mirror of
https://github.com/ikawrakow/ik_llama.cpp.git
synced 2026-06-28 04:30:15 -05:00
* Autoparser - complete refactoring of parser architecture Autoparser: add optional argument reshuffle capability Autoparser: True streaming (#20177) * Relax atomicity constraint for nicer, more pleasent, True Streaming parsing * Whitespace * Remove redundant atomics Revert to OAI-compatible args (#20213) * Revert to OAI-compatible args * Apply workaround::func_args_not_string Fix structured outputs (#20223) * Fix structured outputs * Update common/chat-auto-parser-generator.cpp Co-authored-by: Aldehir Rojas <hello@alde.dev> --------- Co-authored-by: Aldehir Rojas <hello@alde.dev> Fix compile bug (#20203) * Fix compile bug * Update common/chat-auto-parser-helpers.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> # Conflicts: # common/chat-auto-parser-helpers.cpp common : gracefully handle incomplete output (#20191) * common : handle incomplete UTF-8 at end of input in PEG parser * cont : if reached end prematurely, emit needs_more_input to propagate partial output * cont: refactor peg parse context to add lenient flag * cont : remove partial flag, keep lenient flag PEG parser for LFM2 (#20251) * PEG parser for LFM2 * Simplify using python_value() common: map developer role to system (#20215) * Map developer role to system * Simplify common: consolidate PEG string parsers (#20263) * common : consolidate PEG string parsers * cont : fix json_string_content() examples : fix empty items in json_schema_to_grammar.py [no ci] (#19968) * Fix logic for retrieving schema items in `json_schema_to_grammar.py` If `schema['items']` is `{}` and `prefixItems not in schema', as `{}` is Falsy, the original code here will raise an error. I think if `schema['items']` is `{}`, them items should just be `{}` * Apply suggestion from @CISC Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Add tests for arrays with empty items Add two unit tests to `tests/test-json-schema-to-grammar.cpp` that validate handling of arrays when 'items' is an empty schema and when 'prefixItems' is present alongside an empty 'items'. Both tests expect the same generated grammar, ensuring the JSON Schema->grammar conversion treats an empty 'items' schema (and the presence of 'prefixItems') correctly and covering this edge case. --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> Reduce level of content parser warning message to avoid log spam on non-debug verbosity (#20347) do not return if template parse failed add arg to enable parallel tool call common : fix incorrect uses of stoul (#20313) # Conflicts: # common/arg.cpp # src/llama-grammar.cpp examples : fix empty items in json_schema_to_grammar.py [no ci] (#19968) * Fix logic for retrieving schema items in `json_schema_to_grammar.py` If `schema['items']` is `{}` and `prefixItems not in schema', as `{}` is Falsy, the original code here will raise an error. I think if `schema['items']` is `{}`, them items should just be `{}` * Apply suggestion from @CISC Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Add tests for arrays with empty items Add two unit tests to `tests/test-json-schema-to-grammar.cpp` that validate handling of arrays when 'items' is an empty schema and when 'prefixItems' is present alongside an empty 'items'. Both tests expect the same generated grammar, ensuring the JSON Schema->grammar conversion treats an empty 'items' schema (and the presence of 'prefixItems') correctly and covering this edge case. --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> Add support for MiroThinker with new jinja template common/parser: handle reasoning budget (#20297) * v1 * Finished! * Handlie cli * Reasoning sampler * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Less explosive terminology :) * Add utf-8 case and tests * common : migrate reasoning budget sampler to common * cont : clean up * cont : expose state and allow passing as initial state * cont : remove unused imports * cont : update state machine doc string --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> Co-authored-by: Alde Rojas <hello@alde.dev> common/parser: use nlohmann::ordered_json to preserve parameter order (#20385) common/parser: add GigaChatV3/3.1 models support (#19931) Co-authored-by: Mishusha <pmv26021975@gmail.com> common/parser: gracefully handle undetected tool parser, print error message. (#20286) fix: prevent nullptr dereference (#20552) common : fix iterator::end() dereference (#20445) # Conflicts: # common/regex-partial.cpp jinja : add capability check for object args (#20612) common/parser: add `--skip-chat-parsing` to force a pure content parser. (#20289) * Add `--force-pure-content` to force a pure content parser. * Update common/arg.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> common : rework gpt-oss parser (#20393) * common : rework gpt-oss parser * cont : fix gpt-oss tests * cont : add structured output test * cont : rename final to final_msg common : fix gpt-oss content removal (#20745) common/parser: add proper reasoning tag prefill reading (#20424) * Implement proper prefill extraction * Refactor cli parameters, update docs, move reasoning budget sampler part to common/reasoning-budget.cpp * Update tools/server/server-task.cpp * refactor: move grammars to variant, remove grammar_external, handle exception internally * Make code less C++y Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> chat : handle tool calls with no required args in TAG_WITH_TAGGED format (#20764) * chat : handle tool calls with no required args in TAG_WITH_TAGGED format * Update tests/test-chat.cpp [no ci] Co-authored-by: Aldehir Rojas <hello@alde.dev> --------- Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com> Co-authored-by: