Fix langchain_chroma error; pin stable deps

Dockerfile

@@ -2,23 +2,17 @@ FROM python:3.10-slim
 
 WORKDIR /app
 
-# System dependencies
 RUN apt-get update && apt-get install -y \
     git \
     && rm -rf /var/lib/apt/lists/*
 
-# Python dependencies
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Application code
 COPY app.py rag.py ingest.py guardrails.py config.py ./
 
-# Create empty kb_docs directory (PDFs added later via HF UI)
 RUN mkdir -p kb_docs
 
-# Hugging Face Spaces port
 EXPOSE 7860
 
-# Start FastAPI
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

ingest.py

@@ -11,8 +11,8 @@ def load_and_split_docs(path="kb_docs"):
         glob="**/*.pdf",
         loader_cls=PyPDFLoader
     )
-    docs = loader.load()
 
+    docs = loader.load()
     if not docs:
         return []
 
@@ -20,4 +20,5 @@ def load_and_split_docs(path="kb_docs"):
         chunk_size=800,
         chunk_overlap=100
     )
+
     return splitter.split_documents(docs)

rag.py

@@ -1,5 +1,5 @@
+from langchain_community.vectorstores import Chroma
 from langchain_huggingface import HuggingFaceEmbeddings, ChatHuggingFace
-from langchain_chroma import Chroma
 from langchain.schema import SystemMessage, HumanMessage
 
 from ingest import load_and_split_docs
@@ -14,7 +14,7 @@ embeddings = HuggingFaceEmbeddings(
 
 if documents:
     vectorstore = Chroma.from_documents(
-        documents,
+        documents=documents,
         embedding=embeddings
     )
     retriever = vectorstore.as_retriever(search_kwargs={"k": 3})
@@ -32,14 +32,14 @@ def ask_rag_with_status(question: str):
     if not retriever:
         return {
             "status": ["⚠️ No documents uploaded yet"],
-            "answer": "Please upload PDF files to the kb_docs folder."
+            "answer": "Please upload PDF files to the kb_docs folder and restart the Space."
         }
 
     docs = retriever.get_relevant_documents(question)
     context = "\n\n".join(d.page_content for d in docs)
 
     messages = [
-        SystemMessage(content="Answer using the provided context."),
+        SystemMessage(content="Answer using only the provided context."),
         HumanMessage(content=f"Context:\n{context}\n\nQuestion: {question}")
     ]
 

requirements.txt

@@ -3,12 +3,12 @@ uvicorn
 pydantic
 python-dotenv
 
-langchain
-langchain-community
-langchain-core
-langchain-huggingface
+langchain==0.2.17
+langchain-community==0.2.17
+langchain-huggingface==0.1.0
 
-chromadb
+chromadb==0.5.5
 sentence-transformers
+
 pypdf
-huggingface_hub
+huggingface_hub>=0.33.4,<1.0.0