fix: support ChatGPT-subscription & GitHub Copilot providers (litellm 1.87.2 + extra_headers)

README.md

@@ -273,6 +273,16 @@ pageindex_threshold: 20          # PDF pages threshold for PageIndex
 
 `entity_types` (optional): a YAML list overriding the entity-type vocabulary used for entity pages; omit it to use the default `person`, `organization`, `place`, `product`, `work`, `event`, `other`.
 
+`extra_headers` (optional): a YAML mapping of extra HTTP headers sent with every LLM request (forwarded to LiteLLM's `extra_headers`). Useful for providers that expect custom headers, e.g. GitHub Copilot IDE-auth headers:
+
+```yaml
+extra_headers:
+  Editor-Version: vscode/1.95.0
+  Copilot-Integration-Id: vscode-chat
+```
+
+Subscription-based providers that authenticate via OAuth device flow (e.g. `chatgpt/*`, `github_copilot/*`) need no API key — OpenKB skips the missing-key warning for them.
+
 Model names use `provider/model` LiteLLM [format](https://docs.litellm.ai/docs/providers) (OpenAI models can omit the prefix):
 
 | Provider | Model example |

config.yaml.example

@@ -2,6 +2,13 @@ model: gpt-5.4                   # LLM model (any LiteLLM-supported provider)
 language: en                     # Wiki output language
 pageindex_threshold: 20          # PDF pages threshold for PageIndex
 
+# Optional: extra HTTP headers sent with every LLM request (forwarded to
+# LiteLLM's extra_headers). Some providers need these — e.g. GitHub Copilot
+# IDE-auth headers on older litellm versions:
+# extra_headers:
+#   Editor-Version: vscode/1.95.0
+#   Copilot-Integration-Id: vscode-chat
+
 # Optional: override the entity-type vocabulary used for entity pages.
 # Omit this key to use the default 7 types
 # (person, organization, place, product, work, event, other).

openkb/agent/compiler.py

@@ -29,7 +29,7 @@
 import litellm
 import yaml
 
-from openkb.config import DEFAULT_ENTITY_TYPES, resolve_entity_types
+from openkb.config import DEFAULT_ENTITY_TYPES, get_extra_headers, resolve_entity_types
 from openkb.lint import list_existing_wiki_targets, strip_ghost_wikilinks
 from openkb.schema import INDEX_SEED, get_agents_md
 
@@ -323,6 +323,9 @@ def _fmt_messages(messages: list[dict], max_content: int = 200) -> str:
 
 def _llm_call(model: str, messages: list[dict], step_name: str, **kwargs) -> str:
     """Single LLM call with animated progress and debug logging."""
+    extra_headers = get_extra_headers()
+    if extra_headers:
+        kwargs.setdefault("extra_headers", extra_headers)
     logger.debug("LLM request [%s]:\n%s", step_name, _fmt_messages(messages))
     if kwargs:
         logger.debug("LLM kwargs [%s]: %s", step_name, kwargs)
@@ -342,6 +345,9 @@ def _llm_call(model: str, messages: list[dict], step_name: str, **kwargs) -> str
 
 async def _llm_call_async(model: str, messages: list[dict], step_name: str, **kwargs) -> str:
     """Async LLM call with timing output and debug logging."""
+    extra_headers = get_extra_headers()
+    if extra_headers:
+        kwargs.setdefault("extra_headers", extra_headers)
     logger.debug("LLM request [%s]:\n%s", step_name, _fmt_messages(messages))
     if kwargs:
         logger.debug("LLM kwargs [%s]: %s", step_name, kwargs)

openkb/agent/linter.py

@@ -4,8 +4,10 @@
 from pathlib import Path
 
 from agents import Agent, Runner, function_tool
+from agents.model_settings import ModelSettings
 
 from openkb.agent.tools import list_wiki_files, read_wiki_file
+from openkb.config import get_extra_headers
 
 MAX_TURNS = 50
 from openkb.schema import get_agents_md
@@ -79,6 +81,7 @@ def read_file(path: str) -> str:
         instructions=instructions,
         tools=[list_files, read_file],
         model=f"litellm/{model}",
+        model_settings=ModelSettings(extra_headers=get_extra_headers() or None),
     )
 
 

openkb/agent/query.py

@@ -6,6 +6,7 @@
 from agents import Agent, Runner, function_tool
 
 from agents import ToolOutputImage, ToolOutputText
+from openkb.config import get_extra_headers
 from openkb.agent.tools import (
     get_wiki_page_content,
     read_wiki_file,
@@ -94,7 +95,10 @@ def get_image(image_path: str) -> ToolOutputImage | ToolOutputText:
         instructions=instructions,
         tools=[read_file, get_page_content, get_image],
         model=f"litellm/{model}",
-        model_settings=ModelSettings(parallel_tool_calls=False),
+        model_settings=ModelSettings(
+            parallel_tool_calls=False,
+            extra_headers=get_extra_headers() or None,
+        ),
     )
 
