A drop-in replacement chat template for google/gemma-4-31B-it tuned for open-source agentic coding harnesses.

custom_pub_chat_template_gemma4.jinja

{#---------------------------------------------------------------------
   custom_pub_chat_template_gemma4.jinja
   =====================================
   A public, harness-friendly fork of Google's Gemma 4 chat template,
   tuned for open-source agentic coding harnesses like:
     - anomalyco/opencode      (https://github.com/anomalyco/opencode)
     - earendil-works/pi       (https://github.com/earendil-works/pi)
     - openclaw, OpenHarness,  similar Claude-Code-style harnesses

   WHY THIS FORK EXISTS
   --------------------
   The upstream chat template at google/gemma-4-31B-it is correct for
   chat use, but four real edge cases bite agentic coding harnesses:

   1. tool_call.arguments arriving as a JSON string (Vercel AI SDK and
      several OpenAI-compatible adapters serialize this way) is silently
      wrapped in extra braces by the upstream template, producing invalid
      Gemma 4 DSL like  call:fn{{"city":"Tokyo"}}  — nested braces, JSON
      colons, and quoted keys, none of which the model was trained on.
      Symptom: degraded tool-call accuracy, mysterious arguments collapse
      to {} on repeated calls.

   2. Prior-turn reasoning is dropped from history. The model card says
      "historical model output should only include the final response,"
      but agentic harnesses doing multi-step tool calls benefit
      materially from keeping the prior reasoning visible. The Qwen3.6
      analogue of this bug is documented at:
        https://github.com/earendil-works/pi/issues/3325
      Symptom (on Qwen and Gemma alike): after 2-3 turns, every tool call
      collapses to  arguments: {}  even though the model's prior reasoning
      correctly identified the parameters it needed.

   3. enable_thinking defaults to FALSE in the upstream template, and
      most OpenAI-compatible adapters drop unknown request fields:
        https://github.com/anomalyco/opencode/issues/24264
      So the harness ends up with thinking permanently off, agentic
      tool-call accuracy suffers, and there's no obvious failure signal.

   4. JSON  null  values inside tool_call.arguments render as the bare
      string  "None"  (Python repr of None survives Jinja). Optional
      fields are very common in coding tools (find_files, search:
      pattern=..., language=null) and this corrupts the prompt silently.

   This fork is also forked from a private engineering fork used in
   internal harnesses; the public copy reuses the same five patches but
   adds expanded comments, removes references to private design docs,
   and ships with a self-contained pytest conformance suite.

   PATCH INVENTORY (full details next to each patch site below)
   ------------------------------------------------------------
   P1  format_argument: emit JSON null instead of bare "None"
   P2  enable_thinking defaults to TRUE
   P3  tool_call.arguments as string: RAISE instead of silent corruption
   P4  preserve_thinking kwarg (default TRUE) keeps prior <|channel>
   P5  fix HF discussion #62 turn-tag close asymmetry

   INVARIANT
   ---------
   With  enable_thinking=False  AND  preserve_thinking=False  passed
   explicitly, this template renders byte-for-byte identical to the
   upstream verbatim template on every input that doesn't hit P1, P3,
   or P5's bug sites. The conformance suite at
     tests/test_custom_pub_chat_template.py
   locks this in across 21 representative cases.

   USAGE
   -----
   Server side (e.g. vLLM or SGLang):
     --chat-template /path/to/custom_pub_chat_template_gemma4.jinja

   Harness side: no changes required for the common case. If you need
   to force defaults off (e.g. to match upstream behaviour exactly):
     {
       "extra_body": {
         "chat_template_kwargs": {
           "enable_thinking": false,
           "preserve_thinking": false
         }
       }
     }

   For opencode-style providers, this maps to the `chat_template_args`
   field in models config; for pi, set thinkingFormat appropriately
   in the provider's compat block and pi will inject these kwargs.

