Update app.py

app.py

@@ -1,10 +1,13 @@
-#Importing required packages
+# Importing required packages
 import streamlit as st
-import anthropic
 import uuid
+from huggingface_hub import InferenceClient
+
+# Initialize the HuggingFace inference client
+client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta", token=st.secrets["HUGGINGFACE_API_KEY"])
 
 INIT_PROMPT = """
-\n\nHuman: You are MapMentor a trainer in Wardley Mapping. You will help the users learn about Wardley Mapping
+\n\nHuman: You are DarijaBot, a helpful assistant that can converse in both Latin and Arabic alphabet Darija. You will help the users learn about Wardley Mapping.
 """
 
 TRAINING_PROMPT = """
@@ -12,40 +15,34 @@ Here is an outline for a training course that you will give to the user. It cove
 """
 
 INTRO_PROMPT = """
-Hello, I'm DarijaBot 
-
+Hello, I'm DarijaBot! I can help you with your questions about Wardley Mapping in Darija. You can type in either Latin or Arabic script.
 """
 
 REG_PROMPT = """
-\n\nHuman: Here is the user's question about Wardley Mapping:
+\n\nHuman: Here is the user's question in Darija:
 <question>
 {QUESTION}
 </question>
-\n\nAssistant: [MapMentor] <response>
+\n\nAssistant: [DarijaBot] <response>
 """
 
-MODEL = "claude-3-5-sonnet-20240620"
-
 new_prompt = []
 
 if "session_id" not in st.session_state:
     st.session_state.session_id = str(uuid.uuid4())
 
-st.set_page_config(page_title="Anthropic - ChatBot")
-st.sidebar.title("Anthropic - ChatBot")
+st.set_page_config(page_title="DarijaBot - ChatBot")
+st.sidebar.title("DarijaBot - ChatBot")
 st.sidebar.title("Wardley Mapping Mentor")
 st.sidebar.divider()
-st.sidebar.markdown("Developed by Bahae Eddine HALIM](https://linkedin.com/in/halimbahae)", unsafe_allow_html=True)
+st.sidebar.markdown("Developed by [Bahae Eddine HALIM](https://linkedin.com/in/halimbahae)", unsafe_allow_html=True)
 st.sidebar.markdown("Current Version: 0.0.4")
-st.sidebar.markdown("Using claude-2 API")
+st.sidebar.markdown("Using HuggingFaceH4/zephyr-7b-beta API")
 st.sidebar.markdown(st.session_state.session_id)
 st.sidebar.divider()
 
 # Check if the user has provided an API key, otherwise default to the secret
-user_claude_api_key = st.sidebar.text_input("Enter your Anthropic API Key:", placeholder="sk-...", type="password")
-
-if "claude_model" not in st.session_state:
-    st.session_state["claude_model"] = MODEL
+user_huggingface_api_key = st.sidebar.text_input("Enter your HuggingFace API Key:", placeholder="hf_...", type="password")
 
 if "messages" not in st.session_state:
     st.session_state["messages"] = []
@@ -54,14 +51,10 @@ if "messages" not in st.session_state:
 if "all_prompts" not in st.session_state:
     st.session_state["all_prompts"] = INIT_PROMPT + TRAINING_PROMPT
 
-if user_claude_api_key:
-    # If the user has provided an API key, use it
-    client=anthropic.Anthropic(
-      # defaults to os.environ.get("ANTHROPIC_API_KEY")
-      api_key=user_claude_api_key,
-    )
+if user_huggingface_api_key:
+    client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta", token=user_huggingface_api_key)
 else:
-    st.warning("Please enter your Anthropic Claude API key", icon="⚠️")
+    st.warning("Please enter your HuggingFace API key", icon="⚠️")
 
 for message in st.session_state.messages:
     if message["role"] in ["user", "assistant"]:
@@ -69,9 +62,9 @@ for message in st.session_state.messages:
             new_prompt.append(message["content"])
             st.markdown(message["content"])
 
-if user_claude_api_key:
-    if user_input := st.chat_input("How can I help with Wardley Mapping?"):
-        prompt = REG_PROMPT.format(QUESTION = user_input)
+if user_huggingface_api_key:
+    if user_input := st.chat_input("How can I help with Wardley Mapping? (Darija: Latin or Arabic script)"):
+        prompt = REG_PROMPT.format(QUESTION=user_input)
         st.session_state.all_prompts += prompt
         st.session_state.messages.append({"role": "user", "content": user_input})
         with st.chat_message("user"):
@@ -80,24 +73,16 @@ if user_claude_api_key:
             message_placeholder = st.empty()
         full_response = ""
         try:
-            for response in client.completions.create(
-                prompt=st.session_state.all_prompts,
-                stop_sequences=["</response>"],
-                model=MODEL,
-                max_tokens_to_sample=500,
-                stream=True,
-            ):
-                full_response += response.completion
-                message_placeholder.markdown(full_response + "▌")
+            response = client.chat_completion(
+                [{"role": "system", "content": "You are DarijaBot, a helpful assistant that can converse in both Latin and Arabic alphabet Darija."}, {"role": "user", "content": user_input}],
+                max_tokens=512,
+                temperature=0.7,
+                top_p=0.95
+            ).choices[0].message.content
+            full_response += response
+            message_placeholder.markdown(full_response + "▌")
             message_placeholder.markdown(full_response)
-        except anthropic.APIConnectionError as e:
-            st.error("The server could not be reached")
-            print(e.__cause__)  # an underlying Exception, likely raised within httpx.
-        except anthropic.RateLimitError as e:
-            st.error("A 429 status code was received; we should back off a bit.")
-        except anthropic.APIStatusError as e:
-            st.error("Another non-200-range status code was received\nTry again later.")
-            st.error(e.status_code)
-            st.error(e.response)
+        except Exception as e:
+            st.error(f"Error: Unable to fetch response from the API.\nDetails: {e}")
         st.session_state.messages.append({"role": "assistant", "content": full_response})
         st.session_state.all_prompts += full_response