chore: 添加虚拟环境到仓库
- 添加 backend_service/venv 虚拟环境 - 包含所有Python依赖包 - 注意：虚拟环境约393MB，包含12655个文件
This commit is contained in:
@@ -0,0 +1,17 @@
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from .anthropic import Anthropic
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from .anthropic_async import AsyncAnthropic
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from .anthropic_providers import (
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AnthropicBedrock,
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AnthropicVertex,
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AsyncAnthropicBedrock,
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AsyncAnthropicVertex,
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)
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__all__ = [
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"Anthropic",
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"AsyncAnthropic",
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"AnthropicBedrock",
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"AsyncAnthropicBedrock",
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"AnthropicVertex",
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"AsyncAnthropicVertex",
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]
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@@ -0,0 +1,217 @@
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try:
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import anthropic
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from anthropic.resources import Messages
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except ImportError:
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raise ModuleNotFoundError(
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"Please install the Anthropic SDK to use this feature: 'pip install anthropic'"
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)
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import time
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import uuid
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from typing import Any, Dict, Optional
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from posthog.ai.utils import (
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call_llm_and_track_usage,
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get_model_params,
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merge_system_prompt,
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with_privacy_mode,
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)
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from posthog.client import Client as PostHogClient
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class Anthropic(anthropic.Anthropic):
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"""
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A wrapper around the Anthropic SDK that automatically sends LLM usage events to PostHog.
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"""
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_ph_client: PostHogClient
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def __init__(self, posthog_client: PostHogClient, **kwargs):
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"""
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Args:
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posthog_client: PostHog client for tracking usage
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**kwargs: Additional arguments passed to the Anthropic client
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"""
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super().__init__(**kwargs)
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self._ph_client = posthog_client
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self.messages = WrappedMessages(self)
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class WrappedMessages(Messages):
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_client: Anthropic
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def create(
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self,
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posthog_distinct_id: Optional[str] = None,
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posthog_trace_id: Optional[str] = None,
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posthog_properties: Optional[Dict[str, Any]] = None,
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posthog_privacy_mode: bool = False,
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posthog_groups: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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):
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"""
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Create a message using Anthropic's API while tracking usage in PostHog.
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Args:
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posthog_distinct_id: Optional ID to associate with the usage event
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posthog_trace_id: Optional trace UUID for linking events
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posthog_properties: Optional dictionary of extra properties to include in the event
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posthog_privacy_mode: Whether to redact sensitive information in tracking
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posthog_groups: Optional group analytics properties
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**kwargs: Arguments passed to Anthropic's messages.create
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"""
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if posthog_trace_id is None:
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posthog_trace_id = str(uuid.uuid4())
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if kwargs.get("stream", False):
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return self._create_streaming(
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posthog_distinct_id,
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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**kwargs,
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)
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return call_llm_and_track_usage(
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posthog_distinct_id,
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self._client._ph_client,
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"anthropic",
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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self._client.base_url,
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super().create,
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**kwargs,
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)
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def stream(
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self,
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posthog_distinct_id: Optional[str] = None,
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posthog_trace_id: Optional[str] = None,
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posthog_properties: Optional[Dict[str, Any]] = None,
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posthog_privacy_mode: bool = False,
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posthog_groups: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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):
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if posthog_trace_id is None:
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posthog_trace_id = str(uuid.uuid4())
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return self._create_streaming(
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posthog_distinct_id,
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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**kwargs,
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)
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def _create_streaming(
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self,
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posthog_distinct_id: Optional[str],
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posthog_trace_id: Optional[str],
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posthog_properties: Optional[Dict[str, Any]],
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posthog_privacy_mode: bool,
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posthog_groups: Optional[Dict[str, Any]],
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**kwargs: Any,
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):
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start_time = time.time()
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usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
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accumulated_content = []
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response = super().create(**kwargs)
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def generator():
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nonlocal usage_stats
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nonlocal accumulated_content # noqa: F824
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try:
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for event in response:
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if hasattr(event, "usage") and event.usage:
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usage_stats = {
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k: getattr(event.usage, k, 0)
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for k in [
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"input_tokens",
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"output_tokens",
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"cache_read_input_tokens",
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"cache_creation_input_tokens",
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]
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}
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if hasattr(event, "content") and event.content:
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accumulated_content.append(event.content)
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yield event
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finally:
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end_time = time.time()
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latency = end_time - start_time
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output = "".join(accumulated_content)
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self._capture_streaming_event(
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posthog_distinct_id,
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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kwargs,
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usage_stats,
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latency,
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output,
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)
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return generator()
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def _capture_streaming_event(
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self,
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posthog_distinct_id: Optional[str],
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posthog_trace_id: Optional[str],
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posthog_properties: Optional[Dict[str, Any]],
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posthog_privacy_mode: bool,
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posthog_groups: Optional[Dict[str, Any]],
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kwargs: Dict[str, Any],
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usage_stats: Dict[str, int],
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latency: float,
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output: str,
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):
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if posthog_trace_id is None:
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posthog_trace_id = str(uuid.uuid4())
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event_properties = {
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"$ai_provider": "anthropic",
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"$ai_model": kwargs.get("model"),
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"$ai_model_parameters": get_model_params(kwargs),
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"$ai_input": with_privacy_mode(
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self._client._ph_client,
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posthog_privacy_mode,
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merge_system_prompt(kwargs, "anthropic"),
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),
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"$ai_output_choices": with_privacy_mode(
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self._client._ph_client,
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posthog_privacy_mode,
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[{"content": output, "role": "assistant"}],
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),
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"$ai_http_status": 200,
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"$ai_input_tokens": usage_stats.get("input_tokens", 0),
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"$ai_output_tokens": usage_stats.get("output_tokens", 0),
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"$ai_cache_read_input_tokens": usage_stats.get(
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"cache_read_input_tokens", 0
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),
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"$ai_cache_creation_input_tokens": usage_stats.get(
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"cache_creation_input_tokens", 0
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),
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"$ai_latency": latency,
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"$ai_trace_id": posthog_trace_id,
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"$ai_base_url": str(self._client.base_url),
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**(posthog_properties or {}),
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}
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if posthog_distinct_id is None:
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event_properties["$process_person_profile"] = False
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if hasattr(self._client._ph_client, "capture"):
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self._client._ph_client.capture(
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distinct_id=posthog_distinct_id or posthog_trace_id,
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event="$ai_generation",
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properties=event_properties,
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groups=posthog_groups,
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)
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@@ -0,0 +1,217 @@
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try:
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import anthropic
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from anthropic.resources import AsyncMessages
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except ImportError:
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raise ModuleNotFoundError(
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"Please install the Anthropic SDK to use this feature: 'pip install anthropic'"
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)
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import time
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import uuid
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from typing import Any, Dict, Optional
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from posthog.ai.utils import (
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call_llm_and_track_usage_async,
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get_model_params,
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merge_system_prompt,
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with_privacy_mode,
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)
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from posthog.client import Client as PostHogClient
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class AsyncAnthropic(anthropic.AsyncAnthropic):
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"""
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An async wrapper around the Anthropic SDK that automatically sends LLM usage events to PostHog.
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"""
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_ph_client: PostHogClient
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def __init__(self, posthog_client: PostHogClient, **kwargs):
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"""
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Args:
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posthog_client: PostHog client for tracking usage
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**kwargs: Additional arguments passed to the Anthropic client
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"""
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super().__init__(**kwargs)
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self._ph_client = posthog_client
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self.messages = AsyncWrappedMessages(self)
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class AsyncWrappedMessages(AsyncMessages):
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_client: AsyncAnthropic
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async def create(
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self,
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posthog_distinct_id: Optional[str] = None,
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posthog_trace_id: Optional[str] = None,
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posthog_properties: Optional[Dict[str, Any]] = None,
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posthog_privacy_mode: bool = False,
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posthog_groups: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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):
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"""
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Create a message using Anthropic's API while tracking usage in PostHog.