   PINS
   ----
   Forked from google/gemma-4-31B-it @ fcf2302760ae9c6e528a8dbba9dd636e56848237
   Fork date:    2026-05-22
   License:      Apache 2.0 (same as upstream)
   Maintainer:   see repo README

---------------------------------------------------------------------#}

{%- macro format_parameters(properties, required, filter_keys=false) -%}
    {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
    {%- set ns = namespace(found_first=false) -%}
    {%- for key, value in properties | dictsort -%}
        {%- set add_comma = false -%}
        {%- if not filter_keys or key not in standard_keys -%}
            {%- if ns.found_first %},{% endif -%}
            {%- set ns.found_first = true -%}
            {{ key }}:{
            {%- if value['description'] -%}
                description:<|"|>{{ value['description'] }}<|"|>
                {%- set add_comma = true -%}
            {%- endif -%}
            {%- if value['type'] | upper == 'STRING' -%}
                {%- if value['enum'] -%}
                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                    enum:{{ format_argument(value['enum']) }}
                {%- endif -%}
            {%- elif value['type'] | upper == 'ARRAY' -%}
                {%- if value['items'] is mapping and value['items'] -%}
                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                    items:{
                    {%- set ns_items = namespace(found_first=false) -%}
                    {%- for item_key, item_value in value['items'] | dictsort -%}
                        {%- if item_value is not none -%}
                            {%- if ns_items.found_first %},{% endif -%}
                            {%- set ns_items.found_first = true -%}
                            {%- if item_key == 'properties' -%}
                                properties:{
                                {%- if item_value is mapping -%}
                                    {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
                                {%- endif -%}
                                }
                            {%- elif item_key == 'required' -%}
                                required:[
                                {%- for req_item in item_value -%}
                                    <|"|>{{- req_item -}}<|"|>
                                    {%- if not loop.last %},{% endif -%}
                                {%- endfor -%}
                                ]
                            {%- elif item_key == 'type' -%}
                                {%- if item_value is string -%}
                                    type:{{ format_argument(item_value | upper) }}
                                {%- else -%}
                                    type:{{ format_argument(item_value | map('upper') | list) }}
                                {%- endif -%}
                            {%- else -%}
                                {{ item_key }}:{{ format_argument(item_value) }}
                            {%- endif -%}
                        {%- endif -%}
                    {%- endfor -%}
                    }
                {%- endif -%}
            {%- endif -%}
            {%- if value['nullable'] %}
                {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                nullable:true
            {%- endif -%}
            {%- if value['type'] | upper == 'OBJECT' -%}
                {%- if value['properties'] is defined and value['properties'] is mapping -%}
                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                    properties:{
                    {{- format_parameters(value['properties'], value['required'] | default([])) -}}
                    }
                {%- elif value is mapping -%}
                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                    properties:{
                    {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
                    }
                {%- endif -%}
                {%- if value['required'] -%}
                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
                    required:[
                    {%- for item in value['required'] | default([]) -%}
                        <|"|>{{- item -}}<|"|>
                        {%- if not loop.last %},{% endif -%}
                    {%- endfor -%}
                    ]
                {%- endif -%}
            {%- endif -%}
            {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
            type:<|"|>{{ value['type'] | upper }}<|"|>}
        {%- endif -%}
    {%- endfor -%}
{%- endmacro -%}
{%- macro format_function_declaration(tool_data) -%}
    declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
    {%- set params = tool_data['function']['parameters'] -%}
    {%- if params -%}
        ,parameters:{
        {%- if params['properties'] -%}
            properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
        {%- endif -%}
        {%- if params['required'] -%}
            required:[
            {%- for item in params['required'] -%}
                <|"|>{{- item -}}<|"|>
                {{- ',' if not loop.last -}}
            {%- endfor -%}
            ],
        {%- endif -%}
        {%- if params['type'] -%}
            type:<|"|>{{- params['type'] | upper -}}<|"|>}
        {%- endif -%}
    {%- endif -%}
    {%- if 'response' in tool_data['function'] -%}
        {%- set response_declaration = tool_data['function']['response'] -%}
        ,response:{
        {%- if response_declaration['description'] -%}
            description:<|"|>{{- response_declaration['description'] -}}<|"|>,
        {%- endif -%}
        {%- if response_declaration['type'] | upper == 'OBJECT' -%}
            type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
        {%- endif -%}
    {%- endif -%}
    }
{%- endmacro -%}
{%- macro format_argument(argument, escape_keys=True) -%}
    {#- P1 (public fork): emit JSON null for None values rather than the
        bare string "None". Jinja's default coercion of Python's None
        goes through str(None) -> "None", which then leaks into the
        Gemma 4 DSL as a literal token the model has never been trained
        on. Common bite path: a coding tool's optional argument
        (language=null in a find-files call, after=null in a search,
        etc.) → upstream emits  after:None  in the DSL → model
        confusion. We emit  after:null  instead, matching the JSON wire
        format the model has actually seen.

