fix MultiGraph crash, hollow LLM response retry, and skill --help (#796, #795, #792)

#796: add edge_data()/edge_datas() helpers in build.py that tolerate MultiGraph/MultiDiGraph; replace all G.edges[u,v] 2-tuple call sites in __main__.py, serve.py, wiki.py, export.py, analyze.py, benchmark.py; fix same pattern in 10 skill file inline heredocs #795: all 12 skill files now short-circuit on /graphify --help or -h and print the Usage block without running any pipeline steps #792 (hollow response): add _response_is_hollow() predicate in llm.py; when Ollama (or any backend) returns empty/null/whitespace content or a parsed result with no nodes/edges, rewrite finish_reason="length" so _extract_with_adaptive_retry bisects the chunk instead of silently dropping it; applied to _call_openai_compat, _call_claude, _call_bedrock Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-08-28 09:17:02 +00:00 · 2026-05-09 21:17:25 +01:00
parent dc50979a68
commit 23f598f3a0
22 changed files with 416 additions and 46 deletions
@@ -1514,9 +1514,10 @@ def main() -> None:
            sys.exit(0)
        hops = len(path_nodes) - 1
        segments = []
+        from graphify.build import edge_data
        for i in range(len(path_nodes) - 1):
            u, v = path_nodes[i], path_nodes[i + 1]
-            edata = G.edges[u, v]
+            edata = edge_data(G, u, v)
            rel = edata.get("relation", "")
            conf = edata.get("confidence", "")
            conf_str = f" [{conf}]" if conf else ""
@@ -1562,9 +1563,10 @@ def main() -> None:
        print(f"  Degree:    {G.degree(nid)}")
        neighbors = list(G.neighbors(nid))
        if neighbors:
+            from graphify.build import edge_data
            print(f"\nConnections ({len(neighbors)}):")
            for nb in sorted(neighbors, key=lambda n: G.degree(n), reverse=True)[:20]:
-                edata = G.edges[nid, nb]
+                edata = edge_data(G, nid, nb)
                rel = edata.get("relation", "")
                conf = edata.get("confidence", "")
                print(f"  --> {G.nodes[nb].get('label', nb)} [{rel}] [{conf}]")
@@ -3,6 +3,8 @@ from __future__ import annotations
 from pathlib import Path
 import networkx as nx

+from graphify.build import edge_data
+
 # Language families — extensions sharing a runtime can legitimately call each other
 _LANG_FAMILY: dict[str, str] = {
    **{e: "python" for e in (".py", ".pyw")},
@@ -301,7 +303,7 @@ def _cross_community_surprises(
        top_edges = sorted(betweenness.items(), key=lambda x: x[1], reverse=True)[:top_n]
        result = []
        for (u, v), score in top_edges:
-            data = G.edges[u, v]
+            data = edge_data(G, u, v)
            result.append({
                "source": G.nodes[u].get("label", u),
                "target": G.nodes[v].get("label", v),
@@ -6,6 +6,8 @@ from pathlib import Path
 import networkx as nx
 from networkx.readwrite import json_graph

+from graphify.build import edge_data
+

 _CHARS_PER_TOKEN = 4  # standard approximation

@@ -66,7 +68,7 @@ def _query_subgraph_tokens(G: nx.Graph, question: str, depth: int = 3) -> int:
        lines.append(f"NODE {d.get('label', nid)} src={d.get('source_file', '')} loc={d.get('source_location', '')}")
    for u, v in edges_seen:
        if u in visited and v in visited:
-            d = G.edges[u, v]
+            d = edge_data(G, u, v)
            lines.append(f"EDGE {G.nodes[u].get('label', u)} --{d.get('relation', '')}--> {G.nodes[v].get('label', v)}")

    return _estimate_tokens("\n".join(lines))
@@ -45,6 +45,27 @@ def _norm_source_file(p: str | None) -> str | None:
    return p.replace("\\", "/") if p else p


