Upload 3 files

app.py

@@ -14,17 +14,21 @@ from llama_index.llms.openai import OpenAI
 from llama_index.core.tools import QueryEngineTool, ToolMetadata
 from llama_index.core.utils import print_text
 from llama_index.core.agent.react.formatter import ReActChatFormatter
+
+from llama_index.core.agent import ReActAgent
+from llama_index.agent.openai import OpenAIAgent
 from llama_index.core.tools import FunctionTool
 
+
 from prompts import prompt_template
 
-learning_styles = ['traditional', 'Inquiry-based', 'Socratic']
+teaching_styles = ['traditional', 'Inquiry-based', 'Socratic']
 languages = {'English': 'en', 'Spanish': 'es', 'French': 'fr', 'German': 'de', 'Arabic': 'ar', 'Chinese': 'zh-cn', 
              'Hebrew': 'he', 'Hindi': 'hi', 'Italian': 'it', 'Japanese': 'ja', 'Korean': 'ko', 'Portuguese': 'pt'}
 initial_prompt = "How can I help you today?"
 
 
-def launch_bot():
+def launch_bot(agent_type: str):
     def reset():
         cfg = st.session_state.cfg
         llm = OpenAI(model="gpt-4o", temperature=0)        
@@ -79,12 +83,19 @@ def launch_bot():
         prompt = prompt_template.replace("{style}", cfg.style) \
                                 .replace("{language}", cfg.language) \
                                 .replace("{student_age}", str(cfg.student_age))
-        
-        st.session_state.agent = ReActAgent.from_tools(
-            tools=[vectara_tool, rephrase_tool], llm=llm, 
-            verbose=True,
-            react_chat_formatter = ReActChatFormatter(system_header=prompt)
-        )
+        tools = [vectara_tool, rephrase_tool]
+        if agent_type == 'react':
+            st.session_state.agent = ReActAgent.from_tools(
+                tools=tools, llm=llm, verbose=True,
+                react_chat_formatter = ReActChatFormatter(system_header=prompt),
+                max_iterations = 20,
+            )
+        elif agent_type == 'openai':
+            st.session_state.agent = OpenAIAgent.from_tools(
+                tools=tools, llm=llm, verbose=True,
+                system_prompt=prompt)
+        else:
+            raise ValueError(f"Unknown agent type: {agent_type}")        
 
 
     if 'cfg' not in st.session_state:
@@ -92,7 +103,7 @@ def launch_bot():
             'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']),
             'corpus_id': str(os.environ['VECTARA_CORPUS_ID']),
             'api_key': str(os.environ['VECTARA_API_KEY']),
-            'style': learning_styles[0],
+            'style': teaching_styles[0],
             'language': 'English',
             'student_age': 18
         })
@@ -112,7 +123,7 @@ def launch_bot():
         st.markdown("## Welcome to the Justice Harvard e-learning assistant demo.\n\n\n")
 
         st.markdown("\n")
-        cfg.style = st.selectbox('Learning Style:', learning_styles)
+        cfg.style = st.selectbox('Teacher Style:', teaching_styles)
         if st.session_state.style != cfg.style:
             st.session_state.style = cfg.style
             reset()
@@ -173,5 +184,6 @@ def launch_bot():
     sys.stdout.flush()
 
 if __name__ == "__main__":
-    launch_bot()
+    print("Starting up...")
+    launch_bot(agent_type = 'openai')
     

prompts.py

@@ -63,6 +63,7 @@ Answer: Sorry, I cannot answer your question.
 
 ADDITIONAL INSTRUCTIONS:
 - When using a tool, break down complex questions into a set of shorter questions, and ask the tool about each of them.
+- If a tool does not respond with a clear answer or cannot answer the query properly, try to rephrase your query or break it down into sub-queries to help it respond properly.
 - You must make at least one use of a tool for each question before responding.
 - Make sure your response relies on the tools you have used and the information from those tools. 
 - Do not base your response on information that was not provided by the tools.

requirements.txt

@@ -6,4 +6,5 @@ streamlit==1.32.2
 translate==3.6.1
 llama-index==0.10.42
 llama-index-indices-managed-vectara==0.1.4
+llama-index-agent-openai==0.1.5
 pydantic==1.10.15