assistant wip

app.py

@@ -19,7 +19,6 @@ import openai_utils as oai
 PINECONE_KEY = st.secrets["PINECONE_API_KEY"]  # app.pinecone.io
 OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]  # app.pinecone.io
 PINE_CONE_ENVIRONMENT = st.secrets["PINE_CONE_ENVIRONMENT"]  # app.pinecone.io
-OPENAI_ORGANIZATION_ID = st.secrets["OPENAI_ORGANIZATION_ID"]
 model_name = 'text-embedding-ada-002'
 
 embed = OpenAIEmbeddings(
@@ -51,7 +50,7 @@ def init_models():
     return retriever, tokenizer#, vectorstore
 
 
-st.session_state.openai_client = openai.OpenAI(api_key = OPENAI_API_KEY,organization=OPENAI_ORGANIZATION_ID)
+st.session_state.openai_client = oai.get_client() 
 retriever, tokenizer = init_models()
 #st.session_state.messages = [{"role":"system", "content":"You are an assistant who helps users find startups to invest in."}]
 
@@ -191,6 +190,26 @@ def run_query(query, report_type, top_k , regions, countries, is_debug, index_na
     elif report_type=="company_list":  # or st.session_state.new_conversation:
         results = search_index(query, top_k, regions, countries)
         descriptions = "\n".join([f"Description of company \"{res['name']}\":  {res['data']['Summary']}.\n" for res in results[:20] if 'Summary' in res['data']])
+    elif report_type=="assistant":
+        results = search_index(query, top_k, regions, countries)
+        descriptions = "\n".join([f"Description of company \"{res['name']}\":  {res['data']['Summary']}.\n" for res in results[:20] if 'Summary' in res['data']])
+        ntokens = len(descriptions.split(" "))
+        # prompt = utils.clustering_prompt if report_type=="clustered" else utils.default_prompt
+        # prompt_txt = prompt + """        
+        # User query: {query} 
+        # Company descriptions: {descriptions}
+        # """    
+        # prompt_template = PromptTemplate(template=prompt_txt, input_variables=["descriptions", "query"])
+        # prompt = prompt_template.format(descriptions = descriptions, query = query)
+        #print(f"==============================\nPrompt:\n{prompt[:1000]}\n==============================\n")
+        prompt = query
+        m_text = oai.call_openai(prompt, engine=openai_model, temp=0, top_p=1.0)
+        m_text
+        st.session_state.messages.append({"role": "user", "content": query})
+        i = m_text.find("-----")
+        i = 0 if i<0 else i
+        st.session_state.messages.append({"role": "system", "content": m_text[:i]})
+        
     else:
         st.session_state.new_conversation = False
 
@@ -355,7 +374,8 @@ if utils.check_password():
     with tab_advanced:
         #prompt_title = st.selectbox("Report Type", index = 0, options = utils.get_prompts(), on_change=on_prompt_selected, key="advanced_prompts_select", )
         #prompt_title_editable = st.text_input("Title", key="prompt_title_editable")
-        report_type = st.selectbox(label="Response Type", options=["standard", "guided", "company_list", "clustered"], index=0)
+        report_type = st.selectbox(label="Response Type", options=["assistant", "standard", "guided", "company_list", "clustered"], index=0)
+        assistant_id = st.text_input(label="Assistant ID", key="assistant_id", value="asst_fkZtxo127nxKOCcwrwznuCs2")
         default_prompt = st.text_area("Default Prompt", value = utils.default_prompt, height=400, key="advanced_default_prompt_content")
         clustering_prompt = st.text_area("Clustering Prompt", value = utils.clustering_prompt, height=400, key="advanced_clustering_prompt_content")
         #prompt_new = st.button("New", on_click = _prompt(prompt_title, prompt))
@@ -387,5 +407,8 @@ if utils.check_password():
         #     prompt = "guided"
         # else:
         #     prompt = ""
+        oai.start_conversation()
+        #st.session_state.assistant_id = assistant_id
+        st.session_state.report_type = report_type
         run_query(query, report_type, top_k, region_selectbox, countries_selectbox, is_debug, index_namespace, openai_model)
 

openai_utils.py

@@ -1,24 +1,108 @@
 import time
+import openai
+import requests
 import streamlit as st
 
