gokaygokay commited on
Commit
fb29fff
1 Parent(s): 707a6ed

global prompt type

Browse files
Files changed (2) hide show
  1. huggingface_inference_node.py +30 -19
  2. ui_components.py +4 -3
huggingface_inference_node.py CHANGED
@@ -1,13 +1,15 @@
1
  import os
2
- from openai import OpenAI
3
- import anthropic
4
- from groq import Groq
5
  import re
6
  from datetime import datetime
7
 
 
 
 
 
8
  huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
9
  groq_api_key = os.getenv("GROQ_API_KEY")
10
 
 
11
  class LLMInferenceNode:
12
  def __init__(self):
13
  self.huggingface_client = OpenAI(
@@ -16,7 +18,19 @@ class LLMInferenceNode:
16
  )
17
  self.groq_client = Groq(api_key=groq_api_key)
18
 
19
- def generate(self, input_text, happy_talk, compress, compression_level, poster, prompt_type, custom_base_prompt="", provider="Hugging Face", api_key=None, model=None):
 
 
 
 
 
 
 
 
 
 
 
 
20
  try:
21
  default_happy_prompt = """Create a detailed visually descriptive caption of this description, which will be used as a prompt for a text to image AI system (caption only, no instructions like "create an image").Remove any mention of digital artwork or artwork style. Give detailed visual descriptions of the character(s), including ethnicity, skin tone, expression etc. Imagine using keywords for a still for someone who has aphantasia. Describe the image style, e.g. any photographic or art styles / techniques utilized. Make sure to fully describe all aspects of the cinematography, with abundant technical details and visual descriptions. If there is more than one image, combine the elements and characters from all of the images creatively into a single cohesive composition with a single background, inventing an interaction between the characters. Be creative in combining the characters into a single cohesive scene. Focus on two primary characters (or one) and describe an interesting interaction between them, such as a hug, a kiss, a fight, giving an object, an emotional reaction / interaction. If there is more than one background in the images, pick the most appropriate one. Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph. If you feel the images are inappropriate, invent a new scene / characters inspired by these. Additionally, incorporate a specific movie director's visual style and describe the lighting setup in detail, including the type, color, and placement of light sources to create the desired mood and atmosphere. Always frame the scene, including details about the film grain, color grading, and any artifacts or characteristics specific."""
22
 
@@ -47,7 +61,7 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
47
  "only_objects": only_objects_prompt,
48
  "no_figure": no_figure_prompt,
49
  "landscape": landscape_prompt,
50
- "fantasy": fantasy_prompt
51
  }
52
 
53
  # Update this part to handle the prompt_type correctly
@@ -60,13 +74,15 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
60
  print("Using custom base prompt")
61
  else:
62
  base_prompt = default_happy_prompt
63
- print(f"Warning: Unknown or empty prompt type '{prompt_type}'. Using default happy prompt.")
 
 
64
 
65
  if compress and not poster:
66
  compression_chars = {
67
  "soft": 600 if happy_talk else 300,
68
  "medium": 400 if happy_talk else 200,
69
- "hard": 200 if happy_talk else 100
70
  }
71
  char_limit = compression_chars[compression_level]
72
  base_prompt += f" Compress the output to be concise while retaining key visual details. MAX OUTPUT SIZE no more than {char_limit} characters."
@@ -82,7 +98,7 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
82
  top_p=0.95,
83
  messages=[
84
  {"role": "system", "content": system_message},
85
- {"role": "user", "content": user_message}
86
  ],
87
  )
88
  output = response.choices[0].message.content.strip()
@@ -95,7 +111,7 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
95
  temperature=0.7,
96
  messages=[
97
  {"role": "system", "content": system_message},
98
- {"role": "user", "content": user_message}
99
  ],
100
  )
101
  output = response.choices[0].message.content.strip()
@@ -110,14 +126,9 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
110
  messages=[
111
  {
112
  "role": "user",
113
- "content": [
114
- {
115
- "type": "text",
116
- "text": user_message
117
- }
118
- ]
119
  }
120
- ]
121
  )
122
  output = response.content[0].text
123
 
@@ -128,7 +139,7 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
128
  temperature=0.7,
129
  messages=[
130
  {"role": "system", "content": system_message},
131
- {"role": "user", "content": user_message}
132
  ],
133
  )
134
  output = response.choices[0].message.content.strip()
@@ -143,9 +154,9 @@ You are allowed to make up film and branding names, and do them like 80's, 90's
143
  sentences = output.split(". ")
144
  if len(sentences) > 1:
145
  output = ". ".join(sentences[1:]).strip()
146
-
147
  return output
148
 
149
  except Exception as e:
150
  print(f"An error occurred: {e}")
151
- return f"Error occurred while processing the request: {str(e)}"
 
1
  import os
 
 
 
2
  import re
3
  from datetime import datetime
4
 
5
+ import anthropic
6
+ from groq import Groq
7
+ from openai import OpenAI
8
+
9
  huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
10
  groq_api_key = os.getenv("GROQ_API_KEY")
11
 
12
+
13
  class LLMInferenceNode:
14
  def __init__(self):
15
  self.huggingface_client = OpenAI(
 
