Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

README.md

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+# ActasGPT
+

app.py

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+import streamlit as st
+from streamlit_ace import st_ace
+import openai
+from utils import input_prompts, get_completion, get_ideal_prompt
+
+# 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
+
+st.title('Act as GPT')
+
+psw_col, sel_col = st.columns([2, 1])
+
+OPENAI_API_KEY = psw_col.text_input("OpenAI API key", type='password')
+
+model = sel_col.selectbox(
+    'Model',
+    ('gpt-3.5-turbo', 'gpt-4'))
+
+st.write('\n')
+st.write('\n')
+
+# initilizing the selectbox with an empty element
+input_prompts = [''] + input_prompts.tolist()
+
+user_input = st.selectbox('Select an input prompt', input_prompts)
+st.write('Act as:', user_input)
+print(user_input)
+
+if user_input != "":
+    last_sentence = None
+    sentences_counter = -1
+    openai.api_key = OPENAI_API_KEY
+
+    # Receiving input from the df
+    modified_input = get_ideal_prompt(user_input)
+    sentences = modified_input.split(".")
+
+    # TODO: Debug all the dataset (gpt prompt generator)
+
+    # Find the last sentence containing the word "first"
+    for sentence in reversed(sentences):
+        if "first" in sentence.lower().split():
+            last_sentence = sentence.strip()
+            break
+        else:
+            sentences_counter -= 1
+
+    if last_sentence:
+        input_first_half = ". ".join(sentences[:sentences_counter]) + "."
+        st.write(input_first_half)
+        # Create a reactive text area with live update
+        input_second_half = st.text_area("modified_input", value=last_sentence + ".", key="text_area")
+        input_text = input_first_half + input_second_half
+
+        if st.button("Run"):
+            write_col1, write_col2, write_col3 = st.columns([1, 1, 1])
+            output = get_completion(input_text, model)
+            write_col1.write(output)
+            output = get_completion(input_text, model)
+            write_col2.write(output)
+            output = get_completion(input_text, model)
+            write_col3.write(output)

utils.py

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+import pandas as pd
+import openai
+
+prompts_df = pd.read_csv("prompts.csv")
+input_prompts = prompts_df["act"]  # used in streamlit interface
+
+
+
+def get_ideal_prompt(user_prompt):
+    print(user_prompt)
+    filtered_rows = prompts_df[prompts_df['act'].isin([user_prompt])]
+    if not filtered_rows.empty:
+        ideal_prompt = filtered_rows['prompt'].iloc[0]
+        return ideal_prompt
+
+
+get_ideal_prompt("Travel Guide")
+
+
+def get_completion(prompt, model="gpt-3.5-turbo"):
+    if not prompt:
+        return prompt  # Return an empty string if the prompt is invalid
+    # you will be provided with a prompt to act as someone or something, try to give the most ideal output for an unexpierienced user and epxlain everything from scratch
+    messages = [
+        {"role": "system",
+         "content": "You will act as an advanced language model. The user wants you to simulate the experience of interacting with the provided prompt."},
+        {"role": "user", "content": prompt}
+    ]
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=messages,
+        temperature=0.3,
+    )
+    return response.choices[0].message["content"]