        Branch ordering: `is none` must precede `is string`, `is
        mapping`, `is sequence`, etc., because None matches NONE of
        them in Jinja's type tests but the final else-branch
        ({{ argument }}) would otherwise stringify it. -#}
    {%- if argument is none -%}
        {{- 'null' -}}
    {%- elif argument is string -%}
        {{- '<|"|>' + argument + '<|"|>' -}}
    {%- elif argument is boolean -%}
        {{- 'true' if argument else 'false' -}}
    {%- elif argument is mapping -%}
        {{- '{' -}}
        {%- set ns = namespace(found_first=false) -%}
        {%- for key, value in argument | dictsort -%}
            {%- if ns.found_first %},{% endif -%}
            {%- set ns.found_first = true -%}
            {%- if escape_keys -%}
                {{- '<|"|>' + key + '<|"|>' -}}
            {%- else -%}
                {{- key -}}
            {%- endif -%}
            :{{- format_argument(value, escape_keys=escape_keys) -}}
        {%- endfor -%}
        {{- '}' -}}
    {%- elif argument is sequence -%}
        {{- '[' -}}
        {%- for item in argument -%}
            {{- format_argument(item, escape_keys=escape_keys) -}}
            {%- if not loop.last %},{% endif -%}
        {%- endfor -%}
        {{- ']' -}}
    {%- else -%}
        {{- argument -}}
    {%- endif -%}
{%- endmacro -%}
{%- macro strip_thinking(text) -%}
    {%- set ns = namespace(result='') -%}
    {%- for part in text.split('<channel|>') -%}
        {%- if '<|channel>' in part -%}
            {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
        {%- else -%}
            {%- set ns.result = ns.result + part -%}
        {%- endif -%}
    {%- endfor -%}
    {{- ns.result | trim -}}
{%- endmacro -%}

{%- macro format_tool_response_block(tool_name, response) -%}
    {{- '<|tool_response>' -}}
    {%- if response is mapping -%}
        {{- 'response:' + tool_name + '{' -}}
        {%- for key, value in response | dictsort -%}
            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
            {%- if not loop.last %},{% endif -%}
        {%- endfor -%}
        {{- '}' -}}
    {%- else -%}
        {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
    {%- endif -%}
    {{- '<tool_response|>' -}}
{%- endmacro -%}

{%- set ns = namespace(prev_message_type=None) -%}
{%- set loop_messages = messages -%}

{#- P2 (public fork): default enable_thinking to TRUE.

    Why: Gemma 4's upstream template defaults enable_thinking to False
    (or undefined). This is wrong for agentic coding harnesses for two
    reasons:

    1. Google's own model card: thinking "significantly enhances
       function-calling accuracy" — and tool calling IS the core
       contract that coding harnesses use the model for. Defaulting it
       off means most opencode/pi users see degraded tool accuracy and
       have no obvious way to fix it.

    2. Most OpenAI-compatible SDKs (notably Vercel AI SDK used by
       opencode) strip unknown request fields, so a harness that tries
       to pass  chat_template_kwargs.enable_thinking=true  per request
       has it silently dropped. See:
         https://github.com/anomalyco/opencode/issues/24264

    Flipping the SERVER-SIDE default to True makes "the agentic
    happy-path" the default and lets harnesses that explicitly want
    chat-only behaviour override it to false per request:

        {"extra_body":{"chat_template_kwargs":{"enable_thinking":false}}}

    After this `set`, enable_thinking is unconditionally defined as a
    bool, so downstream `is defined` guards are dropped. -#}
{%- set enable_thinking = enable_thinking | default(true) -%}

{{- bos_token -}}
{#- Handle System/Tool Definitions Block -#}
{%- if enable_thinking or tools or messages[0]['role'] in ['system', 'developer'] -%}
    {{- '<|turn>system\n' -}}
    {#- Inject Thinking token at the very top of the FIRST system turn -#}
    {%- if enable_thinking -%}
        {{- '<|think|>\n' -}}
        {%- set ns.prev_message_type = 'think' -%}
    {%- endif -%}
    {%- if messages[0]['role'] in ['system', 'developer'] -%}
        {%- if messages[0]['content'] is string -%}
            {{- messages[0]['content'] | trim -}}
        {%- elif messages[0]['content'] is sequence -%}
            {%- for item in messages[0]['content'] -%}
                {{- item['text'] | trim + ' '-}}
            {%- endfor -%}
        {%- endif -%}
        {%- set loop_messages = messages[1:] -%}
    {%- endif -%}
    {%- if tools -%}
        {%- for tool in tools %}
            {{- '<|tool>' -}}
            {{- format_function_declaration(tool) | trim -}}
            {{- '<tool|>' -}}
        {%- endfor %}
        {%- set ns.prev_message_type = 'tool' -%}
    {%- endif -%}
    {{- '<turn|>\n' -}}
{%- endif %}

{#- P4 (public fork): preserve_thinking kwarg, default TRUE.

