Added grok-4-fast model

app.py

@@ -27,7 +27,7 @@ def load_uploaded_file(uploaded_file):
     return raw_text
 
 # --- Cached Vectorstore with Persistent Cache ---
-@st.cache_data(show_spinner=False)
+@st.cache_resource(show_spinner=False)
 def cached_vectorstore_from_text(raw_text_hash: str, text: str):
     """
     Cache vectorstore based on hash of raw text.
@@ -47,7 +47,7 @@ with st.sidebar:
     model_type = st.radio(
         "Select LLM Backend:",
         options=["groq", "gemini"],
-        format_func=lambda x: "⚡ Groq (Mixtral-8x7B)" if x == "groq" else "🌐 Google Gemini"
+        format_func=lambda x: "⚡ Groq API" if x == "groq" else "🌐 Google Gemini"
     )
 
     uploaded_file = st.file_uploader("Upload a file (optional)", type=["txt", "pdf"])
@@ -145,7 +145,7 @@ if send_triggered:
                             st.code(content.strip(), language="markdown")
 
                 # Clear the input field by rerunning widget with empty value
-                st.experimental_rerun()
+                st.rerun()
 
             except Exception as e:
                 st.error(f"Query failed: {e}")

graph.py

@@ -5,11 +5,12 @@ from typing import TypedDict, Optional, List
 
 from llama_index.core.schema import Document
 from langchain_google_genai import ChatGoogleGenerativeAI
-from langgraph.graph import StateGraph, END
+from langchain_openai import ChatOpenAI
 from llama_index.core import VectorStoreIndex
 from llama_index.core.retrievers import BaseRetriever
 from langchain_groq import ChatGroq
 from transformers import pipeline, BartForConditionalGeneration, BartTokenizer
+from langgraph.graph import StateGraph, END
 
 # --- 1. Define the State for the Graph ---
 class GraphState(TypedDict):
@@ -175,26 +176,26 @@ def build_graph(model_type: str = "groq", retriever=None, summarizer=None):
     If summarizer not provided, initializes a default HuggingFace summarizer.
     """
     
-    if model_type == "groq":
-        api_key = os.getenv("GROQ_API_KEY", "").strip()
-        if not api_key:
-            raise ValueError("GROQ_API_KEY environment variable not set.")
-        llm = ChatGroq(
-            model="x-ai/grok-4-fast:free",  
-            api_key=api_key,
-            temperature=0.7,
-        )
-    elif model_type == "gemini":
-        api_key = os.getenv("GEMINI_API_KEY", "").strip()
-        if not api_key:
-            raise ValueError("GEMINI_API_KEY environment variable not set.")
-        llm = ChatGoogleGenerativeAI(
-            model="gemini-2.0-flash",
-            api_key=api_key,
-            temperature=0.7
-        )
-    else:
-        raise ValueError("Invalid model_type. Choose 'groq' or 'gemini'.")
+    def make_llm(temp: float):
+        if model_type == "groq":
+            api_key = os.getenv("OPENROUTER_API_KEY", "").strip()
+            if not api_key:
+                raise ValueError("OPENROUTER_API_KEY environment variable not set.")
+            return ChatOpenAI(
+                model="x-ai/grok-4-fast:free", 
+                base_url="https://openrouter.ai/api/v1", 
+                api_key=api_key,
+                temperature=temp,
+            )
+        elif model_type == "gemini":
+            api_key = os.getenv("GEMINI_API_KEY", "").strip()
+            if not api_key:
+                raise ValueError("GEMINI_API_KEY environment variable not set.")
+            return ChatGoogleGenerativeAI(
+                model="gemini-2.0-flash",
+                api_key=api_key,
+                temperature=temp,
+            )
     
     def get_default_summarizer():
         tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
@@ -231,6 +232,7 @@ def build_graph(model_type: str = "groq", retriever=None, summarizer=None):
     
     def graph_wrapper(query: str, temperature: float = 0.7, raw_text: str = None, history=None, retriever_override=None):
         active_retriever = retriever_override or retriever
+        llm = make_llm(temperature)
         return compiled_graph.invoke({
             "query": query,
             "retriever": active_retriever.as_retriever() if active_retriever else None,

requirements.txt

@@ -6,6 +6,7 @@ accelerate>=0.30.0
 # LangChain + LangGraph
 langchain>=0.2.1
 langgraph>=0.0.45
+langchain-openai>=0.1.0
 langchain-groq>=0.1.0        
 langchain-google-genai>=1.0.5