Add Mistral platform + Mistral dialect + array-content handling (provider 5)

The 8th registry row: id "mistral", MISTRAL_API_KEY > auth.json
"mistral" scope, https://api.mistral.ai/v1 with KIGI_MISTRAL_BASE_URL
override, enrichment-backed metadata with the tool-calling listing
restriction (embed/moderation/OCR noise).

Mistral is NOT a pure-pattern provider — an adversarial review found two
doc-confirmed blockers that no test exercises (no e2e covers a chat POST),
so the gate-green registry row alone would have shipped it DOA. A research
workflow pinned the exact wire shapes against the mistralai/client-python
SDK source (adversarially verified), then both were fixed:

1. stream_options 422: Mistral's strict Pydantic validator rejects the
   stream_options.include_usage field kigi injects on every streaming
   request (the SDK's request model has no such field). New
   ChatCompat::Mistral dialect strips it (plus the kigi-private message
   fields, like Passthrough). Streaming usage falls back to token
   estimation.
2. Reasoning content arrays: Mistral reasoning models return content as
   Union[str, List[ContentChunk]] on both streaming and non-streaming,
   which the flat Option<String> path could not decode -> aborted turn.
   A UNIVERSAL lenient deserializer (#[serde(from = "Raw..")] on
   ChatResponseMessage + ChatChunkDelta) accepts string-or-array, routing
   {type:text} chunks to the answer and the nested text of {type:thinking}
   chunks to reasoning_content, tolerant of the OPEN chunk union (unknown
   types ignored, never fatal). String content stays byte-identical for
   every other provider (kimi/deepseek/groq/BYOK).

Review refuted all seven attack lines (no regression, no crash, exhaustive)
and flagged one coverage gap, now closed: a stream-consumer integration
test drives a full thinking -> transition -> answer chunk sequence and
proves it yields the same reasoning-sibling + assistant-answer result as
the reasoning_content string path.

Also folds a verified quirk matrix for all 23 remaining API providers into
providers-plan.md, tiered by real difficulty (self-enriching OpenRouter/
Vercel; bare-array Together listing; Messages-dialect MiniMax reusing the
Anthropic machinery; non-Bearer Azure/Bedrock; router wildcards; the OAuth
block).

crates/codegen/kigi-models/src/lib.rs

@@ -70,6 +70,7 @@ pub enum PlatformChatCompat {
     Kimi,
     DeepSeek,
     Passthrough,
+    Mistral,
 }
 
 /// How a platform's API key rides requests (listing, validation, inference).
@@ -316,6 +317,35 @@ const GROQ_SPEC: PlatformSpec = PlatformSpec {
     restrict_to_enriched: true,
 };
 
+/// Base-URL override for Mistral (dev/test escape hatch).
+pub const MISTRAL_BASE_URL_ENV: &str = "KIGI_MISTRAL_BASE_URL";
+
+const MISTRAL_SPEC: PlatformSpec = PlatformSpec {
+    id: "mistral",
+    display_name: "Mistral",
+    base_url: BaseUrlSource::EnvOr {
+        env: MISTRAL_BASE_URL_ENV,
+        default: "https://api.mistral.ai/v1",
+    },
+    uses_oauth: false,
+    allowed_model_prefixes: None,
+    api_key_envs: &["MISTRAL_API_KEY"],
+    vendor: "Mistral",
+    console_host: Some("console.mistral.ai"),
+    login_label: Some("Mistral (API key)"),
+    models_dev_id: Some("mistral"),
+    wire_serves_metadata: false,
+    wire_api: PlatformWireApi::ChatCompletions,
+    listing: ListingDialect::OpenAi,
+    // Mistral's strict validator 422s on `stream_options`, and its reasoning
+    // models return array content — the Mistral dialect handles both.
+    chat_compat: PlatformChatCompat::Mistral,
+    key_header: PlatformKeyHeader::Bearer,
+    // The listing carries embed/moderation/OCR entries; keep tool-calling
+    // chat models only.
+    restrict_to_enriched: true,
+};
+
 /// The platform registry. Platforms are compiled-in spec rows; there is no
 /// dynamic provider registration (PRD F2).
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)]
@@ -334,12 +364,14 @@ pub enum PlatformId {
     DeepSeek,
     /// Groq platform API (API key, OpenAI-compatible ChatCompletions).
     Groq,
+    /// Mistral platform API (API key, OpenAI-compatible ChatCompletions).
+    Mistral,
 }
 
