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Andrei Bratu
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Merge branch 'master' into flow-complete-dx
2 parents 0919d30 + a71c816 commit 190233f

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‎.fernignore‎

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src/humanloop/evals
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src/humanloop/prompt_utils.py
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src/humanloop/path_utils.py
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src/humanloop/client.py
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src/humanloop/overload.py
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src/humanloop/context.py

‎README.md‎

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yield chunk
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```
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## Local File Development
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Humanloop allows you to clone files from your Humanloop workspace to your local filesystem and use them in your code.
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### Syncing Files with the CLI
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```bash
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# Pull all files
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humanloop pull
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# Pull from a directory
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humanloop pull --path="examples/chat"
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# Pull a specific file
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humanloop pull --path="examples/chat/basic.prompt"
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# Pull versions deployed to specific environment
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humanloop pull --environment="production"
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```
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### Using Local Files in the SDK
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To use local files in your code:
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```python
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# Enable local file support
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client = Humanloop(
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api_key="YOUR_API_KEY",
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use_local_files=True
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)
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# Use a local prompt file
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response = client.prompts.call(
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path="examples/chat/basic",
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inputs={"query": "Hello world"}
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)
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```
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For detailed instructions on syncing, see our [Guide to Syncing and Using Local Files](https://humanloop.com/docs/v5/guides/prompts/syncing-files).
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For information about the `.prompt` and `.agent` file formats, see our [File Format Reference](https://humanloop.com/docs/v5/reference/prompt-and-agent-files).
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## Pagination
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Paginated requests will return a `SyncPager` or `AsyncPager`, which can be used as generators for the underlying object.
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You can override the `httpx` client to customize it for your use-case. Some common use-cases include support for proxies
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and transports.
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```python
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import httpx
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from humanloop import Humanloop

‎poetry.lock‎

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‎pyproject.toml‎

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[tool.poetry]
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name = "humanloop"
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version = "0.8.39"
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version = "0.8.40b3"
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description = ""
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readme = "README.md"
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authors = []

‎src/humanloop/cli/__main__.py‎

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from dotenv import load_dotenv
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from humanloop import Humanloop
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from humanloop.sync.sync_client import SyncClient
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from humanloop.sync.file_syncer import FileSyncer
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# Set up logging
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logger = logging.getLogger(__name__)
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"-p",
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help="Path in the Humanloop workspace to pull from (file or directory). You can pull an entire directory (e.g. 'my/directory') "
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"or a specific file (e.g. 'my/directory/my_prompt.prompt'). When pulling a directory, all files within that directory and its subdirectories will be included. "
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"Paths should not contain leading or trailing slashes. "
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"If not specified, pulls from the root of the remote workspace.",
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default=None,
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)
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Currently only supports syncing Prompt and Agent files. Other file types will be skipped."""
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client = get_client(api_key, env_file, base_url)
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sync_client = SyncClient(
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# Although pull() is available on the Humanloop client, we instantiate FileSyncer separately to control its log level.
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# This allows CLI users to toggle between detailed logging (--verbose) and minimal output without affecting the
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# main Humanloop client logger. The FileSyncer uses its own logger namespace (humanloop.sdk.file_syncer), making this
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# modification isolated from the client's OpenTelemetry setup. This client instance is short-lived and only
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# exists for the duration of the CLI command execution.
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file_syncer = FileSyncer(
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client, base_dir=local_files_directory, log_level=logging.DEBUG if verbose else logging.WARNING
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)
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click.echo(click.style(f"Environment: {environment or '(default)'}", fg=INFO_COLOR))
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start_time = time.time()
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successful_files, failed_files = sync_client.pull(path, environment)
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successful_files, failed_files = file_syncer.pull(path, environment)
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duration_ms = int((time.time() - start_time) * 1000)
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# Determine if the operation was successful based on failed_files

