moving code to tools (#65)

* moving code

---------

Co-authored-by: Erick Friis <[email protected]>

libs/tools/.gitignore

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+__pycache__

libs/tools/LICENSE

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+MIT License
+
+Copyright (c) 2024 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/tools/Makefile

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+.PHONY: all format lint test tests integration_tests docker_tests help extended_tests
+
+# Default target executed when no arguments are given to make.
+all: help
+
+# Define a variable for the test file path.
+TEST_FILE ?= tests/unit_tests/
+
+integration_test integration_tests: TEST_FILE = tests/integration_tests/
+
+test tests integration_test integration_tests:
+	poetry run pytest --release $(TEST_FILE)
+
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint format: PYTHON_FILES=.
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/tools --name-only --diff-filter=d main | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=langchain_google_tools
+lint_tests: PYTHON_FILES=tests
+lint_tests: MYPY_CACHE=.mypy_cache_test
+
+lint lint_diff lint_package lint_tests:
+	poetry run ruff .
+	poetry run ruff format $(PYTHON_FILES) --diff
+	poetry run ruff --select I $(PYTHON_FILES)
+	mkdir $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+
+format format_diff:
+	poetry run ruff format $(PYTHON_FILES)
+	poetry run ruff --select I --fix $(PYTHON_FILES)
+
+spell_check:
+	poetry run codespell --toml pyproject.toml
+
+spell_fix:
+	poetry run codespell --toml pyproject.toml -w
+
+check_imports: $(shell find langchain_google_tools -name '*.py')
+	poetry run python ./scripts/check_imports.py $^
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'check_imports				- check imports'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'
+	@echo 'test                         - run unit tests'
+	@echo 'tests                        - run unit tests'
+	@echo 'test TEST_FILE=<test_file>   - run all tests in file'

libs/tools/README.md

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+# langchain-google-genai
+
+This package contains the LangChain integrations for Gemini through their generative-ai SDK.
+
+## Installation
+
+```bash
+pip install -U langchain-google-genai
+```
+
+### Image utilities
+To use image utility methods, like loading images from GCS urls, install with extras group 'images':
+
+```bash
+pip install -e "langchain-google-genai[images]"
+```
+
+## Chat Models
+
+This package contains the `ChatGoogleGenerativeAI` class, which is the recommended way to interface with the Google Gemini series of models.
+
+To use, install the requirements, and configure your environment.
+
+```bash
+export GOOGLE_API_KEY=your-api-key
+```
+
+Then initialize
+
+```python
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+llm = ChatGoogleGenerativeAI(model="gemini-pro")
+llm.invoke("Sing a ballad of LangChain.")
+```
+
+#### Multimodal inputs
+
+Gemini vision model supports image inputs when providing a single chat message. Example:
+
+```
+from langchain_core.messages import HumanMessage
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+llm = ChatGoogleGenerativeAI(model="gemini-pro-vision")
+# example
+message = HumanMessage(
+    content=[
+        {
+            "type": "text",
+            "text": "What's in this image?",
+        },  # You can optionally provide text parts
+        {"type": "image_url", "image_url": "https://picsum.photos/seed/picsum/200/300"},
+    ]
+)
+llm.invoke([message])
+```
+
+The value of `image_url` can be any of the following:
+
+- A public image URL
+- An accessible gcs file (e.g., "gcs://path/to/file.png")
+- A local file path
+- A base64 encoded image (e.g., `data:image/png;base64,abcd124`)
+- A PIL image
+
+
+
+## Embeddings
+
+This package also adds support for google's embeddings models.
+
+```
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+
+embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
+embeddings.embed_query("hello, world!")
+```
+
+## Semantic Retrieval
+
+Enables retrieval augmented generation (RAG) in your application.
+
+```
+# Create a new store for housing your documents.
+corpus_store = GoogleVectorStore.create_corpus(display_name="My Corpus")
+
+# Create a new document under the above corpus.
+document_store = GoogleVectorStore.create_document(
+    corpus_id=corpus_store.corpus_id, display_name="My Document"
+)
+
+# Upload some texts to the document.
+text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0)
+for file in DirectoryLoader(path="data/").load():
+    documents = text_splitter.split_documents([file])
+    document_store.add_documents(documents)
+
+# Talk to your entire corpus with possibly many documents. 
+aqa = corpus_store.as_aqa()
+answer = aqa.invoke("What is the meaning of life?")
+
+# Read the response along with the attributed passages and answerability.
+print(response.answer)
+print(response.attributed_passages)
+print(response.answerable_probability)
+```

libs/tools/langchain_google_tools/__init__.py

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+from langchain_google_tools.bigquery_vector_search import BigQueryVectorSearch
+from langchain_google_tools.documentai_warehouse import DocumentAIWarehouseRetriever
+from langchain_google_tools.gmail.loader import GMailLoader
+from langchain_google_tools.gmail.toolkit import GmailToolkit
+from langchain_google_tools.vertex_ai_search import (
+    VertexAIMultiTurnSearchRetriever,
+    VertexAISearchRetriever,
+)
+
+__all__ = [
+    "BigQueryVectorSearch",
+    "DocumentAIWarehouseRetriever",
+    "GMailLoader",
+    "GmailToolkit",
+    "VertexAIMultiTurnSearchRetriever",
+    "VertexAISearchRetriever",
+]