 impl PlatformId {
     /// All platforms, in catalog precedence order: the subscription channel
     /// first so "default model = first list item" favors it when present.
-    pub const ALL: [PlatformId; 7] = [
+    pub const ALL: [PlatformId; 8] = [
         Self::KimiCode,
         Self::MoonshotCn,
         Self::MoonshotAi,
@@ -347,6 +379,7 @@ impl PlatformId {
         Self::Anthropic,
         Self::DeepSeek,
         Self::Groq,
+        Self::Mistral,
     ];
 
     /// The registry row backing this platform (single source of per-platform
@@ -360,6 +393,7 @@ impl PlatformId {
             Self::Anthropic => &ANTHROPIC_SPEC,
             Self::DeepSeek => &DEEPSEEK_SPEC,
             Self::Groq => &GROQ_SPEC,
+            Self::Mistral => &MISTRAL_SPEC,
         }
     }
 
@@ -1017,9 +1051,10 @@ mod tests {
                 PlatformId::Anthropic => 4,
                 PlatformId::DeepSeek => 5,
                 PlatformId::Groq => 6,
+                PlatformId::Mistral => 7,
             }
         }
-        const VARIANT_COUNT: usize = 7; // update together with `ordinal`
+        const VARIANT_COUNT: usize = 8; // update together with `ordinal`
         let mut seen: Vec<usize> = PlatformId::ALL.iter().map(|&p| ordinal(p)).collect();
         seen.sort_unstable();
         seen.dedup();

crates/codegen/kigi-sampler/src/kimi_compat.rs

@@ -47,6 +47,22 @@ pub(crate) fn adapt_chat_completions_body_for(
         kigi_sampling_types::ChatCompat::Passthrough => {
             strip_kigi_private_message_fields(body);
         }
+        kigi_sampling_types::ChatCompat::Mistral => {
+            strip_kigi_private_message_fields(body);
+            strip_stream_options(body);
+        }
+    }
+}
+
+/// Mistral's strict Pydantic validator 422-rejects `stream_options`
+/// (`extra_forbidden` on `stream_options.include_usage`; its request model
+/// has no such field). kigi injects `stream_options.include_usage` on every
+/// streaming request for the other providers, so strip the whole object for
+/// Mistral. Streaming usage falls back to token estimation (as for any
+/// provider that omits streaming usage).
+fn strip_stream_options(body: &mut Value) {
+    if let Some(obj) = body.as_object_mut() {
+        obj.remove("stream_options");
     }
 }
 
@@ -393,6 +409,38 @@ mod tests {
         assert_eq!(body["messages"][0].get("model_id"), None);
     }
 
+    #[test]
+    fn mistral_dialect_strips_stream_options_and_private_fields() {
+        use kigi_sampling_types::ChatCompat;
+        // Mistral 422s on stream_options (extra_forbidden) and doesn't know
+        // kigi's private message fields; OpenAI-style reasoning_effort stays.
+        let mut body = json!({
+            "model": "mistral-medium-latest",
+            "reasoning_effort": "high",
+            "stream": true,
+            "stream_options": { "include_usage": true },
+            "messages": [
+                { "role": "assistant", "content": "hi",
+                  "reasoning_content": "internal", "model_id": "kigi/x" }
+            ]
+        });
+        adapt_chat_completions_body_for(ChatCompat::Mistral, &mut body);
+        assert_eq!(
+            body.get("stream_options"),
+            None,
+            "stream_options must be stripped"
+        );
+        assert_eq!(body["stream"], json!(true), "stream flag stays");
+        assert_eq!(
+            body["reasoning_effort"],
+            json!("high"),
+            "OpenAI-style effort passes through (Mistral accepts it natively)"
+        );
+        assert_eq!(body["messages"][0].get("reasoning_content"), None);
+        assert_eq!(body["messages"][0].get("model_id"), None);
+        assert_eq!(body["messages"][0]["content"], json!("hi"));
+    }
+
     #[test]
     fn passthrough_dialect_leaves_openai_body_verbatim() {
         use kigi_sampling_types::ChatCompat;

