Update app.py

app.py

@@ -2,11 +2,58 @@ import os
 import time
 import uuid
 from typing import List, Tuple, Optional, Dict, Union
-
-
 import google.generativeai as genai
 import gradio as gr
 from PIL import Image
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain, SequentialChain
+
+# LangChain function for company analysis
+
+def company_analysis(api_key: str, company_name: str) -> dict:
+    
+    os.environ['OPENAI_API_KEY'] = api_key  # Set the OpenAI API key as an environment variable
+    llm = ChatOpenAI()
+    '''
+    # Identify the email's language
+    template1 = "Return the language this email is written in:\n{email}.\nONLY return the language it was written in."
+    prompt1 = ChatPromptTemplate.from_template(template1)
+    chain_1 = LLMChain(llm=llm, prompt=prompt1, output_key="language")
+
+    # Translate the email to English
+    template2 = "Translate this email from {language} to English. Here is the email:\n" + email
+    prompt2 = ChatPromptTemplate.from_template(template2)
+    chain_2 = LLMChain(llm=llm, prompt=prompt2, output_key="translated_email")
+
+    # Provide a summary in English
+    template3 = "Create a short summary of this email:\n{translated_email}"
+    prompt3 = ChatPromptTemplate.from_template(template3)
+    chain_3 = LLMChain(llm=llm, prompt=prompt3, output_key="summary")
+
+    # Provide a reply in English
+    template4 = "Reply to the sender of the email giving a plausible reply based on the {summary} and a promise to address issues"
+    prompt4 = ChatPromptTemplate.from_template(template4)
+    chain_4 = LLMChain(llm=llm, prompt=prompt4, output_key="reply")
+
+    # Provide a translation back to the original language
+    template5 = "Translate the {reply} back to the original {language} of the email."
+    prompt5 = ChatPromptTemplate.from_template(template5)
+    chain_5 = LLMChain(llm=llm, prompt=prompt5, output_key="translated_reply")
+    
+
+    seq_chain = SequentialChain(chains=[chain_1, chain_2, chain_3, chain_4, chain_5],
+                                input_variables=['email'],
+                                output_variables=['language', 'translated_email', 'summary', 'reply', 'translated_reply'],
+                                verbose=True)
+    '''                            
+    return seq_chain(email)
+
+
+
+
+
+
 
 print("google-generativeai:", genai.__version__)
 
@@ -165,6 +212,9 @@ upload_button_component = gr.UploadButton(
     label="Upload Images", file_count="multiple", file_types=["image"], scale=1
 )
 run_button_component = gr.Button(value="Run", variant="primary", scale=1)
+
+run_button_analysis = gr.Button(value="Run", variant="primary", scale=1)
+
 temperature_component = gr.Slider(
     minimum=0,
     maximum=1.0,
@@ -228,6 +278,7 @@ user_inputs = [
     chatbot_component
 ]
 
+
 bot_inputs = [
     google_key_component,
     upload_button_component,
@@ -244,6 +295,23 @@ with gr.Blocks() as demo:
     with gr.Tab("Company Analysis"):
         gr.HTML(TITLE1)
 
+        run_button_analysis.click(
+        fn=company_analysis,
+        inputs=[
+            gr.inputs.Textbox(label="Enter your OpenAI API Key:", type="password"),
+            gr.inputs.Textbox(label="Enter the Company Name:")
+        ],
+        outputs=[
+            gr.outputs.Textbox(label="Language"),
+            gr.outputs.Textbox(label="Summary"),
+            gr.outputs.Textbox(label="Translated Email"),
+            gr.outputs.Textbox(label="Reply in English"),
+            gr.outputs.Textbox(label="Reply in Original Language")
+        ],
+        title="Chain Example: Language, Summary, Translate, Respond & Translate",
+        description="Translates an email to English, provides a summary, plausible reply and translates back to the sender"
+        )
+
       
     with gr.Tab("Investment Strategy"):    
         gr.HTML(TITLE2)