Aldehir Rojas <hello@alde.dev> common/parser : fix out_of_range crash in throw path (#20424 regression) (#20777) * chat : fix out_of_range crash in throw path (#20424 regression) #20424 introduced effective_input = generation_prompt + input, but the throw path uses input.substr(result.end) where result.end is a position within effective_input. Every thinking model with a non-empty generation_prompt crashes with std::out_of_range instead of the intended error message. Test crashes on unpatched master, passes with fix: cmake -B build -DLLAMA_BUILD_TESTS=ON -DLLAMA_BUILD_TOOLS=OFF cmake --build build --target test-chat ./build/bin/test-chat * Update test-chat.cpp * Update test-chat.cpp * Update test-chat.cpp --------- Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com> jinja : fix heap OOB read in value equality comparison (#20782) Address GHSA-q9j6-4hhc-rq9p and GHSA-2q4c-9gq5-5vfp. The three-iterator overload of std::equal in value_array_t::equivalent() and value_object_t::equivalent() reads past the end of the shorter container when comparing arrays or objects of different lengths. Use the four-iterator overload (C++14) which checks both range lengths. Found-by: Pwno common : fix typo in debug log ('extracft' -> 'extract') (#20807) common/parser: fix nasty bug causing subtle corruption of generation prompt (#20825) jinja : refactor token advancement (#20864) * refactor token advancement * exercise sub-expressions common/autoparser : detect reasoning markers when enable_thinking changes system prompt (#20859) common : replace wrap_for_generation with a prefix convenience function and fix gpt-oss (#20912) jinja: fix macro with kwargs (#20960) * jinja: fix macro with kwargs * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * fix newline problem --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> common : inhibit lazy grammar sampler while reasoning is active (#20970) * common : inhibit grammar while reasoning budget is active * cont : update force_pos in accept * cont : fix tests * cont : tweak should apply logic * cont : return early not using grammar sampler * Add tests * cont : prevent backend sampling when reasoning budget enabled * cont : fix typo --------- Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com> # Conflicts: # common/reasoning-budget.h # common/sampling.cpp # tools/cli/cli.cpp # tools/server/server-common.cpp # tools/server/server-task.cpp common/parser: fix reasoning whitespace bugs + extra parser tests (#21085) * fix whitespace reasoning issues + add reconstruction tests * Proper fix * fix Nemotron autoparser test expectations to include newline in marker common : add reasoning_format = none support to gpt-oss (#21094) common/json-schema: fix: handle non-capturing groups (?:...) in JSON schema pattern converter (#21124) The regex-to-grammar converter in _visit_pattern() crashes with SIGSEGV when a JSON schema "pattern" field contains a non-capturing group (?:...). Root cause: when the parser sees '(' followed by '?', it pushes a warning but does not advance past '?:'. The recursive transform() call then interprets '?' as a quantifier and calls seq.back() on an empty vector, causing undefined behavior. This commonly occurs when serving OpenAI-compatible tool calls from clients that include complex regex patterns in their JSON schemas (e.g., date validation patterns like ^(?:(?:\d\d[2468][048]|...)-02-29|...)$). The fix: - Skip '?:' after '(' to treat non-capturing groups as regular groups - For unsupported syntax (?=, ?!, etc.), skip to matching ')' safely, handling escaped characters to avoid miscounting parenthesis depth - Adjust the ')' unbalanced-parentheses check using direct char comparisons instead of substr - Add test cases for non-capturing groups (C++ only, as the JS/Python implementations do not yet support this syntax) common/parser: fix handling of tool definition with missing properties key (#21128) jinja : handle empty expressions correctly (#20913) * Reject empty computed member expressions before returning slices[0] from parse_member_expression_arguments(). * Treat empty computed member expressions with Jinja2 undefined semantics Treat empty computed member expressions like `a[]` as undefined instead of raising a parser error, to match Jinja2 behavior. - return a noop expression for empty computed member arguments - return undefined when a computed member key evaluates to undefined - add Jinja tests covering `a[]|default('fallback')` and `a[] is undefined` * Handle undefined computed member properties Move undefined-property handling to the common member access path, and add a test covering `a[undefined] is undefined`. * Use default undefined value in member access Initialize val and then return it when property is undefined. Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * empty statement parses to blank_expression instead of noop_statement --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> common : gpt-oss handle builtin and unsolicited tool calls (#21213) fix: tool call parsing for LFM2 and LFM2.5 models (#21242) * fix: tool call parsing for LFM2 and LFM2.5 models' * refactor: add test / break out lfm2 and lfm2.5 parsing logic # Conflicts: # common/chat.cpp Relax prefill parser to allow space. (#21240) * Relax prefill parser to allow space. * Move changes from prefix() to parser generation * Only allow spaces if we're not having a pure content parser next common : add commentary rules for gpt-oss-20b (#21286) add reasoning budget model, mtmd: fix gguf conversion for audio/vision mmproj (#21309) * fix gguf conversion for audio/vision mmproj * fix test # Conflicts: # convert_hf_to_gguf.py # examples/eval-callback/eval-callback.cpp # examples/mtmd/CMakeLists.txt # examples/mtmd/clip-impl.h # examples/mtmd/mtmd.cpp # gguf-py/gguf/constants.py # gguf-py/gguf/gguf_writer.py # gguf-py/gguf/tensor_mapping.py # src/CMakeLists.txt # src/llama-arch.cpp # src/llama-arch.h # src/llama-model.cpp # src/llama-model.h # src/llama-vocab.cpp # src/models/models.h # tests/test-llama-archs.cpp # tools/mtmd/clip-graph.h # tools/mtmd/clip-model.h # tools/mtmd/clip.cpp # tools/mtmd/models/models.h fix: gemma 4 template (#21326) chat : avoid including json in chat.h (#21306) jinja: coerce input for string-specific filters (#21370) common : fix tool call type detection for nullable and enum schemas (#21327) * common : fix tool call type detection for nullable and enum schemas * common, tests : fix grammar delegation for nullable/enum schemas and add tests Fix enum type inference to scan all enum values (not just index 0) so schemas like {"enum": [0, "celsius"]} correctly detect string type. Fix schema_delegates in peg-parser to handle nullable type arrays (["string", "null"]) and typeless enum schemas in raw mode, allowing the tagged parser to use raw text instead of JSON-formatted strings. Add test cases for Qwen3-Coder (TAG_WITH_TAGGED format): - nullable string ["string", "null"] - nullable string with null first ["null", "string"] - nullable integer ["integer", "null"] - enum without explicit type key common/parser: fix call ID detection (Mistral parser mostly) + atomicity for tag-json parsers (#21230) * Fix call ID detection (Mistral parser mostly) + atomicity for tag-json parsers * Rename * Update common/chat-auto-parser-generator.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> common : add gemma 4 specialized parser (#21418) * common : add gemma4 dedicated parser * cont : add '<|tool_response>' as eog * cont : emit JSON from Gemma4 tool call AST * cont : more fixes * cont : refactor convert function * cont : refine rules and mapping * cont : add more tests * cont : clean up * cont : remove autoparser gemma4 implementation * cont : more cleanup * cont : rename gemma4.jinja to match the others * cont : add custom template to support interleaved thinking * cont : preserve reasoning in model turns * cont : fix initializer error * cont : fix unused vars * cont : fix accidental static * cont : fix specialized_template signature * fix extra semicolon * remove debug line and extra space [no ci] fix reasoning budget parser: fix MiniMax handling (#21573) jinja : support ensure_ascii=true, string repetition and int/float self-filtering (#21623) * feat: jinja engine improvements for reka-edge Port three Jinja engine improvements needed for the reka-edge model: 1. Python-style string repetition ("ab" * 3 → "ababab") 2. ensure_ascii=true support for tojson filter (escapes non-ASCII to \uXXXX) 3. int() builtin on value_int_t (identity, needed for Reka Edge template) * fix: escape invalid utf8 bytes when ensure_ascii=true The json_ensure_ascii_preserving_format function does not correctly handle an edge case where if UTF-8 parsing fails, it adds the non-ascii character back to the output as a raw byte. This commit fixes that by adding the unicode standard replacement character \\ufffd to the output instead. This is the standard behavior for various programming languages like Python, Rust, Go, etc. * chore: address PR comments 1. Add todo comment for supporting string repetition for array/tuples 2. Add support for float identity operation 3. Move invalid ascii test case to test_fuzzing * chore: accept suggestion for common/jinja/value.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> common : simplify autoparser tagged parser rules (#21216) * common : simplify autoparser tagged parser rules * cont : remove upper limit on optional args * cont : revert changes to parsing at the end * cont : undo arbitrary ordering of optional args * cont : fix uninitialized required parameters * revert to simplify merge * re-apply patches * restore flexible optional arg ordering tests common : fix ambiguous grammar rule in gemma4 (#21661) * common : fix ambiguous grammar rule in gemma4 * cont : fix missing comma... common : enable reasoning budget sampler for gemma4 (#21697) * fix: enable reasoning budget sampler for gemma4 Add thinking_start_tag and thinking_end_tag to common_chat_params_init_gemma4(). Without these, the reasoning budget sampler never activates for gemma4. Make the newline after "thought" optional in the PEG parser to handle budget=0 (sampler forces end tag before the newline). Add test case for empty thinking block. Fixes #21487 * use p.space() instead of p.optional(p.literal("\n")) in gemma4 thought parser common : better align to the updated official gemma4 template (#21704) fix: Fix broken structured output when using $refs in json_schema (#21699) chat: dedicated DeepSeek v3.2 parser + "official" template (#21785) Hide render_message_to_json warning common/gemma4 : handle parsing edge cases (#21760) common: skip reasoning budget sampler when no budget is requested (#21870) * common: skip reasoning budget sampler when no budget is requested After I added thinking_start_tag / thinking_end_tag for gemma4 in #21697, the reasoning budget sampler gets unconditionally created even when no budget is configured (the default -1). The same applies to kimi_k2, lfm2, lfm2_5, and ministral_3 which also set these tags. The budget gets converted to INT_MAX, so the sampler never actually forces any tokens but still runs per-token checks (start tag matching in IDLE state, token-to-piece conversion + UTF-8 checks in COUNTING state). More importantly, the mere existence of the sampler (non-null