+def edge_data(G: nx.Graph, u: str, v: str) -> dict:
+    """Return one edge attribute dict for (u, v), tolerating MultiGraph.
+
+    For MultiGraph/MultiDiGraph there can be multiple parallel edges;
+    this returns the first one (sufficient for callers that only need
+    relation/confidence for rendering). Fixes #796.
+    """
+    raw = G[u][v]
+    if isinstance(G, (nx.MultiGraph, nx.MultiDiGraph)):
+        return next(iter(raw.values()), {})
+    return raw
+
+
+def edge_datas(G: nx.Graph, u: str, v: str) -> list[dict]:
+    """Return every edge attribute dict for (u, v); always a list."""
+    raw = G[u][v]
+    if isinstance(G, (nx.MultiGraph, nx.MultiDiGraph)):
+        return list(raw.values())
+    return [raw]
+
+
 def build_from_json(extraction: dict, *, directed: bool = False) -> nx.Graph:
    """Build a NetworkX graph from an extraction dict.

@@ -10,6 +10,7 @@ import networkx as nx
 from networkx.readwrite import json_graph
 from graphify.security import sanitize_label
 from graphify.analyze import _node_community_map
+from graphify.build import edge_data

 def _obsidian_tag(name: str) -> str:
    """Sanitize a community name for use as an Obsidian tag.
@@ -802,10 +803,10 @@ def to_obsidian(
        if neighbors:
            lines.append("## Connections")
            for neighbor in sorted(neighbors, key=lambda n: G.nodes[n].get("label", n)):
-                edge_data = G.edges[node_id, neighbor]
+                edata = edge_data(G, node_id, neighbor)
                neighbor_label = node_filename[neighbor]
-                relation = edge_data.get("relation", "")
-                confidence = edge_data.get("confidence", "EXTRACTED")
+                relation = edata.get("relation", "")
+                confidence = edata.get("confidence", "EXTRACTED")
                lines.append(f"- [[{neighbor_label}]] - `{relation}` [{confidence}]")
            lines.append("")

@@ -170,6 +170,26 @@ def _parse_llm_json(raw: str) -> dict:
        return {"nodes": [], "edges": [], "hyperedges": []}


+def _response_is_hollow(raw_content: str | None, parsed: dict) -> bool:
+    """Detect a successful HTTP response that yielded no usable extraction.
+
+    A local model under load (most often Ollama) can return HTTP 200 with an
+    empty / null `message.content`, with whitespace, or with a half-generated
+    JSON prefix that fails to parse. All of these collapse to a "successful"
+    call producing zero nodes and zero edges. Without this check the chunk
+    is silently dropped from the corpus because no exception is raised and
+    `finish_reason` is `"stop"` rather than `"length"`. By flagging the
+    result as hollow, callers can re-route it through the same bisection
+    path used for context-window overflow and `finish_reason="length"`.
+    """
+    if raw_content is None or not raw_content.strip():
+        return True
+    nodes = parsed.get("nodes")
+    edges = parsed.get("edges")
+    hyperedges = parsed.get("hyperedges")
+    return not nodes and not edges and not hyperedges
+
+
 def _backend_env_keys(backend: str) -> list[str]:
    """Return accepted API-key environment variables for a backend."""
    cfg = BACKENDS[backend]
@@ -260,7 +280,8 @@ def _call_openai_compat(
    if "moonshot" in base_url:
        kwargs["extra_body"] = {"thinking": {"type": "disabled"}}
    resp = client.chat.completions.create(**kwargs)
-    result = _parse_llm_json(resp.choices[0].message.content or "{}")
+    raw_content = resp.choices[0].message.content
+    result = _parse_llm_json(raw_content or "{}")
    result["input_tokens"] = resp.usage.prompt_tokens if resp.usage else 0
    result["output_tokens"] = resp.usage.completion_tokens if resp.usage else 0
    result["model"] = model
@@ -268,6 +289,20 @@ def _call_openai_compat(
    # mid-generation. The JSON we got back is truncated; callers should
    # treat this as a signal to retry with smaller input.
    result["finish_reason"] = resp.choices[0].finish_reason
+    # An overwhelmed local model (typically Ollama) can return HTTP 200 with
+    # empty / null content or unparseable half-generated JSON. The call looks
+    # successful, `finish_reason` is `"stop"`, and the chunk would be silently
+    # dropped from the corpus. Re-label as `"length"` so the adaptive retry
+    # layer bisects the chunk — same recovery as a true truncation.
+    if _response_is_hollow(raw_content, result) and result["finish_reason"] != "length":
+        print(
+            f"[graphify] {backend or 'backend'} returned a hollow response "
+            f"(content={'empty' if not (raw_content or '').strip() else 'no nodes/edges'}, "
+            f"output_tokens={result['output_tokens']}); "
+            "treating as truncation so adaptive retry can bisect the chunk.",
+            file=sys.stderr,
+        )
+        result["finish_reason"] = "length"
    output_tokens = result["output_tokens"]
    if output_tokens < 50 and backend == "ollama":
        print(
@@ -296,7 +331,8 @@ def _call_claude(api_key: str, model: str, user_message: str, max_tokens: int =
        system=_EXTRACTION_SYSTEM,
        messages=[{"role": "user", "content": user_message}],
    )
-    result = _parse_llm_json(resp.content[0].text if resp.content else "{}")
+    raw_content = resp.content[0].text if resp.content else None
+    result = _parse_llm_json(raw_content or "{}")
    result["input_tokens"] = resp.usage.input_tokens if resp.usage else 0
    result["output_tokens"] = resp.usage.output_tokens if resp.usage else 0
    result["model"] = model
@@ -304,6 +340,13 @@ def _call_claude(api_key: str, model: str, user_message: str, max_tokens: int =
    # vocabulary so the adaptive-retry layer doesn't have to know which
    # backend produced the result.
    result["finish_reason"] = "length" if resp.stop_reason == "max_tokens" else "stop"
+    if _response_is_hollow(raw_content, result) and result["finish_reason"] != "length":
+        print(
+            "[graphify] claude returned a hollow response; treating as "
+            "truncation so adaptive retry can bisect the chunk.",
+            file=sys.stderr,
+        )
+        result["finish_reason"] = "length"
    return result


