Files
langchain/libs/partners/prompty/README.md
Copilot 54542b9385 docs(openai): add comprehensive documentation and examples for extra_body + others (#32149)
This PR addresses the common issue where users struggle to pass custom
parameters to OpenAI-compatible APIs like LM Studio, vLLM, and others.
The problem occurs when users try to use `model_kwargs` for custom
parameters, which causes API errors.

## Problem

Users attempting to pass custom parameters (like LM Studio's `ttl`
parameter) were getting errors:

```python
#  This approach fails
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    model_kwargs={"ttl": 5}  # Causes TypeError: unexpected keyword argument 'ttl'
)
```

## Solution

The `extra_body` parameter is the correct way to pass custom parameters
to OpenAI-compatible APIs:

```python
#  This approach works correctly
llm = ChatOpenAI(
    base_url="http://localhost:1234/v1",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 5}  # Custom parameters go in extra_body
)
```

## Changes Made

1. **Enhanced Documentation**: Updated the `extra_body` parameter
docstring with comprehensive examples for LM Studio, vLLM, and other
providers

2. **Added Documentation Section**: Created a new "OpenAI-compatible
APIs" section in the main class docstring with practical examples

3. **Unit Tests**: Added tests to verify `extra_body` functionality
works correctly:
- `test_extra_body_parameter()`: Verifies custom parameters are included
in request payload
- `test_extra_body_with_model_kwargs()`: Ensures `extra_body` and
`model_kwargs` work together

4. **Clear Guidance**: Documented when to use `extra_body` vs
`model_kwargs`

## Examples Added

**LM Studio with TTL (auto-eviction):**
```python
ChatOpenAI(
    base_url="http://localhost:1234/v1",
    api_key="lm-studio",
    model="mlx-community/QwQ-32B-4bit",
    extra_body={"ttl": 300}  # Auto-evict after 5 minutes
)
```

**vLLM with custom sampling:**
```python
ChatOpenAI(
    base_url="http://localhost:8000/v1",
    api_key="EMPTY",
    model="meta-llama/Llama-2-7b-chat-hf",
    extra_body={
        "use_beam_search": True,
        "best_of": 4
    }
)
```

## Why This Works

- `model_kwargs` parameters are passed directly to the OpenAI client's
`create()` method, causing errors for non-standard parameters
- `extra_body` parameters are included in the HTTP request body, which
is exactly what OpenAI-compatible APIs expect for custom parameters

Fixes #32115.

<!-- START COPILOT CODING AGENT TIPS -->
---

💬 Share your feedback on Copilot coding agent for the chance to win a
$200 gift card! Click
[here](https://survey.alchemer.com/s3/8343779/Copilot-Coding-agent) to
start the survey.

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: mdrxy <61371264+mdrxy@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
2025-07-24 16:43:16 -04:00

1.1 KiB

langchain-prompty

This package contains the LangChain integration with Microsoft Prompty.

Installation

pip install -U langchain-prompty

Usage

Use the create_chat_prompt function to load prompty file as prompt.

from langchain_prompty import create_chat_prompt

prompt = create_chat_prompt('<your .prompty file path>')

Then you can use the prompt for next steps.

Here is an example .prompty file:

---
name: Basic Prompt
description: A basic prompt that uses the GPT-3 chat API to answer questions
authors:
  - author_1
  - author_2
model:
  api: chat
  configuration:
    azure_deployment: gpt-35-turbo
sample:
  firstName: Jane
  lastName: Doe
  question: What is the meaning of life?
  chat_history: []
---
system:
You are an AI assistant who helps people find information.
As the assistant, you answer questions briefly, succinctly, 
and in a personable manner using markdown and even add some personal flair with appropriate emojis.

{% for item in chat_history %}
{{item.role}}:
{{item.content}}
{% endfor %}


user:
{{input}}