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a10a6c0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from typing import List, Optional, Dict
import os
import json
from datetime import datetime
from langchain_core.messages import HumanMessage, AIMessage
from socratic_graph import learner_app, get_resources, get_text_content
from ingest import process_new_files
import shutil
from fastapi import UploadFile, File
from fastapi.staticfiles import StaticFiles
app = FastAPI()
# Enable CORS for React development
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # In production, restrict this to your frontend URL
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# --- MODELS ---
class Message(BaseModel):
role: str # "user" or "assistant"
content: str
class ChatRequest(BaseModel):
messages: List[Message]
grade: str
subject: str
topic: str
hint_level: int
status: str
class ChatResponse(BaseModel):
message: Message
hint_level: int
status: str
context: str
# --- UTILS ---
def convert_to_langchain(messages: List[Message]):
lc_messages = []
for m in messages:
if m.role == "user":
lc_messages.append(HumanMessage(content=m.content))
else:
lc_messages.append(AIMessage(content=m.content))
return lc_messages
# --- ENDPOINTS ---
@app.get("/api/curriculum")
async def get_curriculum():
try:
vector_store = get_resources()
all_data = vector_store.get(include=['metadatas'])
metadatas = all_data['metadatas']
options = {}
for meta in metadatas:
grade = meta.get('grade', 'Unknown')
subject = meta.get('subject', 'Unknown')
topics_str = meta.get('topics', 'General')
if grade not in options: options[grade] = {}
if subject not in options[grade]: options[grade][subject] = set()
t_list = [t.strip().title() for t in topics_str.split(',') if t.strip()]
for t in t_list:
options[grade][subject].add(t)
# Convert sets to sorted lists
final_options = {}
for g in options:
final_options[g] = {}
for s in options[g]:
final_options[g][s] = sorted(list(options[g][s]))
return final_options
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/chat", response_model=ChatResponse)
async def chat(request: ChatRequest):
try:
lc_messages = convert_to_langchain(request.messages)
initial_state = {
"messages": lc_messages,
"hint_level": request.hint_level,
"context": "",
"status": request.status,
"safety_status": "PASS",
"current_topic": request.topic,
"grade": request.grade,
"subject": request.subject,
"selected_topic": request.topic
}
final_state = await learner_app.ainvoke(initial_state)
response_msg = final_state["messages"][-1]
response_text = get_text_content(response_msg.content)
# Log for evaluation (consistent with app.py logic)
log_entry = {
"question": request.messages[-1].content if request.messages else "",
"answer": response_text,
"contexts": [final_state.get("context", "")],
"timestamp": datetime.now().isoformat()
}
with open("eval_logs.jsonl", "a", encoding="utf-8") as f:
f.write(json.dumps(log_entry) + "\n")
return ChatResponse(
message=Message(role="assistant", content=response_text),
hint_level=final_state["hint_level"],
status=final_state["status"],
context=final_state.get("context", "")
)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/ingest")
async def ingest():
try:
result = process_new_files()
return {"status": "success", "message": result}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/upload")
async def upload_file(grade: str, subject: str, file: UploadFile = File(...)):
try:
# Create directory structure: data/Grade/Subject/
target_dir = os.path.join("data", grade, subject)
os.makedirs(target_dir, exist_ok=True)
file_path = os.path.join(target_dir, file.filename)
with open(file_path, "wb") as buffer:
shutil.copyfileobj(file.file, buffer)
return {"status": "success", "filename": file.filename}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# Mount the React production build output directory if it exists
frontend_dist_dir = os.path.join(os.path.dirname(__file__), "frontend", "dist")
if os.path.exists(frontend_dist_dir):
app.mount("/", StaticFiles(directory=frontend_dist_dir, html=True), name="static")
else:
# Optional fallback or message
print("Warning: frontend/dist directory not found. Static files will not be served.")
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
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