Merge branch 'master' into wfh/add_llm_output_to_adapter

This commit is contained in:
William Fu-Hinthorn
2023-11-07 11:19:37 -08:00
19 changed files with 2946 additions and 178 deletions

File diff suppressed because one or more lines are too long

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View File

@@ -6,9 +6,8 @@ from typing import Sequence
from fastapi import FastAPI
from langserve import add_routes
from langserve.packages import get_langserve_export
from langchain_cli.utils.packages import get_package_root
from langchain_cli.utils.packages import get_langserve_export, get_package_root
def create_demo_server(

View File

@@ -9,7 +9,6 @@ from pathlib import Path
from typing import Dict, List, Optional, Tuple
import typer
from langserve.packages import get_langserve_export
from typing_extensions import Annotated
from langchain_cli.utils.events import create_events
@@ -19,7 +18,15 @@ from langchain_cli.utils.git import (
parse_dependencies,
update_repo,
)
from langchain_cli.utils.packages import get_package_root
from langchain_cli.utils.packages import (
LangServeExport,
get_langserve_export,
get_package_root,
)
from langchain_cli.utils.pyproject import (
add_dependencies_to_pyproject_toml,
remove_dependencies_from_pyproject_toml,
)
REPO_DIR = Path(typer.get_app_dir("langchain")) / "git_repos"
@@ -98,7 +105,8 @@ def add(
grouped[key_tup] = lst
installed_destination_paths: List[Path] = []
installed_exports: List[Dict] = []
installed_destination_names: List[str] = []
installed_exports: List[LangServeExport] = []
for (git, ref), group_deps in grouped.items():
if len(group_deps) == 1:
@@ -131,23 +139,38 @@ def add(
copy_repo(source_path, destination_path)
typer.echo(f" - Downloaded {dep['subdirectory']} to {inner_api_path}")
installed_destination_paths.append(destination_path)
installed_destination_names.append(inner_api_path)
installed_exports.append(langserve_export)
if len(installed_destination_paths) == 0:
typer.echo("No packages installed. Exiting.")
return
cwd = Path.cwd()
installed_desination_strs = [
str(p.relative_to(cwd)) for p in installed_destination_paths
]
cmd = ["pip", "install", "-e"] + installed_desination_strs
cmd_str = " \\\n ".join(installed_desination_strs)
install_str = f"To install:\n\npip install -e \\\n {cmd_str}"
typer.echo(install_str)
try:
add_dependencies_to_pyproject_toml(
project_root / "pyproject.toml",
zip(installed_destination_names, installed_destination_paths),
)
except Exception:
# Can fail if user modified/removed pyproject.toml
typer.echo("Failed to add dependencies to pyproject.toml, continuing...")
if typer.confirm("Run it?"):
subprocess.run(cmd, cwd=cwd)
try:
cwd = Path.cwd()
installed_destination_strs = [
str(p.relative_to(cwd)) for p in installed_destination_paths
]
except ValueError:
# Can fail if the cwd is not a parent of the package
typer.echo("Failed to print install command, continuing...")
else:
cmd = ["pip", "install", "-e"] + installed_destination_strs
cmd_str = " \\\n ".join(installed_destination_strs)
install_str = f"To install:\n\npip install -e \\\n {cmd_str}"
typer.echo(install_str)
if typer.confirm("Run it?"):
subprocess.run(cmd, cwd=cwd)
if typer.confirm("\nGenerate route code for these packages?", default=True):
chain_names = []
@@ -187,20 +210,43 @@ def add(
@app_cli.command()
def remove(
api_paths: Annotated[List[str], typer.Argument(help="The API paths to remove")],
*,
project_dir: Annotated[
Optional[Path], typer.Option(help="The project directory")
] = None,
):
"""
Removes the specified package from the current LangServe app.
"""
for api_path in api_paths:
package_dir = Path.cwd() / "packages" / api_path
if not package_dir.exists():
typer.echo(f"Endpoint {api_path} does not exist. Skipping...")
continue
pyproject = package_dir / "pyproject.toml"
langserve_export = get_langserve_export(pyproject)
typer.echo(f"Removing {langserve_export['package_name']}...")
shutil.rmtree(package_dir)
project_root = get_package_root(project_dir)
project_pyproject = project_root / "pyproject.toml"
package_root = project_root / "packages"
remove_deps: List[str] = []
for api_path in api_paths:
package_dir = package_root / api_path
if not package_dir.exists():
typer.echo(f"Package {api_path} does not exist. Skipping...")
continue
try:
pyproject = package_dir / "pyproject.toml"
langserve_export = get_langserve_export(pyproject)
typer.echo(f"Removing {langserve_export['package_name']}...")
shutil.rmtree(package_dir)
remove_deps.append(api_path)
except Exception:
pass
try:
remove_dependencies_from_pyproject_toml(project_pyproject, remove_deps)
except Exception:
# Can fail if user modified/removed pyproject.toml
typer.echo("Failed to remove dependencies from pyproject.toml.")
@app_cli.command()