rbudget) disables backend sampling. Backend sampling lets the GPU select tokens directly, avoiding a full logits transfer from GPU to CPU every token. This could explain the 30% speed regression reported in #21784 (98 t/s to 70 t/s on Vulkan). So I added a reasoning_budget_tokens >= 0 check to the sampler creation condition. When the budget is unlimited, the sampler is not created, backend sampling stays enabled, and no per-token overhead is added. When a budget is explicitly set (0, 128, 1024, etc.), the sampler is created and works as before. * common: preserve rbudget when grammar is lazy Following up on the review feedback on #21870: keep the reasoning budget sampler when grammar_lazy is true, so the thinking-block grammar suppression from #20970 still works when tools are in use. This way, we only skip the sampler when both no budget is set AND grammar is not lazy. autoparser: support case of JSON_NATIVE with per-call markers (test case: Reka-Edge) (#21892) * fix grammar * fix add sampled token --------- Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com> Co-authored-by: firecoperana <firecoperana>
156 lines
11 KiB
Django/Jinja
156 lines
11 KiB
Django/Jinja
{{ bos_token }}{%- macro document_turn(documents) -%}
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{# format documents into chat turn #}
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<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_THINKING|>I will look through the document to address the users needs.<|END_THINKING|><|START_ACTION|>[
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{"tool_call_id": "0", "tool_name": "direct-injected-document", "parameters": {}}
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]<|END_ACTION|><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[
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{
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"tool_call_id": "0",
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"results": {
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{% for doc in documents %}
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"{{ loop.index0 }}": {{doc|tojson}}{% if not loop.last %},
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{% endif %}
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{% endfor %}
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},
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"is_error": null
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}
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]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>{%- endmacro %}
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{%- macro tool_call_id_to_int(messages, tool_call_id) %}
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{%- set counter = namespace(value=0) %}
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{%- set tool_call_id_seen = namespace(value=false) %}
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{%- for msg in messages %}
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{%- if msg.tool_calls %}
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{%- for tool_call in msg.tool_calls %}
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{%- if tool_call.id == tool_call_id and not tool_call_id_seen.value -%}
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{{ counter.value }}
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{%- set tool_call_id_seen.value = true %}
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{%- endif %}
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{%- set counter.value = counter.value + 1 %}
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{%- endfor %}
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{%- endif %}
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{%- endfor %}
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{%- endmacro %}
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{%- macro format_tool_message(messages, tool_msg) -%}
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{# format tool message #}
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{
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"tool_call_id": "{{ tool_call_id_to_int(messages, tool_msg.tool_call_id) }}",
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"results": {
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"0": {{ tool_msg.content|tojson }}
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},
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"is_error": null
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}
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{%- endmacro -%}
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{%- if messages and messages[0]['role']|lower == 'system' %}{%- set developer_preamble = messages[0]['content'] %}{% endif %}
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{%- set tool_idx = namespace(value=0) %}
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{%- set tool_ids_seen = namespace(value=[]) %}
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{%- set sent_documents = namespace(value=false) %}
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<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># System Preamble
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You are in contextual safety mode. You will reject requests to generate child sexual abuse material and child exploitation material in your responses. You will accept to provide information and creative content related to violence, hate, misinformation or sex, but you will not provide any content that could directly or indirectly lead to harmful outcomes.