crates/codegen/kigi-sampler/src/stream/chat_completions.rs

@@ -517,6 +517,85 @@ mod tests {
         }
     }
 
+    /// Deserialize a full chunk from a JSON `delta` so it flows through the
+    /// `#[serde(from = "RawChatChunkDelta")]` content-split path (Mistral
+    /// sends array `content`).
+    fn chunk_from_delta(delta: serde_json::Value) -> ChatCompletionChunk {
+        serde_json::from_value(serde_json::json!({
+            "id": "c",
+            "object": "chat.completion.chunk",
+            "created": 0,
+            "model": "mistral-medium-latest",
+            "choices": [{ "index": 0, "delta": delta, "finish_reason": null }],
+        }))
+        .expect("mistral chunk deserializes")
+    }
+
+    /// End-to-end: a Mistral reasoning stream (array `content` thinking
+    /// deltas → a transition delta carrying both a thinking and a text chunk
+    /// → plain-string answer deltas) is split by deserialization and consumed
+    /// into the SAME reasoning-sibling + assistant-answer result the
+    /// `reasoning_content` string path produces. Closes the array-path
+    /// integration gap.
+    #[tokio::test]
+    async fn mistral_reasoning_array_stream_splits_into_reasoning_and_answer() {
+        let chunks: Vec<Result<ChatCompletionChunk, SamplingError>> = vec![
+            Ok(chunk_from_delta(serde_json::json!({ "content": [
+                { "type": "thinking",
+                  "thinking": [{ "type": "text", "text": "Let me think. " }] }
+            ]}))),
+            Ok(chunk_from_delta(serde_json::json!({ "content": [
+                { "type": "thinking",
+                  "thinking": [{ "type": "text", "text": "It's 22." }] }
+            ]}))),
+            // Transition: one array with a closing thinking chunk AND the
+            // first answer text chunk.
+            Ok(chunk_from_delta(serde_json::json!({ "content": [
+                { "type": "thinking", "thinking": [{ "type": "text", "text": " Done." }] },
+                { "type": "text", "text": "Answer: " }
+            ]}))),
+            // Answer phase: plain-string deltas (no longer arrays).
+            Ok(chunk_from_delta(serde_json::json!({ "content": "22." }))),
+            Ok(final_chunk(FinishReason::Stop)),
+        ];
+        let raw = stream::iter(chunks).boxed();
+        let events = collect(stream_chat_completions(
+            raw,
+            None,
+            rid(),
+            Duration::from_secs(60),
+        ))
+        .await;
+
+        // Channel tokens: thinking rode the Reasoning channel, answer the Text
+        // channel — never crossed.
+        let mut reasoning = String::new();
+        let mut answer = String::new();
+        for e in &events {
+            if let SamplingEvent::ChannelToken { channel, text, .. } = e {
+                match channel {
+                    SamplingChannel::Reasoning => reasoning.push_str(text),
+                    SamplingChannel::Text => answer.push_str(text),
+                }
+            }
+        }
+        assert_eq!(reasoning, "Let me think. It's 22. Done.");
+        assert_eq!(answer, "Answer: 22.");
+
+        // The accumulated final response carries the same split.
+        match events.last().unwrap() {
+            SamplingEvent::Completed { response, .. } => {
+                let r = response
+                    .reasoning_items()
+                    .next()
+                    .expect("array thinking became a reasoning sibling");
+                let rs::SummaryPart::SummaryText(t) = &r.summary[0];
+                assert_eq!(t.text, "Let me think. It's 22. Done.");
+            }
+            other => panic!("expected Completed, got {other:?}"),
+        }
+    }
+
     #[tokio::test]
     async fn tool_call_stream_emits_deltas_and_assembles_final_call() {
         // First chunk has id + name + part of arguments.