View File

@@ -9,10 +9,9 @@ from pathlib import Path
from typing import Optional
import typer
from langserve.packages import get_langserve_export
from typing_extensions import Annotated
from langchain_cli.utils.packages import get_package_root
from langchain_cli.utils.packages import get_langserve_export, get_package_root
package_cli = typer.Typer(no_args_is_help=True, add_completion=False)

View File

@@ -1,5 +1,5 @@
[tool.poetry]
name = "langservehub-template"
name = "__app_name__"
version = "0.1.0"
description = ""
authors = ["Your Name <you@example.com>"]
@@ -7,16 +7,12 @@ readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
sse-starlette = "^1.6.5"
tomli-w = "^1.0.0"
uvicorn = "^0.23.2"
fastapi = "^0.103.2"
langserve = ">=0.0.16"
langserve = {extras = ["server"], version = ">=0.0.22"}
[tool.poetry.group.dev.dependencies]
uvicorn = "^0.23.2"
pygithub = "^2.1.1"
langchain-cli = ">=0.0.15"
[build-system]
requires = ["poetry-core"]

View File

@@ -1,5 +1,7 @@
from pathlib import Path
from typing import Optional, Set
from typing import Any, Dict, Optional, Set, TypedDict
from tomlkit import load
def get_package_root(cwd: Optional[Path] = None) -> Path:
@@ -14,3 +16,30 @@ def get_package_root(cwd: Optional[Path] = None) -> Path:
return package_root
package_root = package_root.parent
raise FileNotFoundError("No pyproject.toml found")
class LangServeExport(TypedDict):
"""
Fields from pyproject.toml that are relevant to LangServe
Attributes:
module: The module to import from, tool.langserve.export_module
attr: The attribute to import from the module, tool.langserve.export_attr
package_name: The name of the package, tool.poetry.name
"""
module: str
attr: str
package_name: str
def get_langserve_export(filepath: Path) -> LangServeExport:
with open(filepath) as f:
data: Dict[str, Any] = load(f)
try:
module = data["tool"]["langserve"]["export_module"]
attr = data["tool"]["langserve"]["export_attr"]
package_name = data["tool"]["poetry"]["name"]
except KeyError as e:
raise KeyError("Invalid LangServe PyProject.toml") from e
return LangServeExport(module=module, attr=attr, package_name=package_name)

View File

@@ -0,0 +1,45 @@
from pathlib import Path
from typing import Any, Dict, Iterable
from tomlkit import dump, inline_table, load
from tomlkit.items import InlineTable
def _get_dep_inline_table(path: Path) -> InlineTable:
dep = inline_table()
dep.update({"path": str(path), "develop": True})
return dep
def add_dependencies_to_pyproject_toml(
pyproject_toml: Path, local_editable_dependencies: Iterable[tuple[str, Path]]
) -> None:
"""Add dependencies to pyproject.toml."""
with open(pyproject_toml, encoding="utf-8") as f:
# tomlkit types aren't amazing - treat as Dict instead
pyproject: Dict[str, Any] = load(f)
pyproject["tool"]["poetry"]["dependencies"].update(
{
name: _get_dep_inline_table(loc.relative_to(pyproject_toml.parent))
for name, loc in local_editable_dependencies
}
)
with open(pyproject_toml, "w", encoding="utf-8") as f:
dump(pyproject, f)
def remove_dependencies_from_pyproject_toml(
pyproject_toml: Path, local_editable_dependencies: Iterable[str]
) -> None:
"""Remove dependencies from pyproject.toml."""
with open(pyproject_toml, encoding="utf-8") as f:
pyproject: Dict[str, Any] = load(f)
# tomlkit types aren't amazing - treat as Dict instead
dependencies = pyproject["tool"]["poetry"]["dependencies"]
for name in local_editable_dependencies:
try:
del dependencies[name]
except KeyError:
pass
with open(pyproject_toml, "w", encoding="utf-8") as f:
dump(pyproject, f)

