groqqer is a lightweight, zero-dependency Go OpenAI-compatible API gateway and proxy for the Groq Streamlit space (https://dromerosm-groq-chatbot.hf.space).

It connects directly to Streamlit's binary WebSocket engine (/_stcore/stream) using a pure Go Protobuf wire-format encoder/decoder. It requires no browser, no Chromium, and no Xvfb, allowing it to run smoothly on minimal headless servers and low-resource containers.

Key Features

Direct WebSocket Protobuf Protocol: Communicates directly with Streamlit's internal engine over RFC 6455 WebSockets and Protocol Buffers wire format.
Completely Headless & Zero Dependencies: Written entirely in pure Go using only the standard library (net/http, crypto/tls, encoding/binary, encoding/json, etc.). No Chromium, Chrome, Xvfb, Puppeteer, or external Go modules required.
Sub-Second Latency: Bypasses browser rendering and DOM parsing entirely, delivering responses with minimal overhead.
OpenAI Compatible API: Exposes standard /v1/models and /v1/chat/completions endpoints. Drop-in replacement for OpenAI SDKs, LiteLLM, Open-WebUI, LibreChat, and LangChain.
System Prompt Support: Formats developer/system instructions cleanly for the target model.
Streaming & Non-Streaming: Supports Server-Sent Events (stream: true) with real-time token streaming and synchronous JSON responses.
Tool / Function Calling: Fully supports OpenAI tools, tool_choice, and multi-turn execution (role: "tool"). Automatically injects schemas and parses <tool_call> outputs into standard OpenAI tool_calls payloads with finish_reason: "tool_calls".
Reasoning Content: Extracts <think> and </think> tags from reasoning models (e.g., Qwen 3.6/3.8) and streams or populates reasoning_content following OpenAI O-series conventions.
Dynamic Model Discovery & Switching: Discovers active models directly from the Streamlit space on startup and allows seamless model switching between requests (qwen/qwen3.6-27b, openai/gpt-oss-120b, openai/gpt-oss-20b, groq/compound, etc.).
SOCKS5 Proxy Support: Native pure Go SOCKS5 proxy client supporting authentication (-socks flag or ALL_PROXY / SOCKS5_PROXY environment variables).

Architecture

+---------------------------+
| OpenAI Client / SDK / App |
+---------------------------+
              |  HTTP POST /v1/chat/completions
              v
+---------------------------+
|          groqqer          |
|  (Pure Go Standard Lib)   |
|   RFC 6455 WS + Protobuf  |
+---------------------------+
              |  WSS (TLS WebSocket)
              v
+---------------------------+
|   Groq Streamlit Space    |
| (dromerosm-groq-chatbot)  |
+---------------------------+

Requirements

Linux / macOS / Windows
Go 1.20+ (for building from source)
No browser or graphics packages needed.

Installation & Build

Clone or navigate to the repository, then build the binary:

make

The optimized binary will be created at bin/groqqer.

Running the Server

Start the gateway with default settings:

./bin/groqqer -port 8080

CLI Flags

Flag	Default	Description
`-port`	`8080`	HTTP server listening port
`-target`	`https://dromerosm-groq-chatbot.hf.space`	Target Groq Streamlit space URL
`-default-model`	`qwen/qwen3.6-27b`	Fallback model if request does not specify one
`-socks`	`""`	SOCKS5 proxy URL (e.g. `socks5://127.0.0.1:1080`)
`-user-agent`	(Chrome UA)	Custom User-Agent string

(Note: legacy flags -browser, -xvfb, and -headless are retained for backward compatibility but are ignored, as groqqer operates completely headless via direct WebSocket).

API Usage Examples

1. List Available Models

curl -s http://127.0.0.1:8080/v1/models

Response:

{
  "object": "list",
  "data": [
    {"id": "qwen/qwen3.6-27b", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "qwen/qwen3.8-27b", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "openai/gpt-oss-120b", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "openai/gpt-oss-20b", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "groq/compound", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "groq/compound-mini", "object": "model", "created": 1788870683, "owned_by": "groq"},
    {"id": "allam-2-7b", "object": "model", "created": 1788870683, "owned_by": "groq"}
  ]
}

2. Chat Completion (Non-Streaming)

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-oss-20b",
    "messages": [
      {"role": "system", "content": "You are a concise assistant. Reply in one sentence."},
      {"role": "user", "content": "What is the capital of France?"}
    ]
  }'

Response:

{
  "id": "chatcmpl-893498c9-2808-4bec-8c6a-2a0352ed69e9",
  "object": "chat.completion",
  "created": 1788870700,
  "model": "openai/gpt-oss-20b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 0,
    "completion_tokens": 0,
    "total_tokens": 0
  }
}

3. Streaming Chat Completion (SSE)

curl -N -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "Count from 1 to 4 separated by commas."}
    ],
    "stream": true
  }'

Output:

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"role":"assistant"}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"reasoning_content":"Thinking process..."}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":"1,"}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":" 2,"}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":" 3,"}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":" 4"}}]}

data: {"id":"chatcmpl-7a06d0fb","object":"chat.completion.chunk","created":1788870705,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]

4. Tool / Function Calling

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "What is the weather in Tokyo right now?"}
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "get_current_weather",
          "description": "Get current weather for a city",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {"type": "string", "description": "City and country"}
            },
            "required": ["location"]
          }
        }
      }
    ],
    "tool_choice": "required"
  }'

Response:

{
  "id": "chatcmpl-29f63b3b-7ab6-444c-8579-49f906007d43",
  "object": "chat.completion",
  "created": 1788870711,
  "model": "qwen/qwen3.6-27b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": null,
        "reasoning_content": "The user is asking for the current weather in Tokyo...",
        "tool_calls": [
          {
            "id": "call_163e8f97",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\"location\":\"Tokyo\"}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ]
}

5. Multi-Turn Tool Response Execution

Send back the tool execution results using role: "tool":

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "What is the weather in Tokyo right now?"},
      {
        "role": "assistant",
        "tool_calls": [
          {
            "id": "call_163e8f97",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\"location\":\"Tokyo\"}"
            }
          }
        ]
      },
      {
        "role": "tool",
        "tool_call_id": "call_163e8f97",
        "name": "get_current_weather",
        "content": "{\"temperature\": \"19°C\", \"weather\": \"Sunny with clear skies\"}"
      }
    ]
  }'

Response:

{
  "id": "chatcmpl-23354bba-33c7-45be-8807-9c84243037b8",
  "object": "chat.completion",
  "created": 1788870718,
  "model": "qwen/qwen3.6-27b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "It's currently 19°C and sunny with clear skies in Tokyo"
      },
      "finish_reason": "stop"
    }
  ]
}

6. Python OpenAI SDK Example

from openai import OpenAI

client = OpenAI(
  base_url="http://127.0.0.1:8080/v1",
  api_key="not-needed"
)

response = client.chat.completions.create(
  model="qwen/qwen3.6-27b",
  messages=[
    {"role": "system", "content": "You are a helpful coding assistant."},
    {"role": "user", "content": "Write a Python function to reverse a string."}
  ]
)

print(response.choices[0].message.content)

License

MIT License