Update app.py

app.py

@@ -26,10 +26,18 @@ from langchain.chat_models import ChatOpenAI
 from langchain.document_loaders import PyPDFLoader
 from langchain.chains.question_answering import load_qa_chain
 
+import generativeai as gen
+
+
+
+
 # turned off due to people using it unethical ways
 openai.api_key = os.environ['openai_key']
 os.environ["OPENAI_API_KEY"] = os.environ['openai_key']
 
+gemini.api_key = os.environ['gemini_key']
+os.environ["GEMINI_API_KEY"] = os.environ['gemini_key']
+
 
 prompt_templates = {"All Needs Experts": "Respond as if you are combination of all needs assessment experts."}
 actor_description = {"All Needs Experts": "<div style='float: left;margin: 0px 5px 0px 5px;'><img src='https://na.weshareresearch.com/wp-content/uploads/2023/04/experts2.jpg' alt='needs expert image' style='width:70px;align:top;'></div>A combiation of all needs assessment experts."}
@@ -86,6 +94,7 @@ def on_prompt_template_change_description(prompt_template):
 
 
 
+
 def submit_message(prompt, prompt_template, temperature, max_tokens, context_length, state):
     
     
@@ -102,6 +111,79 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
             {"prompt": str(prompt), "time": str(datetime.now())}
         )
     
+
+    system_prompt = []
+    if prompt_template:
+        system_prompt = [{ "role": "system", "content": prompt_template }]
+
+    prompt_msg = { "role": "user", "content": prompt }
+
+
+    #try:
+
+    with open("embeddings.pkl", 'rb') as f: 
+        new_docsearch = pickle.load(f)
+        
+
+    query = str(system_prompt + history +  [prompt_msg])
+    
+    docs = new_docsearch.similarity_search(query)
+
+    gen_ai = GenerativeAI.get_client(model="gemini-1.0-pro")
+    response = gen_ai.start_chat(
+        messages=query,  # Pass both history and current prompt
+        max_tokens=max_tokens,
+        temperature=temperature  # Adjust temperature as needed
+    )
+
+    completion = response.messages[-1]  # Extract the completion message
+
+    
+    get_empty_state()
+    state['content'] = completion
+    #state.append(completion.copy())
+    
+    completion = { "content": completion }
+    
+    
+    #state['total_tokens'] += completion['usage']['total_tokens']
+
+
+    
+    #except Exception as e:
+    #    history.append(prompt_msg.copy())
+    #    error  = {
+    #        "role": "system",
+    #        "content": f"Error: {e}"
+    #    }
+    #    history.append(error.copy())
+
+    #total_tokens_used_msg = f"Total tokens used: {state['total_tokens']}"
+
+    chat_messages = [(prompt_msg['content'], completion['content'])]    
+    return '', chat_messages,  state    # total_tokens_used_msg,
+
+
+
+
+
+
+def submit_message_OLD(prompt, prompt_template, temperature, max_tokens, context_length, state):
+    
+    
+    history = state['messages']
+
+    if not prompt:
+        return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], state
+    
+    prompt_template = prompt_templates[prompt_template]
+
+    with open("prompts_archive.csv", "a") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=["prompt", "time"])
+        writer.writerow(
+            {"prompt": str(prompt), "time": str(datetime.now())}
+        )
+    
    # with open(prompts_archive_file, "a") as csvfile:
    #     writer = csv.DictWriter(csvfile, fieldnames=["prompt", "time"])
    #     writer.writerow(