337
libs/cli/poetry.lock generated
View File

@@ -185,101 +185,101 @@ files = [
[[package]]
name = "charset-normalizer"
version = "3.3.1"
version = "3.3.2"
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
optional = false
python-versions = ">=3.7.0"
files = [
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]
[[package]]
@@ -1224,12 +1225,56 @@ files = [
[[package]]
name = "sqlalchemy"
version = "2.0.22"
version = "2.0.23"
description = "Database Abstraction Library"
optional = false
python-versions = ">=3.7"
files = [
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{file = "SQLAlchemy-2.0.23.tar.gz", hash = "sha256:c1bda93cbbe4aa2aa0aa8655c5aeda505cd219ff3e8da91d1d329e143e4aff69"},
]
[package.dependencies]
@@ -1238,7 +1283,8 @@ typing-extensions = ">=4.2.0"
[package.extras]
aiomysql = ["aiomysql (>=0.2.0)", "greenlet (!=0.4.17)"]
aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
asyncio = ["greenlet (!=0.4.17)"]
asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
@@ -1248,7 +1294,7 @@ mssql-pyodbc = ["pyodbc"]
mypy = ["mypy (>=0.910)"]
mysql = ["mysqlclient (>=1.4.0)"]
mysql-connector = ["mysql-connector-python"]
oracle = ["cx_oracle (>=7)"]
oracle = ["cx-oracle (>=8)"]
oracle-oracledb = ["oracledb (>=1.0.1)"]
postgresql = ["psycopg2 (>=2.7)"]
postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
@@ -1258,7 +1304,7 @@ postgresql-psycopg2binary = ["psycopg2-binary"]
postgresql-psycopg2cffi = ["psycopg2cffi"]
postgresql-psycopgbinary = ["psycopg[binary] (>=3.0.7)"]
pymysql = ["pymysql"]
sqlcipher = ["sqlcipher3_binary"]
sqlcipher = ["sqlcipher3-binary"]
[[package]]
name = "sse-starlette"
@@ -1317,6 +1363,17 @@ files = [
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
]
[[package]]
name = "tomlkit"
version = "0.12.2"
description = "Style preserving TOML library"
optional = false
python-versions = ">=3.7"
files = [
{file = "tomlkit-0.12.2-py3-none-any.whl", hash = "sha256:eeea7ac7563faeab0a1ed8fe12c2e5a51c61f933f2502f7e9db0241a65163ad0"},
{file = "tomlkit-0.12.2.tar.gz", hash = "sha256:df32fab589a81f0d7dc525a4267b6d7a64ee99619cbd1eeb0fae32c1dd426977"},
]
[[package]]
name = "typer"
version = "0.9.0"
@@ -1535,4 +1592,4 @@ serve = []
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "0952bdae96fcb733d79128960e2d6ed6309b4366f9781ec142320aeccaeec07a"
content-hash = "9aa00d7144f6e0dea9f8e5df25d0aa69117809ba4eea7d3d0664cd3fcccab2f4"

View File

@@ -8,11 +8,10 @@ readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
typer = {extras = ["all"], version = "^0.9.0"}
tomli = "^2.0.1"
gitpython = "^3.1.40"
langserve = {extras = ["all"], version = ">=0.0.16"}
fastapi = "^0.104.0"
uvicorn = "^0.23.2"
tomlkit = "^0.12.2"
[tool.poetry.scripts]
langchain = "langchain_cli.cli:app"

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain"
version = "0.0.331rc1"
version = "0.0.331rc2"
description = "Building applications with LLMs through composability"
authors = []
license = "MIT"