crates/codegen/kigi-sampling-types/src/types.rs

@@ -487,7 +487,69 @@ pub enum FinishReason {
     FunctionCall,
 }
 
+/// Wire `content` field on a chat response/delta. OpenAI-compatible providers
+/// send a plain string, but reasoning providers (Mistral) send an ARRAY of
+/// typed chunks: `{"type":"text","text":".."}` for the answer and
+/// `{"type":"thinking","thinking":[{"type":"text","text":".."}],...}` for the
+/// chain of thought (verified against the mistralai/client-python SDK models).
+/// The chunk union is OPEN — unknown chunk types are ignored, never fatal.
+#[derive(Deserialize)]
+#[serde(untagged)]
+enum WireContent {
+    Text(String),
+    Chunks(Vec<Value>),
+}
+
+/// Read a chunk's `text` string field into `dst` when present (defensive: a
+/// reference/tool-reference/unknown chunk simply has no `text`).
+fn push_chunk_text(dst: &mut String, chunk: &Value) {
+    if let Some(t) = chunk.get("text").and_then(Value::as_str) {
+        dst.push_str(t);
+    }
+}
+
+fn non_empty(s: String) -> Option<String> {
+    if s.is_empty() { None } else { Some(s) }
+}
+
+impl WireContent {
+    /// Split into `(visible answer text, thinking text)`. A plain string is
+    /// the answer with no thinking; an array routes `text` chunks to the
+    /// answer and the nested `text` of `thinking` chunks to the reasoning
+    /// channel. Byte-identical for string content (the only shape non-Mistral
+    /// providers ever send).
+    fn split(self) -> (Option<String>, Option<String>) {
+        match self {
+            // Preserve string content verbatim (incl. empty) — byte-identical
+            // to the pre-change `content: Option<String>` for every provider
+            // that sends a string.
+            WireContent::Text(s) => (Some(s), None),
+            WireContent::Chunks(chunks) => {
+                let mut answer = String::new();
+                let mut thinking = String::new();
+                for c in &chunks {
+                    match c.get("type").and_then(Value::as_str) {
+                        Some("text") => push_chunk_text(&mut answer, c),
+                        Some("thinking") => {
+                            // `thinking` is a nested list of chunks.
+                            if let Some(inner) = c.get("thinking").and_then(Value::as_array) {
+                                for ic in inner {
+                                    push_chunk_text(&mut thinking, ic);
+                                }
+                            }
+                        }
+                        // reference / tool_reference / unknown → not text.
+                        _ => {}
+                    }
+                }
+                (non_empty(answer), non_empty(thinking))
+            }
+        }
+    }
+}
+
 #[derive(Debug, Serialize, Deserialize, Clone)]
+#[serde(from = "RawChatResponseMessage")]
 pub struct ChatResponseMessage {
     pub role: Role,
     #[serde(skip_serializing_if = "Option::is_none")]
@@ -502,6 +564,38 @@ pub struct ChatResponseMessage {
     pub citations: Option<Vec<String>>,
 }
 
