diff --git a/docs/mint.json b/docs/mint.json index bab8c9134..1b540814e 100644 --- a/docs/mint.json +++ b/docs/mint.json @@ -144,6 +144,7 @@ "v2/integrations/anthropic", "v2/integrations/autogen", "v2/integrations/crewai", + "v2/integrations/daoxe", "v2/integrations/haystack", "v2/integrations/google_adk", "v2/integrations/google_generative_ai", diff --git a/docs/v2/examples/daoxe.mdx b/docs/v2/examples/daoxe.mdx new file mode 100644 index 000000000..d5f70edd9 --- /dev/null +++ b/docs/v2/examples/daoxe.mdx @@ -0,0 +1,100 @@ +--- +title: 'DaoXE' +description: 'DaoXE multi-protocol gateway Chat Completions example with AgentOps' +--- +{/* SOURCE_FILE: examples/daoxe/daoxe_chat_example.py */} + +_View source on GitHub_ + +# DaoXE Chat Completions Example + +This example shows how to monitor DaoXE traffic with AgentOps by using the OpenAI Python client against DaoXE's Chat Completions endpoint. + +DaoXE is a multi-model, multi-protocol API gateway. Here we only exercise the OpenAI-compatible Chat Completions path (`https://daoxe.com/v1` + `chat.completions`), which AgentOps instruments automatically. + +## Installation + + + ```bash pip + pip install -U agentops openai python-dotenv + ``` + ```bash poetry + poetry add -U agentops openai python-dotenv + ``` + ```bash uv + uv pip install -U agentops openai python-dotenv + ``` + + +## Environment + +```bash +export DAOXE_API_KEY="your_daoxe_api_key" +export AGENTOPS_API_KEY="your_agentops_api_key" +export DAOXE_MODEL="your_account_model_id" +``` + +Model IDs are account-scoped. Use authenticated model listing or the live catalog at [daoxe.com/pricing](https://daoxe.com/pricing). DaoXE is available outside mainland China. + +## Code + +```python +from openai import OpenAI +import agentops +import os +from dotenv import load_dotenv + +load_dotenv() +os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY", "your_api_key_here") + +agentops.init( + auto_start_session=False, + trace_name="DaoXE Chat Example", + tags=["daoxe", "chat-completions", "agentops-example"], +) +tracer = agentops.start_trace( + trace_name="DaoXE Chat Example", + tags=["daoxe-example", "multi-protocol-gateway", "agentops-example"], +) + +client = OpenAI( + base_url="https://daoxe.com/v1", + api_key=os.getenv("DAOXE_API_KEY", "your_daoxe_api_key_here"), +) + +response = client.chat.completions.create( + model=os.getenv("DAOXE_MODEL", "YOUR_ACCOUNT_MODEL_ID"), + messages=[ + { + "role": "system", + "content": "You are a concise assistant for API and observability tips.", + }, + { + "role": "user", + "content": "Give one practical tip for monitoring multi-model LLM gateways.", + }, + ], +) + +print(response.choices[0].message.content) + +agentops.end_trace(tracer, end_state="Success") + +print("\n" + "=" * 50) +print("Now let's verify that our LLM calls were tracked properly...") +try: + agentops.validate_trace_spans(trace_context=tracer) + print("\n✅ Success! All LLM spans were properly recorded in AgentOps.") +except agentops.ValidationError as e: + print(f"\n❌ Error validating spans: {e}") + raise +``` + +## Related + +- Integration guide: [DaoXE integration](/v2/integrations/daoxe) +- Product: [https://daoxe.com](https://daoxe.com) + + + + diff --git a/docs/v2/examples/examples.mdx b/docs/v2/examples/examples.mdx index 4bbd0c877..22360439b 100644 --- a/docs/v2/examples/examples.mdx +++ b/docs/v2/examples/examples.mdx @@ -21,6 +21,10 @@ description: 'Examples of AgentOps with various integrations' Unified LLM interface monitoring example + + Multi-protocol gateway Chat Completions via OpenAI client + + } iconType="image" href="/v2/examples/openai"> Advanced multi-tool orchestration with GPT models diff --git a/docs/v2/integrations/daoxe.mdx b/docs/v2/integrations/daoxe.mdx new file mode 100644 index 000000000..ad76d8779 --- /dev/null +++ b/docs/v2/integrations/daoxe.mdx @@ -0,0 +1,149 @@ +--- +title: DaoXE +description: "Track multi-model Chat