@@ -341,6 +384,13 @@ def _call_bedrock(model: str, user_message: str, max_tokens: int = 8192) -> dict
    result["output_tokens"] = usage.get("outputTokens", 0)
    result["model"] = model
    result["finish_reason"] = "length" if resp.get("stopReason") == "max_tokens" else "stop"
+    if _response_is_hollow(text, result) and result["finish_reason"] != "length":
+        print(
+            "[graphify] bedrock returned a hollow response; treating as "
+            "truncation so adaptive retry can bisect the chunk.",
+            file=sys.stderr,
+        )
+        result["finish_reason"] = "length"
    return result


@@ -505,7 +555,7 @@ def _extract_with_adaptive_retry(
    or the API rejects the prompt as too large for the model's context window,
    split the chunk in half and recurse.

-    Two signals drive the retry:
+    Three signals drive the retry, all funnelled through the same code:

    - `finish_reason == "length"` — the model accepted the input but ran out of
      `max_completion_tokens` mid-output. The truncated JSON is unparseable, so
@@ -518,6 +568,12 @@ def _extract_with_adaptive_retry(
      half is the same recovery as for the `length` case and works for the
      same reason.

+    - hollow successful responses — the model returned HTTP 200 with empty,
+      null, or unparseable content (typical of a local Ollama under load).
+      `_call_openai_compat` re-labels these as `finish_reason="length"` so they
+      take the same recovery path; without that the chunk would be silently
+      dropped from the corpus.
+
    Recursion is capped at `max_depth` to bound worst-case cost. A chunk of N
    files can split into up to 2**max_depth pieces — at depth=3 that's 8x. If
    still failing at the cap, we surface the (likely empty) result with a
@@ -6,6 +6,7 @@ from pathlib import Path
 import networkx as nx
 from networkx.readwrite import json_graph
 from graphify.security import sanitize_label
+from graphify.build import edge_data