 

openkb/cli.py

@@ -41,7 +41,10 @@ def filter(self, record: logging.LogRecord) -> bool:
 litellm.suppress_debug_info = True
 from dotenv import load_dotenv
 
-from openkb.config import DEFAULT_CONFIG, load_config, save_config, load_global_config, register_kb
+from openkb.config import (
+    DEFAULT_CONFIG, load_config, save_config, load_global_config, register_kb,
+    resolve_extra_headers, set_extra_headers,
+)
 from openkb.converter import _registry_path, convert_document
 from openkb.locks import atomic_write_json, atomic_write_text, kb_ingest_lock, kb_read_lock
 from openkb.log import append_log
@@ -60,6 +63,11 @@ def filter(self, record: logging.LogRecord) -> bool:
     "ZHIPUAI_API_KEY", "DASHSCOPE_API_KEY",
 )
 
+# Providers that authenticate via OAuth device flow (subscription login
+# handled by LiteLLM itself) — no API key env var is needed, so the
+# missing-key warning would be a false alarm for them.
+_OAUTH_PROVIDERS = {"chatgpt", "github_copilot"}
+
 
 def _extract_provider(model: str) -> str | None:
     """Extract the LiteLLM provider name from a model string.
@@ -100,23 +108,28 @@ def _setup_llm_key(kb_dir: Path | None = None) -> None:
 
     api_key = os.environ.get("LLM_API_KEY", "")
 
-    # Try to resolve the active provider from the KB config
+    # Try to resolve the active provider and extra headers from the KB config
     provider: str | None = None
+    extra_headers: dict[str, str] = {}
     if kb_dir is not None:
         config_path = kb_dir / ".openkb" / "config.yaml"
         if config_path.exists():
             config = load_config(config_path)
             model = config.get("model", "")
             provider = _extract_provider(str(model))
+            extra_headers = resolve_extra_headers(config)
+    set_extra_headers(extra_headers)
 
     if not api_key:
-        # Check if any provider key is already set
+        # Check if any provider key is already set. OAuth-based providers
+        # (ChatGPT subscription, GitHub Copilot) don't use API keys at all,
+        # so the warning is skipped for them.
         check_keys = (
             (f"{provider.upper()}_API_KEY",) if provider
             else _KNOWN_PROVIDER_KEYS
         )
         has_key = any(os.environ.get(k) for k in check_keys)
-        if not has_key:
+        if not has_key and provider not in _OAUTH_PROVIDERS:
             click.echo(
                 "Warning: No LLM API key found. Set one of:\n"
                 f"  1. {kb_dir / '.env' if kb_dir else '<kb_dir>/.env'} — LLM_API_KEY=sk-...\n"

openkb/config.py

@@ -96,6 +96,66 @@ def resolve_entity_types(config: dict) -> list[str]:
     return cleaned
 
 
+def resolve_extra_headers(config: dict) -> dict[str, str]:
+    """Resolve the optional ``extra_headers:`` config key into a str→str dict.
+
+    Some LiteLLM providers need extra HTTP headers on every request (e.g.
+    GitHub Copilot's ``Editor-Version`` IDE-auth headers). Users opt in via
+    an ``extra_headers:`` mapping in config.yaml; the result is forwarded to
+    LiteLLM's ``extra_headers`` parameter on all LLM calls.
+
+    Values are stringified (YAML may parse version-like values as numbers).
+    Entries with a non-string/empty key or a non-scalar value are skipped.
+    A non-mapping ``extra_headers`` is ignored entirely. Warnings are logged
+    only when the key was present but malformed.
+    """
+    raw = config.get("extra_headers")
+    if raw is None:
+        return {}
+    if not isinstance(raw, dict):
+        logger.warning(
+            "config: 'extra_headers' must be a mapping of header name to "
+            "value, got %s — ignoring it.",
+            type(raw).__name__,
+        )
+        return {}
+    headers: dict[str, str] = {}
+    for key, value in raw.items():
+        if not isinstance(key, str) or not key.strip():
+            logger.warning(
+                "config: skipping 'extra_headers' entry with non-string "
+                "or empty key: %r", key,
+            )
+            continue
+        if value is None or not isinstance(value, (str, int, float, bool)):
+            logger.warning(
+                "config: skipping 'extra_headers' entry %r with "
+                "non-scalar value: %r", key, value,
+            )
+            continue
+        headers[key.strip()] = str(value)
+    return headers
+
+
+# Process-wide extra headers for LLM requests, resolved from the active KB's
+# config by the CLI entry points (cli._setup_llm_key). LLM call sites read it
+# via get_extra_headers() so the value doesn't have to be threaded through
+# every compile/agent call chain — mirroring how the API key is applied
+# globally via litellm.api_key / provider env vars.
+_runtime_extra_headers: dict[str, str] = {}
+
+
+def set_extra_headers(headers: dict[str, str]) -> None:
+    """Set the process-wide extra headers for LLM requests."""
+    global _runtime_extra_headers
+    _runtime_extra_headers = dict(headers)
+
+
+def get_extra_headers() -> dict[str, str]:
+    """Return a copy of the process-wide extra headers for LLM requests."""
+    return dict(_runtime_extra_headers)
+
+
 def load_config(config_path: Path) -> dict[str, Any]:
     """Load YAML config from config_path, merged with DEFAULT_CONFIG.
 

