83 lines
2.8 KiB
Python
83 lines
2.8 KiB
Python
from fastapi import APIRouter
|
|
from llama_index.llms import ChatMessage, MessageRole
|
|
from pydantic import BaseModel
|
|
from starlette.responses import StreamingResponse
|
|
|
|
from private_gpt.di import root_injector
|
|
from private_gpt.open_ai.extensions.context_filter import ContextFilter
|
|
from private_gpt.open_ai.openai_models import (
|
|
OpenAICompletion,
|
|
OpenAIMessage,
|
|
to_openai_response,
|
|
to_openai_sse_stream,
|
|
)
|
|
from private_gpt.server.chat.chat_service import ChatService
|
|
|
|
chat_router = APIRouter(prefix="/v1")
|
|
|
|
|
|
class ChatBody(BaseModel):
|
|
messages: list[OpenAIMessage]
|
|
use_context: bool = False
|
|
context_filter: ContextFilter | None = None
|
|
stream: bool = False
|
|
|
|
model_config = {
|
|
"json_schema_extra": {
|
|
"examples": [
|
|
{
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": "How do you fry an egg?",
|
|
}
|
|
],
|
|
"stream": False,
|
|
"use_context": True,
|
|
"context_filter": {
|
|
"docs_ids": ["c202d5e6-7b69-4869-81cc-dd574ee8ee11"]
|
|
},
|
|
}
|
|
]
|
|
}
|
|
}
|
|
|
|
|
|
@chat_router.post(
|
|
"/chat/completions",
|
|
response_model=None,
|
|
responses={200: {"model": OpenAICompletion}},
|
|
tags=["Contextual Completions"],
|
|
)
|
|
def chat_completion(body: ChatBody) -> OpenAICompletion | StreamingResponse:
|
|
"""Given a list of messages comprising a conversation, return a response.
|
|
|
|
If `use_context` is set to `true`, the model will use context coming
|
|
from the ingested documents to create the response. The documents being used can
|
|
be filtered using the `context_filter` and passing the document IDs to be used.
|
|
Ingested documents IDs can be found using `/ingest/list` endpoint. If you want
|
|
all ingested documents to be used, remove `context_filter` altogether.
|
|
|
|
When using `'stream': true`, the API will return data chunks following [OpenAI's
|
|
streaming model](https://platform.openai.com/docs/api-reference/chat/streaming):
|
|
```
|
|
{"id":"12345","object":"completion.chunk","created":1694268190,
|
|
"model":"private-gpt","choices":[{"index":0,"delta":{"content":"Hello"},
|
|
"finish_reason":null}]}
|
|
```
|
|
"""
|
|
service = root_injector.get(ChatService)
|
|
all_messages = [
|
|
ChatMessage(content=m.content, role=MessageRole(m.role)) for m in body.messages
|
|
]
|
|
if body.stream:
|
|
stream = service.stream_chat(
|
|
all_messages, body.use_context, body.context_filter
|
|
)
|
|
return StreamingResponse(
|
|
to_openai_sse_stream(stream), media_type="text/event-stream"
|
|
)
|
|
else:
|
|
response = service.chat(all_messages, body.use_context, body.context_filter)
|
|
return to_openai_response(response)
|