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Args:
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posthog_distinct_id: Optional ID to associate with the usage event
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posthog_trace_id: Optional trace UUID for linking events
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posthog_properties: Optional dictionary of extra properties to include in the event
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posthog_privacy_mode: Whether to redact sensitive information in tracking
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posthog_groups: Optional group analytics properties
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**kwargs: Arguments passed to Anthropic's messages.create
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"""
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if posthog_trace_id is None:
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posthog_trace_id = str(uuid.uuid4())
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if kwargs.get("stream", False):
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return await self._create_streaming(
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posthog_distinct_id,
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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**kwargs,
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)
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return await call_llm_and_track_usage_async(
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posthog_distinct_id,
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self._client._ph_client,
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"anthropic",
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
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self._client.base_url,
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super().create,
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**kwargs,
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)
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async def stream(
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self,
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posthog_distinct_id: Optional[str] = None,
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posthog_trace_id: Optional[str] = None,
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posthog_properties: Optional[Dict[str, Any]] = None,
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posthog_privacy_mode: bool = False,
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posthog_groups: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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):
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if posthog_trace_id is None:
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posthog_trace_id = str(uuid.uuid4())
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return await self._create_streaming(
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posthog_distinct_id,
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posthog_trace_id,
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posthog_properties,
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posthog_privacy_mode,
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posthog_groups,
|
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**kwargs,
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)
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async def _create_streaming(
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self,
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posthog_distinct_id: Optional[str],
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posthog_trace_id: Optional[str],
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posthog_properties: Optional[Dict[str, Any]],
|
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posthog_privacy_mode: bool,
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posthog_groups: Optional[Dict[str, Any]],
|
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**kwargs: Any,
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):
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start_time = time.time()
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usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
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accumulated_content = []
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response = await super().create(**kwargs)
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async def generator():
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nonlocal usage_stats
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nonlocal accumulated_content # noqa: F824
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try:
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async for event in response:
|
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if hasattr(event, "usage") and event.usage:
|
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usage_stats = {
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k: getattr(event.usage, k, 0)
|
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for k in [
|
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"input_tokens",
|
||||
"output_tokens",
|
||||
"cache_read_input_tokens",