    Why: upstream's reasoning re-emission gate fires only when an
    assistant message (a) carries `reasoning`/`reasoning_content`,
    (b) has tool_calls, AND (c) is AFTER the last user message. That
    third clause is what causes the canonical multi-turn-tool-loop
    breakage:

      User: "find files matching '*.py' in src"
      Assistant: (reasoning=...calling find_files...) tool_call:
                 find_files(pattern='*.py', dir='src')
      Tool: [result list]
      User: "now look for '*.ts' too"
      Assistant: (reasoning=...) tool_call: find_files(pattern={}, dir={})
        ↑↑↑ arguments collapse to empty here because the prior
            reasoning the model would have learned to imitate is
            invisible — the previous-turn <|channel> was dropped.

    The same shape was reported on Qwen3.6 and resolved by the
    preserve_thinking kwarg there:
      https://github.com/earendil-works/pi/issues/3325

    Gemma 4's model card says "historical model output should only
    include the final response" — that guidance is correct for plain
    chat but actively harmful for multi-turn agentic tool calling. P4
    optionally drops the (c) gate so prior reasoning stays visible to
    the model on subsequent turns.

    Set preserve_thinking=false to recover upstream behaviour exactly
    (used by the conformance suite to verify byte-identity). -#}
{%- set preserve_thinking = preserve_thinking | default(true) -%}

{#- Pre-scan: find last user message index for reasoning guard -#}
{%- set ns_turn = namespace(last_user_idx=-1) -%}
{%- for i in range(loop_messages | length) -%}
    {%- if loop_messages[i]['role'] == 'user' -%}
        {%- set ns_turn.last_user_idx = i -%}
    {%- endif -%}
{%- endfor -%}

{#- Loop through messages -#}
{%- for message in loop_messages -%}
    {%- if message['role'] != 'tool' -%}
    {%- set ns.prev_message_type = None -%}
    {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
    {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
    {%- set prev_nt = namespace(role=None, found=false) -%}
    {%- if loop.index0 > 0 -%}
        {%- for j in range(loop.index0 - 1, -1, -1) -%}
            {%- if not prev_nt.found -%}
                {%- if loop_messages[j]['role'] != 'tool' -%}
                    {%- set prev_nt.role = loop_messages[j]['role'] -%}
                    {%- set prev_nt.found = true -%}
                {%- endif -%}
            {%- endif -%}
        {%- endfor -%}
    {%- endif -%}
    {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
    {%- if not continue_same_model_turn -%}
        {{- '<|turn>' + role + '\n' }}
    {%- endif -%}

    {#- Render reasoning/reasoning_content as thinking channel.

        Upstream gate (all three required to re-emit):
          (a) the message carries reasoning or reasoning_content,
          (b) the message has tool_calls,
          (c) the message is after the last user message in history.

        P4 (public fork): when preserve_thinking is true (default), drop
        clause (c) so prior assistant turns' <|channel> blocks survive.
        See the long P4 comment above the pre-scan for why this matters
        for agentic tool loops. The (b) gate stays — re-emitting a
        <|channel> on a finalised text-only assistant turn is not in
        the model's training distribution. -#}
    {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
    {%- set thinking_gate = (loop.index0 > ns_turn.last_user_idx) or preserve_thinking -%}
    {%- if thinking_text and thinking_gate and message.get('tool_calls') -%}
        {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
    {%- endif -%}

            {%- if message['tool_calls'] -%}
                {%- for tool_call in message['tool_calls'] -%}
                    {%- set function = tool_call['function'] -%}
                    {{- '<|tool_call>call:' + function['name'] + '{' -}}
                    {%- if function['arguments'] is mapping -%}
                        {%- set ns_args = namespace(found_first=false) -%}
                        {%- for key, value in function['arguments'] | dictsort -%}
                            {%- if ns_args.found_first %},{% endif -%}
                            {%- set ns_args.found_first = true -%}
                            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
                        {%- endfor -%}
                    {%- elif function['arguments'] is none -%}
                        {#- P3 (public fork): None / missing arguments is
                            valid (means: call this tool with no args).
                            Emit an empty {} via the empty for-loop above. -#}
                    {%- else -%}
                        {#- P3 (public fork): refuse string (or any other
                            non-mapping) arguments rather than silently
                            corrupting the prompt.