 def _load_graph(graph_path: str) -> nx.Graph:
@@ -403,7 +404,7 @@ def serve(graph_path: str = "graphify-out/graph.json") -> None:
        nid = matches[0]
        lines = [f"Neighbors of {sanitize_label(G.nodes[nid].get('label', nid))}:"]
        for neighbor in G.neighbors(nid):
-            d = G.edges[nid, neighbor]
+            d = edge_data(G, nid, neighbor)
            rel = d.get("relation", "")
            if rel_filter and rel_filter not in rel.lower():
                continue
@@ -466,7 +467,7 @@ def serve(graph_path: str = "graphify-out/graph.json") -> None:
        segments = []
        for i in range(len(path_nodes) - 1):
            u, v = path_nodes[i], path_nodes[i + 1]
-            edata = G.edges[u, v]
+            edata = edge_data(G, u, v)
            rel = edata.get("relation", "")
            conf = edata.get("confidence", "")
            conf_str = f" [{conf}]" if conf else ""
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -952,7 +954,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1024,7 +1026,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1094,7 +1096,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -952,7 +954,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1024,7 +1026,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1094,7 +1096,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -1011,7 +1013,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1083,7 +1085,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1153,7 +1155,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -53,6 +53,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -1040,7 +1042,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1112,7 +1114,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1182,7 +1184,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -1008,7 +1010,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1080,7 +1082,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1150,7 +1152,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -50,6 +50,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -951,7 +953,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1023,7 +1025,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1093,7 +1095,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -1061,7 +1063,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1133,7 +1135,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1203,7 +1205,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -50,6 +50,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -951,7 +953,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")} [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1023,7 +1025,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1093,7 +1095,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -51,6 +51,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -976,7 +978,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get(\"label\", nid)} [src={d.get(\"source_file\",\"\")} loc={d.get(\"source_location\",\"\")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get(\"label\",u)} --{d.get(\"relation\",\"\")}] [{d.get(\"confidence\",\"\")}]--> {G.nodes[v].get(\"label\",v)}')

 output = '\n'.join(lines)
@@ -1048,7 +1050,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1117,7 +1119,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -21,6 +21,8 @@ Turn any folder of files into a navigable knowledge graph with community detecti

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -54,6 +54,8 @@ Use it for:

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

 Follow these steps in order. Do not skip steps.
@@ -1090,7 +1092,7 @@ for nid in ranked_nodes:
    lines.append(f'  NODE {d.get("label", nid)} [src={d.get("source_file","")} loc={d.get("source_location","")}]')
 for u, v in subgraph_edges:
    if u in subgraph_nodes and v in subgraph_nodes:
-        d = G.edges[u, v]
+        _raw = G[u][v]; d = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
        lines.append(f'  EDGE {G.nodes[u].get("label",u)} --{d.get("relation","")} [{d.get("confidence","")}]--> {G.nodes[v].get("label",v)}')

 output = '\n'.join(lines)
@@ -1166,7 +1168,7 @@ try:
    for i, nid in enumerate(path):
        label = G.nodes[nid].get('label', nid)
        if i < len(path) - 1:
-            edge = G.edges[nid, path[i+1]]
+            _raw = G[nid][path[i+1]]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
            rel = edge.get('relation', '')
            conf = edge.get('confidence', '')
            print(f'  {label} --{rel}--> [{conf}]')
@@ -1240,7 +1242,7 @@ print(f'  degree: {G.degree(nid)}')
 print()
 print('CONNECTIONS:')
 for neighbor in G.neighbors(nid):
-    edge = G.edges[nid, neighbor]
+    _raw = G[nid][neighbor]; edge = next(iter(_raw.values()), {}) if isinstance(G, nx.MultiGraph) else _raw
    nlabel = G.nodes[neighbor].get('label', neighbor)
    rel = edge.get('relation', '')
    conf = edge.get('confidence', '')
@@ -47,9 +47,11 @@ Drop any folder of code, docs, papers, images, or video into graphify and get a

 ## What You Must Do When Invoked

+If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
+
 If no path was given, use `.` (current directory). Do not ask the user for a path.

-If the path argument starts with `https://github.com/` or `http://github.com/`, treat it as a GitHub URL — run Step 0 before anything else, then continue with the resolved local path.
+If the path argument starts with `https://github.com/` or `http://github.com/`, treat it as a GitHub URL - run Step 0 before anything else, then continue with the resolved local path.

 Follow these steps in order. Do not skip steps.