 
+
+OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]  # app.pinecone.io
+OPENAI_ORGANIZATION_ID = st.secrets["OPENAI_ORGANIZATION_ID"]
+
+
+headers = {"Content-Type": "application/json",
+           "Authorization": f"Bearer {OPENAI_API_KEY}"
+           }
+
+SEED = 42     
+
+def get_client():
+    return openai.OpenAI(api_key = OPENAI_API_KEY,organization=OPENAI_ORGANIZATION_ID)
+
 def call_openai(prompt, engine="gpt-3.5-turbo", temp=0, top_p=1.0, max_tokens=4048):
-    try:
-        response = st.session_state.openai_client.chat.completions.create(
-            model=engine,
-            messages=st.session_state.messages + [{"role": "user", "content": prompt}],
-            temperature=temp,
-            max_tokens=max_tokens
-        )
-        print(f"====================\nOpen AI response\n {response}\n====================\n")
-        text = response.choices[0].message.content.strip()
-        return text
-    except Exception as e:
-    #except openai.error.OpenAIError as e:
-        print(f"An error occurred: {str(e)}")
+    if st.session_state.report_type=="assistant":
+        try:
+            thread = st.session_state.assistant_thread
+            assistant_id = st.session_state.assistant_id
+            message = st.session_state.openai_client.beta.threads.messages.create(
+              thread.id,
+              role="user",
+              content=prompt,
+            )            
+            run = st.session_state.openai_client.beta.threads.runs.create(
+                thread_id=thread.id,
+                assistant_id=assistant_id,
+                instructions="Please address the user as Dan"
+            )
+            messages = []
+            while True:
+                # Retrieve the run status
+                run_status = st.session_state.openai_client.beta.threads.runs.retrieve(
+                    thread_id=thread.id,
+                    run_id=run.id
+                )
+
+                # Check and print the step details
+                run_steps = st.session_state.openai_client.beta.threads.runs.steps.list(
+                    thread_id=thread.id,
+                    run_id=run.id
+                )
+                for step in run_steps.data:
+                    if step.type == 'tool_calls':
+                        print(f"Tool {step.type} invoked.")
+
+                    # If step involves code execution, print the code
+                    if step.type == 'code_interpreter':
+                        print(f"Python Code Executed: {step.step_details['code_interpreter']['input']}")
+
+                if run_status.status == 'completed':
+                    # Retrieve all messages from the thread
+                    messages = st.session_state.openai_client.beta.threads.messages.list(
+                        thread_id=thread.id
+                    ) 
+
+                    # Print all messages from the thread
+                    for msg in messages.data:
+                        role = msg.role
+                        content = msg.content[0].text.value
+                        print(f"{role.capitalize()}: {content}")
+                    break  # Exit the polling loop since the run is complete
+                elif run_status.status in ['queued', 'in_progress']:
+                    print(f'{run_status.status.capitalize()}... Please wait.')
+                    time.sleep(1.5)  # Wait before checking again
+                else:
+                    print(f"Run status: {run_status.status}")
+                    break  # Exit the polling loop if the status is neither 'in_progress' nor 'completed'
+            
+
+            print(f"====================\nOpen AI response\n {messages}\n====================\n")
+            text = ""
+            for message in messages:
+                text = text + "\n" + message.content[0].text.value
+            return text
+        except Exception as e:
+        #except openai.error.OpenAIError as e:
+            print(f"An error occurred: {str(e)}")
+    else:        
+        try:
+            response = st.session_state.openai_client.chat.completions.create(
+                model=engine,
+                messages=st.session_state.messages + [{"role": "user", "content": prompt}],
+                temperature=temp,
+                seed = SEED,
+                max_tokens=max_tokens
+            )
+            print(f"====================\nOpen AI response\n {response}\n====================\n")
+            text = response.choices[0].message.content.strip()
+            return text
+        except Exception as e:
+        #except openai.error.OpenAIError as e:
+            print(f"An error occurred: {str(e)}")
     return "Failed to generate a response."
 
 
+def get_assistant(assistant_id):
+    return st.session_state.openai_client.beta.assistants.retrieve(assistant_id)
+
 def send_message(role, content):
     message = st.session_state.openai_client.beta.threads.messages.create(
         thread_id=st.session_state.assistant_thread.id,

utils.py

@@ -18,11 +18,13 @@ import openai
 #         )    
 
 ###
-     
    
 def check_password():
     """Returns `True` if the user had the correct password."""
 
+    if st.secrets['SKIP_PASSWORD']=="True":
+        return True
+
     def password_entered():
         """Checks whether a password entered by the user is correct."""
         if st.session_state["password"] == st.secrets["password"]: