Reestructure app.py

app.py

@@ -12,24 +12,20 @@ from langchain_mistralai import ChatMistralAI
 from langchain_community.document_loaders import WebBaseLoader
 from langchain_core.rate_limiters import InMemoryRateLimiter
 
-# Define a limiter to avoid rate limit issues with MistralAI
-rate_limiter = InMemoryRateLimiter(
-    requests_per_second=0.1,  # <-- MistralAI free. We can only make a request once every second
-    check_every_n_seconds=0.01,  # Wake up every 100 ms to check whether allowed to make a request,
-    max_bucket_size=10,  # Controls the maximum burst size.
-)
+# Load documentation from urls
+def get_docs():
 
-# Get urls
-urlsfile = open("urls.txt")
-urls = urlsfile.readlines()
-urls = [url.replace("\n","") for url in urls]
-urlsfile.close()
+    # Get urls
+    urlsfile = open("urls.txt")
+    urls = urlsfile.readlines()
+    urls = [url.replace("\n","") for url in urls]
+    urlsfile.close()
 
-# Load, chunk and index the contents of the blog.
-loader = WebBaseLoader(urls)
-docs = loader.load()
+    # Load, chunk and index the contents of the blog.
+    loader = WebBaseLoader(urls)
+    docs = loader.load()
 
-print("Pages loaded:",len(docs))
+    return docs
 
 # Join content pages for processing
 def format_docs(docs):
@@ -61,6 +57,17 @@ def RAG(llm, docs, embeddings):
 
     return rag_chain
 
+# Define a limiter to avoid rate limit issues with MistralAI
+rate_limiter = InMemoryRateLimiter(
+    requests_per_second=0.1,  # <-- MistralAI free. We can only make a request once every second
+    check_every_n_seconds=0.01,  # Wake up every 100 ms to check whether allowed to make a request,
+    max_bucket_size=10,  # Controls the maximum burst size.
+)
+
+# Get docs
+docs = get_docs()
+print("Pages loaded:",len(docs))
+
 # LLM model
 llm = ChatMistralAI(model="mistral-large-latest", rate_limiter=rate_limiter)
 
@@ -83,31 +90,34 @@ def handle_prompt(message, history):
     except:
         raise gr.Error("Requests rate limit exceeded")
 
-# Predefined messages and examples
-description = "AI powered assistant which answers any question related to the [CAMELS simulations](https://www.camel-simulations.org/)."
-greetingsmessage = "Hi, I'm the CAMELS DocBot, I'm here to assist you with any question related to the CAMELS simulations."
-example_questions = [
-                    "How can I read a halo file?",
-                    "Which simulation suites are included in CAMELS?",
-                    "Which are the largest volumes in CAMELS simulations?",
-                    "Write a complete snippet of code getting the power spectrum of a simulation"
-                     ]
-
-# Define customized Gradio chatbot
-chatbot = gr.Chatbot([{"role":"assistant", "content":greetingsmessage}],
-                     type="messages",
-                     avatar_images=["ims/userpic.png","ims/camelslogo.jpg"],
-                     height="60vh")
-
-# Define Gradio interface
-demo = gr.ChatInterface(handle_prompt,
+
+if __name__=="__main__":
+
+    # Predefined messages and examples
+    description = "AI powered assistant which answers any question related to the [CAMELS simulations](https://www.camel-simulations.org/)."
+    greetingsmessage = "Hi, I'm the CAMELS DocBot, I'm here to assist you with any question related to the CAMELS simulations."
+    example_questions = [
+                        "How can I read a halo file?",
+                        "Which simulation suites are included in CAMELS?",
+                        "Which are the largest volumes in CAMELS simulations?",
+                        "Write a complete snippet of code getting the power spectrum of a simulation"
+                        ]
+
+    # Define customized Gradio chatbot
+    chatbot = gr.Chatbot([{"role":"assistant", "content":greetingsmessage}],
                         type="messages",
-                        title="CAMELS DocBot",
-                        fill_height=True,
-                        examples=example_questions,
-                        theme=gr.themes.Soft(),
-                        description=description,
-                        cache_examples=False,
-                        chatbot=chatbot)
-
-demo.launch()
+                        avatar_images=["ims/userpic.png","ims/camelslogo.jpg"],
+                        height="60vh")
+
+    # Define Gradio interface
+    demo = gr.ChatInterface(handle_prompt,
+                            type="messages",
+                            title="CAMELS DocBot",
+                            fill_height=True,
+                            examples=example_questions,
+                            theme=gr.themes.Soft(),
+                            description=description,
+                            cache_examples=False,
+                            chatbot=chatbot)
+
+    demo.launch()