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anton_ego_jimmy.py

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+import streamlit as st
+# Model Configuration
+#[model]
+TYPE = "chat" # so that it uses the chat history
+SELECTED_MODEL = "meta-llama/llama-3-1-70b-instruct" # Pick a model_id, you can find them here https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-api-model-ids.html?context=wx&audience=wdp
+#SELECTED_MODEL = "meta-llama/llama-3-405b-instruct"
+#SELECTED_MODEL = "mistralai/mistral-large"
+#SELECTED_MODEL = "mistralai/mixtral-8x7b-instruct-v01"
+VERIFY = False
+
+# Prompt Configuration
+#[prompt]
+SYSTEM_PROMPT = st.secrets["sys_prompt"]
+PROMPT_TEMPLATE = "llama3-instruct (llama-3 & 3.1) - system"
+#PROMPT_TEMPLATE = "mistral & mixtral v2 tokenizer - system"  # <pick prompt template from model_family_syntax below> For example "llama3-instruct (llama-3 & 3.1) - user" if you don't use a system prompt.
+BAKE_IN_PROMPT_SYNTAX = True
+
+# Generation Parameters
+DECODING_METHOD = "greedy" # greedy or sample
+MAX_NEW_TOKENS = 250
+MIN_NEW_TOKENS = 1
+REPETITION_PENALTY = 1.0
+# LENGTH_PENALTY = {'decay_factor': 1.25, 'start_index': 150}
+STOP_SEQUENCES = ["<|end_of_text|>","</s>"] # This one is set up for llama models, if you use mistral </s> is the preferred stop_sequence
+
+# Additional Parameters - Only active if you pick sampling in decoding method
+TEMPERATURE = 0.75
+TOP_P = 1.0
+TOP_K = 50
+
+DISPLAY_CHAT_HISTORY = 1  # 0 to display chat history, 1 to not display chat history
+
+# model_family_syntax = {
+#     "llama3-instruct (llama-3 & 3.1) - system": """\n<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n""",
+#     "llama3-instruct (llama-3 & 3.1) - user": """\n<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n""",
+#     "granite-13b-chat & instruct - system": """\n<|system|>\n{system_prompt}\n<|user|>\n{prompt}\n<|assistant|>\n\n""",
+#     "granite-13b-chat & instruct - user": """\n<|user|>\n{prompt}\n<|assistant|>\n\n""",
+#     "llama2-chat - system": """\n[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n{prompt} [/INST] """,
+#     "llama2-chat - user": """\n[INST] {prompt} [/INST] """,
+#     "mistral & mixtral v2 tokenizer - system": """\n<s>[INST]System Prompt:[{system_prompt}]\n\n{prompt} [/INST]\n""",
+#     "mistral & mixtral v2 tokenizer - system segmented": """\n<s>[INST]System Prompt:{system_prompt}[/INST][INST]{prompt} [/INST]\n""",
+#     "mistral & mixtral v2 tokenizer - user": """\n<s>[INST]{prompt} [/INST]\n"""
+# }

requirements.txt

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+streamlit
+ibm-watsonx-ai
+langchain
+langchain-ibm
+requests

secretsload.py

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+import os
+import toml
+from typing import Dict
+
+def load_stsecrets(config_path: str = '.streamlit/secrets.toml') -> Dict:
+    """
+    Load configuration from Streamlit secrets TOML file and replace placeholders with environment variables.
+    
+    :param config_path: Path to the Streamlit secrets TOML file
+    :return: Dictionary containing the credentials
+    """
+    # Read the TOML file
+    with open(config_path, 'r') as f:
+        config = toml.load(f)
+    
+    # Replace placeholders with environment variables
+    credentials = config.get('credentials', {})
+    for key, value in credentials.items():
+        if isinstance(value, str) and value.startswith('${') and value.endswith('}'):
+            env_var = value[2:-1]  # Remove ${ and }
+            credentials[key] = os.environ.get(env_var)
+            if credentials[key] is None:
+                raise ValueError(f"Environment variable {env_var} is not set")
+    
+    return credentials