@@ -5,6 +5,8 @@ from collections import Counter
 from pathlib import Path
 import networkx as nx

+from graphify.build import edge_data
+

 def _safe_filename(name: str) -> str:
    """Make a label safe for use as a filename across platforms.
@@ -48,7 +50,7 @@ def _community_article(
    conf_counts: Counter = Counter()
    for nid in nodes:
        for neighbor in G.neighbors(nid):
-            ed = G.edges[nid, neighbor]
+            ed = edge_data(G, nid, neighbor)
            conf_counts[ed.get("confidence", "EXTRACTED")] += 1
    total_edges = sum(conf_counts.values()) or 1

@@ -118,7 +120,7 @@ def _god_node_article(G: nx.Graph, nid: str, labels: dict[int, str]) -> str:
    by_relation: dict[str, list[str]] = {}
    for neighbor in sorted(G.neighbors(nid), key=lambda n: G.degree(n), reverse=True):
        nd = G.nodes[neighbor]
-        ed = G.edges[nid, neighbor]
+        ed = edge_data(G, nid, neighbor)
        rel = ed.get("relation", "related")
        neighbor_label = nd.get("label", neighbor)
        conf = ed.get("confidence", "")
@@ -1,6 +1,8 @@
 import json
 from pathlib import Path
-from graphify.build import build_from_json, build, build_merge
+import networkx as nx
+from networkx.readwrite import json_graph
+from graphify.build import build_from_json, build, build_merge, edge_data, edge_datas

 FIXTURES = Path(__file__).parent / "fixtures"