View File

@@ -0,0 +1,92 @@
# neo4j-cypher-memory
This template allows you to have conversations with a Neo4j graph database in natural language, using an OpenAI LLM.
It transforms a natural language question into a Cypher query (used to fetch data from Neo4j databases), executes the query, and provides a natural language response based on the query results.
Additionally, it features a conversational memory module that stores the dialogue history in the Neo4j graph database.
The conversation memory is uniquely maintained for each user session, ensuring personalized interactions.
To facilitate this, please supply both the `user_id` and `session_id` when using the conversation chain.
## Environment Setup
Define the following environment variables:
```
OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
NEO4J_URI=<YOUR_NEO4J_URI>
NEO4J_USERNAME=<YOUR_NEO4J_USERNAME>
NEO4J_PASSWORD=<YOUR_NEO4J_PASSWORD>
```
## Neo4j database setup
There are a number of ways to set up a Neo4j database.
### Neo4j Aura
Neo4j AuraDB is a fully managed cloud graph database service.
Create a free instance on [Neo4j Aura](https://neo4j.com/cloud/platform/aura-graph-database?utm_source=langchain&utm_content=langserve).
When you initiate a free database instance, you'll receive credentials to access the database.
## Populating with data
If you want to populate the DB with some example data, you can run `python ingest.py`.
This script will populate the database with sample movie data.
## Usage
To use this package, you should first have the LangChain CLI installed:
```shell
pip install -U langchain-cli
```
To create a new LangChain project and install this as the only package, you can do:
```shell
langchain app new my-app --package neo4j-cypher-memory
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add neo4j-cypher-memory
```
And add the following code to your `server.py` file:
```python
from neo4j_cypher_memory import chain as neo4j_cypher_memory_chain
add_routes(app, neo4j_cypher_memory_chain, path="/neo4j-cypher-memory")
```
(Optional) Let's now configure LangSmith.
LangSmith will help us trace, monitor and debug LangChain applications.
LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
If you don't have access, you can skip this section
```shell
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
```
If you are inside this directory, then you can spin up a LangServe instance directly by:
```shell
langchain serve
```
This will start the FastAPI app with a server is running locally at
[http://localhost:8000](http://localhost:8000)
We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
We can access the playground at [http://127.0.0.1:8000/neo4j_cypher_memory/playground](http://127.0.0.1:8000/neo4j_cypher/playground)
We can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/neo4j-cypher-memory")
```

View File

@@ -0,0 +1,16 @@
from langchain.graphs import Neo4jGraph
graph = Neo4jGraph()
graph.query(
"""
MERGE (m:Movie {name:"Top Gun"})
WITH m
UNWIND ["Tom Cruise", "Val Kilmer", "Anthony Edwards", "Meg Ryan"] AS actor
MERGE (a:Actor {name:actor})
MERGE (a)-[:ACTED_IN]->(m)
WITH a
WHERE a.name = "Tom Cruise"
MERGE (a)-[:ACTED_IN]->(:Movie {name:"Mission Impossible"})
"""
)

View File

@@ -0,0 +1,23 @@
from neo4j_cypher_memory.chain import chain
if __name__ == "__main__":
original_query = "Who played in Top Gun?"
print(
chain.invoke(
{
"question": original_query,
"user_id": "user_123",
"session_id": "session_1",
}
)
)
follow_up_query = "Did they play in any other movies?"
print(
chain.invoke(
{
"question": follow_up_query,
"user_id": "user_123",
"session_id": "session_1",
}
)
)

View File

@@ -0,0 +1,3 @@
from neo4j_cypher_memory.chain import chain
__all__ = ["chain"]

View File

@@ -0,0 +1,146 @@
from typing import Any, Dict, List
from langchain.chains.graph_qa.cypher_utils import CypherQueryCorrector, Schema
from langchain.chat_models import ChatOpenAI
from langchain.graphs import Neo4jGraph
from langchain.memory import ChatMessageHistory
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.pydantic_v1 import BaseModel
from langchain.schema.output_parser import StrOutputParser
