Remove lightrag_api_open_webui_demo.py file

examples/lightrag_api_open_webui_demo.py

@@ -1,140 +0,0 @@
-from datetime import datetime, timezone
-from fastapi import FastAPI
-from fastapi.responses import StreamingResponse
-import inspect
-import json
-from pydantic import BaseModel
-from typing import Optional
-
-import os
-import logging
-from lightrag import LightRAG, QueryParam
-from lightrag.llm.ollama import ollama_model_complete, ollama_embed
-from lightrag.utils import EmbeddingFunc
-
-import nest_asyncio
-
-WORKING_DIR = "./dickens"
-
-logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO)
-
-if not os.path.exists(WORKING_DIR):
-    os.mkdir(WORKING_DIR)
-
-rag = LightRAG(
-    working_dir=WORKING_DIR,
-    llm_model_func=ollama_model_complete,
-    llm_model_name="qwen2.5:latest",
-    llm_model_max_async=4,
-    llm_model_max_token_size=32768,
-    llm_model_kwargs={"host": "http://localhost:11434", "options": {"num_ctx": 32768}},
-    embedding_func=EmbeddingFunc(
-        embedding_dim=1024,
-        max_token_size=8192,
-        func=lambda texts: ollama_embed(
-            texts=texts, embed_model="bge-m3:latest", host="http://127.0.0.1:11434"
-        ),
-    ),
-)
-
-with open("./book.txt", "r", encoding="utf-8") as f:
-    rag.insert(f.read())
-
-# Apply nest_asyncio to solve event loop issues
-nest_asyncio.apply()
-
-app = FastAPI(title="LightRAG", description="LightRAG API open-webui")
-
-
-# Data models
-MODEL_NAME = "LightRAG:latest"
-
-
-class Message(BaseModel):
-    role: Optional[str] = None
-    content: str
-
-
-class OpenWebUIRequest(BaseModel):
-    stream: Optional[bool] = None
-    model: Optional[str] = None
-    messages: list[Message]
-
-
-# API routes
-
-
-@app.get("/")
-async def index():
-    return "Set Ollama link to http://ip:port/ollama in Open-WebUI Settings"
-
-
-@app.get("/ollama/api/version")
-async def ollama_version():
-    return {"version": "0.4.7"}
-
-
-@app.get("/ollama/api/tags")
-async def ollama_tags():
-    return {
-        "models": [
-            {
-                "name": MODEL_NAME,
-                "model": MODEL_NAME,
-                "modified_at": "2024-11-12T20:22:37.561463923+08:00",
-                "size": 4683087332,
-                "digest": "845dbda0ea48ed749caafd9e6037047aa19acfcfd82e704d7ca97d631a0b697e",
-                "details": {
-                    "parent_model": "",
-                    "format": "gguf",
-                    "family": "qwen2",
-                    "families": ["qwen2"],
-                    "parameter_size": "7.6B",
-                    "quantization_level": "Q4_K_M",
-                },
-            }
-        ]
-    }
-
-
-@app.post("/ollama/api/chat")
-async def ollama_chat(request: OpenWebUIRequest):
-    resp = rag.query(
-        request.messages[-1].content, param=QueryParam(mode="hybrid", stream=True)
-    )
-    if inspect.isasyncgen(resp):
-
-        async def ollama_resp(chunks):
-            async for chunk in chunks:
-                yield (
-                    json.dumps(
-                        {
-                            "model": MODEL_NAME,
-                            "created_at": datetime.now(timezone.utc).strftime(
-                                "%Y-%m-%dT%H:%M:%S.%fZ"
-                            ),
-                            "message": {
-                                "role": "assistant",
-                                "content": chunk,
-                            },
-                            "done": False,
-                        },
-                        ensure_ascii=False,
-                    ).encode("utf-8")
-                    + b"\n"
-                )  # the b"\n" is important
-
-        return StreamingResponse(ollama_resp(resp), media_type="application/json")
-    else:
-        return resp
-
-
-@app.get("/health")
-async def health_check():
-    return {"status": "healthy"}
-
-
-if __name__ == "__main__":
-    import uvicorn
-
-    uvicorn.run(app, host="0.0.0.0", port=8020)