Adding the ability to conversate with the trip itinerary

app.py

@@ -15,17 +15,44 @@ from typing import List, Tuple
 
 import gradio as gr
 import plotly.graph_objects as go
+import os
+import openai
 
 from crew import AddressSummaryCrew, TravelCrew
 from db import log_query
 from fpdf import FPDF
 
-def export_pdf(input_text:str):
+client = openai.OpenAI(
+    api_key=os.environ.get("SAMBANOVA_API_KEY"),
+    base_url="https://api.sambanova.ai/v1",
+)
+
+def start_chat(context):
+    return gr.Chatbot(visible=True), gr.Textbox(visible=True), context
+
+def respond(message, chat_history, context, model="Meta-Llama-3.1-70B-Instruct"):
+    # Simple response incorporating context
+    response = client.chat.completions.create(
+                   model=model,
+                   messages=[{"role":"system",
+                              "content":"You are a helpful assistant"},
+                             {"role": "user",
+                              "content": "Here is a trip itinerary: %s. Please answer the specific question asked by the user. %s " % (message, context)}],
+                   temperature=0.1,
+                   top_p=0.1
+                )
+    result = response.choices[0].message.content
+    bot_message = result
+    chat_history.append((message, bot_message))
+    return "", chat_history
+
+def export_pdf(input_text:str, input_chat:str):
     """
     Create a downloadable pdf for the given input text
 
     Args:
          input_text: The text that needs to be made a pdf
+         input_chat: Chat messages
 
     Result:
          Downloadable pdf
@@ -46,6 +73,21 @@ def export_pdf(input_text:str):
             pdf.set_font("Arial", size=12, style='')
         else:
             pdf.multi_cell(0, 5, clean_line)
+
+    pdf.ln()
+    for conversation in input_chat:
+        counter = 0
+        for line in conversation:
+            clean_line = line.strip()
+            if clean_line:
+                if counter == 0:
+                    pdf.ln()
+                    pdf.set_font("Arial", size=12, style='I')
+                    counter += 1
+                else:
+                    pdf.set_font("Arial", size=12, style='')
+                pdf.multi_cell(0, 5, clean_line)
+
     pdf.output(file_name).encode('latin-1')
     return file_name
 
@@ -140,7 +182,12 @@ def run(
         'children': children,
         'budget': budget,
     }
-    result = TravelCrew(model_name).crew().kickoff(inputs=user_preferences)
+    #result = TravelCrew(model_name).crew().kickoff(inputs=user_preferences)
+    crew = TravelCrew(model_name).crew()
+    result = crew.kickoff(inputs=user_preferences)
+    metrics = crew.usage_metrics
+    logger.info("Result Metrics")
+    logger.info(metrics)
 
     """
         Now we will pass the result to a address summary crew whose job is to extract position
@@ -185,6 +232,8 @@ logger.setLevel(logging.INFO)
 with gr.Blocks() as demo:
     gr.Markdown('Use this app to create a detailed itinerary on how to explore a new place.'
                 ' Itinerary is customized to your taste. Powered by Sambanova Cloud.')
+    # Store context between interactions
+    context = gr.State()
     with gr.Row():
         with gr.Column(scale=1):
             inp_source = gr.Textbox(label='Where are you travelling from?')
@@ -227,24 +276,53 @@ with gr.Blocks() as demo:
                label='Total budget of trip in USD', show_label=True, value=1000, minimum=500, maximum=10000, step=500
             )
             inp_model = gr.Textbox(value="Meta-Llama-3.1-70B-Instruct", label='Sambanova Model Name')
-            button = gr.Button("Plan your Trip")
-            inputs = [inp_source, inp_dest, inp_cal, inp_age, inp_days, inp_interests, inp_cuisine, inp_children, inp_budget, inp_model]
+            plan_button = gr.Button("Plan your Trip")
+        inputs = [inp_source, inp_dest, inp_cal, inp_age, inp_days, inp_interests, inp_cuisine, inp_children, inp_budget, inp_model]
 