                            Bug surface: many OpenAI-compatible SDKs (most
                            notably Vercel AI SDK, used by opencode) hand
                            tool_call.arguments back as a JSON-encoded
                            STRING — e.g. '{"city":"Tokyo"}' — rather
                            than the already-deserialized object. The
                            upstream Gemma 4 template silently emits this
                            string verbatim inside an extra pair of
                            braces, producing invalid Gemma 4 DSL:
                              call:fn{{"city":"Tokyo"}}
                            (nested braces, JSON colons, quoted keys —
                            none of which the model has been trained on).
                            The model usually still produces a plausible
                            response, which makes the bug INSIDIOUS: it
                            looks like a quality problem with the model,
                            not a prompt-corruption bug in the harness.

                            Fix: harnesses MUST deserialize
                              tool_calls[].function.arguments
                            exactly once on ingest and store the object.
                            See the canonical pi-side discussion:
                              https://github.com/earendil-works/pi/issues/3325

                            We raise here so the bug surfaces at the
                            server (an obvious HTTP error to debug)
                            rather than as a quiet model-output
                            regression. -#}
                        {{- raise_exception(
                            "custom_pub_chat_template_gemma4: "
                            "tool_calls[].function.arguments must be a JSON "
                            "object (mapping). Got a "
                            ~ (function['arguments'] | string | length | string)
                            ~ "-char "
                            ~ (function['arguments'].__class__.__name__ if function['arguments'].__class__ is defined else 'non-mapping')
                            ~ ". This is almost always the harness handing back "
                            "a JSON-encoded STRING rather than the deserialized "
                            "object. Deserialize once on ingest and store the "
                            "object. See: github.com/earendil-works/pi/issues/3325"
                        ) -}}
                    {%- endif -%}
                    {{- '}<tool_call|>' -}}
                {%- endfor -%}
                {%- set ns.prev_message_type = 'tool_call' -%}
            {%- endif -%}

            {%- set ns_tr_out = namespace(flag=false) -%}
            {%- if message.get('tool_responses') -%}
                {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
                {%- for tool_response in message['tool_responses'] -%}
                    {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
                    {%- set ns_tr_out.flag = true -%}
                    {%- set ns.prev_message_type = 'tool_response' -%}
                {%- endfor -%}
            {%- elif message.get('tool_calls') -%}
                {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
                {%- set ns_tool_scan = namespace(stopped=false) -%}
                {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
                    {%- if ns_tool_scan.stopped -%}
                    {%- elif loop_messages[k]['role'] != 'tool' -%}
                        {%- set ns_tool_scan.stopped = true -%}
                    {%- else -%}
                        {%- set follow = loop_messages[k] -%}
                        {#- Resolve tool_call_id to function name -#}
                        {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
                        {%- for tc in message['tool_calls'] -%}
                            {%- if tc.get('id') == follow.get('tool_call_id') -%}
                                {%- set ns_tname.name = tc['function']['name'] -%}
                            {%- endif -%}
                        {%- endfor -%}
                        {#- Handle content as string or content-parts array -#}
                        {%- set tool_body = follow.get('content') -%}
                        {%- if tool_body is string -%}
                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
                        {%- elif tool_body is sequence and tool_body is not string -%}
                            {%- set ns_txt = namespace(s='') -%}
                            {%- for part in tool_body -%}
                                {%- if part.get('type') == 'text' -%}
                                    {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
                                {%- endif -%}
                            {%- endfor -%}
                            {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
                            {%- for part in tool_body -%}
                                {%- if part.get('type') == 'image' -%}
                                    {{- '<|image|>' -}}
                                {%- elif part.get('type') == 'audio' -%}
                                    {{- '<|audio|>' -}}
                                {%- elif part.get('type') == 'video' -%}
                                    {{- '<|video|>' -}}
                                {%- endif -%}
                            {%- endfor -%}
                        {%- else -%}
                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
                        {%- endif -%}
                        {%- set ns_tr_out.flag = true -%}
                        {%- set ns.prev_message_type = 'tool_response' -%}
                    {%- endif -%}
                {%- endfor -%}
            {%- endif -%}

