Demo finsihed

app.py

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+import openai
+import gradio as gr
+import pandas as pd
+import tiktoken
+from openai.error import AuthenticationError
+
+encoding = tiktoken.encoding_for_model("gpt-3.5-turbo")
+
+class Bot():
+    def __init__(self):
+        self.car_data = None
+        self.api_key = None
+        self.system_prompt = """You are a salesman in a car dealership. You try to give a detailed answer to the 
+                     questions so that the customer is well advised. Note: If you recommend vehicles, they can only 
+                     be from the csv file provided by the customer. Customer cannot access the csv file himself."""
+        self.lang = "English"
+
+    def process_file(self, file, history):
+        print(file)
+        # throw error if file is not csv
+        if file.name.split(".")[-1] != "csv":
+            if lang == "English":
+                history.append((None, "Please upload a csv file"))
+            else:
+                history.append((None, "Bitte laden Sie eine csv-Datei hoch"))
+            return history
+
+        df = pd.read_csv(file.name)
+        # drop all rows with at least one NaN value
+        df = df.dropna()
+        df = df.drop(columns=["interne_nummer", "ez.1", "kilometer.1", "leistung.1", "leistung", "ez"])
+        # rename column leistung to leistung (kW)
+        # df = df.rename(columns={"leistung": "leistung (kW)"})
+        # df = df.rename(columns={"ez": "Erstzulassung"})
+        df = df.loc[:, ~df.columns.duplicated()]
+
+        # convert csv to text
+        self.car_data = df.to_string(index=False)
+        self.car_data = self.car_data.replace("Car.", "")
+        print(self.car_data)
+        print("Car data token count: ", len(encoding.encode(self.car_data)))
+        if self.api_key:
+            history = []
+        return history
+
+    def run_text(self, history, query):
+        # check api key
+        if not self.api_key:
+            # key must start from "sk-"
+            if not query.startswith("sk-"):
+                if lang == "English":
+                    history.append((None, "Please enter your OpenAI API KEY"))
+                else:
+                    history.append((None, "Bitte geben Sie Ihren OpenAI API-Schlüssel ein"))
+                return history
+            self.api_key = query
+            openai.api_key = query
+            if self.car_data:
+                history = []
+            else:
+                history.append((query, None))
+                if self.lang == "English":
+                    history.append((None, "Please upload a csv file"))
+                else:
+                    history.append((None, "Bitte laden Sie eine csv-Datei hoch"))
+            return history
+
+        if not self.car_data:
+            if self.lang == "English":
+                history.append((None, "Please upload a csv file"))
+            else:
+                history.append((None, "Bitte laden Sie eine csv-Datei hoch"))
+            return history
+
+        # add system message to the front
+        messages = [{"role": "system", "content": self.system_prompt}]
+
+        # add messages from history
+        for q, response in history:
+            if q:
+                messages.append({"role": "user", "content": q})
+            if response:
+                messages.append({"role": "system", "content": response})
+
+        # remove all messages in front of for the first one
+        # if the total number of tokens is greater than 3000
+        total_tokens = self._count_tokens(messages)
+
+        while total_tokens > 1200:
+            messages.pop(1)
+            total_tokens = self._count_tokens(messages)
+
+        # construct prompt from search results
+        if self.lang == "English":
+            prompt = f"""Use the cars in stock below if you need to recommend any vehicles. Only include cars that are in stock
+            and include links to your recommendations. 
+             \n\n Cars in stock: \n {self.car_data} \n\n Query: {query} \n\n Response:"""
+        else:
+            prompt = f"""Verwenden Sie die unten aufgeführten Fahrzeuge, wenn Sie Fahrzeuge empfehlen müssen. 
+            Berücksichtigen Sie nur Fahrzeuge, die auf Lager sind und geben Sie Links zu Ihren Empfehlungen an.
+             \n\n Fahrzeuge auf Lager: \n {self.car_data} \n\n Anfrage: {query} \n\n Antwort:"""
+
+        messages.append({"role": "user", "content": prompt})
+        # print(prompt)