@@ -195,3 +197,87 @@ def test_build_merge_preserves_call_edge_direction(tmp_path):
        f"calls edge target flipped after build_merge round-trip: "
        f"expected {truth_tgt} (b), got {reloaded_calls[0]['target']}"
    )
+
+
+# Regression tests for #796 — edge_data / edge_datas helpers must tolerate
+# MultiGraph and MultiDiGraph, which networkx's node_link_graph() produces
+# whenever the loaded JSON has multigraph: true. Plain G.edges[u, v] crashes
+# on those with `ValueError: not enough values to unpack (expected 3, got 2)`.
+
+def test_edge_data_simple_graph():
+    G = nx.Graph()
+    G.add_edge("a", "b", relation="calls", confidence="EXTRACTED")
+    d = edge_data(G, "a", "b")
+    assert isinstance(d, dict)
+    assert d["relation"] == "calls"
+    assert d["confidence"] == "EXTRACTED"
+
+
+def test_edge_datas_simple_graph_returns_singleton_list():
+    G = nx.Graph()
+    G.add_edge("a", "b", relation="calls", confidence="EXTRACTED")
+    ds = edge_datas(G, "a", "b")
+    assert isinstance(ds, list)
+    assert len(ds) == 1
+    assert ds[0]["relation"] == "calls"
+
+
+def test_edge_data_multigraph_with_parallel_edges():
+    G = nx.MultiGraph()
+    G.add_edge("a", "b", relation="calls", confidence="EXTRACTED")
+    G.add_edge("a", "b", relation="references", confidence="INFERRED")
+    d = edge_data(G, "a", "b")
+    assert isinstance(d, dict)
+    # First parallel edge wins; should be one of the two attribute dicts above.
+    assert d.get("relation") in ("calls", "references")
+
+
+def test_edge_datas_multigraph_returns_all_parallel_edges():
+    G = nx.MultiGraph()
+    G.add_edge("a", "b", relation="calls", confidence="EXTRACTED")
+    G.add_edge("a", "b", relation="references", confidence="INFERRED")
+    ds = edge_datas(G, "a", "b")
+    assert isinstance(ds, list)
+    assert len(ds) == 2
+    relations = {e.get("relation") for e in ds}
+    assert relations == {"calls", "references"}
+
+
+def test_edge_data_multidigraph():
+    G = nx.MultiDiGraph()
+    G.add_edge("a", "b", relation="calls")
+    G.add_edge("a", "b", relation="imports")
+    d = edge_data(G, "a", "b")
+    assert isinstance(d, dict)
+    assert d.get("relation") in ("calls", "imports")
+    ds = edge_datas(G, "a", "b")
+    assert len(ds) == 2
+
+
+def test_edge_data_node_link_multigraph_roundtrip():
+    """A node_link JSON with multigraph: true must load as MultiGraph and the
+    helpers must operate on it without raising the 3-tuple unpack ValueError."""
+    data = {
+        "directed": False,
+        "multigraph": True,
+        "graph": {},
+        "nodes": [
+            {"id": "a", "label": "A"},
+            {"id": "b", "label": "B"},
+        ],
+        "links": [
+            {"source": "a", "target": "b", "relation": "calls", "confidence": "EXTRACTED"},
+            {"source": "a", "target": "b", "relation": "references", "confidence": "INFERRED"},
+        ],
+    }
+    try:
+        G = json_graph.node_link_graph(data, edges="links")
+    except TypeError:
+        G = json_graph.node_link_graph(data)
+    assert isinstance(G, nx.MultiGraph)
+    # Plain G.edges[u, v] would raise here; the helper must not.
+    d = edge_data(G, "a", "b")
+    assert isinstance(d, dict)
+    assert d.get("relation") in ("calls", "references")
+    ds = edge_datas(G, "a", "b")
+    assert len(ds) == 2
@@ -187,3 +187,176 @@ def test_adaptive_retry_re_raises_unrelated_errors(tmp_path):
            llm._extract_with_adaptive_retry(
                [f], backend="kimi", api_key="k", model="m", root=tmp_path, max_depth=3
            )
+
+
+# ---------------------------------------------------------------------------
+# Hollow-response detection: empty / null / unparseable content from a
+# successful HTTP call must route into the same bisection path as a true
+# `finish_reason="length"` truncation, not be silently dropped.
+# ---------------------------------------------------------------------------
+
+
+def test_response_is_hollow_flags_empty_string():
+    assert llm._response_is_hollow("", {"nodes": [], "edges": [], "hyperedges": []})
+
+
+def test_response_is_hollow_flags_none_content():
+    assert llm._response_is_hollow(None, {"nodes": [], "edges": [], "hyperedges": []})
+
+
+def test_response_is_hollow_flags_whitespace_only():
+    assert llm._response_is_hollow("   \n\t  ", {"nodes": [], "edges": [], "hyperedges": []})
+
+
+def test_response_is_hollow_flags_parsed_but_no_nodes_or_edges():
+    # Content was non-empty (e.g. model said `{"sorry": "I cannot"}` or returned
+    # `{}` literally) but the parsed result has nothing usable.
+    assert llm._response_is_hollow('{"sorry": "I cannot"}', {})
+    assert llm._response_is_hollow("{}", {"nodes": [], "edges": [], "hyperedges": []})
+
+
+def test_response_is_hollow_accepts_real_extraction():
+    parsed = {"nodes": [{"id": "x"}], "edges": [], "hyperedges": []}
+    assert not llm._response_is_hollow('{"nodes":[{"id":"x"}]}', parsed)
+    parsed = {"nodes": [], "edges": [{"source": "a", "target": "b"}], "hyperedges": []}
+    assert not llm._response_is_hollow('{"edges":[...]}', parsed)
+
+
+def _fake_openai_response(content, *, finish_reason="stop", prompt_tokens=100, completion_tokens=0):
+    """Build a minimal stand-in for an `openai` SDK ChatCompletion response."""
+    class _Usage:
+        def __init__(self):
