Drop-in Tessera integration for LangChain. One line of config routes your existing ChatOpenAI / ChatAnthropic / ChatMistralAI / ChatGroq / ChatCohere through Tessera's auto-route + auto-cache + auto-compress + auto-batch proxy. Free tier: 60M tokens/mo. Production: 20% of measured savings.
Project description
tessera-langchain
Drop-in cost optimization for LangChain ChatModels. One line of config in your existing ChatOpenAI / ChatAnthropic / ChatMistralAI / ChatGroq / ChatCohere constructor routes your traffic through the Tessera proxy — auto-route, exact + provider-prompt-cache hits, per-role compression, output-length ceiling, batch arbitrage. Free Dev tier: 60M tokens/month, no card. Production: 20% of measured savings, $0 if we save you nothing.
Companion package to tessera-llm-proxy — same proxy, LangChain-shaped API.
Install
pip install tessera-langchain
Quickstart
from langchain_openai import ChatOpenAI
from tessera_langchain import tessera_openai_config
llm = ChatOpenAI(
model="gpt-4o",
openai_api_key="sk-...", # your OpenAI key, unchanged
**tessera_openai_config(api_key="tsr_..."), # one line, routes through Tessera
)
# Existing LangChain code (agents, chains, tools, streaming) runs unchanged.
response = llm.invoke("Summarize a Kubernetes operator architecture in 3 bullets.")
Same pattern for the other providers — tessera_anthropic_config, tessera_mistral_config, tessera_groq_config, tessera_cohere_config.
Or wrap an existing instance:
from tessera_langchain import wrap_openai
llm = wrap_openai(my_existing_ChatOpenAI, tessera_api_key="tsr_...")
Free key
Get a free API key (60M tokens/mo, no card) at tesseraai.io/dev — sign-up takes ~30 seconds and returns an instant tsr_… key plus magic-link dashboard access.
Documentation
Full README with worked-numbers example ($24k → $9.4k OpenAI bill cut), mechanic table, FAQ, and architecture notes:
→ github.com/tessera-llm/tessera-langchain
Tessera platform:
License
Apache-2.0. The SDK is open source; the optimization proxy at api.tesseraai.io is closed. Wire format is open; mechanic implementations are not.
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