‎src/humanloop/client.py‎

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import logging
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import os
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import typing
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from typing import Any, List, Optional, Sequence, Tuple
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import logging
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import httpx
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from opentelemetry.sdk.resources import Resource
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.trace import Tracer
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from humanloop.base_client import AsyncBaseHumanloop, BaseHumanloop
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from humanloop.core.client_wrapper import SyncClientWrapper
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from humanloop.decorators.flow import flow as flow_decorator_factory
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from humanloop.decorators.prompt import prompt_decorator_factory
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from humanloop.decorators.tool import tool_decorator_factory as tool_decorator_factory
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from humanloop.environment import HumanloopEnvironment
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from humanloop.evals import run_eval
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from humanloop.evals.types import (
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DatasetEvalConfig,
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EvaluatorEvalConfig,
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EvaluatorCheck,
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EvaluatorEvalConfig,
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FileEvalConfig,
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)
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from humanloop.base_client import AsyncBaseHumanloop, BaseHumanloop
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from humanloop.overload import overload_client
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from humanloop.decorators.flow import flow as flow_decorator_factory
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from humanloop.decorators.prompt import prompt_decorator_factory
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from humanloop.decorators.tool import tool_decorator_factory as tool_decorator_factory
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from humanloop.environment import HumanloopEnvironment
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from humanloop.evaluations.client import EvaluationsClient
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from humanloop.otel import instrument_provider
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from humanloop.otel.exporter import HumanloopSpanExporter
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from humanloop.otel.processor import HumanloopSpanProcessor
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from humanloop.overload import overload_client
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from humanloop.prompt_utils import populate_template
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from humanloop.prompts.client import PromptsClient
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from humanloop.sync.sync_client import SyncClient, DEFAULT_CACHE_SIZE
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from humanloop.sync.file_syncer import DEFAULT_CACHE_SIZE, FileSyncer
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logger = logging.getLogger("humanloop.sdk")
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)
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# Check if cache_size is non-default but use_local_files is False
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self._sync_client = SyncClient(client=self, base_dir=local_files_directory, cache_size=cache_size)
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self._file_syncer = FileSyncer(client=self, base_dir=local_files_directory, cache_size=cache_size)
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eval_client = ExtendedEvalsClient(client_wrapper=self._client_wrapper)
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eval_client.client = self
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self.evaluations = eval_client
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self.prompts = ExtendedPromptsClient(client_wrapper=self._client_wrapper)
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# Overload the .log method of the clients to be aware of Evaluation Context
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# and the @flow decorator providing the trace_id
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# Additionally, call and log methods are overloaded in the prompts and agents client to support the use of local files
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self.prompts = overload_client(
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client=self.prompts, sync_client=self._sync_client, use_local_files=self.use_local_files
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client=self.prompts, file_syncer=self._file_syncer, use_local_files=self.use_local_files
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)
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self.agents = overload_client(
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client=self.agents, sync_client=self._sync_client, use_local_files=self.use_local_files
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client=self.agents, file_syncer=self._file_syncer, use_local_files=self.use_local_files
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)
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self.flows = overload_client(client=self.flows)
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self.tools = overload_client(client=self.tools)
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or filesystem issues)
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:raises HumanloopRuntimeError: If there's an error communicating with the API
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"""
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return self._sync_client.pull(environment=environment, path=path)
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return self._file_syncer.pull(environment=environment, path=path)
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class AsyncHumanloop(AsyncBaseHumanloop):

‎src/humanloop/core/client_wrapper.py‎

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def get_headers(self) -> typing.Dict[str, str]:
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headers: typing.Dict[str, str] = {
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"User-Agent": "humanloop/0.8.39",
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"User-Agent": "humanloop/0.8.40b3",
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"X-Fern-Language": "Python",
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"X-Fern-SDK-Name": "humanloop",
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"X-Fern-SDK-Version": "0.8.39",
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"X-Fern-SDK-Version": "0.8.40b3",
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}
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headers["X-API-KEY"] = self.api_key
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return headers

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