+
+        # generate response
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",  # change to gpt-3.5-turbo if don't have access
+            messages=messages,
+            temperature=0.3,
+        )['choices'][0]['message']['content']
+
+        # only add query and response to history
+        # the context is not needed
+        history.append((query, response))
+
+        return history
+
+    def generate_welcome_message(self):
+        messages = [{"role": "system", "content": self.system_prompt}]
+        try:
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",  # change to gpt-3.5-turbo if don't have access
+                messages=messages,
+                temperature=0.3,
+            )['choices'][0]['message']['content']
+        except AuthenticationError:
+            if self.lang == "English":
+                response = "Wrong API key. Please enter your OpenAI API KEY"
+            else:
+                response = "Falscher API-Schlüssel. Bitte geben Sie Ihren OpenAI API-Schlüssel ein"
+            self.api_key = None
+        return response
+
+    def _count_tokens(self, messages):
+        total_tokens = 0
+        for message in messages:
+            total_tokens += len(encoding.encode(message['content']))
+        return total_tokens
+
+    def change_language(self, lang, history):
+        self.lang = lang
+        if lang == "English":
+            self.system_prompt = """You are a salesman in a car dealership. You try to give a detailed answer to the 
+                     questions so that the customer is well advised. Note: If you recommend vehicles, they can only 
+                     be from the csv file provided by the customer. Customer cannot access the csv file himself."""
+            if not self.api_key:
+                history = [(None, "Please enter your OpenAI API KEY")]
+                return history
+            if not self.car_data:
+                history = [(None, "Please upload a csv file")]
+                return history
+        else:
+            self.system_prompt = """Sie sind ein Verkäufer in einem Autohaus. Sie versuchen, eine detaillierte Antwort auf die
+                     Fragen zu geben, damit der Kunde gut beraten wird. Hinweis: Wenn Sie Fahrzeuge empfehlen, können sie nur
+                     aus der vom Kunden bereitgestellten CSV-Datei stammen. Der Kunde kann die CSV-Datei nicht selbst aufrufen."""
+            if not self.api_key:
+                history = [(None, "Bitte geben Sie Ihren OpenAI API-Schlüssel ein")]
+                return history
+            if not self.car_data:
+                history = [(None, "Bitte laden Sie eine csv-Datei hoch")]
+                return history
+        return []
+
+
+
+
+
+if __name__ == '__main__':
+    bot = Bot()
+    # ui
+    with gr.Blocks(css="#chatbot .overflow-y-auto{height:500px}") as demo:
+        chatbot = gr.Chatbot([(None, "Please enter your OpenAI API KEY")], elem_id="chatbot", label="HUGO PFOHE - AI Car Salesman").style(height=500)
+        with gr.Row():
+            with gr.Column(scale=1):
+                txt = gr.Textbox(show_label=False, placeholder="What car would you like to buy?").style(
+                    container=False)
+            # with gr.Column(scale=0.15):
+            #     submit = gr.Button("Submit")
+        with gr.Row():
+            with gr.Column(scale=0.34, min_width=0):
+                lang = gr.inputs.Dropdown(choices=['English', 'German'], label="Language", default="English")
+            # with gr.Column(scale=0.33, min_width=0):
+            #     clear = gr.Button("Clear")
+            # with gr.Column(scale=0.33, min_width=0):
+            #     btn = gr.UploadButton("Upload CSV", file_types=["csv"])
+            with gr.Column(scale=0.66, min_width=0):
+                with gr.Row():
+                    clear = gr.Button("Clear")
+                with gr.Row():
+                    btn = gr.UploadButton("Upload CSV", file_types=["csv"])
+
+
+        txt.submit(bot.run_text, [chatbot, txt], chatbot)
+        txt.submit(lambda: "", None, txt)
+        lang.change(bot.change_language, [lang, chatbot], chatbot)
+        # submit.click(txt.submit, [chatbot, txt], chatbot)
+        # submit.click(lambda: "", None, txt)
+        clear.click(lambda: [], None, chatbot)
+        btn.upload(bot.process_file, [btn, chatbot], chatbot)
+        demo.launch()

requirements.txt

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+gradio
+openai
+pandas
+tiktoken