from langchain.schema.runnable import RunnablePassthrough
# Connection to Neo4j
graph = Neo4jGraph()
# Cypher validation tool for relationship directions
corrector_schema = [
Schema(el["start"], el["type"], el["end"])
for el in graph.structured_schema.get("relationships")
]
cypher_validation = CypherQueryCorrector(corrector_schema)
# LLMs
cypher_llm = ChatOpenAI(model_name="gpt-4", temperature=0.0)
qa_llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.0)
def convert_messages(input: List[Dict[str, Any]]) -> ChatMessageHistory:
history = ChatMessageHistory()
for item in input:
history.add_user_message(item["result"]["question"])
history.add_ai_message(item["result"]["answer"])
return history
def get_history(input: Dict[str, Any]) -> ChatMessageHistory:
input.pop("question")
# Lookback conversation window
window = 3
data = graph.query(
"""
MATCH (u:User {id:$user_id})-[:HAS_SESSION]->(s:Session {id:$session_id}),
(s)-[:LAST_MESSAGE]->(last_message)
MATCH p=(last_message)<-[:NEXT*0.."""
+ str(window)
+ """]-()
WITH p, length(p) AS length
ORDER BY length DESC LIMIT 1
UNWIND reverse(nodes(p)) AS node
MATCH (node)-[:HAS_ANSWER]->(answer)
RETURN {question:node.text, answer:answer.text} AS result
""",
params=input,
)
history = convert_messages(data)
return history.messages
def save_history(input):
input.pop("response")
# store history to database
graph.query(
"""MERGE (u:User {id: $user_id})
WITH u
OPTIONAL MATCH (u)-[:HAS_SESSION]->(s:Session{id: $session_id}),
(s)-[l:LAST_MESSAGE]->(last_message)
FOREACH (_ IN CASE WHEN last_message IS NULL THEN [1] ELSE [] END |
CREATE (u)-[:HAS_SESSION]->(s1:Session {id:$session_id}),
(s1)-[:LAST_MESSAGE]->(q:Question {text:$question, cypher:$query, date:datetime()}),
(q)-[:HAS_ANSWER]->(:Answer {text:$output}))
FOREACH (_ IN CASE WHEN last_message IS NOT NULL THEN [1] ELSE [] END |
CREATE (last_message)-[:NEXT]->(q:Question
{text:$question, cypher:$query, date:datetime()}),
(q)-[:HAS_ANSWER]->(:Answer {text:$output}),
(s)-[:LAST_MESSAGE]->(q)
DELETE l) """,
params=input,
)
# Return LLM response to the chain
return input["output"]
# Generate Cypher statement based on natural language input
cypher_template = """This is important for my career.
Based on the Neo4j graph schema below, write a Cypher query that would answer the user's question:
{schema}
Question: {question}
Cypher query:""" # noqa: E501
cypher_prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"Given an input question, convert it to a Cypher query. No pre-amble.",
),
MessagesPlaceholder(variable_name="history"),
("human", cypher_template),
]
)
cypher_response = (
RunnablePassthrough.assign(schema=lambda _: graph.get_schema, history=get_history)
| cypher_prompt
| cypher_llm.bind(stop=["\nCypherResult:"])
| StrOutputParser()
)
# Generate natural language response based on database results
response_template = """Based on the the question, Cypher query, and Cypher response, write a natural language response:
Question: {question}
Cypher query: {query}
Cypher Response: {response}""" # noqa: E501
response_prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"Given an input question and Cypher response, convert it to a "
"natural language answer. No pre-amble.",
),
("human", response_template),
]
)
chain = (
RunnablePassthrough.assign(query=cypher_response)
| RunnablePassthrough.assign(
response=lambda x: graph.query(cypher_validation(x["query"])),
)
| RunnablePassthrough.assign(
output=response_prompt | qa_llm | StrOutputParser(),
)
| save_history
)
# Add typing for input
class Question(BaseModel):
question: str
user_id: str
session_id: str
chain = chain.with_types(input_type=Question)

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[tool.poetry]
name = "neo4j-cypher-memory"
version = "0.1.0"
description = ""
authors = [
"Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = ">=0.0.325"
neo4j = ">5.12"
openai = "^0.28.1"
[tool.poetry.group.dev.dependencies]
langchain-cli = ">=0.0.15"
[tool.langserve]
export_module = "neo4j_cypher_memory"
export_attr = "chain"
[build-system]
requires = [
"poetry-core",
]
build-backend = "poetry.core.masonry.api"