         with gr.Column(scale=2):
-            output_itinerary =\
-            gr.Textbox(
-                label='Complete Personalized Itinerary of your Trip',
-                show_label=True,
-                show_copy_button=True,
-                autoscroll=False,
-            )
+            with gr.Row():
+                output_itinerary =\
+                gr.Textbox(
+                    label='Complete Personalized Itinerary of your Trip',
+                    show_label=True,
+                    show_copy_button=True,
+                    autoscroll=False,
+                )
+
+            # Chat interface (hidden initially)
+            with gr.Row(visible=False) as chat_interface:
+                chatbot = gr.Chatbot()
+                input_msg = gr.Textbox()
+
+            # Chat controls
+            start_chat_btn = gr.Button("Start Chat", visible=False)
+
+            # Download button
             download_btn = gr.Button("Download Itinerary")
 
             output_map = gr.Plot(label='Venues on a Map. Please verify with a Navigation System before traveling.')
             output = [output_itinerary, output_map]
 
-            button.click(fn=run, inputs=inputs, outputs=output)
-            download_btn_hidden = gr.DownloadButton(visible=False, elem_id="download_btn_hidden")
-            download_btn.click(fn=export_pdf, inputs=output_itinerary, outputs=[download_btn_hidden]).then(fn=None, inputs=None, outputs=None, js="() => document.querySelector('#download_btn_hidden').click()")
+    plan_button.click(fn=run, inputs=inputs, outputs=output).then(
+                          lambda: gr.Button(visible=True),
+                          outputs=start_chat_btn)
+
+    download_btn_hidden = gr.DownloadButton(visible=False, elem_id="download_btn_hidden")
+    download_btn.click(fn=export_pdf, inputs=[output_itinerary, chatbot], outputs=[download_btn_hidden]).then(fn=None, inputs=None, outputs=None, js="() => document.querySelector('#download_btn_hidden').click()")
+
+    start_chat_btn.click(
+        start_chat,
+        inputs=output_itinerary,
+        outputs=[chatbot, input_msg, context]
+    ).then(
+        lambda: gr.Row(visible=True),
+        outputs=chat_interface
+    )
+
+    input_msg.submit(
+        respond,
+        inputs=[input_msg, chatbot, context, inp_model],
+        outputs=[input_msg, chatbot]
+    )
 
 demo.launch()

config/tasks.yaml

@@ -5,6 +5,7 @@ personalized_activity_planning_task:
     Also map the date to the day of the week and check if the activity you are recommending in open on that day of the week.
     Focus on activities and events that match the traveler's interests and age group.
     Utilize internet search tools and recommendation engines to gather the information.
+    If you are including a hotel for staying, please provide a link to make a booking at the hotel.
 
     Traveler's information:
 
@@ -39,6 +40,7 @@ restaurant_scenic_location_scout_task:
     Use internet search tools, restaurant review sites, and travel guides.
     Make sure to find a variety of options to suit different tastes and budgets, and ratings for them.
     Extract the address of he restaurant so that the same can be displayed to the user.
+    If it is possible, provide a link to make an online reseravtion at the restaurant.
 
     Traveler's information:
 

crew.py

@@ -20,6 +20,7 @@ class TravelCrew:
         self.agents_config = 'config/agents.yaml'
         self.tasks_config = 'config/tasks.yaml'
         self.llm = LLM(model='sambanova/%s' % model_name)
+        self.manager_llm = LLM(model='sambanova/%s' % model_name)
 
     @typing.no_type_check
     @agent
@@ -131,7 +132,7 @@ class TravelCrew:
     @task
     def itinerary_compilation_task(self) -> Task:
         """
-        A task that plans for museums.
+        A task that plans the complete itinerary
 
         Returns: A task
         """
@@ -153,7 +154,7 @@ class TravelCrew:
         return Crew(
             agents=self.agents,
             tasks=self.tasks,
-            process=Process.sequential,
+            process=Process.sequential
         )