Rename appmod.py to app.py

appmod.py → app.py

@@ -1,30 +1,30 @@
-from fastapi import FastAPI, Query
-from transformers import pipeline
-
-app = FastAPI()
-
-def initialize_pipeline():
-    return pipeline("text2text-generation", model="google/flan-t5-small")
-
-pipe = initialize_pipeline()
-
-@app.get("/")
-def home():
-    return {"message": "Hello Siddhant"}
-
-@app.get("/generate")
-def generate_text(
-    text: str = Query(None, description="Input text to generate from"),
-    prompt: str = Query(None, description="Optional prompt for fine-tuning the generated text"),
-):
-    if not text and not prompt:
-        return {"error": "Please provide either 'text' or 'prompt' parameter."}
-
-    if prompt:
-        input_text = f"{text} {prompt}" if text else prompt
-    else:
-        input_text = text
-
-    output = pipe(input_text, max_length=100, do_sample=True, top_k=50)
-
-    return {"input_text": input_text, "output": output[0]["generated_text"]}
+from fastapi import FastAPI, Query
+from transformers import pipeline
+
+app = FastAPI()
+
+def initialize_pipeline():
+    return pipeline("text-classification", model="FacebookAI/roberta-large-mnli")
+
+pipe = initialize_pipeline()
+
+# @app.get("/docs")
+# def home():
+#     return {"message": "Hello Siddhant"}
+
+@app.get("/")
+def generate_text(
+    text: str = Query(None, description="Input text to generate from"),
+    prompt: str = Query(None, description="Optional prompt for fine-tuning the generated text"),
+):
+    if not text and not prompt:
+        return {"error": "Please provide either 'text' or 'prompt' parameter."}
+
+    if prompt:
+        input_text = f"{text} {prompt}" if text else prompt
+    else:
+        input_text = text
+
+    output = pipe(input_text, max_length=100, do_sample=True, top_k=50)
+
+    return {"input_text": input_text, "output": output[0]["generated_text"]}