adding open-ai api

app.py

@@ -3,11 +3,13 @@
 
 
 import gradio as gr
-import langchain
-import openai
+import os
+import langchain_openai
+import langchain_core
 import json
-# from langchain_openai import ChatOpenAI
-# from langchain.prompt import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
 
 def load_input_fields(filepath):
     """
@@ -57,9 +59,21 @@ def format_to_markdown(objects):
     ]
     return '\n'.join(formatted_list)
 
-
 def enhance_subject(subject, details):
-  return ""
+  prompt = ChatPromptTemplate.from_messages([
+      ("system", "Generate a clear and concise subject, then provide additional details using descriptive language. Ensure the response is specific and avoids ambiguity or contradictions. The subject should inspire an engaging photo that tells a story. Remove any unnecessary information and don't add any punctuation at the end of the subject."),
+      ("user", "The main subject is {subject} {details}.")
+    ])
+  output_parser = StrOutputParser()
+  model = ChatOpenAI(model="gpt-3.5-turbo")
+  chain = ( prompt
+    | model
+    | output_parser
+  )
+  result = chain.invoke({"subject": subject, "details": details})
+  return result
+
+
 input_fields = load_input_fields("input_fields.json")
 # Models
 models = input_fields.get("models")
@@ -124,6 +138,7 @@ def convert_to_temp_format(temperature):
 
 with gr.Blocks() as demo:
   isFrog = gr.State(False)
+
   gr.Markdown(
       """
         # Let's combine a prompt for you!
@@ -143,14 +158,19 @@ with gr.Blocks() as demo:
   )
 
   def enhance_pipeline(isFrog, subject, details):
-    if isFrog:
-      return [gr.Textbox(visible=False), gr.Button(visible=False), gr.TextArea(visible=True)]
+    if isFrog and (subject or details):
+      result = enhance_subject(subject, details)
+      return [gr.Textbox(visible=False), gr.Button(visible=False), gr.TextArea(visible=True, value=result)]
+    elif (subject or details) and not isFrog:
+      return [gr.Textbox(visible=True), gr.Button(visible=True), gr.TextArea(visible=False)]
     else:
-      return [gr.Textbox(visible=(subject or details)), gr.Button(visible=(subject or details)), gr.TextArea(visible=False)]
+      return [gr.Textbox(visible=False), gr.Button(visible=False), gr.TextArea(visible=False)]
+
   
-  def authenticate(pwd_input, confirm_btn, subject, details, isFrog):
-    if pwd_input == "frog":
-      return [gr.TextArea(visible=True, value="You are a true frog"), True, gr.Textbox(visible=False), gr.Button(visible=False)]
+  def authenticate(pwd_input, subject, details):
+    if pwd_input == os.environ.get("MAGIC_WORD"):
+      result = enhance_subject(subject, details)
+      return [gr.TextArea(visible=True, value=result), True, gr.Textbox(visible=False), gr.Button(visible=False)]
     else:
       raise gr.Error("You are not from our pond! Use your own LLM to add some juice to your prompt.")
 
@@ -165,19 +185,22 @@ with gr.Blocks() as demo:
     with gr.Column():
       pwd_input = gr.Textbox(label="Do you know the magic word?", visible=False)
       confirm_btn = gr.Button(value="Confirm Pwd", visible=False)
-      enhanced_prompt = gr.TextArea(label="Compiled Prompt", show_copy_button=True, interactive=True, visible=False)
+      enhanced_prompt = gr.TextArea(label="Enhanced Prompt", show_copy_button=True, interactive=True, visible=False, lines=3)
   
   enhance_button.click(
     enhance_pipeline,
     inputs=[isFrog, ui_subject, ui_details], 
     outputs=[pwd_input, confirm_btn, enhanced_prompt]
   )
+  
+  def clearInput():
+    return ""
 
   confirm_btn.click(
     authenticate, 
-    inputs=[pwd_input, confirm_btn, ui_subject, ui_details, isFrog],
+    inputs=[pwd_input, ui_subject, ui_details],
     outputs=[enhanced_prompt,isFrog, pwd_input, confirm_btn]
-  )
+  ).then(clearInput, outputs=pwd_input)
   
   gr.Markdown(
       """
@@ -293,14 +316,16 @@ with gr.Blocks() as demo:
     with gr.Column(scale=3):
       result_prompt=gr.TextArea(label="Compiled Prompt", show_copy_button=True, interactive=True)
 
-  def compile_prompt(photo_style, subject, weather, time, mood, details, camera_type, camera_angle, shot_type, lens_filter, lighting, model, aspect_ratio, temperature):
+  def compile_prompt(photo_style, subject, enhanced_prompt, weather, time, mood, details, camera_type, camera_angle, shot_type, lens_filter, lighting, model, aspect_ratio, temperature):
     resulting_prompt = ""
     if photo_style and photo_style != "None":
-      resulting_prompt += f"{photo_style} "
-      resulting_prompt += "of "
-    if subject:
+      resulting_prompt += f"{photo_style} of "
+    if subject and (enhanced_prompt is None or enhanced_prompt == ""):
       resulting_prompt += f"{subject}, "
-    if weather or time and (weather != "None" or time != "None"):
+    if enhanced_prompt and enhanced_prompt != "":
+      resulting_prompt += f"{enhanced_prompt}, "
+    if weather != "None" or time != "None":
+      print(weather, time)
       resulting_prompt += "set  "
     if weather and weather != "None":
       resulting_prompt += f" on a {weather} day "
@@ -308,7 +333,7 @@ with gr.Blocks() as demo:
       resulting_prompt += f"at {time} "
     if mood and mood != "None":
       resulting_prompt += f"with a {mood} mood. "
-    if details:
+    if details and (enhanced_prompt is None or enhanced_prompt == ""):
       resulting_prompt += f"Include {details}. "
     if camera_type and camera_type != "None":
       resulting_prompt += f"Shot on {camera_type} "
@@ -331,6 +356,7 @@ with gr.Blocks() as demo:
     inputs=[
       ui_photography_style,
       ui_subject,
+      enhanced_prompt,
       ui_weather,
       ui_time,
       ui_mood, 

requirements.txt

@@ -1,4 +1,3 @@
 gradio>=3.0,<4.0
-openai
-langchain
+langchain_core
 langchain_openai