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src/bot_specs.py

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+import os
+
+bot_name = os.getenv("BOT_NAME") or "jimmy"
+bot_icon = os.getenv("BOT_ICON") or "🧐"
+user_icon = os.getenv("USER_ICON") or "🥷🏻"

src/helper_functions.py

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+import streamlit as st
+from ibm_watsonx_ai import APIClient, Credentials
+from ibm_watsonx_ai.foundation_models import ModelInference
+from io import BytesIO
+from reportlab.lib.pagesizes import letter
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
+from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+from reportlab.lib import colors
+from reportlab.lib.enums import TA_LEFT, TA_RIGHT
+from datetime import datetime
+import regex
+import os
+
+
+def check_password():
+    def password_entered():
+        if st.session_state["password"] == os.getenv("APP_PASSWORD"):
+            st.session_state["password_correct"] = True
+            del st.session_state["password"]
+        else:
+            st.session_state["password_correct"] = False
+
+    if "password_correct" not in st.session_state:
+        st.markdown("\n\n")
+        st.text_input(
+            "Enter the password",
+            type="password",
+            on_change=password_entered,
+            key="password",
+        )
+        st.divider()
+        st.info("Designed and developed by Milan Mrdenovic © IBM Norway 2025")
+        return False
+    elif not st.session_state["password_correct"]:
+        st.markdown("\n\n")
+        st.text_input(
+            "Enter the password",
+            type="password",
+            on_change=password_entered,
+            key="password",
+        )
+        st.divider()
+        st.info("Designed and developed by Milan Mrdenovic © IBM Norway 2025")
+        st.error("😕 Password incorrect")
+        return False
+    else:
+        return True
+
+
+def initialize_session_state():
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = []
+
+
+def setup_watsonxai_client(
+    api_key: str, project_id: str, url: str = "https://eu-de.ml.cloud.ibm.com"
+):
+    """Set up a watsonx.ai python SDK client using an apikey and project_id."""
+    from ibm_watsonx_ai import APIClient, Credentials
+
+    wx_credentials = Credentials(url=url, api_key=api_key)
+    wxai_client = APIClient(wx_credentials, project_id=project_id)
+
+    return wxai_client
+
+
+emoji_pattern = regex.compile(r"\p{Emoji}", flags=regex.UNICODE)
+
+
+def remove_emojis(text):
+    return emoji_pattern.sub(r"", text)
+
+
+def create_pdf_from_chat(chat_history):
+    buffer = BytesIO()
+    doc = SimpleDocTemplate(buffer, pagesize=letter, topMargin=30, bottomMargin=30)
+    styles = getSampleStyleSheet()
+    flowables = []
+
+    title_style = ParagraphStyle(
+        "Title", parent=styles["Heading1"], fontSize=18, spaceAfter=20
+    )
+    flowables.append(
+        Paragraph(
+            f"Chat History - Generated on {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
+            title_style,
+        )
+    )
+
+    user_style = ParagraphStyle(
+        "UserStyle",
+        parent=styles["Normal"],
+        backColor=colors.lightblue,
+        borderPadding=10,
+        alignment=TA_RIGHT,
+    )
+    jimmy_style = ParagraphStyle(
+        "JimmyStyle",
+        parent=styles["Normal"],
+        backColor=colors.lavender,
+        borderPadding=10,
+    )
+
+    for message in chat_history:
+        role = message["role"]
+        content = remove_emojis(message["content"])
+        style = user_style if role == "user" else jimmy_style
+        flowables.append(Paragraph(f"<b>{role.capitalize()}:</b> {content}", style))
+        flowables.append(Spacer(1, 12))
+
+    doc.build(flowables)
+    buffer.seek(0)
+    return buffer
+
+
+def watsonx_chat_prompt(
+    messages,
+    stream=False,
+    client=None,
+    wx_url=None,
+    wx_apikey=None,
+    project_id=None,
+    model_id=None,
+    params=None,
+):
+    """
+    Dynamic chat function for Watson AI
+
+    Args:
+        messages (list): List of message objects following watsonx schema.
+                        Each message should have 'role' and 'content' keys.
+                        Supports system, user, assistant, and tool messages.
+        stream (bool): If True, return streaming generator; if False, return complete response
+        client (APIClient): Pre-configured Watson client (optional)
+        wx_url (str): Watson URL (required if no client)
+        wx_apikey (str): Watson API key (required if no client)
+        project_id (str): Watson project ID (required if no client)
+        model_id (str): Model identifier
+        params (dict): Model parameters (optional)
+
+    Returns:
+        str or generator: Complete response text or streaming generator based on stream parameter
+    """
+    # from ibm_watsonx_ai.foundation_models import ModelInference
+    # from ibm_watsonx_ai import APIClient, Credentials
+
+    if params is None:
+        params = {
+            "temperature": 0.7,
+            "max_tokens": 4096,
+            "top_p": 1.0,
+            "stop": ["</s>", "<|end_of_text|>", "<|endoftext|>"],
+            # "frequency_penalty": 0.5,
+            # "presence_penalty": 0.3,
+        }
+
+    # Use provided client or create new one
+    if client is None:
+        wx_credentials = Credentials(url=wx_url, api_key=wx_apikey)
+        client = APIClient(credentials=wx_credentials, project_id=project_id)
+
+    chat_model = ModelInference(api_client=client, model_id=model_id, params=params)
+
+    if stream:
+        return chat_model.chat_stream(messages=messages)
+    else:
+        return chat_model.chat(messages=messages)
+
+
+def generate_response(watsonx_chat_prompt, stream):
+    if stream:
+        for chunk in watsonx_chat_prompt:
+            if chunk["choices"]:
+                yield chunk["choices"][0]["delta"].get("content", "")
+    else:
+        return watsonx_chat_prompt["choices"][0]["message"]["content"]

src/parameters.py

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+import os
+
+model_id = os.getenv("MODEL_ID") or "meta-llama/llama-3-2-90b-vision-instruct"
+wx_api_key = os.getenv("WX_API_KEY")
+wx_project_id = os.getenv("WX_PROJECT_ID")
+wx_url = os.getenv("WX_URL") or "https://eu-de.ml.cloud.ibm.com"
+system_prompt = os.getenv("SYSTEM_PROMPT") or ""
+params = {
+    "temperature": os.getenv("TEMPERATURE") or 0.7,
+    "max_tokens": os.getenv("AX_TOKENS") or 4096,
+    "top_p": os.getenv("TOP_P") or 1.0,
+    "stop": (
+        os.getenv("STOP_SEQUENCES", "").split(",")
+        if os.getenv("STOP_SEQUENCES")
+        else ["</s>", "<|end_of_text|>", "<|endoftext|>"]
+    ),
+    # "frequency_penalty": os.getenv("FREQUENCY_PENALTY") or 0.5,
+    # "presence_penalty": os.getenv("PRESENCE_PENALTY") or 0.3,
+}
+display_chat_history = os.getenv("DISPLAY_CHAT_HISTORY") or True
+stream_outputs = os.getenv("STREAM_OUTPUTS") or True