Create app.py

app.py

@@ -0,0 +1,149 @@
+import os
+openai.api_key= os.environ.get('API_OPENAI')
+AIRTABLE_API_KEY = os.environ.get('API_AIRTABLE')
+
+import gradio as gr
+import os
+import csv
+from langchain.vectorstores import Pinecone
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.chains import ConversationalRetrievalChain
+from langchain.chat_models import ChatOpenAI
+import openai
+import pinecone
+import datetime
+from tqdm.autonotebook import tqdm
+import requests
+
+embeddings = OpenAIEmbeddings(openai_api_key=openai.api_key)
+
+AIRTABLE_ENDPOINT = "https://api.airtable.com/v0/appv2hF1PzrseVdeW/data_m"
+AIRTABLE_ENDPOINT_LOG = "https://api.airtable.com/v0/appv2hF1PzrseVdeW/log"
+HEADERS = {
+    "Authorization": f"Bearer {AIRTABLE_API_KEY}",
+    "Content-Type": "application/json"
+}
+
+def get_text_by_name(name):
+    params = {
+        "filterByFormula": f"{{name}} = '{name}'"
+    }
+    response = requests.get(AIRTABLE_ENDPOINT, headers=HEADERS, params=params)
+
+    if response.status_code != 200:
+        print(f"Error fetching data. Status code: {response.status_code}. Content: {response.content}")
+        return None
+
+    records = response.json().get("records")
+
+    if not records:
+        print(f"No record found with name: {name}")
+        return None
+
+    # Assuming that names are unique, take the first record.
+    return records[0]["fields"].get("text")
+
+def upload_to_airtable_log(date, question, answer, rating, comment):
+    data = {
+        "records": [{
+            "fields": {
+                 "date": date,
+                 "question": question,
+                 "answer": answer,
+                 "rating": rating,
+                 "comment": comment
+            }
+        }]
+    }
+    response = requests.post(AIRTABLE_ENDPOINT_LOG, headers=HEADERS, json=data)
+
+    if response.status_code != 200:
+        print(f"Error uploading airtable (log ) Status code: {response.status_code}. Content: {response.content}")
+    else:
+        print(f"Successfully uploaded airtable log")
+
+def query_gpt_3_5(prompt, context):
+    prompt = "Instruction: Твоя роль - кваліфікований співробітник саппорту у системи YouControl. Потрібно відповісти на питання від користувача з огляду на контекст. Контекст ми беремо з бази знань, але вона може бути не повна.  Якщо контекст не коректний, то відповідай на свій розсуд або передай запит сапорту, про контекс нічого не пишемо у відповіді."+"""
+    """+ "question:" + prompt + """
+    context:""" + context + """
+    answer:"""
+    completion = openai.ChatCompletion.create(
+    model="gpt-4-0613",
+    messages=[
+      {"role": "user", "content": prompt}
+              ]
+    )
+    return completion.choices[0].message.content
+
+def print_docs(docs):
+    for doc in docs:
+        print(f"Chunk: {doc.page_content}")
+        print(f"Content: {doc.metadata['source']}\n")
+
+# initialize pinecone
+pinecone.init(
+    api_key="078ea261-eaa8-4920-8af6-0870f7f8a096",  # find at app.pinecone.io
+    environment="eu-west4-gcp"  # next to api key in console
+)
+
+index_name = "yc-faq"
+vectorstore = Pinecone.from_existing_index(index_name, embeddings)
+
+def ask_yc_bot(question):
+  if (len(question)<3 ): return "Не зрозумів питання"
+  docs = vectorstore.similarity_search(question)
+  print_docs(docs)
+  source_name = docs[0].metadata['source']
+  file_name  = source_name.replace("/content/drive/MyDrive/yc-bot/faq/", "")
+  result_text = get_text_by_name(file_name)
+  context = ""
+  if result_text:
+      print(f"Text for '{file_name}' is: {result_text}")
+      context = context +  result_text
+
+
+
+  #print (len(context))
+  result = query_gpt_3_5(question, context)
+  result = result + """
+--------------------------------------------------------
+[CONTEXT]
+""" + context
+  return result
+
+
+def comment_bot(slider_value, comment_text, question_text, answer_text):
+    date_d  = datetime.datetime.now().date()
+    date_string = date_d.isoformat()
+    upload_to_airtable_log(date_string, question_text, answer_text, slider_value, comment_text)
+
+    return " "  # Если функция должна что-то возвращать, замените это на нужный вывод
+
+import gradio as gr
+
+description = """<h1>YC - FAQ_BOT</h1>
+"""
+
+demo = gr.Blocks()
+
+with demo:
+    gr.HTML(description)
+    with gr.Row():
+      with gr.Column(scale=1):
+        text = gr.Textbox(lines=7, label = "Вопрос?")
+        b1 = gr.Button("Спросить")
+      with gr.Column(scale=2):
+        answer = gr.Textbox(lines=10, label = "Ответ:")
+
+    with gr.Row():
+        radio = gr.Radio(label="Рейтинг ответа", choices=["Нет", "1", "2", "3", "4", "5"], value="Нет")
+        comment = gr.Textbox(lines=2, label = "Комментарий")
+    with gr.Row():
+        b2 = gr.Button("Прокомментировать ответ ")
+
+    inp_2 = [radio, comment, text, answer]
+    b1.click(ask_yc_bot, inputs=text, outputs=answer)
+    b2.click(comment_bot, inputs=inp_2, outputs=comment)
+
+
+demo.launch(share=False, debug=True)