LangChain | Respan Docs

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Use AI

Add the Docs MCP to your AI coding tool to get help building with Respan. No API key needed.

1 {
2   "mcpServers": {
3     "respan-docs": {
4       "url": "https://docs.respan.ai/mcp"
5     }
6   }
7 }

This integration is for the Respan gateway.

What is LangChain?

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

1 from langchain_openai import ChatOpenAI
2 
3 llm = ChatOpenAI(
4     base_url="https://api.respan.ai/api/",
5     api_key="<Your Respan API Key>",
6     model="gpt-3.5-turbo",
7     streaming=True,
8 )

Step 3: Make Your First Request

1 response = llm.invoke("Hello, world!")
2 print(response)

Switch models

1 # OpenAI GPT models
2 model = "gpt-4o"
3 # model = "claude-3-5-sonnet-20241022"
4 # model = "gemini-1.5-pro"
5 
6 llm = ChatOpenAI(
7     base_url="https://api.respan.ai/api/",
8     api_key="<Your Respan API Key>",
9     model=model,
10 )

See the full model list for all available models.

Supported parameters

OpenAI parameters

We support all the OpenAI parameters. You can pass them directly in the LangChain configuration.

1 llm = ChatOpenAI(
2     base_url="https://api.respan.ai/api/",
3     api_key="<Your Respan API Key>",
4     model="gpt-4o-mini",
5     temperature=0.7,          # Control randomness
6     max_tokens=1000,          # Limit response length
7     streaming=True,           # Enable streaming
8 )

Respan Parameters

Respan parameters can be passed using extra_body for better handling and customization.

1 llm = ChatOpenAI(
2     base_url="https://api.respan.ai/api/",
3     api_key="<Your Respan API Key>",
4     model="gpt-4o-mini",
5     extra_body={
6         "customer_identifier": "user_123",           # Track specific users
7         "fallback_models": ["gpt-3.5-turbo"],       # Automatic fallbacks
8         "metadata": {"session_id": "abc123"},        # Custom metadata
9         "thread_identifier": "conversation_456",     # Group related messages
10         "group_identifier": "team_alpha",           # Organize by groups
11     }
12 )

Advanced Usage

Using with Chains

1 from langchain.chains import ConversationChain
2 from langchain_openai import ChatOpenAI
3 
4 llm = ChatOpenAI(
5     base_url="https://api.respan.ai/api/",
6     api_key="<Your Respan API Key>",
7     model="gpt-4o-mini",
8 )
9 
10 chain = ConversationChain(llm=llm)
11 response = chain.run("Tell me about artificial intelligence")
12 print(response)

View your analytics

Access your Respan dashboard to see detailed analytics

Next Steps

User Management

Track user behavior and patterns

Prompt Management

Manage and version your prompts