            {%- set captured_content -%}
            {%- if message['content'] is string -%}
                {%- if role == 'model' -%}
                    {{- strip_thinking(message['content']) -}}
                {%- else -%}
                    {{- message['content'] | trim -}}
                {%- endif -%}
            {%- elif message['content'] is sequence -%}
                {%- for item in message['content'] -%}
                    {%- if item['type'] == 'text' -%}
                        {%- if role == 'model' -%}
                            {{- strip_thinking(item['text']) -}}
                        {%- else -%}
                            {{- item['text'] | trim -}}
                        {%- endif -%}
                    {%- elif item['type'] == 'image' -%}
                        {{- '<|image|>' -}}
                        {%- set ns.prev_message_type = 'image' -%}
                    {%- elif item['type'] == 'audio' -%}
                        {{- '<|audio|>' -}}
                        {%- set ns.prev_message_type = 'audio' -%}
                    {%- elif item['type'] == 'video' -%}
                        {{- '<|video|>' -}}
                        {%- set ns.prev_message_type = 'video' -%}
                    {%- endif -%}
                {%- endfor -%}
            {%- endif -%}
            {%- endset -%}

            {{- captured_content -}}
            {%- set has_content = captured_content | trim | length > 0 -%}

        {#- P5 (public fork): symmetric continuation close-suppression
            for HF discussion #62.

            The bug: upstream's open suppression at the top of this
            iteration drops the `<|turn>model\n` header when the
            previous non-tool message was also assistant — but the
            close below ALWAYS emits `<turn|>\n`. Two back-to-back
            text-only assistant messages therefore render as:
              <|turn>model\npart 1<turn|>\npart 2<turn|>\n
            That's one open, two closes — malformed. The model
            (Google-confirmed in HF discussion #62) sees it as a
            truncated and re-opened turn, which destabilises long
            multi-step agentic histories that accumulate consecutive
            assistant messages.

            Fix: forward-scan for the next non-tool message. If it is
            another assistant AND this iteration is a TEXT-ONLY
            assistant message (no tool_calls, no tool_responses), the
            next iteration will continue this same turn frame, so
            suppress this iteration's close and emit a single `\n` so
            the two contents don't byte-glue together.

            The narrowing condition (`not message.get('tool_calls')
            and not ns_tr_out.flag`) is critical: the tool-call +
            tool-response chain MUST close normally so the model still
            sees a balanced turn frame around the `<|tool_response>`
            block. Conformance test T13 locks this in. -#}
        {%- set next_nt = namespace(role=None, found=false) -%}
        {%- for j in range(loop.index0 + 1, loop_messages | length) -%}
            {%- if not next_nt.found -%}
                {%- if loop_messages[j]['role'] != 'tool' -%}
                    {%- set next_nt.role = loop_messages[j]['role'] -%}
                    {%- set next_nt.found = true -%}
                {%- endif -%}
            {%- endif -%}
        {%- endfor -%}
        {%- set continues_into_next = (
            role == 'model'
            and next_nt.role == 'assistant'
            and not message.get('tool_calls')
            and not ns_tr_out.flag
        ) -%}

        {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
            {{- '<|tool_response>' -}}
        {%- elif continues_into_next -%}
            {{- '\n' -}}
        {%- elif not (ns_tr_out.flag and not has_content) -%}
            {{- '<turn|>\n' -}}
        {%- endif -%}
    {%- endif -%}
{%- endfor -%}

{%- if add_generation_prompt -%}
    {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
        {{- '<|turn>model\n' -}}
        {#- When thinking is disabled, the upstream contract is to
            pre-fill an empty `<|channel>thought\n<channel|>` block so
            the model skips reasoning. After P2's set at the top of
            the file, `enable_thinking` is unconditionally a bool, so
            the upstream `| default(false)` is unnecessary. (It also
            had a Jinja precedence trap: `|` binds tighter than `not`,
            parsing as `not (enable_thinking | default(false))`. The
            simple `not enable_thinking` form is equivalent and
            clearer.) -#}
        {%- if not enable_thinking -%}
            {{- '<|channel>thought\n<channel|>' -}}
        {%- endif -%}
    {%- endif -%}
{%- endif -%}

thank you for this!

I was getting some errors when trying this template with Pi and LM Studio inference.
Fixed version here:
https://gist.github.com/hashangit/97dcd4ea33dc19c9f4e2d40877c34738/revisions?diff=split&w

(Thank you for the original)