+/// Deserialization mirror of [`ChatResponseMessage`] that accepts array
+/// `content` and folds thinking chunks into `reasoning_content`.
+#[derive(Deserialize)]
+struct RawChatResponseMessage {
+    role: Role,
+    #[serde(default)]
+    content: Option<WireContent>,
+    #[serde(default)]
+    reasoning_content: Option<String>,
+    #[serde(default)]
+    tool_calls: Vec<ToolCallResponse>,
+    #[serde(default)]
+    tool_call_id: Option<String>,
+    #[serde(default)]
+    citations: Option<Vec<String>>,
+}
+
+impl From<RawChatResponseMessage> for ChatResponseMessage {
+    fn from(r: RawChatResponseMessage) -> Self {
+        let (answer, thinking) = r.content.map(WireContent::split).unwrap_or((None, None));
+        ChatResponseMessage {
+            role: r.role,
+            content: answer,
+            // The wire's own `reasoning_content` wins; else thinking chunks.
+            reasoning_content: r.reasoning_content.or(thinking),
+            tool_calls: r.tool_calls,
+            tool_call_id: r.tool_call_id,
+            citations: r.citations,
+        }
+    }
+}
+
 #[derive(Debug, Serialize, Deserialize, Clone)]
 pub struct ToolCallResponse {
     pub id: String,
@@ -649,6 +743,7 @@ pub struct ToolCallFunctionDelta {
 }
 
 #[derive(Debug, Serialize, Deserialize, Clone, Default)]
+#[serde(from = "RawChatChunkDelta")]
 pub struct ChatChunkDelta {
     #[serde(skip_serializing_if = "Option::is_none")]
     pub role: Option<Role>,
@@ -656,16 +751,43 @@ pub struct ChatChunkDelta {
     pub content: Option<String>,
     pub reasoning_content: Option<String>,
     /// Tool call deltas. Handles `null` in JSON as empty vec.
-    #[serde(
-        default,
-        skip_serializing_if = "Vec::is_empty",
-        deserialize_with = "deserialize_null_default"
-    )]
+    #[serde(default, skip_serializing_if = "Vec::is_empty")]
     pub tool_calls: Vec<ToolCallDelta>,
     #[serde(skip_serializing_if = "Option::is_none")]
     pub tool_call_id: Option<String>,
 }
 
+/// Deserialization mirror of [`ChatChunkDelta`] that accepts array `content`
+/// (Mistral reasoning streams a thinking-chunk array during the thinking
+/// phase, then plain-string answer deltas) and folds thinking into
+/// `reasoning_content`.
+#[derive(Deserialize)]
+struct RawChatChunkDelta {
+    #[serde(default)]
+    role: Option<Role>,
+    #[serde(default)]
+    content: Option<WireContent>,
+    #[serde(default)]
+    reasoning_content: Option<String>,
+    #[serde(default, deserialize_with = "deserialize_null_default")]
+    tool_calls: Vec<ToolCallDelta>,
+    #[serde(default)]
+    tool_call_id: Option<String>,
+}
+
+impl From<RawChatChunkDelta> for ChatChunkDelta {
+    fn from(r: RawChatChunkDelta) -> Self {
+        let (answer, thinking) = r.content.map(WireContent::split).unwrap_or((None, None));
+        ChatChunkDelta {
+            role: r.role,
+            content: answer,
+            reasoning_content: r.reasoning_content.or(thinking),
+            tool_calls: r.tool_calls,
+            tool_call_id: r.tool_call_id,
+        }
+    }
+}
+
 /// Parameters to control realtime data.
 #[derive(Serialize, Deserialize, Clone, Debug)]
 pub struct SearchParameters {
@@ -956,6 +1078,11 @@ pub enum ChatCompat {
     DeepSeek,
     /// Leave the body as-is (OpenAI-style `reasoning_effort` passes through).
     Passthrough,
+    /// Mistral wire: OpenAI-style `reasoning_effort` passes through, but the
+    /// strict Pydantic validator 422-rejects `stream_options` (the SDK's
+    /// request model has no such field), so it must be stripped. Also strips
+    /// the kigi-private message fields like Passthrough.
+    Mistral,
 }
 
 pub const REASONING_EFFORT_META_KEY: &str = "reasoningEffort";
@@ -1319,6 +1446,98 @@ mod tests {
     use super::*;
     use serde_json::json;
 
