Update app.py

app.py

@@ -1,44 +1,44 @@
-from fastapi import FastAPI, UploadFile, File
-from typing import List
-import chromadb
-
-app = FastAPI(title="Eroha AgentAPI", version="2.1.1")
-
-client = chromadb.Client()
-collection = client.get_or_create_collection("eroha_docs")
-
-embedder = None
-summarizer = None
-
-@app.get("/")
-def home():
-    return {
-        "message": "Eroha AgentAPI is alive!",
-        "routes": ["/check", "/summarize"]
-    }
-
-@app.get("/check")
-def check_health():
-    return {
-        "status": "ok",
-        "version": "2.1.1",
-        "components": ["lazy embedding", "lazy summarizer"]
-    }
-
-@app.post("/summarize")
-async def summarize_text(files: List[UploadFile] = File(...)):
-    global embedder, summarizer
-    if embedder is None or summarizer is None:
-        from sentence_transformers import SentenceTransformer
-        from transformers import pipeline
-        embedder = SentenceTransformer("all-MiniLM-L6-v2")
-        summarizer = pipeline("text2text-generation", model="google/flan-t5-base")
-
-    texts = []
-    for file in files:
-        content = await file.read()
-        texts.append(content.decode("utf-8"))
-
-    full_text = "\n".join(texts)
-    summary = summarizer(full_text, max_length=150, min_length=40, do_sample=False)
+from fastapi import FastAPI, UploadFile, File
+from typing import List
+import chromadb
+
+app = FastAPI(title="Eroha AgentAPI", version="2.1.1")
+
+client = chromadb.Client()
+collection = client.get_or_create_collection("eroha_docs")
+
+embedder = None
+summarizer = None
+
+@app.get("/")
+def home():
+    return {
+        "message": "Eroha AgentAPI is alive!",
+        "routes": ["/check", "/summarize"]
+    }
+
+@app.get("/check")
+def check_health():
+    return {
+        "status": "ok",
+        "version": "2.1.1",
+        "components": ["lazy embedding", "lazy summarizer"]
+    }
+
+@app.post("/summarize")
+async def summarize_text(files: List[UploadFile] = File(...)):
+    global embedder, summarizer
+    if embedder is None or summarizer is None:
+        from sentence_transformers import SentenceTransformer
+        from transformers import pipeline
+        embedder = SentenceTransformer("all-MiniLM-L6-v2")
+        summarizer = pipeline("text2text-generation", model="google/flan-t5-base")
+
+    texts = []
+    for file in files:
+        content = await file.read()
+        texts.append(content.decode("utf-8"))
+
+    full_text = "\n".join(texts)
+    summary = summarizer(full_text, max_length=150, min_length=40, do_sample=False)
     return {"summary": summary[0]["generated_text"]}