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Your information cutoff date is June 2024.
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You have been trained on data in English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Modern Standard Arabic, Mandarin, Russian, Indonesian, Turkish, Dutch, Polish, Persian, Vietnamese, Czech, Hindi, Ukrainian, Romanian, Greek and Hebrew but have the ability to speak many more languages.
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{% if tools or documents %}
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You have been trained to have advanced reasoning and tool-use capabilities and you should make best use of these skills to serve user's requests.
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## Tool Use
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Think about how you can make best use of the provided tools to help with the task and come up with a high level plan that you will execute first.
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0. Start by writing <|START_THINKING|> followed by a detailed step by step plan of how you will solve the problem. For each step explain your thinking fully and give details of required tool calls (if needed). Unless specified otherwise, you write your plan in natural language. When you finish, close it out with <|END_THINKING|>.
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You can optionally choose to skip this step when the user request is so straightforward to address that only a trivial plan would be needed.
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NOTE: You MUST skip this step when you are directly responding to the user's request without using any tools.
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Then carry out your plan by repeatedly executing the following steps.
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1. Action: write <|START_ACTION|> followed by a list of JSON-formatted tool calls, with each one containing "tool_name" and "parameters" fields.
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When there are multiple tool calls which are completely independent of each other (i.e. they can be executed in parallel), you should list them out all together in one step. When you finish, close it out with <|END_ACTION|>.
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2. Observation: you will then receive results of those tool calls in JSON format in the very next turn, wrapped around by <|START_TOOL_RESULT|> and <|END_TOOL_RESULT|>. Carefully observe those results and think about what to do next. Note that these results will be provided to you in a separate turn. NEVER hallucinate results.
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Every tool call produces a list of results (when a tool call produces no result or a single result, it'll still get wrapped inside a list). Each result is clearly linked to its originating tool call via its "tool_call_id".
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3. Reflection: start the next turn by writing <|START_THINKING|> followed by what you've figured out so far, any changes you need to make to your plan, and what you will do next. When you finish, close it out with <|END_THINKING|>.
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You can optionally choose to skip this step when everything is going according to plan and no special pieces of information or reasoning chains need to be recorded.
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NOTE: You MUST skip this step when you are done with tool-use actions and are ready to respond to the user.
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You can repeat the above 3 steps multiple times (could be 0 times too if no suitable tool calls are available or needed), until you decide it's time to finally respond to the user.
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4. Response: then break out of the loop and write <|START_RESPONSE|> followed by a piece of text which serves as a response to the user's last request. Use all previous tool calls and results to help you when formulating your response. When you finish, close it out with <|END_RESPONSE|>.
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{% if enable_citations %}
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## Grounding
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Importantly, note that "Reflection" and "Response" above can be grounded.
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Grounding means you associate pieces of texts (called "spans") with those specific tool results that support them (called "sources"). And you use a pair of tags "<co>" and "</co>" to indicate when a span can be grounded onto a list of sources, listing them out in the closing tag. Sources from the same tool call are grouped together and listed as "{tool_call_id}:[{list of result indices}]", before they are joined together by ",". E.g., "<co>span</co: 0:[1,2],1:[0]>" means that "span" is supported by result 1 and 2 from "tool_call_id=0" as well as result 0 from "tool_call_id=1".
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{% endif %}
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## Available Tools
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Here is the list of tools that you have available to you.
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You can ONLY use the tools listed here. When a tool is not listed below, it is NOT available and you should NEVER attempt to use it.
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Each tool is represented as a JSON object with fields like "name", "description", "parameters" (per JSON Schema), and optionally, "responses" (per JSON Schema).
