Merge branch 'cookbook/ss-demo' of https://github.com/phidatahq/phidata…

… into cookbook/ss-demo

cookbook/integrations/singlestore/auto_rag/app.py

@@ -21,6 +21,8 @@
 )
 st.title("Local RAG with Web Scraping")
 st.markdown("##### :orange_heart: Built using [phidata](https://github.com/phidatahq/phidata)")
+
+
 def restart_assistant():
     st.session_state["web_assistant"] = None
     st.session_state["web_assistant_run_id"] = None
@@ -38,7 +40,7 @@ def main() -> None:
         return
 
     # Get model
-    local_rag_model = st.sidebar.selectbox("Select Model", options=["openhermes", "codellama"])
+    local_rag_model = st.sidebar.selectbox("Select Model", options=["GPT-4", "Hermes2", "Claude"])
     # Set assistant_type in session state
     if "local_rag_model" not in st.session_state:
         st.session_state["local_rag_model"] = local_rag_model
@@ -111,11 +113,7 @@ def main() -> None:
         if "url_scrape_key" not in st.session_state:
             st.session_state["url_scrape_key"] = 0
 
-        scraped_url = st.sidebar.text_input(
-            "Input URL",
-            type="default",
-            key=st.session_state["url_scrape_key"]
-        )
+        scraped_url = st.sidebar.text_input("Input URL", type="default", key=st.session_state["url_scrape_key"])
         append_button = st.sidebar.button("Search URL")
         if append_button:
             if scraped_url is not None:

cookbook/integrations/singlestore/auto_rag/assistant.py

@@ -1,29 +1,29 @@
 from typing import Optional
+from os import getenv
 
 from phi.assistant import Assistant
 from phi.knowledge import AssistantKnowledge
-from phi.llm.ollama import Ollama
+from phi.llm.openai import OpenAIChat
+from phi.llm.anthropic import Claude
+from phi.llm.ollama import Hermes
 from phi.embedder.ollama import OllamaEmbedder
 from phi.storage.assistant.singlestore import S2AssistantStorage
 from phi.vectordb.singlestore import S2VectorDb
 
-from resources import config  # type: ignore
 
 # Setup SingleStore connection
-db_url = (
-    f"mysql+pymysql://{config['username']}:{config['password']}@{config['host']}:{config['port']}/{config['database']}?charset=utf8mb4"
-)
+db_url = f"mysql+pymysql://{getenv("SINGLESTORE_USERNAME")}:{getenv("SINGLESTORE_PASSWORD")}@{getenv("SINGLESTORE_HOST")}:{getenv("SINGLESTORE_PORT")}/{getenv("SINGLESTORE_DATABASE")}?ssl_ca={getenv("SINGLESTORE_SSL_CERT")}&ssl_verify_cert=true"
 
 local_assistant_storage = S2AssistantStorage(
     table_name="local_rag_assistant",
-    schema=config["database"],
+    schema=getenv("SINGLESTORE_DATABASE"),
     db_url=db_url,
 )
 
 local_assistant_knowledge = AssistantKnowledge(
     vector_db=S2VectorDb(
         collection="web_documents_singlestore",
-        schema=config["database"],
+        schema=getenv("SINGLESTORE_DATABASE"),
         db_url=db_url,
         # Assuming OllamaEmbedder or a compatible embedder is used for SingleStore
         embedder=OllamaEmbedder(model="nomic-embed-text", dimensions=768),
@@ -33,17 +33,25 @@
 
 
 def get_local_rag_assistant(
-    model: str = "openhermes",
+    model: str = "GPT-4",
     user_id: Optional[str] = None,
     run_id: Optional[str] = None,
     debug_mode: bool = False,
 ) -> Assistant:
     """Get a Local URL RAG Assistant with SingleStore backend."""
+
+    if model == "GPT-4":
+        llm = OpenAIChat(model="gpt-4-turbo-preview")
+    elif model == "Hermes2":
+        llm = Hermes(model="adrienbrault/nous-hermes2pro:Q8_0")
+    elif model == "Claude":
+        llm = Claude(model="claude-3-opus-20240229")
+
     return Assistant(
         name="local_rag_assistant",
         run_id=run_id,
         user_id=user_id,
-        llm=Ollama(model=model),
+        llm=llm,
         storage=local_assistant_storage,
         knowledge_base=local_assistant_knowledge,
         add_chat_history_to_messages=False,