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"""
Chat model support.
Includes:
- ChatModel class for basic RAG-style completion/streaming
- get_chat_model() for LangChain-compatible usage with agents
"""
import os
import openai
from langchain_openai import ChatOpenAI
class ChatModel:
"""
Simple wrapper around OpenAI ChatCompletion for non-agent use (RAG).
Supports synchronous and asynchronous responses with streaming output.
"""
def __init__(self, model_name: str = None):
self.model_name = model_name or os.getenv("OPENAI_MODEL", "gpt-3.5-turbo")
self.api_key = os.getenv("OPENAI_API_KEY")
def run(self, prompt: str) -> str:
"""
Synchronously run a prompt against the chat model.
"""
openai.api_key = self.api_key
response = openai.ChatCompletion.create(
model=self.model_name,
messages=[{"role": "user", "content": prompt}],
temperature=0
)
return response.choices[0].message["content"]
async def astream(self, prompt: str):
"""
Asynchronously stream response chunks for a given prompt.
"""
openai.api_key = self.api_key
response = await openai.ChatCompletion.acreate(
model=self.model_name,
messages=[{"role": "user", "content": prompt}],
temperature=0,
stream=True
)
for chunk in response:
if chunk.choices[0].delta.get("content"):
yield chunk.choices[0].delta.content
def get_chat_model():
"""
Returns a LangChain-compatible chat model for use with tools or agents.
"""
return ChatOpenAI(
model=os.getenv("OPENAI_MODEL", "gpt-3.5-turbo"),
temperature=0,
streaming=True,
api_key=os.getenv("OPENAI_API_KEY")
)
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