+    /// String content (the only shape non-Mistral providers send) stays the
+    /// answer verbatim with no thinking — byte-identical to the pre-change
+    /// deserialization.
+    #[test]
+    fn chunk_delta_string_content_unchanged() {
+        let delta: ChatChunkDelta =
+            serde_json::from_value(json!({ "content": "hello world" })).unwrap();
+        assert_eq!(delta.content.as_deref(), Some("hello world"));
+        assert_eq!(delta.reasoning_content, None);
+        // A DeepSeek-style wire reasoning_content still rides its own field.
+        let delta: ChatChunkDelta =
+            serde_json::from_value(json!({ "content": "hi", "reasoning_content": "because" }))
+                .unwrap();
+        assert_eq!(delta.content.as_deref(), Some("hi"));
+        assert_eq!(delta.reasoning_content.as_deref(), Some("because"));
+        // Null / absent content → None.
+        let delta: ChatChunkDelta = serde_json::from_value(json!({})).unwrap();
+        assert_eq!(delta.content, None);
+    }
+
+    /// Mistral reasoning: array content routes `text` chunks to the answer
+    /// and the nested `text` of `thinking` chunks to reasoning_content
+    /// (verified shapes from the mistralai/client-python SDK).
+    #[test]
+    fn chunk_delta_array_content_splits_thinking_and_answer() {
+        // Thinking phase: array with only a thinking chunk (nested list).
+        let delta: ChatChunkDelta = serde_json::from_value(json!({
+            "content": [
+                { "type": "thinking", "thinking": [{ "type": "text", "text": "step 1" }],
+                  "signature": null, "closed": false }
+            ]
+        }))
+        .unwrap();
+        assert_eq!(delta.content, None, "thinking phase has no visible answer");
+        assert_eq!(delta.reasoning_content.as_deref(), Some("step 1"));
+
+        // Answer phase: plain string delta.
+        let delta: ChatChunkDelta =
+            serde_json::from_value(json!({ "content": "the answer" })).unwrap();
+        assert_eq!(delta.content.as_deref(), Some("the answer"));
+        assert_eq!(delta.reasoning_content, None);
+
+        // Transition delta: one array carrying both a closing thinking chunk
+        // and the first text chunk → both channels populated.
+        let delta: ChatChunkDelta = serde_json::from_value(json!({
+            "content": [
+                { "type": "thinking", "thinking": [{ "type": "text", "text": "done" }] },
+                { "type": "text", "text": "Answer: 22" }
+            ]
+        }))
+        .unwrap();
+        assert_eq!(delta.content.as_deref(), Some("Answer: 22"));
+        assert_eq!(delta.reasoning_content.as_deref(), Some("done"));
+    }
+
+    /// The chunk union is OPEN: unknown chunk types and reference chunks are
+    /// ignored, never fatal (SDK's UnknownContentChunk fallback).
+    #[test]
+    fn content_array_tolerates_unknown_chunk_types() {
+        let delta: ChatChunkDelta = serde_json::from_value(json!({
+            "content": [
+                { "type": "reference", "reference_ids": [1, 2] },
+                { "type": "some_future_chunk", "payload": { "x": 1 } },
+                { "type": "text", "text": "visible" }
+            ]
+        }))
+        .unwrap();
+        assert_eq!(delta.content.as_deref(), Some("visible"));
+        assert_eq!(delta.reasoning_content, None);
+    }
+
+    /// Non-streaming ChatResponseMessage gets the same array handling.
+    #[test]
+    fn response_message_array_content_splits() {
+        let msg: ChatResponseMessage = serde_json::from_value(json!({
+            "role": "assistant",
+            "content": [
+                { "type": "thinking", "thinking": [{ "type": "text", "text": "reasoning" }] },
+                { "type": "text", "text": "final" }
+            ]
+        }))
+        .unwrap();
+        assert_eq!(msg.content.as_deref(), Some("final"));
+        assert_eq!(msg.reasoning_content.as_deref(), Some("reasoning"));
+        // String content still works.
+        let msg: ChatResponseMessage = serde_json::from_value(json!({
+            "role": "assistant", "content": "plain"
+        }))
+        .unwrap();
+        assert_eq!(msg.content.as_deref(), Some("plain"));
+    }
+
     #[test]
     fn reasoning_effort_serde_lowercase_round_trip() {
         for v in [