Completions traffic through the DaoXE multi-protocol gateway with AgentOps" +--- + +AgentOps works with [DaoXE](https://daoxe.com) through the OpenAI Python SDK. DaoXE is a multi-model, multi-protocol API gateway (OpenAI Chat Completions / Responses, Anthropic Messages, and other published routes). This page covers the **OpenAI Chat Completions** path that AgentOps instruments automatically when you point the OpenAI client at DaoXE. + +## Installation + + +```bash pip +pip install agentops openai +``` +```bash poetry +poetry add agentops openai +``` +```bash uv +uv pip install agentops openai +``` + + +## Setting Up API Keys + +Before using DaoXE with AgentOps, set: + +- **DAOXE_API_KEY**: From your [DaoXE dashboard](https://daoxe.com) (regions outside mainland China) +- **AGENTOPS_API_KEY**: From your [AgentOps Dashboard](https://app.agentops.ai/) +- **DAOXE_MODEL** (optional): An account-scoped model ID from DaoXE authenticated model discovery or the [pricing catalog](https://daoxe.com/pricing). Model availability depends on your account group — do not hard-code a shared public ID list. + +Export them in your shell or put them in a `.env` file: + + +```bash Export to CLI +export DAOXE_API_KEY="your_daoxe_api_key_here" +export AGENTOPS_API_KEY="your_agentops_api_key_here" +export DAOXE_MODEL="your_account_model_id" +``` +```txt Set in .env file +DAOXE_API_KEY="your_daoxe_api_key_here" +AGENTOPS_API_KEY="your_agentops_api_key_here" +DAOXE_MODEL="your_account_model_id" +``` + + +Load them in Python if you use dotenv: + +```python +from dotenv import load_dotenv +import os + +load_dotenv() + +os.environ["DAOXE_API_KEY"] = os.getenv("DAOXE_API_KEY") +os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY") +``` + +## Basic Usage + +Initialize AgentOps first, then create an OpenAI client with DaoXE as `base_url`. AgentOps records the Chat Completions call automatically. + + +```python Basic Usage +import os +import agentops +from openai import OpenAI + +agentops.init() + +client = OpenAI( + api_key=os.getenv("DAOXE_API_KEY"), + base_url="https://daoxe.com/v1", +) + +response = client.chat.completions.create( + model=os.getenv("DAOXE_MODEL", "YOUR_ACCOUNT_MODEL_ID"), + messages=[ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "user", "content": "Explain multi-protocol API gateways in one sentence."}, + ], +) + +print(response.choices[0].message.content) +``` + + +## Streaming Completions + +Streaming responses are tracked the same way: + + +```python Streaming +import os +import agentops +from openai import OpenAI + +agentops.init() + +client = OpenAI( + api_key=os.getenv("DAOXE_API_KEY"), + base_url="https://daoxe.com/v1", +) + +stream = client.chat.completions.create( + model=os.getenv("DAOXE_MODEL", "YOUR_ACCOUNT_MODEL_ID"), + messages=[ + {"role": "user", "content": "Write a short note about LLM observability."}, + ], + stream=True, +) + +for chunk in stream: + delta = chunk.choices[0].delta.content + if delta is not None: + print(delta, end="", flush=True) +print() +``` + + +## Model IDs + +Pass the model ID your DaoXE account can call. Prefer: + +1. Authenticated `GET https://daoxe.com/v1/models` with your key, or +2. The live catalog on [daoxe.com/pricing](https://daoxe.com/pricing) + +Availability is account-scoped and can change; keep the ID in env (`DAOXE_MODEL`) rather than baking a fixed list into app code. + +## Notes + +- Base URL for Chat Completions: `https://daoxe.com/v1` (path `/chat/completions`). +- Auth header: `Authorization: Bearer $DAOXE_API_KEY`. +- DaoXE also exposes other protocols (for example Anthropic Messages). This AgentOps path uses the OpenAI client + Chat Completions route so existing OpenAI instrumentation applies without custom wrappers. +- DaoXE serves customers outside mainland China; create keys and review limits on [daoxe.com](https://daoxe.com). + +## Examples + + + + Minimal Chat Completions example with AgentOps tracing + + + Source under examples/daoxe + + + + + + + diff --git a/examples/daoxe/README.md b/examples/daoxe/README.md new file mode 100644 index 000000000..97d0608e4 --- /dev/null +++ b/examples/daoxe/README.md @@ -0,0 +1,47 @@ +# DaoXE Examples with AgentOps + +This directory shows how to call DaoXE through the OpenAI Python client and monitor requests with AgentOps. + +DaoXE is a multi-model, multi-protocol API gateway. These examples use the **OpenAI Chat Completions** path: + +- Base URL: `https://daoxe.com/v1` +- Auth: `DAOXE_API_KEY` +- Model: account-scoped ID (`DAOXE_MODEL`) + +## Prerequisites + +- Python >= 3.10 < 3.13 +- Install dependencies: + +```bash +pip install -r requirements.txt +``` + +- Environment: + +```bash +export DAOXE_API_KEY="your_daoxe_api_key" +export AGENTOPS_API_KEY="your_agentops_api_key" +export DAOXE_MODEL="your_account_model_id" +``` + +Model IDs depend on your DaoXE account group. Discover them via authenticated `GET /v1/models` or the live catalog at https://daoxe.com/pricing. DaoXE serves customers outside mainland China. + +## Examples + +### `daoxe_chat_example.py` + +- Initializes AgentOps tracing +- Creates `OpenAI(base_url="https://daoxe.com/v1", api_key=DAOXE_API_KEY)` +- Runs a single Chat Completions request +- Ends the trace and validates spans + +```bash +python daoxe_chat_example.py +``` + +## AgentOps Integration + +AgentOps instruments the OpenAI client, so Chat Completions traffic routed to DaoXE is captured without custom middleware. + +Learn more at https://www.agentops.ai and https://daoxe.com diff --git a/examples/daoxe/daoxe_chat_example.py b/examples/daoxe/daoxe_chat_example.py new file mode 100644 index 000000000..cb788ef83 --- /dev/null +++ b/examples/daoxe/daoxe_chat_example.py @@ -0,0 +1,62 @@ +# DaoXE Chat Completions Example +# +# Demonstrates AgentOps monitoring for DaoXE via the OpenAI Python client. +# DaoXE is a multi-model, multi-protocol API gateway; this script uses the +# OpenAI Chat Completions path (base_url https://daoxe.com/v1). + +# %pip install -U openai +# %pip install -U agentops +# %pip install -U python-dotenv + +from openai import OpenAI +import agentops +import os +from dotenv import load_dotenv + +load_dotenv() +os.environ["AGENTOPS_API_KEY"] = os.getenv("AGENTOPS_API_KEY", "your_api_key_here") + +agentops.init( + auto_start_session=False, + trace_name="DaoXE Chat Example", + tags=["daoxe", "chat-completions", "agentops-example"], +) +tracer = agentops.start_trace( + trace_name="DaoXE Chat Example", + tags=["daoxe-example", "multi-protocol-gateway", "agentops-example"], +) + +# Point the OpenAI client at DaoXE. Model IDs are account-scoped — set DAOXE_MODEL +# from authenticated /v1/models or your DaoXE pricing catalog. +client = OpenAI( + base_url="https://daoxe.com/v1", + api_key=os.getenv("DAOXE_API_KEY", "your_daoxe_api_key_here"), +) + +response = client.chat.completions.create( + model=os.getenv("DAOXE_MODEL", "YOUR_ACCOUNT_MODEL_ID"), + messages=[ + { + "role": "system", + "content": "You are a concise assistant for API and observability tips.", + }, + { + "role": "user", + "content": "Give one practical tip for monitoring multi-model LLM gateways.", + }, + ], +) + +print(response.choices[0].message.content) + +agentops.end_trace(tracer, end_state="Success") + +# Verify spans were recorded in AgentOps +print("\n" + "=" * 50) +print("Now let's verify that our LLM calls were tracked properly...") +try: + agentops.validate_trace_spans(trace_context=tracer) + print("\n✅ Success! All LLM spans were properly recorded in AgentOps.") +except agentops.ValidationError as e: + print(f"\n❌ Error validating spans: {e}") + raise diff --git a/examples/daoxe/requirements.txt b/examples/daoxe/requirements.txt new file mode 100644 index 000000000..7a9bdf7f2 --- /dev/null +++ b/examples/daoxe/requirements.txt @@ -0,0 +1,3 @@ +openai # DaoXE Chat Completions via OpenAI client +agentops +python-dotenv