+            self.prompt_tokens = prompt_tokens
+            self.completion_tokens = completion_tokens
+
+    class _Message:
+        def __init__(self):
+            self.content = content
+
+    class _Choice:
+        def __init__(self):
+            self.message = _Message()
+            self.finish_reason = finish_reason
+
+    class _Resp:
+        def __init__(self):
+            self.choices = [_Choice()]
+            self.usage = _Usage()
+
+    return _Resp()
+
+
+def _install_fake_openai(monkeypatch, fake_resp):
+    """Inject a stub `openai` module so `_call_openai_compat` can run without
+    the real SDK installed. The function does `from openai import OpenAI`
+    inside its body, so we satisfy that lookup via `sys.modules`."""
+    import sys
+    import types
+
+    class _FakeOpenAI:
+        def __init__(self, *_, **__):
+            self.chat = self
+            self.completions = self
+        def create(self, **__):
+            return fake_resp
+
+    fake_module = types.ModuleType("openai")
+    fake_module.OpenAI = _FakeOpenAI
+    monkeypatch.setitem(sys.modules, "openai", fake_module)
+
+
+def test_call_openai_compat_relabels_empty_content_as_length(monkeypatch):
+    # Simulates an overwhelmed Ollama: HTTP 200, empty content, finish_reason
+    # "stop", zero completion tokens. Pre-fix this would silently return an
+    # empty fragment and the chunk would be dropped. Post-fix `finish_reason`
+    # is rewritten to "length" so the adaptive retry layer bisects.
+    fake_resp = _fake_openai_response("", finish_reason="stop", completion_tokens=0)
+    _install_fake_openai(monkeypatch, fake_resp)
+
+    result = llm._call_openai_compat(
+        "http://localhost:11434/v1", "ollama", "qwen2.5-coder:7b",
+        "user msg", temperature=0, max_completion_tokens=8192, backend="ollama",
+    )
+    assert result["finish_reason"] == "length", (
+        "empty content from a 'successful' call must be re-labelled so the "
+        "adaptive retry layer treats it as a truncation and bisects the chunk"
+    )
+
+
+def test_call_openai_compat_relabels_none_content_as_length(monkeypatch):
+    fake_resp = _fake_openai_response(None, finish_reason="stop")
+    _install_fake_openai(monkeypatch, fake_resp)
+
+    result = llm._call_openai_compat(
+        "http://localhost:11434/v1", "ollama", "qwen2.5-coder:7b",
+        "u", temperature=0, max_completion_tokens=8192, backend="ollama",
+    )
+    assert result["finish_reason"] == "length"
+
+
+def test_call_openai_compat_relabels_unparseable_json_as_length(monkeypatch):
+    # A half-generated response: `{"nodes": [{"id":` parses to {} (empty
+    # fragment) via _parse_llm_json's JSONDecodeError fallback. That is also
+    # hollow and must trigger bisection.
+    fake_resp = _fake_openai_response('{"nodes": [{"id":', finish_reason="stop", completion_tokens=20)
+    _install_fake_openai(monkeypatch, fake_resp)
+
+    result = llm._call_openai_compat(
+        "http://localhost:11434/v1", "ollama", "qwen2.5-coder:7b",
+        "u", temperature=0, max_completion_tokens=8192, backend="ollama",
+    )
+    assert result["finish_reason"] == "length"
+
+
+def test_call_openai_compat_preserves_real_finish_reason(monkeypatch):
+    # A genuine extraction with real nodes must NOT be re-labelled.
+    fake_resp = _fake_openai_response(
+        '{"nodes":[{"id":"a"}],"edges":[],"hyperedges":[]}',
+        finish_reason="stop",
+        completion_tokens=200,
+    )
+    _install_fake_openai(monkeypatch, fake_resp)
+
+    result = llm._call_openai_compat(
+        "http://localhost:11434/v1", "k", "m",
+        "u", temperature=0, max_completion_tokens=8192, backend="kimi",
+    )
+    assert result["finish_reason"] == "stop"
+    assert result["nodes"] == [{"id": "a"}]
+
+
+def test_adaptive_retry_bisects_on_hollow_ollama_response(tmp_path):
+    # End-to-end: an overwhelmed Ollama returns hollow on the full 4-file
+    # chunk; halves succeed. The bug being fixed is that pre-fix this
+    # produces zero nodes (chunk silently dropped). Post-fix the hollow
+    # response is relabelled `finish_reason="length"` and the existing
+    # bisection path recovers the full 4 nodes.
+    files = [tmp_path / f"f{i}.md" for i in range(4)]
+    for f in files:
+        f.write_text("hello")
+
+    calls = {"n": 0}
+
+    def fake_extract(chunk, *_, **__):
+        calls["n"] += 1
+        if len(chunk) == 4:
+            # Hollow response: looks successful, finish_reason already
+            # rewritten to "length" by _call_openai_compat.
+            return {
+                "nodes": [], "edges": [], "hyperedges": [],
+                "input_tokens": 100, "output_tokens": 0,
+                "model": "m", "finish_reason": "length",
+            }
+        return _ok(nodes=[{"id": f.stem} for f in chunk])
+
+    with patch("graphify.llm.extract_files_direct", side_effect=fake_extract):
+        result = llm._extract_with_adaptive_retry(
+            files, backend="ollama", api_key="ollama", model="qwen2.5-coder:7b",
+            root=tmp_path, max_depth=3,
+        )
+
+    assert len(result["nodes"]) == 4, (
+        "bisection should recover all 4 nodes from the two halves after the "
+        "full chunk came back hollow"
+    )
+    assert calls["n"] == 3  # 1 hollow + 2 successful halves