Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -1,15 +1,19 @@
|
|
1 |
import os
|
2 |
import time
|
3 |
-
from fastapi import FastAPI
|
4 |
from fastapi.responses import HTMLResponse
|
5 |
from fastapi.staticfiles import StaticFiles
|
6 |
from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate, Settings
|
7 |
from llama_index.llms.huggingface import HuggingFaceInferenceAPI
|
8 |
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
|
9 |
from pydantic import BaseModel
|
|
|
|
|
10 |
import datetime
|
11 |
-
from
|
12 |
-
|
|
|
|
|
13 |
# Define Pydantic model for incoming request body
|
14 |
class MessageRequest(BaseModel):
|
15 |
message: str
|
@@ -18,9 +22,34 @@ class MessageRequest(BaseModel):
|
|
18 |
os.environ["HF_TOKEN"] = os.getenv("HF_TOKEN")
|
19 |
app = FastAPI()
|
20 |
|
21 |
-
app.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
22 |
|
23 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
24 |
# Configure Llama index settings
|
25 |
Settings.llm = HuggingFaceInferenceAPI(
|
26 |
model_name="meta-llama/Meta-Llama-3-8B-Instruct",
|
@@ -89,10 +118,27 @@ def handle_query(query):
|
|
89 |
response ="Sorry, I couldn't find an answer."
|
90 |
current_chat_history.append((query, response))
|
91 |
return response
|
92 |
-
@app.get("/", response_class=HTMLResponse)
|
93 |
-
async def
|
94 |
-
|
95 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
96 |
|
97 |
@app.post("/chat/")
|
98 |
async def chat(request: MessageRequest):
|
@@ -106,5 +152,9 @@ async def chat(request: MessageRequest):
|
|
106 |
}
|
107 |
chat_history.append(message_data)
|
108 |
return {"response": response}
|
|
|
|
|
|
|
|
|
109 |
|
110 |
|
|
|
1 |
import os
|
2 |
import time
|
3 |
+
from fastapi import FastAPI,Request
|
4 |
from fastapi.responses import HTMLResponse
|
5 |
from fastapi.staticfiles import StaticFiles
|
6 |
from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate, Settings
|
7 |
from llama_index.llms.huggingface import HuggingFaceInferenceAPI
|
8 |
from llama_index.embeddings.huggingface import HuggingFaceEmbedding
|
9 |
from pydantic import BaseModel
|
10 |
+
from fastapi.responses import JSONResponse
|
11 |
+
import uuid # for generating unique IDs
|
12 |
import datetime
|
13 |
+
from fastapi.middleware.cors import CORSMiddleware
|
14 |
+
from fastapi.templating import Jinja2Templates
|
15 |
+
|
16 |
+
|
17 |
# Define Pydantic model for incoming request body
|
18 |
class MessageRequest(BaseModel):
|
19 |
message: str
|
|
|
22 |
os.environ["HF_TOKEN"] = os.getenv("HF_TOKEN")
|
23 |
app = FastAPI()
|
24 |
|
25 |
+
@app.middleware("http")
|
26 |
+
async def add_security_headers(request: Request, call_next):
|
27 |
+
response = await call_next(request)
|
28 |
+
response.headers["Content-Security-Policy"] = "frame-ancestors *; frame-src *; object-src *;"
|
29 |
+
response.headers["X-Frame-Options"] = "ALLOWALL"
|
30 |
+
return response
|
31 |
+
|
32 |
+
|
33 |
+
# Allow CORS requests from any domain
|
34 |
+
app.add_middleware(
|
35 |
+
CORSMiddleware,
|
36 |
+
allow_origins=["*"],
|
37 |
+
allow_credentials=True,
|
38 |
+
allow_methods=["*"],
|
39 |
+
allow_headers=["*"],
|
40 |
+
)
|
41 |
+
|
42 |
+
|
43 |
|
44 |
|
45 |
+
@app.get("/favicon.ico")
|
46 |
+
async def favicon():
|
47 |
+
return HTMLResponse("") # or serve a real favicon if you have one
|
48 |
+
|
49 |
+
|
50 |
+
app.mount("/static", StaticFiles(directory="D:\SRUNU (1)\content\SRUNU\static"), name="static")
|
51 |
+
|
52 |
+
templates = Jinja2Templates(directory="static")
|
53 |
# Configure Llama index settings
|
54 |
Settings.llm = HuggingFaceInferenceAPI(
|
55 |
model_name="meta-llama/Meta-Llama-3-8B-Instruct",
|
|
|
118 |
response ="Sorry, I couldn't find an answer."
|
119 |
current_chat_history.append((query, response))
|
120 |
return response
|
121 |
+
@app.get("/ch/{id}", response_class=HTMLResponse)
|
122 |
+
async def load_chat(request: Request, id: str):
|
123 |
+
return templates.TemplateResponse("index.html", {"request": request, "user_id": id})
|
124 |
+
# Route to save chat history
|
125 |
+
@app.post("/hist/")
|
126 |
+
async def save_chat_history(history: dict):
|
127 |
+
# Logic to save chat history, using the `id` from the frontend
|
128 |
+
print(history) # You can replace this with actual save logic
|
129 |
+
return {"message": "Chat history saved"}
|
130 |
+
@app.post("/webhook")
|
131 |
+
async def receive_form_data(request: Request):
|
132 |
+
form_data = await request.json()
|
133 |
+
|
134 |
+
# Generate a unique ID (for tracking user)
|
135 |
+
unique_id = str(uuid.uuid4())
|
136 |
+
|
137 |
+
# Here you can do something with form_data like saving it to a database
|
138 |
+
print("Received form data:", form_data)
|
139 |
+
|
140 |
+
# Send back the unique id to the frontend
|
141 |
+
return JSONResponse({"id": unique_id})
|
142 |
|
143 |
@app.post("/chat/")
|
144 |
async def chat(request: MessageRequest):
|
|
|
152 |
}
|
153 |
chat_history.append(message_data)
|
154 |
return {"response": response}
|
155 |
+
@app.get("/")
|
156 |
+
def read_root():
|
157 |
+
return {"message": "Welcome to the API"}
|
158 |
+
|
159 |
|
160 |
|