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```json
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[
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{% if documents %}
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{"name": "direct-injected-document", "description": "This is a special tool to directly inject user-uploaded documents into the chat as additional context. DO NOT use this tool by yourself!", "parameters": {"type": "object", "properties": {}, "required": []}, "responses": {"200": {"description": "Successfully returned a list of chunked text snippets from the directly uploaded documents.", "content": {"application/json": {"schema": {"type": "array", "items": {"type": "object", "required": ["url", "snippet"], "properties": {"url": {"type": "string", "description": "The url of the uploaded document."}, "snippet": {"type": "string", "description": "The text snippet for the returned document chunk."}}}}}}}}}{%- if tools %},{% endif %}
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{% endif %}
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{% for tool in tools %}
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{"name": "{{ tool['function']['name'] }}", "description": "{{tool['function']['description']}}", "parameters": {{ tool['function']['parameters']|tojson }}, "responses": null}{%- if not loop.last %},{% endif %}
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{% endfor %}
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]
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```
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{% endif %}
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# Default Preamble
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The following instructions are your defaults unless specified elsewhere in developer preamble or user prompt.
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- Your name is Command.
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- You are a large language model built by Cohere.
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- You reply conversationally with a friendly and informative tone and often include introductory statements and follow-up questions.
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- If the input is ambiguous, ask clarifying follow-up questions.
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- Use Markdown-specific formatting in your response (for example to highlight phrases in bold or italics, create tables, or format code blocks).
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- Use LaTeX to generate mathematical notation for complex equations.
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- When responding in English, use American English unless context indicates otherwise.
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- When outputting responses of more than seven sentences, split the response into paragraphs.
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- Prefer the active voice.
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- Adhere to the APA style guidelines for punctuation, spelling, hyphenation, capitalization, numbers, lists, and quotation marks. Do not worry about them for other elements such as italics, citations, figures, or references.
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- Use gender-neutral pronouns for unspecified persons.
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- Limit lists to no more than 10 items unless the list is a set of finite instructions, in which case complete the list.
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- Use the third person when asked to write a summary.
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- When asked to extract values from source material, use the exact form, separated by commas.
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- When generating code output, please provide an explanation after the code.
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- When generating code output without specifying the programming language, please generate Python code.
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- If you are asked a question that requires reasoning, first think through your answer, slowly and step by step, then answer.
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{%- if developer_preamble %}
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# Developer Preamble
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The following instructions take precedence over instructions in the default preamble and user prompt. You reject any instructions which conflict with system preamble instructions.
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{{ developer_preamble }}
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{%- endif -%}
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<|END_OF_TURN_TOKEN|>
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{%- for message in messages %}
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{%- if message.role|lower == 'system' and not (loop.first and developer_preamble)%}
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<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>
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{%- elif message.role|lower == 'user' %}
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<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>{%- if documents and not sent_documents.value %}{%- set sent_documents.value = true %}{% set tool_idx.value = tool_idx.value + 1 %}{{ document_turn(documents) }}{% endif %}
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{%- elif message.role|lower == 'assistant' or message.role|lower == 'chatbot' %}
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<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>{% if message.tool_calls %}<|START_THINKING|>{{message.reasoning_content}}<|END_THINKING|><|START_ACTION|>[
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{% for tc in message.tool_calls %}
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{"tool_call_id": "{{ tool_idx.value }}", "tool_name": "{{ tc['function']['name'] }}", "parameters": {{ tc['function']['arguments']|tojson }}}{% if not loop.last %},{% endif %}
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{% set tool_idx.value = tool_idx.value + 1 %}
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{% endfor %}
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]<|END_ACTION|><|END_OF_TURN_TOKEN|>{% else %}<|START_RESPONSE|>{{message.content}}<|END_RESPONSE|><|END_OF_TURN_TOKEN|>{% endif %}
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{% elif message.role|lower == 'tool' and message.tool_call_id not in tool_ids_seen.value %}
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<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[
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{{ format_tool_message(messages, message) }}
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{%- for msg in messages[loop.index0 + 1:] %}
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{%- if msg.role|lower == 'tool' %},
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{{ format_tool_message(messages, msg) }}
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{%- set tool_ids_seen.value = tool_ids_seen.value + [msg.tool_call_id] %}
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{%- else %}
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{%- break %}
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{%- endif %}
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{%- endfor %}
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]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>
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{%- endif %}
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{%- endfor %}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>{%- if not enable_thinking -%}<|START_THINKING|><|END_THINKING|>{%- endif %} |