Add tabs & tab for panel discussion

app.py

@@ -4,13 +4,15 @@ import streamlit as st
 from ring import LLM_GPT35
 from ring import LLM_GPT4
 from ring import LLM_LLAMA2
+from ring import PREF_ORDER_LLMS
+
 
 from ring import requires_openai_key
 from ring import get_openai_api_key
 from ring import generate_response
+from ring import generate_panel_response
 
-
-__version__ = '0.1.4'
+__version__ = '0.1.5'
 
 col1, col2 = st.columns([3, 1])
 
@@ -19,23 +21,50 @@ with col1:
     st.markdown("**OpenWorm LLM v%s** - work in progress!"%__version__)
 
 with col2:
-   st.image("images/OpenWormLogo.png")
+    st.image("images/OpenWormLogo.png")
+
+tab_free, tab_panel, tab_pubs = st.tabs(["Individual LLMs", "Panel discussion", "Publications"])
+
+
+with tab_free:
+
+    st.markdown("**Ask individual LLMs questions**")
+
+    with st.form("form_free"):
+        
+        text = st.text_area("Ask a question related to _C. elegans_:", "What is the primary role of the C. elegans neuron AVBL?")
+
+        llm_ver = st.selectbox('Which LLM version should I use?', PREF_ORDER_LLMS)
+
+        temperature = st.text_input("Temperature", value=0.1)
+
+        submitted = st.form_submit_button("Submit")
+
+        if requires_openai_key(llm_ver) and not get_openai_api_key():
+            st.info("Please add your OpenAI API key to continue.")
+        elif submitted:
+            response = generate_response(text, llm_ver, temperature)
 
-openai_api_key = None
+            st.info(response)
 
+with tab_panel:
 
+    st.markdown("**Get a consensus answer across multiple LLMs**")
 
-with st.form("my_form"):
-    text = st.text_area("Ask a question related to _C. elegans_:", "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))
+    with st.form("form_panel"):
+        
+        text = st.text_area("Ask a question related to _C. elegans_:", "What is the typical length of the worm C. elegans?")
 
-    temperature = st.text_input("Temperature", value=0.1)
+        temperature = st.text_input("Temperature", value=0.1)
 
-    submitted = st.form_submit_button("Submit")
+        submitted = st.form_submit_button("Submit")
 
-    if requires_openai_key(llm_ver) and not get_openai_api_key():
-        st.info("Please add your OpenAI API key to continue.")
-    elif submitted:
-        response = generate_response(text, llm_ver, temperature)
+        if requires_openai_key(llm_ver) and not get_openai_api_key():
+            st.info("Please add your OpenAI API key to continue.")
+        elif submitted:
+            response = generate_panel_response(text, 
+                                               llm_panelists = [LLM_GPT35, LLM_LLAMA2],
+                                               llm_panel_chair = LLM_GPT4,
+                                               temperature=temperature)
 
-        st.info(response)
+            st.info(response)

ring.py

@@ -13,6 +13,8 @@ LLM_LLAMA2 = 'LLAMA2'
 
 OPENAI_LLMS = [LLM_GPT35, LLM_GPT4]
 
+PREF_ORDER_LLMS = (LLM_LLAMA2, LLM_GPT35, LLM_GPT4)
+
 def requires_openai_key(llm_ver):
 
     return llm_ver in OPENAI_LLMS
@@ -35,21 +37,8 @@ def get_llamaapi_key():
 
     return llamaapi_key
 
+def get_llm(llm_ver, temperature):
 
-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 don't answer the question, but instead explain 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())
 
@@ -73,6 +62,23 @@ def generate_response(input_text, llm_ver, temperature):
 
         llm = ChatLlamaAPI(client=llama)
 
+    return llm
+
+GENERAL_QUERY_PROMPT_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 don't answer the question, but instead explain that you 
+    can currently only answer questions related to C. elegans. Question: {question}
+
+    Answer: """
+
+def generate_response(input_text, llm_ver, temperature):
+
+    prompt = PromptTemplate(
+            template=GENERAL_QUERY_PROMPT_TEMPLATE,
+            input_variables=['question']
+    )
+    
+    llm = get_llm(llm_ver, temperature)
+
     llm_chain = LLMChain(
         prompt=prompt,
         llm=llm
@@ -81,3 +87,71 @@ def generate_response(input_text, llm_ver, temperature):
     response = llm_chain.invoke(input_text)['text']
         
     return response
+
+
+
+def generate_panel_response(input_text, llm_panelists, llm_panel_chair, temperature):
+
+    responses = {}
+
+    for llm_ver in llm_panelists:
+
+        prompt = PromptTemplate(
+                template=GENERAL_QUERY_PROMPT_TEMPLATE,
+                input_variables=['question']
+        )
+
+        llm = get_llm(llm_ver, temperature)
+
+        llm_chain = LLMChain(
+            prompt=prompt,
+            llm=llm
+        )
+        responses[llm_ver] = llm_chain.invoke(input_text)['text']
+
+    panel_chair_prompt = """You are a neuroscientist chairing a panel discussion on the nematode C. elegans. A researcher has asked the following question:
+    {question}
+    and %i experts on the panel have give their answers. 
+    """%(len(llm_panelists))
+
+    for llm_ver in llm_panelists:
+        panel_chair_prompt += """
+The panelist named Dr. %s has provided the answer: %s
+""" % (llm_ver, responses[llm_ver])
+
+    panel_chair_prompt += """
+Please generate a brief answer to the researcher's question based on their responses, pointing out where there is any inconsistency""" +\
+    """ in their answers, and using your own knowledge of C. elegans to try to resolve it.""" 
+
+    print(panel_chair_prompt)
+
+    prompt = PromptTemplate(
+            template=panel_chair_prompt,
+            input_variables=['question']
+    )
+
+    llm = get_llm(llm_panel_chair, temperature)
+
+    llm_chain = LLMChain(
+        prompt=prompt,
+        llm=llm
+    )
+    response_chair = llm_chain.invoke(input_text)['text']
+
+    response = '''**%s**: %s''' % (llm_panel_chair, response_chair)
+
+    response += '''
+
+-----------------------------------
+_Individual responses:_
+
+'''
+    for llm_ver in responses:
+        response += '''
+_**%s**:_ _%s_
+''' %(llm_ver, responses[llm_ver].strip().replace('\n',' '))
+
+
+        
+    return response
+