openkb/skill/creator.py

@@ -19,6 +19,7 @@
 from agents import Agent, Runner, ToolOutputImage, ToolOutputText, function_tool
 from agents.model_settings import ModelSettings
 
+from openkb.config import get_extra_headers
 from openkb.skill import skill_dir
 from openkb.skill.tools import (
     get_skill_page_content as _get_page_content_impl,
@@ -150,7 +151,10 @@ def done(summary: str) -> str:
         # compile. Writes serialise naturally because each
         # `write_skill_file` depends on accumulated reads; the model has
         # no reason to issue parallel writes to the same path.
-        model_settings=ModelSettings(parallel_tool_calls=True),
+        model_settings=ModelSettings(
+            parallel_tool_calls=True,
+            extra_headers=get_extra_headers() or None,
+        ),
     )
 
 

openkb/skill/evaluator.py

@@ -44,7 +44,9 @@
 
 from agents import Agent, Runner
 from agents.exceptions import MaxTurnsExceeded
+from agents.model_settings import ModelSettings
 
+from openkb.config import get_extra_headers
 from openkb.skill import extract_body, extract_frontmatter
 
 
@@ -241,6 +243,7 @@ async def generate_eval_set(
         name="eval-set-generator",
         instructions=instructions,
         model=f"litellm/{model}",
+        model_settings=ModelSettings(extra_headers=get_extra_headers() or None),
     )
     try:
         result = await Runner.run(agent, "Generate the eval set now.", max_turns=3)
@@ -299,6 +302,7 @@ async def grade_one(
         name="trigger-grader",
         instructions=instructions,
         model=f"litellm/{model}",
+        model_settings=ModelSettings(extra_headers=get_extra_headers() or None),
     )
     try:
         result = await Runner.run(agent, f"Question: {question}", max_turns=2)
@@ -347,6 +351,7 @@ async def grade_coverage(
         name="coverage-grader",
         instructions=instructions,
         model=f"litellm/{model}",
+        model_settings=ModelSettings(extra_headers=get_extra_headers() or None),
     )
     try:
         result = await Runner.run(agent, f"Question: {question}", max_turns=2)

pyproject.toml

@@ -25,19 +25,25 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 keywords = ["ai", "rag", "retrieval", "knowledge-base", "llm", "pageindex", "agents", "document"]
+# All dependencies are pinned exactly (supply-chain caution — e.g. the
+# litellm package-poisoning incident). Bump deliberately after vetting
+# each release.
+# litellm 1.87.2 fixes the chatgpt/* (ChatGPT subscription) provider
+# returning empty Responses output (BerriAI/litellm#25429) and
+# auto-injects GitHub Copilot IDE-auth headers.
 dependencies = [
     "pageindex==0.3.0.dev1",
-    "markitdown[docx,pptx,xlsx,xls]>=0.1.5",
-    "trafilatura>=2.0",
-    "click>=8.0",
-    "watchdog>=3.0",
-    "litellm",
-    "openai-agents",
-    "pyyaml",
-    "python-dotenv",
-    "json-repair",
-    "prompt_toolkit>=3.0",
-    "rich>=13.0",
+    "markitdown[docx,pptx,xlsx,xls]==0.1.5",
+    "trafilatura==2.0.0",
+    "click==8.4.0",
+    "watchdog==6.0.0",
+    "litellm==1.87.2",
+    "openai-agents==0.17.3",
+    "pyyaml==6.0.3",
+    "python-dotenv==1.2.2",
+    "json-repair==0.59.10",
+    "prompt_toolkit==3.0.52",
+    "rich==15.0.0",
 ]
 
 [project.urls]
@@ -52,7 +58,7 @@ openkb = "openkb.cli:cli"
 testpaths = ["tests"]
 
 [project.optional-dependencies]
-dev = ["pytest", "pytest-asyncio"]
+dev = ["pytest==9.0.3", "pytest-asyncio==1.3.0"]
 
 [tool.hatch.version]
 source = "vcs"

tests/conftest.py

@@ -2,6 +2,14 @@
 import pytest
 
 
+@pytest.fixture(autouse=True)
+def _reset_extra_headers():
+    """Keep the process-wide LLM extra-headers stash from leaking across tests."""
+    from openkb.config import set_extra_headers
+    yield
+    set_extra_headers({})
+
+
 @pytest.fixture
 def kb_dir(tmp_path):
     """Create a minimal knowledge base directory structure for testing."""