crates/codegen/kigi-shell/src/agent/auth_method.rs

@@ -595,7 +595,8 @@ mod tests {
                 "openai",
                 "anthropic",
                 "deepseek",
-                "groq"
+                "groq",
+                "mistral"
             ]
         );
         assert_eq!(default_id(&built), Some(XAI_API_KEY_METHOD_ID));
@@ -625,7 +626,8 @@ mod tests {
                 "openai",
                 "anthropic",
                 "deepseek",
-                "groq"
+                "groq",
+                "mistral"
             ]
         );
         assert_eq!(default_id(&built), Some(CACHED_TOKEN_AUTH_METHOD_ID));
@@ -648,7 +650,8 @@ mod tests {
                 "openai",
                 "anthropic",
                 "deepseek",
-                "groq"
+                "groq",
+                "mistral"
             ]
         );
         assert_eq!(default_id(&built), Some(CACHED_TOKEN_AUTH_METHOD_ID));
@@ -674,7 +677,8 @@ mod tests {
                 "openai",
                 "anthropic",
                 "deepseek",
-                "groq"
+                "groq",
+                "mistral"
             ]
         );
         assert_eq!(default_id(&built), None);

crates/codegen/kigi-shell/src/agent/config.rs

@@ -4074,6 +4074,7 @@ pub fn sampling_config_for_model(
             kigi_models::PlatformChatCompat::Passthrough => {
                 kigi_sampling_types::ChatCompat::Passthrough
             }
+            kigi_models::PlatformChatCompat::Mistral => kigi_sampling_types::ChatCompat::Mistral,
         })
         .unwrap_or_default();
     SamplerConfig {