18
  )
19
  self.groq_client = Groq(api_key=groq_api_key)
20
 
21
+ def generate(
22
+ self,
23
+ input_text,
24
+ happy_talk,
25
+ compress,
26
+ compression_level,
27
+ poster,
28
+ prompt_type,
29
+ custom_base_prompt="",
30
+ provider="Hugging Face",
31
+ api_key=None,
32
+ model=None,
33
+ ):
34
  try:
35
  default_happy_prompt = """Create a detailed visually descriptive caption of this description, which will be used as a prompt for a text to image AI system (caption only, no instructions like "create an image").Remove any mention of digital artwork or artwork style. Give detailed visual descriptions of the character(s), including ethnicity, skin tone, expression etc. Imagine using keywords for a still for someone who has aphantasia. Describe the image style, e.g. any photographic or art styles / techniques utilized. Make sure to fully describe all aspects of the cinematography, with abundant technical details and visual descriptions. If there is more than one image, combine the elements and characters from all of the images creatively into a single cohesive composition with a single background, inventing an interaction between the characters. Be creative in combining the characters into a single cohesive scene. Focus on two primary characters (or one) and describe an interesting interaction between them, such as a hug, a kiss, a fight, giving an object, an emotional reaction / interaction. If there is more than one background in the images, pick the most appropriate one. Your output is only the caption itself, no comments or extra formatting. The caption is in a single long paragraph. If you feel the images are inappropriate, invent a new scene / characters inspired by these. Additionally, incorporate a specific movie director's visual style and describe the lighting setup in detail, including the type, color, and placement of light sources to create the desired mood and atmosphere. Always frame the scene, including details about the film grain, color grading, and any artifacts or characteristics specific."""
36
 
 
61
  "only_objects": only_objects_prompt,
62
  "no_figure": no_figure_prompt,
63
  "landscape": landscape_prompt,
64
+ "fantasy": fantasy_prompt,
65
  }
66
 
67
  # Update this part to handle the prompt_type correctly
 
74
  print("Using custom base prompt")
75
  else:
76
  base_prompt = default_happy_prompt
77
+ print(
78
+ f"Warning: Unknown or empty prompt type '{prompt_type}'. Using default happy prompt."
79
+ )
80
 
81
  if compress and not poster:
82
  compression_chars = {
83
  "soft": 600 if happy_talk else 300,
84
  "medium": 400 if happy_talk else 200,
85
+ "hard": 200 if happy_talk else 100,
86
  }
87
  char_limit = compression_chars[compression_level]
88
  base_prompt += f" Compress the output to be concise while retaining key visual details. MAX OUTPUT SIZE no more than {char_limit} characters."
 
98
  top_p=0.95,
99
  messages=[
100
  {"role": "system", "content": system_message},
101
+ {"role": "user", "content": user_message},
102
  ],
103
  )
104
  output = response.choices[0].message.content.strip()
 
111
  temperature=0.7,
112
  messages=[
113
  {"role": "system", "content": system_message},
114
+ {"role": "user", "content": user_message},
115
  ],
116
  )
117
  output = response.choices[0].message.content.strip()
 
126
  messages=[
127
  {
128
  "role": "user",
129
+ "content": [{"type": "text", "text": user_message}],
 
 
 
 
 
130
  }
131
+ ],
132
  )
133
  output = response.content[0].text
134
 
 
139
  temperature=0.7,
140
  messages=[
141
  {"role": "system", "content": system_message},
142
+ {"role": "user", "content": user_message},
143
  ],
144
  )
145
  output = response.choices[0].message.content.strip()
 
154
  sentences = output.split(". ")
155
  if len(sentences) > 1:
156
  output = ". ".join(sentences[1:]).strip()
157
+
158
  return output
159
 
160
  except Exception as e:
161
  print(f"An error occurred: {e}")
162
+ return f"Error occurred while processing the request: {str(e)}"
ui_components.py CHANGED
@@ -215,13 +215,14 @@ def create_interface():
215
 
216
  def generate_text_with_llm(output, happy_talk, compress, compression_level, custom_base_prompt, provider, api_key, model):
217
  global selected_prompt_type
218
- print(f"Prompt type selected in UI: {selected_prompt_type}") # Debug print
219
- return llm_node.generate(output, happy_talk, compress, compression_level, False, selected_prompt_type, custom_base_prompt, provider, api_key, model)
 
220
 
221
  generate_text_button.click(
222
  generate_text_with_llm,
223
  inputs=[output, happy_talk, compress, compression_level, custom_base_prompt, llm_provider, api_key, model],
224
- outputs=text_output,
225
  api_name="generate_text"
226
  )
227
 
 
215
 
216
  def generate_text_with_llm(output, happy_talk, compress, compression_level, custom_base_prompt, provider, api_key, model):
217
  global selected_prompt_type
218
+ result = llm_node.generate(output, happy_talk, compress, compression_level, False, selected_prompt_type, custom_base_prompt, provider, api_key, model)
219
+ selected_prompt_type = "happy" # Reset to "happy" after generation
220
+ return result, "happy" # Return the result and the new prompt type value
221
 
222
  generate_text_button.click(
223
  generate_text_with_llm,
224
  inputs=[output, happy_talk, compress, compression_level, custom_base_prompt, llm_provider, api_key, model],
225
+ outputs=[text_output, prompt_type],
226
  api_name="generate_text"
227
  )
228