Respan API Key>" ,
model = "gpt-4o-mini" ,
extra_body = {
"customer_identifier" : "user_123" , # Track specific users
"fallback_models" : [ "gpt-3.5-turbo" ], # Automatic fallbacks
"metadata" : { "session_id" : "abc123" }, # Custom metadata
"thread_identifier" : "conversation_456" , # Group related messages
"group_identifier" : "team_alpha" , # Organize by groups
}
)
Advanced Usage (optional)
Using with Chains
from langchain.chains import ConversationChain
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(
base_url = "https://api.respan.ai/api/" ,
api_key = "<Your Respan API Key>" ,
model = "gpt-4o-mini" ,
)
chain = ConversationChain( llm = llm)
response = chain.run( "Tell me about artificial intelligence" )
print (response)
View your analytics Access your Respan dashboard to see detailed analytics
Next Steps