Update pygpt4all in requirements.txt

.gitignore

@@ -7,3 +7,4 @@ __pycache__
 .yarn
 .chroma
 .pnp.cjs
+models

ggml-try.py

@@ -0,0 +1,81 @@
+"""Adopted from https://github.com/imartinez/privateGPT/blob/main/privateGPT.py
+
+https://raw.githubusercontent.com/imartinez/privateGPT/main/requirements.txt
+
+-c https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin
+"""
+from dotenv import load_dotenv, dotenv_values
+from langchain.chains import RetrievalQA
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+from langchain.vectorstores import Chroma
+from langchain.llms import GPT4All, LlamaCpp
+import os
+import argparse
+import time
+
+from types import SimpleNamespace
+from chromadb.config import Settings
+
+# embeddings_model_name = os.environ.get("EMBEDDINGS_MODEL_NAME")
+# persist_directory = os.environ.get('PERSIST_DIRECTORY')
+
+# load_dotenv()
+# model_type = os.environ.get('MODEL_TYPE')
+# model_path = os.environ.get('MODEL_PATH')
+# model_n_ctx = os.environ.get('MODEL_N_CTX')
+# model_n_batch = int(os.environ.get('MODEL_N_BATCH',8))
+# target_source_chunks = int(os.environ.get('TARGET_SOURCE_CHUNKS',4))
+
+settings = dict([('PERSIST_DIRECTORY', 'db1'),
+             ('MODEL_TYPE', 'GPT4All'),
+             ('MODEL_PATH', 'models/ggml-gpt4all-j-v1.3-groovy.bin'),
+             ('EMBEDDINGS_MODEL_NAME', 'all-MiniLM-L6-v2'),
+             ('MODEL_N_CTX', '1000'),
+             ('MODEL_N_BATCH', '8'),
+             ('TARGET_SOURCE_CHUNKS', '4')])
+
+# models/ggml-gpt4all-j-v1.3-groovy.bin  ~5G
+
+# all-MiniLM-L6-v2 () or
+embeddings_model_name = settings.get("EMBEDDINGS_MODEL_NAME")
+
+# embeddings_model_name = 'all-MiniLM-L6-v2'
+embeddings_model_name = 'paraphrase-multilingual-mpnet-base-v2'
+
+persist_directory = settings.get('PERSIST_DIRECTORY')
+
+model_type = settings.get('MODEL_TYPE')
+model_path = settings.get('MODEL_PATH')
+model_n_ctx = settings.get('MODEL_N_CTX')
+model_n_batch = int(settings.get('MODEL_N_BATCH',8))
+target_source_chunks = int(settings.get('TARGET_SOURCE_CHUNKS',4))
+
+# Define the Chroma settings
+CHROMA_SETTINGS = Settings(
+        chroma_db_impl='duckdb+parquet',
+        persist_directory=persist_directory,
+        anonymized_telemetry=False
+)
+
+args = SimpleNamespace(hide_source=False, mute_stream=False)
+
+embeddings = HuggingFaceEmbeddings(model_name=embeddings_model_name)
+db = Chroma(persist_directory=persist_directory, embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
+
+retriever = db.as_retriever(search_kwargs={"k": target_source_chunks})
+# activate/deactivate the streaming StdOut callback for LLMs
+callbacks = [] if args.mute_stream else [StreamingStdOutCallbackHandler()]
+# Prepare the LLM
+match model_type:
+    case "LlamaCpp":
+        llm = LlamaCpp(model_path=model_path, n_ctx=model_n_ctx, n_batch=model_n_batch, callbacks=callbacks, verbose=False)
+    case "GPT4All":
+        llm = GPT4All(model=model_path, n_ctx=model_n_ctx, backend='gptj', n_batch=model_n_batch, callbacks=callbacks, verbose=False)
+    case _default:
+        # raise exception if model_type is not supported
+        raise Exception(f"Model type {model_type} is not supported. Please choose one of the following: LlamaCpp, GPT4All")
+
+# need about 5G RAM
+
+qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not args.hide_source)

requirements-cuda.txt

@@ -27,4 +27,5 @@ docx2txt
 
 safetensors
 about-time
-openai
+openai
+pygpt4all

requirements-win10-cpu.txt

@@ -30,4 +30,6 @@ docx2txt
 about-time
 openai
 more-itertools
-# tqdm
+# tqdm
+
+pygpt4all

requirements.txt

@@ -28,4 +28,7 @@ docx2txt
 about-time
 openai
 more-itertools
-# tqdm
+
+#
+wheel
+pygpt4all