crates/codegen/kigi-shell/src/agent/models_fetch.rs

@@ -1206,6 +1206,90 @@ mod tests {
         );
     }
 
+    /// Mistral-cycle e2e: embed pollution restricted away, and the Mistral
+    /// dialect (strips stream_options, handles reasoning arrays) is mapped.
+    #[tokio::test(flavor = "multi_thread")]
+    #[serial_test::serial]
+    async fn mistral_listing_restricts_and_maps_mistral_dialect() {
+        let platform_server = wiremock::MockServer::start().await;
+        wiremock::Mock::given(wiremock::matchers::method("GET"))
+            .and(wiremock::matchers::path("/models"))
+            .and(wiremock::matchers::header("Authorization", "Bearer msk-1"))
+            .respond_with(wiremock::ResponseTemplate::new(200).set_body_json(
+                serde_json::json!({ "data": [
+                    { "id": "devstral-latest", "object": "model" },
+                    { "id": "mistral-embed", "object": "model" }
+                ]}),
+            ))
+            .expect(1)
+            .mount(&platform_server)
+            .await;
+        let modelsdev_server = wiremock::MockServer::start().await;
+        wiremock::Mock::given(wiremock::matchers::method("GET"))
+            .and(wiremock::matchers::path("/api.json"))
+            .respond_with(wiremock::ResponseTemplate::new(200).set_body_json(
+                serde_json::json!({ "mistral": { "models": {
+                    "devstral-latest": {
+                        "limit": {"context": 262144, "output": 65536},
+                        "tool_call": true
+                    },
+                    "mistral-embed": { "limit": {"context": 8000} }
+                }}}),
+            ))
+            .expect(1)
+            .mount(&modelsdev_server)
+            .await;
+        let cache_dir = tempfile::tempdir().unwrap();
+        let _base = kigi_test_support::EnvGuard::set(
+            kigi_models::MISTRAL_BASE_URL_ENV,
+            platform_server.uri(),
+        );
+        let _mdev = kigi_test_support::EnvGuard::set(
+            crate::agent::enrichment_fetch::MODELS_DEV_URL_ENV,
+            format!("{}/api.json", modelsdev_server.uri()),
+        );
+        let _mdev_cache = kigi_test_support::EnvGuard::set(
+            crate::agent::enrichment_fetch::MODELS_DEV_CACHE_DIR_ENV,
+            cache_dir.path(),
+        );
+        let endpoints = crate::agent::config::EndpointsConfig::default();
+        let keys = crate::agent::models::PlatformApiKeys::test_single(
+            kigi_models::PlatformId::Mistral,
+            "msk-1",
+        );
+        let result = tokio::task::spawn_blocking(move || {
+            fetch_platform_models_blocking(&endpoints, None, &keys)
+        })
+        .await
+        .unwrap()
+        .expect("fetch must succeed");
+        assert_eq!(
+            result
+                .models
+                .iter()
+                .map(|m| m.id.as_deref().unwrap_or_default())
+                .collect::<Vec<_>>(),
+            vec!["mistral/devstral-latest"],
+            "embed (enrichment-known, not tool-calling) must be dropped"
+        );
+        let entry = &result.models[0];
+        assert_eq!(entry.context_window.get(), 262_144);
+        assert_eq!(entry.max_completion_tokens, Some(65_536));
+        let model_entry = crate::agent::config::ModelEntry::from_config_entry(entry);
+        let creds = crate::agent::config::ResolvedCredentials {
+            api_key: Some("msk-1".into()),
+            base_url: entry.base_url.clone(),
+            auth_type: kigi_chat_state::AuthType::ApiKey,
+            auth_scheme: Default::default(),
+        };
+        let cfg = crate::agent::config::sampling_config_for_model(&model_entry, creds, None);
+        assert_eq!(
+            cfg.chat_compat,
+            kigi_sampling_types::ChatCompat::Mistral,
+            "mistral entries must map to the Mistral dialect (stream_options strip)"
+        );
+    }
+
     #[test]
     fn get_env_keys_parses_strings_and_rejects_non_strings() {
         use crate::agent::config::EnvKeys;

crates/codegen/kigi-tui/src/app/app_view.rs

@@ -6894,7 +6894,7 @@ pub(crate) mod tests {
     #[test]
     fn pending_menu_items_lists_interactive_methods_plus_quit() {
         let items = pending_menu_items(&fresh_user_auth_methods(), None);
-        assert_eq!(items.len(), 8, "7 login rows + Quit, got {items:?}");
+        assert_eq!(items.len(), 9, "8 login rows + Quit, got {items:?}");
         assert!(
             matches!(&items[0], PendingMenuItem::Login { label } if label == "Kimi Code (OAuth)"),
             "row 0 must be the OAuth login, got {:?}",
@@ -6943,7 +6943,14 @@ pub(crate) mod tests {
                 label: "Groq (API key)".into(),
             }
         );
-        assert_eq!(items[7], PendingMenuItem::Quit);
+        assert_eq!(
+            items[7],
+            PendingMenuItem::ApiKey {
+                target: PlatformLogin(kigi_shell::models::PlatformId::Mistral),
+                label: "Mistral (API key)".into(),
+            }
+        );
+        assert_eq!(items[8], PendingMenuItem::Quit);
         // The non-interactive methods must never appear as rows.
         let byok = kigi_shell::agent::auth_method::build_auth_methods(
             kigi_shell::agent::auth_method::AuthMethodsBuildInputs {
@@ -6954,7 +6961,7 @@ pub(crate) mod tests {
         );
         assert_eq!(
             pending_menu_items(&byok.methods, None).len(),
-            8,
+            9,
             "xai.api_key / cached_token must not add rows"
         );
     }