Restructure

.gitignore

@@ -0,0 +1 @@
+/__pycache__

app.py

@@ -1,103 +1,36 @@
 import streamlit
 import streamlit as st
-from langchain_community.llms import OpenAI
 
-from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain
+from ring import LLM_GPT35
+from ring import LLM_GPT4
+from ring import LLM_LLAMA2
 
-import os
+from ring import requires_openai_key
+from ring import get_openai_api_key
+from ring import generate_response
 
-__version__ = '0.1.3'
 
-LLM_GPT35 = 'GPT3.5'
-LLM_GPT4 = 'GPT4'
-LLM_LLAMA2 = 'LLAMA2'
+__version__ = '0.1.4'
+
 
 st.title("Project Sydney")
 st.text("OpenWorm LLM v%s - work in progress!"%__version__)
 
 openai_api_key = None
 
-with st.sidebar:
-    openai_api_key_sb = st.text_input("OpenAI API Key", type="password")
-    "[Get an OpenAI API key](https://platform.openai.com/account/api-keys)"
-
-
-def get_openai_api_key():
-
-    if openai_api_key_sb == None or len(openai_api_key_sb)==0:
-        openai_api_key = os.environ.get('OPENAI_API_KEY')
-        if openai_api_key==None:
-            openai_api_key = str(open('../oaik','r').readline())
-    else:
-        openai_api_key = openai_api_key_sb
-
-    return openai_api_key
-
-
-def get_llamaapi_key():
-
-    llamaapi_key = os.environ.get('LLAMAAPI_KEY')
-
-    return llamaapi_key
-
-
-def generate_response(input_text, llm_ver, temperature):
-
-    template = """You are a neuroscientist who is answering questions about the worm C. elegans. Provide succinct, yet scientifically accurate
-    answers. If the question is not related to biology, physics or chemistry, then state that you 
-    can currently only answer questions related to C. elegans. Question: {question}
-
-    Answer: """
-
-    
-    prompt = PromptTemplate(
-            template=template,
-        input_variables=['question']
-    )
-    
-    if llm_ver==LLM_GPT35:
-        llm = OpenAI(temperature=temperature, openai_api_key=get_openai_api_key())
-
-    elif llm_ver==LLM_GPT4:
-        from langchain_openai import ChatOpenAI
-        llm = ChatOpenAI(model_name='gpt-4', openai_api_key=get_openai_api_key(), temperature=temperature)
-
-    elif llm_ver==LLM_LLAMA2:
-        from llamaapi import LlamaAPI
-        import asyncio
-
-        # Create a new event loop
-        loop = asyncio.new_event_loop()
-
-        # Set the event loop as the current event loop
-        asyncio.set_event_loop(loop)
-        
-        llama = LlamaAPI(get_llamaapi_key())      
-
-        from langchain_experimental.llms import ChatLlamaAPI
-
-        llm = ChatLlamaAPI(client=llama)
-
-    llm_chain = LLMChain(
-        prompt=prompt,
-        llm=llm
-    )
-
-    response = llm_chain.invoke(input_text)['text']
-        
-    st.info(response)
 
 
 with st.form("my_form"):
-    text = st.text_area("Enter text:", "What is the primary role of the C. elegans neuron ADAL?")
-    llm_ver = st.selectbox('Which LLM version?', (LLM_GPT35, LLM_GPT4, LLM_LLAMA2))
+    text = st.text_area("Enter text:", "What is the primary role of the C. elegans neuron AVBL?")
+    llm_ver = st.selectbox('Which LLM version should I use?', (LLM_GPT35, LLM_GPT4, LLM_LLAMA2))
 
     temperature = st.text_input("Temperature", value=0.1)
 
     submitted = st.form_submit_button("Submit")
 
-    if not get_openai_api_key():
+    if requires_openai_key(llm_ver) and not get_openai_api_key():
         st.info("Please add your OpenAI API key to continue.")
     elif submitted:
-        generate_response(text, llm_ver, temperature)
+        response = generate_response(text, llm_ver, temperature)
+
+        st.info(response)

ring.py

@@ -0,0 +1,83 @@
+
+import os
+
+from langchain_community.llms import OpenAI
+
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+
+
+LLM_GPT35 = 'GPT3.5'
+LLM_GPT4 = 'GPT4'
+LLM_LLAMA2 = 'LLAMA2'
+
+OPENAI_LLMS = [LLM_GPT35, LLM_GPT4]
+
+def requires_openai_key(llm_ver):
+
+    return llm_ver in OPENAI_LLMS
+
+def get_openai_api_key():
+
+    #if openai_api_key_sb == None or len(openai_api_key_sb)==0:
+    openai_api_key = os.environ.get('OPENAI_API_KEY')
+    if openai_api_key==None:
+        openai_api_key = str(open('../oaik','r').readline())
+    #else:
+    #    openai_api_key = openai_api_key_sb
+
+    return openai_api_key
+
+
+def get_llamaapi_key():
+
+    llamaapi_key = os.environ.get('LLAMAAPI_KEY')
+
+    return llamaapi_key
+
+
+def generate_response(input_text, llm_ver, temperature):
+
+    template = """You are a neuroscientist who is answering questions about the worm C. elegans. Provide succinct, yet scientifically accurate
+    answers. If the question is not related to biology, physics or chemistry, then state that you 
+    can currently only answer questions related to C. elegans. Question: {question}
+
+    Answer: """
+
+    
+    prompt = PromptTemplate(
+            template=template,
+        input_variables=['question']
+    )
+    
+    if llm_ver==LLM_GPT35:
+        llm = OpenAI(temperature=temperature, openai_api_key=get_openai_api_key())
+
+    elif llm_ver==LLM_GPT4:
+        from langchain_openai import ChatOpenAI
+        llm = ChatOpenAI(model_name='gpt-4', openai_api_key=get_openai_api_key(), temperature=temperature)
+
+    elif llm_ver==LLM_LLAMA2:
+        from llamaapi import LlamaAPI
+        import asyncio
+
+        # Create a new event loop
+        loop = asyncio.new_event_loop()
+
+        # Set the event loop as the current event loop
+        asyncio.set_event_loop(loop)
+        
+        llama = LlamaAPI(get_llamaapi_key())      
+
+        from langchain_experimental.llms import ChatLlamaAPI
+
+        llm = ChatLlamaAPI(client=llama)
+
+    llm_chain = LLMChain(
+        prompt=prompt,
+        llm=llm
+    )
+
+    response = llm_chain.invoke(input_text)['text']
+        
+    return response