|
||||
"cache_creation_input_tokens",
|
||||
]
|
||||
}
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||||
|
||||
if hasattr(event, "content") and event.content:
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||||
accumulated_content.append(event.content)
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yield event
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||||
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finally:
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end_time = time.time()
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latency = end_time - start_time
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output = "".join(accumulated_content)
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await self._capture_streaming_event(
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posthog_distinct_id,
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posthog_trace_id,
|
||||
posthog_properties,
|
||||
posthog_privacy_mode,
|
||||
posthog_groups,
|
||||
kwargs,
|
||||
usage_stats,
|
||||
latency,
|
||||
output,
|
||||
)
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||||
|
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return generator()
|
||||
|
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async def _capture_streaming_event(
|
||||
self,
|
||||
posthog_distinct_id: Optional[str],
|
||||
posthog_trace_id: Optional[str],
|
||||
posthog_properties: Optional[Dict[str, Any]],
|
||||
posthog_privacy_mode: bool,
|
||||
posthog_groups: Optional[Dict[str, Any]],
|
||||
kwargs: Dict[str, Any],
|
||||
usage_stats: Dict[str, int],
|
||||
latency: float,
|
||||
output: str,
|
||||
):
|
||||
if posthog_trace_id is None:
|
||||
posthog_trace_id = str(uuid.uuid4())
|
||||
|
||||
event_properties = {
|
||||
"$ai_provider": "anthropic",
|
||||
"$ai_model": kwargs.get("model"),
|
||||
"$ai_model_parameters": get_model_params(kwargs),
|
||||
"$ai_input": with_privacy_mode(
|
||||
self._client._ph_client,
|
||||
posthog_privacy_mode,
|
||||
merge_system_prompt(kwargs, "anthropic"),
|
||||
),
|
||||
"$ai_output_choices": with_privacy_mode(
|
||||
self._client._ph_client,
|
||||
posthog_privacy_mode,
|
||||
[{"content": output, "role": "assistant"}],
|
||||
),
|
||||
"$ai_http_status": 200,
|
||||
"$ai_input_tokens": usage_stats.get("input_tokens", 0),
|
||||
"$ai_output_tokens": usage_stats.get("output_tokens", 0),
|
||||
"$ai_cache_read_input_tokens": usage_stats.get(
|
||||
"cache_read_input_tokens", 0
|
||||
),
|
||||
"$ai_cache_creation_input_tokens": usage_stats.get(
|
||||
"cache_creation_input_tokens", 0
|
||||
),
|
||||
"$ai_latency": latency,
|
||||
"$ai_trace_id": posthog_trace_id,
|
||||
"$ai_base_url": str(self._client.base_url),
|
||||
**(posthog_properties or {}),
|
||||
}
|
||||
|
||||
if posthog_distinct_id is None:
|
||||
event_properties["$process_person_profile"] = False
|
||||
|
||||
if hasattr(self._client._ph_client, "capture"):
|
||||
self._client._ph_client.capture(
|
||||
distinct_id=posthog_distinct_id or posthog_trace_id,
|
||||
event="$ai_generation",
|
||||
properties=event_properties,
|
||||
groups=posthog_groups,
|
||||
)
|
||||
@@ -0,0 +1,62 @@
|
||||
try:
|
||||
import anthropic
|
||||
except ImportError:
|
||||
raise ModuleNotFoundError(
|
||||
"Please install the Anthropic SDK to use this feature: 'pip install anthropic'"
|
||||
)
|
||||
|
||||
from posthog.ai.anthropic.anthropic import WrappedMessages
|
||||
from posthog.ai.anthropic.anthropic_async import AsyncWrappedMessages
|
||||
from posthog.client import Client as PostHogClient
|
||||
|
||||
|
||||
class AnthropicBedrock(anthropic.AnthropicBedrock):
|
||||
"""
|
||||
A wrapper around the Anthropic Bedrock SDK that automatically sends LLM usage events to PostHog.
|
||||
"""
|
||||
|
||||
_ph_client: PostHogClient
|
||||
|
||||
def __init__(self, posthog_client: PostHogClient, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._ph_client = posthog_client
|
||||
self.messages = WrappedMessages(self)
|
||||
|
||||
|
||||
class AsyncAnthropicBedrock(anthropic.AsyncAnthropicBedrock):
|
||||
"""
|
||||
A wrapper around the Anthropic Bedrock SDK that automatically sends LLM usage events to PostHog.
|
||||
"""
|
||||
|
||||
_ph_client: PostHogClient
|
||||
|
||||
def __init__(self, posthog_client: PostHogClient, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._ph_client = posthog_client
|
||||
self.messages = AsyncWrappedMessages(self)
|
||||
|
||||
|
||||
class AnthropicVertex(anthropic.AnthropicVertex):
|
||||
"""
|
||||
A wrapper around the Anthropic Vertex SDK that automatically sends LLM usage events to PostHog.
|
||||
"""
|
||||
|
||||
_ph_client: PostHogClient
|
||||
|
||||
def __init__(self, posthog_client: PostHogClient, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._ph_client = posthog_client
|
||||
self.messages = WrappedMessages(self)
|
||||
|
||||
|
||||
class AsyncAnthropicVertex(anthropic.AsyncAnthropicVertex):
|
||||
"""
|
||||
A wrapper around the Anthropic Vertex SDK that automatically sends LLM usage events to PostHog.
|
||||
"""
|
||||
|
||||
_ph_client: PostHogClient
|
||||
|
||||
def __init__(self, posthog_client: PostHogClient, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._ph_client = posthog_client
|
||||
self.messages = AsyncWrappedMessages(self)
|
||||
Reference in New Issue
Block a user